diff --git a/src/bufr/BufrParser/Exports/Variables/AircraftAltitudeVariable.cpp b/src/bufr/BufrParser/Exports/Variables/AircraftAltitudeVariable.cpp
index 06849a24d..5b8a70429 100644
--- a/src/bufr/BufrParser/Exports/Variables/AircraftAltitudeVariable.cpp
+++ b/src/bufr/BufrParser/Exports/Variables/AircraftAltitudeVariable.cpp
@@ -88,7 +88,6 @@ namespace Ingester
 
         for (size_t idx = 0; idx < referenceObj->size(); idx++)
         {
-            std::cout << "idx = " << idx << std::endl;
             for (auto nameIt = includedFields.rbegin(); nameIt != includedFields.rend(); ++nameIt)
             {
                 const auto& fieldName = *nameIt;
@@ -102,14 +101,12 @@ namespace Ingester
                         {
                             aircraftAlts[idx]  =
                                 11000.0f - (std::log1p(value / 22630.0f) / 0.0001576106f);
-                            std::cout << "section 1" << std::endl;
                         }
                         else
                         {
                             aircraftAlts[idx]  =
                                 (1.0f - powf((value / 101325.0f),
                                              (1.0f / 5.256f))) * (288.15f / 0.0065f);
-                            std::cout << "section 2" << std::endl;
                         }
                     }
                     else if (includedFieldMap.find(ConfKeys::AircraftIndicatedAltitude)
@@ -119,7 +116,6 @@ namespace Ingester
                         {
                             aircraftAlts[idx] =
                              includedFieldMap[ConfKeys::AircraftIndicatedAltitude]->getAsFloat(idx);
-                            std::cout << "section 3" << std::endl;
                         }
                     }
                 }
@@ -127,16 +123,13 @@ namespace Ingester
                 {
                     // This variable is only used in conjunction with pressure.
                     continue;
-                    std::cout << "section 4" << std::endl;
                 }
                 else if (!fieldValues->isMissing(idx))
                 {
                     std::cout << " fieldValues = " << fieldValues << std::endl;
                     aircraftAlts[idx] = fieldValues->getAsFloat(idx);
-                    std::cout << "section 5" << std::endl;
                 }
             }
-        std::cout << "AA = " << aircraftAlts[idx] << std::endl;
         }
 
         return std::make_shared<DataObject<float>>(aircraftAlts,
diff --git a/src/compo/aeronet_aaod2ioda.py b/src/compo/aeronet_aaod2ioda.py
index 0dd9b3bf9..6261362fe 100755
--- a/src/compo/aeronet_aaod2ioda.py
+++ b/src/compo/aeronet_aaod2ioda.py
@@ -19,6 +19,7 @@
 #        -o: output IODA file
 
 import numpy as np
+import netCDF4 as nc
 import inspect, sys, os, argparse
 import pandas as pd
 from datetime import datetime, timedelta
@@ -123,6 +124,8 @@ def add_data(infile):
     print(aeronetinv_chan)
     print(frequency)
 
+    long_missing_value = nc.default_fillvals['i8']
+
     nlocs, columns = f3.shape
     nchans = len(aeronetinv_chan)
     if nlocs == 0:
@@ -134,93 +137,123 @@ def add_data(infile):
     outdata = defaultdict(lambda: DefaultOrderedDict(OrderedDict))
     varAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
 
-    obsvars = {'aerosol_optical_depth': ['aod_coincident_input[440nm]', 'aod_coincident_input[675nm]',
-                                         'aod_coincident_input[870nm]', 'aod_coincident_input[1020nm]'],
-               'absorption_aerosol_optical_depth': ['absorption_aod[440nm]', 'absorption_aod[675nm]',
-                                                    'absorption_aod[870nm]', 'absorption_aod[1020nm]']}
+    obsvars = {'aerosolOpticalDepth': ['aod_coincident_input[440nm]', 'aod_coincident_input[675nm]',
+                                       'aod_coincident_input[870nm]', 'aod_coincident_input[1020nm]'],
+               'absorptionAerosolOpticalDepth': ['absorption_aod[440nm]', 'absorption_aod[675nm]',
+                                                 'absorption_aod[870nm]', 'absorption_aod[1020nm]']}
 
-    AttrData = {
-        'converter': os.path.basename(__file__)
-    }
+    # A dictionary of global attributes.  More filled in further down.
+    AttrData = {}
+    AttrData['ioda_object_type'] = 'absorptionAOD'
+    AttrData['sensor'] = 'aeronet'
 
-    DimDict = {
-    }
+    # A dictionary of variable dimensions.
+    DimDict = {}
 
+    # A dictionary of variable names and their dimensions.
     VarDims = {
-        'aerosol_optical_depth': ['nlocs', 'nchans'],
-        'absorption_aerosol_optical_depth': ['nlocs', 'nchans'],
-        'frequency': ['nchans'],
-        'sensor_channel': ['nchans']
+        'aerosolOpticalDepth': ['Location', 'Channel'],
+        'absorptionAerosolOpticalDepth': ['Location', 'Channel'],
+        'sensorCentralFrequency': ['Channel'],
+        'sensorChannelNumber': ['Channel']
     }
 
+    # Get the group names we use the most.
+    metaDataName = iconv.MetaDataName()
+    obsValName = iconv.OvalName()
+    obsErrName = iconv.OerrName()
+    qcName = iconv.OqcName()
+
     # Define varDict variables
     for key, value in obsvars.items():
-        varDict[key]['valKey'] = key, iconv.OvalName()
-        varAttrs[key, iconv.OvalName()]['_FillValue'] = -999.
-        varAttrs[key, iconv.OvalName()]['coordinates'] = 'longitude latitude station_elevation'
-        varAttrs[key, iconv.OvalName()]['units'] = '1'
-        varDict[key]['errKey'] = key, iconv.OerrName()
-        varAttrs[key, iconv.OerrName()]['_FillValue'] = -999.
-        varAttrs[key, iconv.OerrName()]['coordinates'] = 'longitude latitude station_elevation'
-        varAttrs[key, iconv.OerrName()]['units'] = '1'
-        varDict[key]['qcKey'] = key, iconv.OqcName()
-        varAttrs[key, iconv.OqcName()]['_FillValue'] = -999
-        varAttrs[key, iconv.OqcName()]['coordinates'] = 'longitude latitude station_elevation'
-        varAttrs[key, iconv.OqcName()]['units'] = 'unitless'
+        varDict[key]['valKey'] = key, obsValName
+        varDict[key]['errKey'] = key, obsErrName
+        varDict[key]['qcKey'] = key, qcName
+        varAttrs[key, obsValName]['coordinates'] = 'longitude latitude stationElevation'
+        varAttrs[key, obsErrName]['coordinates'] = 'longitude latitude stationElevation'
+        varAttrs[key, qcName]['coordinates'] = 'longitude latitude stationElevation'
+        varAttrs[key, obsValName]['_FillValue'] = -9999.
+        varAttrs[key, obsErrName]['_FillValue'] = -9999.
+        varAttrs[key, qcName]['_FillValue'] = -9999
+        varAttrs[key, obsValName]['units'] = '1'
+        varAttrs[key, obsErrName]['units'] = '1'
 
     for key, value in obsvars.items():
-        outdata[varDict[key]['valKey']] = np.array(np.float32(f3[value].fillna(np.float32(-999.))))
-        outdata[varDict[key]['qcKey']] = np.where(outdata[varDict[key]['valKey']] == np.float32(-999.),
+        outdata[varDict[key]['valKey']] = np.array(np.float32(f3[value].fillna(np.float32(-9999.))))
+        outdata[varDict[key]['qcKey']] = np.where(outdata[varDict[key]['valKey']] == np.float32(-9999.),
                                                   1, 0)
-        if key in ["aerosol_optical_depth"]:
-            outdata[varDict[key]['errKey']] = np.where(outdata[varDict[key]['valKey']] == np.float32(-999.),
-                                                       np.float32(-999.), np.float32(0.02))
+        if key in ["aerosolOpticalDepth"]:
+            outdata[varDict[key]['errKey']] = np.where(outdata[varDict[key]['valKey']] == np.float32(-9999.),
+                                                       np.float32(-9999.), np.float32(0.02))
         else:
-            outdata[varDict[key]['errKey']] = np.full((nlocs, nchans), np.float32(-999.))
+            outdata[varDict[key]['errKey']] = np.full((nlocs, nchans), np.float32(-9999.))
 
-    outdata[('latitude', 'MetaData')] = np.array(np.float32(f3['latitude']))
-    outdata[('longitude', 'MetaData')] = np.array(np.float32(f3['longitude']))
-    outdata[('station_elevation', 'MetaData')] = np.array(np.float32(f3['elevation']))
-    varAttrs[('station_elevation', 'MetaData')]['units'] = 'm'
-    outdata[('surface_type', 'MetaData')] = np.full((nlocs), 1)
-    varAttrs[('surface_type', 'MetaData')]['units'] = 'unitless'
-
-    # Whether aaod reaches Level 2.0 without the threshold of aod440 >= 0.4 (0: yes, 1: no)
-    outdata[('aaod_l2_qc_without_aod440_le_0.4_threshold', 'MetaData')] = np.where(f3['if_retrieval_is_l2(without_l2_0.4_aod_440_threshold)'] == 1, 0, 1)
-    varAttrs[('aaod_l2_qc_without_aod440_le_0.4_threshold', 'MetaData')]['units'] = 'unitless'
+    outdata[('latitude', metaDataName)] = np.array(np.float32(f3['latitude']))
+    outdata[('longitude', metaDataName)] = np.array(np.float32(f3['longitude']))
+    outdata[('stationElevation', metaDataName)] = np.array(np.float32(f3['elevation']))
+    varAttrs[('stationElevation', metaDataName)]['units'] = 'm'
 
     # Whether Coincident_AOD440nm in aeronet_cad.txt reaches Level 2.0 (0: yes, 1: no)
-    outdata[('aod_l2_qc', 'MetaData')] = np.where(f3['if_aod_is_l2'] == 1, 0, 1)
-    varAttrs[('aod_l2_qc', 'MetaData')]['units'] = 'unitless'
+    qcL2Aod = np.where(f3['if_aod_is_l2'] == 1, 0, 1)
 
     # aaod inversion type: 0 for ALM20 and 1 for ALM15
-    outdata[('aaod_l2_qc', 'MetaData')] = np.where(f3['inversion_data_quality_level'] == 'lev20', 0, 1)
-    varAttrs[('aaod_l2_qc', 'MetaData')]['units'] = 'unitless'
+    qcL2Aaod = np.where(f3['inversion_data_quality_level'] == 'lev20', 0, 1)
 
+    # Whether aaod reaches Level 2.0 without the threshold of aod440 >= 0.4 (0: yes, 1: no)
+    qcL2Aaod2 = np.where(f3['if_retrieval_is_l2(without_l2_0.4_aod_440_threshold)'] == 1, 0, 1)
+
+    qcAll = np.full(len(qcL2Aod), long_missing_value, dtype=np.int32)
+    for i in range(len(qcL2Aod)):
+        qc1 = qcL2Aod[i]
+        qc2 = qcL2Aaod[i]
+        qc3 = qcL2Aaod2[i]
+        if qc1 == 0 and qc2 == 0 and qc3 == 0:
+            # Both AOD and AAOD w/and w/o aod440>0.4 threshold reach L2.
+            qcAll[i] = 0
+        elif qc1 == 0 and qc2 == 0 and qc3 == 1:
+            # Both AOD and AAOD w/ aod440>0.4 threshold reaches L2,
+            # but AAOD w/o aod440>0.4 threshold does not.
+            qcAll[i] = 1
+        elif qc1 == 0 and qc2 == 1 and qc3 == 0:
+            # Both AOD and AAOD w/o aod440>0.4 threshold reaches L2,
+            # but AAOD w/ aod440>0.4 threshold does not.
+            qcAll[i] = 2
+        elif qc1 == 0 and qc2 == 1 and qc3 == 1:
+            # Only AOD reaches L2.
+            qcAll[i] = 3
+        elif qc1 == 1 and qc2 == 0 and qc3 == 0:
+            # AAOD w/ and w/o aod440>0.4 threshold reaches L2,
+            # but AOD does not.
+            qcAll[i] = 4
+        elif qc1 == 1 and qc2 == 0 and qc3 == 1:
+            # AAOD w/ aod440>0.4 threshold reaches L2,
+            # but AOD and AAOD w/o aod440>0.4 threshold do not.
+            qcAll[i] = 5
+        elif qc1 == 1 and qc2 == 1 and qc3 == 0:
+            # AAOD w/o  aod440>0.4 threshold reaches L2,
+            # but AOD and AAOD w/ aod440>0.4 threshold do not.
+            qcAll[i] = 6
+        elif qc1 == 1 and qc2 == 1 and qc3 == 1:
+            # Neither AOD or AAOD w/ and w/o aod440>0.4 threshold reaches L2.
+            qcAll[i] = 7
+
+    outdata[('qualityFlags', metaDataName)] = qcAll
     c = np.empty([nlocs], dtype=object)
     c[:] = np.array(f3.siteid)
-    outdata[('station_id', 'MetaData')] = c
-    varAttrs[('station_id', 'MetaData')]['units'] = ''
+    outdata[('stationIdentification', metaDataName)] = c
 
     d = np.empty([nlocs], dtype=object)
     for i in range(nlocs):
         d[i] = f3.time[i].strftime('%Y-%m-%dT%H:%M:%SZ')
-    outdata[('datetime', 'MetaData')] = d
-    varAttrs[('datetime', 'MetaData')]['units'] = ''
+    outdata[('dateTime', metaDataName)] = d
 
-    outdata[('frequency', 'MetaData')] = np.float32(frequency)
-    varAttrs[('frequency', 'MetaData')]['units'] = 'Hz'
-    outdata[('sensor_channel', 'MetaData')] = np.int32(aeronetinv_chan)
-    varAttrs[('sensor_channel', 'MetaData')]['units'] = 'unitless'
+    outdata[('sensorCentralFrequency', metaDataName)] = np.float32(frequency)
+    varAttrs[('sensorCentralFrequency', metaDataName)]['units'] = 'Hz'
+    outdata[('sensorChannelNumber', metaDataName)] = np.int32(aeronetinv_chan)
 
     # Add global atrributes
-    DimDict['nlocs'] = nlocs
-    DimDict['nchans'] = aeronetinv_chan
-    AttrData['nlocs'] = np.int32(DimDict['nlocs'])
-    AttrData['nchans'] = np.int32(nchans)
-    AttrData['observation_type'] = 'AAOD'
-    AttrData['sensor'] = 'aeronet'
-    AttrData['surface_type'] = 'ocean=0,land=1,costal=2'
+    DimDict['Location'] = nlocs
+    DimDict['Channel'] = aeronetinv_chan
 
     # Setup the IODA writer
     writer = iconv.IodaWriter(outfile, locationKeyList, DimDict)
diff --git a/src/compo/aeronet_aod2ioda.py b/src/compo/aeronet_aod2ioda.py
index dfc0a6bc3..5749a896f 100644
--- a/src/compo/aeronet_aod2ioda.py
+++ b/src/compo/aeronet_aod2ioda.py
@@ -103,82 +103,79 @@ def add_data(infile):
         print('Zero AERONET AOD is available in file: ' + infile + ' and exit.')
         exit(0)
 
-    locationKeyList = [("latitude", "float"), ("longitude", "float"), ("datetime", "string")]
+    locationKeyList = [("latitude", "float"), ("longitude", "float"), ("dateTime", "string")]
     varDict = defaultdict(lambda: defaultdict(dict))
     outdata = defaultdict(lambda: DefaultOrderedDict(OrderedDict))
     varAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
 
-    obsvars = {'aerosol_optical_depth': ['aod_340nm', 'aod_380nm',
-                                         'aod_440nm', 'aod_675nm',
-                                         'aod_500nm', 'aod_870nm',
-                                         'aod_1020nm', 'aod_1640nm']}
+    obsvars = {'aerosolOpticalDepth': ['aod_340nm', 'aod_380nm',
+                                       'aod_440nm', 'aod_675nm',
+                                       'aod_500nm', 'aod_870nm',
+                                       'aod_1020nm', 'aod_1640nm']}
 
-    AttrData = {
-        'converter': os.path.basename(__file__),
-    }
+    # A dictionary of global attributes.  More filled in further down.
+    AttrData = {}
+    AttrData['ioda_object_type'] = 'AOD'
+    AttrData['sensor'] = 'aeronet'
 
-    DimDict = {
-    }
+    # A dictionary of variable dimensions.
+    DimDict = {}
 
+    # A dictionary of variable names and their dimensions.
     VarDims = {
-        'aerosol_optical_depth': ['nlocs', 'nchans'],
-        'frequency': ['nchans'],
-        'sensor_channel': ['nchans']
+        'aerosolOpticalDepth': ["Location", "Channel"],
+        'sensorCentralFrequency': ['Channel'],
+        'sensorChannelNumber': ['Channel']
     }
 
+    # Get the group names we use the most.
+    metaDataName = iconv.MetaDataName()
+    obsValName = iconv.OvalName()
+    obsErrName = iconv.OerrName()
+    qcName = iconv.OqcName()
+
     for key, value in obsvars.items():
-        varDict[key]['valKey'] = key, iconv.OvalName()
-        varAttrs[key, iconv.OvalName()]['_FillValue'] = -999.
-        varAttrs[key, iconv.OvalName()]['coordinates'] = 'longitude latitude station_elevation'
-        varAttrs[key, iconv.OvalName()]['units'] = '1'
-        varDict[key]['errKey'] = key, iconv.OerrName()
-        varAttrs[key, iconv.OerrName()]['_FillValue'] = -999.
-        varAttrs[key, iconv.OerrName()]['units'] = '1'
-        varAttrs[key, iconv.OerrName()]['coordinates'] = 'longitude latitude station_elevation'
-        varDict[key]['qcKey'] = key, iconv.OqcName()
-        varAttrs[key, iconv.OqcName()]['_FillValue'] = -999
-        varAttrs[key, iconv.OqcName()]['coordinates'] = 'longitude latitude station_elevation'
-        varAttrs[key, iconv.OqcName()]['units'] = 'unitless'
+        varDict[key]['valKey'] = key, obsValName
+        varDict[key]['errKey'] = key, obsErrName
+        varDict[key]['qcKey'] = key, qcName
+        varAttrs[key, obsValName]['coordinates'] = 'longitude latitude stationElevation'
+        varAttrs[key, obsErrName]['coordinates'] = 'longitude latitude stationElevation'
+        varAttrs[key, qcName]['coordinates'] = 'longitude latitude stationElevation'
+        varAttrs[key, obsValName]['_FillValue'] = -9999.
+        varAttrs[key, obsErrName]['_FillValue'] = -9999.
+        varAttrs[key, qcName]['_FillValue'] = -9999
+        varAttrs[key, obsValName]['units'] = '1'
+        varAttrs[key, obsErrName]['units'] = '1'
 
     for key, value in obsvars.items():
-        outdata[varDict[key]['valKey']] = np.array(np.float32(f3[value].fillna(np.float32(-999.))))
-        outdata[varDict[key]['qcKey']] = np.where(outdata[varDict[key]['valKey']] == np.float32(-999.),
+        outdata[varDict[key]['valKey']] = np.array(np.float32(f3[value].fillna(np.float32(-9999.))))
+        outdata[varDict[key]['qcKey']] = np.where(outdata[varDict[key]['valKey']] == np.float32(-9999.),
                                                   1, 0)
-        outdata[varDict[key]['errKey']] = np.where(outdata[varDict[key]['valKey']] == np.float32(-999.),
-                                                   np.float32(-999.), np.float32(0.02))
+        outdata[varDict[key]['errKey']] = np.where(outdata[varDict[key]['valKey']] == np.float32(-9999.),
+                                                   np.float32(-9999.), np.float32(0.02))
 
     # Add metadata variables
-    outdata[('latitude', 'MetaData')] = np.array(np.float32(f3['latitude']))
-    outdata[('longitude', 'MetaData')] = np.array(np.float32(f3['longitude']))
-    outdata[('station_elevation', 'MetaData')] = np.array(np.float32(f3['elevation']))
-    varAttrs[('station_elevation', 'MetaData')]['units'] = 'm'
-    outdata[('surface_type', 'MetaData')] = np.full((nlocs), 1)
-    varAttrs[('surface_type', 'MetaData')]['units'] = 'unitless'
+    outdata[('latitude', metaDataName)] = np.array(np.float32(f3['latitude']))
+    outdata[('longitude', metaDataName)] = np.array(np.float32(f3['longitude']))
+    outdata[('stationElevation', metaDataName)] = np.array(np.float32(f3['elevation']))
+    varAttrs[('stationElevation', metaDataName)]['units'] = 'm'
 
     c = np.empty([nlocs], dtype=object)
     c[:] = np.array(f3.siteid)
-    outdata[('station_id', 'MetaData')] = c
-    varAttrs[('station_id', 'MetaData')]['units'] = ''
+    outdata[('stationIdentification', metaDataName)] = c
 
     d = np.empty([nlocs], dtype=object)
     for i in range(nlocs):
         d[i] = f3.time[i].strftime('%Y-%m-%dT%H:%M:%SZ')
-    outdata[('datetime', 'MetaData')] = d
-    varAttrs[('datetime', 'MetaData')]['units'] = ''
+    outdata[('dateTime', metaDataName)] = d
 
-    outdata[('frequency', 'MetaData')] = np.float32(frequency)
-    varAttrs[('frequency', 'MetaData')]['units'] = 'Hz'
-    outdata[('sensor_channel', 'MetaData')] = np.int32(aod_chan)
-    varAttrs[('sensor_channel', 'MetaData')]['units'] = 'unitless'
+    outdata[('sensorCentralFrequency', metaDataName)] = np.float32(frequency)
+    varAttrs[('sensorCentralFrequency', metaDataName)]['units'] = 'Hz'
+    outdata[('sensorChannelNumber', metaDataName)] = np.int32(aod_chan)
 
     # Add global atrributes
-    DimDict['nlocs'] = nlocs
-    DimDict['nchans'] = aod_chan
-    AttrData['nlocs'] = np.int32(DimDict['nlocs'])
-    AttrData['nchans'] = np.int32(nchans)
-    AttrData['observation_type'] = 'AOD'
-    AttrData['sensor'] = 'aeronet'
-    AttrData['surface_type'] = 'ocean=0,land=1,costal=2'
+    DimDict['Location'] = nlocs
+    DimDict['Channel'] = aod_chan
 
     # Setup the IODA writer
     writer = iconv.IodaWriter(outfile, locationKeyList, DimDict)
diff --git a/src/compo/airnow2ioda-nc.py b/src/compo/airnow2ioda-nc.py
index c149c315f..d2c7766b2 100755
--- a/src/compo/airnow2ioda-nc.py
+++ b/src/compo/airnow2ioda-nc.py
@@ -1,20 +1,66 @@
 #!/usr/bin/env python3
-# read airnow data and convert to netcdf
+# Read airnow text data file and convert to IODA netcdf
+import os, sys
+from datetime import datetime
+from pathlib import Path
 import netCDF4 as nc
 import numpy as np
-import inspect, os, sys, argparse
 import pandas as pd
-from datetime import datetime
-from pathlib import Path
 
 IODA_CONV_PATH = Path(__file__).parent/"@SCRIPT_LIB_PATH@"
 if not IODA_CONV_PATH.is_dir():
     IODA_CONV_PATH = Path(__file__).parent/'..'/'lib-python'
 sys.path.append(str(IODA_CONV_PATH.resolve()))
-import meteo_utils
-import ioda_conv_ncio as iconv
+
 from collections import defaultdict, OrderedDict
 from orddicts import DefaultOrderedDict
+import ioda_conv_engines as iconv
+
+os.environ["TZ"] = "UTC"
+
+# Dictionary of output variables (ObsVal, ObsError, and PreQC).
+# First is the incoming variable name followed by list of IODA outgoing name and units.
+
+varDict = {'PM2.5': ['particulatematter2p5Surface', 'mg m-3'],
+           'OZONE': ['ozoneSurface', 'ppmV']}
+
+locationKeyList = [("latitude", "float", "degrees_north"),
+                   ("longitude", "float", "degrees_east"),
+                   ("dateTime", "long", "seconds since 1970-01-01T00:00:00Z"),
+                   ("stationElevation", "float", "m"),
+                   ("height", "float", "m"),
+                   ("stationIdentification", "string", "")]
+meta_keys = [m_item[0] for m_item in locationKeyList]
+
+GlobalAttrs = {'converter': os.path.basename(__file__),
+               'ioda_version': 2,
+               'description': 'AIRNow data (converted from text/csv to IODA',
+               'source': 'Unknown (ftp)'}
+
+iso8601_string = locationKeyList[meta_keys.index('dateTime')][2]
+epoch = datetime.fromisoformat(iso8601_string[14:-1])
+
+metaDataName = iconv.MetaDataName()
+obsValName = iconv.OvalName()
+obsErrName = iconv.OerrName()
+qcName = iconv.OqcName()
+
+float_missing_value = nc.default_fillvals['f4']
+int_missing_value = nc.default_fillvals['i4']
+double_missing_value = nc.default_fillvals['f8']
+long_missing_value = nc.default_fillvals['i8']
+string_missing_value = '_'
+
+missing_vals = {'string': string_missing_value,
+                'integer': int_missing_value,
+                'long': long_missing_value,
+                'float': float_missing_value,
+                'double': double_missing_value}
+dtypes = {'string': object,
+          'integer': np.int32,
+          'long': np.int64,
+          'float': np.float32,
+          'double': np.float64}
 
 
 def read_monitor_file(sitefile=None):
@@ -86,6 +132,8 @@ def add_data(infile, sitefile):
 
 if __name__ == '__main__':
 
+    import argparse
+
     parser = argparse.ArgumentParser(
         description=(
             'Reads single AIRNow text file '
@@ -113,46 +161,76 @@ def add_data(infile, sitefile):
     f3 = f.dropna(subset=['PM2.5'], how='any').reset_index()
     nlocs, columns = f3.shape
 
-    obsvars = {'pm25': 'pm25', 'o3': 'o3', }
-    AttrData = {'converter': os.path.basename(__file__), }
-
-    locationKeyList = [("latitude", "float"), ("longitude", "float"),
-                       ("station_elevation", "float"), ("height", "float"), ("station_id", "string"),
-                       ("datetime", "string")]
-
-    writer = iconv.NcWriter(args.output, locationKeyList)
-
-    varDict = defaultdict(lambda: defaultdict(dict))
-    outdata = defaultdict(lambda: DefaultOrderedDict(OrderedDict))
-    loc_mdata = defaultdict(lambda: DefaultOrderedDict(OrderedDict))
-    var_mdata = defaultdict(lambda: DefaultOrderedDict(OrderedDict))
-    units = {}
-    units['pm25'] = 'microgram/m3'
-    units['o3'] = 'ppmV'
-
-    for i in ['pm25', 'o3']:
-        varDict[i]['valKey'] = i, writer.OvalName()
-        varDict[i]['errKey'] = i, writer.OerrName()
-        varDict[i]['qcKey'] = i, writer.OqcName()
-
-    d = np.empty([nlocs], 'S20')
-    d[:] = np.array(f3.time[1].strftime('%Y-%m-%dT%H:%M:%SZ'))
-    loc_mdata['datetime'] = writer.FillNcVector(d, 'datetime')
-    loc_mdata['latitude'] = np.array(f3['latitude'])
-    loc_mdata['longitude'] = np.array(f3['longitude'])
-    loc_mdata['height'] = np.full((nlocs), 10.)
-    loc_mdata['station_elevation'] = np.array(f3['elevation'])
-
-    c = np.empty([nlocs], dtype='S20')
-    c[:] = np.array(f3.siteid)
-    loc_mdata['station_id'] = writer.FillNcVector(c, 'string')
-
-    outdata[varDict['pm25']['valKey']] = np.array(f3['PM2.5'].fillna(nc.default_fillvals['f4']))
-    outdata[varDict['o3']['valKey']] = np.array((f3['OZONE']/1000).fillna(nc.default_fillvals['f4']))
-    for i in ['pm25', 'o3']:
-        outdata[varDict[i]['errKey']] = np.full((nlocs), 0.1)
-        outdata[varDict[i]['qcKey']] = np.full((nlocs), 0)
-
-    writer._nvars = 2
-    writer._nlocs = nlocs
-    writer.BuildNetcdf(outdata, loc_mdata, var_mdata, AttrData, units)
+    dt = f3.time[1].to_pydatetime()
+    time_offset = round((dt - epoch).total_seconds())
+
+    ioda_data = {}         # The final outputs.
+    data = {}              # Before assigning the output types into the above.
+    for key in varDict.keys():
+        data[key] = []
+    for key in meta_keys:
+        data[key] = []
+
+    # Fill the temporary data arrays from input file column data
+    data['stationIdentification'] = np.full(nlocs, f3.siteid, dtype='S20')
+    data['dateTime'] = np.full(nlocs, np.int64(time_offset))
+    data['latitude'] = np.array(f3['latitude'])
+    data['longitude'] = np.array(f3['longitude'])
+    data['stationElevation'] = np.array(f3['elevation'])
+    data['height'] = np.array(f3['elevation'])
+    for n in range(nlocs):
+        data['height'][n] = data['height'][n] + 10.0   # 10 meters above stationElevation
+
+    for n, key in enumerate(varDict.keys()):
+        if n == 0:
+            key1 = key
+            var1 = varDict[key][0]
+        elif n == 1:
+            key2 = key
+            var2 = varDict[key][0]
+
+    data[var1] = np.array(f3[key1].fillna(float_missing_value))
+    data[var2] = np.array((f3[key2]/1000).fillna(float_missing_value))
+
+    DimDict = {'Location': nlocs}
+
+    varDims = {}
+    for key in varDict.keys():
+        variable = varDict[key][0]
+        varDims[variable] = ['Location']
+
+    # Set units of the MetaData variables and all _FillValues.
+    varAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
+    for key in meta_keys:
+        dtypestr = locationKeyList[meta_keys.index(key)][1]
+        if locationKeyList[meta_keys.index(key)][2]:
+            varAttrs[(key, metaDataName)]['units'] = locationKeyList[meta_keys.index(key)][2]
+        varAttrs[(key, metaDataName)]['_FillValue'] = missing_vals[dtypestr]
+
+    # Set units and FillValue attributes for groups associated with observed variable.
+    for key in varDict.keys():
+        variable = varDict[key][0]
+        units = varDict[key][1]
+        varAttrs[(variable, obsValName)]['units'] = units
+        varAttrs[(variable, obsErrName)]['units'] = units
+        varAttrs[(variable, obsValName)]['coordinates'] = 'longitude latitude'
+        varAttrs[(variable, obsErrName)]['coordinates'] = 'longitude latitude'
+        varAttrs[(variable, qcName)]['coordinates'] = 'longitude latitude'
+        varAttrs[(variable, obsValName)]['_FillValue'] = float_missing_value
+        varAttrs[(variable, obsErrName)]['_FillValue'] = float_missing_value
+        varAttrs[(variable, qcName)]['_FillValue'] = int_missing_value
+
+    # Fill the final IODA data:  MetaData then ObsValues, ObsErrors, and QC
+    for key in meta_keys:
+        dtypestr = locationKeyList[meta_keys.index(key)][1]
+        ioda_data[(key, metaDataName)] = np.array(data[key], dtype=dtypes[dtypestr])
+
+    for key in varDict.keys():
+        variable = varDict[key][0]
+        ioda_data[(variable, obsValName)] = np.array(data[variable], dtype=np.float32)
+        ioda_data[(variable, obsErrName)] = np.full(nlocs, 0.1, dtype=np.float32)
+        ioda_data[(variable, qcName)] = np.full(nlocs, 2, dtype=np.int32)
+
+    # setup the IODA writer and write everything out.
+    writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
+    writer.BuildIoda(ioda_data, varDims, varAttrs, GlobalAttrs)
diff --git a/src/compo/mls_o3_nc2ioda.py b/src/compo/mls_o3_nc2ioda.py
index e3a67056d..5bfd6c1df 100755
--- a/src/compo/mls_o3_nc2ioda.py
+++ b/src/compo/mls_o3_nc2ioda.py
@@ -29,38 +29,44 @@
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("air_pressure", "float"),
-    ("dateTime", "integer"),
+    ("pressure", "float"),
+    ("dateTime", "long"),
 ]
 
+varname_ozone = 'ozoneProfile'
+
 ioda2nc = {}
 ioda2nc['latitude'] = 'HDFEOS/SWATHS/O3/Geolocation Fields/Latitude'
 ioda2nc['longitude'] = 'HDFEOS/SWATHS/O3/Geolocation Fields/Longitude'
 ioda2nc['dateTime'] = 'HDFEOS/SWATHS/O3/Geolocation Fields/Time'
-ioda2nc['air_pressure'] = 'HDFEOS/SWATHS/O3/Geolocation Fields/Pressure'
+ioda2nc['pressure'] = 'HDFEOS/SWATHS/O3/Geolocation Fields/Pressure'
 ioda2nc['valKey'] = 'HDFEOS/SWATHS/O3/Data Fields/O3'
 ioda2nc['precision'] = 'HDFEOS/SWATHS/O3/Data Fields/O3Precision'
 ioda2nc['convergence'] = 'HDFEOS/SWATHS/O3/Data Fields/Convergence'
 ioda2nc['status'] = 'HDFEOS/SWATHS/O3/Data Fields/Status'
 ioda2nc['quality'] = 'HDFEOS/SWATHS/O3/Data Fields/Quality'
-ioda2nc['solar_zenith_angle'] = 'HDFEOS/SWATHS/O3/Geolocation Fields/SolarZenithAngle'
+ioda2nc['solarZenithAngle'] = 'HDFEOS/SWATHS/O3/Geolocation Fields/SolarZenithAngle'
 
 obsvars = {
-    'mole_fraction_of_ozone_in_air': 'mole_fraction_of_ozone_in_air',
+    'mole_fraction_of_ozone_in_air': varname_ozone,
 }
 
 AttrData = {
-    'converter': os.path.basename(__file__),
-    'nvars': np.int32(len(obsvars)),
+    'converter': os.path.basename(__file__)
 }
 
 DimDict = {
 }
 
 VarDims = {
-    'mole_fraction_of_ozone_in_air': ['nlocs'],
+    varname_ozone: ['Location'],
 }
 
+metaDataName = iconv.MetaDataName()
+obsValName = iconv.OvalName()
+obsErrName = iconv.OerrName()
+qcName = iconv.OqcName()
+
 
 class mls(object):
     def __init__(self, filenames, lvmin, lvmax, sTAI, eTAI, nrt, qcOn, errorOn):
@@ -76,33 +82,34 @@ def __init__(self, filenames, lvmin, lvmax, sTAI, eTAI, nrt, qcOn, errorOn):
         self.endTAI = eTAI
         self.nrt = nrt
         for v in list(ioda2nc.keys()):
-            if(v != 'valKey' and v != 'errKey'):
+            if(v == 'status' or v == 'precision' or v == 'convergence' or v == 'quality'):
+                pass
+            elif(v != 'valKey' and v != 'errKey'):
                 self.outdata[(v, 'MetaData')] = []
-        self.outdata[('level', 'MetaData')] = []
-        self._setVarDict('mole_fraction_of_ozone_in_air')
-        self.outdata[self.varDict['mole_fraction_of_ozone_in_air']['valKey']] = []
+        self.outdata[('referenceLevel', 'MetaData')] = []
+        self._setVarDict(varname_ozone)
+        self.outdata[self.varDict[varname_ozone]['valKey']] = []
         if(self.qcOn):
-            self.outdata[self.varDict['mole_fraction_of_ozone_in_air']['errKey']] = []
+            self.outdata[self.varDict[varname_ozone]['errKey']] = []
 
         self._read()
 
     # set ioda variable keys
     def _setVarDict(self, iodavar):
-        self.varDict[iodavar]['valKey'] = iodavar, iconv.OvalName()
+        self.varDict[iodavar]['valKey'] = iodavar, obsValName
         if(self.qcOn):
-            self.varDict[iodavar]['errKey'] = iodavar, iconv.OerrName()
-        self.varDict[iodavar]['qcKey'] = iodavar, iconv.OqcName()
+            self.varDict[iodavar]['errKey'] = iodavar, obsErrName
+        self.varDict[iodavar]['qcKey'] = iodavar, qcName
 
     # set variable attributes for IODA
     def _setVarAttr(self, iodavar):
-        self.varAttrs[iodavar, iconv.OvalName()]['coordinates'] = 'longitude latitude'
-        self.varAttrs[iodavar, iconv.OerrName()]['coordinates'] = 'longitude latitude'
-        self.varAttrs[iodavar, iconv.OqcName()]['coordinates'] = 'longitude latitude'
-        self.varAttrs[iodavar, iconv.OvalName()]['units'] = 'ppmv'
-        self.varAttrs[iodavar, iconv.OerrName()]['units'] = 'ppmv'
+        self.varAttrs[iodavar, obsValName]['coordinates'] = 'longitude latitude'
+        self.varAttrs[iodavar, obsErrName]['coordinates'] = 'longitude latitude'
+        self.varAttrs[iodavar, qcName]['coordinates'] = 'longitude latitude'
+        self.varAttrs[iodavar, obsValName]['units'] = 'ppmv'
+        self.varAttrs[iodavar, obsErrName]['units'] = 'ppmv'
 
         varsToAddUnits = list(ioda2nc.keys())
-        varsToAddUnits.append('level')
         for v in varsToAddUnits:
             if(v != 'valKey' and v != 'errKey'):
                 vkey = (v, 'MetaData')
@@ -110,14 +117,14 @@ def _setVarAttr(self, iodavar):
                     self.varAttrs[vkey]['units'] = 'Pa'
                 elif(v == 'dateTime'):
                     self.varAttrs[vkey]['units'] = 'seconds since 1993-01-01T00:00:00Z'
-                elif('angle' in v.lower() or 'latitude' in v.lower() or 'longitude' in v.lower()):
-                    self.varAttrs[vkey]['units'] = 'degrees'
-                elif('flag' in v.lower()):
-                    self.varAttrs[vkey]['units'] = 'unitless'
+                elif('latitude' in v.lower()):
+                    self.varAttrs[vkey]['units'] = 'degree_north'
+                elif('longitude' in v.lower()):
+                    self.varAttrs[vkey]['units'] = 'degree_east'
+                elif('angle' in v.lower()):
+                    self.varAttrs[vkey]['units'] = 'degree'
                 elif('prior' in v.lower()):
                     self.varAttrs[vkey]['units'] = 'ppmv'
-                else:
-                    self.varAttrs[vkey]['units'] = 'unitless'
 
     # Read data needed from raw MLS file.
     def _read_nc(self, filename, ifile, maxfile):
@@ -139,7 +146,7 @@ def _read_nc(self, filename, ifile, maxfile):
 
         d = {}
         for k in list(ioda2nc.keys()):
-            if (k == 'air_pressure'):
+            if (k == 'pressure'):
                 d[k] = ncd[ioda2nc[k]][...]*100.  # convert to Pa
                 d[k].mask = False
             else:
@@ -179,13 +186,13 @@ def _just_flatten(self, d):
         dd['precision'] = d['precision'][idx, self.lmin:self.lmax+1]
         lvec = np.arange(self.lmin+1, self.lmax+2)
         dd['level'], dd['status'] = np.meshgrid(np.arange(self.lmin+1, self.lmax+2), d['status'][idx])
-        dd['air_pressure'], dd['dateTime'] = np.meshgrid(d['air_pressure'][self.lmin:self.lmax+1], d['dateTime'][idx])
+        dd['pressure'], dd['dateTime'] = np.meshgrid(d['pressure'][self.lmin:self.lmax+1], d['dateTime'][idx])
         dd['quality'] = np.tile(d['quality'][idx], (lvec.shape[0], 1)).T
         dd['convergence'] = np.tile(d['convergence'][idx], (lvec.shape[0], 1)).T
         dd['status'] = np.tile(d['status'][idx], (lvec.shape[0], 1)).T
         dd['latitude'] = np.tile(d['latitude'][idx], (lvec.shape[0], 1)).T
         dd['longitude'] = np.tile(d['longitude'][idx], (lvec.shape[0], 1)).T
-        dd['solar_zenith_angle'] = np.tile(d['solar_zenith_angle'][idx], (lvec.shape[0], 1)).T
+        dd['solarZenithAngle'] = np.tile(d['solarZenithAngle'][idx], (lvec.shape[0], 1)).T
         for k in list(dd.keys()):
             dd[k] = np.asarray(dd[k])
             dd[k] = dd[k].flatten().tolist()
@@ -209,9 +216,9 @@ def _do_qc(self, d):
                 if(d['dateTime'][irec] < self.startTAI or d['dateTime'][irec] > self.endTAI):
                     continue
                 for k in list(d.keys()):
-                    if (len(d[k].shape) == 1 and k != 'air_pressure'):
+                    if (len(d[k].shape) == 1 and k != 'pressure'):
                         dd[k].append(d[k][irec])
-                    elif (k == 'air_pressure'):
+                    elif (k == 'pressure'):
                         dd[k].append(d[k][ilev])
                     elif k != 'errKey':
                         dd[k].append(d[k][irec, ilev])
@@ -220,7 +227,7 @@ def _do_qc(self, d):
 
     def _read(self):
         # set up variable names for IODA
-        self._setVarAttr('mole_fraction_of_ozone_in_air')
+        self._setVarAttr(varname_ozone)
 
         # loop through input filenames
         for i, f in enumerate(self.filenames):
@@ -238,7 +245,11 @@ def _read(self):
                     d['errKey'].append(self._calc_error(
                         val, d['precision'][ival], d['level'][ival]-1))
             for v in list(d.keys()):
-                if(v != 'valKey' and v != 'errKey'):
+                if(v == 'status' or v == 'precision' or v == 'convergence' or v == 'quality'):
+                    pass
+                elif(v == 'level'):
+                    self.outdata[('referenceLevel', 'MetaData')].extend(d[v])
+                elif(v != 'valKey' and v != 'errKey'):
                     self.outdata[(v, 'MetaData')].extend(d[v])
             for ncvar, iodavar in obsvars.items():
                 self.outdata[self.varDict[iodavar]
@@ -246,8 +257,8 @@ def _read(self):
                 if(self.errorOn):
                     self.outdata[self.varDict[iodavar]['errKey']].extend(d['errKey'])
 
-        DimDict['nlocs'] = np.float32(len(self.outdata[('dateTime', 'MetaData')]))
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+        nlocs = len(self.outdata[('dateTime', 'MetaData')])
+        DimDict['Location'] = nlocs
 
         for k in self.outdata.keys():
             self.outdata[k] = np.asarray(self.outdata[k])
diff --git a/src/compo/modis_aod2ioda.py b/src/compo/modis_aod2ioda.py
index 8f9487529..561946204 100755
--- a/src/compo/modis_aod2ioda.py
+++ b/src/compo/modis_aod2ioda.py
@@ -28,26 +28,30 @@
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string")
+    ("dateTime", "long")
 ]
 
+obsvars = ["aerosolOpticalDepth"]
 
-obsvars = {
-    'A': "aerosol_optical_depth_4",
-}
-
+# A dictionary of global attributes.  More filled in further down.
 AttrData = {
     'converter': os.path.basename(__file__),
-    'nvars': np.int32(len(obsvars)),
+    'description': 'AOD at 550nm'
 }
 
+# A dictionary of variable dimensions.
+DimDict = {}
 
-DimDict = {
-}
+# A dictionary of variable names and their dimensions.
+VarDims = {'aerosolOpticalDepth': ['Location']}
 
-VarDims = {
-    'aerosol_optical_depth': ['nlocs']
-}
+# Get the group names we use the most.
+metaDataName = iconv.MetaDataName()
+obsValName = iconv.OvalName()
+obsErrName = iconv.OerrName()
+qcName = iconv.OqcName()
+
+long_missing_value = nc.default_fillvals['i8']
 
 
 class AOD(object):
@@ -58,47 +62,55 @@ def __init__(self, filenames, obs_time, pltfrm):
         self.varDict = defaultdict(lambda: defaultdict(dict))
         self.outdata = defaultdict(lambda: DefaultOrderedDict(OrderedDict))
         self.varAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
+        # there's absolutely no difference in the hdf4 files attributes
+        # between Terra and Aqua files. So it is user specified
+        AttrData['platform'] = pltfrm
+        # sensor would be always MODIS for this converter
+        AttrData['sensor'] = 'MODIS'
+        AttrData['datetimeReference'] = obs_time
         self._read()
 
     def _read(self):
         # set up variable names for IODA
-        for ncvar, iodavar in obsvars.items():
-            self.varDict[iodavar]['valKey'] = iodavar, iconv.OvalName()
-            self.varDict[iodavar]['errKey'] = iodavar, iconv.OerrName()
-            self.varDict[iodavar]['qcKey'] = iodavar, iconv.OqcName()
-            self.varAttrs[iodavar, iconv.OvalName()]['coordinates'] = 'longitude latitude'
-            self.varAttrs[iodavar, iconv.OerrName()]['coordinates'] = 'longitude latitude'
-            self.varAttrs[iodavar, iconv.OqcName()]['coordinates'] = 'longitude latitude'
-            self.varAttrs[iodavar, iconv.OvalName()]['_FillValue'] = -9999.
-            self.varAttrs[iodavar, iconv.OerrName()]['_FillValue'] = -9999.
-            self.varAttrs[iodavar, iconv.OqcName()]['_FillValue'] = -9999
-            self.varAttrs[iodavar, iconv.OvalName()]['units'] = '1'
-            self.varAttrs[iodavar, iconv.OqcName()]['units'] = 'unitless'
-            self.varAttrs[iodavar, iconv.OerrName()]['units'] = 'unitless'
+        for iodavar in obsvars:
+            self.varDict[iodavar]['valKey'] = iodavar, obsValName
+            self.varDict[iodavar]['errKey'] = iodavar, obsErrName
+            self.varDict[iodavar]['qcKey'] = iodavar, qcName
+            self.varAttrs[iodavar, obsValName]['coordinates'] = 'longitude latitude'
+            self.varAttrs[iodavar, obsErrName]['coordinates'] = 'longitude latitude'
+            self.varAttrs[iodavar, qcName]['coordinates'] = 'longitude latitude'
+            self.varAttrs[iodavar, obsValName]['_FillValue'] = -9999.
+            self.varAttrs[iodavar, obsErrName]['_FillValue'] = -9999.
+            self.varAttrs[iodavar, qcName]['_FillValue'] = -9999
+            self.varAttrs[iodavar, obsValName]['units'] = '1'
+            self.varAttrs[iodavar, obsErrName]['units'] = '1'
+
+        # All of MODIS AOD data have a singular reference time
+        self.varAttrs[('dateTime', metaDataName)]['units'] = 'seconds since 1993-01-01T00:00:00Z'
+
+        # Make empty lists for the output vars
+        self.outdata[('latitude', metaDataName)] = np.array([], dtype=np.float32)
+        self.outdata[('longitude', metaDataName)] = np.array([], dtype=np.float32)
+        self.outdata[('dateTime', metaDataName)] = np.array([], dtype=np.int64)
+        for iodavar in obsvars:
+            self.outdata[self.varDict[iodavar]['valKey']] = np.array([], dtype=np.float32)
+            self.outdata[self.varDict[iodavar]['errKey']] = np.array([], dtype=np.float32)
+            self.outdata[self.varDict[iodavar]['qcKey']] = np.array([], dtype=np.int32)
 
         # loop through input filenames
-        first = True
         for f in self.filenames:
             hdf = SD(f, SDC.READ)
-            # there's absolutely no difference in the hdf4 files attributes
-            # between Terra and Aqua files. So it is user specified
-            AttrData['platform'] = self.pltfrm
-            # sensor would be always MODIS for this converter
-            AttrData['sensor'] = 'MODIS'
-
-            obstime = self.obs_time
-            AttrData['date_time'] = self.obs_time
-            AttrData['observation_type'] = 'Aod'
 
             #  Get variables
             modis_time = hdf.select('Scan_Start_Time')[:].ravel()
-
-            # convert time to date_string
+            print(f"length of time var: {len(modis_time)}")
+            modis_time = modis_time.astype('float32')
             lats = hdf.select('Latitude')[:].ravel()
             lats = lats.astype('float32')
             lons = hdf.select('Longitude')[:].ravel()
             lons = lons.astype('float32')
             aod = hdf.select('AOD_550_Dark_Target_Deep_Blue_Combined')[:].ravel()
+            aod = aod.astype('float64')
             land_sea_flag = hdf.select('Land_sea_Flag')[:].ravel()
             QC_flag = hdf.select('Land_Ocean_Quality_Flag')[:].ravel()
             QC_flag = QC_flag.astype('int32')
@@ -117,10 +129,9 @@ def _read(self):
             sen_zen = sen_zen[pos_index]
             unc_land = unc_land[pos_index] * 1E-3  # see scale factor
             modis_time = modis_time[pos_index]
-            obs_time = np.empty_like(QC_flag, dtype=object)
-            obs_time_2 = [datetime.fromisoformat('1993-01-01') + timedelta(seconds=x) for x in modis_time]
-            for t in range(len(obs_time_2)):
-                obs_time[t] = obs_time_2[t].strftime('%Y-%m-%dT%H:%M:%SZ')
+            obs_time = np.full(len(modis_time), long_missing_value, dtype=np.int64)
+            for n, t in enumerate(modis_time):
+                obs_time[n] = round(t)
 
             # uncertainty estimates:
             # From MODIS file (over ocean) and Levy, 2010 (over land)
@@ -129,34 +140,17 @@ def _read(self):
             over_ocean = np.logical_not(land_sea_flag > 0)
             over_land = np.logical_not(land_sea_flag == 0)
             UNC = np.where(over_land, unc_land, np.add(0.05, np.multiply(0.15, aod)))
-            if first:
-                self.outdata[('latitude', 'MetaData')] = lats
-                self.outdata[('longitude', 'MetaData')] = lons
-                self.outdata[('datetime', 'MetaData')] = obs_time
-            else:
-                self.outdata[('latitude', 'MetaData')] = np.concatenate((self.outdata[('latitude', 'MetaData')], lats))
-                self.outdata[('longitude', 'MetaData')] = np.concatenate((self.outdata[('longitude', 'MetaData')], lons))
-                self.outdata[('datetime', 'MetaData')] = np.concatenate((self.outdata[('datetime', 'MetaData')], obs_time))
-
-            for ncvar, iodavar in obsvars.items():
-                data = aod.astype('float32')
-                err = UNC.astype('float32')
-                if first:
-                    self.outdata[self.varDict[iodavar]['valKey']] = data
-                    self.outdata[self.varDict[iodavar]['errKey']] = err
-                    self.outdata[self.varDict[iodavar]['qcKey']] = QC_flag
-
-                else:
-                    self.outdata[self.varDict[iodavar]['valKey']] = np.concatenate(
-                        (self.outdata[self.varDict[iodavar]['valKey']], data))
-                    self.outdata[self.varDict[iodavar]['errKey']] = np.concatenate(
-                        (self.outdata[self.varDict[iodavar]['errKey']], err))
-                    self.outdata[self.varDict[iodavar]['qcKey']] = np.concatenate(
-                        (self.outdata[self.varDict[iodavar]['qcKey']], QC_flag))
-
-            first = False
-        DimDict['nlocs'] = len(self.outdata[('datetime', 'MetaData')])
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+
+            self.outdata[('latitude', metaDataName)] = np.append(self.outdata[('latitude', metaDataName)], np.array(lats, dtype=np.float32))
+            self.outdata[('longitude', metaDataName)] = np.append(self.outdata[('longitude', metaDataName)], np.array(lons, dtype=np.float32))
+            self.outdata[('dateTime', metaDataName)] = np.append(self.outdata[('dateTime', metaDataName)], np.array(obs_time, dtype=np.int64))
+
+            for iodavar in obsvars:
+                self.outdata[self.varDict[iodavar]['valKey']] = np.append(self.outdata[self.varDict[iodavar]['valKey']], np.array(aod, dtype=np.float32))
+                self.outdata[self.varDict[iodavar]['errKey']] = np.append(self.outdata[self.varDict[iodavar]['errKey']], np.array(UNC, dtype=np.float32))
+                self.outdata[self.varDict[iodavar]['qcKey']] = np.append(self.outdata[self.varDict[iodavar]['qcKey']], np.array(QC_flag, dtype=np.int32))
+
+        DimDict['Location'] = len(self.outdata[('dateTime', metaDataName)])
 
 
 def main():
diff --git a/src/compo/mopitt_co_nc2ioda.py b/src/compo/mopitt_co_nc2ioda.py
index a88b7aed8..44af99c7c 100755
--- a/src/compo/mopitt_co_nc2ioda.py
+++ b/src/compo/mopitt_co_nc2ioda.py
@@ -27,11 +27,11 @@
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string"),
+    ("dateTime", "long"),
 ]
 
 obsvars = {
-    'carbonmonoxide_total_column': 'carbon_monoxide_in_total_column',
+    'carbonmonoxide_total_column': 'carbonmonoxideTotal',
 }
 
 AttrData = {
@@ -43,7 +43,7 @@
 }
 
 VarDims = {
-    'carbon_monoxide_in_total_column': ['nlocs'],
+    'carbonmonoxideTotal': ['Location'],
 }
 
 # constants
@@ -64,7 +64,7 @@ def __init__(self, filenames, time_range):
 
     def _read(self):
         # set up variable names for IODA
-        for iodavar in ['carbon_monoxide_in_total_column']:
+        for iodavar in ['carbonmonoxideTotal']:
             self.varDict[iodavar]['valKey'] = iodavar, iconv.OvalName()
             self.varDict[iodavar]['errKey'] = iodavar, iconv.OerrName()
             self.varDict[iodavar]['qcKey'] = iodavar, iconv.OqcName()
@@ -164,7 +164,7 @@ def _read(self):
 
             if first:
                 # add metadata variables
-                self.outdata[('datetime', 'MetaData')] = times[flg]
+                self.outdata[('dateTime', 'MetaData')] = times[flg]
                 self.outdata[('latitude', 'MetaData')] = lats[flg]
                 self.outdata[('longitude', 'MetaData')] = lons[flg]
                 self.outdata[('apriori_term', 'RtrvlAncData')] = ap_tc[flg]
@@ -182,8 +182,8 @@ def _read(self):
                 self.outdata[self.varDict[iodavar]['qcKey']] = qa[flg]
 
             else:
-                self.outdata[('datetime', 'MetaData')] = np.concatenate((
-                    self.outdata[('datetime', 'MetaData')], times[flg]))
+                self.outdata[('dateTime', 'MetaData')] = np.concatenate((
+                    self.outdata[('dateTime', 'MetaData')], times[flg]))
                 self.outdata[('latitude', 'MetaData')] = np.concatenate((
                     self.outdata[('latitude', 'MetaData')], lats[flg]))
                 self.outdata[('longitude', 'MetaData')] = np.concatenate((
@@ -209,8 +209,8 @@ def _read(self):
                         (self.outdata[self.varDict[iodavar]['qcKey']], qa[flg]))
             first = False
 
-        DimDict['nlocs'] = len(self.outdata[('datetime', 'MetaData')])
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+        DimDict['Location'] = len(self.outdata[('dateTime', 'MetaData')])
+        AttrData['Location'] = np.int32(DimDict['Location'])
 
         for k in range(nlevs):
             varname = 'averaging_kernel_level_'+str(k+1)
diff --git a/src/compo/omi_o3_nc2ioda.py b/src/compo/omi_o3_nc2ioda.py
index 778001ce3..5decb1b3c 100755
--- a/src/compo/omi_o3_nc2ioda.py
+++ b/src/compo/omi_o3_nc2ioda.py
@@ -24,39 +24,36 @@
 from orddicts import DefaultOrderedDict
 import ioda_conv_engines as iconv
 
-
-def is_bit_set(integer_value, bit_position):
-    return (integer_value & (1 << bit_position)) != 0
-
-
 # Global Dictionaries.
 
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("dateTime", "integer"),
+    ("dateTime", "long"),
 ]
 
+# Name to call the output ozone variable
+varname_ozone = 'ozoneTotal'
+
+# Dictionary of variable name found in input file and corresponding output name
+obsvars = {
+    'integrated_layer_ozone_in_air': varname_ozone,
+}
+
 ioda2nc = {}
 ioda2nc['latitude'] = 'HDFEOS/SWATHS/OMI Column Amount O3/Geolocation Fields/Latitude'
 ioda2nc['longitude'] = 'HDFEOS/SWATHS/OMI Column Amount O3/Geolocation Fields/Longitude'
 ioda2nc['dateTime'] = 'HDFEOS/SWATHS/OMI Column Amount O3/Geolocation Fields/Time'
-ioda2nc['solar_zenith_angle'] = 'HDFEOS/SWATHS/OMI Column Amount O3/Geolocation Fields/SolarZenithAngle'
+ioda2nc['solarZenithAngle'] = 'HDFEOS/SWATHS/OMI Column Amount O3/Geolocation Fields/SolarZenithAngle'
 ioda2nc['prior_o3'] = 'HDFEOS/SWATHS/OMI Column Amount O3/Data Fields/APrioriLayerO3'
 # ioda2nc['Layer_Efficiency'] = 'HDFEOS/SWATHS/OMI Column Amount O3/Data Fields/LayerEfficiency'
 ioda2nc['valKey'] = 'HDFEOS/SWATHS/OMI Column Amount O3/Data Fields/ColumnAmountO3'
 ioda2nc['quality_flag'] = 'HDFEOS/SWATHS/OMI Column Amount O3/Data Fields/QualityFlags'
 ioda2nc['algorithm_flag'] = 'HDFEOS/SWATHS/OMI Column Amount O3/Data Fields/AlgorithmFlags'
 
-
-obsvars = {
-    'integrated_layer_ozone_in_air': 'integrated_layer_ozone_in_air',
-}
-
 AttrData = {
     'converter': os.path.basename(__file__),
-    'nvars': np.int32(len(obsvars)),
-    'satellite': 'aura',
+    'platformCommonName': 'aura',
     'sensor': 'omi',
 }
 
@@ -64,9 +61,17 @@ def is_bit_set(integer_value, bit_position):
 }
 
 VarDims = {
-    'integrated_layer_ozone_in_air': ['nlocs'],
+    varname_ozone: ['Location'],
 }
 
+missing_value = nc.default_fillvals['f4']
+int_missing_value = nc.default_fillvals['i4']
+long_missing_value = nc.default_fillvals['i8']
+
+
+def is_bit_set(integer_value, bit_position):
+    return (integer_value & (1 << bit_position)) != 0
+
 
 class omi(object):
     def __init__(self, filenames, sTAI, eTAI, qcOn):
@@ -77,15 +82,17 @@ def __init__(self, filenames, sTAI, eTAI, qcOn):
         self.startTAI = sTAI
         self.endTAI = eTAI
         self.qcOn = qcOn
-        self._setVarDict('integrated_layer_ozone_in_air')
+        self._setVarDict(varname_ozone)
 
         # initialize dictionary with  empty list for MetaData variable to populate later.
         vars2output = list(ioda2nc.keys())
-        vars2output.append('scan_position')
+        vars2output.append('sensorScanPosition')
         for v in vars2output:
-            if(v != 'valKey'):
+            if(v == 'quality_flag' or v == 'algorithm_flag' or v == 'prior_o3'):
+                pass
+            elif(v != 'valKey'):
                 self.outdata[(v, 'MetaData')] = []
-        self.outdata[self.varDict['integrated_layer_ozone_in_air']['valKey']] = []
+        self.outdata[self.varDict[varname_ozone]['valKey']] = []
         self._read()
 
     # set ioda variable keys
@@ -95,11 +102,9 @@ def _setVarDict(self, iodavar):
     # set variable attributes for IODA
     def _setVarAttr(self, iodavar):
         self.varAttrs[iodavar, iconv.OvalName()]['coordinates'] = 'longitude latitude'
-        missing_value = 9.96921e+36
-        int_missing_value = -2147483647
         self.varAttrs[iodavar, iconv.OvalName()]['_FillValue'] = missing_value
         varsToAddUnits = list(ioda2nc.keys())
-        varsToAddUnits.append('scan_position')
+        varsToAddUnits.append('sensorScanPosition')
         for v in varsToAddUnits:
             if(v != 'valKey'):
                 vkey = (v, 'MetaData')
@@ -107,10 +112,13 @@ def _setVarAttr(self, iodavar):
                     self.varAttrs[vkey]['units'] = 'Pa'
                 elif(v == 'dateTime'):
                     self.varAttrs[vkey]['units'] = 'seconds since 1993-01-01T00:00:00Z'
+                    self.varAttrs[vkey]['_FillValue'] = long_missing_value
+                elif('latitude' in v.lower()):
+                    self.varAttrs[vkey]['units'] = 'degree_north'
+                elif('longitude' in v.lower()):
+                    self.varAttrs[vkey]['units'] = 'degree_east'
                 elif('angle' in v.lower()):
-                    self.varAttrs[vkey]['units'] = 'degrees'
-                elif('flag' in v.lower()):
-                    self.varAttrs[vkey]['units'] = 'unitless'
+                    self.varAttrs[vkey]['units'] = 'degree'
                 elif('prior' in v.lower()):
                     self.varAttrs[vkey]['units'] = 'ppmv'
         self.varAttrs[iodavar, iconv.OvalName()]['units'] = 'DU'
@@ -122,6 +130,8 @@ def _read_nc(self, filename):
         # use dictionary above to just read fields we want out of the netcdf.
         for k in list(ioda2nc.keys()):
             d[k] = ncd[ioda2nc[k]][...]
+            if k == 'dateTime':
+                d[k] = np.round(d[k])
             d[k].mask = False
         ncd.close()
         return d
@@ -137,8 +147,8 @@ def _just_flatten(self, d):
                 scn_tmp = scn_tmp.astype('float32')
                 tmp = tmp.astype(np.int64)
                 dd[k] = tmp.flatten().tolist()
-                dd['scan_position'] = scn_tmp.flatten().tolist()
-            elif(k == 'Prior_O3'):
+                dd['sensorScanPosition'] = scn_tmp.flatten().tolist()
+            elif(k.lower() == 'prior_o3'):
                 dd[k] = d[k][:, :, 0].flatten().tolist()
             else:
                 dd[k] = d[k].flatten().tolist()
@@ -153,7 +163,7 @@ def _do_qc(self, d):
         # intialize dictonary of qc'd variables
         dd = {}
         flatVars = list(ioda2nc.keys())
-        flatVars.append('scan_position')
+        flatVars.append('sensorScanPosition')
         for v in flatVars:
             dd[v] = []
 
@@ -200,20 +210,20 @@ def _do_qc(self, d):
                 if (six_set or eight_set or nine_set):
                     continue
                 # could simply this further with one if statement possibly more clever use of a bit masking.
-                dd['scan_position'].append(float(iscan+1))
+                dd['sensorScanPosition'].append(float(iscan+1))
                 for v in flatVars:
                     if(v == 'dateTime'):
                         dd[v].append(d[v][itime])
                     elif(v == 'prior_o3'):
                         dd[v].append(d[v][itime, iscan, 0])
-                    elif(v != 'scan_position'):
+                    elif(v != 'sensorScanPosition'):
                         dd[v].append(d[v][itime, iscan])
 
         return dd
 
     def _read(self):
         # set up variable names for IODA
-        for iodavar in ['integrated_layer_ozone_in_air', ]:
+        for iodavar in [varname_ozone, ]:
             # self._setVarDict(var)
             self._setVarAttr(iodavar)
         # loop through input filenames
@@ -227,18 +237,21 @@ def _read(self):
                 d = self._just_flatten(nc_data)
             # add MetaData variables.
             for v in list(d.keys()):
-                if(v != 'valKey'):
+                if(v == 'quality_flag' or v == 'algorithm_flag' or v == 'prior_o3'):
+                    pass
+                elif(v != 'valKey'):
                     self.outdata[(v, 'MetaData')].extend(d[v])
 
             for ncvar, iodavar in obsvars.items():
                 self.outdata[self.varDict[iodavar]
                              ['valKey']].extend(d['valKey'])
-        DimDict['nlocs'] = len(self.outdata[('longitude', 'MetaData')])
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+
+        nlocs = len(self.outdata[('longitude', 'MetaData')])
+        DimDict['Location'] = np.int64(nlocs)
         # add dummy air_pressure so UFO will know this is a total column ob, and not partial.
-        self.outdata[('air_pressure', 'MetaData')] = np.zeros(
-            DimDict['nlocs']).tolist()
-        self.varAttrs[('air_pressure', 'MetaData')]['units'] = 'Pa'
+        self.outdata[('pressure', 'MetaData')] = np.zeros(
+            DimDict['Location']).tolist()
+        self.varAttrs[('pressure', 'MetaData')]['units'] = 'Pa'
 
         for k in self.outdata.keys():
             self.outdata[k] = np.asarray(self.outdata[k])
@@ -247,7 +260,7 @@ def _read(self):
             elif(self.outdata[k].dtype == 'int64' and k != ('dateTime', 'MetaData')):
                 self.outdata[k] = self.outdata[k].astype('int32')
             elif(self.outdata[k].dtype == 'uint16' or self.outdata[k].dtype == 'uint8'):
-                self.outdata[k] = self.outdata[k].astype(int)
+                self.outdata[k] = self.outdata[k].astype('int32')
         self.outdata[('dateTime', 'MetaData')] = self.outdata[('dateTime', 'MetaData')].astype('int64')
         # ensure lon is 0-360
         self.outdata[('longitude', 'MetaData')] = self.outdata[('longitude', 'MetaData')] % 360
diff --git a/src/compo/ompsnm_o3_nc2ioda.py b/src/compo/ompsnm_o3_nc2ioda.py
index ca72c0785..0502c4b59 100755
--- a/src/compo/ompsnm_o3_nc2ioda.py
+++ b/src/compo/ompsnm_o3_nc2ioda.py
@@ -25,21 +25,27 @@
 from orddicts import DefaultOrderedDict
 import ioda_conv_engines as iconv
 
-
-# Global Dictionaries.
+# Dictionary of essential MetaData
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
     ("dateTime", "long"),
 ]
 
+# Name to call the output ozone variable
+varname_ozone = 'ozoneTotal'
+
+# Dictionary of variable name found in input file and corresponding output name
+obsvars = {
+    'integrated_layer_ozone_in_air': varname_ozone,
+}
 
 # dictionary to map things we're putting into ioda and taking out of instrument native format
 ioda2nc = {}
 ioda2nc['latitude'] = 'GeolocationData/Latitude'
 ioda2nc['longitude'] = 'GeolocationData/Longitude'
 ioda2nc['dateTime'] = 'GeolocationData/Time'
-ioda2nc['solar_zenith_angle'] = 'GeolocationData/SolarZenithAngle'
+ioda2nc['solarZenithAngle'] = 'GeolocationData/SolarZenithAngle'
 ioda2nc['valKey'] = 'ScienceData/ColumnAmountO3'
 ioda2nc['ground_pixel_quality'] = 'GeolocationData/GroundPixelQualityFlags'
 ioda2nc['quality_flags'] = 'ScienceData/QualityFlags'
@@ -47,15 +53,9 @@
 ioda2nc['measurement_quality_flags'] = 'ScienceData/MeasurementQualityFlags'
 ioda2nc['instrument_quality_flags'] = 'GeolocationData/InstrumentQualityFlags'
 
-
-obsvars = {
-    'integrated_layer_ozone_in_air': 'integrated_layer_ozone_in_air',
-}
-
 AttrData = {
     'converter': os.path.basename(__file__),
-    'nvars': np.int32(len(obsvars)),
-    'satellite': 'npp',
+    'platformCommonName': 'npp',
     'sensor': 'ompsnm',
 }
 
@@ -63,7 +63,7 @@
 }
 
 VarDims = {
-    'integrated_layer_ozone_in_air': ['nlocs'],
+    varname_ozone: ['Location'],
 }
 
 
@@ -75,17 +75,19 @@ def __init__(self, filenames, sTAI, eTAI):
         self.varAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
         self.startTAI = sTAI
         self.endTAI = eTAI
-        self._setVarDict('integrated_layer_ozone_in_air')
+        self._setVarDict(varname_ozone)
 
         vars2output = list(ioda2nc.keys())
-        vars2output.append('scan_position')
+        vars2output.append('sensorScanPosition')
         for v in vars2output:
-            if(v != 'valKey'):
+            if('quality' in v or 'flags' in v):
+                pass
+            elif(v != 'valKey'):
                 self.outdata[(v, 'MetaData')] = []
-        self.outdata[self.varDict['integrated_layer_ozone_in_air']['valKey']] = []
+        self.outdata[self.varDict[varname_ozone]['valKey']] = []
 
-        self._setVarDict('integrated_layer_ozone_in_air')
-        self.outdata[self.varDict['integrated_layer_ozone_in_air']['valKey']] = []
+        self._setVarDict(varname_ozone)
+        self.outdata[self.varDict[varname_ozone]['valKey']] = []
 
         self._read()
 
@@ -98,7 +100,7 @@ def _setVarAttr(self, iodavar):
         self.varAttrs[iodavar, iconv.OvalName()]['coordinates'] = 'longitude latitude'
 
         varsToAddUnits = list(ioda2nc.keys())
-        varsToAddUnits.append('scan_position')
+        varsToAddUnits.append('sensorScanPosition')
         for v in varsToAddUnits:
             if(v != 'valKey'):
                 vkey = (v, 'MetaData')
@@ -108,15 +110,11 @@ def _setVarAttr(self, iodavar):
                     self.varAttrs[vkey]['units'] = 'seconds since 1993-01-01T00:00:00Z'
                 elif('angle' in v.lower()):
                     self.varAttrs[vkey]['units'] = 'degrees'
-                elif('flag' in v.lower()):
-                    self.varAttrs[vkey]['units'] = 'unitless'
                 elif('prior' in v.lower()):
                     self.varAttrs[vkey]['units'] = 'ppmv'
-                else:
-                    self.varAttrs[vkey]['units'] = 'unitless'
         self.varAttrs[iodavar, iconv.OvalName()]['units'] = 'DU'
 
-        vkey = ('air_pressure', 'MetaData')
+        vkey = ('pressure', 'MetaData')
         self.varAttrs[vkey]['units'] = 'Pa'
 
     # Read data needed from raw OMPSNM file.
@@ -132,8 +130,8 @@ def _read_nc(self, filename):
         # mesh time and scan_position to get flattened array instead of using loops
         time_vec = d['dateTime']
         scan_position_vec = np.arange(1, d['valKey'].shape[1]+1)
-        d['scan_position'], d['dateTime'] = np.meshgrid(scan_position_vec, time_vec)
-        d['scan_position'] = d['scan_position'].astype('float32')
+        d['sensorScanPosition'], d['dateTime'] = np.meshgrid(scan_position_vec, time_vec)
+        d['sensorScanPosition'] = d['sensorScanPosition'].astype('float32')
         d['measurement_quality_flags'].mask = False
         d['instrument_quality_flags'].mask = False
         d['measurement_quality_flags'] = np.tile(d['measurement_quality_flags'], (scan_position_vec.shape[0], 1)).T
@@ -144,7 +142,7 @@ def _read_nc(self, filename):
 
     def _read(self):
         # set up variable names for IODA
-        for iodavar in ['integrated_layer_ozone_in_air', ]:
+        for iodavar in [varname_ozone, ]:
             # self._setVarDict(var)
             self._setVarAttr(iodavar)
         # loop through input filenames
@@ -152,15 +150,17 @@ def _read(self):
             fileData, idx = self._read_nc(f)
             # add metadata variables
             for v in list(fileData.keys()):
-                if(v != 'valKey' and v != 'ozone_Apriori' and v != 'layer_efficiency'):
+                if('quality' in v or 'flags' in v):
+                    pass
+                elif(v != 'valKey' and v != 'ozone_Apriori' and v != 'layer_efficiency'):
                     #  add metadata variables
                     self.outdata[(v, 'MetaData')].extend(fileData[v][idx].flatten().tolist())
             for ncvar, iodavar in obsvars.items():
                 self.outdata[self.varDict[iodavar]['valKey']].extend(fileData['valKey'][idx].flatten().tolist())
 
         # add dummy air_pressure so UFO will know this is a total column ob, and not partial.
-        nloc = len(self.outdata[('dateTime', 'MetaData')])
-        self.outdata[('air_pressure', 'MetaData')] = np.zeros(nloc).tolist()
+        nlocs = len(self.outdata[('dateTime', 'MetaData')])
+        self.outdata[('pressure', 'MetaData')] = np.zeros(nlocs).tolist()
 
         for k in self.outdata.keys():
             self.outdata[k] = np.asarray(self.outdata[k])
@@ -168,8 +168,7 @@ def _read(self):
                 self.outdata[k] = self.outdata[k].astype('float32')
             elif(self.outdata[k].dtype == 'int64' and k != ('dateTime', 'MetaData')):
                 self.outdata[k] = self.outdata[k].astype('int32')
-        DimDict['nlocs'] = self.outdata[('dateTime', 'MetaData')].shape[0]
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+        DimDict['Location'] = nlocs
         self.outdata[('dateTime', 'MetaData')] = self.outdata[('dateTime', 'MetaData')].astype(np.int64)
         self.outdata[('longitude', 'MetaData')] = self.outdata[('longitude', 'MetaData')] % 360
 # end ompsnm object.
diff --git a/src/compo/tropomi_no2_co_nc2ioda.py b/src/compo/tropomi_no2_co_nc2ioda.py
index 2e28d367c..34ac03c7d 100755
--- a/src/compo/tropomi_no2_co_nc2ioda.py
+++ b/src/compo/tropomi_no2_co_nc2ioda.py
@@ -27,7 +27,7 @@
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string"),
+    ("dateTime", "string"),
 ]
 
 AttrData = {
@@ -58,10 +58,6 @@ def _read(self):
         varname_str = list(self.obsVar.keys())[0]
         print('Processing variable: %s' % (varname_str), flush=1)
         iodavar = self.obsVar[varname_str]
-        # if self.columnType == 'total':
-        #     iodavar = self.obsVar['nitrogendioxide_total_column']
-        # elif self.columnType == 'tropo':
-        #     iodavar = self.obsVar['nitrogendioxide_tropospheric_column']
         self.varDict[iodavar]['valKey'] = iodavar, iconv.OvalName()
         self.varDict[iodavar]['errKey'] = iodavar, iconv.OerrName()
         self.varDict[iodavar]['qcKey'] = iodavar, iconv.OqcName()
@@ -124,11 +120,7 @@ def _read(self):
             AttrData['averaging_kernel_levels'] = np.int32(nlevs)
 
             # scale the avk using AMF ratio and tropopause level for tropo column
-            if self.varname == 'no2':
-                nlocf = len(trop_layer[flg])
-            elif self.varname == 'co':
-                nlocf = len(lats[flg])
-
+            nlocf = len(lats[flg])
             scaleAK = np.ones((nlocf, nlevs), dtype=np.float32)
             if self.varname == 'no2' and self.columnType == 'tropo':
                 # do not loop over nlocs here this makes the execution very slow
@@ -138,7 +130,7 @@ def _read(self):
 
             if first:
                 # add metadata variables
-                self.outdata[('datetime', 'MetaData')] = times[flg]
+                self.outdata[('dateTime', 'MetaData')] = times[flg]
                 self.outdata[('latitude', 'MetaData')] = lats[flg]
                 self.outdata[('longitude', 'MetaData')] = lons[flg]
                 self.outdata[('quality_assurance_value', 'MetaData')] = qa_value[flg]
@@ -157,11 +149,11 @@ def _read(self):
                 if self.varname == 'no2':
                     self.outdata[varname_pr] = ak[nlevs-1, 1] + bk[nlevs-1, 1]*ps[...].ravel()
                 elif self.varname == 'co':
-                    self.outdata[varname_pr] = np.zeros((nlocf, nlevs), dtype=np.float32)
+                    self.outdata[varname_pr] = np.zeros((nlocf), dtype=np.float32)
 
             else:
-                self.outdata[('datetime', 'MetaData')] = np.concatenate((
-                    self.outdata[('datetime', 'MetaData')], times[flg]))
+                self.outdata[('dateTime', 'MetaData')] = np.concatenate((
+                    self.outdata[('dateTime', 'MetaData')], times[flg]))
                 self.outdata[('latitude', 'MetaData')] = np.concatenate((
                     self.outdata[('latitude', 'MetaData')], lats[flg]))
                 self.outdata[('longitude', 'MetaData')] = np.concatenate((
@@ -184,7 +176,7 @@ def _read(self):
                         (self.outdata[varname_pr], ak[nlevs-1, 1] + bk[nlevs-1, 1]*ps[...].ravel()[flg]))
                 elif self.varname == 'co':
                     self.outdata[varname_pr] = np.concatenate(
-                        (self.outdata[varname_pr], np.zeros((nlocf, nlevs), dtype=np.float32)))
+                        (self.outdata[varname_pr], np.zeros((nlocf), dtype=np.float32)))
 
             for ncvar, iodavar in self.obsVar.items():
 
@@ -210,8 +202,8 @@ def _read(self):
 
             first = False
 
-        DimDict['nlocs'] = len(self.outdata[('datetime', 'MetaData')])
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+        DimDict['Location'] = len(self.outdata[('dateTime', 'MetaData')])
+        AttrData['Location'] = np.int32(DimDict['Location'])
 
         for k in range(nlevs):
             varname = 'averaging_kernel_level_'+str(k+1)
@@ -267,33 +259,31 @@ def main():
     args = parser.parse_args()
 
     if args.variable == "co":
-        var_in_name = 'carbonmonoxide'
-        var_out_name = 'carbon_monoxide'
+        var_name = 'carbonmonoxide'
         if args.column == "tropo":
             print('CO is only available for total column, reset column to total', flush=1)
             args.column = 'total'
     elif args.variable == "no2":
-        var_in_name = 'nitrogendioxide'
-        var_out_name = 'nitrogen_dioxide'
+        var_name = 'nitrogendioxide'
 
     if args.column == "tropo":
 
         obsVar = {
-            var_in_name+'_tropospheric_column': var_out_name+'_in_tropospheric_column'
+            var_name+'_tropospheric_column': var_name+'Column'
         }
 
         varDims = {
-            var_out_name+'_in_tropospheric_column': ['nlocs']
+            var_name+'Column': ['Location']
         }
 
     elif args.column == "total":
 
         obsVar = {
-            var_in_name+'_total_column': var_out_name+'_in_total_column'
+            var_name+'_total_column': var_name+'Total'
         }
 
         varDims = {
-            var_out_name+'_in_total_column': ['nlocs']
+            var_name+'Total': ['Location']
         }
 
     # Read in the NO2 data
diff --git a/src/compo/viirs_aod2ioda.py b/src/compo/viirs_aod2ioda.py
index bec5d4e73..a8fe8a343 100644
--- a/src/compo/viirs_aod2ioda.py
+++ b/src/compo/viirs_aod2ioda.py
@@ -26,26 +26,28 @@
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string")
+    ("dateTime", "integer")
 ]
 
+obsvars = ["aerosolOpticalDepth"]
 
-obsvars = {
-    'A': "aerosol_optical_depth",
-}
+# A dictionary of global attributes.  More filled in further down.
+AttrData = {}
+AttrData['ioda_object_type'] = 'AOD at 550nm'
 
-AttrData = {
-    'converter': os.path.basename(__file__),
-    'nvars': np.int32(len(obsvars)),
-}
+# A dictionary of variable dimensions.
+DimDict = {}
 
+# A dictionary of variable names and their dimensions.
+VarDims = {'aerosolOpticalDepth': ['Location']}
 
-DimDict = {
-}
+# Get the group names we use the most.
+metaDataName = iconv.MetaDataName()
+obsValName = iconv.OvalName()
+obsErrName = iconv.OerrName()
+qcName = iconv.OqcName()
 
-VarDims = {
-    'aerosol_optical_depth': ['nlocs', 'nchans'],
-}
+long_missing_value = nc.default_fillvals['i8']
 
 
 class AOD(object):
@@ -61,35 +63,42 @@ def __init__(self, filenames, method, mask, thin):
 
     def _read(self):
         # set up variable names for IODA
-        for ncvar, iodavar in obsvars.items():
-            self.varDict[iodavar]['valKey'] = iodavar, iconv.OvalName()
-            self.varDict[iodavar]['errKey'] = iodavar, iconv.OerrName()
-            self.varDict[iodavar]['qcKey'] = iodavar, iconv.OqcName()
-
-            self.varAttrs[iodavar, iconv.OvalName()]['coordinates'] = 'longitude latitude'
-            self.varAttrs[iodavar, iconv.OerrName()]['coordinates'] = 'longitude latitude'
-            self.varAttrs[iodavar, iconv.OqcName()]['coordinates'] = 'longitude latitude'
-            self.varAttrs[iodavar, iconv.OvalName()]['units'] = '1'
-            self.varAttrs[iodavar, iconv.OerrName()]['units'] = 'unitless'
-            self.varAttrs[iodavar, iconv.OqcName()]['units'] = 'unitless'
+        for iodavar in obsvars:
+            self.varDict[iodavar]['valKey'] = iodavar, obsValName
+            self.varDict[iodavar]['errKey'] = iodavar, obsErrName
+            self.varDict[iodavar]['qcKey'] = iodavar, qcName
+            self.varAttrs[iodavar, obsValName]['coordinates'] = 'longitude latitude'
+            self.varAttrs[iodavar, obsErrName]['coordinates'] = 'longitude latitude'
+            self.varAttrs[iodavar, qcName]['coordinates'] = 'longitude latitude'
+            self.varAttrs[iodavar, obsValName]['_FillValue'] = -9999.
+            self.varAttrs[iodavar, obsErrName]['_FillValue'] = -9999.
+            self.varAttrs[iodavar, qcName]['_FillValue'] = -9999
+            self.varAttrs[iodavar, obsValName]['units'] = '1'
+            self.varAttrs[iodavar, obsErrName]['units'] = '1'
+
+        # Make empty lists for the output vars
+        self.outdata[('latitude', metaDataName)] = []
+        self.outdata[('longitude', metaDataName)] = []
+        self.outdata[('dateTime', metaDataName)] = np.array([], dtype=object)
+        for iodavar in obsvars:
+            self.outdata[self.varDict[iodavar]['valKey']] = []
+            self.outdata[self.varDict[iodavar]['errKey']] = []
+            self.outdata[self.varDict[iodavar]['qcKey']] = []
 
         # loop through input filenamess
-        first = True
         for f in self.filenames:
-            ncd = nc.Dataset(f)
+            ncd = nc.Dataset(f, 'r')
             gatts = {attr: getattr(ncd, attr) for attr in ncd.ncattrs()}
-            base_datetime = gatts["time_coverage_end"]
+            base_datetime = datetime.strptime(gatts["time_coverage_end"], '%Y-%m-%dT%H:%M:%SZ')
             self.satellite = gatts["satellite_name"]
             self.sensor = gatts["instrument_name"]
-            AttrData["observation_type"] = "AOD"
-            AttrData["satellite"] = self.satellite
+            AttrData["platform"] = self.satellite
             AttrData["sensor"] = self.sensor
 
             if AttrData['sensor'] == 'VIIRS':
                 AttrData['sensor'] = "v.viirs-m_npp"
-            if AttrData['satellite'] == 'NPP':
-                AttrData['satellite'] = "suomi_npp"
-            AttrData['date_time_string'] = base_datetime
+            if AttrData['platform'] == 'NPP':
+                AttrData['platform'] = "suomi_npp"
 
             lons = ncd.variables['Longitude'][:].ravel()
             lats = ncd.variables['Latitude'][:].ravel()
@@ -130,36 +139,19 @@ def _read(self):
                 errs[qcpath != 1] = 0.111431 + 0.128699*vals[qcpath != 1]
 
             #  Write out data
-
-            #  Values
-
-            if first:
-                self.outdata[self.varDict[iodavar]['valKey']] = vals
-                self.outdata[self.varDict[iodavar]['errKey']] = errs
-                self.outdata[self.varDict[iodavar]['qcKey']] = qcall
-            else:
-                self.outdata[self.varDict[iodavar]['valKey']] = np.concatenate(
-                    (self.outdata[self.varDict[iodavar]['valKey']], vals))
-                self.outdata[self.varDict[iodavar]['errKey']] = np.concatenate(
-                    (self.outdata[self.varDict[iodavar]['errKey']], errs))
-                self.outdata[self.varDict[iodavar]['qcKey']] = np.concatenate(
-                    (self.outdata[self.varDict[iodavar]['qcKey']], qcall))
-
-            #  Add Meta data
-
-            if first:
-                self.outdata[('latitude', 'MetaData')] = lats
-                self.outdata[('longitude', 'MetaData')] = lons
-                self.outdata[('datetime', 'MetaData')] = obs_time
-            else:
-                self.outdata[('latitude', 'MetaData')] = np.concatenate((self.outdata[('latitude', 'MetaData')], lats))
-                self.outdata[('longitude', 'MetaData')] = np.concatenate((self.outdata[('longitude', 'MetaData')], lons))
-                self.outdata[('datetime', 'MetaData')] = np.concatenate((self.outdata[('datetime', 'MetaData')], obs_time))
-
-            first = False
-
-        DimDict['nlocs'] = len(self.outdata[('latitude', 'MetaData')])
-        DimDict['nchans'] = np.array([4])
+            self.outdata[('latitude', metaDataName)] = np.append(self.outdata[('latitude', metaDataName)], np.array(lats, dtype=np.float32))
+            self.outdata[('longitude', metaDataName)] = np.append(self.outdata[('longitude', metaDataName)], np.array(lons, dtype=np.float32))
+            self.outdata[('dateTime', metaDataName)] = np.append(self.outdata[('dateTime', metaDataName)], np.array(obs_time, dtype=object))
+
+            for iodavar in obsvars:
+                self.outdata[self.varDict[iodavar]['valKey']] = np.append(
+                    self.outdata[self.varDict[iodavar]['valKey']], np.array(vals, dtype=np.float32))
+                self.outdata[self.varDict[iodavar]['errKey']] = np.append(
+                    self.outdata[self.varDict[iodavar]['errKey']], np.array(errs, dtype=np.float32))
+                self.outdata[self.varDict[iodavar]['qcKey']] = np.append(
+                    self.outdata[self.varDict[iodavar]['qcKey']], np.array(qcall, dtype=np.int32))
+
+        DimDict['Location'] = len(self.outdata[('latitude', metaDataName)])
 
 
 def main():
diff --git a/src/conventional/CMakeLists.txt b/src/conventional/CMakeLists.txt
index 6737e7638..55f4c925c 100644
--- a/src/conventional/CMakeLists.txt
+++ b/src/conventional/CMakeLists.txt
@@ -1,9 +1,11 @@
 list(APPEND programs
   amv_ssec_ascii2ioda.py
   amdar_bufr2ioda.py
+  amv_ssec_ascii2ioda.py
   buoy_bufr2ioda.py
   metar_csv2ioda.py
-  decode_bufr_LDM_raob.py
+  sonde_bufr2ioda.py
+  sonde_tac2ioda.py
   ship_bufr2ioda.py
   sonde_tac2ioda.py
   synop_bufr2ioda.py
diff --git a/src/conventional/amdar_bufr2ioda.py b/src/conventional/amdar_bufr2ioda.py
index b648438a7..d49a4118f 100644
--- a/src/conventional/amdar_bufr2ioda.py
+++ b/src/conventional/amdar_bufr2ioda.py
@@ -28,17 +28,15 @@
 os.environ["TZ"] = "UTC"
 
 locationKeyList = [
-    ("aircraft_id", "string", ""),
-    ("aircraft_flightNum", "string", ""),
-    ("aircraft_tailNum", "string", ""),
-    ("obs_sequenceNum", "integer", ""),
-    ("originationAirport", "string", ""),
-    ("destinationAirport", "string", ""),
-    ("flight_phase", "integer", ""),
-    ("roll_angle", "float", "degrees"),
-    ("roll_angle_quality", "integer", ""),
-    ("aircraft_speed", "float", "m s-1"),
-    ("aircraft_heading", "integer", "degrees"),
+    ("aircraftIdentifier", "string", ""),
+    ("aircraftFlightNumber", "string", ""),
+    ("aircraftTailNumber", "string", ""),
+    ("observationSequenceNum", "integer", ""),
+    ("aircraftFlightPhase", "integer", ""),
+    ("aircraftRollAngle", "float", "degrees"),
+    ("aircraftRollAngleQuality", "integer", ""),
+    ("aircraftVelocity", "float", "m s-1"),
+    ("aircraftHeading", "integer", "degrees"),
     ("latitude", "float", "degrees_north"),
     ("longitude", "float", "degrees_east"),
     ("height", "float", "m"),
@@ -47,17 +45,15 @@
 meta_keys = [m_item[0] for m_item in locationKeyList]
 
 metaDataKeyList = {
-    'aircraft_id': ['aircraftRegistrationNumberOrOtherIdentification'],
-    'aircraft_flightNum': ['aircraftFlightNumber'],
-    'aircraft_tailNum': ['aircraftTailNumber'],
-    'obs_sequenceNum': ['observationSequenceNumber'],
-    'originationAirport': ['originationAirport'],
-    'destinationAirport': ['destinationAirport'],
-    'flight_phase': ['detailedPhaseOfFlight'],
-    'roll_angle': ['aircraftRollAngle'],
-    'roll_angle_quality': ['aircraftRollAngleQuality'],
-    'aircraft_speed': ['aircraftTrueAirspeed'],
-    'aircraft_heading': ['aircraftTrueHeading'],
+    'aircraftIdentifier': ['aircraftRegistrationNumberOrOtherIdentification'],
+    'aircraftFlightNumber': ['aircraftFlightNumber'],
+    'aircraftTailNumber': ['aircraftTailNumber'],
+    'observationSequenceNum': ['observationSequenceNumber'],
+    'aircraftFlightPhase': ['detailedPhaseOfFlight'],
+    'aircraftRollAngle': ['aircraftRollAngle'],
+    'aircraftRollAngleQuality': ['aircraftRollAngleQuality'],
+    'aircraftVelocity': ['aircraftTrueAirspeed'],
+    'aircraftHeading': ['aircraftTrueHeading'],
     'latitude': ['latitude'],
     'longitude': ['longitude'],
     'height': ['Constructed', 'globalNavigationSatelliteSystemAltitude', 'height', 'flightLevel'],
@@ -70,15 +66,15 @@
 raw_obsvars = ['airTemperature', 'mixingRatio', 'windDirection', 'windSpeed']
 
 # The outgoing IODA variables (ObsValues), their units, and assigned constant ObsError.
-obsvars = ['air_temperature', 'specific_humidity', 'eastward_wind', 'northward_wind']
+obsvars = ['airTemperature', 'specificHumidity', 'windEastward', 'windNorthward']
 obsvars_units = ['K', 'kg kg-1', 'm s-1', 'm s-1']
 obserrlist = [1.2, 0.75E-3, 1.7, 1.7]
 
 VarDims = {
-    'air_temperature': ['nlocs'],
-    'specific_humidity': ['nlocs'],
-    'eastward_wind': ['nlocs'],
-    'northward_wind': ['nlocs'],
+    'airTemperature': ['Location'],
+    'specificHumidity': ['Location'],
+    'windEastward': ['Location'],
+    'windNorthward': ['Location'],
 }
 
 metaDataName = iconv.MetaDataName()
@@ -91,7 +87,7 @@
     'ioda_version': 2,
     'description': 'Aircraft observations converted from BUFR',
     'source': 'LDM at NCAR-RAL',
-    'source_files': ''
+    'sourceFiles': ''
 }
 
 DimDict = {
@@ -138,12 +134,12 @@ def main(file_names, output_file):
 
     for fname in file_names:
         logging.debug("Reading file: " + fname)
-        AttrData['source_files'] += ", " + fname
+        AttrData['sourceFiles'] += ", " + fname
 
         data, count, start_pos = read_file(fname, count, start_pos, data)
 
-    AttrData['source_files'] = AttrData['source_files'][2:]
-    logging.debug("All source files: " + AttrData['source_files'])
+    AttrData['sourceFiles'] = AttrData['sourceFiles'][2:]
+    logging.debug("All source files: " + AttrData['sourceFiles'])
 
     if not data:
         logging.critical("ABORT: no message data was captured, stopping execution.")
@@ -151,8 +147,7 @@ def main(file_names, output_file):
     logging.info("--- {:9.4f} BUFR read seconds ---".format(time.time() - start_time))
 
     nlocs = len(data['dateTime'])
-    DimDict = {'nlocs': nlocs}
-    AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+    DimDict = {'Location': nlocs}
 
     # Set coordinates and units of the ObsValues.
     for n, iodavar in enumerate(obsvars):
@@ -164,12 +159,12 @@ def main(file_names, output_file):
         varAttrs[iodavar, qcName]['coordinates'] = 'longitude latitude'
         varAttrs[iodavar, obsValName]['units'] = obsvars_units[n]
         varAttrs[iodavar, obsErrName]['units'] = obsvars_units[n]
-        varAttrs[iodavar, qcName]['units'] = 'unitless'
 
     # Set units of the MetaData variables and all _FillValues.
     for key in meta_keys:
         dtypestr = locationKeyList[meta_keys.index(key)][1]
-        varAttrs[(key, metaDataName)]['units'] = locationKeyList[meta_keys.index(key)][2]
+        if locationKeyList[meta_keys.index(key)][2]:
+            varAttrs[(key, metaDataName)]['units'] = locationKeyList[meta_keys.index(key)][2]
         varAttrs[(key, metaDataName)]['_FillValue'] = missing_vals[dtypestr]
         obs_data[(key, metaDataName)] = np.array(data[key], dtype=dtypes[dtypestr])
 
@@ -481,10 +476,10 @@ def read_bufr_message(f, count, start_pos, data):
             spfh[n] = mixing_ratio / (1.0 + mixing_ratio)
 
     # Move everything into the final data dictionary, including metadata.
-    data['eastward_wind'] = np.append(data['eastward_wind'], uwnd)
-    data['northward_wind'] = np.append(data['northward_wind'], vwnd)
-    data['specific_humidity'] = np.append(data['specific_humidity'], spfh)
-    data['air_temperature'] = np.append(data['air_temperature'], vals['airTemperature'])
+    data['windEastward'] = np.append(data['windEastward'], uwnd)
+    data['windNorthward'] = np.append(data['windNorthward'], vwnd)
+    data['specificHumidity'] = np.append(data['specificHumidity'], spfh)
+    data['airTemperature'] = np.append(data['airTemperature'], vals['airTemperature'])
     for key in meta_keys:
         data[key] = np.append(data[key], meta_data[key])
 
diff --git a/src/conventional/amv_ssec_ascii2ioda.py b/src/conventional/amv_ssec_ascii2ioda.py
index 70a1722b6..87c21658a 100644
--- a/src/conventional/amv_ssec_ascii2ioda.py
+++ b/src/conventional/amv_ssec_ascii2ioda.py
@@ -23,21 +23,28 @@
 
 os.environ["TZ"] = "UTC"
 
-varDict = {'eastward_wind': ['eastward_wind', 'm s-1'],
-           'northward_wind': ['northward_wind', 'm s-1']}
+varDict = {'windEastward': ['windEastward', 'm s-1'],
+           'windNorthward': ['windNorthward', 'm s-1']}
 
 locationKeyList = [("latitude", "float", "degrees_north"),
                    ("longitude", "float", "degrees_east"),
                    ("dateTime", "long", "seconds since 1970-01-01T00:00:00Z"),
-                   ("air_pressure", "float", "Pa"),
+                   ("pressure", "float", "Pa"),
                    ("sensorCentralFrequency", "float", "Hz"),
                    ("sensorZenithAngle", "float", "degrees"),
                    ("windTrackingCorrelation", "float", "1"),
                    ("windHeightAssignMethod", "integer", ""),
-                   ("satelliteID", "integer", "")]
+                   ("satelliteIdentifier", "integer", "")]
 
 meta_keys = [m_item[0] for m_item in locationKeyList]
 
+GlobalAttrs = {
+    'converter': os.path.basename(__file__),
+    'ioda_version': 2,
+    'description': 'Satellite atmospheric motion vectors (AMV)',
+    'source': 'SSEC (ftp)'
+}
+
 iso8601_string = locationKeyList[meta_keys.index('dateTime')][2]
 epoch = datetime.fromisoformat(iso8601_string[14:-1])
 
@@ -118,12 +125,12 @@ def main(file_names, output_file, datetimeRef):
 
     nlocs = len(data['dateTime'])
     logging.info(f" found a total of {nlocs} observations")
-    DimDict = {'nlocs': nlocs}
+    DimDict = {'Location': nlocs}
 
     varDims = {}
     for key in varDict.keys():
         variable = varDict[key][0]
-        varDims[variable] = ['nlocs']
+        varDims[variable] = ['Location']
 
     varAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
 
@@ -184,20 +191,15 @@ def read_file(file_name, data):
 
         for row in reader:
             try:
-                year = int(row['day'][0:4])
-                month = int(row['day'][4:6])
-                day = int(row['day'][6:])
-                hour = int(row['hms'][0:2])
-                minute = int(row['hms'][2:])
-                second = 0
-                dtg = datetime(year, month, day, hour, minute, second)
+                dtg = datetime.strptime(f"{row['day']} {row['hms']}", '%Y%m%d %H%M')
                 time_offset = np.int64(round((dtg - epoch).total_seconds()))
                 local_data['dateTime'] = np.append(local_data['dateTime'], time_offset)
                 local_data['longitude'] = np.append(local_data['longitude'], float(row['lon']))
                 local_data['latitude'] = np.append(local_data['latitude'], float(row['lat']))
 
                 pres = float(row['pre'])*100.
-                local_data['air_pressure'] = np.append(local_data['air_pressure'], pres)
+                local_data['pressure'] = np.append(local_data['pressure'], pres)
+
                 wdir = float(row['dir'])*1.0
                 wspd = float(row['spd'])*1.0
                 if (wdir >= 0 and wdir <= 360 and wspd >= 0 and wspd < 300):
@@ -206,8 +208,8 @@ def read_file(file_name, data):
                     uwnd = float_missing_value
                     vwnd = float_missing_value
 
-                local_data['eastward_wind'] = np.append(local_data['eastward_wind'], uwnd)
-                local_data['northward_wind'] = np.append(local_data['northward_wind'], vwnd)
+                local_data['windEastward'] = np.append(local_data['windEastward'], uwnd)
+                local_data['windNorthward'] = np.append(local_data['windNorthward'], vwnd)
 
                 if row['type'] in known_freq.keys():
                     freq = known_freq[row['type']]
@@ -221,8 +223,8 @@ def read_file(file_name, data):
                 else:
                     satid = int_missing_value
                     unk_sat.append(row['sat'])
-                local_data['satelliteID'] = np.append(local_data['satelliteID'], satid)
 
+                local_data['satelliteIdentifier'] = np.append(local_data['satelliteIdentifier'], satid)
                 local_data['sensorZenithAngle'] = np.append(local_data['sensorZenithAngle'], float(row['rff']))
                 local_data['windTrackingCorrelation'] = np.append(local_data['windTrackingCorrelation'], float(row['qi']))
                 local_data['windHeightAssignMethod'] = np.append(local_data['windHeightAssignMethod'], int(row['int']))
@@ -233,8 +235,8 @@ def read_file(file_name, data):
                 keyerr = True
 
                 if (e.args[0] == 'dir') or (e.args[0] == 'spd'):
-                    local_data['eastward_wind'] = np.append(local_data['eastward_wind'], float_missing_value)
-                    local_data['northward_wind'] = np.append(local_data['northward_wind'], float_missing_value)
+                    local_data['windEastward'] = np.append(local_data['windEastward'], float_missing_value)
+                    local_data['windNorthward'] = np.append(local_data['windNorthward'], float_missing_value)
                 else:
                     local_data[known_var[e.args[0]][0]] = np.append(local_data[known_var[e.args[0]][0]], known_var[e.args[0]][1])
 
@@ -279,7 +281,6 @@ def read_file(file_name, data):
 
     parser.set_defaults(debug=False)
     parser.set_defaults(verbose=False)
-    parser.set_defaults(datetimeReference=" ")
     optional = parser.add_argument_group(title='optional arguments')
     optional.add_argument('--debug', action='store_true',
                           help='enable debug messages')
diff --git a/src/conventional/buoy_bufr2ioda.py b/src/conventional/buoy_bufr2ioda.py
index 1d51f4786..85c777729 100644
--- a/src/conventional/buoy_bufr2ioda.py
+++ b/src/conventional/buoy_bufr2ioda.py
@@ -28,22 +28,22 @@
 os.environ["TZ"] = "UTC"
 
 locationKeyList = [
-    ("station_id", "integer", ""),
-    ("station_name", "string", ""),
+    ("stationIdentification", "integer", ""),
+    ("stationLongName", "string", ""),
     ("latitude", "float", "degrees_north"),
     ("longitude", "float", "degrees_east"),
-    ("station_elevation", "float", "m"),
+    ("stationElevation", "float", "m"),
     ("height", "float", "m"),
     ("dateTime", "long", "seconds since 1970-01-01T00:00:00Z")
 ]
 meta_keys = [m_item[0] for m_item in locationKeyList]
 
 metaDataKeyList = {
-    'station_id': ['marineObservingPlatformIdentifier'],
-    'station_name': ['stationOrSiteName'],
+    'stationIdentification': ['marineObservingPlatformIdentifier'],
+    'stationLongName': ['stationOrSiteName'],
     'latitude': ['latitude'],
     'longitude': ['longitude'],
-    'station_elevation': ['heightOfStationGroundAboveMeanSeaLevel'],
+    'stationElevation': ['heightOfStationGroundAboveMeanSeaLevel'],
     'height': ['heightOfSensorAboveWaterSurface',
                'heightOfBarometerAboveMeanSeaLevel'],
     'dateTime': ['Constructed']
@@ -61,22 +61,22 @@
                'pressureReducedToMeanSeaLevel']
 
 # The outgoing IODA variables (ObsValues), their units, and assigned constant ObsError.
-obsvars = ['air_temperature',
-           'specific_humidity',
-           'sea_surface_temperature',
-           'eastward_wind',
-           'northward_wind',
-           'surface_pressure']
+obsvars = ['airTemperature',
+           'specificHumidity',
+           'seaSurfaceTemperature',
+           'windEastward',
+           'windNorthward',
+           'stationPressure']
 obsvars_units = ['K', 'kg kg-1', 'K', 'm s-1', 'm s-1', 'Pa']
 obserrlist = [1.2, 0.75E-3, 2.2, 1.7, 1.7, 120.0]
 
 VarDims = {
-    'air_temperature': ['nlocs'],
-    'specific_humidity': ['nlocs'],
-    'sea_surface_temperature': ['nlocs'],
-    'eastward_wind': ['nlocs'],
-    'northward_wind': ['nlocs'],
-    'surface_pressure': ['nlocs']
+    'airTemperature': ['Location'],
+    'specificHumidity': ['Location'],
+    'seaSurfaceTemperature': ['Location'],
+    'windEastward': ['Location'],
+    'windNorthward': ['Location'],
+    'stationPressure': ['Location']
 }
 
 metaDataName = iconv.MetaDataName()
@@ -89,7 +89,7 @@
     'ioda_version': 2,
     'description': 'Surface (Ship) observations converted from BUFR',
     'source': 'LDM at NCAR-RAL',
-    'source_files': ''
+    'sourceFiles': ''
 }
 
 DimDict = {
@@ -136,12 +136,12 @@ def main(file_names, output_file):
 
     for fname in file_names:
         logging.debug("Reading file: " + fname)
-        AttrData['source_files'] += ", " + fname
+        AttrData['sourceFiles'] += ", " + fname
 
         data, count, start_pos = read_file(fname, count, start_pos, data)
 
-    AttrData['source_files'] = AttrData['source_files'][2:]
-    logging.debug("All source files: " + AttrData['source_files'])
+    AttrData['sourceFiles'] = AttrData['sourceFiles'][2:]
+    logging.debug("All source files: " + AttrData['sourceFiles'])
 
     if not data:
         logging.critical("ABORT: no message data was captured, stopping execution.")
@@ -149,8 +149,7 @@ def main(file_names, output_file):
     logging.info("--- {:9.4f} BUFR read seconds ---".format(time.time() - start_time))
 
     nlocs = len(data['dateTime'])
-    DimDict = {'nlocs': nlocs}
-    AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+    DimDict = {'Location': nlocs}
 
     # Set coordinates and units of the ObsValues.
     for n, iodavar in enumerate(obsvars):
@@ -162,12 +161,12 @@ def main(file_names, output_file):
         varAttrs[iodavar, qcName]['coordinates'] = 'longitude latitude'
         varAttrs[iodavar, obsValName]['units'] = obsvars_units[n]
         varAttrs[iodavar, obsErrName]['units'] = obsvars_units[n]
-        varAttrs[iodavar, qcName]['units'] = 'unitless'
 
     # Set units of the MetaData variables and all _FillValues.
     for key in meta_keys:
         dtypestr = locationKeyList[meta_keys.index(key)][1]
-        varAttrs[(key, metaDataName)]['units'] = locationKeyList[meta_keys.index(key)][2]
+        if locationKeyList[meta_keys.index(key)][2]:
+            varAttrs[(key, metaDataName)]['units'] = locationKeyList[meta_keys.index(key)][2]
         varAttrs[(key, metaDataName)]['_FillValue'] = missing_vals[dtypestr]
         obs_data[(key, metaDataName)] = np.array(data[key], dtype=dtypes[dtypestr])
 
@@ -436,12 +435,12 @@ def read_bufr_message(f, count, start_pos, data):
     mask_height = np.logical_or(meta_data['height'] < -425, meta_data['height'] > 800)
     meta_data['height'][mask_height] = float_missing_value
 
-    # If the height of the observation (sensor) is missing, try to fill it with station_elevation.
-    for n, elev in enumerate(meta_data['station_elevation']):
+    # If the height of the observation (sensor) is missing, try to fill it with stationElevation.
+    for n, elev in enumerate(meta_data['stationElevation']):
         if (elev > -425 and elev < 800 and np.abs(meta_data['height'][n]-elev) > 50):
             meta_data['height'][n] = elev + 2
         else:
-            meta_data['station_elevation'][n] = 0.5
+            meta_data['stationElevation'][n] = 0.5
             meta_data['height'][n] = 2.0
 
     # Next, get the raw observed weather variables we want.
@@ -495,12 +494,12 @@ def read_bufr_message(f, count, start_pos, data):
             spfh[n] = met_utils.specific_humidity(dewpoint, psfc)
 
     # Move everything into the final data dictionary, including metadata.
-    data['eastward_wind'] = np.append(data['eastward_wind'], uwnd)
-    data['northward_wind'] = np.append(data['northward_wind'], vwnd)
-    data['specific_humidity'] = np.append(data['specific_humidity'], spfh)
-    data['air_temperature'] = np.append(data['air_temperature'], vals['airTemperature'])
-    data['surface_pressure'] = np.append(data['surface_pressure'], vals['nonCoordinatePressure'])
-    data['sea_surface_temperature'] = np.append(data['sea_surface_temperature'], vals['seaSurfaceTemperature'])
+    data['windEastward'] = np.append(data['windEastward'], uwnd)
+    data['windNorthward'] = np.append(data['windNorthward'], vwnd)
+    data['specificHumidity'] = np.append(data['specificHumidity'], spfh)
+    data['airTemperature'] = np.append(data['airTemperature'], vals['airTemperature'])
+    data['stationPressure'] = np.append(data['stationPressure'], vals['nonCoordinatePressure'])
+    data['seaSurfaceTemperature'] = np.append(data['seaSurfaceTemperature'], vals['seaSurfaceTemperature'])
     for key in meta_keys:
         data[key] = np.append(data[key], meta_data[key])
 
diff --git a/src/conventional/metar_csv2ioda.py b/src/conventional/metar_csv2ioda.py
old mode 100644
new mode 100755
index b6228a97c..055ce1ad9
--- a/src/conventional/metar_csv2ioda.py
+++ b/src/conventional/metar_csv2ioda.py
@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 
 #
-# (C) Copyright 2020, 2021 UCAR
+# (C) Copyright 2020-2022 UCAR
 #
 # This software is licensed under the terms of the Apache Licence Version 2.0
 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
@@ -20,6 +20,7 @@
 from pathlib import Path
 import csv
 import netCDF4
+import logging
 
 IODA_CONV_PATH = Path(__file__).parent/"@SCRIPT_LIB_PATH@"
 if not IODA_CONV_PATH.is_dir():
@@ -30,46 +31,62 @@
 from collections import defaultdict, OrderedDict
 from orddicts import DefaultOrderedDict
 import meteo_utils
-from def_jedi_utils import concat_obs_dict
 
 os.environ["TZ"] = "UTC"
 
-locationKeyList = [
-    ("station_id", "string"),
-    ("latitude", "float"),
-    ("longitude", "float"),
-    ("station_elevation", "float"),
-    ("height", "float"),
-    ("dateTime", "integer"),
-]
-
-obsvars = {
-    'ob_temp': 'air_temperature',
-    'ob_spfh': 'specific_humidity',
-    'ob_psfc': 'surface_pressure',
-    'ob_uwnd': 'eastward_wind',
-    'ob_vwnd': 'northward_wind',
-}
-
+locationKeyList = [("stationICAO", "string", ""),
+                   ("latitude", "float", "degrees_north"),
+                   ("longitude", "float", "degrees_east"),
+                   ("stationElevation", "float", "m"),
+                   ("height", "float", "m"),
+                   ("dateTime", "long", "seconds since 1970-01-01T00:00:00Z")]
+meta_keys = [m_item[0] for m_item in locationKeyList]
+
+obsvars = ['airTemperature',
+           'specificHumidity',
+           'stationPressure',
+           'windEastward',
+           'windNorthward']
 obsvars_units = ['K', 'kg kg-1', 'Pa', 'm s-1', 'm s-1']
-
-VarDims = {
-    'ob_temp': ['nlocs'],
-    'ob_spfh': ['nlocs'],
-    'ob_psfc': ['nlocs'],
-    'ob_uwnd': ['nlocs'],
-    'ob_vwnd': ['nlocs'],
-}
-
-AttrData = {
-    'converter': os.path.basename(__file__),
-    'ioda_version': 2,
-    'description': 'METAR surface observation data converted from CSV',
-    'source': 'NCAR-RAL METAR database (gthompsn)',
-}
-
-DimDict = {
-}
+obserrlist = [1.2, 0.75E-3, 120.0, 1.7, 1.7]
+
+VarDims = {'airTemperature': ['Location'],
+           'specificHumidity': ['Location'],
+           'stationPressure': ['Location'],
+           'windEastward': ['Location'],
+           'windNorthward': ['Location']}
+
+AttrData = {'converter': os.path.basename(__file__),
+            'ioda_object_version': 2,
+            'description': 'METAR surface observation data converted from CSV',
+            'source': 'NCAR-RAL METAR database (gthompsn)'}
+
+DimDict = {}
+
+metaDataName = iconv.MetaDataName()
+obsValName = iconv.OvalName()
+obsErrName = iconv.OerrName()
+qcName = iconv.OqcName()
+
+float_missing_value = netCDF4.default_fillvals['f4']
+int_missing_value = netCDF4.default_fillvals['i4']
+double_missing_value = netCDF4.default_fillvals['f8']
+long_missing_value = netCDF4.default_fillvals['i8']
+string_missing_value = '_'
+
+iso8601_string = locationKeyList[meta_keys.index('dateTime')][2]
+epoch = datetime.fromisoformat(iso8601_string[14:-1])
+
+missing_vals = {'string': string_missing_value,
+                'integer': int_missing_value,
+                'long': long_missing_value,
+                'float': float_missing_value,
+                'double': double_missing_value}
+dtypes = {'string': object,
+          'integer': np.int32,
+          'long': np.int64,
+          'float': np.float32,
+          'double': np.float64}
 
 
 class reformatMetar(object):
@@ -79,12 +96,11 @@ def __init__(self, filename, date):
         self.filename = filename
         self.date = date
         self.meteo_utils = meteo_utils.meteo_utils()
-        self.float_fill = netCDF4.default_fillvals['f4']
         self.varDict = defaultdict(lambda: DefaultOrderedDict(dict))
         self.outdata = defaultdict(lambda: DefaultOrderedDict(OrderedDict))
         self.varAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
 
-        AttrData['datetime_reference'] = date.strftime("%Y-%m-%dT%H:%M:%SZ")
+        AttrData['datetimeReference'] = date.strftime("%Y-%m-%dT%H:%M:%SZ_PT1H")
 
         # Read in CSV-formatted file of METAR data
         self._rd_metars()
@@ -93,51 +109,45 @@ def __init__(self, filename, date):
 
     def _rd_metars(self):
 
-        n = 0
-        for iodavar in obsvars.values():
-            self.varDict[iodavar]['valKey'] = iodavar, iconv.OvalName()
-            self.varDict[iodavar]['errKey'] = iodavar, iconv.OerrName()
-            self.varDict[iodavar]['qcKey'] = iodavar, iconv.OqcName()
-            self.varAttrs[iodavar, iconv.OvalName()]['coordinates'] = 'longitude latitude'
-            self.varAttrs[iodavar, iconv.OerrName()]['coordinates'] = 'longitude latitude'
-            self.varAttrs[iodavar, iconv.OqcName()]['coordinates'] = 'longitude latitude'
-            self.varAttrs[iodavar, iconv.OvalName()]['units'] = obsvars_units[n]
-            self.varAttrs[iodavar, iconv.OerrName()]['units'] = obsvars_units[n]
-            self.varAttrs[iodavar, iconv.OqcName()]['units'] = 'unitless'
-            n += 1
-
-        # Set units of some MetaData variables
-        self.varAttrs['station_elevation', 'MetaData']['units'] = 'm'
-        self.varAttrs['height', 'MetaData']['units'] = 'm'
-        self.varAttrs['dateTime', 'MetaData']['units'] = 'seconds since 1970-01-01T00:00:00Z'
+        # Set units of the MetaData variables and all _FillValues.
+        for key in meta_keys:
+            dtypestr = locationKeyList[meta_keys.index(key)][1]
+            self.varAttrs[(key, metaDataName)]['_FillValue'] = missing_vals[dtypestr]
+            this_units = locationKeyList[meta_keys.index(key)][2]
+            if this_units:
+                self.varAttrs[(key, metaDataName)]['units'] = this_units
+
+        # Set coordinates and units of the ObsValues.
+        for n, iodavar in enumerate(obsvars):
+            self.varDict[iodavar]['valKey'] = iodavar, obsValName
+            self.varDict[iodavar]['errKey'] = iodavar, obsErrName
+            self.varDict[iodavar]['qcKey'] = iodavar, qcName
+            self.varAttrs[iodavar, obsValName]['coordinates'] = 'longitude latitude'
+            self.varAttrs[iodavar, obsErrName]['coordinates'] = 'longitude latitude'
+            self.varAttrs[iodavar, qcName]['coordinates'] = 'longitude latitude'
+            self.varAttrs[iodavar, obsValName]['units'] = obsvars_units[n]
+            self.varAttrs[iodavar, obsErrName]['units'] = obsvars_units[n]
 
         # data is the dictionary of incoming observation (METAR) data
         data = {}
-
-        data['ob_icao'] = []
-        data['ob_lat'] = []
-        data['ob_lon'] = []
-        data['ob_time'] = []
-        data['ob_datetime'] = []
-        data['ob_elev'] = []
-        data['ob_hght'] = []
-        data['ob_psfc'] = []
-        data['ob_temp'] = []
-        data['ob_spfh'] = []
-        data['ob_uwnd'] = []
-        data['ob_vwnd'] = []
+        for key in meta_keys:
+            data[key] = []
+        for key in obsvars:
+            data[key] = []
 
         '''
         Read in the METARs data
-        Header contains: Unix_time,DateString,ICAO,Latitude,Longitude,Elev,Temp,Dewp,Wdir,Wspd,Wgst,Vis,\
-        Pcp,Pcp3h,Pcp6h,Pcp24h,QcFlag,WxString,WxCode,Altimeter,Cvg1,Bas1,Cvg2,Bas2,Cvg3,Bas3,Length,Raw
+        Header contains: Unix_time,DateString,ICAO,Latitude,Longitude,Elev,Temp,Dewp,Wdir,Wspd,Wgst,Vis,  # noqa
+        Pcp,Pcp3h,Pcp6h,Pcp24h,QcFlag,WxString,WxCode,Altimeter,Cvg1,Bas1,Cvg2,Bas2,Cvg3,Bas3,Length,Raw  # noqa
         '''
 
         # open file in read mode
         with open(self.filename, 'r') as fh:
+            missing = float_missing_value
             # pass the file object to reader() to get the reader object
             csv_dict_reader = csv.DictReader(fh)
             column_names = csv_dict_reader.fieldnames
+            logging.info("Header, columns = " + ", ".join(column_names))
             # Iterate over each row in the csv using reader object
             for row in csv_dict_reader:
                 # row variable is a list that represents a row in csv
@@ -152,99 +162,87 @@ def _rd_metars(self):
                     lon = float(row['Longitude'])
                     elev = float(row['Elev'])
                     if (elev < -999 or elev > 8450):
-                        elev = self.float_fill
-                        hght = self.float_fill
-                    else:
-                        hght = elev + 2.0           # Height of observation assumed 2 meters above station elevation
+                        elev = missing
+                        hght = missing
+                    else:         # Height of observation assumed 2 meters above station elevation
+                        hght = elev + 2.0
                 except (csv.Error, ValueError):
                     continue
                 try:
                     temp = float(row['Temp']) + self.meteo_utils.C_2_K
                 except (csv.Error, ValueError):
-                    temp = self.float_fill
+                    temp = missing
                 try:
                     dewp = float(row['Dewp']) + self.meteo_utils.C_2_K
                 except (csv.Error, ValueError):
-                    dewp = self.float_fill
+                    dewp = missing
                 try:
                     wdir = float(row['Wdir'])
                 except (csv.Error, ValueError):
-                    wdir = self.float_fill
+                    wdir = missing
                 try:
                     wspd = float(row['Wspd']) * self.meteo_utils.KTS_2_MS
                 except (csv.Error, ValueError):
-                    wspd = self.float_fill
+                    wspd = missing
 
-                if ((wdir is not self.float_fill) and (wspd is not self.float_fill)):
+                if ((wdir != missing) and (wspd != missing)):
                     if (wdir == 0 and wspd == 0):
                         uwnd = 0.0
                         vwnd = 0.0
                     elif (wdir > 0 and wdir <= 360 and wspd > 0):
                         uwnd, vwnd = self.meteo_utils.dir_speed_2_uv(wdir, wspd)
                     else:
-                        uwnd = self.float_fill
-                        vwnd = self.float_fill
+                        uwnd = missing
+                        vwnd = missing
                 else:
-                    uwnd = self.float_fill
-                    vwnd = self.float_fill
+                    uwnd = missing
+                    vwnd = missing
 
                 try:
                     altim = float(row['Altimeter'])
                     psfc = self.meteo_utils.altim_2_sfcPressure(altim, elev)
                 except (csv.Error, ValueError):
-                    altim = self.float_fill
-                    psfc = self.float_fill
+                    altim = missing
+                    psfc = missing
 
-                if ((psfc is not self.float_fill) and (temp is not self.float_fill) and (dewp is not self.float_fill)):
+                if ((psfc != missing) and (temp != missing) and (dewp != missing)):
                     spfh = self.meteo_utils.specific_humidity(dewp, psfc)
                 else:
-                    spfh = self.float_fill
-
-                data['ob_icao'].append(icao)
-                data['ob_datetime'].append(utime)
-                data['ob_lat'].append(lat)
-                data['ob_lon'].append(lon)
-                data['ob_elev'].append(elev)
-                data['ob_hght'].append(hght)
-                data['ob_psfc'].append(psfc)
-                data['ob_temp'].append(temp)
-                data['ob_spfh'].append(spfh)
-                data['ob_uwnd'].append(uwnd)
-                data['ob_vwnd'].append(vwnd)
+                    spfh = missing
+
+                data['stationICAO'].append(icao)
+                data['dateTime'].append(utime)
+                data['latitude'].append(lat)
+                data['longitude'].append(lon)
+                data['stationElevation'].append(elev)
+                data['height'].append(hght)
+                data['stationPressure'].append(psfc)
+                data['airTemperature'].append(temp)
+                data['specificHumidity'].append(spfh)
+                data['windEastward'].append(uwnd)
+                data['windNorthward'].append(vwnd)
 
         fh.close()
 
-        nlocs = len(data['ob_datetime'])
-
-        self.outdata[('station_id', 'MetaData')] = np.array(data['ob_icao'], dtype=object)
-        self.outdata[('dateTime', 'MetaData')] = np.array(data['ob_datetime'], dtype=np.int64)
-        self.outdata[('latitude', 'MetaData')] = np.array(data['ob_lat'], dtype=np.float32)
-        self.outdata[('longitude', 'MetaData')] = np.array(data['ob_lon'], dtype=np.float32)
-        self.outdata[('station_elevation', 'MetaData')] = np.array(data['ob_elev'], dtype=np.float32)
-        self.outdata[('height', 'MetaData')] = np.array(data['ob_hght'], dtype=np.float32)
-        iodavar = 'surface_pressure'
-        self.outdata[(iodavar, iconv.OvalName())] = np.array(data['ob_psfc'], dtype=np.float32)
-        self.outdata[(iodavar, iconv.OerrName())] = np.full((nlocs), 200.0, dtype=np.float32)
-        self.outdata[(iodavar, iconv.OqcName())] = np.full((nlocs), 2, dtype=np.int32)
-        iodavar = 'air_temperature'
-        self.outdata[(iodavar, iconv.OvalName())] = np.array(data['ob_temp'], dtype=np.float32)
-        self.outdata[(iodavar, iconv.OerrName())] = np.full((nlocs), 0.2, dtype=np.float32)
-        self.outdata[(iodavar, iconv.OqcName())] = np.full((nlocs), 2, dtype=np.int32)
-        iodavar = 'specific_humidity'
-        self.outdata[(iodavar, iconv.OvalName())] = np.array(data['ob_spfh'], dtype=np.float32)
-        self.outdata[(iodavar, iconv.OerrName())] = np.full((nlocs), 0.75E-3, dtype=np.float32)
-        self.outdata[(iodavar, iconv.OqcName())] = np.full((nlocs), 2, dtype=np.int32)
-        iodavar = 'eastward_wind'
-        self.outdata[(iodavar, iconv.OvalName())] = np.array(data['ob_uwnd'], dtype=np.float32)
-        self.outdata[(iodavar, iconv.OerrName())] = np.full((nlocs), 0.7, dtype=np.float32)
-        self.outdata[(iodavar, iconv.OqcName())] = np.full((nlocs), 2, dtype=np.int32)
-        iodavar = 'northward_wind'
-        self.outdata[(iodavar, iconv.OvalName())] = np.array(data['ob_vwnd'], dtype=np.float32)
-        self.outdata[(iodavar, iconv.OerrName())] = np.full((nlocs), 0.7, dtype=np.float32)
-        self.outdata[(iodavar, iconv.OqcName())] = np.full((nlocs), 2, dtype=np.int32)
-
-        DimDict['nlocs'] = nlocs
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+        nlocs = len(data['dateTime'])
+        DimDict['Location'] = nlocs
+
+        # Set units of the MetaData variables and all _FillValues.
+        for key in meta_keys:
+            dtypestr = locationKeyList[meta_keys.index(key)][1]
+            self.varAttrs[(key, metaDataName)]['_FillValue'] = missing_vals[dtypestr]
+            this_units = locationKeyList[meta_keys.index(key)][2]
+            if this_units:
+                self.varAttrs[(key, metaDataName)]['units'] = this_units
+            self.outdata[(key, metaDataName)] = np.array(data[key], dtype=dtypes[dtypestr])
+
+        # Transfer from the 1-D data vectors and ensure output data (obs_data) types using numpy.
+        # The value of 2 for the preQC is NCEP-EMC prepBUFR code table 7 meaning not-checked QC.
+        # per source: https://www.emc.ncep.noaa.gov/mmb/data_processing/prepbufr.doc/table_7.htm
+        for n, iodavar in enumerate(obsvars):
+            self.outdata[(iodavar, obsValName)] = np.array(data[iodavar], dtype=np.float32)
+            self.outdata[(iodavar, obsErrName)] = np.full(nlocs, obserrlist[n], dtype=np.float32)
+            self.outdata[(iodavar, qcName)] = np.full(nlocs, 2, dtype=np.int32)
 
         return
 
@@ -256,7 +254,7 @@ def main():
         description=desc,
         formatter_class=ArgumentDefaultsHelpFormatter)
     parser.add_argument(
-        '-i', '--input', nargs='+', help='name of the input METARs CSV-formatted file',
+        '-i', '--input', help='name of the input METARs CSV-formatted file',
         type=str, required=True, default=None)
     parser.add_argument(
         '-o', '--output', help='name of the output netCDF IODA-ready file',
@@ -269,21 +267,13 @@ def main():
 
     fdate = datetime.strptime(args.date, '%Y%m%d%H')
 
-    obs_data = {}
-    for afile in args.input:
-        metar = None
-        metar = reformatMetar(afile, fdate)
-        file_obs_data = metar.outdata
-        if obs_data:
-            concat_obs_dict(obs_data, file_obs_data)
-        else:
-            obs_data = file_obs_data
+    obs = reformatMetar(args.input, fdate)
 
     # setup the IODA writer
     writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
 
     # write everything out
-    writer.BuildIoda(obs_data, VarDims, metar.varAttrs, AttrData)
+    writer.BuildIoda(obs.outdata, VarDims, obs.varAttrs, AttrData)
 
 
 if __name__ == '__main__':
diff --git a/src/conventional/ship_bufr2ioda.py b/src/conventional/ship_bufr2ioda.py
index 6660b878f..64bc156cc 100644
--- a/src/conventional/ship_bufr2ioda.py
+++ b/src/conventional/ship_bufr2ioda.py
@@ -28,26 +28,26 @@
 os.environ["TZ"] = "UTC"
 
 locationKeyList = [
-    ("station_id", "string", ""),
-    ("ship_heading", "integer", ""),
-    ("ship_speed", "float", ""),
+    ("stationIdentification", "string", ""),
+    ("shipHeading", "integer", ""),
+    ("shipVelocity", "float", ""),
     ("latitude", "float", "degrees_north"),
     ("longitude", "float", "degrees_east"),
-    ("station_elevation", "float", "m"),
+    ("stationElevation", "float", "m"),
     ("height", "float", "m"),
     ("dateTime", "long", "seconds since 1970-01-01T00:00:00Z")
 ]
 meta_keys = [m_item[0] for m_item in locationKeyList]
 
 metaDataKeyList = {
-    'station_id': ['shipOrMobileLandStationIdentifier'],
-    'ship_heading': ['directionOfMotionOfMovingObservingPlatform'],
-    'ship_speed': ['movingObservingPlatformSpeed'],
+    'stationIdentification': ['shipOrMobileLandStationIdentifier'],
+    'shipHeading': ['directionOfMotionOfMovingObservingPlatform'],
+    'shipVelocity': ['movingObservingPlatformSpeed'],
     'latitude': ['latitude'],
     'longitude': ['longitude'],
-    'station_elevation': ['Constructed',
-                          'heightOfStationGroundAboveMeanSeaLevel',
-                          'heightOfSensorAboveWaterSurface'],
+    'stationElevation': ['Constructed',
+                         'heightOfStationGroundAboveMeanSeaLevel',
+                         'heightOfSensorAboveWaterSurface'],
     'height': ['Constructed',
                'heightOfBarometerAboveMeanSeaLevel',
                'heightOfStationGroundAboveMeanSeaLevel'],
@@ -66,22 +66,22 @@
                'pressureReducedToMeanSeaLevel']
 
 # The outgoing IODA variables (ObsValues), their units, and assigned constant ObsError.
-obsvars = ['air_temperature',
-           'specific_humidity',
-           'sea_surface_temperature',
-           'eastward_wind',
-           'northward_wind',
-           'surface_pressure']
+obsvars = ['airTemperature',
+           'specificHumidity',
+           'seaSurfaceTemperature',
+           'windEastward',
+           'windNorthward',
+           'stationPressure']
 obsvars_units = ['K', 'kg kg-1', 'K', 'm s-1', 'm s-1', 'Pa']
 obserrlist = [1.2, 0.75E-3, 2.2, 1.7, 1.7, 120.0]
 
 VarDims = {
-    'air_temperature': ['nlocs'],
-    'specific_humidity': ['nlocs'],
-    'sea_surface_temperature': ['nlocs'],
-    'eastward_wind': ['nlocs'],
-    'northward_wind': ['nlocs'],
-    'surface_pressure': ['nlocs']
+    'airTemperature': ['Location'],
+    'specificHumidity': ['Location'],
+    'seaSurfaceTemperature': ['Location'],
+    'windEastward': ['Location'],
+    'windNorthward': ['Location'],
+    'stationPressure': ['Location']
 }
 
 metaDataName = iconv.MetaDataName()
@@ -94,7 +94,7 @@
     'ioda_version': 2,
     'description': 'Surface (Ship) observations converted from BUFR',
     'source': 'LDM at NCAR-RAL',
-    'source_files': ''
+    'sourceFiles': ''
 }
 
 DimDict = {
@@ -141,12 +141,12 @@ def main(file_names, output_file):
 
     for fname in file_names:
         logging.debug("Reading file: " + fname)
-        AttrData['source_files'] += ", " + fname
+        AttrData['sourceFiles'] += ", " + fname
 
         data, count, start_pos = read_file(fname, count, start_pos, data)
 
-    AttrData['source_files'] = AttrData['source_files'][2:]
-    logging.debug("All source files: " + AttrData['source_files'])
+    AttrData['sourceFiles'] = AttrData['sourceFiles'][2:]
+    logging.debug("All source files: " + AttrData['sourceFiles'])
 
     if not data:
         logging.critical("ABORT: no message data was captured, stopping execution.")
@@ -154,8 +154,7 @@ def main(file_names, output_file):
     logging.info("--- {:9.4f} BUFR read seconds ---".format(time.time() - start_time))
 
     nlocs = len(data['dateTime'])
-    DimDict = {'nlocs': nlocs}
-    AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+    DimDict = {'Location': nlocs}
 
     # Set coordinates and units of the ObsValues.
     for n, iodavar in enumerate(obsvars):
@@ -167,7 +166,6 @@ def main(file_names, output_file):
         varAttrs[iodavar, qcName]['coordinates'] = 'longitude latitude'
         varAttrs[iodavar, obsValName]['units'] = obsvars_units[n]
         varAttrs[iodavar, obsErrName]['units'] = obsvars_units[n]
-        varAttrs[iodavar, qcName]['units'] = 'unitless'
 
     # Set units of the MetaData variables and all _FillValues.
     for key in meta_keys:
@@ -441,12 +439,12 @@ def read_bufr_message(f, count, start_pos, data):
     mask_height = np.logical_or(meta_data['height'] < -425, meta_data['height'] > 800)
     meta_data['height'][mask_height] = float_missing_value
 
-    # If the height of the observation (sensor) is missing, try to fill it with station_elevation.
-    for n, elev in enumerate(meta_data['station_elevation']):
+    # If the height of the observation (sensor) is missing, try to fill it with stationElevation.
+    for n, elev in enumerate(meta_data['stationElevation']):
         if (elev > -425 and elev < 800 and np.abs(meta_data['height'][n]-elev) > 50):
             meta_data['height'][n] = elev + 2
         else:
-            meta_data['station_elevation'][n] = 1.0
+            meta_data['stationElevation'][n] = 1.0
             meta_data['height'][n] = 10.0
 
     # Next, get the raw observed weather variables we want.
@@ -500,12 +498,12 @@ def read_bufr_message(f, count, start_pos, data):
             spfh[n] = met_utils.specific_humidity(dewpoint, psfc)
 
     # Move everything into the final data dictionary, including metadata.
-    data['eastward_wind'] = np.append(data['eastward_wind'], uwnd)
-    data['northward_wind'] = np.append(data['northward_wind'], vwnd)
-    data['specific_humidity'] = np.append(data['specific_humidity'], spfh)
-    data['air_temperature'] = np.append(data['air_temperature'], vals['airTemperature'])
-    data['surface_pressure'] = np.append(data['surface_pressure'], vals['nonCoordinatePressure'])
-    data['sea_surface_temperature'] = np.append(data['sea_surface_temperature'], vals['oceanographicWaterTemperature'])
+    data['windEastward'] = np.append(data['windEastward'], uwnd)
+    data['windNorthward'] = np.append(data['windNorthward'], vwnd)
+    data['specificHumidity'] = np.append(data['specificHumidity'], spfh)
+    data['airTemperature'] = np.append(data['airTemperature'], vals['airTemperature'])
+    data['stationPressure'] = np.append(data['stationPressure'], vals['nonCoordinatePressure'])
+    data['seaSurfaceTemperature'] = np.append(data['seaSurfaceTemperature'], vals['oceanographicWaterTemperature'])
     for key in meta_keys:
         data[key] = np.append(data[key], meta_data[key])
 
diff --git a/src/conventional/decode_bufr_LDM_raob.py b/src/conventional/sonde_bufr2ioda.py
similarity index 91%
rename from src/conventional/decode_bufr_LDM_raob.py
rename to src/conventional/sonde_bufr2ioda.py
index 2c0810b6f..298cca0c8 100644
--- a/src/conventional/decode_bufr_LDM_raob.py
+++ b/src/conventional/sonde_bufr2ioda.py
@@ -30,23 +30,23 @@
 locationKeyList = [
     ("latitude", "float", "degrees_north", "keep"),
     ("longitude", "float", "degrees_east", "keep"),
-    ("station_elevation", "float", "m", "keep"),
+    ("stationElevation", "float", "m", "keep"),
     ("dateTime", "long", "seconds since 1970-01-01T00:00:00Z", "keep"),
-    ("LaunchTime", "long", "seconds since 1970-01-01T00:00:00Z", "keep"),
-    ("air_pressure", "float", "Pa", "keep"),
-    ("geopotential_height", "float", "m", "keep"),
+    ("releaseTime", "long", "seconds since 1970-01-01T00:00:00Z", "keep"),
+    ("pressure", "float", "Pa", "keep"),
+    ("geopotentialHeight", "float", "m", "keep"),
     ("vertSignificance", "integer", "", "toss"),
     ("latDisplacement", "float", "degrees", "toss"),
     ("lonDisplacement", "float", "degrees", "toss"),
     ("timeDisplacement", "float", "s", "toss"),
     ("wmoBlockNumber", "integer", "", "toss"),
     ("wmoStationNumber", "integer", "", "toss"),
-    ("station_id", "string", "", "keep"),
-    ("instrumentType", "integer", "", "keep"),
-    ("instrumentRadiationCorrectionInfo", "integer", "", "keep"),
-    ("instrumentHumidityCorrectionInfo", "integer", "", "keep"),
-    ("temperatureSensorType", "integer", "", "keep"),
-    ("humiditySensorType", "integer", "", "keep"),
+    ("stationIdentification", "string", "", "keep"),
+    ("instrumentIdentifier", "integer", "", "keep"),
+    # ("instrumentRadiationCorrectionInfo", "integer", "", "keep"),
+    # ("instrumentHumidityCorrectionInfo", "integer", "", "keep"),
+    # ("temperatureSensorType", "integer", "", "keep"),
+    # ("humiditySensorType", "integer", "", "keep"),
     ("year", "integer", "", "toss"),
     ("month", "integer", "", "toss"),
     ("day", "integer", "", "toss"),
@@ -59,25 +59,25 @@
 metaDataKeyList = {
     'latitude': ['latitude'],
     'longitude': ['longitude'],
-    'station_elevation': ['Constructed', 'heightOfBarometerAboveMeanSeaLevel',
-                          'heightOfStationGroundAboveMeanSeaLevel', 'heightOfStation', 'height'],
+    'stationElevation': ['Constructed', 'heightOfBarometerAboveMeanSeaLevel',
+                         'heightOfStationGroundAboveMeanSeaLevel', 'heightOfStation', 'height'],
     'dateTime': ['Constructed'],
-    'LaunchTime': ['Constructed'],
-    'air_pressure': ['pressure', 'nonCoordinatePressure'],
-    'geopotential_height': ['nonCoordinateGeopotentialHeight', 'geopotentialHeight'],
+    'releaseTime': ['Constructed'],
+    'pressure': ['pressure', 'nonCoordinatePressure'],
+    'geopotentialHeight': ['nonCoordinateGeopotentialHeight', 'geopotentialHeight'],
     'vertSignificance': ['extendedVerticalSoundingSignificance', 'verticalSoundingSignificance'],
     'latDisplacement': ['latitudeDisplacement'],
     'lonDisplacement': ['longitudeDisplacement'],
     'timeDisplacement': ['timePeriod'],
     'wmoBlockNumber': ['blockNumber'],
     'wmoStationNumber': ['stationNumber'],
-    'station_id': ['Constructed'],
+    'stationIdentification': ['Constructed'],
     # "stationLongName": 'shipOrMobileLandStationIdentifier',
-    "instrumentType": ['radiosondeType'],
-    "instrumentRadiationCorrectionInfo": ['solarAndInfraredRadiationCorrection'],
-    "instrumentHumidityCorrectionInfo": ['correctionAlgorithmsForHumidityMeasurements'],
-    "temperatureSensorType": ['temperatureSensorType'],
-    "humiditySensorType": ['humiditySensorType'],
+    "instrumentIdentifier": ['radiosondeType'],
+    # "instrumentRadiationCorrectionInfo": ['solarAndInfraredRadiationCorrection'],
+    # "instrumentHumidityCorrectionInfo": ['correctionAlgorithmsForHumidityMeasurements'],
+    # "temperatureSensorType": ['temperatureSensorType'],
+    # "humiditySensorType": ['humiditySensorType'],
     # "instrumentSerialNum": 'radiosondeSerialNumber',
     # "instrumentSoftwareVersion": 'softwareVersionNumber',
     'year': ['year'],
@@ -92,16 +92,16 @@
 raw_obsvars = ['airTemperature', 'dewpointTemperature', 'windDirection', 'windSpeed']
 
 # The outgoing IODA variables (ObsValues), their units, and assigned constant ObsError.
-obsvars = ['air_temperature', 'virtual_temperature', 'specific_humidity', 'eastward_wind', 'northward_wind']
+obsvars = ['airTemperature', 'virtualTemperature', 'specificHumidity', 'windEastward', 'windNorthward']
 obsvars_units = ['K', 'K', 'kg kg-1', 'm s-1', 'm s-1']
 obserrlist = [1.2, 1.2, 0.75E-3, 1.7, 1.7]
 
 VarDims = {
-    'air_temperature': ['nlocs'],
-    'virtual_temperature': ['nlocs'],
-    'specific_humidity': ['nlocs'],
-    'eastward_wind': ['nlocs'],
-    'northward_wind': ['nlocs']
+    'airTemperature': ['Location'],
+    'virtualTemperature': ['Location'],
+    'specificHumidity': ['Location'],
+    'windEastward': ['Location'],
+    'windNorthward': ['Location']
 }
 
 AttrData = {
@@ -175,7 +175,7 @@ def main(file_names, output_file, datetimeRef):
     logging.info("--- {:9.4f} BUFR read seconds ---".format(time.time() - start_time))
 
     nlocs = count[1]
-    DimDict = {'nlocs': nlocs}
+    DimDict = {'Location': nlocs}
 
     # Set coordinates and units of the ObsValues.
     for n, iodavar in enumerate(obsvars):
@@ -589,7 +589,7 @@ def read_bufr_message(f, count, start_pos, data):
                 target_number = len(temp_data['timeDisplacement'])
             elif temp_data['latDisplacement'] is not None:
                 target_number = len(temp_data['latDisplacement'])
-            elif temp_data['air_pressure'] is not None:
+            elif temp_data['pressure'] is not None:
                 target_number = len(temp_data['air_pressure'])
             elif temp_data['airTemperature'] is not None:
                 target_number = len(temp_data['airTemperature'])
@@ -626,13 +626,13 @@ def read_bufr_message(f, count, start_pos, data):
             meta_data['dateTime'] = specialty_time(temp_data['timeDisplacement'][b:e],
                       meta_data['year'][0], meta_data['month'][0], meta_data['day'][0],      # noqa
                       meta_data['hour'][0], meta_data['minute'][0], meta_data['second'][0])  # noqa
-            meta_data['LaunchTime'] = np.full(target_number, meta_data['dateTime'][0])
+            meta_data['releaseTime'] = np.full(target_number, meta_data['dateTime'][0])
         else:
             meta_data['dateTime'][0] = specialty_time([0],
                       meta_data['year'][0], meta_data['month'][0], meta_data['day'][0],      # noqa
                       meta_data['hour'][0], meta_data['minute'][0], meta_data['second'][0])  # noqa
             meta_data['dateTime'] = np.full(target_number, meta_data['dateTime'][0])
-            meta_data['LaunchTime'] = np.full(target_number, meta_data['dateTime'][0])
+            meta_data['releaseTime'] = np.full(target_number, meta_data['dateTime'][0])
 
         # Sondes also have lat/lon displacement from launch/release location.
         if temp_data['latDisplacement'] is not None and temp_data['lonDisplacement'] is not None:
@@ -663,20 +663,20 @@ def read_bufr_message(f, count, start_pos, data):
             if (lat < -90 or lat > 90):
                 meta_data['latitude'][n] = meta_data['latitude'][n-1]
 
-        # Forcably create station_id 5-char string from WMO block+station number.
-        meta_data['station_id'] = np.full(target_number, string_missing_value, dtype='<S5')
+        # Forcably create stationIdentification 5-char string from WMO block+station number.
+        meta_data['stationIdentification'] = np.full(target_number, string_missing_value, dtype='<S5')
         for n, block in enumerate(meta_data['wmoBlockNumber']):
             number = meta_data['wmoStationNumber'][n]
             if (block > 0 and block < 100 and number > 0 and number < 1000):
-                meta_data['station_id'][n] = "{:02d}".format(block) + "{:03d}".format(number)
+                meta_data['stationIdentification'][n] = "{:02d}".format(block) + "{:03d}".format(number)
             if n == 0:
                 count[3] += 1
-                logging.info(f"Processing sonde for station: {meta_data['station_id'][n]}")
+                logging.info(f"Processing sonde for station: {meta_data['stationIdentification'][n]}")
 
         # Very odd, sometimes the first level of data has some variables set to zero. Reset to missing.
-        if (meta_data['geopotential_height'][0] == 0 or meta_data['air_pressure'][0] == 0):
-            meta_data['geopotential_height'][0] = float_missing_value
-            meta_data['air_pressure'][0] = float_missing_value
+        if (meta_data['geopotentialHeight'][0] == 0 or meta_data['pressure'][0] == 0):
+            meta_data['geopotentialHeight'][0] = float_missing_value
+            meta_data['pressure'][0] = float_missing_value
 
         # And now processing the observed variables we care about.
         nbad = 0
@@ -723,7 +723,7 @@ def read_bufr_message(f, count, start_pos, data):
 
         spfh = np.full(target_number, float_missing_value)
         for n, dewpoint in enumerate(vals['dewpointTemperature']):
-            pres = meta_data['air_pressure'][n]
+            pres = meta_data['pressure'][n]
             if dewpoint and pres:
                 if (dewpoint > 50 and dewpoint < 325 and pres > 100 and pres < 109900):
                     spfh[n] = met_utils.specific_humidity(dewpoint, pres)
@@ -736,17 +736,17 @@ def read_bufr_message(f, count, start_pos, data):
 
         tvirt = np.full(target_number, float_missing_value)
         for n, temp in enumerate(airt):
-            pres = meta_data['air_pressure'][n]
+            pres = meta_data['pressure'][n]
             if (temp != float_missing_value and spfh[n] and pres < 108000 and pres > 10000):
                 qvapor = max(1.0e-12, spfh[n]/(1.0-spfh[n]))
                 tvirt[n] = temp*(1.0 + 0.61*qvapor)
 
         # Finally fill up the output data dictionary with observed variables.
-        data['eastward_wind'] = np.append(data['eastward_wind'], uwnd)
-        data['northward_wind'] = np.append(data['northward_wind'], vwnd)
-        data['specific_humidity'] = np.append(data['specific_humidity'], spfh)
-        data['air_temperature'] = np.append(data['air_temperature'], airt)
-        data['virtual_temperature'] = np.append(data['virtual_temperature'], tvirt)
+        data['windEastward'] = np.append(data['windEastward'], uwnd)
+        data['windNorthward'] = np.append(data['windNorthward'], vwnd)
+        data['specificHumidity'] = np.append(data['specificHumidity'], spfh)
+        data['airTemperature'] = np.append(data['airTemperature'], airt)
+        data['virtualTemperature'] = np.append(data['virtualTemperature'], tvirt)
 
         obnum += 1
 
diff --git a/src/conventional/sonde_tac2ioda.py b/src/conventional/sonde_tac2ioda.py
index e8221fb0a..def658933 100644
--- a/src/conventional/sonde_tac2ioda.py
+++ b/src/conventional/sonde_tac2ioda.py
@@ -1,3 +1,4 @@
+#!/usr/bin/env python3
 ###########################################################################
 # These functions decode WMO format soundings which contain at least the
 # mandatory levels (TTAA, TTCC), and also can include significant temperature
@@ -63,32 +64,32 @@
 
 # The outgoing IODA MetaData variables, their data type, and units.
 MetaDataKeyList = [
-    ("station_id", "string", ""),
+    ("stationIdentification", "string", ""),
     ("latitude", "float", "degrees_north"),
     ("longitude", "float", "degrees_east"),
-    ("station_elevation", "float", "m"),
+    ("stationElevation", "float", "m"),
     ("height", "float", "m"),
-    ("air_pressure", "float", "Pa"),
-    ("launch_time", "string", ""),
-    ("dateTime", "long", "seconds since 1970-01-01T00:00:00Z"),
+    ("pressure", "float", "Pa"),
+    ("releaseTime", "long", "seconds since 1970-01-01T00:00:00Z"),
+    ("dateTime", "long", "seconds since 1970-01-01T00:00:00Z")
 ]
 meta_keys = [m_item[0] for m_item in MetaDataKeyList]
 
 # The outgoing IODA variables (ObsValues), their units, and assigned constant ObsError.
-obsvars = ['air_temperature',
-           'specific_humidity',
-           'virtual_temperature',
-           'eastward_wind',
-           'northward_wind']
+obsvars = ['airTemperature',
+           'specificHumidity',
+           'virtualTemperature',
+           'windEastward',
+           'windNorthward']
 obsvars_units = ['K', 'kg kg-1', 'K', 'm s-1', 'm s-1']
 obserrlist = [1.2, 0.75E-3, 1.5, 1.7, 1.7]
 
 VarDims = {
-    'air_temperature': ['nlocs'],
-    'specific_humidity': ['nlocs'],
-    'virtual_temperature': ['nlocs'],
-    'eastward_wind': ['nlocs'],
-    'northward_wind': ['nlocs']
+    'airTemperature': ['Location'],
+    'specificHumidity': ['Location'],
+    'virtualTemperature': ['Location'],
+    'windEastward': ['Location'],
+    'windNorthward': ['Location']
 }
 
 metaDataName = iconv.MetaDataName()
@@ -815,9 +816,6 @@ def getPressureLevels(section, levels):
     section['levels'] = {}
     pressures = sorted(levels.keys(), reverse=True)
 
-    if len(pressures) < 1:
-        return
-
     # loop through each height and try to find surrounding heights with defined
     # levels to interpolate or extrapolate pressure level from
 
@@ -860,9 +858,6 @@ def getHeights(section, levels):
     """
     pressures = sorted(levels.keys(), reverse=True)
 
-    if len(pressures) < 1:
-        return
-
     for pressure in sorted(section['levels'].keys(), reverse=True):
         pressurelo = pressures[0]
         pressureup = pressures[-1]
@@ -952,6 +947,7 @@ def change_vars(profile):
     # launch is usually initiated close to 11:05Z.
     this_datetime = datetime(profile['year'], profile['month'], profile['day'], profile['hour'], 0, 0)
     launch_time = this_datetime - timedelta(seconds=55*60)
+    time_offset1 = round((launch_time - epoch).total_seconds())
     previous_time = launch_time
 
     heightKm1 = profile['elev']
@@ -994,19 +990,19 @@ def change_vars(profile):
         time_offset = round((this_datetime - epoch).total_seconds())
         previous_time = this_datetime
 
-        new_profile['station_id'].append(profile['synop'])
+        new_profile['stationIdentification'].append(profile['synop'])
         new_profile['latitude'].append(profile['lat'])
         new_profile['longitude'].append(profile['lon'])
-        new_profile['station_elevation'].append(profile['elev'])
-        new_profile['launch_time'].append(launch_time.strftime("%Y-%m-%dT%H:%M:%SZ"))
+        new_profile['stationElevation'].append(profile['elev'])
+        new_profile['releaseTime'].append(time_offset1)
         new_profile['dateTime'].append(time_offset)
-        new_profile['air_pressure'].append(pres)
+        new_profile['pressure'].append(pres)
         new_profile['height'].append(height)
-        new_profile['air_temperature'].append(temp)
-        new_profile['virtual_temperature'].append(tvirt)
-        new_profile['specific_humidity'].append(spfh)
-        new_profile['eastward_wind'].append(u)
-        new_profile['northward_wind'].append(v)
+        new_profile['airTemperature'].append(temp)
+        new_profile['virtualTemperature'].append(tvirt)
+        new_profile['specificHumidity'].append(spfh)
+        new_profile['windEastward'].append(u)
+        new_profile['windNorthward'].append(v)
 
     """
     Based on height and time and the wind componenents, predict the lat, lon positions
@@ -1021,13 +1017,13 @@ def change_vars(profile):
 
     for idx in range(1, len(delta_t)):
 
-        if (new_profile['eastward_wind'][idx-1] != float_missing_value and new_profile['northward_wind'][idx-1] != float_missing_value):
+        if (new_profile['windEastward'][idx-1] != float_missing_value and new_profile['windNorthward'][idx-1] != float_missing_value):
             # move north-south
-            d_north = new_profile['northward_wind'][idx-1] * delta_t[idx-1]
+            d_north = new_profile['windNorthward'][idx-1] * delta_t[idx-1]
             location = geod.direct(points=previous_loc[:2], azimuths=0., distances=d_north)[0]
             new_profile['latitude'][idx] = location[1]
             # move east-west
-            d_east = new_profile['eastward_wind'][idx-1] * delta_t[idx-1]
+            d_east = new_profile['windEastward'][idx-1] * delta_t[idx-1]
             location = geod.direct(points=location[:2], azimuths=90., distances=d_east)[0]
             new_profile['longitude'][idx] = location[0]
         else:
@@ -1164,7 +1160,7 @@ def append_ioda_data(in_profile, obs_data):
 
     if args.netcdf:
         ioda_data = {}
-        DimDict = {'nlocs': ntotal}
+        DimDict = {'Location': ntotal}
         AttrData['sourceFiles'] = AttrData['sourceFiles'][2:]
         # Set coordinates and units of the ObsValues.
         for n, iodavar in enumerate(obsvars):
diff --git a/src/conventional/synop_bufr2ioda.py b/src/conventional/synop_bufr2ioda.py
index ff1cb9c5d..5bc2b614b 100644
--- a/src/conventional/synop_bufr2ioda.py
+++ b/src/conventional/synop_bufr2ioda.py
@@ -28,13 +28,13 @@
 os.environ["TZ"] = "UTC"
 
 locationKeyList = [
-    ("station_id", "string", "", "keep"),
+    ("stationIdentification", "string", "", "keep"),
     # ("station_name", "string", "", "keep"),
     ("wmoBlockNumber", "integer", "", "toss"),
     ("wmoStationNumber", "integer", "", "toss"),
     ("latitude", "float", "degrees_north", "keep"),
     ("longitude", "float", "degrees_east", "keep"),
-    ("station_elevation", "float", "m", "keep"),
+    ("stationElevation", "float", "m", "keep"),
     ("height", "float", "m", "keep"),
     ("dateTime", "long", "seconds since 1970-01-01T00:00:00Z", "keep"),
     ("year", "integer", "", "toss"),
@@ -52,11 +52,11 @@
     # 'station_name': ['stationOrSiteName'],   This fails due to unicode characters
     'latitude': ['latitude'],
     'longitude': ['longitude'],
-    'station_elevation': ['heightOfStationGroundAboveMeanSeaLevel'],
+    'stationElevation': ['heightOfStationGroundAboveMeanSeaLevel'],
     'height': ['Constructed',
                'heightOfBarometerAboveMeanSeaLevel',
                'heightOfStationGroundAboveMeanSeaLevel'],
-    'station_id': ['Constructed'],
+    'stationIdentification': ['Constructed'],
     'dateTime': ['Constructed'],
     'year': ['year'],
     'month': ['month'],
@@ -76,22 +76,22 @@
                'nonCoordinatePressure']
 
 # The outgoing IODA variables (ObsValues), their units, and assigned constant ObsError.
-obsvars = ['air_temperature',
-           'specific_humidity',
-           'virtual_temperature',
-           'eastward_wind',
-           'northward_wind',
-           'surface_pressure']
+obsvars = ['airTemperature',
+           'specificHumidity',
+           'virtualTemperature',
+           'windEastward',
+           'windNorthward',
+           'stationPressure']
 obsvars_units = ['K', 'kg kg-1', 'K', 'm s-1', 'm s-1', 'Pa']
 obserrlist = [1.2, 0.75E-3, 1.5, 1.7, 1.7, 120.0]
 
 VarDims = {
-    'air_temperature': ['nlocs'],
-    'specific_humidity': ['nlocs'],
-    'virtual_temperature': ['nlocs'],
-    'eastward_wind': ['nlocs'],
-    'northward_wind': ['nlocs'],
-    'surface_pressure': ['nlocs']
+    'airTemperature': ['Location'],
+    'specificHumidity': ['Location'],
+    'virtualTemperature': ['Location'],
+    'windEastward': ['Location'],
+    'windNorthward': ['Location'],
+    'stationPressure': ['Location']
 }
 
 metaDataName = iconv.MetaDataName()
@@ -104,7 +104,7 @@
     'ioda_version': 2,
     'description': 'Surface (SYNOP) observations converted from BUFR',
     'source': 'LDM at NCAR-RAL',
-    'source_files': ''
+    'sourceFiles': ''
 }
 
 DimDict = {
@@ -151,12 +151,12 @@ def main(file_names, output_file):
 
     for fname in file_names:
         logging.debug("Reading file: " + fname)
-        AttrData['source_files'] += ", " + fname
+        AttrData['sourceFiles'] += ", " + fname
 
         data, count, start_pos = read_file(fname, count, start_pos, data)
 
-    AttrData['source_files'] = AttrData['source_files'][2:]
-    logging.debug("All source files: " + AttrData['source_files'])
+    AttrData['sourceFiles'] = AttrData['sourceFiles'][2:]
+    logging.debug("All source files: " + AttrData['sourceFiles'])
 
     if not data:
         logging.critical("ABORT: no message data was captured, stopping execution.")
@@ -164,8 +164,7 @@ def main(file_names, output_file):
     logging.info("--- {:9.4f} BUFR read seconds ---".format(time.time() - start_time))
 
     nlocs = len(data['dateTime'])
-    DimDict = {'nlocs': nlocs}
-    AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+    DimDict = {'Location': nlocs}
 
     # Set coordinates and units of the ObsValues.
     for n, iodavar in enumerate(obsvars):
@@ -177,7 +176,6 @@ def main(file_names, output_file):
         varAttrs[iodavar, qcName]['coordinates'] = 'longitude latitude'
         varAttrs[iodavar, obsValName]['units'] = obsvars_units[n]
         varAttrs[iodavar, obsErrName]['units'] = obsvars_units[n]
-        varAttrs[iodavar, qcName]['units'] = 'unitless'
 
     # Set units of the MetaData variables and all _FillValues.
     for key in meta_keys:
@@ -499,7 +497,7 @@ def read_bufr_message(f, count, start_pos, data):
     meta_data['height'][mask_height] = float_missing_value
 
     # If the height of the observation (sensor) is missing, try to fill it with station_elevation.
-    for n, elev in enumerate(meta_data['station_elevation']):
+    for n, elev in enumerate(meta_data['stationElevation']):
         if (elev > -425 and elev < 8500):
             meta_data['height'][n] = elev + 2
 
@@ -579,12 +577,12 @@ def read_bufr_message(f, count, start_pos, data):
                     tvirt[n] = airt[n]*(1.0 + 0.61*qvapor)
 
     # Finally fill up the output data dictionary with observed variables.
-    data['eastward_wind'] = np.append(data['eastward_wind'], uwnd)
-    data['northward_wind'] = np.append(data['northward_wind'], vwnd)
-    data['specific_humidity'] = np.append(data['specific_humidity'], spfh)
-    data['air_temperature'] = np.append(data['air_temperature'], airt)
-    data['virtual_temperature'] = np.append(data['virtual_temperature'], tvirt)
-    data['surface_pressure'] = np.append(data['surface_pressure'], psfc)
+    data['windEastward'] = np.append(data['windEastward'], uwnd)
+    data['windNorthward'] = np.append(data['windNorthward'], vwnd)
+    data['specificHumidity'] = np.append(data['specificHumidity'], spfh)
+    data['airTemperature'] = np.append(data['airTemperature'], airt)
+    data['virtualTemperature'] = np.append(data['virtualTemperature'], tvirt)
+    data['stationPressure'] = np.append(data['stationPressure'], psfc)
 
     logging.info(f"number of observations so far: {count[1]} from {count[0]} BUFR msgs.")
     logging.info(f"number of invalid or useless observations: {count[2]}")
diff --git a/src/gnssro/gnssro_bufr2ioda.py b/src/gnssro/gnssro_bufr2ioda.py
index 3b681430c..a740bc04d 100644
--- a/src/gnssro/gnssro_bufr2ioda.py
+++ b/src/gnssro/gnssro_bufr2ioda.py
@@ -17,6 +17,7 @@
 import os
 from pathlib import Path
 from itertools import repeat
+import netCDF4 as nc
 
 IODA_CONV_PATH = Path(__file__).parent/"@SCRIPT_LIB_PATH@"
 if not IODA_CONV_PATH.is_dir():
@@ -30,13 +31,18 @@
 # globals
 ioda_float_type = 'float32'
 ioda_int_type = 'int32'
-float_missing_value = -1.0e+37
-int_missing_value = -2147483647
+float_missing_value = nc.default_fillvals['f4']
+int_missing_value = nc.default_fillvals['i4']
+long_missing_value = nc.default_fillvals['i8']
+string_missing_value = '_'
+
+iso8601_string = 'seconds since 1970-01-01T00:00:00Z'
+epoch = datetime.fromisoformat(iso8601_string[14:-1])
 
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string")
+    ("dateTime", "long")
 ]
 
 
@@ -68,42 +74,45 @@ def main(args):
     # prepare global attributes we want to output in the file,
     # in addition to the ones already loaded in from the input file
     GlobalAttrs = {}
-    GlobalAttrs['date_time_string'] = args.date.strftime("%Y-%m-%dT%H:%M:%SZ")
-    date_time_int32 = np.array(int(args.date.strftime("%Y%m%d%H")), dtype='int32')
-    GlobalAttrs['date_time'] = date_time_int32.item()
+    GlobalAttrs['datetimeReference'] = args.date.strftime("%Y-%m-%dT%H:%M:%SZ")
     GlobalAttrs['converter'] = os.path.basename(__file__)
 
     # pass parameters to the IODA writer
     VarDims = {
-        'bending_angle': ['nlocs'],
-        'refractivity': ['nlocs']
+        'bendingAngle': ['Location'],
+        'atmosphericRefractivity': ['Location']
     }
 
     # write them out
-    nlocs = obs_data[('bending_angle', 'ObsValue')].shape[0]
-    DimDict = {'nlocs': nlocs}
+    nlocs = obs_data[('bendingAngle', 'ObsValue')].shape[0]
+    DimDict = {'Location': nlocs}
     meta_data_types = def_meta_types()
     for k, v in meta_data_types.items():
         locationKeyList.append((k, v))
     writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
     VarAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
-    VarAttrs[('bending_angle', 'ObsValue')]['units'] = 'Radians'
-    VarAttrs[('bending_angle', 'ObsError')]['units'] = 'Radians'
-    VarAttrs[('bending_angle', 'PreQC')]['units'] = 'unitless'
-    VarAttrs[('refractivity', 'ObsValue')]['units'] = 'N'
-    VarAttrs[('refractivity', 'ObsError')]['units'] = 'N'
-    VarAttrs[('refractivity', 'PreQC')]['units'] = 'unitless'
-
-    VarAttrs[('bending_angle', 'ObsValue')]['_FillValue'] = float_missing_value
-    VarAttrs[('bending_angle', 'ObsError')]['_FillValue'] = float_missing_value
-    VarAttrs[('bending_angle', 'PreQC')]['_FillValue'] = int_missing_value
-    VarAttrs[('refractivity', 'ObsValue')]['_FillValue'] = float_missing_value
-    VarAttrs[('refractivity', 'ObsError')]['_FillValue'] = float_missing_value
-    VarAttrs[('refractivity', 'PreQC')]['_FillValue'] = int_missing_value
+    VarAttrs[('bendingAngle', 'ObsValue')]['units'] = 'Radians'
+    VarAttrs[('bendingAngle', 'ObsError')]['units'] = 'Radians'
+    VarAttrs[('atmosphericRefractivity', 'ObsValue')]['units'] = 'N units'
+    VarAttrs[('atmosphericRefractivity', 'ObsError')]['units'] = 'N units'
+    VarAttrs[('height', 'MetaData')]['units'] = 'm'
+    VarAttrs[('latitude', 'MetaData')]['units'] = 'degree_north'
+    VarAttrs[('longitude', 'MetaData')]['units'] = 'degree_east'
+    VarAttrs[('dateTime', 'MetaData')]['units'] = iso8601_string
+    VarAttrs[('sensorAzimuthAngle', 'MetaData')]['units'] = 'degree'
+    VarAttrs[('geoidUndulation', 'MetaData')]['units'] = 'm'
+    VarAttrs[('earthRadiusCurvature', 'MetaData')]['units'] = 'm'
+
+    VarAttrs[('bendingAngle', 'ObsValue')]['_FillValue'] = float_missing_value
+    VarAttrs[('bendingAngle', 'ObsError')]['_FillValue'] = float_missing_value
+    VarAttrs[('bendingAngle', 'PreQC')]['_FillValue'] = int_missing_value
+    VarAttrs[('atmosphericRefractivity', 'ObsValue')]['_FillValue'] = float_missing_value
+    VarAttrs[('atmosphericRefractivity', 'ObsError')]['_FillValue'] = float_missing_value
+    VarAttrs[('atmosphericRefractivity', 'PreQC')]['_FillValue'] = int_missing_value
 
     VarAttrs[('latitude', 'MetaData')]['_FillValue'] = float_missing_value
     VarAttrs[('longitude', 'MetaData')]['_FillValue'] = float_missing_value
-    VarAttrs[('altitude', 'MetaData')]['_FillValue'] = float_missing_value
+    VarAttrs[('height', 'MetaData')]['_FillValue'] = float_missing_value
 
     # final write to IODA file
     writer.BuildIoda(obs_data, VarDims, VarAttrs, GlobalAttrs)
@@ -153,10 +162,13 @@ def get_meta_data(bufr):
     hour = codes_get(bufr, 'hour')
     minute = codes_get(bufr, 'minute')
     second = codes_get(bufr, 'second')  # non-integer value
+    second = round(second)
 
-    # should really add seconds
-    dtg = ("%4i-%.2i-%.2iT%.2i:%.2i:00Z" % (year, month, day, hour, minute))
-    profile_meta_data['datetime'] = datetime.strptime(dtg, "%Y-%m-%dT%H:%M:%SZ")
+    # get string date, translate to a datetime object, then offset from epoch
+    dtg = ("%4i-%.2i-%.2iT%.2i:%.2i:%.2iZ" % (year, month, day, hour, minute, second))
+    this_datetime = datetime.strptime(dtg, "%Y-%m-%dT%H:%M:%SZ")
+    time_offset = round((this_datetime - epoch).total_seconds())
+    profile_meta_data['dateTime'] = np.int64(time_offset)
 
     return profile_meta_data
 
@@ -189,12 +201,12 @@ def get_obs_data(bufr, profile_meta_data, add_qc, record_number=None):
     # ! Bit 3=Rising Occulation (1=rising; 0=setting)
     # ! Bit 4=Excess Phase non-nominal
     # ! Bit 5=Bending Angle non-nominal
-    i_non_nominal = get_normalized_bit(profile_meta_data['qualityFlag'], bit_index=16-1)
-    i_phase_non_nominal = get_normalized_bit(profile_meta_data['qualityFlag'], bit_index=16-4)
-    i_bang_non_nominal = get_normalized_bit(profile_meta_data['qualityFlag'], bit_index=16-5)
-    iasc = get_normalized_bit(profile_meta_data['qualityFlag'], bit_index=16-3)
+    i_non_nominal = get_normalized_bit(profile_meta_data['qualityFlags'], bit_index=16-1)
+    i_phase_non_nominal = get_normalized_bit(profile_meta_data['qualityFlags'], bit_index=16-4)
+    i_bang_non_nominal = get_normalized_bit(profile_meta_data['qualityFlags'], bit_index=16-5)
+    iasc = get_normalized_bit(profile_meta_data['qualityFlags'], bit_index=16-3)
     # add rising/setting (ascending/descending) bit
-    obs_data[('ascending_flag', 'MetaData')] = np.array(np.repeat(iasc, krepfac[0]), dtype=ioda_int_type)
+    obs_data[('satelliteAscendingFlag', 'MetaData')] = np.array(np.repeat(iasc, krepfac[0]), dtype=ioda_int_type)
 
     # print( " ... RO QC flags: %i  %i  %i  %i" % (i_non_nominal, i_phase_non_nominal, i_bang_non_nominal, iasc) )
 
@@ -203,9 +215,9 @@ def get_obs_data(bufr, profile_meta_data, add_qc, record_number=None):
         return {}
 
     # value, ob_error, qc
-    obs_data[('bending_angle', "ObsValue")] = assign_values(bang)
-    obs_data[('bending_angle', "ObsError")] = assign_values(bang_err)
-    obs_data[('bending_angle', "PreQC")] = np.full(krepfac[0], 0, dtype=ioda_int_type)
+    obs_data[('bendingAngle', "ObsValue")] = assign_values(bang)
+    obs_data[('bendingAngle', "ObsError")] = assign_values(bang_err)
+    obs_data[('bendingAngle', "PreQC")] = np.full(krepfac[0], 0, dtype=ioda_int_type)
 
     # (geometric) height is read as integer but expected as float in output
     height = codes_get_array(bufr, 'height', ktype=float)
@@ -216,31 +228,32 @@ def get_obs_data(bufr, profile_meta_data, add_qc, record_number=None):
     refrac_conf = codes_get_array(bufr, 'percentConfidence')[sum(krepfac[:1])+1:sum(krepfac[:2])+1]
 
     # value, ob_error, qc
-    obs_data[('refractivity', "ObsValue")] = assign_values(refrac)
-    obs_data[('refractivity', "ObsError")] = assign_values(refrac_err)
-    obs_data[('refractivity', "PreQC")] = np.full(krepfac[0], 0, dtype=ioda_int_type)
+    obs_data[('atmosphericRefractivity', "ObsValue")] = assign_values(refrac)
+    obs_data[('atmosphericRefractivity', "ObsError")] = assign_values(refrac_err)
+    obs_data[('atmosphericRefractivity', "PreQC")] = np.full(krepfac[0], 0, dtype=ioda_int_type)
 
     meta_data_types = def_meta_types()
 
     obs_data[('latitude', 'MetaData')] = assign_values(lats)
     obs_data[('longitude', 'MetaData')] = assign_values(lons)
-    obs_data[('impact_parameter', 'MetaData')] = assign_values(impact)
-    obs_data[('altitude', 'MetaData')] = assign_values(height)
+    obs_data[('impactParameterRO', 'MetaData')] = assign_values(impact)
+    obs_data[('height', 'MetaData')] = assign_values(height)
     for k, v in profile_meta_data.items():
-        if type(v) is int:
+        if type(v) is np.int64:
+            obs_data[(k, 'MetaData')] = np.array(np.repeat(v, krepfac[0]), dtype=np.int64)
+        elif type(v) is int:
             obs_data[(k, 'MetaData')] = np.array(np.repeat(v, krepfac[0]), dtype=ioda_int_type)
         elif type(v) is float:
             obs_data[(k, 'MetaData')] = np.array(np.repeat(v, krepfac[0]), dtype=ioda_float_type)
-        else:  # something else (datetime for instance)
-            string_array = np.repeat(v.strftime("%Y-%m-%dT%H:%M:%SZ"), krepfac[0])
-            obs_data[(k, 'MetaData')] = string_array.astype(object)
+        else:  # something else (what do we do with it)
+            print(f"Found neither float nor in, type={type(v)}; skipping")
 
     # set record number (multi file procesing will change this)
     if record_number is None:
         nrec = 1
     else:
         nrec = record_number
-    obs_data[('record_number', 'MetaData')] = np.array(np.repeat(nrec, krepfac[0]), dtype=ioda_int_type)
+    obs_data[('sequenceNumber', 'MetaData')] = np.array(np.repeat(nrec, krepfac[0]), dtype=ioda_int_type)
 
     # get derived profiles
     geop = codes_get_array(bufr, 'geopotentialHeight')[:-1]
@@ -250,10 +263,10 @@ def get_obs_data(bufr, profile_meta_data, add_qc, record_number=None):
     prof_conf = codes_get_array(bufr, 'percentConfidence')[sum(krepfac[:2])+1:sum(krepfac)+1]
 
     # Compute impact height
-    obs_data[('impact_height', 'MetaData')] = \
-        obs_data[('impact_parameter', 'MetaData')] - \
-        obs_data[('geoid_height_above_reference_ellipsoid', 'MetaData')] - \
-        obs_data[('earth_radius_of_curvature', 'MetaData')]
+    obs_data[('impactHeightRO', 'MetaData')] = \
+        obs_data[('impactParameterRO', 'MetaData')] - \
+        obs_data[('geoidUndulation', 'MetaData')] - \
+        obs_data[('earthRadiusCurvature', 'MetaData')]
 
     if add_qc:
         good = quality_control(profile_meta_data, height, lats, lons)
@@ -272,8 +285,8 @@ def quality_control(profile_meta_data, heights, lats, lons):
 
     # bad radius or
     # large geoid undulation
-    if (profile_meta_data['earth_radius_of_curvature'] > 6450000.) or (profile_meta_data['earth_radius_of_curvature'] < 6250000.) or \
-       (abs(profile_meta_data['geoid_height_above_reference_ellipsoid']) > 200):
+    if (profile_meta_data['earthRadiusCurvature'] > 6450000.) or (profile_meta_data['earthRadiusCurvature'] < 6250000.) or \
+       (abs(profile_meta_data['geoidUndulation']) > 200):
         good = []
         # bad profile
     return good
@@ -282,16 +295,16 @@ def quality_control(profile_meta_data, heights, lats, lons):
 def def_meta_data():
 
     meta_data_keys = {
-        "qualityFlag": 'radioOccultationDataQualityFlags',
-        "geoid_height_above_reference_ellipsoid": 'geoidUndulation',
-        "sensor_azimuth_angle": 'bearingOrAzimuth',
-        "time": 'timeIncrement',
-        "earth_radius_of_curvature": 'earthLocalRadiusOfCurvature',
-        "occulting_sat_id": 'satelliteIdentifier',
-        "occulting_sat_is": 'satelliteInstruments',
-        "process_center": 'centre',
-        "reference_sat_id": 'platformTransmitterIdNumber',
-        "gnss_sat_class": 'satelliteClassification',
+        "qualityFlags": 'radioOccultationDataQualityFlags',
+        "geoidUndulation": 'geoidUndulation',
+        "sensorAzimuthAngle": 'bearingOrAzimuth',
+        # "timeIncrement": 'timeIncrement',
+        "earthRadiusCurvature": 'earthLocalRadiusOfCurvature',
+        "satelliteIdentifier": 'satelliteIdentifier',
+        "satelliteInstrument": 'satelliteInstruments',
+        "dataProviderOrigin": 'centre',
+        "satelliteTransmitterId": 'platformTransmitterIdNumber',
+        "satelliteConstellationRO": 'satelliteClassification',
     }
 
     return meta_data_keys
@@ -302,18 +315,18 @@ def def_meta_types():
     meta_data_types = {
         "latitude": "float",
         "longitude": "float",
-        "datetime": "string",
-        'impact_parameter': 'float',
-        'impact_height': 'float',
+        "dateTime": "long",
+        'impactParameterRO': 'float',
+        'impactHeightRO': 'float',
         'height': 'float',
-        "qualityFlag": 'integer',
-        "geoid_height_above_reference_ellipsoid": 'float',
-        "earth_radius_of_curvature": 'float',
-        "occulting_sat_id": 'integer',
-        "occulting_sat_is": 'integer',
-        "process_center": 'string',
-        "reference_sat_id": 'integer',
-        "gnss_sat_class": 'integer',
+        "qualityFlags": 'integer',
+        "geoidUndulation": 'float',
+        "earthRadiusCurvature": 'float',
+        "satelliteIdentifier": 'integer',
+        "satelliteInstrument": 'integer',
+        "dataProviderOrigin": 'string',
+        "satelliteTransmitterId": 'integer',
+        "satelliteConstellationRO": 'integer',
     }
 
     return meta_data_types
@@ -347,11 +360,13 @@ def concat_obs_dict(obs_data, append_obs_data):
         else:
             if obs_data[gv_key].dtype == float:
                 fill_data = np.repeat(float_missing_value, append_length, dtype=ioda_float_type)
+            elif obs_data[gv_key].dtype == np.int64:
+                fill_data = np.repeat(long_missing_value, append_length, dtype=np.int64)
             elif obs_data[gv_key].dtype == int:
                 fill_data = np.repeat(int_missing_value, append_length, dtype=ioda_int_type)
             elif obs_data[gv_key].dtype == object:
-                # string type, extend with empty strings
-                fill_data = np.repeat("", append_length, dtype=object)
+                # string type, extend with string missing value
+                fill_data = np.repeat(string_missing_value, append_length, dtype=object)
             obs_data[gv_key] = np.append(obs_data[gv_key], fill_data)
 
 
diff --git a/src/goes/goes.py b/src/goes/goes.py
index b1095e901..cfe4ac1b0 100644
--- a/src/goes/goes.py
+++ b/src/goes/goes.py
@@ -2,8 +2,8 @@
 # goes.py
 #
 # This class loads, calculates, filters, and makes accessible the variables and attributes required by the
-# GoesConverter class for a single GOES-16 or GOES-17 LB1 ABI channel (1-16). The brightness temperature and reflectance
-# factor calculations used in this class are derived from sections 3.4.1.2 and 3.4.1.3 in the
+# GoesConverter class for a single GOES-16 or GOES-17 LB1 ABI channel (1-16). The brightness temperature and albedo
+# calculations used in this class are derived from sections 3.4.1.2 and 3.4.1.3 in the
 # "GOES-R Advanced Baseline Imager (ABI) Algorithm Theoretical Basis Document For Cloud and Moisture Imagery Product
 # (CMIP)" Version 3.0 July 30, 2012 (https://www.star.nesdis.noaa.gov/goesr/docs/ATBD/Imagery.pdf). The calculations for
 # the propagation of standard error are from section 2.5.5 of the "NIST/SEMATECH e-Handbook of Statistical Methods"
@@ -184,7 +184,7 @@ def _load_rad_data_array(self):
 
     def _create_obsvalue_rf_data_array(self):
         """
-        Creates a local data array variable containing the calculated obsvalue reflectance factor data
+        Creates a local data array variable containing the calculated obsvalue albedo data
         after fill value filtering by the DQF flags.
         """
         self._obsvalue_rf_data_array = self._rad_data_array * self._kappa0
@@ -199,7 +199,7 @@ def _create_obsvalue_bt_data_array(self):
 
     def _create_obserror_rf_data_array(self):
         """
-        Creates a local data array variable containing the calculated obserror reflectance factor data
+        Creates a local data array variable containing the calculated obserror albedo data
         after fill value filtering by the DQF flags.
         """
         sqrt_comp = np.power(self._kappa0, 2) * np.power(self._std_dev_radiance_value_of_valid_pixels, 2)
@@ -225,7 +225,7 @@ def get_input_file_path(self):
 
     def get_obsvalue_rf_data_array(self):
         """
-        Returns the obsvalue reflectance factor data array.
+        Returns the obsvalue albedo data array.
         """
         return self._obsvalue_rf_data_array
 
@@ -237,7 +237,7 @@ def get_obsvalue_bt_data_array(self):
 
     def get_obserror_rf_data_array(self):
         """
-        Returns the obserror reflectance factor data array.
+        Returns the obserror albedo data array.
         """
         return self._obserror_rf_data_array
 
diff --git a/src/goes/goes_converter.py b/src/goes/goes_converter.py
index ae30730f4..c858a6572 100755
--- a/src/goes/goes_converter.py
+++ b/src/goes/goes_converter.py
@@ -17,24 +17,24 @@
 # /MetaData/dateTime
 # /MetaData/latitude -> units
 # /MetaData/longitude -> units
-# /MetaData/elevation_angle -> units
-# /MetaData/scan_angle -> units
-# /MetaData/scan_position
-# /MetaData/sensor_azimuth_angle -> units
-# /MetaData/sensor_view_angle -> units
-# /MetaData/sensor_zenith_angle -> units
-# /MetaData/solar_azimuth_angle -> units
-# /MetaData/solar_zenith_angle -> units
-# /MetaData/sensor_channel
-# /ObsError/reflectance_factor or /ObsError/brightness_temperature
-# /ObsValue/reflectance_factor or /ObsValue/brightness_temperature
-# /ObsError/brightness_temperature -> units
-# /ObsValue/brightness_temperature -> units
-# /PreQC/reflectance_factor or /PreQC/brightness_temperature
-# /PreQC/reflectance_factor -> flag_values or /PreQC/brightness_temperature -> flag_values
-# /PreQC/reflectance_factor -> flag_meanings or /PreQC/brightness_temperature -> flag_meanings
-# /nchans
-# /nlocs
+# /MetaData/sensorElevationAngle -> units
+# /MetaData/sensorScanAngle -> units
+# /MetaData/sensorScanPosition
+# /MetaData/sensorAzimuthAngle -> units
+# /MetaData/sensorViewAngle -> units
+# /MetaData/sensorZenithAngle -> units
+# /MetaData/solarAzimuthAngle -> units
+# /MetaData/solarZenithAngle -> units
+# /MetaData/sensorChannelNumber
+# /ObsError/albedo or /ObsError/brightnessTemperature
+# /ObsValue/albedo or /ObsValue/brightnessTemperature
+# /ObsError/brightnessTemperature -> units
+# /ObsValue/brightnessTemperature -> units
+# /PreQC/albedo or /PreQC/brightnessTemperature
+# /PreQC/albedo -> flag_values or /PreQC/brightnessTemperature -> flag_values
+# /PreQC/albedo -> flag_meanings or /PreQC/brightnessTemperature -> flag_meanings
+# /Channel
+# /Location
 #
 
 import os
@@ -56,9 +56,9 @@ def __init__(self, input_file_paths, latlon_file_path, output_file_path_rf, outp
         Constructor
         input_file_paths - A list of the absolute paths to all 16 ABI channels from the same hour
         latlon_file_path - The path to an existing GoesLatLon file or if it does not exist the path to write the file
-        output_file_path_rf - The path to write the IODAv2 reflectance factor data file
+        output_file_path_rf - The path to write the IODAv2 albedo (reflectance factor) data file
         output_file_path_bt - The path to write the IODAv2 brightness temperature data file
-        include_rf - Boolean value indicating whether to create the reflectance factor output data file: False (default)
+        include_rf - Boolean value indicating whether to create the albedo output data file: False (default)
         resolution - The resolution in km: 8 (default), 4, 8, 16, 32, 64
         """
         self._input_file_paths = input_file_paths
@@ -92,7 +92,7 @@ def _check_arguments(self):
 
     def _initialize(self):
         """
-        Create two local dictionaries contained the Goes class instances for reflectance factor (ABI channels 1-6)
+        Create two local dictionaries contained the Goes class instances for albedo (ABI channels 1-6)
         and brightness temperature (ABI channels 7-16). This function also assigns the file path for a template GOES file
         from ABI channel 7.
         """
@@ -161,7 +161,7 @@ def _create_metadata_latitude_variable(self, output_dataset):
         output_dataset - A netCDF Dataset object
         """
         latitude_data_array = self._latlon_dataset['MetaData'].variables['latitude'][:].real
-        output_dataset.createVariable('/MetaData/latitude', 'f4', 'nlocs', fill_value=-999)
+        output_dataset.createVariable('/MetaData/latitude', 'f4', 'Location', fill_value=-999)
         output_dataset['/MetaData/latitude'][:] = latitude_data_array
         output_dataset['/MetaData/latitude'].setncattr('units', 'degrees_north')
 
@@ -171,72 +171,72 @@ def _create_metadata_longitude_variable(self, output_dataset):
         output_dataset - A netCDF4 Dataset object
         """
         longitude_data_array = self._latlon_dataset['MetaData'].variables['longitude'][:].real
-        output_dataset.createVariable('/MetaData/longitude', 'f4', 'nlocs', fill_value=-999)
+        output_dataset.createVariable('/MetaData/longitude', 'f4', 'Location', fill_value=-999)
         output_dataset['/MetaData/longitude'][:] = longitude_data_array
         output_dataset['/MetaData/longitude'].setncattr('units', 'degrees_east')
 
     def _create_metadata_scan_angle_variable(self, output_dataset):
         """
-        Creates the /MetaData/scan_angle variable in an output netCDF4 dataset.
+        Creates the /MetaData/sensorScanAngle variable in an output netCDF4 dataset.
         output_dataset - A netCDF4 Dataset object
         """
-        scan_angle_data_array = self._latlon_dataset['MetaData'].variables['scan_angle'][:].real
-        output_dataset.createVariable('/MetaData/scan_angle', 'f4', 'nlocs', fill_value=-999)
-        output_dataset['/MetaData/scan_angle'][:] = scan_angle_data_array
-        output_dataset['/MetaData/scan_angle'].setncattr('units', 'degrees')
+        scan_angle_data_array = self._latlon_dataset['MetaData'].variables['sensorScanAngle'][:].real
+        output_dataset.createVariable('/MetaData/sensorScanAngle', 'f4', 'Location', fill_value=-999)
+        output_dataset['/MetaData/sensorScanAngle'][:] = scan_angle_data_array
+        output_dataset['/MetaData/sensorScanAngle'].setncattr('units', 'degrees')
 
     def _create_metadata_elevation_angle_variable(self, output_dataset):
         """
-        Creates the /MetaData/elevation_angle variable in an output netCDF4 dataset.
+        Creates the /MetaData/sensorElevationAngle variable in an output netCDF4 dataset.
         output_dataset - A netCDF4 Dataset object
         """
-        elevation_angle_data_array = self._latlon_dataset['MetaData'].variables['elevation_angle'][:].real
-        output_dataset.createVariable('/MetaData/elevation_angle', 'f4', 'nlocs', fill_value=-999)
-        output_dataset['/MetaData/elevation_angle'][:] = elevation_angle_data_array
-        output_dataset['/MetaData/elevation_angle'].setncattr('units', 'degrees')
+        elevation_angle_data_array = self._latlon_dataset['MetaData'].variables['sensorElevationAngle'][:].real
+        output_dataset.createVariable('/MetaData/sensorElevationAngle', 'f4', 'Location', fill_value=-999)
+        output_dataset['/MetaData/sensorElevationAngle'][:] = elevation_angle_data_array
+        output_dataset['/MetaData/sensorElevationAngle'].setncattr('units', 'degrees')
 
     def _create_metadata_scan_position_variable(self, output_dataset):
         """
-        Creates the /MetaData/scan_position variable in an output netCDF4 dataset.
+        Creates the /MetaData/sensorScanPosition variable in an output netCDF4 dataset.
         output_dataset - A netCDF4 Dataset object
         """
-        scan_position_data_array = self._latlon_dataset['MetaData'].variables['scan_position'][:].real
-        output_dataset.createVariable('/MetaData/scan_position', 'f4', 'nlocs', fill_value=-999)
-        output_dataset['/MetaData/scan_position'][:] = scan_position_data_array
+        scan_position_data_array = self._latlon_dataset['MetaData'].variables['sensorScanPosition'][:].real
+        output_dataset.createVariable('/MetaData/sensorScanPosition', 'f4', 'Location', fill_value=-999)
+        output_dataset['/MetaData/sensorScanPosition'][:] = scan_position_data_array
 
     def _create_metadata_sensor_zenith_angle_variable(self, output_dataset):
         """
-        Creates the /MetaData/sensor_zenith_angle variable in an output netCDF4 dataset.
+        Creates the /MetaData/sensorZenithAngle variable in an output netCDF4 dataset.
         output_dataset - A netCDF4 Dataset object
         """
-        sensor_zenith_angle_data_array = self._latlon_dataset['MetaData'].variables['sensor_zenith_angle'][:].real
-        output_dataset.createVariable('/MetaData/sensor_zenith_angle', 'f4', 'nlocs', fill_value=-999)
-        output_dataset['/MetaData/sensor_zenith_angle'][:] = sensor_zenith_angle_data_array
-        output_dataset['/MetaData/sensor_zenith_angle'].setncattr('units', 'degrees')
+        sensor_zenith_angle_data_array = self._latlon_dataset['MetaData'].variables['sensorZenithAngle'][:].real
+        output_dataset.createVariable('/MetaData/sensorZenithAngle', 'f4', 'Location', fill_value=-999)
+        output_dataset['/MetaData/sensorZenithAngle'][:] = sensor_zenith_angle_data_array
+        output_dataset['/MetaData/sensorZenithAngle'].setncattr('units', 'degrees')
 
     def _create_metadata_sensor_azimuth_angle_variable(self, output_dataset):
         """
-        Creates the /MetaData/sensor_azimuth_angle variable in an output netCDF4 dataset.
+        Creates the /MetaData/sensorAzimuthAngle variable in an output netCDF4 dataset.
         output_dataset - A netCDF4 Dataset object
         """
-        sensor_azimuth_angle_data_array = self._latlon_dataset['MetaData'].variables['sensor_azimuth_angle'][:].real
-        output_dataset.createVariable('/MetaData/sensor_azimuth_angle', 'f4', 'nlocs', fill_value=-999)
-        output_dataset['/MetaData/sensor_azimuth_angle'][:] = sensor_azimuth_angle_data_array
-        output_dataset['/MetaData/sensor_azimuth_angle'].setncattr('units', 'degrees')
+        sensor_azimuth_angle_data_array = self._latlon_dataset['MetaData'].variables['sensorAzimuthAngle'][:].real
+        output_dataset.createVariable('/MetaData/sensorAzimuthAngle', 'f4', 'Location', fill_value=-999)
+        output_dataset['/MetaData/sensorAzimuthAngle'][:] = sensor_azimuth_angle_data_array
+        output_dataset['/MetaData/sensorAzimuthAngle'].setncattr('units', 'degrees')
 
     def _create_metadata_sensor_view_angle_variable(self, output_dataset):
         """
-        Creates the /MetaData/sensor_view_angle variable in an output netCDF4 dataset.
+        Creates the /MetaData/sensorViewAngle variable in an output netCDF4 dataset.
         output_dataset - A netCDF4 Dataset object
         """
-        sensor_view_angle_data_array = self._latlon_dataset['MetaData'].variables['sensor_view_angle'][:].real
-        output_dataset.createVariable('/MetaData/sensor_view_angle', 'f4', 'nlocs', fill_value=-999)
-        output_dataset['/MetaData/sensor_view_angle'][:] = sensor_view_angle_data_array
-        output_dataset['/MetaData/sensor_view_angle'].setncattr('units', 'degrees')
+        sensor_view_angle_data_array = self._latlon_dataset['MetaData'].variables['sensorViewAngle'][:].real
+        output_dataset.createVariable('/MetaData/sensorViewAngle', 'f4', 'Location', fill_value=-999)
+        output_dataset['/MetaData/sensorViewAngle'][:] = sensor_view_angle_data_array
+        output_dataset['/MetaData/sensorViewAngle'].setncattr('units', 'degrees')
 
     def _create_metadata_solar_zenith_angle_variable(self, output_dataset):
         """
-        Creates the /MetaData/solar_zenith_angle variable in an output netCDF4 dataset.
+        Creates the /MetaData/solarZenithAngle variable in an output netCDF4 dataset.
         output_dataset - A netCDF4 Dataset object
         """
         dataset = Dataset(self._input_file_path_template, 'r')
@@ -269,13 +269,13 @@ def _create_metadata_solar_zenith_angle_variable(self, output_dataset):
         dataset.close()
         dataset_latlon.close()
         solar_zenith_angle_data_array = np.nan_to_num(solar_zenith_angle_data_array, nan=-999)
-        output_dataset.createVariable('/MetaData/solar_zenith_angle', 'f4', 'nlocs', fill_value=-999)
-        output_dataset['/MetaData/solar_zenith_angle'][:] = solar_zenith_angle_data_array
-        output_dataset['/MetaData/solar_zenith_angle'].setncattr('units', 'degrees')
+        output_dataset.createVariable('/MetaData/solarZenithAngle', 'f4', 'Location', fill_value=-999)
+        output_dataset['/MetaData/solarZenithAngle'][:] = solar_zenith_angle_data_array
+        output_dataset['/MetaData/solarZenithAngle'].setncattr('units', 'degrees')
 
     def _create_metadata_solar_azimuth_angle_variable(self, output_dataset):
         """
-        Creates the /MetaData/solar_azimuth_angle variable in an output netCDF4 dataset.
+        Creates the /MetaData/solarAzimuthAngle variable in an output netCDF4 dataset.
         output_dataset - A netCDF4 Dataset object
         """
         dataset = Dataset(self._input_file_path_template, 'r')
@@ -299,20 +299,20 @@ def _create_metadata_solar_azimuth_angle_variable(self, output_dataset):
         dataset.close()
         dataset_latlon.close()
         solar_azimuth_angle_data_array = np.nan_to_num(solar_azimuth_angle_data_array, nan=-999)
-        output_dataset.createVariable('/MetaData/solar_azimuth_angle', 'f4', 'nlocs', fill_value=-999)
-        output_dataset['/MetaData/solar_azimuth_angle'][:] = solar_azimuth_angle_data_array
-        output_dataset['/MetaData/solar_azimuth_angle'].setncattr('units', 'degrees')
+        output_dataset.createVariable('/MetaData/solarAzimuthAngle', 'f4', 'Location', fill_value=-999)
+        output_dataset['/MetaData/solarAzimuthAngle'][:] = solar_azimuth_angle_data_array
+        output_dataset['/MetaData/solarAzimuthAngle'].setncattr('units', 'degrees')
 
-    def _create_nlocs_dimension(self, output_dataset):
+    def _create_location_dimension(self, output_dataset):
         """
-        Creates the nlocs dimension in an output netCDF4 dataset.
+        Creates the Location dimension in an output netCDF4 dataset.
         output_dataset - A netCDF4 Dataset object
         """
-        nlocs = self._latlon_dataset.dimensions['nlocs'].size
-        output_dataset.createDimension('nlocs', nlocs)
-        output_dataset.createVariable('nlocs', 'i4', 'nlocs')
-        output_dataset.variables['nlocs'].setncattr('suggested_chunk_dim', nlocs)
-        output_dataset.variables['nlocs'][:] = np.arange(1, nlocs + 1, 1, dtype='int32')
+        Location = self._latlon_dataset.dimensions['Location'].size
+        output_dataset.createDimension('Location', Location)
+        output_dataset.createVariable('Location', 'i4', 'Location')
+        output_dataset.variables['Location'].setncattr('suggested_chunk_dim', round(Location*0.01))
+        output_dataset.variables['Location'][:] = np.arange(1, Location + 1, 1, dtype='int32')
 
     @staticmethod
     def _create_groups(output_dataset):
@@ -326,28 +326,28 @@ def _create_groups(output_dataset):
         output_dataset.createGroup('PreQC')
 
     @staticmethod
-    def _create_nchans_dimension(output_dataset, nchans):
+    def _create_channel_dimension(output_dataset, Channel):
         """
-        Creates the nchans dimension in an output netCDF4 dataset.
+        Creates the Channel dimension in an output netCDF4 dataset.
         output_dataset - A netCDF4 Dataset object
-        nchans - An integer indicating the number of nchans: 6 (for reflectance factor)
+        Channel - An integer indicating the number of Channel: 6 (for albedo)
                                                           or 10 (for brightness temperature)
         """
-        output_dataset.createDimension('nchans', nchans)
-        output_dataset.createVariable('nchans', 'i4', 'nchans')
-        if nchans == 6:
-            output_dataset.variables['nchans'][:] = [1, 2, 3, 4, 5, 6]
-        elif nchans == 10:
-            output_dataset.variables['nchans'][:] = [7, 8, 9, 10, 11, 12, 13, 14, 15, 16]
+        output_dataset.createDimension('Channel', Channel)
+        output_dataset.createVariable('Channel', 'i4', 'Channel')
+        if Channel == 6:
+            output_dataset.variables['Channel'][:] = [1, 2, 3, 4, 5, 6]
+        elif Channel == 10:
+            output_dataset.variables['Channel'][:] = [7, 8, 9, 10, 11, 12, 13, 14, 15, 16]
 
     @staticmethod
     def _create_metadata_sensor_channel_variable(output_dataset):
         """
-        Creates the /MetaData/sensor_channel variable in an output netCDF4 dataset.
+        Creates the /MetaData/sensorChannelNumber variable in an output netCDF4 dataset.
         output_dataset - A netCDF4 Dataset object
         """
-        output_dataset.createVariable('/MetaData/sensor_channel', 'i4', 'nchans')
-        output_dataset['/MetaData/sensor_channel'][:] = output_dataset['nchans'][:]
+        output_dataset.createVariable('/MetaData/sensorChannelNumber', 'i4', 'Channel')
+        output_dataset['/MetaData/sensorChannelNumber'][:] = output_dataset['Channel'][:]
 
     @staticmethod
     def _create_root_group_attributes(output_dataset, resolution, platform_id):
@@ -361,16 +361,16 @@ def _create_root_group_attributes(output_dataset, resolution, platform_id):
         output_dataset.setncattr('platform_identifier', platform_id)
 
     @staticmethod
-    def _get_nlocs(dataset):
+    def _get_Location(dataset):
         """
-        Returns the nlocs dimension size for the provided netCDF4 Dataset.
-        dataset - the dataset to extract the nlocs size
+        Returns the Location dimension size for the provided netCDF4 Dataset.
+        dataset - the dataset to extract the Location size
         """
-        return dataset.dimensions['nlocs'].size
+        return dataset.dimensions['Location'].size
 
-    def _create_preqc_reflectance_factor_variable(self, output_dataset):
+    def _create_preqc_albedo_variable(self, output_dataset):
         """
-        Creates the /PreQC/reflectance_factor variable variable and associated attributes in an output netCDF4 dataset.
+        Creates the /PreQC/albedo variable and associated attributes in an output netCDF4 dataset.
         output_dataset - A netCDF4 Dataset object
         """
         temp_dict = {}
@@ -382,16 +382,16 @@ def _create_preqc_reflectance_factor_variable(self, output_dataset):
         data_array = temp_dict[0]
         for i in range(1, counter):
             data_array = np.column_stack((data_array, temp_dict[i]))
-        output_dataset.createVariable('/PreQC/reflectance_factor', 'i4', ('nlocs', 'nchans'), fill_value=-999)
-        output_dataset['/PreQC/reflectance_factor'][:] = data_array
-        output_dataset['/PreQC/reflectance_factor'].setncattr('flag_values', '0,1,2,3')
-        output_dataset['/PreQC/reflectance_factor'].setncattr('flag_meanings',
-                                                              'good_pixel_qf,conditionally_usable_pixel_qf,'
-                                                              'out_of_range_pixel_qf,no_value_pixel_qf')
+        output_dataset.createVariable('/PreQC/albedo', 'i4', ('Location', 'Channel'), fill_value=-999)
+        output_dataset['/PreQC/albedo'][:] = data_array
+        output_dataset['/PreQC/albedo'].setncattr('flag_values', '0,1,2,3')
+        output_dataset['/PreQC/albedo'].setncattr('flag_meanings',
+                                                  'good_pixel_qf,conditionally_usable_pixel_qf,'
+                                                  'out_of_range_pixel_qf,no_value_pixel_qf')
 
     def _create_preqc_brightness_temperature_variable(self, output_dataset):
         """
-        Creates the /PreQC/brightness_temperature variable and associated attributes in an output netCDF4 dataset.
+        Creates the /PreQC/brightnessTemperature variable and associated attributes in an output netCDF4 dataset.
         output_dataset - A netCDF4 Dataset object
         """
         temp_dict = {}
@@ -403,17 +403,17 @@ def _create_preqc_brightness_temperature_variable(self, output_dataset):
         data_array = temp_dict[0]
         for i in range(1, counter):
             data_array = np.column_stack((data_array, temp_dict[i]))
-        output_dataset.createVariable('/PreQC/brightness_temperature', 'i4', ('nlocs', 'nchans'),
+        output_dataset.createVariable('/PreQC/brightnessTemperature', 'i4', ('Location', 'Channel'),
                                       fill_value=-999)
-        output_dataset['/PreQC/brightness_temperature'][:] = data_array
-        output_dataset['/PreQC/brightness_temperature'].setncattr('flag_values', '0,1,2,3')
-        output_dataset['/PreQC/brightness_temperature'].setncattr('flag_meanings',
-                                                                  'good_pixel_qf,conditionally_usable_pixel_qf,'
-                                                                  'out_of_range_pixel_qf,no_value_pixel_qf')
+        output_dataset['/PreQC/brightnessTemperature'][:] = data_array
+        output_dataset['/PreQC/brightnessTemperature'].setncattr('flag_values', '0,1,2,3')
+        output_dataset['/PreQC/brightnessTemperature'].setncattr('flag_meanings',
+                                                                 'good_pixel_qf,conditionally_usable_pixel_qf,'
+                                                                 'out_of_range_pixel_qf,no_value_pixel_qf')
 
-    def _create_obsvalue_reflectance_factor_variable(self, output_dataset):
+    def _create_obsvalue_albedo_variable(self, output_dataset):
         """
-        Creates the /ObsValue/reflectance_factor variable in an output netCDF4 dataset.
+        Creates the /ObsValue/albedo variable in an output netCDF4 dataset.
         output_dataset - A netCDF4 Dataset object
         """
         temp_dict = {}
@@ -425,13 +425,13 @@ def _create_obsvalue_reflectance_factor_variable(self, output_dataset):
         data_array = temp_dict[0]
         for i in range(1, counter):
             data_array = np.column_stack((data_array, temp_dict[i]))
-        output_dataset.createVariable('/ObsValue/reflectance_factor', 'f4', ('nlocs', 'nchans'),
+        output_dataset.createVariable('/ObsValue/albedo', 'f4', ('Location', 'Channel'),
                                       fill_value=-999)
-        output_dataset['/ObsValue/reflectance_factor'][:] = data_array
+        output_dataset['/ObsValue/albedo'][:] = data_array
 
     def _create_obsvalue_brightness_temperature_variable(self, output_dataset):
         """
-        Creates the /ObsValue/brightness_temperature variable in an output netCDF4 dataset.
+        Creates the /ObsValue/brightnessTemperature variable in an output netCDF4 dataset.
         output_dataset - A netCDF4 Dataset object
         """
         temp_dict = {}
@@ -443,14 +443,14 @@ def _create_obsvalue_brightness_temperature_variable(self, output_dataset):
         data_array = temp_dict[0]
         for i in range(1, counter):
             data_array = np.column_stack((data_array, temp_dict[i]))
-        output_dataset.createVariable('/ObsValue/brightness_temperature', 'f4', ('nlocs', 'nchans'),
+        output_dataset.createVariable('/ObsValue/brightnessTemperature', 'f4', ('Location', 'Channel'),
                                       fill_value=-999)
-        output_dataset['/ObsValue/brightness_temperature'][:] = data_array
-        output_dataset['/ObsValue/brightness_temperature'].setncattr('units', 'K')
+        output_dataset['/ObsValue/brightnessTemperature'][:] = data_array
+        output_dataset['/ObsValue/brightnessTemperature'].setncattr('units', 'K')
 
-    def _create_obserror_reflectance_factor_variable(self, output_dataset):
+    def _create_obserror_albedo_variable(self, output_dataset):
         """
-        Creates the /ObsError/reflectance_factor variable in an output netCDF4 dataset.
+        Creates the /ObsError/albedo variable in an output netCDF4 dataset.
         output_dataset - A netCDF4 Dataset object
         """
         temp_dict = {}
@@ -462,13 +462,13 @@ def _create_obserror_reflectance_factor_variable(self, output_dataset):
         data_array = temp_dict[0]
         for i in range(1, counter):
             data_array = np.column_stack((data_array, temp_dict[i]))
-        output_dataset.createVariable('/ObsError/reflectance_factor', 'f4', ('nlocs', 'nchans'),
+        output_dataset.createVariable('/ObsError/albedo', 'f4', ('Location', 'Channel'),
                                       fill_value=-999)
-        output_dataset['/ObsError/reflectance_factor'][:] = data_array
+        output_dataset['/ObsError/albedo'][:] = data_array
 
     def _create_obserror_brightness_temperature_variable(self, output_dataset):
         """
-        Creates the /ObsError/brightness_temperature variable in an output netCDF4 dataset.
+        Creates the /ObsError/brightnessTemperature variable in an output netCDF4 dataset.
         output_dataset - A netCDF4 Dataset object
         """
         temp_dict = {}
@@ -480,10 +480,10 @@ def _create_obserror_brightness_temperature_variable(self, output_dataset):
         data_array = temp_dict[0]
         for i in range(1, counter):
             data_array = np.column_stack((data_array, temp_dict[i]))
-        output_dataset.createVariable('/ObsError/brightness_temperature', 'f4', ('nlocs', 'nchans'),
+        output_dataset.createVariable('/ObsError/brightnessTemperature', 'f4', ('Location', 'Channel'),
                                       fill_value=-999)
-        output_dataset['/ObsError/brightness_temperature'][:] = data_array
-        output_dataset['/ObsError/brightness_temperature'].setncattr('units', 'K')
+        output_dataset['/ObsError/brightnessTemperature'][:] = data_array
+        output_dataset['/ObsError/brightnessTemperature'].setncattr('units', 'K')
 
     def _create_metadata_time_variable(self, output_dataset):
         """
@@ -495,9 +495,9 @@ def _create_metadata_time_variable(self, output_dataset):
         time_offset = round((self._start_date - epoch).total_seconds())   # seconds since epoch.
         start_date = self._start_date.strftime('%Y-%m-%dT%H:%M:%SZ')
         output_dataset.setncattr("date_time", start_date)
-        datetime_array = np.full(self._get_nlocs(output_dataset), np.int64(time_offset))
+        datetime_array = np.full(self._get_Location(output_dataset), np.int64(time_offset))
 
-        output_dataset.createVariable('/MetaData/dateTime', 'i8', 'nlocs')
+        output_dataset.createVariable('/MetaData/dateTime', 'i8', 'Location')
         output_dataset['/MetaData/dateTime'][:] = datetime_array
         output_dataset['/MetaData/dateTime'].setncattr('units', iso8601_string)
 
@@ -513,7 +513,7 @@ def _load_all_goes(self):
 
     def convert(self):
         """
-        Creates the reflectance factor (if include_rf is True) and brightness temperature IODAv2 data files.
+        Creates the albedo (if include_rf is True) and brightness temperature IODAv2 data files.
         This functions also checks for the existence and nadir change of the GoesLatLon data file.
         """
         self._initialize()
@@ -538,8 +538,8 @@ def _convert_bt(self):
         dataset = Dataset(self._output_file_path_bt, 'w')
         GoesConverter._create_groups(dataset)
         GoesConverter._create_root_group_attributes(dataset, self._resolution, self._platform_id)
-        GoesConverter._create_nchans_dimension(dataset, 10)
-        self._create_nlocs_dimension(dataset)
+        GoesConverter._create_channel_dimension(dataset, 10)
+        self._create_location_dimension(dataset)
         GoesConverter._create_metadata_sensor_channel_variable(dataset)
         self._create_metadata_latitude_variable(dataset)
         self._create_metadata_longitude_variable(dataset)
@@ -559,13 +559,13 @@ def _convert_bt(self):
 
     def _convert_rf(self):
         """
-        Creates the reflectance factor IODAv2 data file.
+        Creates the albedo IODAv2 data file.
         """
         dataset = Dataset(self._output_file_path_rf, 'w')
         GoesConverter._create_groups(dataset)
         GoesConverter._create_root_group_attributes(dataset, self._resolution, self._platform_id)
-        GoesConverter._create_nchans_dimension(dataset, 6)
-        self._create_nlocs_dimension(dataset)
+        GoesConverter._create_channel_dimension(dataset, 6)
+        self._create_location_dimension(dataset)
         GoesConverter._create_metadata_sensor_channel_variable(dataset)
         self._create_metadata_latitude_variable(dataset)
         self._create_metadata_longitude_variable(dataset)
@@ -578,7 +578,7 @@ def _convert_rf(self):
         self._create_metadata_solar_zenith_angle_variable(dataset)
         self._create_metadata_solar_azimuth_angle_variable(dataset)
         self._create_metadata_time_variable(dataset)
-        self._create_obsvalue_reflectance_factor_variable(dataset)
-        self._create_obserror_reflectance_factor_variable(dataset)
-        self._create_preqc_reflectance_factor_variable(dataset)
+        self._create_obsvalue_albedo_variable(dataset)
+        self._create_obserror_albedo_variable(dataset)
+        self._create_preqc_albedo_variable(dataset)
         dataset.close()
diff --git a/src/goes/goes_latlon.py b/src/goes/goes_latlon.py
index 6309eecdb..781055c02 100644
--- a/src/goes/goes_latlon.py
+++ b/src/goes/goes_latlon.py
@@ -13,17 +13,17 @@
 #
 # /GROUP/VARIABLE -> ATTRIBUTE
 #
-# /MetaData/elevation_angle
-# /MetaData/scan_angle
-# /MetaData/scan_position
-# /MetaData/sensor_azimuth_angle -> units
-# /MetaData/sensor_view_angle -> units
-# /MetaData/sensor_zenith_angle -> units
+# /MetaData/sensorElevationAngle
+# /MetaData/sensorScanAngle
+# /MetaData/sensorScanPosition
+# /MetaData/sensorAzimuthAngle
+# /MetaData/sensorViewAngle
+# /MetaData/sensorZenithAngle
 # /MetaData/latitude
 # /MetaData/latitude -> lat_nadir
 # /MetaData/longitude
 # /MetaData/longitude -> lon_nadir
-# /nlocs
+# /Location
 #
 from netCDF4 import Dataset
 from numpy import ma
@@ -192,31 +192,31 @@ def create(self):
         sensor_zenith_angle, sensor_azimuth_angle, sensor_view_angle = \
             self._calc_sensor_zenith_azimuth_view_angles(latitude, longitude)
         latlon_dataset = Dataset(self._latlon_file_path, 'w')
-        nlocs = len(latitude)
-        latlon_dataset.createDimension('nlocs', nlocs)
-        latlon_dataset.createVariable('nlocs', 'i4', ('nlocs',))
-        latlon_dataset.variables['nlocs'][:] = np.arange(1, nlocs + 1, 1, dtype='int32')
+        Location = len(latitude)
+        latlon_dataset.createDimension('Location', Location)
+        latlon_dataset.createVariable('Location', 'i4', ('Location',))
+        latlon_dataset.variables['Location'][:] = np.arange(1, Location + 1, 1, dtype='int32')
         nonexistent_indices = len(self._lat_fill_value_index_array[0])
         latlon_dataset.createDimension('nonexistent_indices', nonexistent_indices)
         latlon_dataset.createVariable('nonexistent_indices', 'i4', ('nonexistent_indices',))
         latlon_dataset.variables['nonexistent_indices'][:] = np.array(self._lat_fill_value_index_array[0])
         latlon_dataset.createGroup('MetaData')
-        latlon_dataset.createVariable('/MetaData/latitude', 'f4', 'nlocs', fill_value=-999)
-        latlon_dataset.createVariable('/MetaData/longitude', 'f4', 'nlocs', fill_value=-999)
-        latlon_dataset.createVariable('/MetaData/scan_angle', 'f4', 'nlocs', fill_value=-999)
-        latlon_dataset.createVariable('/MetaData/scan_position', 'i4', 'nlocs', fill_value=-999)
-        latlon_dataset.createVariable('/MetaData/elevation_angle', 'f4', 'nlocs', fill_value=-999)
-        latlon_dataset.createVariable('/MetaData/sensor_zenith_angle', 'f4', 'nlocs', fill_value=-999)
-        latlon_dataset.createVariable('/MetaData/sensor_azimuth_angle', 'f4', 'nlocs', fill_value=-999)
-        latlon_dataset.createVariable('/MetaData/sensor_view_angle', 'f4', 'nlocs', fill_value=-999)
+        latlon_dataset.createVariable('/MetaData/latitude', 'f4', 'Location', fill_value=-999)
+        latlon_dataset.createVariable('/MetaData/longitude', 'f4', 'Location', fill_value=-999)
+        latlon_dataset.createVariable('/MetaData/sensorScanAngle', 'f4', 'Location', fill_value=-999)
+        latlon_dataset.createVariable('/MetaData/sensorScanPosition', 'i4', 'Location', fill_value=-999)
+        latlon_dataset.createVariable('/MetaData/sensorElevationAngle', 'f4', 'Location', fill_value=-999)
+        latlon_dataset.createVariable('/MetaData/sensorZenithAngle', 'f4', 'Location', fill_value=-999)
+        latlon_dataset.createVariable('/MetaData/sensorAzimuthAngle', 'f4', 'Location', fill_value=-999)
+        latlon_dataset.createVariable('/MetaData/sensorViewAngle', 'f4', 'Location', fill_value=-999)
         latlon_dataset['/MetaData/latitude'][:] = latitude
         latlon_dataset['/MetaData/longitude'][:] = longitude
-        latlon_dataset['/MetaData/scan_angle'][:] = scan_angle
-        latlon_dataset['/MetaData/scan_position'][:] = scan_position
-        latlon_dataset['/MetaData/elevation_angle'][:] = elevation_angle
-        latlon_dataset['/MetaData/sensor_zenith_angle'][:] = sensor_zenith_angle
-        latlon_dataset['/MetaData/sensor_azimuth_angle'][:] = sensor_azimuth_angle
-        latlon_dataset['/MetaData/sensor_view_angle'][:] = sensor_view_angle
+        latlon_dataset['/MetaData/sensorScanAngle'][:] = scan_angle
+        latlon_dataset['/MetaData/sensorScanPosition'][:] = scan_position
+        latlon_dataset['/MetaData/sensorElevationAngle'][:] = elevation_angle
+        latlon_dataset['/MetaData/sensorZenithAngle'][:] = sensor_zenith_angle
+        latlon_dataset['/MetaData/sensorAzimuthAngle'][:] = sensor_azimuth_angle
+        latlon_dataset['/MetaData/sensorViewAngle'][:] = sensor_view_angle
         lat_nadir, lon_nadir = self._get_nadir_attributes()
         latlon_dataset['/MetaData/latitude'].setncattr('lat_nadir', lat_nadir)
         latlon_dataset['/MetaData/longitude'].setncattr('lon_nadir', lon_nadir)
diff --git a/src/gsi-ncdiag/gsi_ncdiag.py b/src/gsi-ncdiag/gsi_ncdiag.py
index a216d4c64..8f149aa12 100644
--- a/src/gsi-ncdiag/gsi_ncdiag.py
+++ b/src/gsi-ncdiag/gsi_ncdiag.py
@@ -80,38 +80,60 @@
     # 132 are dropsondes
 }
 
+# WMO satellite IDs
+wmo_satid = {
+    'aqua': 784,
+    'metop-a': 4,
+    'metop-b': 3,
+    'metop-c': 5,
+    'noaa-15': 206,
+    'noaa-18': 209,
+    'noaa-19': 223,
+    'noaa-20': 225,
+    'npp': 224,
+}
+
+wmo_instid = {
+    'amsua': 570,
+    'atms': 621,
+    'iasi': 221,
+    'abi': 617,
+    'omps': 947,
+    'sbuv': 956,
+}
+
 # LocKeyList = { 'gsiname':('IODAname','dtype')}
 all_LocKeyList = {
-    'Station_ID': ('station_id', 'string'),
-    'Time': ('datetime', 'string'),
+    'Station_ID': ('stationIdentification', 'string'),
+    'Time': ('dateTime', 'string'),
     'time': ('time', 'string'),
-    'ascending_flag': ('ascending_flag', 'string'),
-    'earth_radius_of_curvature': ('earth_radius_of_curvature', 'string'),
-    'reference_sat_id': ('reference_sat_id', 'string'),
-    'occulting_sat_id': ('occulting_sat_id', 'string'),
-    'record_number': ('record_number', 'string'),
-    'geoid_height_above_reference_ellipsoid': ('geoid_height_above_reference_ellipsoid', 'string'),
-    'gnss_sat_class': ('gnss_sat_class', 'string'),
-    'impact_height': ('impact_height', 'string'),
-    'impact_parameter': ('impact_parameter', 'string'),
+    'ascending_flag': ('satelliteAscendingFlag', 'integer'),
+    'earth_radius_of_curvature': ('earthRadiusCurvature', 'float'),
+    'reference_sat_id': ('satelliteTransmitterId', 'integer'),
+    'occulting_sat_id': ('satelliteIdentifier', 'integer'),
+    'record_number': ('sequenceNumber', 'integer'),
+    'geoid_height_above_reference_ellipsoid': ('geoidUndulation', 'float'),
+    'gnss_sat_class': ('satelliteConstellationRO', 'string'),
+    'impact_height': ('impactHeightRO', 'float'),
+    'impact_parameter': ('impactParameterRO', 'float'),
     'Latitude': ('latitude', 'float'),
     'Longitude': ('longitude', 'float'),
-    'Station_Elevation': ('station_elevation', 'float'),
-    'Pressure': ('air_pressure', 'float'),
+    'Station_Elevation': ('stationElevation', 'float'),
+    'Pressure': ('pressure', 'float'),
     'Height': ('height', 'float'),
-    'Elevation': ('height_above_mean_sea_level', 'float'),
-    'Obs_Time': ('datetime', 'string'),
-    'Scan_Position': ('scan_position', 'float'),
-    'Sat_Zenith_Angle': ('sensor_zenith_angle', 'float'),
-    'Sat_Azimuth_Angle': ('sensor_azimuth_angle', 'float'),
-    'Sol_Zenith_Angle': ('solar_zenith_angle', 'float'),
-    'Sol_Azimuth_Angle': ('solar_azimuth_angle', 'float'),
-    'Scan_Angle': ('sensor_view_angle', 'float'),
-    'Surface_type': ('surface_type', 'integer'),
-    'Dominant_Sfc_Type': ('surface_type', 'integer'),
+    'Elevation': ('heightOfSurface', 'float'),
+    'Obs_Time': ('dateTime', 'string'),
+    'Scan_Position': ('sensorScanPosition', 'float'),
+    'Sat_Zenith_Angle': ('sensorZenithAngle', 'float'),
+    'Sat_Azimuth_Angle': ('sensorAzimuthAngle', 'float'),
+    'Sol_Zenith_Angle': ('solarZenithAngle', 'float'),
+    'Sol_Azimuth_Angle': ('solarAzimuthAngle', 'float'),
+    'Scan_Angle': ('sensorViewAngle', 'float'),
+    'Surface_type': ('surfaceQualifier', 'integer'),
+    'Dominant_Sfc_Type': ('surfaceQualifier', 'integer'),
     'MODIS_deep_blue_flag': ('modis_deep_blue_flag', 'integer'),
-    'Reference_Pressure': ('air_pressure', 'float'),
-    'Solar_Zenith_Angle': ('solar_zenith_angle', 'float'),
+    'Reference_Pressure': ('pressure', 'float'),
+    'Solar_Zenith_Angle': ('solarZenithAngle', 'float'),
     'Row_Anomaly_Index': ('row_anomaly_index', 'float'),
     'TopLevelPressure': ('top_level_pressure', 'float'),
     'BottomLevelPressure': ('bottom_level_pressure', 'float'),
@@ -121,29 +143,29 @@
     'YoverR': ('radar_tilt', 'float'),
     'ZoverR': ('radar_dir3', 'float'),
     'Vterminal': ('vterminal', 'float'),
-    'SWCM_spec_type': ('satwind_spectral_type', 'float'),
-    'SAZA_sat_zen_angle': ('sensor_zenith_angle', 'float'),
-    'SCCF_chan_wavelen': ('channel_wavelength', 'float'),
-    'QI_with_FC': ('satwind_quality_ind_with_fc', 'float'),
-    'QI_without_FC': ('satwind_quality_ind_no_fc', 'float'),
-    'Data_Vertical_Velocity': ('data_vertical_velocity', 'float'),
-    'LaunchTime': ('LaunchTime', 'float'),
+    'SWCM_spec_type': ('windComputationMethod', 'integer'),
+    'SAZA_sat_zen_angle': ('sensorZenithAngle', 'float'),
+    'SCCF_chan_wavelen': ('sensorCentralFrequency', 'double'),
+    'QI_with_FC': ('percentConfidenceWithForecast', 'float'),
+    'QI_without_FC': ('percentConfidenceWithoutForecast', 'float'),
+    'Data_Vertical_Velocity': ('windUpward', 'float'),
+    'LaunchTime': ('releaseTime', 'float'),
 }
 
 checkuv = {
-    "eastward_wind": "u",
-    "northward_wind": "v",
+    "windEastward": "u",
+    "windNorthward": "v",
 }
 
 conv_varnames = {
-    "tv": ["virtual_temperature"],
-    "tsen": ["air_temperature"],
-    "uv": ["eastward_wind", "northward_wind"],
-    "ps": ["surface_pressure"],
-    "q": ["specific_humidity"],
-    "bend": ["bending_angle"],
-    "refract": ["refractivity"],
-    "sst": ["sea_surface_temperature"],
+    "tv": ["virtualTemperature"],
+    "tsen": ["airTemperature"],
+    "uv": ["windEastward", "windNorthward"],
+    "ps": ["stationPressure"],
+    "q": ["specificHumidity"],
+    "bend": ["bendingAngle"],
+    "refract": ["atmosphericRefractivity"],
+    "sst": ["seaSurfaceTemperature"],
 }
 
 conv_gsivarnames = {
@@ -159,7 +181,6 @@
 
 gsi_add_vars_allsky = {
     'Observation_Type': 'ObsType',
-    'Observation_Subtype': 'ObsSubType',
     'Prep_Use_Flag': 'PreUseFlag',
     'Analysis_Use_Flag': 'GsiUseFlag',
     'Nonlinear_QC_Rel_Wgt': 'GsiQCWeight',
@@ -189,7 +210,6 @@
 gsi_add_vars = {
     'ObsBias': 'GsiObsBias',
     'Observation_Type': 'ObsType',
-    'Observation_Subtype': 'ObsSubType',
     'Prep_Use_Flag': 'PreUseFlag',
     'Analysis_Use_Flag': 'GsiUseFlag',
     'Nonlinear_QC_Rel_Wgt': 'GsiQCWeight',
@@ -222,7 +242,6 @@
 
 gsi_add_vars_uv = {
     'Observation_Type': 'ObsType',
-    'Observation_Subtype': 'ObsSubType',
     'Prep_Use_Flag': 'PreUseFlag',
     'Analysis_Use_Flag': 'GsiUseFlag',
     'Nonlinear_QC_Rel_Wgt': 'GsiQCWeight',
@@ -254,7 +273,9 @@
     'PreUseFlag',
     'GsiUseFlag',
     'ObsType',
-    'ObsSubType',
+    'Observation_Subtype',
+    'observationTypeNum',
+    'observationSubTypeNum',
     'Analysis_Use_Flag',
 ]
 
@@ -298,14 +319,14 @@
 ]
 
 chan_metadata_dict = {
-    'sensor_chan': 'sensor_channel',
-    'use_flag': 'gsi_use_flag',
-    'frequency': 'sensor_band_central_radiation_frequency',
-    'polarization': 'polarization',
-    'wavenumber': 'sensor_band_central_radiation_wavenumber',
-    'error_variance': 'ObsError',
-    'mean_lapse_rate': 'mean_lapse_rate',
+    'sensor_chan': 'sensorChannelNumber',
+    'frequency': 'sensorCentralFrequency',
+    'polarization': 'sensorPolarizationDirection',
+    'wavenumber': 'sensorCentralWavenumber',
 }
+# 'use_flag': 'gsi_use_flag',
+# 'error_variance': 'ObsError',
+# 'mean_lapse_rate': 'lapseRate',
 
 chan_metadata_int = [
     'sensor_channel',
@@ -423,35 +444,54 @@
     'ompslpnc',
     'mls55',
 ]
+
 # units
 # 'IODA/UFO_variable_name': 'Unit'
 units_values = {
-    'virtual_temperature': 'K',
+    'latitude': 'degree_north',
+    'longitude': 'degree_east',
+    'stationElevation': 'm',
+    'height': 'm',
+    'pressure': 'Pa',
+    'airTemperature': 'K',
+    'airTemperatureAt2M': 'K',
+    'virtualTemperature': 'K',
+    'virtualTemperatureAt2M': 'K',
+    'specificHumidity': 'kg kg-1',
+    'specificHumidityAt2M': 'kg kg-1',
+    'waterVaporMixingRatio': 'kg kg-1',
+    'relativeHumidity': '1',
+    'windNorthward': 'm s-1',
+    'windEastward': 'm s-1',
+    'windSpeed': 'm s-1',
+    'windDirection': 'degree',
+    'windSpeedAt10M': 'm s-1',
+    'windDirectionAt10M': 'degree',
+    'geopotentialHeight': 'm',
+    'height': 'm',
+    'heightOfSurface': 'm',
+    'stationPressure': 'Pa',
+    'seaSurfaceTemperature': 'K',
     'atmosphere_ln_pressure_coordinate': '1',
-    'specific_humidity': '1',
-    'northward_wind': 'm s-1',
-    'eastward_wind': 'm s-1',
-    'geopotential_height': 'm',
+    'air_pressure_levels': 'Pa',
     'geopotential_height_levels': 'm',
-    'height_above_mean_sea_level': 'm',
-    'surface_pressure': 'Pa',
-    'sea_surface_temperature': 'K',
     'surface_temperature': 'K',
     'surface_roughness_length': 'm',
     'surface_geometric_height': 'm',
-    'surface_altitude': 'm',
-    'geoid_height_above_reference_ellipsoid': 'Meters',
-    'earth_radius_of_curvature': 'Meters',
-    'impact_height': 'Meters',
-    'impact_parameter': 'Meters',
-    'land_area_fraction': '1',
-    'air_temperature': 'K',
-    'air_pressure': 'Pa',
-    'air_pressure_levels': 'Pa',
-    'humidity_mixing_ratio': '1',
-    'mole_fraction_of_carbon_dioxide_in_air': '1',
-    'mole_fraction_of_ozone_in_air': '1',
-    'integrated_layer_ozone_in_air': 'DU',
+    'surface_geopotential_height': 'm',
+    'geoidUndulation': 'm',
+    'earthRadiusCurvature': 'm',
+    'impactHeightRO': 'm',
+    'impactParameterRO': 'm',
+    'bendingAngle': 'radians',
+    'landAreaFraction': '1',
+    'waterAreaFraction': '1',
+    'seaIceFraction': '1',
+    'surface_snow_area_fraction': '1',
+    'vegetation_area_fraction': '1',
+    'ozoneLayer': 'DU',
+    'ozoneTotal': 'DU',
+    'carbondioxideLayer': '1',
     'atmosphere_mass_content_of_cloud_liquid_water': 'kg m-2',
     'effective_radius_of_cloud_liquid_water_particle': 'm',
     'atmosphere_mass_content_of_cloud_ice': 'kg m-2',
@@ -460,26 +500,17 @@
     'effective_radius_of_rain_particle': '1e-6 m',
     'mass_content_of_snow_in_atmosphere_layer': 'kg m-2',
     'effective_radius_of_snow_particle': '1e-6 m',
-    'water_area_fraction': '1',
-    'land_area_fraction': '1',
-    'ice_area_fraction': '1',
-    'surface_snow_area_fraction': '1',
-    'vegetation_area_fraction': '1',
     'surface_temperature_where_sea': 'K',
     'surface_temperature_where_land': 'K',
     'surface_temperature_where_ice': 'K',
     'surface_temperature_where_snow': 'K',
-    'surface_wind_speed': 'm s-1',
-    'wind_speed': 'm s-1',
-    'surface_wind_from_direction': 'degree',
     'leaf_area_index': '1',
     'volume_fraction_of_condensed_water_in_soil': '1',
-    'soil_temperature': 'K',
+    'soilTemperature': 'K',
     'land_type_index_NPOESS': '1',
     'vegetation_type_index': '1',
     'soil_type': '1',
     'surface_snow_thickness': 'm',
-    'humidity_mixing_ratio': '1',
     'wind_reduction_factor_at_10m': '1',
     'sulf': '1',
     'bc1': '1',
@@ -495,33 +526,32 @@
     'seas2': '1',
     'seas3': '1',
     'seas4': '1',
-    'latitude': 'degrees_north',
-    'longitude': 'degrees_east',
-    'station_elevation': 'm',
-    'height': 'm',
-    'height_above_mean_sea_level': 'm',
-    'scan_position': '1',
-    'sensor_zenith_angle': 'degree',
-    'sensor_azimuth_angle': 'degree',
-    'solar_zenith_angle': 'degree',
-    'solar_azimuth_angle': 'degree',
+    'sensorViewAngle': 'degree',
+    'sensorZenithAngle': 'degree',
+    'sensorAzimuthAngle': 'degree',
+    'solarZenithAngle': 'degree',
+    'solarAzimuthAngle': 'degree',
     'modis_deep_blue_flag': '1',
     'row_anomaly_index': '1',
     'total_ozone_error_flag': '1',
     'profile_ozone_error_flag': '1',
     'top_level_pressure': 'Pa',
     'bottom_level_pressure': 'Pa',
-    'tropopause_pressure': 'Pa',
+    'tropopausePressure': 'Pa',
     'brightness_temperature_jacobian_surface_temperature': '1',
     'brightness_temperature_jacobian_surface_emissivity': 'K',
     'brightness_temperature_jacobian_air_temperature': '1',
-    'brightness_temperature_jacobian_humidity_mixing_ratio': 'K/g/Kg ',
+    'brightness_temperature_jacobian_humidity_mixing_ratio': 'K/g/kg ',
     'optical_thickness_of_atmosphere_layer': '1',
-    'clw_retrieved_from_observation': 'kg/m/m',
-    'clw_retrieved_from_background': 'kg/m/m',
-    'scat_retrieved_from_observation': '1',
-    'LaunchTime': 'hours',
-    'bending_angle': 'radians',
+    'cloudWaterRetrievedFromObservation': 'kg m-2',
+    'cloudWaterRetrievedFromSimulatedObservation': 'kg m-2',
+    'scatteringIndexRetrievedFromObservation': '1',
+    'releaseTime': 'seconds since 1970-01-01T00:00:00Z',
+    'sensorCentralWavenumber': 'm-1',
+    'sensorCentralFrequency': 'Hz',
+    'brightnessTemperature': 'K',
+    'percentConfidenceWithForecast': 'percent',
+    'percentConfidenceWithoutForecast': 'percent',
 }
 
 # @TestReference
@@ -535,10 +565,10 @@
 test_fields = {}
 
 test_fields_allsky = {
-    'clwp_amsua': ('clw_retrieved_from_observation', 'float'),
-    'clw_guess_retrieval': ('clw_retrieved_from_background', 'float'),
+    'clwp_amsua': ('cloudWaterRetrievedFromObservation', 'float'),
+    'clw_guess_retrieval': ('cloudWaterRetrievedFromSimulatedObservation', 'float'),
     'clw_symmetric_amount': ('clw_symmetric_amount', 'float'),
-    'scat_amsua': ('scat_retrieved_from_observation', 'float'),
+    'scat_amsua': ('scatteringIndexRetrievedFromObservation', 'float'),
 }
 test_fields_with_channels_allsky = {
     'Hydrometeor_Affected_Channels': ('Hydrometeor_Affected_Channels', 'float'),
@@ -691,7 +721,6 @@ def toGeovals(self, OutDir, clobber=True):
                     # for isort in range(len(record_number_new)):
                     #     print('isort, idx, record_number, record_number_new',isort,\
                     #         record_number[isort], record_number_new[isort] )
-
                 # set up output file
                 ncout = nc.Dataset(outname, 'w', format='NETCDF4')
                 ncout.setncattr(
@@ -699,11 +728,11 @@ def toGeovals(self, OutDir, clobber=True):
                         self.validtime.strftime("%Y%m%d%H")))
                 # get nlocs
                 nlocs = np.sum(idx)
-                ncout.createDimension("nlocs", nlocs)
+                ncout.createDimension("Location", nlocs)
                 # other dims
                 if (v != "sst"):
                     ncout.createDimension(
-                        "nlevs", self.df.dimensions["atmosphere_pressure_coordinate_arr_dim"].size)
+                        "Layer", self.df.dimensions["atmosphere_pressure_coordinate_arr_dim"].size)
                     ncout.createDimension(
                         "ninterfaces", self.df.dimensions["atmosphere_pressure_coordinate_interface_arr_dim"].size)
                 dimname = "Station_ID_maxstrlen"
@@ -719,7 +748,7 @@ def toGeovals(self, OutDir, clobber=True):
                         vdata = np.frombuffer(vdata, dtype=var.dtype)
                         vdata = np.reshape(vdata, dims)
                         if vname in geovals_metadata_dict.keys():
-                            dims = ("nlocs",) + var.dimensions[1:]
+                            dims = ("Location",) + var.dimensions[1:]
                             var_out = ncout.createVariable(geovals_metadata_dict[vname], vdata.dtype, dims)
                             if v == 'bend':
                                 var_out[...] = vdata[idx_sorted, ...]
@@ -727,19 +756,18 @@ def toGeovals(self, OutDir, clobber=True):
                                 var_out[...] = vdata[idx, ...]
                         if vname in geovals_vars.keys():
                             if (len(var.dimensions) == 1):
-                                dims = ("nlocs",)
+                                dims = ("Location",)
                             else:
                                 if (vname == "atmosphere_pressure_coordinate_interface") or (
                                         vname == "geopotential_height_levels"):
-                                    dims = ("nlocs", "ninterfaces")
+                                    dims = ("Location", "ninterfaces")
                                 else:
-                                    dims = ("nlocs", "nlevs")
+                                    dims = ("Location", "Layer")
                             var_out = ncout.createVariable(geovals_vars[vname], vdata.dtype, dims)
                             if v == 'bend':
                                 var_out[...] = vdata[idx_sorted, ...]
                             else:
                                 var_out[...] = vdata[idx, ...]
-
                 ncout.close()
 
     def toIODAobs(self, OutDir, clobber=True, platforms=None):
@@ -800,16 +828,16 @@ def toIODAobs(self, OutDir, clobber=True, platforms=None):
                     varDict[value]['valKey'] = value, iconv.OvalName()
                     varDict[value]['errKey'] = value, iconv.OerrName()
                     varDict[value]['qcKey'] = value, iconv.OqcName()
-                    VarDims[value] = ['nlocs']
+                    VarDims[value] = ['Location']
                     varAttrs[varDict[value]['valKey']]['units'] = units_values[value]
                     varAttrs[varDict[value]['errKey']]['units'] = units_values[value]
-                    varAttrs[varDict[value]['qcKey']]['units'] = 'unitless'
                     varAttrs[varDict[value]['valKey']]['coordinates'] = 'longitude latitude'
                     varAttrs[varDict[value]['errKey']]['coordinates'] = 'longitude latitude'
                     varAttrs[varDict[value]['qcKey']]['coordinates'] = 'longitude latitude'
                     varAttrs[varDict[value]['valKey']]['_FillValue'] = self.FLOAT_FILL
                     varAttrs[varDict[value]['errKey']]['_FillValue'] = self.FLOAT_FILL
                     varAttrs[varDict[value]['qcKey']]['_FillValue'] = self.INT_FILL
+
                 if v == 'bend':
                     # sort record_number
                     record_number = self.var('record_number')[idx]
@@ -897,6 +925,8 @@ def toIODAobs(self, OutDir, clobber=True, platforms=None):
                             else:
                                 tmp[tmp > 4e8] = self.FLOAT_FILL
                             outdata[gvname] = tmp
+                            if gvname[1] != 'PreUseFlag' and gvname[1] != 'ObsType' and gvname[1] != 'GsiUseFlag' and gvname[1] != 'GsiQCWeight':
+                                varAttrs[gvname]['units'] = units_values[gvname[0]]
                     # create a GSI effective QC variable
                     gsiqcname = outvars[o], 'GsiEffectiveQC'
                     errname = outvars[o], 'GsiFinalObsError'
@@ -904,7 +934,6 @@ def toIODAobs(self, OutDir, clobber=True, platforms=None):
                     gsiqc[outdata[errname] == 1e8] = 1
                     gsiqc[outdata[(outvars[o], "GsiUseFlag")] < 0] = 1
                     outdata[gsiqcname] = gsiqc.astype(np.int32)
-                    varAttrs[gsiqcname]['units'] = 'unitless'
                     varAttrs[gsiqcname]['_FillValue'] = self.INT_FILL
                     # store values in output data dictionary
                     outdata[varDict[outvars[o]]['valKey']] = obsdata
@@ -913,6 +942,7 @@ def toIODAobs(self, OutDir, clobber=True, platforms=None):
 
                 for lvar in LocVars:
                     loc_mdata_name = all_LocKeyList[lvar][0]
+                    dtype = all_LocKeyList[lvar][1]
                     if lvar == 'Station_ID':
                         tmp = self.var(lvar)[idx]
                         StationIDs = [bytes((b''.join(tmp[a])).decode('iso-8859-1').encode('utf8')) for a in range(len(tmp))]
@@ -922,7 +952,7 @@ def toIODAobs(self, OutDir, clobber=True, platforms=None):
                         obstimes = [self.validtime + dt.timedelta(hours=float(tmp[a])) for a in range(len(tmp))]
                         obstimes = [a.strftime("%Y-%m-%dT%H:%M:%SZ") for a in obstimes]
                         outdata[(loc_mdata_name, 'MetaData')] = np.array(obstimes, dtype=object)
-                        varAttrs[(loc_mdata_name, 'MetaData')]['units'] = 'UTC Time in YYYY-MM-DDTHH:MM:SSZ format'
+                    #   varAttrs[(loc_mdata_name, 'MetaData')]['units'] = 'seconds since 1970-01-01T00:00:00Z'
                     # special logic for unit conversions depending on GSI version
                     elif lvar == 'Pressure':
                         tmpps = self.var(lvar)[idx]
@@ -958,9 +988,15 @@ def toIODAobs(self, OutDir, clobber=True, platforms=None):
                             outdata[(loc_mdata_name, 'MetaData')] = self.var(lvar)[idx]
                             varAttrs[(loc_mdata_name, 'MetaData')]['units'] = 'm'
                     else:
-                        outdata[(loc_mdata_name, 'MetaData')] = self.var(lvar)[idx]
+                        if dtype == 'integer':
+                            outdata[(loc_mdata_name, 'MetaData')] = self.var(lvar)[idx].astype(np.int32)
+                        elif dtype == 'long':
+                            outdata[(loc_mdata_name, 'MetaData')] = self.var(lvar)[idx].astype(np.int64)
+                        else:
+                            outdata[(loc_mdata_name, 'MetaData')] = self.var(lvar)[idx]
                         if loc_mdata_name in units_values.keys():
                             varAttrs[(loc_mdata_name, 'MetaData')]['units'] = units_values[loc_mdata_name]
+
                 # put the TestReference fields in the structure for writing out
                 for tvar in TestVars:
                     if tvar in test_fields_:
@@ -970,12 +1006,12 @@ def toIODAobs(self, OutDir, clobber=True, platforms=None):
                         outdata[(test_mdata_name, 'TestReference')] = tmp
 
                 # writer metadata
-                DimDict['nlocs'] = len(StationIDs)
+                DimDict['Location'] = len(StationIDs)
 
                 writer = iconv.IodaWriter(outname, LocKeyList, DimDict)
                 writer.BuildIoda(outdata, VarDims, varAttrs, globalAttrs)
 
-                print("ProcessedL %d Conventional obs processed to: %s" % (len(obsdata), outname))
+                print("Processed %d Conventional obs processed to: %s" % (len(obsdata), outname))
 
 
 def grabobsidx(obsdata, platform, var):
@@ -1083,28 +1119,30 @@ def toGeovals(self, OutDir, clobber=True):
         ncout.setncattr("date_time", np.int32(self.validtime.strftime("%Y%m%d%H")))
         ncout.setncattr("satellite", self.satellite)
         ncout.setncattr("sensor", self.sensor)
+
         # get nlocs
-        nlocs = self.nobs / self.nchans
-        ncout.createDimension("nlocs", nlocs)
+        nlocs = int(self.nobs / self.nchans)
+        ncout.createDimension("Location", nlocs)
+
         # other dims
-        ncout.createDimension("nlevs", self.df.dimensions["air_temperature_arr_dim"].size)
-        ncout.createDimension("nlevsp1", self.df.dimensions["air_pressure_levels_arr_dim"].size)
+        ncout.createDimension("Layer", self.df.dimensions["air_temperature_arr_dim"].size)
+        ncout.createDimension("Level", self.df.dimensions["air_pressure_levels_arr_dim"].size)
 
         for var in self.df.variables.values():
             vname = var.name
             if vname in geovals_metadata_dict.keys():
-                dims = ("nlocs",)
+                dims = ("Location",)
                 var_out = ncout.createVariable(geovals_metadata_dict[vname], var.dtype, dims)
                 vdata = var[:]
                 vdata = vdata[::self.nchans]
                 var_out[:] = vdata
             elif vname in geovals_vars.keys():
                 if (len(var.dimensions) == 1):
-                    dims = ("nlocs",)
+                    dims = ("Location",)
                 elif "_levels" in vname:
-                    dims = ("nlocs", "nlevsp1")
+                    dims = ("Location", "Level")
                 else:
-                    dims = ("nlocs", "nlevs")
+                    dims = ("Location", "Level")
                 var_out = ncout.createVariable(geovals_vars[vname], var.dtype, dims)
                 vdata = var[...]
                 vdata = vdata[::self.nchans, ...]
@@ -1138,16 +1176,18 @@ def toObsdiag(self, OutDir, clobber=True):
         # set up output file
         ncout = nc.Dataset(outname, 'w', format='NETCDF4')
         ncout.setncattr("date_time", np.int32(self.validtime.strftime("%Y%m%d%H")))
-        ncout.setncattr("satellite", self.satellite)
+        ncout.setncattr("platform", self.satellite)
         ncout.setncattr("sensor", self.sensor)
+
         # get nlocs
-        nlocs = self.nobs / self.nchans
-        ncout.createDimension("nlocs", nlocs)
+        nlocs = int(self.nobs / self.nchans)
+        ncout.createDimension("Location", nlocs)
+
         # other dims
-        nlevs = self.df.dimensions["air_pressure_arr_dim"].size
-        nlevsp1 = self.df.dimensions["air_pressure_levels_arr_dim"].size
+        Layer = self.df.dimensions["air_pressure_arr_dim"].size
+        Level = self.df.dimensions["air_pressure_levels_arr_dim"].size
 
-        ncout.createDimension("nlevs", self.df.dimensions["air_pressure_arr_dim"].size)
+        ncout.createDimension("Layer", self.df.dimensions["air_pressure_arr_dim"].size)
 
         # get channel info and list
         chan_number = self.darr('sensor_chan')
@@ -1161,7 +1201,7 @@ def toObsdiag(self, OutDir, clobber=True):
         for var in self.df.variables.values():
             vname = var.name
             if vname in obsdiag_metadata_dict.keys():
-                dims = ("nlocs",)
+                dims = ("Location",)
                 var_out = ncout.createVariable(obsdiag_metadata_dict[vname], var.dtype, dims)
                 vdata = var[:]
                 vdata = vdata[::self.nchans]
@@ -1169,7 +1209,7 @@ def toObsdiag(self, OutDir, clobber=True):
             elif vname in obsdiag_vars.keys():
                 # print("toObsdiag: var.shape = ", var.shape)
                 if (len(var.dimensions) == 1):
-                    dims = ("nlocs",)
+                    dims = ("Location",)
                     for c in range(len(chanlist)):
                         var_name = obsdiag_vars[vname]+"_"+"{:d}".format(chanlist[c])
                         idx = chan_indx == c+1
@@ -1181,9 +1221,9 @@ def toObsdiag(self, OutDir, clobber=True):
                         vdata = vdata[idx]
                         var_out[:] = vdata
                 elif "_levels" in vname:
-                    dims = ("nlocs", "nlevsp1")
+                    dims = ("Location", "Level")
                 else:
-                    dims = ("nlocs", "nlevs")
+                    dims = ("Location", "Level")
                     for c in range(len(chanlist)):
                         var_name = obsdiag_vars[vname]+"_"+"{:d}".format(chanlist[c])
                         idx = chan_indx == c+1
@@ -1251,17 +1291,17 @@ def toIODAobs(self, OutDir, ObsBias, QCVars, TestRefs, clobber=True):
 
         chanlist = chan_number
 
-        value = "brightness_temperature"
+        value = "brightnessTemperature"
         varDict[value]['valKey'] = value, iconv.OvalName()
         varDict[value]['errKey'] = value, iconv.OerrName()
         varDict[value]['qcKey'] = value, iconv.OqcName()
-        VarDims[value] = ['nlocs', 'nchans']
+        VarDims[value] = ['Location', 'Channel']
         varAttrs[varDict[value]['valKey']]['units'] = 'K'
         varAttrs[varDict[value]['errKey']]['units'] = 'K'
-        varAttrs[varDict[value]['qcKey']]['units'] = 'unitless'
-        varAttrs[varDict[value]['valKey']]['coordinates'] = 'longitude latitude'
-        varAttrs[varDict[value]['errKey']]['coordinates'] = 'longitude latitude'
-        varAttrs[varDict[value]['qcKey']]['coordinates'] = 'longitude latitude'
+#       varAttrs[varDict[value]['qcKey']]['units'] = 'unitless'
+#       varAttrs[varDict[value]['valKey']]['coordinates'] = 'longitude latitude'
+#       varAttrs[varDict[value]['errKey']]['coordinates'] = 'longitude latitude'
+#       varAttrs[varDict[value]['qcKey']]['coordinates'] = 'longitude latitude'
         varAttrs[varDict[value]['valKey']]['_FillValue'] = self.FLOAT_FILL
         varAttrs[varDict[value]['errKey']]['_FillValue'] = self.FLOAT_FILL
         varAttrs[varDict[value]['qcKey']]['_FillValue'] = self.INT_FILL
@@ -1285,12 +1325,13 @@ def toIODAobs(self, OutDir, ObsBias, QCVars, TestRefs, clobber=True):
             for vbc in valuebc:
                 varDict[vbc]['bctKey'] = vbc, iconv.ObiastermName()
                 varDict[vbc]['bcpKey'] = vbc, iconv.ObiaspredName()
-                VarDims[(vbc, 'MetaData')] = ['nlocs']
+                VarDims[(vbc, 'MetaData')] = ['Location']
                 ibc += 1
         obsdata = self.var('Observation')
         try:
             obserr = self.var('Input_Observation_Error')
         except IndexError:
+            # obserr = 1./self.var('Inverse_Observation_Error')
             obserr = np.repeat(self.var('error_variance'), nlocs, axis=0)
         obsqc = self.var('QC_Flag').astype(np.int32)
         if (ObsBias):
@@ -1340,7 +1381,7 @@ def toIODAobs(self, OutDir, ObsBias, QCVars, TestRefs, clobber=True):
                 obstimes = [self.validtime + dt.timedelta(hours=float(tmp[a])) for a in range(len(tmp))]
                 obstimes = [a.strftime("%Y-%m-%dT%H:%M:%SZ") for a in obstimes]
                 outdata[(loc_mdata_name, 'MetaData')] = np.array(obstimes, dtype=object)
-                varAttrs[(loc_mdata_name, 'MetaData')]['units'] = 'UTC Time in YYYY-MM-DDTHH:MM:SSZ format'
+                # varAttrs[(loc_mdata_name, 'MetaData')]['units'] = 'seconds since 1970-01-01T00:00:00Z'
             elif self.sensor == "gmi" and lvar in gmi_chan_dep_loc_vars:
                 # Channels 1-9
                 tmp = self.var(lvar)[::nchans]
@@ -1354,6 +1395,11 @@ def toIODAobs(self, OutDir, ObsBias, QCVars, TestRefs, clobber=True):
                 outdata[(loc_mdata_name+'1', 'MetaData')] = tmp
                 if loc_mdata_name in units_values.keys():
                     varAttrs[(loc_mdata_name+'1', 'MetaData')]['units'] = units_values[loc_mdata_name]
+                # tmp = self.var(lvar)[::nchans]
+                # tmp[tmp > 4e8] = self.FLOAT_FILL
+                # outdata[(loc_mdata_name, 'MetaData')] = tmp
+                # if loc_mdata_name in units_values.keys():
+                #     varAttrs[(loc_mdata_name, 'MetaData')]['units'] = units_values[loc_mdata_name]
             else:
                 tmp = self.var(lvar)[::nchans]
                 tmp[tmp > 4e8] = self.FLOAT_FILL
@@ -1368,7 +1414,7 @@ def toIODAobs(self, OutDir, ObsBias, QCVars, TestRefs, clobber=True):
                 tmp = self.var(tvar)[:]
                 tmp[tmp > 4e8] = self.FLOAT_FILL
                 outdata[test_mdata_name] = np.reshape(tmp, (nlocs, nchans))
-                VarDims[test_mdata_name] = ['nlocs', 'nchans']
+                VarDims[test_mdata_name] = ['Location', 'Channel']
                 if test_fields_with_channels_[tvar][0] in units_values.keys():
                     varAttrs[test_mdata_name]['units'] = units_values[test_fields_with_channels_[tvar][0]]
 
@@ -1377,9 +1423,10 @@ def toIODAobs(self, OutDir, ObsBias, QCVars, TestRefs, clobber=True):
                 tmp = self.var(tvar)[::nchans]
                 tmp[tmp > 4e8] = self.FLOAT_FILL
                 outdata[test_mdata_name] = tmp
-                VarDims[test_mdata_name] = ['nlocs']
+                VarDims[test_mdata_name] = ['Location']
                 if test_fields_[tvar][0] in units_values.keys():
-                    varAttrs[test_mdata_name]['units'] = units_values[test_fields_[tvar][0]]
+                    if tvar != 'scat_amsua':
+                        varAttrs[test_mdata_name]['units'] = units_values[test_fields_[tvar][0]]
 
         gsi_add_radvars = gsi_add_vars
         if (QCVars):
@@ -1415,12 +1462,12 @@ def toIODAobs(self, OutDir, ObsBias, QCVars, TestRefs, clobber=True):
                     tmp = tmp.astype(np.int32)
                 else:
                     tmp[tmp > 4e8] = self.FLOAT_FILL
-                gvname = "brightness_temperature", iodavar
+                gvname = "brightnessTemperature", iodavar
                 outdata[gvname] = np.reshape(tmp, (nlocs, nchans))
-                VarDims[gvname] = ['nlocs', 'nchans']
+                VarDims[gvname] = ['Location', 'Channel']
 
         # brightness temperature variables
-        value = 'brightness_temperature'
+        value = 'brightnessTemperature'
         obsdata[obsdata > 9e5] = self.FLOAT_FILL
         obsqc[obsdata > 9e5] = self.INT_FILL
 
@@ -1428,14 +1475,25 @@ def toIODAobs(self, OutDir, ObsBias, QCVars, TestRefs, clobber=True):
         outdata[varDict[value]['valKey']] = np.reshape(obsdata, (nlocs, nchans))
         outdata[varDict[value]['errKey']] = np.reshape(obserr, (nlocs, nchans))
         outdata[varDict[value]['qcKey']] = np.reshape(obsqc.astype(np.int32), (nlocs, nchans))
-        # create a GSI effective QC variable
+
+        # create a GSI effective QC variable (group)
         gsiqcname = value, 'GsiEffectiveQC'
         errname = value, 'GsiFinalObsError'
         gsiqc = np.zeros_like(outdata[varDict[value]['valKey']])
         gsiqc[outdata[errname] > 1e8] = 1
         gsiqc[np.reshape(self.var('QC_Flag'), (nlocs, nchans)) < 0] = 1
         outdata[gsiqcname] = gsiqc.astype(np.int32)
-        varAttrs[gsiqcname]['units'] = 'unitless'
+
+        # create a GSI related variable (group)
+        varAttrs[errname]['units'] = 'K'
+        grpname = value, 'GsiBc'
+        varAttrs[grpname]['units'] = 'K'
+        grpname = value, 'GsiHofXBc'
+        varAttrs[grpname]['units'] = 'K'
+        grpname = value, 'GsiHofX'
+        varAttrs[grpname]['units'] = 'K'
+        grpname = value, 'GsiHofXClr'
+        varAttrs[grpname]['units'] = 'K'
 
         if (ObsBias):
             valuebc = [
@@ -1473,20 +1531,26 @@ def toIODAobs(self, OutDir, ObsBias, QCVars, TestRefs, clobber=True):
                     outdata[(value2, 'MetaData')] = self.var(key).astype(np.int32)
                 else:
                     outdata[(value2, 'MetaData')] = self.var(key).astype(np.float32)
-                VarDims[(value2, 'MetaData')] = ['nchans']
+                    # Frequency units is GHz in CRTM/GSI
+                    if value2 == 'sensorCentralFrequency':
+                        outdata[(value2, 'MetaData')] = outdata[(value2, 'MetaData')]*1.e9
+                    # Wavenumber unit is cm-1 in CRTM/GSI
+                    if value2 == 'sensorCentralWavenumber':
+                        outdata[(value2, 'MetaData')] = outdata[(value2, 'MetaData')]*1.e2
+                VarDims[(value2, 'MetaData')] = ['Channel']
                 if value2 in units_values.keys():
                     varAttrs[(value2, 'MetaData')]['units'] = units_values[value2]
             except IndexError:
                 pass
 
         # global attributes
-        globalAttrs["satellite"] = self.satellite
-        globalAttrs["sensor"] = self.sensor
+        globalAttrs["platform"] = np.array([wmo_satid[self.satellite]], dtype=np.int32)
+        globalAttrs["sensor"] = np.array([wmo_instid[self.sensor]], dtype=np.int32)
 
         # set dimension lengths in the writer since we are bypassing
         # ExtractObsData
-        DimDict['nlocs'] = nlocs
-        DimDict['nchans'] = chanlist
+        DimDict['Location'] = nlocs
+        DimDict['Channel'] = chanlist
 
         writer = iconv.IodaWriter(outname, LocKeyList, DimDict)
         writer.BuildIoda(outdata, VarDims, varAttrs, globalAttrs)
@@ -1559,13 +1623,15 @@ def toGeovals(self, OutDir, clobber=True):
         ncout.setncattr("date_time", np.int32(self.validtime.strftime("%Y%m%d%H")))
         ncout.setncattr("satellite", self.satellite)
         ncout.setncattr("sensor", self.sensor)
+
         # get nlocs
         nlocs = self.nobs
-        ncout.createDimension("nlocs", nlocs)
+        ncout.createDimension("Location", nlocs)
+
         # other dims
-        ncout.createDimension("nlevs", self.df.dimensions["mole_fraction_of_ozone_in_air_arr_dim"].size)
+        ncout.createDimension("Layer", self.df.dimensions["mole_fraction_of_ozone_in_air_arr_dim"].size)
         if (self.sensor in oz_lay_sensors):
-            ncout.createDimension("nlevsp1", self.df.dimensions["air_pressure_levels_arr_dim"].size)
+            ncout.createDimension("Level", self.df.dimensions["air_pressure_levels_arr_dim"].size)
         for var in self.df.variables.values():
             vname = var.name
             if vname in geovals_metadata_dict.keys():
@@ -1575,11 +1641,11 @@ def toGeovals(self, OutDir, clobber=True):
                 var_out[:] = vdata
             elif vname in geovals_vars.keys():
                 if (len(var.dimensions) == 1):
-                    dims = ("nlocs",)
+                    dims = ("Location",)
                 elif "_levels" in vname:
-                    dims = ("nlocs", "nlevsp1")
+                    dims = ("Location", "Level")
                 else:
-                    dims = ("nlocs", "nlevs")
+                    dims = ("Location", "Layer")
                 var_out = ncout.createVariable(geovals_vars[vname], var.dtype, dims)
                 vdata = var[...]
                 var_out[...] = vdata
@@ -1612,20 +1678,19 @@ def toIODAobs(self, OutDir, clobber=True):
 
         nlocs = self.nobs
         vname = "integrated_layer_ozone_in_air"
-        if (self.sensor in oz_lev_sensors):
+        if (self.sensor in oz_lay_sensors):
             vname = "mole_fraction_of_ozone_in_air"
         varDict[vname]['valKey'] = vname, iconv.OvalName()
         varDict[vname]['errKey'] = vname, iconv.OerrName()
         varDict[vname]['qcKey'] = vname, iconv.OqcName()
-        VarDims[vname] = ['nlocs']
+        VarDims[vname] = ['Location']
         if (self.sensor in oz_lev_sensors):
             varAttrs[varDict[vname]['valKey']]['units'] = 'mol mol-1'
             varAttrs[varDict[vname]['errKey']]['units'] = 'mol mol-1'
         else:
             varAttrs[varDict[vname]['valKey']]['units'] = 'DU'
             varAttrs[varDict[vname]['errKey']]['units'] = 'DU'
-
-        varAttrs[varDict[vname]['qcKey']]['units'] = 'unitless'
+        # varAttrs[varDict[vname]['qcKey']]['units'] = 'unitless'
         varAttrs[varDict[vname]['valKey']]['_FillValue'] = self.FLOAT_FILL
         varAttrs[varDict[vname]['errKey']]['_FillValue'] = self.FLOAT_FILL
         varAttrs[varDict[vname]['qcKey']]['_FillValue'] = self.INT_FILL
@@ -1634,26 +1699,27 @@ def toIODAobs(self, OutDir, clobber=True):
         try:
             tmp = self.var('Input_Observation_Error')
         except IndexError:
-            tmp = 1./self.var('Inverse_Observation_Error')
+            # tmp = 1./self.var('Inverse_Observation_Error')
+            tmp = np.repeat(self.var('error_variance'), nlocs, axis=0)
         tmp[tmp < self.EPSILON] = 0
         obserr = tmp
         obserr[np.isinf(obserr)] = self.FLOAT_FILL
         obsqc = self.var('Analysis_Use_Flag').astype(np.int32)
         for lvar in LocVars:
             loc_mdata_name = all_LocKeyList[lvar][0]
-            if lvar == 'Time':
+            if lvar == 'Time' or lvar == 'time':
                 tmp = self.var(lvar)
                 obstimes = [self.validtime+dt.timedelta(hours=float(tmp[a])) for a in range(len(tmp))]
                 obstimes = [a.strftime("%Y-%m-%dT%H:%M:%SZ") for a in obstimes]
                 outdata[(loc_mdata_name, 'MetaData')] = np.array(obstimes, dtype=object)
-                varAttrs[(loc_mdata_name, 'MetaData')]['units'] = 'UTC Time in YYYY-MM-DDTHH:MM:SSZ format'
+                # varAttrs[(loc_mdata_name, 'MetaData')]['units'] = 'seconds since 1970-01-01T00:00:00Z'
             else:
                 tmp = self.var(lvar)
                 tmp[tmp > 4e8] = self.FLOAT_FILL
                 outdata[(loc_mdata_name, 'MetaData')] = tmp
                 if loc_mdata_name in units_values.keys():
                     varAttrs[(loc_mdata_name, 'MetaData')]['units'] = units_values[loc_mdata_name]
-            VarDims[(loc_mdata_name, 'MetaData')] = ['nlocs']
+            VarDims[(loc_mdata_name, 'MetaData')] = ['Location']
 
         for gsivar, iodavar in gsi_add_vars.items():
             # some special actions need to be taken depending on var name...
@@ -1684,12 +1750,12 @@ def toIODAobs(self, OutDir, clobber=True):
         outdata[varDict[vname]['errKey']] = obserr
         outdata[varDict[vname]['qcKey']] = obsqc
 
-        globalAttrs["satellite"] = self.satellite
-        globalAttrs["sensor"] = self.sensor
+        globalAttrs["platform"] = np.array([wmo_satid[self.satellite]], dtype=np.int32)
+        globalAttrs["sensor"] = np.array([wmo_instid[self.sensor]], dtype=np.int32)
 
         # set dimension lengths in the writer since we are bypassing
         # ExtractObsData
-        DimDict['nlocs'] = nlocs
+        DimDict['Location'] = nlocs
 
         writer = iconv.IodaWriter(outname, LocKeyList, DimDict)
         writer.BuildIoda(outdata, VarDims, varAttrs, globalAttrs)
@@ -1759,24 +1825,24 @@ def toGeovals(self, OutDir, clobber=True):
         ncout.setncattr("date_time", np.int32(self.validtime.strftime("%Y%m%d%H")))
         # get nlocs
         nlocs = self.nobs
-        ncout.createDimension("nlocs", nlocs)
+        ncout.createDimension("Location", nlocs)
         # other dims
-        ncout.createDimension("nlevs", self.df.dimensions["nlevs"].size)
+        ncout.createDimension("Layer", self.df.dimensions["Layer"].size)
         # ncout.createDimension("nlevsp1", self.df.dimensions["air_pressure_levels_arr_dim"].size)
         for var in self.df.variables.values():
             vname = var.name
             if vname in geovals_metadata_dict.keys():
-                dims = ("nlocs",)
+                dims = ("Location",)
                 var_out = ncout.createVariable(geovals_metadata_dict[vname], var.dtype, dims)
                 vdata = var[:]
                 var_out[:] = vdata
             elif vname in geovals_vars.keys():
                 if (len(var.dimensions) == 1):
-                    dims = ("nlocs",)
+                    dims = ("Location",)
                 elif "_levels" in vname:
-                    dims = ("nlocs", "nlevsp1")
+                    dims = ("Location", "Level")
                 else:
-                    dims = ("nlocs", "nlevs")
+                    dims = ("Location", "Layer")
                 var_out = ncout.createVariable(geovals_vars[vname], var.dtype, dims)
                 vdata = var[...]
                 var_out[...] = vdata
@@ -1823,7 +1889,7 @@ def toIODAobs(self, OutDir, clobber=True):
             varDict[value]['valKey'] = value, iconv.OvalName()
             varDict[value]['errKey'] = value, iconv.OerrName()
             varDict[value]['qcKey'] = value, iconv.OqcName()
-            VarDims[value] = ['nlocs']
+            VarDims[value] = ['Location']
             varAttrs[varDict[value]['valKey']]['units'] = myunits
             varAttrs[varDict[value]['errKey']]['units'] = myunits
             varAttrs[varDict[value]['qcKey']]['units'] = 'unitless'
@@ -1866,7 +1932,7 @@ def toIODAobs(self, OutDir, clobber=True):
                 obstimes = [self.validtime+dt.timedelta(hours=float(tmp[a])) for a in range(len(tmp))]
                 obstimes = [a.strftime("%Y-%m-%dT%H:%M:%SZ") for a in obstimes]
                 outdata[(loc_mdata_name, 'MetaData')] = np.array(obstimes, dtype=object)
-                varAttrs[(loc_mdata_name, 'MetaData')]['units'] = 'UTC Time in YYYY-MM-DDTHH:MM:SSZ format'
+                # varAttrs[(loc_mdata_name, 'MetaData')]['units'] = 'seconds since 1970-01-01T00:00:00Z'
             else:
                 tmp = self.var(lvar)[:]
                 tmp[tmp > 4e8] = self.FLOAT_FILL
@@ -1878,7 +1944,7 @@ def toIODAobs(self, OutDir, clobber=True):
 
         # set dimension lengths in the writer since we are bypassing
         # ExtractObsData
-        DimDict['nlocs'] = nlocs
+        DimDict['Location'] = nlocs
 
         writer = iconv.IodaWriter(outname, LocKeyList, DimDict)
         writer.BuildIoda(outdata, VarDims, varAttrs, globalAttrs)
diff --git a/src/hdf5/atms_netcdf_hdf5_2ioda.py b/src/hdf5/atms_netcdf_hdf5_2ioda.py
index 149bc99be..f97d3f368 100755
--- a/src/hdf5/atms_netcdf_hdf5_2ioda.py
+++ b/src/hdf5/atms_netcdf_hdf5_2ioda.py
@@ -5,7 +5,7 @@
 """
 
 import argparse
-from datetime import datetime, timedelta
+from datetime import datetime
 import glob
 # from concurrent.futures import ProcessPoolExecutor
 from pathlib import Path
@@ -27,8 +27,18 @@
 SNPP_WMO_sat_ID = 224
 NOAA20_WMO_sat_ID = 225
 NOAA21_WMO_sat_ID = 226
+ATMS_WMO_sensor_ID = 621
+
+float_missing_value = iconv.get_default_fill_val(np.float32)
+int_missing_value = iconv.get_default_fill_val(np.int32)
+
+metaDataName = iconv.MetaDataName()
+obsValName = iconv.OvalName()
+obsErrName = iconv.OerrName()
+qcName = iconv.OqcName()
 
 GlobalAttrs = {
+    "sensor": str(ATMS_WMO_sensor_ID),
     "platformCommonName": "ATMS",
     "platformLongDescription": "ATMS Brightness Temperature Data",
     "sensorCentralFrequency": [23.8,
@@ -40,7 +50,7 @@
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string")
+    ("dateTime", "object")
 ]
 
 
@@ -63,8 +73,11 @@ def main(args):
 #           else:
 #               obs_data = file_obs_data
 
+    WMO_sat_ID = get_WMO_satellite_ID(input_files[0])
+    GlobalAttrs['platform'] = np.int32(WMO_sat_ID)
     for afile in input_files:
         file_obs_data = get_data_from_files(afile)
+        WMO_sat_ID = get_WMO_satellite_ID(afile)
         if not file_obs_data:
             print("INFO: non-nominal file skipping")
             continue
@@ -72,51 +85,39 @@ def main(args):
             concat_obs_dict(obs_data, file_obs_data)
         else:
             obs_data = file_obs_data
+        if WMO_sat_ID != GlobalAttrs['platform']:
+            print(' ERROR:  IODA and subsequent UFO expect individual files to be a single satellite and sensor ')
+            print('    .... initial file satellite: ', GlobalAttrs['platform'])
+            print('    ...... final file satellite: ', WMO_sat_ID)
+            sys.exit()
 
-# V2 nlocs_int32 = np.array(len(obs_data[('latitude', 'MetaData')]), dtype='int32')
-    nlocs_int32 = np.array(len(obs_data[('latitude', 'MetaData')]), dtype='float32')  # this is float32 in old convention
-    nlocs = nlocs_int32.item()
-    nchans = len(obs_data[('channelNumber', 'MetaData')])
+    nlocs_int = np.array(len(obs_data[('latitude', metaDataName)]), dtype='int64')
+    nlocs = nlocs_int.item()
+    nchans = len(obs_data[('sensorChannelNumber', metaDataName)])
 
     # prepare global attributes we want to output in the file,
     # in addition to the ones already loaded in from the input file
-    GlobalAttrs['date_time_string'] = dtg.strftime("%Y-%m-%dT%H:%M:%SZ")
-    date_time_int32 = np.array(int(dtg.strftime("%Y%m%d%H")), dtype='int32')
-    GlobalAttrs['date_time'] = date_time_int32.item()
-    GlobalAttrs['converter'] = os.path.basename(__file__)
+    GlobalAttrs['datetimeRange'] = np.array([obs_data[('dateTime', metaDataName)][0].strftime("%Y-%m-%dT%H:%M:%SZ"),
+                                             obs_data[('dateTime', metaDataName)][-1].strftime("%Y-%m-%dT%H:%M:%SZ")], dtype=object)
+    GlobalAttrs['datetimeReference'] = dtg.strftime("%Y-%m-%dT%H:%M:%SZ")
 
     # pass parameters to the IODA writer
-# V2     'brightnessTemperature': ['nlocs', 'nchans']
     VarDims = {
-        'brightness_temperature': ['nlocs', 'nchans'],
-        'channelNumber': ['nchans'],
+        'brightnessTemperature': ['Location', 'Channel'],
+        'sensorChannelNumber': ['Channel'],
     }
 
     DimDict = {
-        'nlocs': nlocs,
-        'nchans': obs_data[('channelNumber', 'MetaData')],
+        'Location': nlocs,
+        'Channel': obs_data[('sensorChannelNumber', metaDataName)],
     }
     writer = iconv.IodaWriter(output_filename, locationKeyList, DimDict)
 
     VarAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
-# V2 VarAttrs[('brightnessTemperature', 'ObsValue')]['units'] = 'K'
-# V2 VarAttrs[('brightnessTemperature', 'ObsError')]['units'] = 'K'
-# V2 VarAttrs[('brightnessTemperature', 'PreQC')]['units'] = 'unitless'
-    VarAttrs[('brightness_temperature', 'ObsValue')]['units'] = 'K'
-    VarAttrs[('brightness_temperature', 'ObsError')]['units'] = 'K'
-    VarAttrs[('brightness_temperature', 'PreQC')]['units'] = 'unitless'
-
-    missing_value = 9.96921e+36
-    int_missing_value = -2147483647
-# V2 VarAttrs[('brightnessTemperature', 'ObsValue')]['_FillValue'] = missing_value
-# V2 VarAttrs[('brightnessTemperature', 'ObsError')]['_FillValue'] = missing_value
-# V2 VarAttrs[('brightnessTemperature', 'PreQC')]['_FillValue'] = int_missing_value
-    VarAttrs[('brightness_temperature', 'ObsValue')]['_FillValue'] = missing_value
-    VarAttrs[('brightness_temperature', 'ObsError')]['_FillValue'] = missing_value
-    VarAttrs[('brightness_temperature', 'PreQC')]['_FillValue'] = int_missing_value
-
-#   there can be more than one input file
-#   GlobalAttrs['converter'] = os.path.basename(__file__)
+
+    set_obspace_attributes(VarAttrs)
+    set_metadata_attributes(VarAttrs)
+
     # final write to IODA file
     writer.BuildIoda(obs_data, VarDims, VarAttrs, GlobalAttrs)
 
@@ -188,54 +189,44 @@ def get_data(f, g, obs_data):
     # 'spatial_lbl_len', 'subsat_lat', 'subsat_lon', 'sun_glint_dist', 'sun_glint_lat', 'sun_glint_lon',
     # 'surf_alt', 'surf_alt_sdev', 'utc_tuple', 'utc_tuple_lbl', 'utc_tuple_lbl_len', 'view_ang', 'warm_nedt', 'xtrack'
 
-    WMO_sat_ID = get_WMO_satellite_ID(f.filename)
-
     # example: dimension ( 180, 96 ) == dimension( nscan, nbeam_pos )
     try:
         nscans = np.shape(g['lat'])[0]
         nbeam_pos = np.shape(g['lat'])[1]
-        obs_data[('latitude', 'MetaData')] = np.array(g['lat'][:, :].flatten(), dtype='float32')
-        obs_data[('longitude', 'MetaData')] = np.array(g['lon'][:, :].flatten(), dtype='float32')
-        obs_data[('channelNumber', 'MetaData')] = np.array(g['channel'][:], dtype='int32')
-# V2     obs_data[('fieldOfViewNumber', 'MetaData')] = np.tile(np.arange(nbeam_pos, dtype='int32') + 1, (nscans, 1)).flatten()
-        obs_data[('scan_position', 'MetaData')] = np.tile(np.arange(nbeam_pos, dtype='float32') + 1, (nscans, 1)).flatten()
-# V2     obs_data[('solarZenithAngle', 'MetaData')] = np.array(g['sol_zen'][:, :].flatten(), dtype='float32')
-        obs_data[('solar_zenith_angle', 'MetaData')] = np.array(g['sol_zen'][:, :].flatten(), dtype='float32')
-# V2     obs_data[('solarAzimuthAngle', 'MetaData')] = np.array(g['sol_azi'][:, :].flatten(), dtype='float32')
-        obs_data[('solar_azimuth_angle', 'MetaData')] = np.array(g['sol_azi'][:, :].flatten(), dtype='float32')
-# V2     obs_data[('sensorZenithAngle', 'MetaData')] = np.array(g['sat_zen'][:, :].flatten(), dtype='float32')
-        obs_data[('sensor_zenith_angle', 'MetaData')] = np.array(g['sat_zen'][:, :].flatten(), dtype='float32')
-# V2     obs_data[('sensorAzimuthAngle', 'MetaData')] = np.array(g['sat_azi'][:, :].flatten(), dtype='float32')
-        obs_data[('sensor_azimuth_angle', 'MetaData')] = np.array(g['sat_azi'][:, :].flatten(), dtype='float32')
-        obs_data[('sensor_view_angle', 'MetaData')] = np.array(g['view_ang'][:, :].flatten(), dtype='float32')
-        nlocs = len(obs_data[('latitude', 'MetaData')])
-        obs_data[('satelliteId', 'MetaData')] = np.full((nlocs), WMO_sat_ID, dtype='int32')
-        obs_data[('datetime', 'MetaData')] = np.array(get_string_dtg(g['obs_time_utc'][:, :, :]), dtype=object)
+        obs_data[('latitude', metaDataName)] = np.array(g['lat'][:, :].flatten(), dtype='float32')
+        obs_data[('longitude', metaDataName)] = np.array(g['lon'][:, :].flatten(), dtype='float32')
+        obs_data[('sensorChannelNumber', metaDataName)] = np.array(g['channel'][:], dtype='int32')
+        obs_data[('fieldOfViewNumber', metaDataName)] = np.tile(np.arange(nbeam_pos, dtype='int32') + 1, (nscans, 1)).flatten()
+        obs_data[('sensorScanPosition', metaDataName)] = np.tile(np.arange(nbeam_pos, dtype='int32') + 1, (nscans, 1)).flatten()
+        obs_data[('solarZenithAngle', metaDataName)] = np.array(g['sol_zen'][:, :].flatten(), dtype='float32')
+        obs_data[('solarAzimuthAngle', metaDataName)] = np.array(g['sol_azi'][:, :].flatten(), dtype='float32')
+        obs_data[('sensorZenithAngle', metaDataName)] = np.array(g['sat_zen'][:, :].flatten(), dtype='float32')
+        obs_data[('sensorAzimuthAngle', metaDataName)] = np.array(g['sat_azi'][:, :].flatten(), dtype='float32')
+        obs_data[('sensorViewAngle', metaDataName)] = np.array(g['view_ang'][:, :].flatten(), dtype='float32')
+        nlocs = len(obs_data[('latitude', metaDataName)])
+        obs_data[('dateTime', metaDataName)] = np.array(get_observation_time(g['obs_time_utc'][:, :, :]), dtype='object')
 
     # BaseException is a catch-all mechamism
     except BaseException:
         # this section is for the NOAA CLASS files and need to be tested
-        obs_data[('latitude', 'MetaData')] = np.array(g['All_Data']['ATMS-SDR-GEO_All']['Latitude'][:, :].flatten(), dtype='float32')
-        obs_data[('longitude', 'MetaData')] = np.array(g['All_Data']['ATMS-SDR-GEO_All']['Longitude'][:, :].flatten(), dtype='float32')
+        obs_data[('latitude', metaDataName)] = np.array(g['All_Data']['ATMS-SDR-GEO_All']['Latitude'][:, :].flatten(), dtype='float32')
+        obs_data[('longitude', metaDataName)] = np.array(g['All_Data']['ATMS-SDR-GEO_All']['Longitude'][:, :].flatten(), dtype='float32')
 
     # example: dimension ( 180, 96, 22 ) == dimension( nscan, nbeam_pos, nchannel )
     try:
-        nchans = len(obs_data[('channelNumber', 'MetaData')])
-        nlocs = len(obs_data[('latitude', 'MetaData')])
-# V2     obs_data[('brightnessTemperature', "ObsValue")] = np.array(np.vstack(g['antenna_temp']), dtype='float32')
-# V2     obs_data[('brightnessTemperature', "ObsError")] = np.full((nlocs, nchans), 5.0, dtype='float32')
-# V2     obs_data[('brightnessTemperature', "PreQC")] = np.full((nlocs, nchans), 0, dtype='int32')
-        obs_data[('brightness_temperature', "ObsValue")] = np.array(np.vstack(g['antenna_temp']), dtype='float32')
-        obs_data[('brightness_temperature', "ObsError")] = np.full((nlocs, nchans), 5.0, dtype='float32')
-        obs_data[('brightness_temperature', "PreQC")] = np.full((nlocs, nchans), 0, dtype='int32')
+        nchans = len(obs_data[('sensorChannelNumber', metaDataName)])
+        nlocs = len(obs_data[('latitude', metaDataName)])
+        obs_data[('brightnessTemperature', obsValName)] = np.array(np.vstack(g['antenna_temp']), dtype='float32')
+        obs_data[('brightnessTemperature', obsErrName)] = np.full((nlocs, nchans), 5.0, dtype='float32')
+        obs_data[('brightnessTemperature', qcName)] = np.full((nlocs, nchans), 0, dtype='int32')
     except BaseException:
         # this section is for the NOAA CLASS files and need to be tested
         scaled_data = np.vstack(f['All_Data']['ATMS-SDR_All']['BrightnessTemperature'])
         scale_fac = f['All_Data']['ATMS-SDR_All']['BrightnessTemperatureFactors'][:].flatten()
 
-        obs_data[('brightnessTemperature', "ObsValue")] = np.array((scaled_data * scale_fac[0]) + scale_fac[1], dtype='float32')
-        obs_data[('brightnessTemperature', "ObsError")] = np.full((nlocs, nchans), 5.0, dtype='float32')
-        obs_data[('brightnessTemperature', "PreQC")] = np.full((nlocs, nchans), 0, dtype='int32')
+        obs_data[('brightnessTemperature', obsValName)] = np.array((scaled_data * scale_fac[0]) + scale_fac[1], dtype='float32')
+        obs_data[('brightnessTemperature', obsErrName)] = np.full((nlocs, nchans), 5.0, dtype='float32')
+        obs_data[('brightnessTemperature', qcName)] = np.full((nlocs, nchans), 0, dtype='int32')
 
     return obs_data
 
@@ -257,45 +248,38 @@ def get_WMO_satellite_ID(filename):
     return WMO_sat_ID
 
 
-def get_string_dtg(obs_time_utc):
+def get_observation_time(obs_time_utc):
 
     year = obs_time_utc[:, :, 0].flatten()
     month = obs_time_utc[:, :, 1].flatten()
     day = obs_time_utc[:, :, 2].flatten()
     hour = obs_time_utc[:, :, 3].flatten()
     minute = obs_time_utc[:, :, 4].flatten()
+    second = 0
     dtg = []
     for i, yyyy in enumerate(year):
-        cdtg = ("%4i-%.2i-%.2iT%.2i:%.2i:00Z" % (yyyy, month[i], day[i], hour[i], minute[i]))
-        dtg.append(cdtg)
+        observation_time = datetime(yyyy, month[i], day[i], hour[i], minute[i], second)
+        dtg.append(observation_time)
 
     return dtg
 
 
 def init_obs_loc():
-    # V2     ('brightnessTemperature', "ObsValue"): [],
-    # V2     ('brightnessTemperature', "ObsError"): [],
-    # V2     ('brightnessTemperature', "PreQC"): [],
-    # V2     ('fieldOfViewNumber', 'MetaData'): [],
-    # V2     ('solarZenithAngle', 'MetaData'): [],
-    # V2     ('solarAzimuthAngle', 'MetaData'): [],
-    # V2     ('sensorZenithAngle', 'MetaData'): [],
-    # V2     ('sensorAzimuthAngle', 'MetaData'): [],
     obs = {
-        ('brightness_temperature', "ObsValue"): [],
-        ('brightness_temperature', "ObsError"): [],
-        ('brightness_temperature', "PreQC"): [],
-        ('satelliteId', 'MetaData'): [],
-        ('channelNumber', 'MetaData'): [],
-        ('latitude', 'MetaData'): [],
-        ('longitude', 'MetaData'): [],
-        ('datetime', 'MetaData'): [],
-        ('scan_position', 'MetaData'): [],
-        ('solar_zenith_angle', 'MetaData'): [],
-        ('solar_azimuth_angle', 'MetaData'): [],
-        ('sensor_zenith_angle', 'MetaData'): [],
-        ('sensor_view_angle', 'MetaData'): [],
-        ('sensor_azimuth_angle', 'MetaData'): [],
+        ('brightnessTemperature', obsValName): [],
+        ('brightnessTemperature', obsErrName): [],
+        ('brightnessTemperature', qcName): [],
+        ('sensorChannelNumber', metaDataName): [],
+        ('latitude', metaDataName): [],
+        ('longitude', metaDataName): [],
+        ('dateTime', metaDataName): [],
+        ('sensorScanPosition', metaDataName): [],
+        ('fieldOfViewNumber', metaDataName): [],
+        ('solarZenithAngle', metaDataName): [],
+        ('solarAzimuthAngle', metaDataName): [],
+        ('sensorZenithAngle', metaDataName): [],
+        ('sensorAzimuthAngle', metaDataName): [],
+        ('sensorViewAngle', metaDataName): [],
     }
 
     return obs
@@ -312,6 +296,27 @@ def concat_obs_dict(obs_data, append_obs_data):
             print("WARNING: ", gv_key, " is missing from append_obs_data dictionary")
 
 
+def set_metadata_attributes(VarAttrs):
+    VarAttrs[('sensorZenithAngle', metaDataName)]['units'] = 'degree'
+    VarAttrs[('sensorViewAngle', metaDataName)]['units'] = 'degree'
+    VarAttrs[('solarZenithAngle', metaDataName)]['units'] = 'degree'
+    VarAttrs[('sensorAzimuthAngle', metaDataName)]['units'] = 'degree'
+    VarAttrs[('solarAzimuthAngle', metaDataName)]['units'] = 'degree'
+
+    return VarAttrs
+
+
+def set_obspace_attributes(VarAttrs):
+    VarAttrs[('brightnessTemperature', obsValName)]['units'] = 'K'
+    VarAttrs[('brightnessTemperature', obsErrName)]['units'] = 'K'
+
+    VarAttrs[('brightnessTemperature', obsValName)]['_FillValue'] = float_missing_value
+    VarAttrs[('brightnessTemperature', obsErrName)]['_FillValue'] = float_missing_value
+    VarAttrs[('brightnessTemperature', qcName)]['_FillValue'] = int_missing_value
+
+    return VarAttrs
+
+
 if __name__ == "__main__":
 
     parser = argparse.ArgumentParser(
diff --git a/src/land/CMakeLists.txt b/src/land/CMakeLists.txt
index e0d7c4b67..f85915e17 100644
--- a/src/land/CMakeLists.txt
+++ b/src/land/CMakeLists.txt
@@ -1,6 +1,4 @@
 list(APPEND programs
-  ims_scf2ioda.py
-  afwa_snod2ioda.py
   ghcn_snod2ioda.py
   smap_ssm2ioda.py
   smos_ssm2ioda.py
diff --git a/src/land/afwa_snod2ioda.py b/src/land/afwa_snod2ioda.py
deleted file mode 100644
index b7547ce6a..000000000
--- a/src/land/afwa_snod2ioda.py
+++ /dev/null
@@ -1,176 +0,0 @@
-#!/usr/bin/env python3
-#
-# (C) Copyright 2021 NOAA/NWS/NCEP/EMC
-#
-# This software is licensed under the terms of the Apache Licence Version 2.0
-# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
-###################################################
-import pygrib
-import time, os, sys
-import argparse
-import netCDF4 as nc
-import numpy as np
-import pyproj
-from datetime import datetime, timedelta
-from pathlib import Path
-
-IODA_CONV_PATH = Path(__file__).parent/"@SCRIPT_LIB_PATH@"
-if not IODA_CONV_PATH.is_dir():
-    IODA_CONV_PATH = Path(__file__).parent/'..'/'lib-python'
-sys.path.append(str(IODA_CONV_PATH.resolve()))
-
-import ioda_conv_engines as iconv
-from collections import defaultdict, OrderedDict
-from orddicts import DefaultOrderedDict
-
-locationKeyList = [
-    ("latitude", "float"),
-    ("longitude", "float"),
-    ("datetime", "string")
-]
-
-obsvars = {
-    'snow_depth': 'snowDepth',
-}
-
-AttrData = {
-    'converter': os.path.basename(__file__),
-}
-
-DimDict = {
-}
-
-VarDims = {
-    'snowDepth': ['nlocs'],
-}
-
-os.environ["TZ"] = "UTC"
-
-
-class AFWA(object):
-
-    def __init__(self, filename, mask):
-        self.filename = filename
-        self.mask = mask
-        self.varDict = defaultdict(lambda: defaultdict(dict))
-        self.outdata = defaultdict(lambda: DefaultOrderedDict(OrderedDict))
-        self.varAttrs = defaultdict(lambda: DefaultOrderedDict(OrderedDict))
-        self._read()
-
-    def _read(self):
-        # set up variable names for IODA
-        for iodavar in ['snowDepth']:
-            self.varDict[iodavar]['valKey'] = iodavar, iconv.OvalName()
-            self.varDict[iodavar]['errKey'] = iodavar, iconv.OerrName()
-            self.varDict[iodavar]['qcKey'] = iodavar, iconv.OqcName()
-            self.varAttrs[iodavar, iconv.OvalName()]['coordinates'] = 'longitude latitude'
-            self.varAttrs[iodavar, iconv.OerrName()]['coordinates'] = 'longitude latitude'
-            self.varAttrs[iodavar, iconv.OqcName()]['coordinates'] = 'longitude latitude'
-            self.varAttrs[iodavar, iconv.OvalName()]['units'] = 'm'
-            self.varAttrs[iodavar, iconv.OerrName()]['units'] = 'm'
-            self.varAttrs[iodavar, iconv.OqcName()]['units'] = 'unitless'
-
-        data = pygrib.open(self.filename)
-        lat, lon = data[1].latlons()
-        lons = lon[:].ravel()
-        lats = lat[:].ravel()
-        vals = data[1].values[:].ravel()
-
-        # use stereographic projection to calculate lat/lon as read of
-        # lat/lon is not correct for afwa grib1 file
-        lat1 = data[1]['latitudeOfFirstGridPointInDegrees']
-        lon1 = data[1]['longitudeOfFirstGridPointInDegrees']
-        nx = data[1]['Nx']
-        ny = data[1]['Ny']
-        dx = data[1]['DxInMetres']
-        dy = data[1]['DyInMetres']
-        # this works for corner assumption to get symmetric data
-        dxfac = 1.000376522
-        dx = dxfac*dx
-        dy = dxfac*dy
-
-        myparams = data[1].projparams
-        # reset Lat of True Origin(lat_ts)for Soutern Hemisphere grib file
-        if myparams['lat_0'] == -90.0:
-            myparams['lat_ts'] = -60.0
-
-        pj = pyproj.Proj(myparams)
-        llcrnrx, llcrnry = pj(lon1, lat1)
-        x = llcrnrx - dx*np.arange(nx)
-        y = llcrnry + dy*np.arange(ny)
-        x, y = np.meshgrid(x, y)
-        lon, lat = pj(x, y, inverse=True)
-        lons = lon[:].ravel()
-        lats = lat[:].ravel()
-        # setup snowCover and mask_flag
-        vals = vals.astype('float32')
-        errs = 0.0*vals.astype('float32')
-        qflg = 0*vals.astype('int32')
-        lats = lats.astype('float32')
-        lons = lons.astype('float32')
-        times = np.empty_like(vals, dtype=object)
-
-        if self.mask == "maskout":
-            mask = np.logical_not(vals.mask)
-            vals = vals[mask]
-            errs = errs[mask]
-            qflg = qflg[mask]
-            lons = lons[mask]
-            lats = lats[mask]
-            times = times[mask]
-        # get global attributes
-        start_datetime = data[1].analDate
-        base_datetime = start_datetime.isoformat() + "Z"
-        data.close()
-        AttrData['date_time_string'] = base_datetime
-
-        for i in range(len(lons)):
-            times[i] = base_datetime
-
-        # add metadata variables
-        self.outdata[('datetime', 'MetaData')] = times
-        self.outdata[('latitude', 'MetaData')] = lats
-        self.outdata[('longitude', 'MetaData')] = lons
-
-        # add output variables
-        for iodavar in ['snowDepth']:
-            self.outdata[self.varDict[iodavar]['valKey']] = vals
-            self.outdata[self.varDict[iodavar]['errKey']] = errs
-            self.outdata[self.varDict[iodavar]['qcKey']] = qflg
-        DimDict['nlocs'] = len(self.outdata[('datetime', 'MetaData')])
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
-
-
-def main():
-
-    parser = argparse.ArgumentParser(
-        description=('Read AFWA snow depth file(s) and Converter'
-                     ' of native grib format for observations of snow'
-                     ' depth to IODA netCDF format.')
-    )
-    parser.add_argument('-i', '--input',
-                        help="name of afwa snow depth input file(s)",
-                        type=str, required=True)
-    parser.add_argument('-o', '--output',
-                        help="name of ioda output file",
-                        type=str, required=True)
-    optional = parser.add_argument_group(title='optional arguments')
-    optional.add_argument(
-        '-m', '--mask',
-        help="maskout missing values: maskout/default, default=none",
-        type=str, required=True)
-
-    args = parser.parse_args()
-
-    # Read in the AFWA snow depth data
-    snod = AFWA(args.input, args.mask)
-
-    # setup the IODA writer
-    writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
-
-    # write everything out
-    writer.BuildIoda(snod.outdata, VarDims, snod.varAttrs, AttrData)
-
-
-if __name__ == '__main__':
-    main()
diff --git a/src/land/ascat_ssm2ioda.py b/src/land/ascat_ssm2ioda.py
index 3ebc8730d..63ff9bfb4 100755
--- a/src/land/ascat_ssm2ioda.py
+++ b/src/land/ascat_ssm2ioda.py
@@ -27,7 +27,7 @@
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string")
+    ("dateTime", "long")
 ]
 
 obsvars = {
@@ -42,9 +42,12 @@
 }
 
 VarDims = {
-    'soilMoistureNormalized': ['nlocs'],
+    'soilMoistureNormalized': ['Location'],
 }
 
+iso8601_string = '1970-01-01T00:00:00Z'
+epoch = datetime.fromisoformat(iso8601_string[:-1])
+
 
 class ascat(object):
     def __init__(self, filename, mask):
@@ -65,19 +68,20 @@ def _read(self):
             self.varAttrs[iodavar, iconv.OvalName()]['coordinates'] = 'longitude latitude'
             self.varAttrs[iodavar, iconv.OerrName()]['coordinates'] = 'longitude latitude'
             self.varAttrs[iodavar, iconv.OqcName()]['coordinates'] = 'longitude latitude'
-            self.varAttrs[iodavar, iconv.OvalName()]['units'] = 'percent'
-            self.varAttrs[iodavar, iconv.OerrName()]['units'] = 'percent'
-            self.varAttrs[iodavar, iconv.OqcName()]['units'] = 'unitless'
+            self.varAttrs[iodavar, iconv.OvalName()]['units'] = '1'
+            self.varAttrs[iodavar, iconv.OerrName()]['units'] = '1'
 
         # open input file name
         ncd = nc.Dataset(self.filename, 'r')
         # set and get global attributes
-        AttrData["satellite"] = ncd.getncattr('source')
+        # A satellite ID is expected for satellite attribute, use sensor instead
+        AttrData['sensor'] = ncd.getncattr('source')
         AttrData['platform'] = ncd.getncattr('platform_long_name')
         lats = ncd.variables['lat'][:].ravel()
         lons = ncd.variables['lon'][:].ravel()
         vals = ncd.variables['soil_moisture'][:].ravel()
         errs = ncd.variables['soil_moisture_error'][:].ravel()
+        errs = errs*0.01     # Scale from zero to one.
         wflg = ncd.variables['wetland_flag'][:].ravel()
         tflg = ncd.variables['topography_flag'][:].ravel()
         times = np.empty_like(vals, dtype=object)
@@ -88,6 +92,7 @@ def _read(self):
         vals = vals.astype('float32')
         lats = lats.astype('float32')
         lons = lons.astype('float32')
+        vals = vals*0.01
         qflg = 0*vals.astype('int32')
         wflg = wflg.astype('int32')
         tflg = tflg.astype('int32')
@@ -104,25 +109,26 @@ def _read(self):
             secs = secs[mask]
             times = times[mask]
 
-        for i in range(len(lons)):
+        for i in range(len(secs)):
             base_date = datetime(2000, 1, 1) + timedelta(seconds=int(secs[i]))
-            base_datetime = base_date.strftime("%Y-%m-%dT%H:%M:%SZ")
-            AttrData['date_time_string'] = base_datetime
-            times[i] = base_datetime
+            time_offset = np.int64(round((base_date - epoch).total_seconds()))
+            times[i] = time_offset
+
+        self.varAttrs['dateTime', 'MetaData']['units'] = 'seconds since ' + iso8601_string
 
         # add metadata variables
-        self.outdata[('datetime', 'MetaData')] = times
-        self.outdata[('latitude', 'MetaData')] = lats
-        self.outdata[('longitude', 'MetaData')] = lons
-        self.outdata[('wetlandFraction', 'MetaData')] = wflg
-        self.outdata[('topographyComplexity', 'MetaData')] = tflg
+        self.outdata[('dateTime', 'MetaData')] = np.array(times, dtype=np.int64)
+        self.outdata[('latitude', 'MetaData')] = np.array(lats, dtype=np.float32)
+        self.outdata[('longitude', 'MetaData')] = np.array(lons, dtype=np.float32)
+        self.outdata[('wetlandFraction', 'MetaData')] = np.array(wflg, dtype=np.float32)
+        self.outdata[('topographyComplexity', 'MetaData')] = np.array(tflg, dtype=np.float32)
 
-        for iodavar in ['soilMoistureNormalized']:
-            self.outdata[self.varDict[iodavar]['valKey']] = vals
-            self.outdata[self.varDict[iodavar]['errKey']] = errs
-            self.outdata[self.varDict[iodavar]['qcKey']] = qflg
-        DimDict['nlocs'] = len(self.outdata[('datetime', 'MetaData')])
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+        iodavar = 'soilMoistureNormalized'
+        self.outdata[self.varDict[iodavar]['valKey']] = np.array(vals, dtype=np.float32)
+        self.outdata[self.varDict[iodavar]['errKey']] = np.array(errs, dtype=np.float32)
+        self.outdata[self.varDict[iodavar]['qcKey']] = np.array(qflg, dtype=np.int32)
+
+        DimDict['Location'] = len(self.outdata[('dateTime', 'MetaData')])
 
 
 def main():
@@ -156,8 +162,8 @@ def main():
     # setup the IODA writer
     writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
 
-    ssm.varAttrs[('wetlandFraction', 'MetaData')]['units'] = 'unitless'
-    ssm.varAttrs[('topographyComplexity', 'MetaData')]['units'] = 'unitless'
+    ssm.varAttrs[('wetlandFraction', 'MetaData')]['units'] = '1'
+    ssm.varAttrs[('topographyComplexity', 'MetaData')]['units'] = '1'
 
     # write everything out
     writer.BuildIoda(ssm.outdata, VarDims, ssm.varAttrs, AttrData)
diff --git a/src/land/ghcn_snod2ioda.py b/src/land/ghcn_snod2ioda.py
index a6f53721b..f48d128c5 100755
--- a/src/land/ghcn_snod2ioda.py
+++ b/src/land/ghcn_snod2ioda.py
@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 #
-# (C) Copyright 2021 NOAA/NWS/NCEP/EMC
+# (C) Copyright 2021-2022 NOAA/NWS/NCEP/EMC
 #
 # This software is licensed under the terms of the Apache Licence Version 2.0
 #
@@ -27,7 +27,7 @@
     ("latitude", "float"),
     ("longitude", "float"),
     ("height", "float"),
-    ("datetime", "string")
+    ("dateTime", "string")
 ]
 
 obsvars = {
@@ -35,14 +35,13 @@
 }
 
 AttrData = {
-    'converter': os.path.basename(__file__),
 }
 
 DimDict = {
 }
 
 VarDims = {
-    'totalSnowDepth': ['nlocs'],
+    'totalSnowDepth': ['Location'],
 }
 
 
@@ -70,9 +69,8 @@ def _read(self):
         self.varAttrs[iodavar, iconv.OvalName()]['coordinates'] = 'longitude latitude'
         self.varAttrs[iodavar, iconv.OerrName()]['coordinates'] = 'longitude latitude'
         self.varAttrs[iodavar, iconv.OqcName()]['coordinates'] = 'longitude latitude'
-        self.varAttrs[iodavar, iconv.OvalName()]['units'] = 'mm'
-        self.varAttrs[iodavar, iconv.OerrName()]['units'] = 'mm'
-        self.varAttrs[iodavar, iconv.OqcName()]['units'] = 'unitless'
+        self.varAttrs[iodavar, iconv.OvalName()]['units'] = 'm'
+        self.varAttrs[iodavar, iconv.OerrName()]['units'] = 'm'
 
         def assignValue(colrowValue, df400):
             if colrowValue == '' or pd.isnull(colrowValue):
@@ -162,14 +160,14 @@ def assignValue(colrowValue, df400):
         my_date = datetime.strptime(startdate, "%Y%m%d")
         start_datetime = my_date.strftime('%Y-%m-%d')
         base_datetime = start_datetime + 'T18:00:00Z'
-        AttrData['date_time_string'] = base_datetime
 
         for i in range(len(vals)):
             if vals[i] >= 0.0:
-                errs[i] = 40.0
+                errs[i] = 0.04
+                vals[i] = 0.001*vals[i]
             times[i] = base_datetime
         # add metadata variables
-        self.outdata[('datetime', 'MetaData')] = times
+        self.outdata[('dateTime', 'MetaData')] = times
         self.outdata[('stationIdentification', 'MetaData')] = sites
         self.outdata[('latitude', 'MetaData')] = lats
         self.outdata[('longitude', 'MetaData')] = lons
@@ -180,8 +178,7 @@ def assignValue(colrowValue, df400):
         self.outdata[self.varDict[iodavar]['errKey']] = errs
         self.outdata[self.varDict[iodavar]['qcKey']] = qflg
 
-        DimDict['nlocs'] = len(self.outdata[('datetime', 'MetaData')])
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+        DimDict['Location'] = len(self.outdata[('dateTime', 'MetaData')])
 
 
 def main():
diff --git a/src/land/ims_scf2ioda.py b/src/land/ims_scf2ioda.py
deleted file mode 100644
index 78476567a..000000000
--- a/src/land/ims_scf2ioda.py
+++ /dev/null
@@ -1,155 +0,0 @@
-#!/usr/bin/env python3
-#
-# (C) Copyright 2021 NOAA/NWS/NCEP/EMC
-#
-# This software is licensed under the terms of the Apache Licence Version 2.0
-# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
-#
-import pygrib
-import time, os, sys
-import argparse
-import netCDF4 as nc
-import numpy as np
-from datetime import datetime, timedelta
-from pathlib import Path
-
-IODA_CONV_PATH = Path(__file__).parent/"@SCRIPT_LIB_PATH@"
-if not IODA_CONV_PATH.is_dir():
-    IODA_CONV_PATH = Path(__file__).parent/'..'/'lib-python'
-sys.path.append(str(IODA_CONV_PATH.resolve()))
-
-import ioda_conv_engines as iconv
-from collections import defaultdict, OrderedDict
-from orddicts import DefaultOrderedDict
-
-locationKeyList = [
-    ("latitude", "float"),
-    ("longitude", "float"),
-    ("datetime", "string")
-]
-
-obsvars = {
-    'snow_cover_fraction': 'snowCover',
-}
-
-AttrData = {
-    'converter': os.path.basename(__file__),
-}
-
-DimDict = {
-}
-
-VarDims = {
-    'snowCover': ['nlocs'],
-}
-
-
-class imsscf(object):
-
-    def __init__(self, filename, mask):
-        self.filename = filename
-        self.mask = mask
-        self.varDict = defaultdict(lambda: defaultdict(dict))
-        self.outdata = defaultdict(lambda: DefaultOrderedDict(OrderedDict))
-        self.varAttrs = defaultdict(lambda: DefaultOrderedDict(OrderedDict))
-        self._read()
-
-    def _read(self):
-
-        # set up variable names for IODA
-        for iodavar in ['snowCover']:
-            self.varDict[iodavar]['valKey'] = iodavar, iconv.OvalName()
-            self.varDict[iodavar]['errKey'] = iodavar, iconv.OerrName()
-            self.varDict[iodavar]['qcKey'] = iodavar, iconv.OqcName()
-            self.varAttrs[iodavar, iconv.OvalName()]['coordinates'] = 'longitude latitude'
-            self.varAttrs[iodavar, iconv.OerrName()]['coordinates'] = 'longitude latitude'
-            self.varAttrs[iodavar, iconv.OqcName()]['coordinates'] = 'longitude latitude'
-            self.varAttrs[iodavar, iconv.OvalName()]['units'] = 'percent'
-            self.varAttrs[iodavar, iconv.OerrName()]['units'] = 'percent'
-            self.varAttrs[iodavar, iconv.OqcName()]['units'] = 'unitless'
-
-        # read self.filename to get data
-        data = pygrib.open(self.filename)
-        lat, lon = data[1].latlons()
-        lons = lon[:].ravel()
-        lats = lat[:].ravel()
-        vals = data.select(name='Snow cover')[0].values[:].ravel()
-        # defined errors and qc
-        vals = vals.astype('float32')
-        lats = lats.astype('float32')
-        lons = lons.astype('float32')
-        errs = 0.08*vals
-        qflg = 0*vals.astype('int32')
-        times = np.empty_like(vals, dtype=object)
-
-        if self.mask == "maskout":
-            mask = np.logical_not(vals.mask)
-            vals = vals[mask]
-            errs = errs[mask]
-            qflg = qflg[mask]
-            lons = lons[mask]
-            lats = lats[mask]
-            times = times[mask]
-        # get global attributes
-        start_datetime = data[1].analDate
-        base_datetime = start_datetime.isoformat() + "Z"
-        # grbs.close()
-
-        # write global attributes out
-        self.satellite = "POES/GOES"
-        self.sensor = "IMS.Multisensor"
-        AttrData["observation_type"] = "Snow Cover Fraction"
-        AttrData["satellite"] = self.satellite
-        AttrData["sensor"] = self.sensor
-        AttrData['date_time_string'] = base_datetime
-
-        for i in range(len(lons)):
-            times[i] = base_datetime
-
-        # add metadata variables
-        self.outdata[('datetime', 'MetaData')] = times
-        self.outdata[('latitude', 'MetaData')] = lats
-        self.outdata[('longitude', 'MetaData')] = lons
-
-        # add output variables
-        for iodavar in ['snowCover']:
-            self.outdata[self.varDict[iodavar]['valKey']] = vals
-            self.outdata[self.varDict[iodavar]['errKey']] = errs
-            self.outdata[self.varDict[iodavar]['qcKey']] = qflg
-        DimDict['nlocs'] = len(self.outdata[('datetime', 'MetaData')])
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
-
-
-def main():
-
-    parser = argparse.ArgumentParser(
-        description=('Read IMS snow cover fraction file(s) and Converter'
-                     ' of native grib2 format for observations of snow'
-                     ' cover fraction to IODA netCDF format.')
-    )
-    parser.add_argument('-i', '--input',
-                        help="name of ims snow cover input file(s)",
-                        type=str, required=True)
-    parser.add_argument('-o', '--output',
-                        help="name of ioda output file",
-                        type=str, required=True)
-    optional = parser.add_argument_group(title='optional arguments')
-    optional.add_argument(
-        '-m', '--mask',
-        help="maskout missing values: maskout/default, default=none",
-        type=str, required=True)
-
-    args = parser.parse_args()
-
-    # Read in the IMS snow cover data
-    scf = imsscf(args.input, args.mask)
-
-    # setup the IODA writer
-    writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
-
-    # write the data out
-    writer.BuildIoda(scf.outdata, VarDims, scf.varAttrs, AttrData)
-
-
-if __name__ == '__main__':
-    main()
diff --git a/src/land/imsfv3_scf2ioda.py b/src/land/imsfv3_scf2ioda.py
index 800e5a6b1..bd805d72a 100644
--- a/src/land/imsfv3_scf2ioda.py
+++ b/src/land/imsfv3_scf2ioda.py
@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 #
-# (C) Copyright 2021 NOAA/NWS/NCEP/EMC
+# (C) Copyright 2020-2022 NOAA/NWS/NCEP/EMC
 #
 # This software is licensed under the terms of the Apache Licence Version 2.0
 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
@@ -28,7 +28,7 @@
     ("latitude", "float"),
     ("longitude", "float"),
     ("height", "float"),
-    ("datetime", "string")
+    ("dateTime", "string")
 ]
 
 obsvars = {
@@ -37,15 +37,14 @@
 }
 
 AttrData = {
-    'converter': os.path.basename(__file__),
 }
 
 DimDict = {
 }
 
 VarDims = {
-    'snowCoverFraction': ['nlocs'],
-    'totalSnowDepth': ['nlocs'],
+    'snowCoverFraction': ['Location'],
+    'totalSnowDepth': ['Location'],
 }
 
 
@@ -71,22 +70,19 @@ def _read(self):
             if iodavar == 'snowCoverFraction':
                 self.varAttrs[iodavar, iconv.OvalName()]['units'] = '1'
                 self.varAttrs[iodavar, iconv.OerrName()]['units'] = '1'
-                self.varAttrs[iodavar, iconv.OqcName()]['units'] = 'unitless'
                 self.varAttrs[iodavar, iconv.OvalName()]['_FillValue'] = -999.
                 self.varAttrs[iodavar, iconv.OerrName()]['_FillValue'] = -999.
                 self.varAttrs[iodavar, iconv.OqcName()]['_FillValue'] = -999
 
             if iodavar == 'totalSnowDepth':
-                self.varAttrs[iodavar, iconv.OvalName()]['units'] = 'mm'
-                self.varAttrs[iodavar, iconv.OerrName()]['units'] = 'mm'
-                self.varAttrs[iodavar, iconv.OqcName()]['units'] = 'unitless'
+                self.varAttrs[iodavar, iconv.OvalName()]['units'] = 'm'
+                self.varAttrs[iodavar, iconv.OerrName()]['units'] = 'm'
                 self.varAttrs[iodavar, iconv.OvalName()]['_FillValue'] = -999.
                 self.varAttrs[iodavar, iconv.OerrName()]['_FillValue'] = -999.
                 self.varAttrs[iodavar, iconv.OqcName()]['_FillValue'] = -999
 
         # read netcdf file
         ncd = nc.Dataset(self.filename)
-        AttrData["sensor"] = "IMS Multisensor"
         lons = ncd.variables['lon'][:]
         lats = ncd.variables['lat'][:]
         oros = ncd.variables['oro'][:]
@@ -103,7 +99,7 @@ def _read(self):
         qdflg = 0*sndv.astype('int32')
         errsc = 0.0*sncv
         errsd = 0.0*sndv
-        errsd[:] = 80.0
+        errsd[:] = 0.08
         ncd.close()
 
         times = np.empty_like(sncv, dtype=object)
@@ -113,13 +109,13 @@ def _read(self):
         my_date = datetime.strptime(str_date, "%Y%m%d")
         start_datetime = my_date.strftime('%Y-%m-%d')
         base_datetime = start_datetime + 'T18:00:00Z'
-        AttrData['date_time_string'] = base_datetime
 
         for i in range(len(lats)):
             times[i] = base_datetime
+            sndv[i] = 0.001*sndv[i]
 
         # add metadata variables
-        self.outdata[('datetime', 'MetaData')] = times
+        self.outdata[('dateTime', 'MetaData')] = times
         self.outdata[('latitude', 'MetaData')] = lats
         self.outdata[('longitude', 'MetaData')] = lons
         self.outdata[('height', 'MetaData')] = oros
@@ -136,8 +132,7 @@ def _read(self):
                     self.outdata[self.varDict[iodavar]['valKey']] = sndv
                     self.outdata[self.varDict[iodavar]['errKey']] = errsd
                     self.outdata[self.varDict[iodavar]['qcKey']] = qdflg
-        DimDict['nlocs'] = len(self.outdata[('datetime', 'MetaData')])
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+        DimDict['Location'] = len(self.outdata[('dateTime', 'MetaData')])
 
 
 def main():
diff --git a/src/land/owp_snow_obs.py b/src/land/owp_snow_obs.py
index 475ed3e10..62fb62aa8 100644
--- a/src/land/owp_snow_obs.py
+++ b/src/land/owp_snow_obs.py
@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 
-# (C) Copyright 2019 UCAR
+# (C) Copyright 2019-2022 UCAR
 # This software is licensed under the terms of the Apache Licence Version 2.0
 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
 
@@ -32,11 +32,11 @@
     to IODA output files. """)
 
 # obs file name -> ioda file name
-output_var_dict = {'snow_depth_m': 'snow_depth', 'snow_water_equivalent_mm': 'swe'}
+output_var_dict = {'snow_depth_m': 'totalSnowDepth', 'snow_water_equivalent_mm': 'snowWaterEquivalent'}
 # ioda file_name -> ioda file units
-output_var_unit_dict = {'snow_depth': 'm', 'swe': 'mm'}
+output_var_unit_dict = {'totalSnowDepth': 'm', 'snowWaterEquivalent': 'kg m-2'}
 one = 1.00000000000000
-output_conversion_factor = {'snow_depth': one, 'swe': one}
+output_conversion_factor = {'totalSnowDepth': one, 'snowWaterEquivalent': one}
 
 col_types = {
     'StnObjID': np.int32,
@@ -48,25 +48,22 @@
     'rec_elev_m': np.float32,
     'latitude': np.float64,
     'longitude': np.float64,
-    'datetime': str,
+    'dateTime': str,
     'variable_name': str}
 
 location_key_list = [
     ("latitude", "float"),
     ("longitude", "float"),
     ("height", "integer"),
-    ("datetime", "string"), ]
+    ("dateTime", "string"), ]
 
 dim_dict = {}
 
 var_dims = {
-    'snow_depth': ['nlocs'],
-    'swe': ['nlocs'], }
+    'totalSnowDepth': ['Location'],
+    'snowWaterEquivalent': ['Location'], }
 
-attr_data = {
-    'converter': os.path.basename(__file__),
-    'converter_version': 0.3,
-    'nvars': np.int32(len(var_dims)), }
+attr_data = {}
 
 fill_value = 9.96921e+36
 
@@ -108,7 +105,6 @@ def __init__(
 
     def _read(self):
         # print(f"Reading: {self.file_in}")
-        self.attr_data['obs_file'] = str(self.file_in.split('/')[-1])
         # use pandas to get the data lined up
         obs_df = pd.read_csv(self.file_in, header=0, index_col=False, dtype=col_types)
 
@@ -135,7 +131,7 @@ def _read(self):
             .sort_index()
             .reset_index())
 
-        self.attr_data['ref_date_time'] = (
+        self.attr_data['datetimeReference'] = (
             pd.to_datetime(obs_df.datetime[0])
             .round('D')
             .strftime('%Y-%m-%dT%H:%M:%SZ'))
@@ -173,14 +169,13 @@ def _read(self):
                     wh_not_var_other = np.where(np.isnan(obs_df[f'ObsValue {var_other}']))[0]  # 1-D
                     obs_df = obs_df.drop(wh_not_var_other).reset_index()
 
-        self.data[('datetime', 'MetaData')] = obs_df.datetime.values
+        self.data[('dateTime', 'MetaData')] = obs_df.datetime.values
         self.data[('latitude', 'MetaData')] = obs_df.latitude.values.astype('float32')
         self.data[('longitude', 'MetaData')] = obs_df.longitude.values.astype('float32')
 
         self.data[('height', 'MetaData')] = obs_df.rec_elev_m.values.astype('float32')
-        self.data[('station_id', 'MetaData')] = obs_df.StnID.values
+        self.data[('stationIdentification', 'MetaData')] = obs_df.StnID.values
         self.var_metadata[('height', 'MetaData')]['units'] = 'm'
-        self.var_metadata[('station_id', 'MetaData')]['units'] = 'unitless'
 
         for obs_var, ioda_var in output_var_dict.items():
             # define the ioda variable
@@ -190,10 +185,9 @@ def _read(self):
             # define ioda meta/ancillary
             for name in [iconv.OvalName(), iconv.OerrName(), iconv.OqcName()]:
                 self.var_metadata[ioda_var, name]['coordinates'] = 'longitude latitude'
-                self.var_metadata[ioda_var, name]['units'] = output_var_unit_dict[ioda_var]  # not really for Oqc... but
-            # just kidding for OqcName... a lazy tag along above, fix now (less code to overwrite)
-            self.var_metadata[ioda_var, iconv.OqcName()]['units'] = 'unitless'
-            # the data
+                if(iconv.OqcName() != name):
+                    self.var_metadata[ioda_var, name]['units'] = output_var_unit_dict[ioda_var]
+
             conv_fact = output_conversion_factor[ioda_var]
             self.data[self.var_dict[ioda_var]['valKey']] = (
                 mask_nans(obs_df[f'ObsValue {obs_var}'].values * conv_fact))
@@ -206,9 +200,7 @@ def _read(self):
             self.data[self.var_dict[ioda_var]['qcKey']] = (
                 mask_nans(obs_df[f'PreQC {obs_var}'].values * conv_fact))
 
-        nlocs = len(self.data[('datetime', 'MetaData')])
-        dim_dict['nlocs'] = nlocs
-        attr_data['nlocs'] = np.int32(nlocs)
+        dim_dict['Location'] = len(self.data[('dateTime', 'MetaData')])
 
     def write(self):
         writer = iconv.IodaWriter(self.file_out, location_key_list, dim_dict)
diff --git a/src/land/smap9km_ssm2ioda.py b/src/land/smap9km_ssm2ioda.py
index b5ccbd0d2..35937fba5 100644
--- a/src/land/smap9km_ssm2ioda.py
+++ b/src/land/smap9km_ssm2ioda.py
@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 #
-# (C) Copyright 2022 EMC/NCEP/NWS/NOAA
+# (C) Copyright 2020-2022 EMC/NCEP/NWS/NOAA
 #
 # This software is licensed under the terms of the Apache Licence Version 2.0
 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
@@ -22,11 +22,13 @@
 from collections import defaultdict, OrderedDict
 from orddicts import DefaultOrderedDict
 
+os.environ["TZ"] = "UTC"
+
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
     ("depthBelowSoilSurface", "float"),
-    ("datetime", "string")
+    ("dateTime", "long")
 ]
 
 obsvars = {
@@ -34,16 +36,19 @@
 }
 
 AttrData = {
-    'converter': os.path.basename(__file__),
 }
 
 DimDict = {
 }
 
 VarDims = {
-    'soilMoistureVolumetric': ['nlocs'],
+    'soilMoistureVolumetric': ['Location'],
 }
 
+# Usual reference time for these data is 12UTC 1Jan2000
+iso8601_string = 'seconds since 2000-01-01T12:00:00Z'
+epoch = datetime.fromisoformat(iso8601_string[14:-1])
+
 
 class smap(object):
     def __init__(self, args):
@@ -67,20 +72,18 @@ def _read(self):
             self.varAttrs[iodavar, iconv.OqcName()]['coordinates'] = 'longitude latitude'
             self.varAttrs[iodavar, iconv.OvalName()]['units'] = 'm3 m-3'
             self.varAttrs[iodavar, iconv.OerrName()]['units'] = 'm3 m-3'
-            self.varAttrs[iodavar, iconv.OqcName()]['units'] = 'unitless'
 
         # open input file name
         ncd = nc.Dataset(self.filename, 'r')
         # set and get global attributes
-        self.satellite = "SMAP"
-        self.sensor = "radar and radiometer"
-        AttrData["satellite"] = self.satellite
-        AttrData["sensor"] = self.sensor
+        self.satellite = 789
+        self.sensor = 432
+        AttrData["platform"] = np.array([self.satellite], dtype=np.int32)
+        AttrData["sensor"] = np.array([self.sensor], dtype=np.int32)
 
         data = ncd.groups['Soil_Moisture_Retrieval_Data'].variables['soil_moisture'][:]
         vals = data[:].ravel()
         _FillValue = ncd.groups['Soil_Moisture_Retrieval_Data'].variables['soil_moisture'].getncattr('_FillValue')
-        self.varAttrs['soilMoistureVolumetric', iconv.OvalName()]['_FillValue'] = _FillValue
         valid_max = ncd.groups['Soil_Moisture_Retrieval_Data'].variables['soil_moisture'].getncattr('valid_max')
         valid_min = ncd.groups['Soil_Moisture_Retrieval_Data'].variables['soil_moisture'].getncattr('valid_min')
 
@@ -95,7 +98,7 @@ def _read(self):
         refsec = ncd.groups['Soil_Moisture_Retrieval_Data'].variables['tb_time_seconds'][:].ravel()
 
         deps = np.full_like(vals, self.assumedSoilDepth)
-        times = np.empty_like(vals, dtype=object)
+        times = np.empty_like(vals, dtype=np.int64)
 
         if self.mask:
             with np.errstate(invalid='ignore'):
@@ -113,8 +116,6 @@ def _read(self):
             refsec = refsec[mask]
             times = times[mask]
 
-        # get datetime and reference time 12UTC 1Jan2000
-        base_date = datetime(2000, 1, 1, 12, 0)
         vals = vals.astype('float32')
         lats = lats.astype('float32')
         lons = lons.astype('float32')
@@ -127,34 +128,28 @@ def _read(self):
         ecoli = ecoli.astype('int32')
 
         for i in range(len(lons)):
-            dt = base_date + timedelta(seconds=int(refsec[i]))
-            times[i] = dt.strftime("%Y-%m-%dT%H:%M:%SZ")
+            times[i] = int(refsec[i])
             errs[i] = 0.04
         # add metadata variables
-        self.outdata[('datetime', 'MetaData')] = times
+        self.outdata[('dateTime', 'MetaData')] = times
+        self.varAttrs[('dateTime', 'MetaData')]['units'] = iso8601_string
         self.outdata[('latitude', 'MetaData')] = lats
         self.outdata[('longitude', 'MetaData')] = lons
         self.varAttrs[('latitude', 'MetaData')]['units'] = 'degree_north'
         self.varAttrs[('longitude', 'MetaData')]['units'] = 'degree_east'
         self.outdata[('depthBelowSoilSurface', 'MetaData')] = deps
         self.varAttrs[('depthBelowSoilSurface', 'MetaData')]['units'] = 'm'
-        self.outdata[('surfaceFlag', 'MetaData')] = sflg
-        self.varAttrs[('surfaceFlag', 'MetaData')]['units'] = 'unitless'
+        self.outdata[('surfaceQualifier', 'MetaData')] = sflg
         self.outdata[('vegetationOpacity', 'MetaData')] = vegop
-        self.varAttrs[('vegetationOpacity', 'MetaData')]['units'] = 'unitless'
         self.outdata[('easeRowIndex', 'MetaData')] = erowi
-        self.varAttrs[('easeRowIndex', 'MetaData')]['units'] = '1'
         self.outdata[('easeColumnIndex', 'MetaData')] = ecoli
-        self.varAttrs[('easeColumnIndex', 'MetaData')]['units'] = '1'
 
         for iodavar in ['soilMoistureVolumetric']:
             self.outdata[self.varDict[iodavar]['valKey']] = vals
             self.outdata[self.varDict[iodavar]['errKey']] = errs
             self.outdata[self.varDict[iodavar]['qcKey']] = qflg
 
-        AttrData['date_time_string'] = times[0]
-        DimDict['nlocs'] = len(self.outdata[('datetime', 'MetaData')])
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+        DimDict['Location'] = len(self.outdata[('dateTime', 'MetaData')])
 
 
 def main():
diff --git a/src/land/smap_ssm2ioda.py b/src/land/smap_ssm2ioda.py
index 8e6a81bec..d8d6447ae 100644
--- a/src/land/smap_ssm2ioda.py
+++ b/src/land/smap_ssm2ioda.py
@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 #
-# (C) Copyright 2021 EMC/NCEP/NWS/NOAA
+# (C) Copyright 2021-2022 EMC/NCEP/NWS/NOAA
 #
 # This software is licensed under the terms of the Apache Licence Version 2.0
 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
@@ -22,11 +22,13 @@
 from collections import defaultdict, OrderedDict
 from orddicts import DefaultOrderedDict
 
+os.environ["TZ"] = "UTC"
+
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
     ("depthBelowSoilSurface", "float"),
-    ("datetime", "string")
+    ("dateTime", "long")
 ]
 
 obsvars = {
@@ -34,16 +36,18 @@
 }
 
 AttrData = {
-    'converter': os.path.basename(__file__),
 }
 
 DimDict = {
 }
 
 VarDims = {
-    'soilMoistureVolumetric': ['nlocs'],
+    'soilMoistureVolumetric': ['Location'],
 }
 
+iso8601_string = 'seconds since 1970-01-01T00:00:00Z'
+epoch = datetime.fromisoformat(iso8601_string[14:-1])
+
 
 class smap(object):
     def __init__(self, args):
@@ -67,15 +71,14 @@ def _read(self):
             self.varAttrs[iodavar, iconv.OqcName()]['coordinates'] = 'longitude latitude'
             self.varAttrs[iodavar, iconv.OvalName()]['units'] = 'm3 m-3'
             self.varAttrs[iodavar, iconv.OerrName()]['units'] = 'm3 m-3'
-            self.varAttrs[iodavar, iconv.OqcName()]['units'] = 'unitless'
 
         # open input file name
         ncd = nc.Dataset(self.filename, 'r')
         # set and get global attributes
-        self.satellite = "SMAP"
-        self.sensor = "radar and radiometer"
-        AttrData["satellite"] = self.satellite
-        AttrData["sensor"] = self.sensor
+        satelliteID = 789
+        sensorID = 432
+        AttrData["platform"] = np.array([satelliteID], dtype=np.int32)
+        AttrData["sensor"] = np.array([sensorID], dtype=np.int32)
 
         data = ncd.groups['Soil_Moisture_Retrieval_Data'].variables['soil_moisture'][:]
         vals = data[:].ravel()
@@ -89,7 +92,7 @@ def _read(self):
         qflg = ncd.groups['Soil_Moisture_Retrieval_Data'].variables['retrieval_qual_flag'][:].ravel()
 
         deps = np.full_like(vals, self.assumedSoilDepth)
-        times = np.empty_like(vals, dtype=object)
+        times = np.empty_like(vals, dtype=np.int64)
 
         if self.mask:
             with np.errstate(invalid='ignore'):
@@ -106,14 +109,13 @@ def _read(self):
         str_split = self.filename.split("_")
         str_datetime = str_split[7]
         my_datetime = datetime.strptime(str_datetime, "%Y%m%dT%H%M%S")
-        base_datetime = my_datetime.strftime('%Y-%m-%dT%H:%M:%SZ')
+        time_offset = round((my_datetime - epoch).total_seconds())
         vals = vals.astype('float32')
         lats = lats.astype('float32')
         lons = lons.astype('float32')
         deps = deps.astype('float32')
         errs = errs.astype('float32')
         qflg = qflg.astype('int32')
-        AttrData['date_time_string'] = base_datetime
 
         for i in range(len(lons)):
 
@@ -127,10 +129,11 @@ def _read(self):
             else:
                 qflg[i] = 1
 
-            times[i] = base_datetime
+            times[i] = time_offset
 
         # add metadata variables
-        self.outdata[('datetime', 'MetaData')] = times
+        self.outdata[('dateTime', 'MetaData')] = times
+        self.varAttrs[('dateTime', 'MetaData')]['units'] = iso8601_string
         self.outdata[('latitude', 'MetaData')] = lats
         self.outdata[('longitude', 'MetaData')] = lons
         self.outdata[('depthBelowSoilSurface', 'MetaData')] = deps
@@ -141,8 +144,7 @@ def _read(self):
             self.outdata[self.varDict[iodavar]['errKey']] = errs
             self.outdata[self.varDict[iodavar]['qcKey']] = qflg
 
-        DimDict['nlocs'] = len(self.outdata[('datetime', 'MetaData')])
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+        DimDict['Location'] = len(self.outdata[('dateTime', 'MetaData')])
 
 
 def main():
diff --git a/src/land/smos_ssm2ioda.py b/src/land/smos_ssm2ioda.py
index c59645334..0dd501d7f 100644
--- a/src/land/smos_ssm2ioda.py
+++ b/src/land/smos_ssm2ioda.py
@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 #
-# (C) Copyright 2021 NOAA/NWS/NCEP/EMC
+# (C) Copyright 2020-2022 NOAA/NWS/NCEP/EMC
 #
 # This software is licensed under the terms of the Apache Licence Version 2.0
 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
@@ -24,7 +24,7 @@
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string")
+    ("dateTime", "string")
 ]
 
 obsvars = {
@@ -32,14 +32,13 @@
 }
 
 AttrData = {
-    'converter': os.path.basename(__file__),
 }
 
 DimDict = {
 }
 
 VarDims = {
-    'soilMoistureVolumetric': ['nlocs'],
+    'soilMoistureVolumetric': ['Location'],
 }
 
 
@@ -65,14 +64,14 @@ def _read(self):
             self.varAttrs[iodavar, iconv.OqcName()]['coordinates'] = 'longitude latitude'
             self.varAttrs[iodavar, iconv.OvalName()]['units'] = 'm3 m-3'
             self.varAttrs[iodavar, iconv.OerrName()]['units'] = 'm3 m-3'
-            self.varAttrs[iodavar, iconv.OqcName()]['units'] = 'unitless'
 
         # open input file name
         ncd = nc.Dataset(self.filename, 'r')
         # set and get global attributes
-        AttrData["observation_type"] = "surface soil moisture"
-        AttrData["satellite"] = "SMOS"
-        AttrData["sensor"] = "MIRAS"
+        satelliteID = 46
+        sensorID = 176
+        AttrData["platform"] = np.array([satelliteID], dtype=np.int32)
+        AttrData["sensor"] = np.array([sensorID], dtype=np.int32)
 
         lons = ncd.variables['longitude'][:]
         lats = ncd.variables['latitude'][:]
@@ -112,11 +111,10 @@ def _read(self):
             base_date = datetime(2000, 1, 1) + timedelta(days=int(ddys[i]))
             dt = base_date + timedelta(seconds=int(secs[i]))
             base_datetime = dt.strftime("%Y-%m-%dT%H:%M:%SZ")
-            AttrData['date_time_string'] = base_datetime
             times[i] = base_datetime
 
         # add metadata variables
-        self.outdata[('datetime', 'MetaData')] = times
+        self.outdata[('dateTime', 'MetaData')] = times
         self.outdata[('latitude', 'MetaData')] = lats
         self.outdata[('longitude', 'MetaData')] = lons
 
@@ -125,8 +123,7 @@ def _read(self):
             self.outdata[self.varDict[iodavar]['errKey']] = errs
             self.outdata[self.varDict[iodavar]['qcKey']] = qflg
 
-        DimDict['nlocs'] = len(self.outdata[('datetime', 'MetaData')])
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+        DimDict['Location'] = len(self.outdata[('dateTime', 'MetaData')])
 
 
 def main():
diff --git a/src/lib-python/ioda_conv_engines.py b/src/lib-python/ioda_conv_engines.py
index ad7fb57b2..7b357871b 100644
--- a/src/lib-python/ioda_conv_engines.py
+++ b/src/lib-python/ioda_conv_engines.py
@@ -1,4 +1,5 @@
 #!/usr/bin/env python
+import datetime as dt
 import ioda_obs_space as ioda_os
 import numpy as np
 from collections import OrderedDict
@@ -38,7 +39,7 @@ def OqcName():
     return _oqc_name
 
 
-def get_default_fill_val(mydtype):
+def get_default_fill_val(mydtype, isDateTime=False):
     dtype_tmp = np.array([], dtype=mydtype)
     NumpyDtype = dtype_tmp.dtype
     if (NumpyDtype == np.dtype('float64')):
@@ -58,7 +59,10 @@ def get_default_fill_val(mydtype):
     elif (NumpyDtype == np.dtype('U1')):
         fillval = '\x00'
     elif (NumpyDtype == np.dtype('object')):
-        fillval = '\x00'
+        if (isDateTime):
+            fillval = dt.datetime(2200, 1, 1, tzinfo=dt.timezone.utc)
+        else:
+            fillval = '\x00'
     else:
         print("ERROR: Unrecognized data type", NumpyDtype)
         exit(-2)
@@ -76,6 +80,7 @@ def get_default_fill_val(mydtype):
 class IodaWriter(object):
     # Constructor
     def __init__(self, Fname, LocKeyList, DimDict, TestKeyList=None):
+        # note: loc_key_list does nothing
         self._loc_key_list = LocKeyList
         self._dim_dict = DimDict
         self._test_key_list = TestKeyList
@@ -91,8 +96,8 @@ def WriteGeoVars(self, GeoVars, GeoVarDims, GeoVarAttrs):
                 dims = GeoVarDims[VarName]
             else:
                 # assume it is just nlocs
-                dims = ['nlocs']
-            fillval = get_default_fill_val(Vvals.dtype)
+                dims = ['Location']
+            fillval = get_default_fill_val(Vvals.dtype, isinstance(Vvals[0], dt.datetime))
             # get fill value
             if VarName in GeoVarAttrs.keys():
                 if '_FillValue' in GeoVarAttrs[VarName].keys():
@@ -120,8 +125,8 @@ def WriteObsVars(self, ObsVars, VarDims, VarAttrs):
                 dims = VarDims[Vname]
             else:
                 # assume it is just nlocs
-                dims = ['nlocs']
-            fillval = get_default_fill_val(Vvals.dtype)
+                dims = ['Location']
+            fillval = get_default_fill_val(Vvals.dtype, isinstance(Vvals[0], dt.datetime))
             # get fill value
             if VarKey in VarAttrs.keys():
                 if '_FillValue' in VarAttrs[VarKey].keys():
@@ -148,6 +153,25 @@ def WriteObsVars(self, ObsVars, VarDims, VarAttrs):
             except KeyError:
                 pass  # no metadata for this variable
 
+    def VerifyDateTime(self, ObsVars):
+        # this method will check if the variable
+        # MetaData/dateTime is a string or datetime object
+        # if string, convert to datetime object
+        VarKey = ('dateTime', 'MetaData')
+        if VarKey not in ObsVars.keys():
+            raise KeyError("Required variable 'MetaData/dateTime' does not exist.")
+        dtvar = ObsVars[VarKey]
+        # check if the array is type 'object' or not
+        # otherwise we will assume it is an integer and already set up
+        if (dtvar.dtype == np.dtype('object')):
+            # object is used for strings or datetime objects
+            if (isinstance(dtvar[0], str)):
+                # convert ISO date strings to datetime objects
+                newdtvar = [dt.datetime.strptime(x, "%Y-%m-%dT%H:%M:%SZ") for x in dtvar]
+                ObsVars[VarKey] = np.array(newdtvar, dtype=object)
+
+        return ObsVars
+
     def WriteGlobalAttrs(self, GlobalAttrs):
         # this method will create global attributes from GlobalAttrs dictionary
         for AttrKey, AttrVal in GlobalAttrs.items():
@@ -155,6 +179,8 @@ def WriteGlobalAttrs(self, GlobalAttrs):
 
     def BuildIoda(self, ObsVars, VarDims, VarAttrs, GlobalAttrs,
                   TestData=None, geovals=False):
+        # check and fix dateTime if necessary
+        ObsVars = self.VerifyDateTime(ObsVars)
         if geovals:
             self.WriteGeoVars(ObsVars, VarDims, VarAttrs)
         else:
@@ -176,6 +202,7 @@ def ExtractObsData(ObsData, loc_key_list):
     # can be preallocated, and variable numbers can be assigned
     ObsVarList = []
     ObsVarExamples = []
+    ObsVarTypes = []
     for LocKey, LocDict in ObsData.items():
         _nlocs += 1
         for VarKey, VarVal in LocDict.items():
@@ -184,6 +211,7 @@ def ExtractObsData(ObsData, loc_key_list):
             if (VarKey not in ObsVarList):
                 ObsVarList.append(VarKey)
                 ObsVarExamples.append(VarVal)
+                ObsVarTypes.append(type(VarVal))
         # Extract the locations metadata encoded in the keys
         for i in range(len(loc_key_list)):
             (LocVname, LocVtype) = loc_key_list[i]
@@ -191,18 +219,23 @@ def ExtractObsData(ObsData, loc_key_list):
             if (locvar not in ObsVarList):
                 ObsVarList.append(locvar)
                 ObsVarExamples.append(LocKey[i])
+                if (LocVtype == "long"):
+                    # For case where MetaData/dateTime is directly assigned 64-bit integers
+                    ObsVarTypes.append(np.int64)
+                else:
+                    ObsVarTypes.append(type(LocKey[i]))
 
     # Preallocate arrays and fill them up with data from the dictionary
     ObsVars = OrderedDict()
     for o in range(len(ObsVarList)):
-        VarType = type(ObsVarExamples[o])
+        VarType = ObsVarTypes[o]
         if (VarType in [float, np.float32, np.float64]):
             defaultval = get_default_fill_val(np.float32)
             defaultvaltype = np.float32
-        elif ((VarType in [np.int64]) and (o == ('dateTime', 'MetaData'))):
+        elif (VarType in [np.int64]):
             defaultval = get_default_fill_val(np.int64)
             defaultvaltype = np.int64
-        elif (VarType in [int, np.int64, np.int32, np.int8]):
+        elif (VarType in [int, np.int32, np.int8]):
             defaultval = get_default_fill_val(np.int32)
             defaultvaltype = np.int32
         elif (VarType in [str, np.str_]):
diff --git a/src/lib-python/meteo_sounding_utils.py b/src/lib-python/meteo_sounding_utils.py
index e2f0879bb..73c161421 100644
--- a/src/lib-python/meteo_sounding_utils.py
+++ b/src/lib-python/meteo_sounding_utils.py
@@ -66,11 +66,6 @@ def zext_up(pres_lower, pres_upper, temperature, hght_lower):
     :param hght_lower: Height of lower layer (m)
     :return: Extrapolated height (m)
     """
-    if pres_upper is None or pres_lower is None:
-        return None
-    if pres_upper <= 0 or pres_lower <= 0 or temperature is None or hght_lower is None:
-        return None
-
     return hght_lower + (Rd * (temperature + CTOK) / G) * math.log(pres_lower / pres_upper)
 
 # --+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+
@@ -86,11 +81,6 @@ def zext_down(pres_lower, pres_upper, temperature, hght_upper):
     :param hght_upper: Height of upper layer (m)
     :return: Extrapolated height (m)
     """
-    if pres_upper is None or pres_lower is None:
-        return None
-    if pres_upper <= 0 or pres_lower <= 0 or temperature is None or hght_upper is None:
-        return None
-
     return hght_upper - (Rd * (temperature + CTOK) / G) * math.log(pres_lower / pres_upper)
 
 # --+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+---+
diff --git a/src/marine/amsr2_icec2ioda.py b/src/marine/amsr2_icec2ioda.py
index ee1494f10..44b2cfd76 100755
--- a/src/marine/amsr2_icec2ioda.py
+++ b/src/marine/amsr2_icec2ioda.py
@@ -7,7 +7,7 @@
 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
 #
 
-import sys
+import os, sys
 import argparse
 import numpy as np
 from datetime import datetime, timedelta
@@ -22,17 +22,24 @@
 import ioda_conv_engines as iconv
 from orddicts import DefaultOrderedDict
 
+os.environ["TZ"] = "UTC"
 
-vName = "sea_ice_area_fraction"
+vName = "seaIceFraction"
 
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string")
+    ("dateTime", "long")
 ]
 
+icec_FillValue = None
+icec_units = ''
+
 GlobalAttrs = {}
 
+iso8601_string = 'seconds since 1970-01-01T00:00:00Z'
+epoch = datetime.fromisoformat(iso8601_string[14:-1])
+
 
 class iceconc(object):
     def __init__(self, filenames, date):
@@ -48,6 +55,9 @@ def _read(self):
         errKey = vName, iconv.OerrName()
         qcKey = vName, iconv.OqcName()
 
+        global icec_FillValue
+        global icec_units
+
         for f in self.filenames:
             print(" Reading file: ", f)
             ncd = nc.Dataset(f, 'r')
@@ -62,7 +72,8 @@ def _read(self):
             lat = ncd.variables['Latitude'][:]
             icec = ncd.variables['NASA_Team_2_Ice_Concentration'][:]
             icec_FillValue = ncd.variables['NASA_Team_2_Ice_Concentration']._FillValue
-            icec_units = ncd.variables['NASA_Team_2_Ice_Concentration'].units
+            icec_units = str(ncd.variables['NASA_Team_2_Ice_Concentration'].units)
+            print(f" units: {icec_units}")
             icec_qc = ncd.variables['Flags'][:]
             qc_FillValue = ncd.variables['Flags']._FillValue
             qc_units = ncd.variables['Flags'].units
@@ -71,7 +82,7 @@ def _read(self):
             lon = lon[mask]
             lat = lat[mask]
             icec = icec[mask]
-            icec_qc = icec_qc[mask]
+            icec_qc = icec_qc[mask].astype(np.int32)
 
             for i in range(len(lon)):
                 # get date from filename
@@ -80,16 +91,11 @@ def _read(self):
                 date1 = datetime.strptime(datestart, "%Y-%m-%dT%H:%M:%S.%fZ")
                 date2 = datetime.strptime(dateend, "%Y-%m-%dT%H:%M:%S.%fZ")
                 avg = date1 + (date2 - date1) * 0.5
-                locKey = lat[i], lon[i], avg.strftime("%Y-%m-%dT%H:%M:%SZ")
+                time_offset = round((avg - epoch).total_seconds())
+                locKey = lat[i], lon[i], time_offset
                 self.data[locKey][valKey] = icec[i] * 0.01
-                self.VarAttrs[locKey][valKey]['_FillValue'] = icec_FillValue
-                self.VarAttrs[locKey][valKey]['units'] = icec_units
                 self.data[locKey][errKey] = 0.1
-                self.VarAttrs[locKey][errKey]['_FillValue'] = icec_FillValue
-                self.VarAttrs[locKey][errKey]['units'] = icec_units
                 self.data[locKey][qcKey] = icec_qc[i]
-                self.VarAttrs[locKey][qcKey]['_FillValue'] = qc_FillValue
-                self.VarAttrs[locKey][qcKey]['units'] = qc_units
             ncd.close()
 
 
@@ -117,7 +123,7 @@ def main():
     fdate = datetime.strptime(args.date, '%Y%m%d%H')
 #
     VarDims = {
-        'sea_ice_area_fraction': ['nlocs'],
+        vName: ['Location'],
     }
 
     # Read in the Ice concentration
@@ -126,9 +132,14 @@ def main():
     # write them out
     ObsVars, nlocs = iconv.ExtractObsData(icec.data, locationKeyList)
 
-    DimDict = {'nlocs': nlocs}
+    DimDict = {'Location': nlocs}
     writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
 
+    icec.VarAttrs[('dateTime', 'MetaData')]['units'] = iso8601_string
+    icec.VarAttrs[(vName, 'ObsValue')]['units'] = icec_units
+    icec.VarAttrs[(vName, 'ObsValue')]['_FillValue'] = icec_FillValue
+    icec.VarAttrs[(vName, 'ObsError')]['units'] = icec_units
+    icec.VarAttrs[(vName, 'ObsError')]['_FillValue'] = icec_FillValue
     writer.BuildIoda(ObsVars, VarDims, icec.VarAttrs, GlobalAttrs)
 
 
diff --git a/src/marine/argoClim2ioda.py b/src/marine/argoClim2ioda.py
index 14ca29e34..5731cdf8b 100755
--- a/src/marine/argoClim2ioda.py
+++ b/src/marine/argoClim2ioda.py
@@ -67,9 +67,12 @@ def _readData(self):
         assert self.varname in ['TEMPERATURE', 'SALINITY'],\
             "%s is not a valid variable name" % self.varname
 
+        self.varname2 = 'waterTemperature'
+
         lon = nc.variables['LONGITUDE'][:]
         lat = nc.variables['LATITUDE'][:]
-        pres = nc.variables['PRESSURE'][:]
+        pres = nc.variables['PRESSURE'][:]  # pressure in decibar
+        depth = pres   # 1 decibar = 1 meter, so you can use pressure as depth
 
         # Get absolute time instead of time since epoch
         dtime = nc.variables['TIME']
@@ -100,9 +103,10 @@ def _readData(self):
             time = timeArray[bI:eI]
 
         mean = nc.variables['ARGO_%s_MEAN' % self.varname][:]
+        meanK = [x+273.15 for x in mean]
 
         # create a full field from mean and anomaly
-        fullField = anomaly + np.tile(mean, (anomaly.shape[0], 1, 1, 1))
+        fullField = anomaly + np.tile(meanK, (anomaly.shape[0], 1, 1, 1))
 
         try:
             nc.close()
@@ -115,7 +119,7 @@ def _readData(self):
         self.data = {}
         self.data['lat'] = lat
         self.data['lon'] = lon
-        self.data['pres'] = pres
+        self.data['depth'] = depth
         self.data['time'] = time
         self.data['field'] = fullField.data
 
@@ -137,8 +141,8 @@ def __init__(self, filename, date, argo):
         self.locKeyList = [
             ("latitude", "float"),
             ("longitude", "float"),
-            ("pressure", "float"),
-            ("datetime", "string")
+            ("depthBelowWaterSurface", "float"),
+            ("dateTime", "string")
         ]
 
         self.GlobalAttrs = {
@@ -149,17 +153,17 @@ def __init__(self, filename, date, argo):
         self.data = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
         self.varAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
 
-        valKey = argo.varname, iconv.OvalName()
-        errKey = argo.varname, iconv.OerrName()
-        qcKey = argo.varname, iconv.OqcName()
+        valKey = argo.varname2, iconv.OvalName()
+        errKey = argo.varname2, iconv.OerrName()
+        qcKey = argo.varname2, iconv.OqcName()
 
         # There has to be a better way than explicitly looping over 4! dimensions
         for t, time in enumerate(argo.data['time']):
             for y, lat in enumerate(argo.data['lat']):
                 for x, lon in enumerate(argo.data['lon']):
-                    for z, pres in enumerate(argo.data['pres']):
+                    for z, depth in enumerate(argo.data['depth']):
 
-                        locKey = lat, lon, pres, time.strftime('%Y-%m-%dT%H:%M:%SZ')
+                        locKey = lat, lon, depth, time.strftime('%Y-%m-%dT%H:%M:%SZ')
 
                         val = argo.data['field'][t, z, y, x]
                         err = 0.
@@ -169,21 +173,22 @@ def __init__(self, filename, date, argo):
                         self.data[locKey][errKey] = err
                         self.data[locKey][qcKey] = qc
 
-        self.varAttrs[argo.varname, iconv.OvalName()]['_FillValue'] = -999.
-        self.varAttrs[argo.varname, iconv.OerrName()]['_FillValue'] = -999.
-        self.varAttrs[argo.varname, iconv.OqcName()]['_FillValue'] = -999
-        self.varAttrs[argo.varname, iconv.OvalName()]['units'] = 'degree_C'
-        self.varAttrs[argo.varname, iconv.OerrName()]['units'] = 'degree_C'
-        self.varAttrs[argo.varname, iconv.OqcName()]['units'] = 'unitless'
+        self.varAttrs[argo.varname2, iconv.OvalName()]['_FillValue'] = -999.
+        self.varAttrs[argo.varname2, iconv.OerrName()]['_FillValue'] = -999.
+        self.varAttrs[argo.varname2, iconv.OqcName()]['_FillValue'] = -999
+        self.varAttrs[argo.varname2, iconv.OvalName()]['units'] = 'K'
+        self.varAttrs[argo.varname2, iconv.OerrName()]['units'] = 'K'
+        self.varAttrs['depthBelowWaterSurface', 'MetaData']['units'] = 'm'
 
         # Extract obs
-        ObsVars, nlocs = iconv.ExtractObsData(self.data, self.locKeyList)
-        DimDict = {'nlocs': nlocs}
+        ObsVars, Location = iconv.ExtractObsData(self.data, self.locKeyList)
+        DimDict = {'Location': Location}
         varDims = {
-            'TEMPERATURE': ['nlocs']
+            'waterTemperature': ['Location']
         }
         # Set up IODA writer
         self.writer = iconv.IodaWriter(self.filename, self.locKeyList, DimDict)
+
         # Write out observations
         self.writer.BuildIoda(ObsVars, varDims, self.varAttrs, self.GlobalAttrs)
 
@@ -227,7 +232,7 @@ def main():
     }
 
     varDims = {
-        'TEMPERATURE': ['nlocs']
+        'waterTemperature': ['Location']
     }
 
     IODA(foutput, fdate, argo)
diff --git a/src/marine/avhrr_radiance2ioda.py b/src/marine/avhrr_radiance2ioda.py
index a1f41f56c..a3ba60183 100755
--- a/src/marine/avhrr_radiance2ioda.py
+++ b/src/marine/avhrr_radiance2ioda.py
@@ -25,12 +25,12 @@
 import ioda_conv_engines as iconv
 from orddicts import DefaultOrderedDict
 
-output_var_names = ["brightness_temperature"]
+output_var_names = ["brightnessTemperature"]
 
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string")
+    ("dateTime", "long")
 ]
 
 GlobalAttrs = {}
@@ -43,6 +43,8 @@
 
 chan_number = {3, 4, 5}
 
+time_units = ''     # Will fill in below.
+
 
 def read_input(input_args):
     """
@@ -64,9 +66,14 @@ def read_input(input_args):
     print("Reading ", input_file)
     ncd = nc.Dataset(input_file, 'r')
 
+    global time_units
     # get the base time (should only have 1 or 2 time slots)
     time_base = ncd.variables['time'][:]
-    basetime = dateutil.parser.parse(ncd.variables['time'].units[-20:])
+    time_units = ncd.variables['time'].units[-19:] + 'Z'
+    s = list(time_units)
+    s[10] = "T"
+    time_units = 'seconds since ' + "".join(s)
+    basetime = dateutil.parser.parse(ncd.variables['time'].units[-19:])
 
     # get some of the global attributes that we are interested in
 
@@ -138,9 +145,8 @@ def read_input(input_args):
     # create a string version of the date for each observation
     dates = []
     for i in range(len(lons)):
-        obs_date = basetime + \
-            timedelta(seconds=float(time[i]+3600*data_in['scan_line_time'][i]))  # check later
-        dates.append(obs_date.strftime("%Y-%m-%dT%H:%M:%SZ"))
+        dates.append(round(3600*data_in['scan_line_time'][i]))
+    dates = np.array(dates, dtype=np.int64)
 
     # output values
     nchans = len(chan_number)
@@ -162,19 +168,18 @@ def read_input(input_args):
     # allocate space for output depending on which variables are to be saved
 
     obs_data = {}
-    obs_data[('datetime', 'MetaData')] = np.empty(len(dates), dtype=object)
-    obs_data[('datetime', 'MetaData')][:] = dates
+    obs_data[('dateTime', 'MetaData')] = dates.astype(np.int64)
     obs_data[('latitude', 'MetaData')] = lats
     obs_data[('longitude', 'MetaData')] = lons
-    obs_data[('record_number', 'MetaData')] = data_in['scan_line_number']
-    obs_data[('height_above_mean_sea_level', 'MetaData')] = 840*np.ones((obs_dim))
-    obs_data[('sensor_azimuth_angle', 'MetaData')] = data_in['sensor_azimuth_angle']
-    obs_data[('sensor_zenith_angle', 'MetaData')] = data_in['sensor_zenith_angle']
-    obs_data[('solar_zenith_angle', 'MetaData')] = data_in['solar_zenith_angle']
-    obs_data[('solar_azimuth_angle', 'MetaData')] = data_in['solar_azimuth_angle']
-    obs_data[('scan_position', 'MetaData')] = data_in['scan_line_number']
-    obs_data[output_var_names[0], global_config['oval_name']] = val_tb
-    obs_data[output_var_names[0], global_config['oerr_name']] = err
+    obs_data[('sequenceNumber', 'MetaData')] = data_in['scan_line_number']
+    obs_data[('height', 'MetaData')] = 840*np.ones((obs_dim)).astype('float32')
+    obs_data[('sensorAzimuthAngle', 'MetaData')] = data_in['sensor_azimuth_angle']
+    obs_data[('sensorZenithAngle', 'MetaData')] = data_in['sensor_zenith_angle']
+    obs_data[('solarZenithAngle', 'MetaData')] = data_in['solar_zenith_angle']
+    obs_data[('solarAzimuthAngle', 'MetaData')] = data_in['solar_azimuth_angle']
+    obs_data[('scanPosition', 'MetaData')] = data_in['scan_line_number']
+    obs_data[output_var_names[0], global_config['oval_name']] = val_tb.astype('float32')
+    obs_data[output_var_names[0], global_config['oerr_name']] = err.astype('float32')
     obs_data[output_var_names[0], global_config['opqc_name']] = qc.astype('int32')
 
     return (obs_data, GlobalAttrs)
@@ -248,7 +253,7 @@ def main():
 
     # prepare global attributes we want to output in the file,
     # in addition to the ones already loaded in from the input file
-    GlobalAttrs['date_time_string'] = args.date.strftime("%Y-%m-%dT%H:%M:%SZ")
+    GlobalAttrs['datetimeReference'] = args.date.strftime("%Y-%m-%dT%H:%M:%SZ")
     GlobalAttrs['thinning'] = args.thin
     GlobalAttrs['converter'] = os.path.basename(__file__)
 
@@ -259,24 +264,24 @@ def main():
     # pass parameters to the IODA writer
     # (needed because we are bypassing ExtractObsData within BuildNetcdf)
     VarDims = {
-        'brightness_temperature': ['nlocs', 'nchans']
+        'brightnessTemperature': ['Location', 'Channel']
     }
 
     nchans = len(chan_number)
     nlocs = len(obs_data[('longitude', 'MetaData')])
     DimDict = {
-        'nlocs': nlocs,
-        'nchans': list(chan_number)
+        'Location': nlocs,
+        'Channel': list(chan_number)
     }
 
     writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
 
-    VarAttrs[('brightness_temperature', 'ObsValue')]['units'] = 'Kelvin'
-    VarAttrs[('brightness_temperature', 'ObsError')]['units'] = 'Kelvin'
-    VarAttrs[('brightness_temperature', 'PreQC')]['units'] = 'unitless'
-    VarAttrs[('brightness_temperature', 'ObsValue')]['_FillValue'] = 999
-    VarAttrs[('brightness_temperature', 'ObsError')]['_FillValue'] = 999
-    VarAttrs[('brightness_temperature', 'PreQC')]['_FillValue'] = 999
+    VarAttrs[('dateTime', 'MetaData')]['units'] = time_units
+    VarAttrs[('brightnessTemperature', 'ObsValue')]['units'] = 'K'
+    VarAttrs[('brightnessTemperature', 'ObsError')]['units'] = 'K'
+    VarAttrs[('brightnessTemperature', 'ObsValue')]['_FillValue'] = 999
+    VarAttrs[('brightnessTemperature', 'ObsError')]['_FillValue'] = 999
+    VarAttrs[('brightnessTemperature', 'PreQC')]['_FillValue'] = 999
 
     writer.BuildIoda(obs_data, VarDims, VarAttrs, GlobalAttrs)
 
diff --git a/src/marine/copernicus_l3swh2ioda.py b/src/marine/copernicus_l3swh2ioda.py
index 3e9732a4e..f35043ef6 100755
--- a/src/marine/copernicus_l3swh2ioda.py
+++ b/src/marine/copernicus_l3swh2ioda.py
@@ -28,23 +28,24 @@
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string"),
+    ("dateTime", "long"),
 ]
 
+time_units = 'seconds since 2000-01-01T00:00:00Z'
+
 obsvars = {
     'swh': 'swh',
 }
 
 AttrData = {
     'converter': os.path.basename(__file__),
-    'nvars': np.int32(len(obsvars)),
 }
 
 DimDict = {
 }
 
 VarDims = {
-    'swh': ['nlocs'],
+    'swh': ['Location'],
 }
 
 
@@ -62,9 +63,9 @@ def __init__(self, filename, factor):
         ncd.close()
 
         # set time stamp for all obs
-        self.datetime = np.empty_like(self.swh, dtype=object)
+        self.datetime = np.empty_like(self.swh, dtype=np.int64)
         for t in range(len(self.datetime)):
-            self.datetime[t] = datetime.utcfromtimestamp(self.time[t]+datetime(2000, 1, 1, 0, tzinfo=pytz.UTC).timestamp()).strftime("%Y-%m-%dT%H:%M:%SZ")
+            self.datetime[t] = self.time[t]
 
         # Remove observations out of sane bounds
         qci = np.where(self.swh > 0.0)
@@ -89,7 +90,7 @@ def __init__(self, filename, factor):
     # Open input file and read relevant info
     def _read(self):
         # set up variable names for IODA
-        iodavar = 'sea_surface_wave_significant_height'
+        iodavar = 'waveHeightSignificant'
         self.varDict[iodavar]['valKey'] = iodavar, iconv.OvalName()
         self.varDict[iodavar]['errKey'] = iodavar, iconv.OerrName()
         self.varDict[iodavar]['qcKey'] = iodavar, iconv.OqcName()
@@ -100,15 +101,15 @@ def _read(self):
         swh = copernicus(self.filename, self.factor)
 
         # map copernicus to ioda data structure
-        self.outdata[('datetime', 'MetaData')] = swh.datetime
+        self.outdata[('dateTime', 'MetaData')] = swh.datetime
+        self.var_mdata[('dateTime', 'MetaData')]['units'] = time_units
         self.outdata[('latitude', 'MetaData')] = swh.lats
         self.outdata[('longitude', 'MetaData')] = swh.lons
         self.outdata[self.varDict[iodavar]['valKey']] = swh.swh
         self.outdata[self.varDict[iodavar]['errKey']] = swh.err
         self.outdata[self.varDict[iodavar]['qcKey']] = np.zeros(swh.nlocs, dtype=np.int32)
 
-        DimDict['nlocs'] = swh.nlocs
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+        DimDict['Location'] = swh.nlocs
 
 
 def main():
diff --git a/src/marine/copernicus_l4adt2ioda.py b/src/marine/copernicus_l4adt2ioda.py
index 30d0cb7e7..709f3d89c 100755
--- a/src/marine/copernicus_l4adt2ioda.py
+++ b/src/marine/copernicus_l4adt2ioda.py
@@ -26,7 +26,7 @@
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string"),
+    ("dateTime", "long"),
 ]
 
 obsvars = {
@@ -35,16 +35,18 @@
 
 AttrData = {
     'converter': os.path.basename(__file__),
-    'nvars': np.int32(len(obsvars)),
 }
 
 DimDict = {
 }
 
 VarDims = {
-    'adt': ['nlocs'],
+    'adt': ['Location'],
 }
 
+iso8601_string = 'seconds since 1970-01-01T00:00:00Z'
+epoch = datetime.fromisoformat(iso8601_string[14:-1])
+
 
 class copernicus(object):
     def __init__(self, filename):
@@ -58,7 +60,7 @@ def __init__(self, filename):
         self.lats = self.lats.ravel()
         self.adt = np.squeeze(ncd.variables['adt'][:]).ravel()
         self.err = np.squeeze(ncd.variables['err_sla'][:]).ravel()
-        self.date = ncd.getncattr('time_coverage_start')
+        self.time_coverage_start = ncd.getncattr('time_coverage_start')
         ncd.close()
 
         # Remove observations out of sane bounds
@@ -68,9 +70,6 @@ def __init__(self, filename):
         self.lats = self.lats[qci]
         self.adt = self.adt[qci].astype(np.single)
         self.err = self.err[qci].astype(np.single)
-        # Same time stamp for all obs within 1 file
-        self.datetime = np.empty_like(self.adt, dtype=object)
-        self.datetime[:] = self.date
 
 
 class copernicus_l4adt2ioda(object):
@@ -87,7 +86,7 @@ def __init__(self, filename, datetime=None):
     # Open input file and read relevant info
     def _read(self):
         # set up variable names for IODA
-        iodavar = 'absolute_dynamic_topography'
+        iodavar = 'absoluteDynamicTopography'
         self.varDict[iodavar]['valKey'] = iodavar, iconv.OvalName()
         self.varDict[iodavar]['errKey'] = iodavar, iconv.OerrName()
         self.varDict[iodavar]['qcKey'] = iodavar, iconv.OqcName()
@@ -97,20 +96,33 @@ def _read(self):
         # read input filename
         adt = copernicus(self.filename)
         # put the time at 00 between start and end coverage time
-        if self.datetime is not None:
-            ymdh = datetime.strptime(self.datetime, "%Y%m%d")
-            ymdhm = ymdh.strftime("%Y-%m-%dT%H:%M:%SZ")
-            adt.datetime[:] = ymdhm
+        if adt.time_coverage_start is not None:
+            this_datetime = datetime.strptime(adt.time_coverage_start[:-1], "%Y-%m-%dT%H:%M:%S")
+            time_offset = round((this_datetime - epoch).total_seconds())
+        else:
+            try:
+                this_datetime = datetime.strptime(adt.datetime, "%Y-%m-%dT%H:%M:%SZ")
+                time_offset = round((this_datetime - epoch).total_seconds())
+            except Exception:
+                print(f"ABORT, failure to find timestamp; check format,"
+                      " it should be like 2014-07-29T12:00:00Z whereas"
+                      " you entered {self.datetime}")
+                sys.exit()
+
+        # Same time stamp for all obs within 1 file
+        adt.datetime = np.empty_like(adt.adt, dtype=np.int64)
+        adt.datetime[:] = time_offset
+
         # map copernicus to ioda data structure
-        self.outdata[('datetime', 'MetaData')] = adt.datetime
+        self.outdata[('dateTime', 'MetaData')] = adt.datetime
+        self.var_mdata[('dateTime', 'MetaData')]['units'] = iso8601_string
         self.outdata[('latitude', 'MetaData')] = adt.lats
         self.outdata[('longitude', 'MetaData')] = adt.lons
         self.outdata[self.varDict[iodavar]['valKey']] = adt.adt
         self.outdata[self.varDict[iodavar]['errKey']] = adt.err
         self.outdata[self.varDict[iodavar]['qcKey']] = np.zeros(adt.nlocs, dtype=np.int32)
 
-        DimDict['nlocs'] = adt.nlocs
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+        DimDict['Location'] = adt.nlocs
 
 
 def main():
diff --git a/src/marine/cryosat_ice2ioda.py b/src/marine/cryosat_ice2ioda.py
index 2fb41623e..b4c878a2c 100755
--- a/src/marine/cryosat_ice2ioda.py
+++ b/src/marine/cryosat_ice2ioda.py
@@ -76,12 +76,12 @@ def _read(self):
             os.remove("cryosat_nc4classic.nc")
 
 
-vName = "sea_ice_freeboard"
+vName = "seaIceFreeboard"
 
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string")
+    ("dateTime", "string")
 ]
 
 GlobalAttrs = {
@@ -98,7 +98,7 @@ def main():
     required = parser.add_argument_group(title='required arguments')
     required.add_argument(
         '-i', '--input',
-        help="Cryosat-2 ice freeboard obs input file(s)",
+        help="Cryosat-2 sea ice freeboard obs input file(s)",
         type=str, nargs='+', required=True)
     required.add_argument(
         '-o', '--output',
@@ -119,7 +119,7 @@ def main():
     args = parser.parse_args()
     fdate = datetime.strptime(args.date, '%Y%m%d%H')
     VarDims = {
-        vName: ['nlocs'],
+        vName: ['Location'],
     }
 
     # Read in
@@ -127,14 +127,13 @@ def main():
 
     # write them out
 
-    ObsVars, nlocs = iconv.ExtractObsData(ice.data, locationKeyList)
-    DimDict = {'nlocs': nlocs}
+    ObsVars, Location = iconv.ExtractObsData(ice.data, locationKeyList)
+    DimDict = {'Location': Location}
     writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
 
     VarAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
     VarAttrs[vName, iconv.OvalName()]['units'] = 'm'
     VarAttrs[vName, iconv.OerrName()]['units'] = 'm'
-    VarAttrs[vName, iconv.OqcName()]['units'] = 'unitless'
     VarAttrs[vName, iconv.OvalName()]['_FillValue'] = -32768
     VarAttrs[vName, iconv.OerrName()]['_FillValue'] = -999.
     VarAttrs[vName, iconv.OqcName()]['_FillValue'] = -2147483648
diff --git a/src/marine/emc_ice2ioda.py b/src/marine/emc_ice2ioda.py
index 717f22c07..4350f9de6 100755
--- a/src/marine/emc_ice2ioda.py
+++ b/src/marine/emc_ice2ioda.py
@@ -74,12 +74,12 @@ def _read(self, date):
                 self.data[locKey][qcKey] = qc[i]
 
 
-vName = "sea_ice_area_fraction"
+vName = "seaIceFraction"
 
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string")
+    ("dateTime", "string")
 ]
 
 GlobalAttrs = {
@@ -96,7 +96,7 @@ def main():
     required = parser.add_argument_group(title='required arguments')
     required.add_argument(
         '-i', '--input',
-        help="EMC ice fraction obs input file(s)",
+        help="EMC sea ice fraction obs input file(s)",
         type=str, nargs='+', required=True)
     required.add_argument(
         '-o', '--output',
@@ -117,20 +117,19 @@ def main():
     args = parser.parse_args()
     fdate = datetime.strptime(args.date, '%Y%m%d%H')
     VarDims = {
-        vName: ['nlocs'],
+        vName: ['Location'],
     }
     # Read in
     ice = Observation(args.input, args.thin, fdate)
 
     # write them out
-    ObsVars, nlocs = iconv.ExtractObsData(ice.data, locationKeyList)
-    DimDict = {'nlocs': nlocs}
+    ObsVars, Location = iconv.ExtractObsData(ice.data, locationKeyList)
+    DimDict = {'Location': Location}
     writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
 
     VarAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
     VarAttrs[vName, iconv.OvalName()]['units'] = '1'
     VarAttrs[vName, iconv.OerrName()]['units'] = '1'
-    VarAttrs[vName, iconv.OqcName()]['units'] = 'unitless'
 
     writer.BuildIoda(ObsVars, VarDims, VarAttrs, GlobalAttrs)
 
diff --git a/src/marine/gds2_sst2ioda.py b/src/marine/gds2_sst2ioda.py
index b6efe4af0..82a843150 100755
--- a/src/marine/gds2_sst2ioda.py
+++ b/src/marine/gds2_sst2ioda.py
@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 
 #
-# (C) Copyright 2019-2021 UCAR
+# (C) Copyright 2019-2022 UCAR
 #
 # This software is licensed under the terms of the Apache Licence Version 2.0
 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
@@ -26,23 +26,59 @@
 import ioda_conv_engines as iconv
 from orddicts import DefaultOrderedDict
 
-output_var_names = [
-    "sea_surface_temperature",
-    "sea_surface_skin_temperature"]
+os.environ["TZ"] = "UTC"
 
-locationKeyList = [
-    ("latitude", "float"),
-    ("longitude", "float"),
-    ("datetime", "string")
-]
-
-GlobalAttrs = {}
-
-VarAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
+# The first section of three variables are related to the IODA output file.
 
-DimDict = {}
+varInfo = [('sst', 'seaSurfaceTemperature', 'K', 999.0),
+           ('skin_sst', 'seaSurfaceSkinTemperature', 'K', 999.0)]
+var_keys = [var_key[0] for var_key in varInfo]
 
-VarDims = {}
+locationKeyList = [
+    ("latitude", "float", "degrees_north"),
+    ("longitude", "float", "degrees_east"),
+    ("dateTime", "long", "seconds since 1970-01-01T00:00:00Z")
+]
+meta_keys = [m_item[0] for m_item in locationKeyList]
+
+GlobalAttrs = {
+    'odb_version': 1,
+    'converter': os.path.basename(__file__),
+    'ioda_version': 2,
+    'description': "Sea-surface temperature from GHRRST Data Specification (GDS2.0) L2/3 formatted"
+}
+
+# This list of variables is from the input file.
+
+incoming_vars = ['quality_level',
+                 'sses_bias',
+                 'sses_standard_deviation',
+                 'sea_surface_temperature']
+
+iso8601_string = locationKeyList[meta_keys.index('dateTime')][2]
+epoch = datetime.fromisoformat(iso8601_string[14:-1])
+
+metaDataName = iconv.MetaDataName()
+obsValName = iconv.OvalName()
+obsErrName = iconv.OerrName()
+qcName = iconv.OqcName()
+
+float_missing_value = 999.0   # More typically nc.default_fillvals['f4']
+int_missing_value = nc.default_fillvals['i4']
+double_missing_value = nc.default_fillvals['f8']
+long_missing_value = nc.default_fillvals['i8']
+string_missing_value = '_'
+
+missing_vals = {'string': string_missing_value,
+                'integer': int_missing_value,
+                'long': long_missing_value,
+                'float': float_missing_value,
+                'double': double_missing_value}
+dtypes = {'string': object,
+          'integer': np.int32,
+          'long': np.int64,
+          'float': np.float32,
+          'double': np.float64}
 
 
 def read_input(input_args):
@@ -62,7 +98,7 @@ def read_input(input_args):
     input_file = input_args[0]
     global_config = input_args[1]
 
-    print("Reading ", input_file)
+    print(f"Reading input file: {input_file}")
     ncd = nc.Dataset(input_file, 'r')
 
     # get the base time (should only have 1 or 2 time slots)
@@ -72,7 +108,11 @@ def read_input(input_args):
     # get some of the global attributes that we are interested in
 
     for v in ('platform', 'sensor', 'processing_level'):
-        GlobalAttrs[v] = ncd.getncattr(v)
+        if v == 'processing_level':
+            v2 = 'processingLevel'
+        else:
+            v2 = v
+        GlobalAttrs[v2] = ncd.getncattr(v)
 
     # get the QC flags, and calculate a mask from the non-missing values
     # (since L3 files are mostly empty, fields need a mask applied immediately
@@ -87,7 +127,7 @@ def read_input(input_args):
     # If len(time) > 1, also need to repeat the lat/lon vals
     lons = ncd.variables['lon'][:].ravel()
     lats = ncd.variables['lat'][:].ravel()
-    if GlobalAttrs['processing_level'][:2] == 'L3':
+    if GlobalAttrs['processingLevel'][:2] == 'L3':
         len_grid = len(lons)*len(lats)
         lons, lats = np.meshgrid(lons, lats, copy=False)
         lons = np.tile(lons.ravel(), len(time_base)).ravel()[mask]
@@ -100,14 +140,11 @@ def read_input(input_args):
     # calculate the basetime offsets
     time = np.tile(np.atleast_2d(time_base).T, (1, len_grid)).ravel()[mask]
 
+    # Determine the observed time.
+    data_in['sst_dtime'] = ncd.variables['sst_dtime'][:].ravel()[mask]
+
     # load in all the other data and apply the missing value mask
-    input_vars = (
-        'quality_level',
-        'sst_dtime',
-        'sses_bias',
-        'sses_standard_deviation',
-        'sea_surface_temperature')
-    for v in input_vars:
+    for v in incoming_vars:
         if v not in data_in:
             data_in[v] = ncd.variables[v][:].ravel()[mask]
     ncd.close()
@@ -119,7 +156,7 @@ def read_input(input_args):
 
     # also, sometimes certain input variables have their own mask due to
     # missing values
-    for v in input_vars:
+    for v in incoming_vars:
         if np.ma.is_masked(data_in[v]):
             mask = np.logical_and(mask, np.logical_not(data_in[v].mask))
 
@@ -127,57 +164,84 @@ def read_input(input_args):
     time = time[mask]
     lons = lons[mask]
     lats = lats[mask]
-    for v in input_vars:
+    for v in incoming_vars:
         data_in[v] = data_in[v][mask]
 
     # create a string version of the date for each observation
     dates = []
+    data_in['sst_dtime'] = data_in['sst_dtime'][mask]
     for i in range(len(lons)):
-        obs_date = basetime + \
-            timedelta(seconds=float(time[i]+data_in['sst_dtime'][i]))
-        dates.append(obs_date.strftime("%Y-%m-%dT%H:%M:%SZ"))
+        obs_date = basetime + timedelta(seconds=float(time[i]+data_in['sst_dtime'][i]))
+        obs_date = int((obs_date - epoch).total_seconds())
+        dates.append(np.int64(obs_date))
 
     # calculate output values
     # Note: the qc flags in GDS2.0 run from 0 to 5, with higher numbers
     # being better. IODA typically expects 0 to be good, and higher numbers
     # are bad, so the qc flags flipped here.
-    # TODO change everything in soca to handle K instead of C ?
-    val_sst_skin = data_in['sea_surface_temperature'] - 273.15
+    val_sst_skin = data_in['sea_surface_temperature']
     val_sst = val_sst_skin - data_in['sses_bias']
     err = data_in['sses_standard_deviation']
     qc = 5 - data_in['quality_level']
 
-    # allocate space for output depending on which variables are to be saved
-
-    obs_dim = (len(lons))
     obs_data = {}
-    if global_config['output_sst']:
-        obs_data[(output_var_names[0], global_config['oval_name'])] = np.zeros(obs_dim)
-        obs_data[(output_var_names[0], global_config['oerr_name'])] = np.zeros(obs_dim)
-        obs_data[(output_var_names[0], global_config['opqc_name'])] = np.zeros(obs_dim)
-
-    if global_config['output_skin_sst']:
-        obs_data[(output_var_names[1], global_config['oval_name'])] = np.zeros(obs_dim)
-        obs_data[(output_var_names[1], global_config['oerr_name'])] = np.zeros(obs_dim)
-        obs_data[(output_var_names[1], global_config['opqc_name'])] = np.zeros(obs_dim)
 
-    obs_data[('datetime', 'MetaData')] = np.empty(len(dates), dtype=object)
-    obs_data[('datetime', 'MetaData')][:] = dates
-    obs_data[('latitude', 'MetaData')] = lats
-    obs_data[('longitude', 'MetaData')] = lons
+    # First, populate the MetaData.
+    obs_data[('dateTime', metaDataName)] = dates
+    obs_data[('latitude', metaDataName)] = lats
+    obs_data[('longitude', metaDataName)] = lons
 
+    # Next, populate the observed variables.
     if global_config['output_sst']:
-        obs_data[output_var_names[0], global_config['oval_name']] = val_sst
-        obs_data[output_var_names[0], global_config['oerr_name']] = err
-        obs_data[output_var_names[0], global_config['opqc_name']] = qc.astype('int32')
+        obs_data[('sst', obsValName)] = val_sst.astype('float32')
+        obs_data[('sst', obsErrName)] = err.astype('float32')
+        obs_data[('sst', qcName)] = qc.astype('int32')
+
     if global_config['output_skin_sst']:
-        obs_data[output_var_names[1], global_config['oval_name']] = val_sst_skin
-        obs_data[output_var_names[1], global_config['oerr_name']] = err
-        obs_data[output_var_names[1], global_config['opqc_name']] = qc.astype('int32')
+        obs_data[('skin_sst', obsValName)] = val_sst_skin.astype('float32')
+        obs_data[('skin_sst', obsErrName)] = err.astype('float32')
+        obs_data[('skin_sst', qcName)] = qc.astype('int32')
 
     return (obs_data, GlobalAttrs)
 
 
+def IODA(filename, GlobalAttrs, nlocs, obs_data):
+
+    DimDict = {'Location': nlocs}
+    varDims = {}
+    varAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
+    data = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
+
+    # Set units and FillValue attributes for groups associated with observed variable.
+    for key in var_keys:
+        if (key, obsValName) in obs_data:
+            var_name = varInfo[var_keys.index(key)][1]
+            varDims[var_name] = ['Location']
+            varAttrs[(var_name, obsValName)]['units'] = varInfo[var_keys.index(key)][2]
+            varAttrs[(var_name, obsErrName)]['units'] = varInfo[var_keys.index(key)][2]
+            varAttrs[(var_name, obsValName)]['_FillValue'] = varInfo[var_keys.index(key)][3]
+            varAttrs[(var_name, obsErrName)]['_FillValue'] = varInfo[var_keys.index(key)][3]
+            varAttrs[(var_name, qcName)]['_FillValue'] = int_missing_value
+
+            data[(var_name, obsValName)] = np.array(obs_data[(key, obsValName)], dtype=np.float32)
+            data[(var_name, obsErrName)] = np.array(obs_data[(key, obsErrName)], dtype=np.float32)
+            data[(var_name, qcName)] = np.array(obs_data[(key, qcName)], dtype=np.int32)
+
+    # Set units of the MetaData variables and all _FillValues.
+    for key in meta_keys:
+        dtypestr = locationKeyList[meta_keys.index(key)][1]
+        if locationKeyList[meta_keys.index(key)][2]:
+            varAttrs[(key, metaDataName)]['units'] = locationKeyList[meta_keys.index(key)][2]
+        varAttrs[(key, metaDataName)]['_FillValue'] = missing_vals[dtypestr]
+        data[(key, metaDataName)] = np.array(obs_data[(key, metaDataName)], dtype=dtypes[dtypestr])
+
+    # Initialize the writer, then write the file.
+    writer = iconv.IodaWriter(filename, locationKeyList, DimDict)
+    writer.BuildIoda(data, varDims, varAttrs, GlobalAttrs)
+
+    return
+
+
 def main():
 
     # Get command line arguments
@@ -239,9 +303,6 @@ def main():
     global_config = {}
     global_config['date'] = args.date
     global_config['thin'] = args.thin
-    global_config['oval_name'] = iconv.OvalName()
-    global_config['oerr_name'] = iconv.OerrName()
-    global_config['opqc_name'] = iconv.OqcName()
     global_config['output_sst'] = args.sst
     global_config['output_skin_sst'] = args.skin_sst
     pool_inputs = [(i, global_config) for i in args.input]
@@ -253,52 +314,24 @@ def main():
     # concatenate the data from the files
     obs_data, GlobalAttrs = obs[0]
 
+    # Add additional global attributes we want to output in the file.
+    GlobalAttrs['sourceFiles'] = ", ".join(args.input)
+    GlobalAttrs['datetimeReference'] = args.date.strftime("%Y-%m-%dT%H:%M:%SZ")
+    GlobalAttrs['thinning'] = args.thin
+
     for i in range(1, len(obs)):
         for k in obs_data:
             axis = len(obs[i][0][k].shape)-1
             obs_data[k] = np.concatenate(
                 (obs_data[k], obs[i][0][k]), axis=axis)
 
-    # prepare global attributes we want to output in the file,
-    # in addition to the ones already loaded in from the input file
-    GlobalAttrs['date_time_string'] = args.date.strftime("%Y-%m-%dT%H:%M:%SZ")
-    GlobalAttrs['thinning'] = args.thin
-    GlobalAttrs['converter'] = os.path.basename(__file__)
-
-    # determine which variables we are going to output
-    selected_names = []
-    if args.sst:
-        selected_names.append(output_var_names[0])
-    if args.skin_sst:
-        selected_names.append(output_var_names[1])
-
-    # pass parameters to the IODA writer
-    # (needed because we are bypassing ExtractObsData within BuildNetcdf)
-    VarDims = {
-        'sea_surface_temperature': ['nlocs'],
-        'sea_surface_skin_temperature': ['nlocs'],
-    }
-
-    nlocs = len(obs_data[('longitude', 'MetaData')])
-
-    DimDict = {'nlocs': nlocs}
-
-    writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
-
-    VarAttrs[('sea_surface_temperature', 'ObsValue')]['units'] = 'celsius'
-    VarAttrs[('sea_surface_temperature', 'ObsError')]['units'] = 'celsius'
-    VarAttrs[('sea_surface_temperature', 'PreQC')]['units'] = 'unitless'
-    VarAttrs[('sea_surface_skin_temperature', 'ObsValue')]['units'] = 'celsius'
-    VarAttrs[('sea_surface_skin_temperature', 'ObsError')]['units'] = 'celsius'
-    VarAttrs[('sea_surface_skin_temperature', 'PreQC')]['units'] = 'unitless'
-    VarAttrs[('sea_surface_temperature', 'ObsValue')]['_FillValue'] = 999
-    VarAttrs[('sea_surface_temperature', 'ObsError')]['_FillValue'] = 999
-    VarAttrs[('sea_surface_temperature', 'PreQC')]['_FillValue'] = 999
-    VarAttrs[('sea_surface_skin_temperature', 'ObsValue')]['_FillValue'] = 999
-    VarAttrs[('sea_surface_skin_temperature', 'ObsError')]['_FillValue'] = 999
-    VarAttrs[('sea_surface_skin_temperature', 'PreQC')]['_FillValue'] = 999
-
-    writer.BuildIoda(obs_data, VarDims, VarAttrs, GlobalAttrs)
+    # Total number of observations.
+    nlocs = len(obs_data[('dateTime', metaDataName)])
+
+    print(f"Preparing to write {nlocs} observations to {args.output}")
+
+    # Write out the file.
+    IODA(args.output, GlobalAttrs, nlocs, obs_data)
 
 
 if __name__ == '__main__':
diff --git a/src/marine/glider2ioda.py b/src/marine/glider2ioda.py
index b09cc2570..de9449aef 100644
--- a/src/marine/glider2ioda.py
+++ b/src/marine/glider2ioda.py
@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 
 #
-# (C) Copyright 2019 UCAR
+# (C) Copyright 2019-2022 UCAR
 #
 # This software is licensed under the terms of the Apache Licence Version 2.0
 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
@@ -25,14 +25,14 @@
 from orddicts import DefaultOrderedDict
 
 vName = [
-    "sea_water_temperature",
-    "sea_water_salinity"]
+    "waterTemperature",
+    "salinity"]
 
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("depth", "float"),
-    ("datetime", "string")
+    ("depthBelowWaterSurface", "float"),
+    ("dateTime", "long")
 ]
 
 GlobalAttrs = {
@@ -74,7 +74,7 @@ def _read(self):
         Sqcs = ncd.variables['salinity_qc'][:]-1
         errs = np.squeeze(errs)
         ncd.close()
-        base_date = datetime(1970, 1, 1)
+
         ii = int((self.lon_eth_HAT10-self.lon_wth_HAT10)/self.dxy)+10
         jj = int((self.lat_nth_HAT10-self.lat_sth_HAT10)/self.dxy)+10
         kk = int((self.mdep)/self.dz)+10
@@ -93,10 +93,10 @@ def _read(self):
                         valKey = vName[j], iconv.OvalName()
                         errKey = vName[j], iconv.OerrName()
                         qcKey = vName[j], iconv.OqcName()
-                        dt = base_date + timedelta(seconds=int(time[i]))
-                        locKey = lats[i], lons[i], dpth[i], dt.strftime("%Y-%m-%dT%H:%M:%SZ")
+                        dt = int(time[i])
+                        locKey = lats[i], lons[i], dpth[i], dt
                         if j == 0:
-                            self.data[locKey][valKey] = temperature[i]
+                            self.data[locKey][valKey] = temperature[i] + 273.15
                             self.data[locKey][errKey] = errs[i]
                             self.data[locKey][qcKey] = Tqcs[i]
                         else:
@@ -132,20 +132,21 @@ def main():
     yamlfile = args.yaml
     fdate = datetime.strptime(args.date, '%Y%m%d%H')
     VarDims = {
-        'sea_water_temperature': ['nlocs'],
-        'sea_water_salinity': ['nlocs']}
+        'waterTemperature': ['Location'],
+        'salinity': ['Location']}
     prof = Profile(args.input, args.yaml, fdate)
-    GlobalAttrs['date_time_string'] = fdate.strftime("%Y-%m-%dT%H:%M:%SZ")
     ObsVars, nlocs = iconv.ExtractObsData(prof.data, locationKeyList)
-    DimDict = {'nlocs': nlocs}
+    DimDict = {'Location': nlocs}
     writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
     VarAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
-    VarAttrs[('sea_water_temperature', 'ObsValue')]['units'] = 'celsius'
-    VarAttrs[('sea_water_salinity', 'ObsValue')]['units'] = 'psu'
-    VarAttrs[('sea_water_temperature', 'ObsValue')]['_FillValue'] = -32767
-    VarAttrs[('sea_water_salinity', 'ObsValue')]['_FillValue'] = -32767
-    VarAttrs[('sea_water_temperature', 'PreQC')]['units'] = ''
-    VarAttrs[('sea_water_salinity', 'ObsError')]['units'] = ''
+    VarAttrs[('waterTemperature', 'ObsValue')]['units'] = 'K'
+    VarAttrs[('waterTemperature', 'ObsError')]['units'] = 'K'
+    VarAttrs[('salinity', 'ObsValue')]['units'] = '1'
+    VarAttrs[('salinity', 'ObsError')]['units'] = '1'
+    VarAttrs[('depthBelowWaterSurface', 'MetaData')]['units'] = 'm'
+    VarAttrs[('dateTime', 'MetaData')]['units'] = 'seconds since 1970-01-01T00:00:00Z'
+    VarAttrs[('waterTemperature', 'ObsValue')]['_FillValue'] = -32767
+    VarAttrs[('salinity', 'ObsValue')]['_FillValue'] = -32767
     writer.BuildIoda(ObsVars, VarDims, VarAttrs, GlobalAttrs)
 
 
diff --git a/src/marine/gmao_obs2ioda.py b/src/marine/gmao_obs2ioda.py
index bce852e5a..dfddcc2c4 100755
--- a/src/marine/gmao_obs2ioda.py
+++ b/src/marine/gmao_obs2ioda.py
@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 
-# (C) Copyright 2019 UCAR
+# (C) Copyright 2019-2022 UCAR
 #
 # This software is licensed under the terms of the Apache Licence Version 2.0
 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
@@ -11,8 +11,9 @@
 
 from __future__ import print_function
 import sys
+import os
 from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
-import netCDF4 as nc4
+import netCDF4 as nc
 import numpy as np
 from datetime import datetime
 from pathlib import Path
@@ -22,43 +23,55 @@
     IODA_CONV_PATH = Path(__file__).parent/'..'/'lib-python'
 sys.path.append(str(IODA_CONV_PATH.resolve()))
 
-import ioda_conv_ncio as iconv
+import ioda_conv_engines as iconv
 from orddicts import DefaultOrderedDict
 
+os.environ["TZ"] = "UTC"
 
-# obsIdDict is defined as obsid_dict in ocean_obs.py
-obsIdDict = {
-    5521: 'sea_water_salinity',  # Salinity
-    3073: 'sea_water_temperature',  # Temperature
-    5525: 'sea_surface_temperature',  # SST
-    5526: 'absolute_dynamic_topography',  # SSH (Not used ...)
-    5351: 'absolute_dynamic_topography',  # SSH
-    6000: 'sea_ice_area_fraction',  # AICE
-    6001: 'sea_ice_thickness'  # HICE
-}
-
-
+# varDict has a numerical code to match a variable type attribute in the netCDF input file
+# followed by an abbreviated name, IODA output var name, units, then acceptable min/max vals.
 varDict = {
-    'sea_water_salinity': 'sal',
-    'sea_water_temperature': 'temp',
-    'sea_surface_temperature': 'sst',
-    'absolute_dynamic_topography': 'adt',
-    'sea_ice_area_fraction': 'frac',
-    'sea_ice_thickness': 'thick'
+    5521: ['sal', 'salinity', '1', 0.0, 50.0],
+    3073: ['temp', 'waterTemperature', 'K', 271.0, 325.0],
+    5525: ['sst', 'seaSurfaceTemperature', 'K', 271.0, 325.0],
+    5526: ['adt', 'absoluteDynamicTopography', 'm', -5.0, 5.0],
+    5351: ['adt', 'absoluteDynamicTopography', 'm', -5.0, 5.0],   # not used
+    6000: ['frac', 'seaIceFraction', '1', 0.0, 1.0],
+    6001: ['thick', 'iceThickness', 'm', 0.001, 5000.0],
 }
 
-
-def flipDict(dictIn):
-
-    dictOut = {}
-
-    for key, value in dictIn.items():
-        if value not in dictOut:
-            dictOut[value] = [key]
-        else:
-            dictOut[value].append(key)
-
-    return dictOut
+locationKeyList = [
+    ("latitude", "float", "degrees_north"),
+    ("longitude", "float", "degrees_east"),
+    ("depthBelowWaterSurface", "float", "m"),
+    ("dateTime", "long", "seconds since 1970-01-01T00:00:00Z")
+]
+meta_keys = [m_item[0] for m_item in locationKeyList]
+
+iso8601_string = locationKeyList[meta_keys.index('dateTime')][2]
+epoch = datetime.fromisoformat(iso8601_string[14:-1])
+
+metaDataName = iconv.MetaDataName()
+obsValName = iconv.OvalName()
+obsErrName = iconv.OerrName()
+qcName = iconv.OqcName()
+
+float_missing_value = nc.default_fillvals['f4']
+int_missing_value = nc.default_fillvals['i4']
+double_missing_value = nc.default_fillvals['f8']
+long_missing_value = nc.default_fillvals['i8']
+string_missing_value = '_'
+
+missing_vals = {'string': string_missing_value,
+                'integer': int_missing_value,
+                'long': long_missing_value,
+                'float': float_missing_value,
+                'double': double_missing_value}
+dtypes = {'string': object,
+          'integer': np.int32,
+          'long': np.int64,
+          'float': np.float32,
+          'double': np.float64}
 
 
 class GMAOobs(object):
@@ -69,38 +82,43 @@ def __init__(self, filename, date):
         self.date = date
 
         # Read GMAO data
-        self._read()
+        self._read(self.date)
 
         return
 
-    def _read(self):
-
-        data = {}
-
-        nc = nc4.Dataset(self.filename)
+    def _read(self, date):
 
-        data['nobs'] = len(nc.dimensions['nobs'])
+        self.date = date
 
-        data['typ'] = nc.variables['typ'][:].data
-        data['lon'] = nc.variables['lon'][:].data
-        data['lat'] = nc.variables['lat'][:].data
-        data['depth'] = nc.variables['depth'][:].data
-        data['value'] = nc.variables['value'][:].data
-        data['oerr'] = nc.variables['oerr'][:].data
+        data = {}
 
-        nc.close()
+        ncd = nc.Dataset(self.filename)
 
-        self.data = data
+        nobs = len(ncd.dimensions['nobs'])
+        data['nobs'] = nobs
 
-        return
+        # The input file(s) contain no date information, so take it from command line info.
+        data['dateTime'] = np.full(nobs, np.int64(round((self.date - epoch).total_seconds())))
 
+        data['longitude'] = ncd.variables['lon'][:].data
+        data['latitude'] = ncd.variables['lat'][:].data
+        data['depthBelowWaterSurface'] = ncd.variables['depth'][:].data
+        types = ncd.variables['typ'][:].data
+        values = ncd.variables['value'][:].data
+        values[np.isnan(values)] = float_missing_value
+        errors = ncd.variables['oerr'][:].data
 
-class refGMAOobs(object):
+        for key in varDict.keys():
+            key_var = varDict[key][0] + "_vals"
+            key_err = varDict[key][0] + "_errs"
+            data[key_var] = np.full(nobs, float_missing_value)
+            data[key_err] = np.full(nobs, float_missing_value)
+            ind = np.where(types == key)
+            data[key_var][ind] = values[ind]
+            data[key_err][ind] = errors[ind]
 
-    def __init__(self, filename, date, data):
+        ncd.close()
 
-        self.filename = filename
-        self.date = date
         self.data = data
 
         return
@@ -108,28 +126,40 @@ def __init__(self, filename, date, data):
 
 class IODA(object):
 
-    def __init__(self, filename, date, varName, obsList):
-        '''
-        Initialize IODA writer class,
-        transform to IODA data structure and,
-        write out to IODA file.
-        '''
+    def __init__(self, files_input, filename, date, obsList):
 
+        self.files_input = files_input
         self.filename = filename
         self.date = date
 
-        self.locKeyList = [
-            ("latitude", "float"),
-            ("longitude", "float"),
-            ("depth", "float"),
-            ("datetime", "string")
-        ]
-
-        self.AttrData = {
+        GlobalAttrs = {
             'odb_version': 1,
-            'date_time_string': self.date.strftime("%Y-%m-%dT%H:%M:%SZ")
+            'converter': os.path.basename(__file__),
+            'ioda_version': 2,
+            'sourceFiles': ", ".join(self.files_input),
+            'datetimeReference': self.date.strftime('%Y-%m-%dT%H:%M:%S%z'),
+            'description': "GMAO Ocean Observations"
         }
 
+        varAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
+
+        # Set units of the MetaData variables and all _FillValues.
+        for key in meta_keys:
+            dtypestr = locationKeyList[meta_keys.index(key)][1]
+            if locationKeyList[meta_keys.index(key)][2]:
+                varAttrs[(key, metaDataName)]['units'] = locationKeyList[meta_keys.index(key)][2]
+            varAttrs[(key, metaDataName)]['_FillValue'] = missing_vals[dtypestr]
+
+        # Set units and FillValue attributes for groups associated with observed variable.
+        for key in varDict.keys():
+            variable = varDict[key][1]
+            units = varDict[key][2]
+            varAttrs[(variable, obsValName)]['units'] = units
+            varAttrs[(variable, obsErrName)]['units'] = units
+            varAttrs[(variable, obsValName)]['_FillValue'] = float_missing_value
+            varAttrs[(variable, obsErrName)]['_FillValue'] = float_missing_value
+            varAttrs[(variable, qcName)]['_FillValue'] = int_missing_value
+
         # Skip out if there are no obs!
         totalObs = 0
         for obs in obsList:
@@ -140,126 +170,78 @@ def __init__(self, filename, date, varName, obsList):
             print('No %s observations for IODA!' % varName)
             return
 
-        self.writer = iconv.NcWriter(self.filename, self.locKeyList)
-
-        self.keyDict = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
-
-        self.keyDict[varName]['valKey'] = varName, self.writer.OvalName()
-        self.keyDict[varName]['errKey'] = varName, self.writer.OerrName()
-        self.keyDict[varName]['qcKey'] = varName, self.writer.OqcName()
-
         # data is the dictionary containing IODA friendly data structure
-        self.data = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
-
-        recKey = 0
+        data = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
 
+        nlocs = 0
         for obs in obsList:
-
-            if obs.data['nobs'] <= 0:
-                continue
-
-            for n in range(obs.data['nobs']):
-
-                oval = obs.data['value'][n]
-                oerr = obs.data['oerr'][n]
-
-                if discardOb(varName, oval):
-                    continue
-
-                lat = obs.data['lat'][n]
-                lon = obs.data['lon'][n]
-                lvl = obs.data['depth'][n]
-
-                locKey = lat, lon, lvl, obs.date.strftime("%Y-%m-%dT%H:%M:%SZ")
-
-                valKey = self.keyDict[varName]['valKey']
-                errKey = self.keyDict[varName]['errKey']
-                qcKey = self.keyDict[varName]['qcKey']
-
-                self.data[recKey][locKey][valKey] = oval
-                self.data[recKey][locKey][errKey] = oerr
-                self.data[recKey][locKey][qcKey] = 0
-
-        (ObsVars, LocMdata, VarMdata) = self.writer.ExtractObsData(self.data)
-        self.writer.BuildNetcdf(ObsVars, LocMdata, VarMdata, self.AttrData)
+            nlocs = obs.data['nobs']
+            for n in range(nlocs):
+                # Transfer the MetaData info into the IODA final data container.
+                for key in meta_keys:
+                    dtypestr = locationKeyList[meta_keys.index(key)][1]
+                    val = obs.data[key][n]
+                    varVals = np.array(val, dtype=dtypes[dtypestr])
+                    # If on the first time through, set the data dict entry
+                    # to a numpy array with a specified data type. Otherwise, append
+                    # the incoming data to the current data.
+                    if (key, metaDataName) in data:
+                        data[(key, metaDataName)] = np.append(
+                            data[(key, metaDataName)], varVals)
+                    else:
+                        data[(key, metaDataName)] = varVals
+
+                varDims = {}
+                # Fill up the final array of observed values and obsErrors
+                for key in varDict.keys():
+                    key_var = varDict[key][0] + "_vals"
+                    key_err = varDict[key][0] + "_errs"
+                    variable = varDict[key][1]
+                    min_val = varDict[key][3]
+                    max_val = varDict[key][4]
+
+                    if all(x == float_missing_value for x in obs.data[key_var]):
+                        continue
+
+                    varDims = {key_var: ['Location']}
+
+                    # ObsValue
+                    varVals = np.array(obs.data[key_var][n], dtype=dtypes['float'])
+                    if 'Temperature' in variable:
+                        if varVals != float_missing_value:
+                            varVals = varVals + 273.15
+                    if (varVals < min_val or varVals > max_val):
+                        varVals = float_missing_value
+                    if (variable, obsValName) in data:
+                        data[(variable, obsValName)] = np.append(
+                            data[(variable, obsValName)], np.float32(varVals))
+                    else:
+                        data[(variable, obsValName)] = np.float32(varVals)
+
+                    # ObsError
+                    varVals = np.array(obs.data[key_err][n], dtype=dtypes['float'])
+                    if (variable, obsErrName) in data:
+                        data[(variable, obsErrName)] = np.append(
+                            data[(variable, obsErrName)], np.float32(varVals))
+                    else:
+                        data[(variable, obsErrName)] = np.float32(varVals)
+
+                    # QC (preQC) value (zero for now)
+                    if (variable, qcName) in data:
+                        data[(variable, qcName)] = np.append(data[(variable, qcName)], np.int32(0))
+                    else:
+                        data[(variable, qcName)] = np.int32(0)
+
+        print(f"Found a total number of observations: {nlocs}")
+
+        # Initialize the writer, then write the file.
+        DimDict = {'Location': nlocs}
+        self.writer = iconv.IodaWriter(self.filename, locationKeyList, DimDict)
+        self.writer.BuildIoda(data, varDims, varAttrs, GlobalAttrs)
 
         return
 
 
-def separateObs(obsList):
-
-    obsDict = {}
-    for key in obsIdDict.keys():
-
-        obsListKey = []
-
-        for obs in obsList:
-
-            date = obs.date
-            filename = obs.filename
-
-            ind = np.where(obs.data['typ'] == key)
-
-            data = {}
-            data['nobs'] = len(ind[0])
-            data['typ'] = obs.data['typ'][ind]
-            data['lon'] = obs.data['lon'][ind]
-            data['lat'] = obs.data['lat'][ind]
-            data['depth'] = obs.data['depth'][ind]
-            data['value'] = obs.data['value'][ind]
-            data['oerr'] = obs.data['oerr'][ind]
-
-            obsListKey.append(refGMAOobs(filename, date, data))
-
-        obsDict[key] = obsListKey
-
-    return obsDict
-
-
-def sortDict(obsDictIn):
-
-    # Flip the obsIdDict
-    obsIdDictFlipped = flipDict(obsIdDict)
-
-    obsDictOut = {}
-
-    # Loop over flipped obsIdDict
-    for key, values in obsIdDictFlipped.items():
-
-        obsList = []
-        for value in values:
-            obsList.append(obsDictIn[value])
-
-        # Flatten the newly created list of lists
-        obsDictOut[key] = [item for sublist in obsList for item in sublist]
-
-    return obsDictOut
-
-
-def discardOb(varName, obsValue):
-
-    discardOb = True
-
-    if varName in ["sea_water_salinity"]:
-        if 0. <= obsValue <= 50.:
-            discardOb = False
-    elif varName in ["sea_water_temperature", "sea_surface_temperature"]:
-        if -2. <= obsValue <= 100.:
-            discardOb = False
-    elif varName in ["absolute_dynamic_topography"]:
-        if -5. <= obsValue <= 5.:
-            discardOb = False
-    elif varName in ["sea_ice_area_fraction"]:
-        if 0. <= obsValue <= 1.:
-            discardOb = False
-    elif varName in ["sea_ice_thickness"]:
-        discardOb = False
-    else:
-        raise SystemExit("Unknown observation variable %s" % varName)
-
-    return discardOb
-
-
 def main():
 
     parser = ArgumentParser(
@@ -293,15 +275,12 @@ def main():
 
     obsList = []
     for fname, idate in zip(fList, dList):
-        obsList.append(GMAOobs(fname, idate))
-
-    obsDict = separateObs(obsList)
+        if not os.path.isfile(fname):
+            parser.error('Input (-i option) file: ', fname, ' does not exist')
 
-    obsDictSorted = sortDict(obsDict)
+        obsList.append(GMAOobs(fname, idate))
 
-    for key, value in varDict.items():
-        fout = '%s_%s.nc' % (foutput, value)
-        IODA(fout, fdate, key, obsDictSorted[key])
+    IODA(fList, foutput, fdate, obsList)
 
 
 if __name__ == '__main__':
diff --git a/src/marine/godae_bgc_argo2ioda.py b/src/marine/godae_bgc_argo2ioda.py
index 2eb23bdd3..ccc8c87df 100644
--- a/src/marine/godae_bgc_argo2ioda.py
+++ b/src/marine/godae_bgc_argo2ioda.py
@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 
 #
-# (C) Copyright 2021 UCAR
+# (C) Copyright 2021-2022 UCAR
 #
 # This software is licensed under the terms of the Apache Licence Version 2.0
 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
@@ -9,7 +9,9 @@
 
 from __future__ import print_function
 import sys
+import os
 import argparse
+import numpy as np
 import netCDF4 as nc
 from datetime import datetime, timedelta
 from pathlib import Path
@@ -23,18 +25,43 @@
 import ioda_conv_engines as iconv
 from orddicts import DefaultOrderedDict
 
-vName = {
-    'CHL': "mass_concentration_of_chlorophyll_in_sea_water",
-}
+os.environ["TZ"] = "UTC"
+
+varInfo = ['chlorophyllMassConcentration', 'mg m-3', 999.]
+varDims = {varInfo[0]: ['Location']}
 
 locationKeyList = [
-    ("latitude", "float"),
-    ("longitude", "float"),
-    ("depth", "float"),
-    ("datetime", "string")
+    ("latitude", "float", "degrees_north"),
+    ("longitude", "float", "degrees_east"),
+    ("depthBelowWaterSurface", "float", "m"),
+    ("dateTime", "long", "seconds since 1950-01-01T00:00:00Z")
 ]
-
-GlobalAttrs = {}
+meta_keys = [m_item[0] for m_item in locationKeyList]
+
+iso8601_string = locationKeyList[meta_keys.index('dateTime')][2]
+epoch = datetime.fromisoformat(iso8601_string[14:-1])
+
+metaDataName = iconv.MetaDataName()
+obsValName = iconv.OvalName()
+obsErrName = iconv.OerrName()
+qcName = iconv.OqcName()
+
+float_missing_value = 999.
+int_missing_value = 99900
+double_missing_value = nc.default_fillvals['f8']
+long_missing_value = nc.default_fillvals['i8']
+string_missing_value = '_'
+
+missing_vals = {'string': string_missing_value,
+                'integer': int_missing_value,
+                'long': long_missing_value,
+                'float': float_missing_value,
+                'double': double_missing_value}
+dtypes = {'string': object,
+          'integer': np.int32,
+          'long': np.int64,
+          'float': np.float32,
+          'double': np.float64}
 
 
 class Profile(object):
@@ -56,23 +83,92 @@ def _read(self):
         qcs = ncd.variables['CHLA_ADJUSTED_QC'][:]
         ncd.close()
 
-        base_date = datetime(1950, 1, 1)
+        obs = {}
+        for key in meta_keys:
+            obs[key] = []
+        obs['vals'] = []
+        obs['errs'] = []
+        obs['qc'] = []
 
         for i in range(len(dpth[1])-1):
 
             if ma.getmask(vals)[1][i] == 1:
                 continue
 
-            valKey = vName['CHL'], iconv.OvalName()
-            errKey = vName['CHL'], iconv.OerrName()
-            qcKey = vName['CHL'], iconv.OqcName()
+            dt = epoch + timedelta(days=float(time[1]))
+            obs['dateTime'].append(np.int64(round((dt - epoch).total_seconds())))
+            obs['latitude'].append(ma.getdata(lats)[1])
+            obs['longitude'].append(ma.getdata(lons)[1])
+            obs['depthBelowWaterSurface'].append(ma.getdata(dpth)[1][i])
+            obs['vals'].append(ma.getdata(vals)[1][i])
+            obs['errs'].append(ma.getdata(errs)[1][i])
+            obs['qc'].append(0)
+
+        self.data = obs
+
+        return
+
+
+class IODA(object):
+
+    def __init__(self, files_input, filename, date, obsList):
 
-            dt = base_date + timedelta(days=float(time[1]))
-            locKey = ma.getdata(lats)[1], ma.getdata(lons)[1], \
-                ma.getdata(dpth)[1][i], dt.strftime("%Y-%m-%dT%H:%M:%SZ")
-            self.data[locKey][valKey] = ma.getdata(vals)[1][i]
-            self.data[locKey][errKey] = ma.getdata(errs)[1][i]
-            self.data[locKey][qcKey] = 0
+        '''
+        Initialize IODA writer class,
+        transform to IODA data structure and,
+        write out to IODA file.
+        '''
+
+        self.filename = filename
+        self.date = date
+
+        self.GlobalAttrs = {
+            'converter': os.path.basename(__file__),
+            'ioda_version': 2,
+            'sourceFiles': ", ".join(files_input),
+            'datetimeReference': self.date.strftime('%Y-%m-%dT%H:%M:%S%z'),
+            'description': "GODAE Profile Observations of chlorophyll (BGC-Argo)"
+        }
+
+        self.varAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
+
+        # Set units and FillValue attributes for groups associated with observed variable.
+        self.varAttrs[(varInfo[0], obsValName)]['units'] = varInfo[1]
+        self.varAttrs[(varInfo[0], obsErrName)]['units'] = varInfo[1]
+        self.varAttrs[(varInfo[0], obsValName)]['_FillValue'] = varInfo[2]
+        self.varAttrs[(varInfo[0], obsErrName)]['_FillValue'] = varInfo[2]
+        self.varAttrs[(varInfo[0], qcName)]['_FillValue'] = int_missing_value
+
+        # data is the dictionary containing IODA friendly data structure
+        self.data = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
+
+        nobs = 0
+        for obs in obsList:
+
+            nobs += len(obs.data['vals'])
+            if nobs <= 0:
+                print('No observations for IODA!')
+                continue
+
+            # Set units of the MetaData variables and all _FillValues.
+            for key in meta_keys:
+                dtypestr = locationKeyList[meta_keys.index(key)][1]
+                if locationKeyList[meta_keys.index(key)][2]:
+                    self.varAttrs[(key, metaDataName)]['units'] = locationKeyList[meta_keys.index(key)][2]
+                self.varAttrs[(key, metaDataName)]['_FillValue'] = missing_vals[dtypestr]
+                self.data[(key, metaDataName)] = np.array(obs.data[key], dtype=dtypes[dtypestr])
+
+            # Fill up the final array of observed values, obsErrors, and Qc
+            self.data[(varInfo[0], obsValName)] = np.array(obs.data['vals'], dtype=float)
+            self.data[(varInfo[0], obsErrName)] = np.array(obs.data['errs'], dtype=float)
+            self.data[(varInfo[0], qcName)] = np.array(obs.data['qc'], dtype=np.int32)
+
+        # Initialize the writer, then write the file.
+        DimDict = {'Location': nobs}
+        self.writer = iconv.IodaWriter(self.filename, locationKeyList, DimDict)
+        self.writer.BuildIoda(self.data, varDims, self.varAttrs, self.GlobalAttrs)
+
+        return
 
 
 def main():
@@ -80,7 +176,7 @@ def main():
     parser = argparse.ArgumentParser(
         description=(
             'Read BGC-Argo chlorophyll profile from godae'
-            '  and convert to IODA v2 format.'
+            ' and convert to IODA v2 format.'
         )
     )
 
@@ -88,7 +184,7 @@ def main():
     required.add_argument(
         '-i', '--input',
         help="name of BGC-Argo observation input file(s)",
-        type=str, required=True)
+        type=str, nargs='+', required=True)
     required.add_argument(
         '-o', '--output',
         help="path of ioda output file",
@@ -98,29 +194,18 @@ def main():
         help="base date for the center of the window",
         metavar="YYYYMMDDHH", type=str, required=True)
     args = parser.parse_args()
-    fdate = datetime.strptime(args.date, '%Y%m%d%H')
 
-    VarDims = {
-        'mass_concentration_of_chlorophyll_in_sea_water': ['nlocs'],
-    }
-
-    # Read in argo profiles
-    prof = Profile(args.input, fdate)
-
-    # write them out
-    ObsVars, nlocs = iconv.ExtractObsData(prof.data, locationKeyList)
+    fList = args.input
+    foutput = args.output
+    fdate = datetime.strptime(args.date, '%Y%m%d%H')
 
-    DimDict = {'nlocs': nlocs}
-    writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
+    obsList = []
+    for fname in fList:
+        obs = Profile(fname, fdate)       # Read in argo profiles
+        obsList.append(obs)
 
-    VarAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
-    VarAttrs[('mass_concentration_of_chlorophyll_in_sea_water', 'ObsValue')]['units'] = 'mg m-3'
-    VarAttrs[('mass_concentration_of_chlorophyll_in_sea_water', 'ObsError')]['units'] = 'mg m-3'
-    VarAttrs[('mass_concentration_of_chlorophyll_in_sea_water', 'PreQC')]['units'] = 'unitless'
-    VarAttrs[('mass_concentration_of_chlorophyll_in_sea_water', 'ObsValue')]['_FillValue'] = 999.
-    VarAttrs[('mass_concentration_of_chlorophyll_in_sea_water', 'ObsError')]['_FillValue'] = 999.
-    VarAttrs[('mass_concentration_of_chlorophyll_in_sea_water', 'PreQC')]['_FillValue'] = 999
-    writer.BuildIoda(ObsVars, VarDims, VarAttrs, GlobalAttrs)
+    # Write the output file.
+    IODA(fList, foutput, fdate, obsList)
 
 
 if __name__ == '__main__':
diff --git a/src/marine/godae_profile2ioda.py b/src/marine/godae_profile2ioda.py
index 6fbb3f5c2..0b7ca904a 100755
--- a/src/marine/godae_profile2ioda.py
+++ b/src/marine/godae_profile2ioda.py
@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 
 #
-# (C) Copyright 2019-2021 UCAR
+# (C) Copyright 2019-2022 UCAR
 #
 # This software is licensed under the terms of the Apache Licence Version 2.0
 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
@@ -9,6 +9,9 @@
 
 from __future__ import print_function
 import sys
+import os
+import numpy as np
+import netCDF4 as nc
 from datetime import datetime
 from scipy.io import FortranFile
 from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
@@ -22,6 +25,51 @@
 import ioda_conv_engines as iconv
 from orddicts import DefaultOrderedDict
 
+os.environ["TZ"] = "UTC"
+
+varDict = {
+    'ob_tmp': ['waterTemperature', 'K'],
+    'ob_sal': ['salinity', '1']
+}
+
+varDims = {
+    'waterTemperature': ['Location'],
+    'salinity': ['Location'],
+}
+
+locationKeyList = [
+    ("latitude", "float", "degrees_north"),
+    ("longitude", "float", "degrees_east"),
+    ("depthBelowWaterSurface", "float", "m"),
+    ("dateTime", "long", "seconds since 1970-01-01T00:00:00Z")
+]
+meta_keys = [m_item[0] for m_item in locationKeyList]
+
+iso8601_string = locationKeyList[meta_keys.index('dateTime')][2]
+epoch = datetime.fromisoformat(iso8601_string[14:-1])
+
+metaDataName = iconv.MetaDataName()
+obsValName = iconv.OvalName()
+obsErrName = iconv.OerrName()
+qcName = iconv.OqcName()
+
+float_missing_value = -999.
+int_missing_value = -99900
+double_missing_value = nc.default_fillvals['f8']
+long_missing_value = nc.default_fillvals['i8']
+string_missing_value = '_'
+
+missing_vals = {'string': string_missing_value,
+                'integer': int_missing_value,
+                'long': long_missing_value,
+                'float': float_missing_value,
+                'double': double_missing_value}
+dtypes = {'string': object,
+          'integer': np.int32,
+          'long': np.int64,
+          'float': np.float32,
+          'double': np.float64}
+
 
 class profile(object):
 
@@ -50,7 +98,7 @@ def _rd_prof(self):
 
         # data is the dictionary with data structure as in ocn_obs.f
         data = {}
-
+        data['dateTime'] = []
         data['n_obs'], data['n_lvl'], data['n_vrsn'] = fh.read_ints('>i4')
 
         print('    number profiles: %d' % data['n_obs'])
@@ -62,8 +110,8 @@ def _rd_prof(self):
             return
 
         data['ob_btm'] = fh.read_reals('>f4')
-        data['ob_lat'] = fh.read_reals('>f4')
-        data['ob_lon'] = fh.read_reals('>f4')
+        data['latitude'] = fh.read_reals('>f4')
+        data['longitude'] = fh.read_reals('>f4')
         data['ob_ls'] = fh.read_reals('>i4')
         data['ob_lt'] = fh.read_reals('>i4')
         data['ob_ssh'] = fh.read_reals('>f4')
@@ -73,7 +121,7 @@ def _rd_prof(self):
         data['ob_tmp_typ'] = fh.read_reals('>i4')
         data['ob_tmp_qc'] = fh.read_reals('>f4')
 
-        data['ob_lvl'] = []
+        data['depthBelowWaterSurface'] = []
         data['ob_sal'] = []
         data['ob_sal_err'] = []
         data['ob_sal_prb'] = []
@@ -82,7 +130,7 @@ def _rd_prof(self):
         data['ob_tmp_prb'] = []
 
         for n in range(data['n_obs']):
-            data['ob_lvl'].append(fh.read_reals('>f4'))
+            data['depthBelowWaterSurface'].append(fh.read_reals('>f4'))
             data['ob_sal'].append(fh.read_reals('>f4'))
             data['ob_sal_err'].append(fh.read_reals('>f4'))
             data['ob_sal_prb'].append(fh.read_reals('>f4'))
@@ -144,6 +192,15 @@ def _rd_prof(self):
 
         fh.close()
 
+        # Transfer timestamp into seconds since epoch and convert Celcius to Kelvin
+        for n in range(data['n_obs']):
+            dtg = datetime.strptime(data['ob_dtg'][n], '%Y%m%d%H%M')
+            time_offset = np.int64(round((dtg - epoch).total_seconds()))
+            data['dateTime'].append(time_offset)
+
+            for k, depth in enumerate(data['depthBelowWaterSurface'][n]):
+                data['ob_tmp'][n][k] = data['ob_tmp'][n][k] + 273.15
+
         self.data = data
 
         return
@@ -151,7 +208,7 @@ def _rd_prof(self):
 
 class IODA(object):
 
-    def __init__(self, filename, date, varDict, varDims, obsList):
+    def __init__(self, files_input, filename, date, obsList):
         '''
         Initialize IODA writer class,
         transform to IODA data structure and,
@@ -160,71 +217,103 @@ def __init__(self, filename, date, varDict, varDims, obsList):
 
         self.filename = filename
         self.date = date
-        self.varDict = varDict
-
-        self.locKeyList = [
-            ("latitude", "float"),
-            ("longitude", "float"),
-            ("depth", "float"),
-            ("datetime", "string")
-        ]
 
-        self.GlobalAttrs = {
+        GlobalAttrs = {
             'odb_version': 1,
+            'converter': os.path.basename(__file__),
+            'ioda_version': 2,
+            'sourceFiles': ", ".join(files_input),
+            'datetimeReference': self.date.strftime('%Y-%m-%dT%H:%M:%S%z'),
+            'description': "GODAE Profile Observations of salinity and temperature"
         }
 
-        self.keyDict = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
-        self.varAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
-        for key in self.varDict.keys():
-            value = self.varDict[key][0]
-            units = self.varDict[key][1]
-            self.keyDict[key]['valKey'] = value, iconv.OvalName()
-            self.keyDict[key]['errKey'] = value, iconv.OerrName()
-            self.keyDict[key]['qcKey'] = value, iconv.OqcName()
-            self.varAttrs[value, iconv.OvalName()]['_FillValue'] = -999.
-            self.varAttrs[value, iconv.OerrName()]['_FillValue'] = -999.
-            self.varAttrs[value, iconv.OqcName()]['_FillValue'] = -999
-            self.varAttrs[value, iconv.OvalName()]['units'] = units
-            self.varAttrs[value, iconv.OerrName()]['units'] = units
-            self.varAttrs[value, iconv.OqcName()]['units'] = "unitless"
+        varAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
+
+        # Set units of the MetaData variables and all _FillValues.
+        for key in meta_keys:
+            dtypestr = locationKeyList[meta_keys.index(key)][1]
+            if locationKeyList[meta_keys.index(key)][2]:
+                varAttrs[(key, metaDataName)]['units'] = locationKeyList[meta_keys.index(key)][2]
+            varAttrs[(key, metaDataName)]['_FillValue'] = missing_vals[dtypestr]
+
+        # Set units and FillValue attributes for groups associated with observed variable.
+        for key in varDict.keys():
+            value = varDict[key][0]
+            units = varDict[key][1]
+            varAttrs[(value, obsValName)]['units'] = units
+            varAttrs[(value, obsErrName)]['units'] = units
+            varAttrs[(value, obsValName)]['_FillValue'] = float_missing_value
+            varAttrs[(value, obsErrName)]['_FillValue'] = float_missing_value
+            varAttrs[(value, qcName)]['_FillValue'] = int_missing_value
 
         # data is the dictionary containing IODA friendly data structure
-        self.data = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
+        data = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
 
+        nprofs = 0
+        nlocs = 0
         for obs in obsList:
 
-            if obs.data['n_obs'] <= 0:
-                print('No profile observations for IODA!')
+            nprofs = obs.data['n_obs']
+            if nprofs <= 0:
+                print('No observations for IODA!')
                 continue
 
-            for n in range(obs.data['n_obs']):
-
-                lat = obs.data['ob_lat'][n]
-                lon = obs.data['ob_lon'][n]
-                dtg = datetime.strptime(obs.data['ob_dtg'][n], '%Y%m%d%H%M')
-
-                for ilev, lvl in enumerate(obs.data['ob_lvl'][n]):
-
-                    locKey = lat, lon, lvl, dtg.strftime("%Y-%m-%dT%H:%M:%SZ")
-
-                    for key in self.varDict.keys():
-                        val = obs.data[key][n][ilev]
-                        err = obs.data[key+'_err'][n][ilev]
-                        qc = (100 * obs.data[key+'_qc'][n]).astype('i4')
-                        if obs.data[key+'_prb'][n][ilev] >= 1.000:
-                            val = -999.00
-                        valKey = self.keyDict[key]['valKey']
-                        errKey = self.keyDict[key]['errKey']
-                        qcKey = self.keyDict[key]['qcKey']
-                        self.data[locKey][valKey] = val
-                        self.data[locKey][errKey] = err
-                        self.data[locKey][qcKey] = qc
-
-        ObsVars, nlocs = iconv.ExtractObsData(self.data, self.locKeyList)
-        DimDict = {'nlocs': nlocs}
-        self.writer = iconv.IodaWriter(self.filename, self.locKeyList, DimDict)
-        self.varAttrs['depth', 'MetaData']['units'] = "m"
-        self.writer.BuildIoda(ObsVars, varDims, self.varAttrs, self.GlobalAttrs)
+            for n in range(nprofs):
+                for k, depth in enumerate(obs.data['depthBelowWaterSurface'][n]):
+                    nlocs += 1
+                    # Transfer the MetaData info into the IODA final data container.
+                    for key in meta_keys:
+                        dtypestr = locationKeyList[meta_keys.index(key)][1]
+                        if isinstance(obs.data[key][n], list):
+                            val = obs.data[key][n][k]
+                        else:
+                            val = obs.data[key][n]
+                        varVals = np.array(val, dtype=dtypes[dtypestr])
+                        # If on the first time through, set the data dict entry
+                        # to a numpy array with a specified data type. Otherwise, append
+                        # the incoming data to the current data.
+                        if (key, metaDataName) in data:
+                            data[(key, metaDataName)] = np.append(
+                                data[(key, metaDataName)], varVals)
+                        else:
+                            data[(key, metaDataName)] = varVals
+
+                    # Fill up the final array of observed values, obsErrors, and Qc
+                    for key in varDict.keys():
+                        value = varDict[key][0]
+                        varErr = key + '_err'
+                        varQc = key + '_qc'
+
+                        # ObsValue
+                        varVals = np.array(obs.data[key][n][k], dtype=dtypes['float'])
+                        if (value, obsValName) in data:
+                            data[(value, obsValName)] = np.append(
+                                data[(value, obsValName)], varVals)
+                        else:
+                            data[(value, obsValName)] = varVals
+
+                        # ObsError
+                        varVals = np.array(obs.data[varErr][n][k], dtype=dtypes['float'])
+                        if (value, obsErrName) in data:
+                            data[(value, obsErrName)] = np.append(
+                                data[(value, obsErrName)], varVals)
+                        else:
+                            data[(value, obsErrName)] = varVals
+
+                        # QC
+                        varVals = np.array(obs.data[varQc][n]*100, dtype=dtypes['integer'])
+                        if (value, qcName) in data:
+                            data[(value, qcName)] = np.append(
+                                data[(value, qcName)], varVals)
+                        else:
+                            data[(value, qcName)] = varVals
+
+        print(f"Found a total number of observations: {nlocs}")
+
+        # Initialize the writer, then write the file.
+        DimDict = {'Location': nlocs}
+        self.writer = iconv.IodaWriter(self.filename, locationKeyList, DimDict)
+        self.writer.BuildIoda(data, varDims, varAttrs, GlobalAttrs)
 
         return
 
@@ -256,18 +345,7 @@ def main():
         obs = profile(fname, fdate)
         obsList.append(obs)
 
-    varDict = {
-        #              var name,             units
-        'ob_tmp': ['sea_water_temperature', 'C'],
-        'ob_sal': ['sea_water_salinity', 'PSU']
-    }
-
-    varDims = {
-        'sea_water_temperature': ['nlocs'],
-        'sea_water_salinity': ['nlocs'],
-    }
-
-    IODA(foutput, fdate, varDict, varDims, obsList)
+    IODA(fList, foutput, fdate, obsList)
 
 
 if __name__ == '__main__':
diff --git a/src/marine/godae_ship2ioda.py b/src/marine/godae_ship2ioda.py
index 096839ccf..64f47e51e 100755
--- a/src/marine/godae_ship2ioda.py
+++ b/src/marine/godae_ship2ioda.py
@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 
 #
-# (C) Copyright 2019-2021 UCAR
+# (C) Copyright 2019-2022 UCAR
 #
 # This software is licensed under the terms of the Apache Licence Version 2.0
 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
@@ -9,7 +9,9 @@
 
 from __future__ import print_function
 import sys
+import os
 import numpy as np
+import netCDF4 as nc
 from datetime import datetime
 from scipy.io import FortranFile
 from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
@@ -23,6 +25,43 @@
 import ioda_conv_engines as iconv
 from orddicts import DefaultOrderedDict
 
+os.environ["TZ"] = "UTC"
+
+varInfo = ['seaSurfaceTemperature', 'K', -999.]
+varDims = {'seaSurfaceTemperature': ['Location']}
+
+locationKeyList = [
+    ("latitude", "float", "degrees_north"),
+    ("longitude", "float", "degrees_east"),
+    ("dateTime", "long", "seconds since 1970-01-01T00:00:00Z")
+]
+meta_keys = [m_item[0] for m_item in locationKeyList]
+
+iso8601_string = locationKeyList[meta_keys.index('dateTime')][2]
+epoch = datetime.fromisoformat(iso8601_string[14:-1])
+
+metaDataName = iconv.MetaDataName()
+obsValName = iconv.OvalName()
+obsErrName = iconv.OerrName()
+qcName = iconv.OqcName()
+
+float_missing_value = -999.
+int_missing_value = -99900
+double_missing_value = nc.default_fillvals['f8']
+long_missing_value = nc.default_fillvals['i8']
+string_missing_value = '_'
+
+missing_vals = {'string': string_missing_value,
+                'integer': int_missing_value,
+                'long': long_missing_value,
+                'float': float_missing_value,
+                'double': double_missing_value}
+dtypes = {'string': object,
+          'integer': np.int32,
+          'long': np.int64,
+          'float': np.float32,
+          'double': np.float64}
+
 
 class ship(object):
 
@@ -51,7 +90,7 @@ def _rd_ship(self):
 
         # data is the dictionary with data structure as in ocn_obs.f
         data = {}
-
+        data['dateTime'] = []
         data['n_obs'], data['n_lvl'], data['n_vrsn'] = fh.read_ints('>i4')
 
         print('    number ship obs: %d' % data['n_obs'])
@@ -64,8 +103,8 @@ def _rd_ship(self):
 
         data['ob_wm'] = fh.read_reals('>i4')
         data['ob_glb'] = fh.read_reals('>f4')
-        data['ob_lat'] = fh.read_reals('>f4')
-        data['ob_lon'] = fh.read_reals('>f4')
+        data['latitude'] = fh.read_reals('>f4')
+        data['longitude'] = fh.read_reals('>f4')
         data['ob_age'] = fh.read_reals('>f4')
         data['ob_clm'] = fh.read_reals('>f4')
         data['ob_qc'] = fh.read_reals('>f4')
@@ -94,6 +133,13 @@ def _rd_ship(self):
 
         fh.close()
 
+        # Transfer timestamp into seconds since epoch and convert Celcius to Kelvin
+        for n in range(data['n_obs']):
+            dtg = datetime.strptime(data['ob_dtg'][n], '%Y%m%d%H%M')
+            time_offset = np.int64(round((dtg - epoch).total_seconds()))
+            data['dateTime'].append(time_offset)
+            data['ob_sst'][n] = data['ob_sst'][n] + 273.15
+
         self.data = data
 
         return
@@ -101,7 +147,7 @@ def _rd_ship(self):
 
 class IODA(object):
 
-    def __init__(self, filename, date, varDict, varDims, obsList):
+    def __init__(self, files_input, filename, date, obsList):
         '''
         Initialize IODA writer class,
         transform to IODA data structure and,
@@ -110,71 +156,52 @@ def __init__(self, filename, date, varDict, varDims, obsList):
 
         self.filename = filename
         self.date = date
-        self.varDict = varDict
-
-        self.locKeyList = [
-            ("latitude", "float"),
-            ("longitude", "float"),
-            ("datetime", "string")
-        ]
 
         self.GlobalAttrs = {
+            'converter': os.path.basename(__file__),
+            'ioda_version': 2,
+            'sourceFiles': ", ".join(files_input),
+            'datetimeReference': self.date.strftime('%Y-%m-%dT%H:%M:%S%z'),
+            'description': "GODAE Ship Observations of sea surface temperature"
         }
 
-        self.keyDict = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
         self.varAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
-        for key in self.varDict.keys():
-            value = self.varDict[key]
-            self.keyDict[key]['valKey'] = value, iconv.OvalName()
-            self.keyDict[key]['errKey'] = value, iconv.OerrName()
-            self.keyDict[key]['qcKey'] = value, iconv.OqcName()
-            # TO DO the missing value should be the one defined in class ship
-            # instead of being hardcoded here
-            self.varAttrs[value, iconv.OvalName()]['_FillValue'] = -999.
-            self.varAttrs[value, iconv.OerrName()]['_FillValue'] = -999.
-            self.varAttrs[value, iconv.OqcName()]['_FillValue'] = -999
-            self.varAttrs[value, iconv.OvalName()]['units'] = 'degree_C'
-            self.varAttrs[value, iconv.OerrName()]['units'] = 'degree_C'
-            self.varAttrs[value, iconv.OqcName()]['units'] = 'unitless'
+
+        # Set units and FillValue attributes for groups associated with observed variable.
+        self.varAttrs[(varInfo[0], obsValName)]['units'] = varInfo[1]
+        self.varAttrs[(varInfo[0], obsErrName)]['units'] = varInfo[1]
+        self.varAttrs[(varInfo[0], obsValName)]['_FillValue'] = varInfo[2]
+        self.varAttrs[(varInfo[0], obsErrName)]['_FillValue'] = varInfo[2]
+        self.varAttrs[(varInfo[0], qcName)]['_FillValue'] = int_missing_value
 
         # data is the dictionary containing IODA friendly data structure
         self.data = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
 
+        nobs = 0
         for obs in obsList:
 
-            if obs.data['n_obs'] <= 0:
-                print('No ship observations for IODA!')
+            nobs += obs.data['n_obs']
+            if nobs <= 0:
+                print('No observations for IODA!')
                 continue
 
-            for n in range(obs.data['n_obs']):
-
-                lat = obs.data['ob_lat'][n]
-                lon = obs.data['ob_lon'][n]
-                dtg = datetime.strptime(obs.data['ob_dtg'][n], '%Y%m%d%H%M')
-
-                locKey = lat, lon, dtg.strftime("%Y-%m-%dT%H:%M:%SZ")
-
-                for key in self.varDict.keys():
+            # Set units of the MetaData variables and all _FillValues.
+            for key in meta_keys:
+                dtypestr = locationKeyList[meta_keys.index(key)][1]
+                if locationKeyList[meta_keys.index(key)][2]:
+                    self.varAttrs[(key, metaDataName)]['units'] = locationKeyList[meta_keys.index(key)][2]
+                self.varAttrs[(key, metaDataName)]['_FillValue'] = missing_vals[dtypestr]
+                self.data[(key, metaDataName)] = np.array(obs.data[key], dtype=dtypes[dtypestr])
 
-                    val = obs.data[key][n]
-                    err = 0.5
-                    qc = (100*obs.data['ob_qc'][n]).astype('i4')
+            # Fill up the final array of observed values, obsErrors, and Qc
+            self.data[(varInfo[0], obsValName)] = np.array(obs.data['ob_sst'], dtype=np.float32)
+            self.data[(varInfo[0], obsErrName)] = np.full(nobs, 0.5, dtype=np.float32)
+            self.data[(varInfo[0], qcName)] = np.array(obs.data['ob_qc']*100, dtype=np.int32)
 
-                    valKey = self.keyDict[key]['valKey']
-                    errKey = self.keyDict[key]['errKey']
-                    qcKey = self.keyDict[key]['qcKey']
-
-                    self.data[locKey][valKey] = val
-                    self.data[locKey][errKey] = err
-                    self.data[locKey][qcKey] = qc
-        # Extract obs
-        ObsVars, nlocs = iconv.ExtractObsData(self.data, self.locKeyList)
-        DimDict = {'nlocs': nlocs}
-
-        # Set up IODA writer
-        self.writer = iconv.IodaWriter(self.filename, self.locKeyList, DimDict)
-        # Write out observations
-        self.writer.BuildIoda(ObsVars, varDims, self.varAttrs, self.GlobalAttrs)
+        # Initialize the writer, then write the file.
+        DimDict = {'Location': nobs}
+        self.writer = iconv.IodaWriter(self.filename, locationKeyList, DimDict)
+        self.writer.BuildIoda(self.data, varDims, self.varAttrs, self.GlobalAttrs)
 
         return
 
@@ -204,15 +231,7 @@ def main():
     for fname in fList:
         obsList.append(ship(fname, fdate))
 
-    varDict = {
-        'ob_sst': 'sea_surface_temperature',
-    }
-
-    varDims = {
-        'sea_surface_temperature': ['nlocs'],
-    }
-
-    IODA(foutput, fdate, varDict, varDims, obsList)
+    IODA(fList, foutput, fdate, obsList)
 
 
 if __name__ == '__main__':
diff --git a/src/marine/godae_trak2ioda.py b/src/marine/godae_trak2ioda.py
index d8a67628b..d5cc18ffd 100755
--- a/src/marine/godae_trak2ioda.py
+++ b/src/marine/godae_trak2ioda.py
@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 
 #
-# (C) Copyright 2019-2021 UCAR
+# (C) Copyright 2019-2022 UCAR
 #
 # This software is licensed under the terms of the Apache Licence Version 2.0
 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
@@ -9,7 +9,9 @@
 
 from __future__ import print_function
 import sys
+import os
 import numpy as np
+import netCDF4 as nc
 from datetime import datetime
 from scipy.io import FortranFile
 from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
@@ -23,13 +25,61 @@
 import ioda_conv_engines as iconv
 from orddicts import DefaultOrderedDict
 
+os.environ["TZ"] = "UTC"
+
+varDict = {
+    'ob_sst': 'seaSurfaceTemperature',
+    'ob_sal': 'seaSurfaceSalinity',
+    'ob_uuu': 'seaSurfaceZonalWind',
+    'ob_vvv': 'seaSurfaceMeridionalWind'
+}
+
+varDims = {
+    'seaSurfaceTemperature': ['Location'],
+    'seaSurfaceSalinity': ['Location'],
+    'seaSurfaceZonalWind': ['Location'],
+    'seaSurfaceMeridionalWind': ['Location']
+}
+
 unitDict = {
-    'ob_sst': 'degree_C',
-    'ob_sal': 'PSU',
-    'ob_uuu': 'm/s',
-    'ob_vvv': 'm/s'
+    'ob_sst': 'K',
+    'ob_sal': '1',
+    'ob_uuu': 'm s-1',
+    'ob_vvv': 'm s-1'
 }
 
+locationKeyList = [
+    ("latitude", "float", "degrees_north"),
+    ("longitude", "float", "degrees_east"),
+    ("dateTime", "long", "seconds since 1970-01-01T00:00:00Z")
+]
+meta_keys = [m_item[0] for m_item in locationKeyList]
+
+iso8601_string = locationKeyList[meta_keys.index('dateTime')][2]
+epoch = datetime.fromisoformat(iso8601_string[14:-1])
+
+metaDataName = iconv.MetaDataName()
+obsValName = iconv.OvalName()
+obsErrName = iconv.OerrName()
+qcName = iconv.OqcName()
+
+float_missing_value = -999.
+int_missing_value = -99900
+double_missing_value = nc.default_fillvals['f8']
+long_missing_value = nc.default_fillvals['i8']
+string_missing_value = '_'
+
+missing_vals = {'string': string_missing_value,
+                'integer': int_missing_value,
+                'long': long_missing_value,
+                'float': float_missing_value,
+                'double': double_missing_value}
+dtypes = {'string': object,
+          'integer': np.int32,
+          'long': np.int64,
+          'float': np.float32,
+          'double': np.float64}
+
 
 class trak(object):
 
@@ -58,7 +108,7 @@ def _rd_trak(self):
 
         # data is the dictionary with data structure as in ocn_obs.f
         data = {}
-
+        data['dateTime'] = []
         data['n_obs'], data['n_lvl'], data['n_vrsn'] = fh.read_ints('>i4')
 
         print('    number trak obs: %d' % data['n_obs'])
@@ -72,8 +122,8 @@ def _rd_trak(self):
         data['ob_wm'] = fh.read_reals('>i4')
         data['ob_gsal'] = fh.read_reals('>f4')
         data['ob_gsst'] = fh.read_reals('>f4')
-        data['ob_lat'] = fh.read_reals('>f4')
-        data['ob_lon'] = fh.read_reals('>f4')
+        data['latitude'] = fh.read_reals('>f4')
+        data['longitude'] = fh.read_reals('>f4')
         data['ob_age'] = fh.read_reals('>f4')
         data['ob_csal'] = fh.read_reals('>f4')
         data['ob_csst'] = fh.read_reals('>f4')
@@ -97,6 +147,13 @@ def _rd_trak(self):
 
         fh.close()
 
+        # Transfer timestamp into seconds since epoch and convert Celcius to Kelvin
+        for n in range(data['n_obs']):
+            dtg = datetime.strptime(data['ob_dtg'][n], '%Y%m%d%H%M')
+            time_offset = np.int64(round((dtg - epoch).total_seconds()))
+            data['dateTime'].append(time_offset)
+            data['ob_sst'][n] = data['ob_sst'][n] + 273.15
+
         self.data = data
 
         return
@@ -104,7 +161,7 @@ def _rd_trak(self):
 
 class IODA(object):
 
-    def __init__(self, filename, date, varDict, varDims, obsList):
+    def __init__(self, files_input, filename, date, obsList):
         '''
         Initialize IODA writer class,
         transform to IODA data structure and,
@@ -113,75 +170,61 @@ def __init__(self, filename, date, varDict, varDims, obsList):
 
         self.filename = filename
         self.date = date
-        self.varDict = varDict
-
-        self.locKeyList = [
-            ("latitude", "float"),
-            ("longitude", "float"),
-            ("datetime", "string")
-        ]
 
         self.GlobalAttrs = {
+            'converter': os.path.basename(__file__),
+            'ioda_version': 2,
+            'sourceFiles': ", ".join(files_input),
+            'datetimeReference': self.date.strftime('%Y-%m-%dT%H:%M:%S%z'),
+            'description': "GODAE Ship Observations of sea surface temperature"
         }
 
-        self.keyDict = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
         self.varAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
-        for key in self.varDict.keys():
-            value = self.varDict[key]
-            self.keyDict[key]['valKey'] = value, iconv.OvalName()
-            self.keyDict[key]['errKey'] = value, iconv.OerrName()
-            self.keyDict[key]['qcKey'] = value, iconv.OqcName()
-            self.varAttrs[value, iconv.OvalName()]['_FillValue'] = -999.
-            self.varAttrs[value, iconv.OerrName()]['_FillValue'] = -999.
-            self.varAttrs[value, iconv.OqcName()]['_FillValue'] = -999
-            self.varAttrs[value, iconv.OvalName()]['units'] = unitDict[key]
-            self.varAttrs[value, iconv.OerrName()]['units'] = unitDict[key]
-            self.varAttrs[value, iconv.OqcName()]['units'] = 'unitless'
+
+        # Set units and FillValue attributes for groups associated with observed variable.
+        for key in varDict.keys():
+            value = varDict[key]
+            self.varAttrs[(value, obsValName)]['units'] = unitDict[key]
+            self.varAttrs[(value, obsErrName)]['units'] = unitDict[key]
+            self.varAttrs[(value, obsValName)]['_FillValue'] = float_missing_value
+            self.varAttrs[(value, obsErrName)]['_FillValue'] = float_missing_value
+            self.varAttrs[(value, qcName)]['_FillValue'] = int_missing_value
 
         # data is the dictionary containing IODA friendly data structure
         self.data = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
 
+        nobs = 0
         for obs in obsList:
 
-            if obs.data['n_obs'] <= 0:
-                print('No trak observations for IODA!')
+            nobs += obs.data['n_obs']
+            if nobs <= 0:
+                print('No observations for IODA!')
                 continue
 
-            for n in range(obs.data['n_obs']):
-
-                lat = obs.data['ob_lat'][n]
-                lon = obs.data['ob_lon'][n]
-                dtg = datetime.strptime(obs.data['ob_dtg'][n], '%Y%m%d%H%M')
-
-                locKey = lat, lon, dtg.strftime("%Y-%m-%dT%H:%M:%SZ")
-
-                for key in self.varDict.keys():
-
-                    if key in ['ob_uuu', 'ob_vvv']:
-                        varName = 'vel'
-                    else:
-                        varName = key.split('_')[-1]
-
-                    val = obs.data[key][n]
-                    err = 1.0
-                    qc = (100*obs.data['ob_qc_'+varName][n]).astype('i4')
-
-                    valKey = self.keyDict[key]['valKey']
-                    errKey = self.keyDict[key]['errKey']
-                    qcKey = self.keyDict[key]['qcKey']
-
-                    self.data[locKey][valKey] = val
-                    self.data[locKey][errKey] = err
-                    self.data[locKey][qcKey] = qc
-        # Extract obs
-        ObsVars, nlocs = iconv.ExtractObsData(self.data, self.locKeyList)
-        DimDict = {'nlocs': nlocs}
-
-        # Set up IODA writer
-        self.writer = iconv.IodaWriter(self.filename, self.locKeyList, DimDict)
-
-        # Write out observations
-        self.writer.BuildIoda(ObsVars, varDims, self.varAttrs, self.GlobalAttrs)
+            # Set units of the MetaData variables and all _FillValues.
+            for key in meta_keys:
+                dtypestr = locationKeyList[meta_keys.index(key)][1]
+                if locationKeyList[meta_keys.index(key)][2]:
+                    self.varAttrs[(key, metaDataName)]['units'] = locationKeyList[meta_keys.index(key)][2]
+                self.varAttrs[(key, metaDataName)]['_FillValue'] = missing_vals[dtypestr]
+                self.data[(key, metaDataName)] = np.array(obs.data[key], dtype=dtypes[dtypestr])
+
+            # Fill up the final array of observed values, obsErrors, and Qc
+            for key in varDict.keys():
+                value = varDict[key]
+                if key in ['ob_uuu', 'ob_vvv']:
+                    varQc = 'ob_qc_vel'
+                else:
+                    varQc = 'ob_' + key.split('_')[-1]
+
+                self.data[(value, obsValName)] = np.array(obs.data[key], dtype=np.float32)
+                self.data[(value, obsErrName)] = np.full(nobs, 1.0, dtype=np.float32)
+                self.data[(value, qcName)] = np.array(obs.data[varQc]*100, dtype=np.int32)
+
+        # Initialize the writer, then write the file.
+        DimDict = {'Location': nobs}
+        self.writer = iconv.IodaWriter(self.filename, locationKeyList, DimDict)
+        self.writer.BuildIoda(self.data, varDims, self.varAttrs, self.GlobalAttrs)
 
         return
 
@@ -212,21 +255,7 @@ def main():
     for fname in fList:
         obsList.append(trak(fname, fdate))
 
-    varDict = {
-        'ob_sst': 'sea_surface_temperature',
-        'ob_sal': 'sea_surface_salinity',
-        'ob_uuu': 'sea_surface_zonal_wind',
-        'ob_vvv': 'sea_surface_meriodional_wind'
-    }
-
-    varDims = {
-        'sea_surface_temperature': ['nlocs'],
-        'sea_surface_salinity': ['nlocs'],
-        'sea_surface_zonal_wind': ['nlocs'],
-        'sea_surface_meriodional_wind': ['nlocs']
-    }
-
-    IODA(foutput, fdate, varDict, varDims, obsList)
+    IODA(fList, foutput, fdate, obsList)
 
 
 if __name__ == '__main__':
diff --git a/src/marine/hgodas_adt2ioda.py b/src/marine/hgodas_adt2ioda.py
index 2d5d59c86..de6d86973 100755
--- a/src/marine/hgodas_adt2ioda.py
+++ b/src/marine/hgodas_adt2ioda.py
@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 
 #
-# (C) Copyright 2019 UCAR
+# (C) Copyright 2019-2022 UCAR
 #
 # This software is licensed under the terms of the Apache Licence Version 2.0
 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
@@ -9,8 +9,10 @@
 
 from __future__ import print_function
 import sys
+import os
 import argparse
 import netCDF4 as nc
+import numpy as np
 from datetime import datetime, timedelta
 from pathlib import Path
 
@@ -22,24 +24,41 @@
 import ioda_conv_engines as iconv
 from orddicts import DefaultOrderedDict
 
+os.environ["TZ"] = "UTC"
 
-vName = "absolute_dynamic_topography"
+varInfo = ['absoluteDynamicTopography', 'm']
 
 locationKeyList = [
-    ("latitude", "float"),
-    ("longitude", "float"),
-    ("datetime", "string")
+    ("latitude", "float", "degrees_north"),
+    ("longitude", "float", "degrees_east"),
+    ("dateTime", "long", "seconds since 1970-01-01T00:00:00Z")
 ]
-
-GlobalAttrs = {
-}
-
-VarDims = {
-    vName: ['nlocs'],
-}
-
-DimDict = {
-}
+meta_keys = [m_item[0] for m_item in locationKeyList]
+
+iso8601_string = locationKeyList[meta_keys.index('dateTime')][2]
+epoch = datetime.fromisoformat(iso8601_string[14:-1])
+
+metaDataName = iconv.MetaDataName()
+obsValName = iconv.OvalName()
+obsErrName = iconv.OerrName()
+qcName = iconv.OqcName()
+
+float_missing_value = -999.
+int_missing_value = -999
+double_missing_value = nc.default_fillvals['f8']
+long_missing_value = nc.default_fillvals['i8']
+string_missing_value = '_'
+
+missing_vals = {'string': string_missing_value,
+                'integer': int_missing_value,
+                'long': long_missing_value,
+                'float': float_missing_value,
+                'double': double_missing_value}
+dtypes = {'string': object,
+          'integer': np.int32,
+          'long': np.int64,
+          'float': np.float32,
+          'double': np.float64}
 
 
 class Observation(object):
@@ -47,32 +66,27 @@ class Observation(object):
     def __init__(self, filename, date):
         self.filename = filename
         self.date = date
-        self.data = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
-        self.VarAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
         self._read()
 
     def _read(self):
+
+        data = {}
+        data['dateTime'] = []
+        data['vals'] = []
+        data['errs'] = []
+        data['qcs'] = []
+
         ncd = nc.Dataset(self.filename)
+        data['longitude'] = ncd.variables['lon'][:]
+        data['latitude'] = ncd.variables['lat'][:]
         time = ncd.variables['time'][:]
-        lons = ncd.variables['lon'][:]
-        lats = ncd.variables['lat'][:]
         hrs = ncd.variables['hr'][:]
         vals = ncd.variables['val'][:]
         errs = ncd.variables['err'][:]
         qcs = ncd.variables['qc'][:]
         ncd.close()
 
-        base_date = datetime(1970, 1, 1) + timedelta(seconds=int(time[0]))
-
-        valKey = vName, iconv.OvalName()
-        errKey = vName, iconv.OerrName()
-        qcKey = vName, iconv.OqcName()
-        self.VarAttrs[vName, iconv.OvalName()]['_FillValue'] = -999.
-        self.VarAttrs[vName, iconv.OerrName()]['_FillValue'] = -999.
-        self.VarAttrs[vName, iconv.OqcName()]['_FillValue'] = -999
-        self.VarAttrs[vName, iconv.OvalName()]['units'] = 'm'
-        self.VarAttrs[vName, iconv.OerrName()]['units'] = 'm'
-        self.VarAttrs[vName, iconv.OqcName()]['units'] = 'unitless'
+        base_date = epoch + timedelta(seconds=int(time[0]))
 
         for i in range(len(hrs)):
             # there shouldn't be any bad obs, but just in case remove them all
@@ -80,10 +94,70 @@ def _read(self):
                 continue
 
             dt = base_date + timedelta(hours=float(hrs[i]))
-            locKey = lats[i], lons[i], dt.strftime("%Y-%m-%dT%H:%M:%SZ")
-            self.data[locKey][valKey] = vals[i]
-            self.data[locKey][errKey] = errs[i]
-            self.data[locKey][qcKey] = qcs[i]
+            time_offset = np.int64(round((dt - epoch).total_seconds()))
+            data['dateTime'].append(time_offset)
+            data['vals'].append(vals[i])
+            data['errs'].append(errs[i])
+            data['qcs'].append(np.int32(qcs[i]))
+
+        self.data = data
+
+
+class IODA(object):
+
+    def __init__(self, file_input, filename, date, obs):
+
+        self.file_input = file_input
+        self.filename = filename
+        self.date = date
+
+        self.GlobalAttrs = {
+            'converter': os.path.basename(__file__),
+            'ioda_version': 2,
+            'sourceFiles': self.file_input,
+            'datetimeReference': self.date.strftime('%Y-%m-%dT%H:%M:%S%z'),
+            'description': "Absolute Dynamic Topography (ADT) observations"
+                           " used in Hybrid-GODAS"
+        }
+
+        self.varAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
+
+        # Set units and FillValue attributes for groups associated with observed variable.
+        self.varAttrs[(varInfo[0], obsValName)]['units'] = varInfo[1]
+        self.varAttrs[(varInfo[0], obsErrName)]['units'] = varInfo[1]
+        self.varAttrs[(varInfo[0], obsValName)]['_FillValue'] = float_missing_value
+        self.varAttrs[(varInfo[0], obsErrName)]['_FillValue'] = float_missing_value
+        self.varAttrs[(varInfo[0], qcName)]['_FillValue'] = int_missing_value
+
+        # Set units of the MetaData variables and all _FillValues.
+        for key in meta_keys:
+            dtypestr = locationKeyList[meta_keys.index(key)][1]
+            if locationKeyList[meta_keys.index(key)][2]:
+                self.varAttrs[(key, metaDataName)]['units'] = locationKeyList[meta_keys.index(key)][2]
+            self.varAttrs[(key, metaDataName)]['_FillValue'] = missing_vals[dtypestr]
+
+        # data is the dictionary containing IODA friendly data structure
+        self.data = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
+
+        for key in meta_keys:
+            dtypestr = locationKeyList[meta_keys.index(key)][1]
+            self.data[(key, metaDataName)] = np.array(obs.data[key], dtype=dtypes[dtypestr])
+
+        # Fill up the final array of observed values, obsErrors, and Qc
+        self.data[(varInfo[0], obsValName)] = np.array(obs.data['vals'], dtype=np.float32)
+        self.data[(varInfo[0], obsErrName)] = np.array(obs.data['errs'], dtype=np.float32)
+        self.data[(varInfo[0], qcName)] = np.array(obs.data['qcs'], dtype=np.int32)
+
+        nlocs = len(obs.data['vals'])
+        DimDict = {'Location': nlocs}
+        varDims = {varInfo[0]: ['Location']}
+
+        # Initialize the writer, then write the file.
+        print(f"Writing the output file: {self.filename} with {nlocs} observations in it.")
+        self.writer = iconv.IodaWriter(self.filename, locationKeyList, DimDict)
+        self.writer.BuildIoda(self.data, varDims, self.varAttrs, self.GlobalAttrs)
+
+        return
 
 
 def main():
@@ -113,17 +187,8 @@ def main():
     # Read in the adt
     adt = Observation(args.input, fdate)
 
-    # Extract Obsdata
-    ObsVars, nlocs = iconv.ExtractObsData(adt.data, locationKeyList)
-
-    # Set attributes
-    DimDict['nlocs'] = nlocs
-
-    # Set up the IODA writer
-    writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
-
-    # write them out
-    writer.BuildIoda(ObsVars, VarDims, adt.VarAttrs, GlobalAttrs)
+    # Write out the IODA output file.
+    IODA(args.input, args.output, fdate, adt)
 
 
 if __name__ == '__main__':
diff --git a/src/marine/hgodas_insitu2ioda.py b/src/marine/hgodas_insitu2ioda.py
index c6cc7b4b9..759a1b2d2 100755
--- a/src/marine/hgodas_insitu2ioda.py
+++ b/src/marine/hgodas_insitu2ioda.py
@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 
 #
-# (C) Copyright 2019-2021 UCAR
+# (C) Copyright 2019-2022 UCAR
 #
 # This software is licensed under the terms of the Apache Licence Version 2.0
 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
@@ -10,8 +10,9 @@
 from __future__ import print_function
 import sys
 import argparse
+import numpy as np
 import netCDF4 as nc
-from datetime import datetime, timedelta
+from datetime import datetime
 from pathlib import Path
 
 IODA_CONV_PATH = Path(__file__).parent/"@SCRIPT_LIB_PATH@"
@@ -25,15 +26,15 @@
 
 vName = {
     #          var name,            units
-    2210: ["sea_water_temperature", "C"],
-    2220: ["sea_water_salinity", "PSU"]
+    2210: ["waterTemperature", "K"],
+    2220: ["salinity", "1"]
 }
 
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("depth", "float"),
-    ("datetime", "string")
+    ("depthBelowWaterSurface", "float"),
+    ("dateTime", "long")
 ]
 
 GlobalAttrs = {
@@ -50,6 +51,11 @@ def __init__(self, filename, date):
         self.VarAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
         self.floatDefFillVal = iconv.get_default_fill_val('float32')
         self.intDefFillVal = iconv.get_default_fill_val('int32')
+
+        self.VarAttrs['depthBelowWaterSurface', 'MetaData']['units'] = 'm'
+        self.VarAttrs['latitude', 'MetaData']['units'] = 'degrees_north'
+        self.VarAttrs['longitude', 'MetaData']['units'] = 'degrees_east'
+        self.VarAttrs['dateTime', 'MetaData']['units'] = 'seconds since 1970-01-01T00:00:00Z'
         self._read()
 
     def _read(self):
@@ -65,9 +71,7 @@ def _read(self):
         qcs = ncd.variables['qc'][:]
         ncd.close()
 
-        base_date = datetime(1970, 1, 1) + timedelta(seconds=int(time[0]))
-
-        self.VarAttrs['depth', 'MetaData']['units'] = 'm'
+        dt = np.full(len(qcs), 0, dtype=np.int64)
         for i in range(len(hrs)):
             # there shouldn't be any bad obs, but just in case remove them all
             if qcs[i] != 0:
@@ -80,15 +84,16 @@ def _read(self):
             self.VarAttrs[varName, iconv.OqcName()]['_FillValue'] = self.intDefFillVal
             self.VarAttrs[varName, iconv.OvalName()]['units'] = varUnits
             self.VarAttrs[varName, iconv.OerrName()]['units'] = varUnits
-            self.VarAttrs[varName, iconv.OqcName()]['units'] = 'unitless'
 
             valKey = varName, iconv.OvalName()
             errKey = varName, iconv.OerrName()
             qcKey = varName, iconv.OqcName()
 
-            dt = base_date + timedelta(hours=float(hrs[i]))
-            locKey = lats[i], lons[i], dpth[i], dt.strftime(
-                "%Y-%m-%dT%H:%M:%SZ")
+            if obid[i] == 2210:
+                vals[i] = vals[i] + 273.15
+
+            dt[i] = time[0] + hrs[i]*3600
+            locKey = lats[i], lons[i], dpth[i], dt[i]
             self.data[locKey][valKey] = vals[i]
             self.data[locKey][errKey] = errs[i]
             self.data[locKey][qcKey] = qcs[i]
@@ -119,18 +124,17 @@ def main():
     fdate = datetime.strptime(args.date, '%Y%m%d%H')
 
     VarDims = {
-        'sea_water_temperature': ['nlocs'],
-        'sea_water_salinity': ['nlocs'],
+        'watertemperature': ['Location'],
+        'salinity': ['Location'],
     }
 
     # Read in the profiles
     prof = Profile(args.input, fdate)
 
     # write them out
-    GlobalAttrs['date_time_string'] = fdate.strftime("%Y-%m-%dT%H:%M:%SZ")
     ObsVars, nlocs = iconv.ExtractObsData(prof.data, locationKeyList)
 
-    DimDict = {'nlocs': nlocs}
+    DimDict = {'Location': nlocs}
     writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
     writer.BuildIoda(ObsVars, VarDims, prof.VarAttrs, GlobalAttrs)
 
diff --git a/src/marine/hgodas_sst2ioda.py b/src/marine/hgodas_sst2ioda.py
index 8cb3041da..15b050fc4 100755
--- a/src/marine/hgodas_sst2ioda.py
+++ b/src/marine/hgodas_sst2ioda.py
@@ -24,13 +24,13 @@
 
 
 vName = {
-    'T': "sea_surface_temperature",
+    'T': "seaSurfaceTemperature",
 }
 
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string")
+    ("dateTime", "string")
 ]
 
 GlobalAttrs = {}
@@ -70,7 +70,7 @@ def _read(self):
             count += 1
             dt = base_date + timedelta(hours=float(hrs[i]))
             locKey = lats[i], lons[i], dt.strftime("%Y-%m-%dT%H:%M:%SZ")
-            self.data[locKey][valKey] = vals[i]
+            self.data[locKey][valKey] = vals[i] + 273.15
             self.data[locKey][errKey] = errs[i]
             self.data[locKey][qcKey] = qcs[i]
 
@@ -93,25 +93,24 @@ def main():
     fdate = datetime.strptime(args.date, '%Y%m%d%H')
 
     VarDims = {
-        'sea_surface_temperature': ['nlocs'],
+        'seaSurfaceTemperature': ['Location'],
     }
 
     # Read in the profiles
     prof = Profile(args.input, fdate)
 
     # write them out
-    ObsVars, nlocs = iconv.ExtractObsData(prof.data, locationKeyList)
+    ObsVars, Location = iconv.ExtractObsData(prof.data, locationKeyList)
 
-    DimDict = {'nlocs': nlocs}
+    DimDict = {'Location': Location}
     writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
 
     VarAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
-    VarAttrs[('sea_surface_temperature', 'ObsValue')]['units'] = 'Celsius'
-    VarAttrs[('sea_surface_temperature', 'ObsError')]['units'] = 'Celsius'
-    VarAttrs[('sea_surface_temperature', 'PreQC')]['units'] = 'unitless'
-    VarAttrs[('sea_surface_temperature', 'ObsValue')]['_FillValue'] = 999
-    VarAttrs[('sea_surface_temperature', 'ObsError')]['_FillValue'] = 999
-    VarAttrs[('sea_surface_temperature', 'PreQC')]['_FillValue'] = 999
+    VarAttrs[('seaSurfaceTemperature', 'ObsValue')]['units'] = 'K'
+    VarAttrs[('seaSurfaceTemperature', 'ObsError')]['units'] = 'K'
+    VarAttrs[('seaSurfaceTemperature', 'ObsValue')]['_FillValue'] = 999
+    VarAttrs[('seaSurfaceTemperature', 'ObsError')]['_FillValue'] = 999
+    VarAttrs[('seaSurfaceTemperature', 'PreQC')]['_FillValue'] = 999
     writer.BuildIoda(ObsVars, VarDims, VarAttrs, GlobalAttrs)
 
 
diff --git a/src/marine/ndbc_hfradar2ioda.py b/src/marine/ndbc_hfradar2ioda.py
index 83539fcd3..29d753672 100644
--- a/src/marine/ndbc_hfradar2ioda.py
+++ b/src/marine/ndbc_hfradar2ioda.py
@@ -22,15 +22,14 @@
 from collections import defaultdict, OrderedDict
 from orddicts import DefaultOrderedDict
 
-vName = ["sea_water_meridional_current",
-         "sea_water_zonal_current",
-         "DOPX",
-         "DOPY"]
+vName = ["waterMeridionalVelocity",
+         "waterZonalVelocity",
+         ]
 
 locKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string")
+    ("dateTime", "long")
 ]
 
 GlobalAttrs = {
@@ -56,9 +55,8 @@ def _read(self):
         vals_v = ncd.variables['v'][:]
         dopx = ncd.variables['dopx'][:]
         dopy = ncd.variables['dopy'][:]
-        units = '1970-01-01 00:00:00'
-        reftime = dateutil.parser.parse(units)
         ncd.close()
+
         lons, lats = np.meshgrid(lons, lats)
         lons = lons.flatten()
         lats = lats.flatten()
@@ -75,8 +73,8 @@ def _read(self):
                 qcKey = vName[j], iconv.OqcName()
                 if vals_u[i] != '--':
                     count += 1
-                    obs_date = reftime + timedelta(seconds=int(time[i]))
-                    locKey = lats[i], lons[i], obs_date.strftime("%Y-%m-%dT%H:%M:%SZ")
+                    obs_date = int(time[i])
+                    locKey = lats[i], lons[i], obs_date
                     if j == 0:
                         self.data[locKey][valKey] = vals_u[i]
                         self.data[locKey][errKey] = 0.1
@@ -117,21 +115,23 @@ def main():
     args = parser.parse_args()
     fdate = datetime.strptime(args.date, '%Y%m%d%H')
     VarDims = {
-        'sea_water_meridional_current': ['nlocs'],
-        'sea_water_zonal_current': ['nlocs']}
+        'waterMeridionalVelocity': ['Location'],
+        'waterZonalVelocity': ['Location']}
     radar = Observation(args.input, fdate)
-    GlobalAttrs['date_time_string'] = fdate.strftime("%Y-%m-%dT%H:%M:%SZ")
 
     ObsVars, nlocs = iconv.ExtractObsData(radar.data, locKeyList)
-    DimDict = {'nlocs': nlocs}
+    DimDict = {'Location': nlocs}
     writer = iconv.IodaWriter(args.output, locKeyList, DimDict)
     VarAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
-    VarAttrs[('sea_water_meridional_current', 'ObsValue')]['units'] = 'm/s'
-    VarAttrs[('sea_water_zonal_current', 'ObsValue')]['units'] = 'm/s'
-    VarAttrs[('sea_water_meridional_current', 'ObsValue')]['_FillValue'] = -32767
-    VarAttrs[('sea_water_zonal_current', 'ObsValue')]['_FillValue'] = -32767
-    VarAttrs[('longitude', 'MetaData')]['units'] = 'degree'
-    VarAttrs[('latitude', 'MetaData')]['units'] = 'degree'
+    VarAttrs[('waterMeridionalVelocity', 'ObsValue')]['units'] = 'm s-1'
+    VarAttrs[('waterMeridionalVelocity', 'ObsError')]['units'] = 'm s-1'
+    VarAttrs[('waterZonalVelocity', 'ObsValue')]['units'] = 'm s-1'
+    VarAttrs[('waterZonalVelocity', 'ObsError')]['units'] = 'm s-1'
+    VarAttrs[('waterMeridionalVelocity', 'ObsValue')]['_FillValue'] = -32767
+    VarAttrs[('waterZonalVelocity', 'ObsValue')]['_FillValue'] = -32767
+    VarAttrs[('longitude', 'MetaData')]['units'] = 'degrees_east'
+    VarAttrs[('latitude', 'MetaData')]['units'] = 'degrees_north'
+    VarAttrs[('dateTime', 'MetaData')]['units'] = 'seconds since 1970-01-01T00:00:00Z'
     writer.BuildIoda(ObsVars, VarDims, VarAttrs, GlobalAttrs)
 
 
diff --git a/src/marine/nsidc_l4cdr_ice2ioda.py b/src/marine/nsidc_l4cdr_ice2ioda.py
index 82ac05c39..9c854fffd 100755
--- a/src/marine/nsidc_l4cdr_ice2ioda.py
+++ b/src/marine/nsidc_l4cdr_ice2ioda.py
@@ -8,7 +8,7 @@
 #
 
 from __future__ import print_function
-import sys
+import os, sys
 import argparse
 import netCDF4 as nc
 from datetime import datetime, timedelta
@@ -24,6 +24,9 @@
 import ioda_conv_engines as iconv
 from orddicts import DefaultOrderedDict
 
+iso8601_string = 'seconds since 1970-01-01T00:00:00Z'
+epoch = datetime.fromisoformat(iso8601_string[14:-1])
+
 
 class Observation(object):
 
@@ -41,6 +44,7 @@ def _read(self):
         datein = ncd.variables['time'][:] + 0.5
         reftime = dateutil.parser.parse(ncd.variables['time'].units[-20:])
         obs_date = reftime + timedelta(days=float(datein))
+        time_offset = round((obs_date - epoch).total_seconds())
 
         data_in = {}
         input_vars = (
@@ -90,7 +94,7 @@ def _read(self):
             qc = qc[mask_thin]
 
         for i in range(len(lons)):
-            locKey = lats[i], lons[i], obs_date.strftime("%Y-%m-%dT%H:%M:%SZ")
+            locKey = lats[i], lons[i], time_offset
             self.data[locKey][valKey] = vals[i]
             self.VarAttrs[locKey][valKey]['_FillValue'] = vals_FillValue
             self.VarAttrs[locKey][valKey]['units'] = vals_units
@@ -100,20 +104,20 @@ def _read(self):
             self.VarAttrs[locKey][errKey]['_FillValue'] = errs_FillValue
             self.VarAttrs[locKey][errKey]['units'] = errs_units
             self.data[locKey][qcKey] = 1
-            self.VarAttrs[locKey][qcKey]['units'] = 'unitless'
-
 
-vName = "sea_ice_area_fraction"
 
+vName = "seaIceFraction"
 
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string")
+    ("dateTime", "long")
 ]
 
 GlobalAttrs = {
-    'odb_version': 1,
+    'converter': os.path.basename(__file__),
+    'ioda_version': 2,
+    'odb_version': 1
 }
 
 
@@ -148,16 +152,17 @@ def main():
     args = parser.parse_args()
     fdate = datetime.strptime(args.date, '%Y%m%d%H')
     VarDims = {
-        vName: ['nlocs'],
+        vName: ['Location'],
     }
     # Read in
     ice = Observation(args.input, args.thin, fdate)
 
     # write them out
     ObsVars, nlocs = iconv.ExtractObsData(ice.data, locationKeyList)
-    DimDict = {'nlocs': nlocs}
+    DimDict = {'Location': nlocs}
     writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
 
+    ice.VarAttrs['dateTime', 'MetaData']['units'] = iso8601_string
     writer.BuildIoda(ObsVars, VarDims, ice.VarAttrs, GlobalAttrs)
 
 
diff --git a/src/marine/ostia_l4sst2ioda.py b/src/marine/ostia_l4sst2ioda.py
index 836b75856..7c278fc16 100755
--- a/src/marine/ostia_l4sst2ioda.py
+++ b/src/marine/ostia_l4sst2ioda.py
@@ -27,7 +27,7 @@
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string"),
+    ("dateTime", "long"),
 ]
 
 obsvars = {
@@ -35,15 +35,14 @@
 }
 
 AttrData = {
-    'converter': os.path.basename(__file__),
-    'nvars': np.int32(len(obsvars)),
+    'converter': os.path.basename(__file__)
 }
 
 DimDict = {
 }
 
 VarDims = {
-    'sst': ['nlocs'],
+    'sst': ['Location'],
 }
 
 
@@ -57,19 +56,16 @@ def __init__(self, filename):
         self.lons = self.lons.ravel()
         self.lats = self.lats.ravel()
         self.sst = np.squeeze(ncd.variables['analysed_sst'][:]).ravel()
-        self.sst = self.sst-273.15
         self.err = np.squeeze(ncd.variables['analysis_error'][:]).ravel()
-        self.time = ncd.variables['time'][:]
+        this_datetime = ncd.variables['time'][:].astype(np.int)
         ncd.close()
 
         # Same time stamp for all obs within 1 file
-        self.datetime = np.empty_like(self.sst, dtype=object)
-        base_date = datetime(1981, 1, 1)
-        dt = base_date + timedelta(days=float(self.time/86400.0))
-        self.datetime[:] = dt.strftime("%Y-%m-%dT%H:%M:%SZ")
+        self.datetime = np.full(len(self.lats), this_datetime)
+        self.time_units = 'seconds since 1981-01-01T00:00:00Z'
 
         # Remove observations out of sane bounds
-        qci = np.where(np.abs(self.sst) < 99.0)
+        qci = np.where(np.abs(self.sst) < 355.0)
         self.nlocs = len(qci[0])
         self.lons = self.lons[qci].astype(np.single)
         self.lats = self.lats[qci].astype(np.single)
@@ -82,7 +78,6 @@ class ostia_l4sst2ioda(object):
     def __init__(self, filename):
         self.filename = filename
         self.varDict = defaultdict(lambda: defaultdict(dict))
-        self.metaDict = defaultdict(lambda: defaultdict(dict))
         self.outdata = defaultdict(lambda: DefaultOrderedDict(OrderedDict))
         self.var_mdata = defaultdict(lambda: DefaultOrderedDict(OrderedDict))
         self._read()
@@ -90,26 +85,28 @@ def __init__(self, filename):
     # Open input file and read relevant info
     def _read(self):
         # set up variable names for IODA
-        iodavar = 'sea_surface_temperature'
+        iodavar = 'seaSurfaceTemperature'
         self.varDict[iodavar]['valKey'] = iodavar, iconv.OvalName()
         self.varDict[iodavar]['errKey'] = iodavar, iconv.OerrName()
         self.varDict[iodavar]['qcKey'] = iodavar, iconv.OqcName()
-        self.var_mdata[iodavar, iconv.OvalName()]['units'] = 'c'
-        self.var_mdata[iodavar, iconv.OerrName()]['units'] = 'c'
+        self.var_mdata[iodavar, iconv.OvalName()]['units'] = 'K'
+        self.var_mdata[iodavar, iconv.OerrName()]['units'] = 'K'
 
         # read input filename
         sst = ostia(self.filename)
 
         # map ostia to ioda data structure
-        self.outdata[('datetime', 'MetaData')] = sst.datetime
+        self.outdata[('dateTime', 'MetaData')] = sst.datetime
+        self.var_mdata[('dateTime', 'MetaData')]['units'] = sst.time_units
         self.outdata[('latitude', 'MetaData')] = sst.lats
+        self.var_mdata[('latitude', 'MetaData')]['units'] = 'degrees_north'
         self.outdata[('longitude', 'MetaData')] = sst.lons
+        self.var_mdata[('longitude', 'MetaData')]['units'] = 'degrees_east'
         self.outdata[self.varDict[iodavar]['valKey']] = sst.sst
         self.outdata[self.varDict[iodavar]['errKey']] = sst.err
         self.outdata[self.varDict[iodavar]['qcKey']] = np.zeros(sst.nlocs, dtype=np.int32)
 
-        DimDict['nlocs'] = sst.nlocs
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+        DimDict['Location'] = sst.nlocs
 
 
 def main():
diff --git a/src/marine/pace_oc2ioda.py b/src/marine/pace_oc2ioda.py
index 6262c5f63..b0ecd2f66 100755
--- a/src/marine/pace_oc2ioda.py
+++ b/src/marine/pace_oc2ioda.py
@@ -26,8 +26,9 @@
 import ioda_conv_engines as iconv
 from orddicts import DefaultOrderedDict
 
-output_var_names = [
-    "mass_concentration_of_chlorophyll_in_sea_water"]
+os.environ["TZ"] = "UTC"
+
+output_var_names = ["chlorophyllMassConcentration"]
 
 DimDict = {}
 
@@ -38,7 +39,7 @@
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string"),
+    ("dateTime", "long"),
 ]
 
 
@@ -62,9 +63,13 @@ def read_input(input_args):
     print("Reading ", input_file)
     ncd = nc.Dataset(input_file, 'r')
 
-    # get global attributes
-    for v in ('platform', 'instrument', 'processing_level'):
-        GlobalAttrs[v] = ncd.getncattr(v)
+    # get global attributes (dictionary key is incoming name, being renamed).
+    global_attribs = {'platform': 'platformCommonName',
+                      'instrument': 'sensor',
+                      'processing_level': 'processingLevel'}
+    for v in global_attribs.keys():
+        new_name = global_attribs[v]
+        GlobalAttrs[new_name] = ncd.getncattr(v)
 
     # get QC flags, and calculate a mask from the non-missing values
     # since L2 OC files are quite empty, need a mask applied immediately
@@ -115,10 +120,9 @@ def read_input(input_args):
         data_in[v] = data_in[v][mask]
 
     # create a string version of the date for each observation
-    dates = []
+    dates = np.empty(len(lons), dtype=np.int64)
     for i in range(len(lons)):
-        obs_date = basetime + timedelta(seconds=float(data_in['time'][i]))
-        dates.append(obs_date.strftime("%Y-%m-%dT%H:%M:%SZ"))
+        dates[i] = round(data_in['time'][i])
 
     # allocate space for output depending on which variables are to be saved
     obs_dim = (len(lons))
@@ -129,8 +133,7 @@ def read_input(input_args):
     obs_data[(output_var_names[0], global_config['opqc_name'])] = np.zeros(obs_dim)
 
     # Add the metadata
-    obs_data[('datetime', 'MetaData')] = np.empty(len(dates), dtype=object)
-    obs_data[('datetime', 'MetaData')][:] = dates
+    obs_data[('dateTime', 'MetaData')] = dates
     obs_data[('latitude', 'MetaData')] = lats
     obs_data[('longitude', 'MetaData')] = lons
 
@@ -139,7 +142,7 @@ def read_input(input_args):
     obs_data[output_var_names[0], global_config['oerr_name']] = data_in['chlor_a']*0.0
     obs_data[output_var_names[0], global_config['opqc_name']] = data_in['l2_flags']
 
-    return (obs_data, GlobalAttrs)
+    return (obs_data, basetime, GlobalAttrs)
 
 
 def main():
@@ -202,7 +205,7 @@ def main():
     obs = pool.map(read_input, pool_inputs)
 
     # concatenate the data from the files
-    obs_data, GlobalAttrs = obs[0]
+    obs_data, basetime, GlobalAttrs = obs[0]
     for i in range(1, len(obs)):
         obs_data.update(obs[i][0])
     # Get the nlocs
@@ -210,19 +213,18 @@ def main():
 
     # prepare global attributes we want to output in the file,
     # in addition to the ones already loaded in from the input file
-    GlobalAttrs['date_time_string'] = args.date.strftime("%Y-%m-%dT%H:%M:%SZ")
+    GlobalAttrs['datetimeReference'] = args.date.strftime("%Y-%m-%dT%H:%M:%SZ")
     GlobalAttrs['thinning'] = args.thin
     GlobalAttrs['converter'] = os.path.basename(__file__)
-    DimDict['nlocs'] = nlocs
-    GlobalAttrs['nlocs'] = np.int32(DimDict['nlocs'])
+    DimDict['Location'] = nlocs
 
-    VarAttrs[output_var_names[0], global_config['oval_name']]['units'] = 'mg ^m-3'
-    VarAttrs[output_var_names[0], global_config['oerr_name']]['units'] = 'mg ^m-3'
-    VarAttrs[output_var_names[0], global_config['opqc_name']]['units'] = 'unitless'
+    VarAttrs['dateTime', 'MetaData']['units'] = 'seconds since ' + basetime.strftime("%Y-%m-%dT%H:%M:%SZ")
+    VarAttrs[output_var_names[0], global_config['oval_name']]['units'] = 'mg m-3'
+    VarAttrs[output_var_names[0], global_config['oerr_name']]['units'] = 'mg m-3'
     VarAttrs[output_var_names[0], global_config['oval_name']]['_FillValue'] = -32767.
     VarAttrs[output_var_names[0], global_config['oerr_name']]['_FillValue'] = -32767.
     VarAttrs[output_var_names[0], global_config['opqc_name']]['_FillValue'] = -32767
-    VarDims["mass_concentration_of_chlorophyll_in_sea_water"] = ['nlocs']
+    VarDims["chlorophyllMassConcentration"] = ['Location']
 
     # setup the IODA writer
     writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
diff --git a/src/marine/pace_radiance2ioda.py b/src/marine/pace_radiance2ioda.py
index 0d81cb2f1..bee0910a0 100755
--- a/src/marine/pace_radiance2ioda.py
+++ b/src/marine/pace_radiance2ioda.py
@@ -25,16 +25,21 @@
 import ioda_conv_engines as iconv
 from orddicts import DefaultOrderedDict
 
+os.environ["TZ"] = "UTC"
+# The setting of basetime is temporary as it will get modified in the data reading routine.
+basetime = datetime.fromisoformat('1970-01-01T00:00:00')
+
 output_var_names = ["radiance"]
 
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string")
+    ("dateTime", "long")
 ]
 
 GlobalAttrs = {
     'odb_version': 1,
+    'converter': os.path.basename(__file__)
 }
 
 VarAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
@@ -43,7 +48,7 @@
 
 VarDims = {}
 
-chan_number = range(1, 250)  # we havew 120 Blue band 120 Red band and 9 SWRI
+chan_number = range(1, 250)  # we have 120 Blue band 120 Red band and 9 SWRI
 
 
 def read_input(input_args):
@@ -66,6 +71,7 @@ def read_input(input_args):
     ncd = nc.Dataset(input_file, 'r')
     # get the base time (should only have 1 or 2 time slots)
     time_base = ncd.groups['scan_line_attributes'].variables['time'][:]
+    global basetime   # We wish to overrride the initial setting of basetime.
     basetime = dateutil.parser.parse(ncd.groups['scan_line_attributes'].variables['time'].units[-20:])
 
     # Determine the lat/lon grid.
@@ -123,10 +129,9 @@ def read_input(input_args):
     lats = lats[mask]
 
     # create a string version of the date for each observation
-    dates = []
+    dates = np.empty(len(lons), dtype=np.int64)
     for i in range(len(lons)):
-        obs_date = basetime + timedelta(seconds=float(time[i]))
-        dates.append(obs_date.strftime("%Y-%m-%dT%H:%M:%SZ"))
+        dates[i] = round(time[i])
 
     # output values
     nchans = len(chan_number)
@@ -147,18 +152,16 @@ def read_input(input_args):
     # allocate space for output depending on which variables are to be saved
 
     obs_data = {}
-    obs_data[('datetime', 'MetaData')] = np.empty(len(dates), dtype=object)
-    obs_data[('datetime', 'MetaData')][:] = dates
+    obs_data[('dateTime', 'MetaData')] = dates
     obs_data[('latitude', 'MetaData')] = lats
     obs_data[('longitude', 'MetaData')] = lons
-    obs_data[('time', 'MetaData')] = time.astype('float32')
-    obs_data[('height_above_mean_sea_level', 'MetaData')] = np.zeros((obs_dim), dtype=np.float32)
-    obs_data[('sensor_azimuth_angle', 'MetaData')] = data_in['sensor_azimuth']
-    obs_data[('sensor_zenith_angle', 'MetaData')] = data_in['sensor_zenith']
-    obs_data[('sensor_view_angle', 'MetaData')] = data_in['sensor_zenith']
-    obs_data[('solar_zenith_angle', 'MetaData')] = data_in['solar_zenith']
-    obs_data[('solar_azimuth_angle', 'MetaData')] = data_in['solar_azimuth']
-    obs_data[('sensor_band_central_radiation_wavenumber', 'VarMetaData')] = wavelength.astype('float32')
+    obs_data[('height', 'MetaData')] = np.zeros((obs_dim), dtype=np.float32)
+    obs_data[('sensorAzimuthAngle', 'MetaData')] = data_in['sensor_azimuth'].astype('float32')
+    obs_data[('sensorZenithAngle', 'MetaData')] = data_in['sensor_zenith'].astype('float32')
+    obs_data[('sensorViewAngle', 'MetaData')] = data_in['sensor_zenith'].astype('float32')
+    obs_data[('solarZenithAngle', 'MetaData')] = data_in['solar_zenith'].astype('float32')
+    obs_data[('solarAzimuthAngle', 'MetaData')] = data_in['solar_azimuth'].astype('float32')
+    obs_data[('sensorCentralWavenumber', 'MetaData')] = wavelength.astype('float32')
     obs_data[output_var_names[0], global_config['oval_name']] = val_radiance.astype('float32')
     obs_data[output_var_names[0], global_config['oerr_name']] = err.astype('float32')
     obs_data[output_var_names[0], global_config['opqc_name']] = qc.astype('int32')
@@ -221,9 +224,8 @@ def main():
 
     # prepare global attributes we want to output in the file,
     # in addition to the ones already loaded in from the input file
-    GlobalAttrs['date_time_string'] = args.date.strftime("%Y-%m-%dT%H:%M:%SZ")
+    GlobalAttrs['datetimeReference'] = args.date.strftime("%Y-%m-%dT%H:%M:%SZ")
     GlobalAttrs['thinning'] = args.thin
-    GlobalAttrs['converter'] = os.path.basename(__file__)
 
     # determine which variables we are going to output
     selected_names = []
@@ -232,28 +234,32 @@ def main():
     # pass parameters to the IODA writer
     # (needed because we are bypassing ExtractObsData within BuildNetcdf)
     VarDims = {
-        'radiance': ['nlocs', 'nchans'],
-        'sensor_band_central_radiation_wavenumber': ['nchans']
+        'radiance': ['Location', 'Channel'],
+        'sensorCentralWavenumber': ['Channel']
     }
 
     nchans = len(chan_number)
     nlocs = len(obs_data[('longitude', 'MetaData')])
-    ndatetime = np.zeros((20), dtype=np.float32)
     DimDict = {
-        'nlocs': nlocs,
-        'nchans': list(chan_number),
-        'nvars': list(chan_number),
-        'ndatetime': list(ndatetime)
+        'Location': nlocs,
+        'Channel': list(chan_number),
     }
 
     writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
 
-    VarAttrs[('radiance', 'ObsValue')]['units'] = 'W m^-2 um^-1 sr^-1'
-    VarAttrs[('radiance', 'ObsError')]['units'] = 'W m^-2 um^-1 sr^-1'
-    VarAttrs[('radiance', 'PreQC')]['units'] = 'unitless'
+    VarAttrs[('dateTime', 'MetaData')]['units'] = 'seconds since ' + basetime.strftime("%Y-%m-%dT%H:%M:%SZ")
+    VarAttrs[('radiance', 'ObsValue')]['units'] = 'W m-2 sr-1'
+    VarAttrs[('radiance', 'ObsError')]['units'] = 'W m-2 sr-1'
     VarAttrs[('radiance', 'ObsValue')]['_FillValue'] = -32767
     VarAttrs[('radiance', 'ObsError')]['_FillValue'] = 999
     VarAttrs[('radiance', 'PreQC')]['_FillValue'] = 999
+    for k in list(obs_data.keys()):
+        if 'angle' in k[0].lower():
+            VarAttrs[(k[0], k[1])]['units'] = 'degree'
+        elif 'wavenumber' in k[0].lower():
+            VarAttrs[(k[0], k[1])]['units'] = 'm-1'
+        elif k[0] == 'height':
+            VarAttrs[(k[0], k[1])]['units'] = 'm'
 
     writer.BuildIoda(obs_data, VarDims, VarAttrs, GlobalAttrs)
 
diff --git a/src/marine/rads_adt2ioda.py b/src/marine/rads_adt2ioda.py
index 11bd5d854..05e2e22ff 100755
--- a/src/marine/rads_adt2ioda.py
+++ b/src/marine/rads_adt2ioda.py
@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 
 #
-# (C) Copyright 2019 UCAR
+# (C) Copyright 2019-2022 UCAR
 #
 # This software is licensed under the terms of the Apache Licence Version 2.0
 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
@@ -9,8 +9,10 @@
 
 from __future__ import print_function
 import sys
+import os
 import argparse
 import netCDF4 as nc
+import numpy as np
 from datetime import datetime, timedelta
 import dateutil.parser
 from pathlib import Path
@@ -23,84 +25,150 @@
 import ioda_conv_engines as iconv
 from orddicts import DefaultOrderedDict
 
-vName = "absolute_dynamic_topography"
+os.environ["TZ"] = "UTC"
+
+varInfo = ['absoluteDynamicTopography', 'm']
 
 locationKeyList = [
-    ("latitude", "float"),
-    ("longitude", "float"),
-    ("datetime", "string")
+    ("latitude", "float", "degrees_north"),
+    ("longitude", "float", "degrees_east"),
+    ("dateTime", "long", "seconds since 1970-01-01T00:00:00Z")
 ]
-
-GlobalAttrs = {
-}
-
-VarDims = {
-    vName: ['nlocs'],
-}
-
-DimDict = {
-}
+meta_keys = [m_item[0] for m_item in locationKeyList]
+
+iso8601_string = locationKeyList[meta_keys.index('dateTime')][2]
+epoch = datetime.fromisoformat(iso8601_string[14:-1])
+
+metaDataName = iconv.MetaDataName()
+obsValName = iconv.OvalName()
+obsErrName = iconv.OerrName()
+qcName = iconv.OqcName()
+
+float_missing_value = nc.default_fillvals['f4']
+int_missing_value = nc.default_fillvals['i4']
+double_missing_value = nc.default_fillvals['f8']
+long_missing_value = nc.default_fillvals['i8']
+string_missing_value = '_'
+
+missing_vals = {'string': string_missing_value,
+                'integer': int_missing_value,
+                'long': long_missing_value,
+                'float': float_missing_value,
+                'double': double_missing_value}
+dtypes = {'string': object,
+          'integer': np.int32,
+          'long': np.int64,
+          'float': np.float32,
+          'double': np.float64}
 
 
 class Observation(object):
 
     def __init__(self, filename, date):
-
         self.filename = filename
         self.date = date
-        self.data = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
-        self.VarAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
         self._read()
 
     def _read(self):
 
-        ncd = nc.MFDataset(self.filename)
+        data = {}
+        data['dateTime'] = []
+        data['vals'] = []
+        data['errs'] = []
+        data['qcs'] = []
+
+        ncd = nc.Dataset(self.filename)
         time = ncd.variables['time_mjd'][:]
-        lons = ncd.variables['lon'][:]
-        lats = ncd.variables['lat'][:]
-        vals = ncd.variables['adt_egm2008'][:]
-        val_units = ncd.variables['adt_egm2008'].units
-        Fill_val = ncd.variables['adt_egm2008']._FillValue
-        scale_factor = ncd.variables['adt_egm2008'].scale_factor
+        data['longitude'] = ncd.variables['lon'][:]
+        data['latitude'] = ncd.variables['lat'][:]
+        vals = ncd.variables['adt_xgm2016'][:]
+        data['val_units'] = ncd.variables['adt_xgm2016'].units
+        data['Fill_val'] = ncd.variables['adt_xgm2016']._FillValue
+        scale_factor = ncd.variables['adt_xgm2016'].scale_factor
         units = ncd.variables['time_mjd'].units[-23:-4]
         reftime = dateutil.parser.parse(units)
         ncd.close()
 
-        valKey = vName, iconv.OvalName()
-        errKey = vName, iconv.OerrName()
-        qcKey = vName, iconv.OqcName()
-        self.VarAttrs[vName, iconv.OvalName()]['_FillValue'] = Fill_val
-        self.VarAttrs[vName, iconv.OerrName()]['_FillValue'] = Fill_val
-        self.VarAttrs[vName, iconv.OqcName()]['_FillValue'] = Fill_val
-        self.VarAttrs[vName, iconv.OvalName()]['units'] = val_units
-        self.VarAttrs[vName, iconv.OerrName()]['units'] = val_units
-        self.VarAttrs[vName, iconv.OqcName()]['units'] = 'unitless'
+        for i in range(len(time)):
+            dt = reftime + timedelta(days=time[i])
+            time_offset = np.int64(round((dt - epoch).total_seconds()))
+            data['dateTime'].append(time_offset)
+            data['vals'].append(vals[i])
+            data['errs'].append(0.1)
+            data['qcs'].append(0)
 
-        for i in range(len(lons)):
+        self.data = data
 
-            obs_date = reftime + timedelta(days=time[i])
 
-            locKey = lats[i], lons[i], obs_date.strftime("%Y-%m-%dT%H:%M:%SZ")
-            self.data[locKey][valKey] = vals[i]
-            self.data[locKey][errKey] = 0.1
-            self.data[locKey][qcKey] = 0
+class IODA(object):
 
+    def __init__(self, file_input, filename, date, obs):
 
-def main():
+        self.file_input = file_input
+        self.filename = filename
+        self.date = date
+
+        self.GlobalAttrs = {
+            'converter': os.path.basename(__file__),
+            'ioda_version': 2,
+            'sourceFiles': self.file_input,
+            'datetimeReference': self.date.strftime('%Y-%m-%dT%H:%M:%S%z'),
+            'description': "Absolute Dynamic Topography (ADT) observations from NESDIS"
+        }
+
+        self.varAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
+
+        # Set units and FillValue attributes for groups associated with observed variable.
+        self.varAttrs[(varInfo[0], obsValName)]['units'] = obs.data['val_units']
+        self.varAttrs[(varInfo[0], obsErrName)]['units'] = obs.data['val_units']
+        self.varAttrs[(varInfo[0], obsValName)]['_FillValue'] = obs.data['Fill_val']
+        self.varAttrs[(varInfo[0], obsErrName)]['_FillValue'] = obs.data['Fill_val']
+        self.varAttrs[(varInfo[0], qcName)]['_FillValue'] = int_missing_value
+
+        # Set units of the MetaData variables and all _FillValues.
+        for key in meta_keys:
+            dtypestr = locationKeyList[meta_keys.index(key)][1]
+            if locationKeyList[meta_keys.index(key)][2]:
+                self.varAttrs[(key, metaDataName)]['units'] = locationKeyList[meta_keys.index(key)][2]
+            self.varAttrs[(key, metaDataName)]['_FillValue'] = missing_vals[dtypestr]
+
+        # data is the dictionary containing IODA friendly data structure
+        self.data = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
 
-    # Get command line arguments
+        for key in meta_keys:
+            dtypestr = locationKeyList[meta_keys.index(key)][1]
+            self.data[(key, metaDataName)] = np.array(obs.data[key], dtype=dtypes[dtypestr])
+
+        # Fill up the final array of observed values, obsErrors, and Qc
+        self.data[(varInfo[0], obsValName)] = np.array(obs.data['vals'], dtype=np.float32)
+        self.data[(varInfo[0], obsErrName)] = np.array(obs.data['errs'], dtype=np.float32)
+        self.data[(varInfo[0], qcName)] = np.array(obs.data['qcs'], dtype=np.int32)
+
+        nlocs = len(obs.data['vals'])
+        DimDict = {'Location': nlocs}
+        varDims = {varInfo[0]: ['Location']}
+
+        # Initialize the writer, then write the file.
+        print(f"Writing the output file: {self.filename} with {nlocs} observations in it.")
+        self.writer = iconv.IodaWriter(self.filename, locationKeyList, DimDict)
+        self.writer.BuildIoda(self.data, varDims, self.varAttrs, self.GlobalAttrs)
+
+        return
+
+
+def main():
     parser = argparse.ArgumentParser(
         description=(
-            'Reads absolute dynamic topography (ADT) observations'
-            ' from NESDIS file(s) and converts into IODA formatted'
-            ' output files')
+            'Read absolute dynamic topography (ADT) observations'
+            ' file(s) that have already been QCd and thinned for use in'
+            ' Hybrid-GODAS system.')
     )
 
     required = parser.add_argument_group(title='required arguments')
     required.add_argument(
         '-i', '--input',
-        help="RADS observation input file(s)",
-        type=str, nargs='+', required=True)
+        help="name of RADS observation input file(s)",
+        type=str, required=True)
     required.add_argument(
         '-o', '--output',
         help="path of ioda output file",
@@ -109,24 +177,14 @@ def main():
         '-d', '--date',
         help="base date for the center of the window",
         metavar="YYYYMMDDHH", type=str, required=True)
-
     args = parser.parse_args()
     fdate = datetime.strptime(args.date, '%Y%m%d%H')
 
-    # Read in the altimeter
-    altim = Observation(args.input, fdate)
-
-    # Extract Obsdata
-    ObsVars, nlocs = iconv.ExtractObsData(altim.data, locationKeyList)
-
-    # Set attributes
-    DimDict['nlocs'] = nlocs
-
-    # Set up the IODA writer
-    writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
+    # Read in the adt (altimeter) data
+    adt = Observation(args.input, fdate)
 
-    # Write the obs out
-    writer.BuildIoda(ObsVars, VarDims, altim.VarAttrs, GlobalAttrs)
+    # Write out the IODA output file.
+    IODA(args.input, args.output, fdate, adt)
 
 
 if __name__ == '__main__':
diff --git a/src/marine/smap_sss2ioda.py b/src/marine/smap_sss2ioda.py
index bac861662..ef8524f7b 100755
--- a/src/marine/smap_sss2ioda.py
+++ b/src/marine/smap_sss2ioda.py
@@ -8,6 +8,7 @@
 #
 
 import sys
+import os
 import argparse
 import numpy as np
 from datetime import datetime, timedelta
@@ -24,17 +25,21 @@
 import ioda_conv_engines as iconv
 from orddicts import DefaultOrderedDict
 
+os.environ["TZ"] = "UTC"
 
-vName = "sea_surface_salinity"
+vName = "seaSurfaceSalinity"
 
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string")
+    ("dateTime", "long")
 ]
 
 GlobalAttrs = {}
 
+iso8601_string = 'seconds since 1970-01-01T00:00:00Z'
+epoch = datetime.fromisoformat(iso8601_string[14:-1])
+
 
 class Salinity(object):
     def __init__(self, filenames, date):
@@ -95,7 +100,7 @@ def _read(self):
             data = {}
             for v in source_var_name:
                 if v == 'sss_qc':
-                    data[v] = ncd.variables[source_var_name[v]][:].flatten().astype(int)
+                    data[v] = ncd.variables[source_var_name[v]][:].flatten().astype(np.int32)
                 else:
                     data[v] = ncd.variables[source_var_name[v]][:].flatten()
 
@@ -114,8 +119,8 @@ def _read(self):
             # for each observation
             for i in range(len(data['time'])):
                 obs_date = basetime + timedelta(seconds=float(data['time'][i]))
-                locKey = data['lat'][i], data['lon'][i], obs_date.strftime(
-                    "%Y-%m-%dT%H:%M:%SZ")
+                time_offset = round((obs_date - epoch).total_seconds())
+                locKey = data['lat'][i], data['lon'][i], time_offset
                 self.data[locKey][valKey] = data['sss'][i]
                 # if source == 'JPL':          #RTOFS-DA
                 #   if data['sss_qc'][i] <= 4:
@@ -134,7 +139,7 @@ def main():
 
     parser = argparse.ArgumentParser(
         description=(
-            'Read JPL/RSS SMAP sea surface salinity (SSS) file(s) and convert'
+            'Read JPL/RSS SMAP seaSurfaceSalinity (SSS) file(s) and convert'
             ' to a concatenated IODA formatted output file.')
     )
     required = parser.add_argument_group(title='required arguments')
@@ -154,25 +159,25 @@ def main():
     fdate = datetime.strptime(args.date, '%Y%m%d%H')
 
     VarDims = {
-        'sea_surface_salinity': ['nlocs'],
+        'seaSurfaceSalinity': ['Location'],
     }
 
-    # Read in the salinity
+    # Read in the seaSurfaceSalinity
     sal = Salinity(args.input, fdate)
 
     # write them out
-    ObsVars, nlocs = iconv.ExtractObsData(sal.data, locationKeyList)
+    ObsVars, Location = iconv.ExtractObsData(sal.data, locationKeyList)
 
-    DimDict = {'nlocs': nlocs}
+    DimDict = {'Location': Location}
     writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
 
     VarAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
-    VarAttrs[('sea_surface_salinity', 'ObsValue')]['units'] = 'PSU'
-    VarAttrs[('sea_surface_salinity', 'ObsError')]['units'] = 'PSU'
-    VarAttrs[('sea_surface_salinity', 'PreQC')]['units'] = 'unitless'
-    VarAttrs[('sea_surface_salinity', 'ObsValue')]['_FillValue'] = 999
-    VarAttrs[('sea_surface_salinity', 'ObsError')]['_FillValue'] = 999
-    VarAttrs[('sea_surface_salinity', 'PreQC')]['_FillValue'] = 999
+    VarAttrs[('dateTime', 'MetaData')]['units'] = iso8601_string
+    VarAttrs[('seaSurfaceSalinity', 'ObsValue')]['units'] = 'PSU'
+    VarAttrs[('seaSurfaceSalinity', 'ObsError')]['units'] = 'PSU'
+    VarAttrs[('seaSurfaceSalinity', 'ObsValue')]['_FillValue'] = 999
+    VarAttrs[('seaSurfaceSalinity', 'ObsError')]['_FillValue'] = 999
+    VarAttrs[('seaSurfaceSalinity', 'PreQC')]['_FillValue'] = 999
     writer.BuildIoda(ObsVars, VarDims, VarAttrs, GlobalAttrs)
 
 
diff --git a/src/marine/smos_sss2ioda.py b/src/marine/smos_sss2ioda.py
index 38ac34430..781d00494 100755
--- a/src/marine/smos_sss2ioda.py
+++ b/src/marine/smos_sss2ioda.py
@@ -8,6 +8,7 @@
 #
 
 import sys
+import os
 import argparse
 import numpy as np
 from datetime import datetime, timedelta
@@ -22,17 +23,21 @@
 import ioda_conv_engines as iconv
 from orddicts import DefaultOrderedDict
 
+os.environ["TZ"] = "UTC"
 
-vName = "sea_surface_salinity"
+vName = "seaSurfaceSalinity"
 
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string")
+    ("dateTime", "long")
 ]
 
 GlobalAttrs = {}
 
+iso8601_string = 'seconds since 1970-01-01T00:00:00Z'
+epoch = datetime.fromisoformat(iso8601_string[14:-1])
+
 
 class Salinity(object):
     def __init__(self, filenames, date):
@@ -63,7 +68,7 @@ def _read(self):
             sss = ncd.variables['SSS_corr'][:]
             sss_err = ncd.variables['Sigma_SSS_corr'][:]
             sss_qc = ncd.variables['Dg_quality_SSS_corr'][:]
-            sss_qc = sss_qc.astype(int)
+            sss_qc = sss_qc.astype(np.int32)
 
             mask = np.logical_not(sss.mask)
             lon = lon[mask]
@@ -84,11 +89,9 @@ def _read(self):
                 MM1 = f[n+19+11:n+19+13]
                 SS1 = f[n+19+13:n+19+15]
                 #
-                seconds = (datetime.strptime(date1+HH1+MM1+SS1, '%Y%m%d%H%M%S') - datetime.strptime(
-                           date1, '%Y%m%d')).total_seconds()
-                basetime = datetime.strptime(date1, '%Y%m%d')
-                obs_date = basetime + timedelta(seconds=int(seconds))
-                locKey = lat[i], lon[i], obs_date.strftime("%Y-%m-%dT%H:%M:%SZ")
+                this_dt = datetime.strptime(date1+HH1+MM1+SS1, '%Y%m%d%H%M%S')
+                time_offset = round((this_dt - epoch).total_seconds())
+                locKey = lat[i], lon[i], time_offset
                 self.data[locKey][valKey] = sss[i]
                 self.data[locKey][errKey] = sss_err[i]
                 self.data[locKey][qcKey] = sss_qc[i]
@@ -99,7 +102,7 @@ def main():
 
     parser = argparse.ArgumentParser(
         description=(
-            'Read JPL/RSS SMOS sea surface salinity (SSS) file(s) and convert'
+            'Read JPL/RSS SMOS seaSurfaceSalinity (SSS) file(s) and convert'
             ' to a concatenated IODA formatted output file.')
     )
     required = parser.add_argument_group(title='required arguments')
@@ -119,25 +122,25 @@ def main():
     fdate = datetime.strptime(args.date, '%Y%m%d%H')
 #
     VarDims = {
-        'sea_surface_salinity': ['nlocs'],
+        'seaSurfaceSalinity': ['Location'],
     }
 
-    # Read in the salinity
+    # Read in the seaSurfaceSalinity
     sal = Salinity(args.input, fdate)
 
     # write them out
-    ObsVars, nlocs = iconv.ExtractObsData(sal.data, locationKeyList)
+    ObsVars, Location = iconv.ExtractObsData(sal.data, locationKeyList)
 
-    DimDict = {'nlocs': nlocs}
+    DimDict = {'Location': Location}
     writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
 
     VarAttrs = DefaultOrderedDict(lambda: DefaultOrderedDict(dict))
-    VarAttrs[('sea_surface_salinity', 'ObsValue')]['units'] = 'PSU'
-    VarAttrs[('sea_surface_salinity', 'ObsError')]['units'] = 'PSU'
-    VarAttrs[('sea_surface_salinity', 'PreQC')]['units'] = 'unitless'
-    VarAttrs[('sea_surface_salinity', 'ObsValue')]['_FillValue'] = 999
-    VarAttrs[('sea_surface_salinity', 'ObsError')]['_FillValue'] = 999
-    VarAttrs[('sea_surface_salinity', 'PreQC')]['_FillValue'] = 999
+    VarAttrs[('dateTime', 'MetaData')]['units'] = iso8601_string
+    VarAttrs[('seaSurfaceSalinity', 'ObsValue')]['units'] = 'PSU'
+    VarAttrs[('seaSurfaceSalinity', 'ObsError')]['units'] = 'PSU'
+    VarAttrs[('seaSurfaceSalinity', 'ObsValue')]['_FillValue'] = 999
+    VarAttrs[('seaSurfaceSalinity', 'ObsError')]['_FillValue'] = 999
+    VarAttrs[('seaSurfaceSalinity', 'PreQC')]['_FillValue'] = 999
     writer.BuildIoda(ObsVars, VarDims, VarAttrs, GlobalAttrs)
 
 
diff --git a/src/marine/swot_l2adt2ioda.py b/src/marine/swot_l2adt2ioda.py
index 265aba6e5..1617f070e 100755
--- a/src/marine/swot_l2adt2ioda.py
+++ b/src/marine/swot_l2adt2ioda.py
@@ -28,7 +28,7 @@
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string"),
+    ("dateTime", "long"),
 ]
 
 obsvars = {
@@ -36,15 +36,14 @@
 }
 
 AttrData = {
-    'converter': os.path.basename(__file__),
-    'nvars': np.int32(len(obsvars)),
+    'converter': os.path.basename(__file__)
 }
 
 DimDict = {
 }
 
 VarDims = {
-    'adt': ['nlocs'],
+    'adt': ['Location'],
 }
 
 
@@ -52,7 +51,6 @@ class swot_l2adt2ioda(object):
     def __init__(self, filename):
         self.filename = filename
         self.varDict = defaultdict(lambda: defaultdict(dict))
-        self.metaDict = defaultdict(lambda: defaultdict(dict))
         self.outdata = defaultdict(lambda: DefaultOrderedDict(OrderedDict))
         self.var_mdata = defaultdict(lambda: DefaultOrderedDict(OrderedDict))
         self._read()
@@ -73,20 +71,25 @@ def _read(self):
         err_units = ncd.variables['ssh_karin'].units
         err_scale_factor = ncd.variables['ssh_karin'].scale_factor
         self.qcflag = ncd.variables['ssha_karin_qual'][:].ravel()
-        # get the time data, convert to timestamps
+        # get the time data, chop off milliseconds, set the units
         time_var = ncd.variables['time']
+        time_units = time_var.units[:-2] + "Z"
+        s = list(time_units)
+        s[24] = "T"
+        time_units = "".join(s)
         num_pixels = ncd.dimensions['num_pixels'].size
-        self.time = nc.num2date(np.repeat(time_var[:], num_pixels),
-                                time_var.units)  # only_use_cftime_datetimes=False)
-        for t in range(len(self.time)):
-            self.time[t] = self.time[t].strftime("%Y-%m-%dT%H:%M:%SZ")
+        self.time = np.zeros(len(time_var)*num_pixels, dtype=np.int64)
+        for t in range(len(time_var)):
+            for n in range(num_pixels):
+                self.time[n + t*num_pixels] = np.round(time_var[t])
+
         ncd.close()
 
         # estimate adt from SSH and Geoid height
         adt = np.where(self.ssha == Fillvalue, Fillvalue, self.ssha + self.mssh - self.geoid)
 
         # set up variable names for IODA
-        iodavar = 'absolute_dynamic_topography'
+        iodavar = 'absoluteDynamicTopography'
         self.varDict[iodavar]['valKey'] = iodavar, iconv.OvalName()
         self.varDict[iodavar]['errKey'] = iodavar, iconv.OerrName()
         self.varDict[iodavar]['qcKey'] = iodavar, iconv.OqcName()
@@ -94,20 +97,22 @@ def _read(self):
         self.var_mdata[iodavar, iconv.OerrName()]['units'] = err_units
         self.var_mdata[iodavar, iconv.OvalName()]['_FillValue'] = Fillvalue
         self.var_mdata[iodavar, iconv.OerrName()]['_FillValue'] = err_Fillvalue
-        self.var_mdata[iodavar, iconv.OvalName()]['scale_factor'] = scale_factor
-        self.var_mdata[iodavar, iconv.OerrName()]['scale_factor'] = err_scale_factor
+        # self.var_mdata[iodavar, iconv.OvalName()]['scaleFactor'] = scale_factor
+        # self.var_mdata[iodavar, iconv.OerrName()]['scaleFactor'] = err_scale_factor
 
         # map swot adt to ioda data structure
-        self.outdata[('datetime', 'MetaData')] = self.time
-        self.outdata[('latitude', 'MetaData')] = self.lats
-        self.outdata[('longitude', 'MetaData')] = self.lons
+        self.outdata[('dateTime', 'MetaData')] = self.time
+        self.var_mdata[('dateTime', 'MetaData')]['units'] = time_units
+        self.outdata[('latitude', 'MetaData')] = self.lats.astype('float32')
+        self.var_mdata[('latitude', 'MetaData')]['units'] = "degrees_north"
+        self.outdata[('longitude', 'MetaData')] = self.lons.astype('float32')
+        self.var_mdata[('longitude', 'MetaData')]['units'] = "degrees_east"
         self.outdata[self.varDict[iodavar]['valKey']] = adt
         # The current uncertainity values seem to be wrong so setting error to 1
         self.outdata[self.varDict[iodavar]['errKey']] = np.ones(np.shape(self.err))
         self.outdata[self.varDict[iodavar]['qcKey']] = self.qcflag.astype('int32')
 
-        DimDict['nlocs'] = len(adt)
-        AttrData['nlocs'] = np.int32(DimDict['nlocs'])
+        DimDict['Location'] = len(adt)
 
 
 def main():
diff --git a/src/marine/viirs_modis_l2_oc2ioda.py b/src/marine/viirs_modis_l2_oc2ioda.py
index 419ddfe2f..5343e303f 100755
--- a/src/marine/viirs_modis_l2_oc2ioda.py
+++ b/src/marine/viirs_modis_l2_oc2ioda.py
@@ -27,8 +27,8 @@
 from orddicts import DefaultOrderedDict
 
 output_var_names = [
-    "ocean_mass_content_of_particulate_organic_matter_expressed_as_carbon",
-    "mass_concentration_of_chlorophyll_in_sea_water"]
+    "oceanMassParticulateAsCarbon",
+    "chlorophyllMassConcentration"]
 
 DimDict = {}
 
@@ -39,9 +39,13 @@
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string"),
+    ("dateTime", "long"),
 ]
 
+obsValName = iconv.OvalName()
+obsErrName = iconv.OerrName()
+qcName = iconv.OqcName()
+
 
 def read_input(input_args):
     """
@@ -64,8 +68,9 @@ def read_input(input_args):
     ncd = nc.Dataset(input_file, 'r')
 
     # get global attributes
-    for v in ('platform', 'instrument', 'processing_level'):
-        GlobalAttrs[v] = ncd.getncattr(v)
+    GlobalAttrs['platformCommonName'] = ncd.getncattr('platform')
+    GlobalAttrs['sensor'] = ncd.getncattr('instrument')
+    GlobalAttrs['processingLevel'] = str(ncd.getncattr('processing_level')+' processing')
 
     # get QC flags, and calculate a mask from the non-missing values
     # since L2 OC files are quite empty, need a mask applied immediately
@@ -91,6 +96,7 @@ def read_input(input_args):
     time = (np.repeat(sla.variables['msec'][:].ravel(),
             pixels_per_line).ravel() - sla.variables['msec'][0])/1000.0
     data_in['time'] = time[mask]
+    time_units = basetime.strftime("%Y-%m-%dT%H:%M:%SZ")
 
     # load in all the other data and apply the missing value mask
     input_vars = ('poc', 'chlor_a')
@@ -115,49 +121,36 @@ def read_input(input_args):
     # create a string version of the date for each observation
     dates = []
     for i in range(len(lons)):
-        obs_date = basetime + timedelta(seconds=float(data_in['time'][i]))
-        dates.append(obs_date.strftime("%Y-%m-%dT%H:%M:%SZ"))
+        dates.append(np.int64(data_in['time'][i]))
 
     # allocate space for output depending on which variables are to be saved
     obs_dim = (len(lons))
     obs_data = {}
     if global_config['output_poc']:
-        obs_data[(output_var_names[0], global_config['oval_name'])] = \
-            np.zeros(obs_dim)
-        obs_data[(output_var_names[0], global_config['oerr_name'])] = \
-            np.zeros(obs_dim)
-        obs_data[(output_var_names[0], global_config['opqc_name'])] = \
-            np.zeros(obs_dim)
+        obs_data[(output_var_names[0], obsValName)] = np.zeros(obs_dim)
+        obs_data[(output_var_names[0], obsErrName)] = np.zeros(obs_dim)
+        obs_data[(output_var_names[0], qcName)] = np.zeros(obs_dim)
     if global_config['output_chl']:
-        obs_data[(output_var_names[1], global_config['oval_name'])] = \
-            np.zeros(obs_dim)
-        obs_data[(output_var_names[1], global_config['oerr_name'])] = \
-            np.zeros(obs_dim)
-        obs_data[(output_var_names[1], global_config['opqc_name'])] = \
-            np.zeros(obs_dim)
+        obs_data[(output_var_names[1], obsValName)] = np.zeros(obs_dim)
+        obs_data[(output_var_names[1], obsErrName)] = np.zeros(obs_dim)
+        obs_data[(output_var_names[1], qcName)] = np.zeros(obs_dim)
 
     # Add the metadata
-    obs_data[('datetime', 'MetaData')] = np.empty(len(dates), dtype=object)
-    obs_data[('datetime', 'MetaData')][:] = dates
+    obs_data[('dateTime', 'MetaData')] = np.empty(len(dates), dtype=np.int64)
+    obs_data[('dateTime', 'MetaData')][:] = dates
     obs_data[('latitude', 'MetaData')] = lats
     obs_data[('longitude', 'MetaData')] = lons
 
     if global_config['output_poc']:
-        obs_data[output_var_names[0], global_config['oval_name']] = \
-            data_in['poc']
-        obs_data[output_var_names[0], global_config['oerr_name']] = \
-            data_in['poc']*0.0
-        obs_data[output_var_names[0], global_config['opqc_name']] = \
-            data_in['l2_flags']
+        obs_data[output_var_names[0], obsValName] = data_in['poc']
+        obs_data[output_var_names[0], obsErrName] = data_in['poc']*0.0
+        obs_data[output_var_names[0], qcName] = data_in['l2_flags']
     if global_config['output_chl']:
-        obs_data[output_var_names[1], global_config['oval_name']] = \
-            data_in['chlor_a']
-        obs_data[output_var_names[1], global_config['oerr_name']] = \
-            data_in['chlor_a']*0.0
-        obs_data[output_var_names[1], global_config['opqc_name']] = \
-            data_in['l2_flags']
+        obs_data[output_var_names[1], obsValName] = data_in['chlor_a']
+        obs_data[output_var_names[1], obsErrName] = data_in['chlor_a']*0.0
+        obs_data[output_var_names[1], qcName] = data_in['l2_flags']
 
-    return (obs_data, GlobalAttrs)
+    return (obs_data, GlobalAttrs, time_units)
 
 
 def main():
@@ -218,9 +211,6 @@ def main():
     global_config = {}
     global_config['date'] = args.date
     global_config['thin'] = args.thin
-    global_config['oval_name'] = iconv.OvalName()
-    global_config['oerr_name'] = iconv.OerrName()
-    global_config['opqc_name'] = iconv.OqcName()
     global_config['output_poc'] = args.poc
     global_config['output_chl'] = args.chl
 
@@ -235,50 +225,39 @@ def main():
     obs = pool.map(read_input, pool_inputs)
 
     # concatenate the data from the files
-    obs_data, GlobalAttrs = obs[0]
+    obs_data, GlobalAttrs, time_units = obs[0]
     for i in range(1, len(obs)):
         obs_data.update(obs[i][0])
-    # Get the nlocs
-    nlocs = len(obs_data[('longitude', 'MetaData')])
+    # Get the Location
+    Location = len(obs_data[('longitude', 'MetaData')])
 
     # prepare global attributes we want to output in the file,
     # in addition to the ones already loaded in from the input file
-    GlobalAttrs['date_time_string'] = args.date.strftime("%Y-%m-%dT%H:%M:%SZ")
+    GlobalAttrs['datetimeReference'] = args.date.strftime("%Y-%m-%dT%H:%M:%SZ")
     GlobalAttrs['thinning'] = args.thin
     GlobalAttrs['converter'] = os.path.basename(__file__)
-    DimDict['nlocs'] = nlocs
-    GlobalAttrs['nlocs'] = np.int32(DimDict['nlocs'])
+    DimDict['Location'] = Location
+
+    VarAttrs[('dateTime', 'MetaData')]['units'] = 'seconds since ' + time_units
+    VarAttrs[('latitude', 'MetaData')]['units'] = 'degrees_north'
+    VarAttrs[('longitude', 'MetaData')]['units'] = 'degrees_east'
 
     # determine which variables we are going to output
     if args.poc:
-        VarAttrs[output_var_names[0], global_config['oval_name']]['units'] = \
-            'mg ^m-3'
-        VarAttrs[output_var_names[0], global_config['oerr_name']]['units'] = \
-            'mg ^m-3'
-        VarAttrs[output_var_names[0], global_config['opqc_name']]['units'] = \
-            'unitless'
-        VarAttrs[output_var_names[0], global_config['oval_name']]['_FillValue'] = \
-            -32767.
-        VarAttrs[output_var_names[0], global_config['oerr_name']]['_FillValue'] = \
-            -32767.
-        VarAttrs[output_var_names[0], global_config['opqc_name']]['_FillValue'] = \
-            -32767
-        VarDims["ocean_mass_content_of_particulate_organic_matter_expressed_as_carbon"] = ['nlocs']
+        VarAttrs[output_var_names[0], obsValName]['units'] = 'mg m-3'
+        VarAttrs[output_var_names[0], obsErrName]['units'] = 'mg m-3'
+        VarAttrs[output_var_names[0], obsValName]['_FillValue'] = -32767.
+        VarAttrs[output_var_names[0], obsErrName]['_FillValue'] = -32767.
+        VarAttrs[output_var_names[0], qcName]['_FillValue'] = -32767
+        VarDims["oceanMassParticulateAsCarbon"] = ['Location']
 
     if args.chl:
-        VarAttrs[output_var_names[1], global_config['oval_name']]['units'] = \
-            'mg ^m-3'
-        VarAttrs[output_var_names[1], global_config['oerr_name']]['units'] = \
-            'mg ^m-3'
-        VarAttrs[output_var_names[1], global_config['opqc_name']]['units'] = \
-            'unitless'
-        VarAttrs[output_var_names[1], global_config['oval_name']]['_FillValue'] = \
-            -32767.
-        VarAttrs[output_var_names[1], global_config['oerr_name']]['_FillValue'] = \
-            -32767.
-        VarAttrs[output_var_names[1], global_config['opqc_name']]['_FillValue'] = \
-            -32767
-        VarDims["mass_concentration_of_chlorophyll_in_sea_water"] = ['nlocs']
+        VarAttrs[output_var_names[1], obsValName]['units'] = 'mg m-3'
+        VarAttrs[output_var_names[1], obsErrName]['units'] = 'mg m-3'
+        VarAttrs[output_var_names[1], obsValName]['_FillValue'] = -32767.
+        VarAttrs[output_var_names[1], obsErrName]['_FillValue'] = -32767.
+        VarAttrs[output_var_names[1], qcName]['_FillValue'] = -32767
+        VarDims["chlorophyllMassConcentration"] = ['Location']
 
     # setup the IODA writer
     writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
diff --git a/src/marine/viirs_modis_l3_oc2ioda.py b/src/marine/viirs_modis_l3_oc2ioda.py
index 38ae8b7e3..84a45c10a 100755
--- a/src/marine/viirs_modis_l3_oc2ioda.py
+++ b/src/marine/viirs_modis_l3_oc2ioda.py
@@ -26,11 +26,11 @@
 
 
 vName = {
-    'chlor_a': "mass_concentration_of_chlorophyll_in_sea_water",
+    'chlor_a': "chlorophyllMassConcentration",
 }
 
 VarDims = {
-    vName['chlor_a']: ['nlocs']
+    vName['chlor_a']: ['Location']
 }
 
 DimDict = {}
@@ -38,11 +38,15 @@
 locationKeyList = [
     ("latitude", "float"),
     ("longitude", "float"),
-    ("datetime", "string")
+    ("dateTime", "long")
 ]
 
 GlobalAttrs = {}
 
+# Prepare dateTime info
+iso8601_string = '1970-01-01T00:00:00Z'
+epoch = datetime.fromisoformat(iso8601_string[:-1])
+
 
 class OCL3(object):
 
@@ -66,12 +70,18 @@ def _read(self):
         lons = lons.ravel()[mask]
         lats = lats.ravel()[mask]
 
-        # get global attributes
-        for v in ('platform', 'instrument', 'processing_version',
-                  'time_coverage_start'):
-            GlobalAttrs[v] = ncd.getncattr(v)
+        GlobalAttrs['platform'] = ncd.getncattr('platform')
+        GlobalAttrs['sensor'] = ncd.getncattr('instrument')
+        GlobalAttrs['description'] = str(ncd.getncattr('processing_level')+' processing')
+
+        timevar = ncd.getncattr('time_coverage_start')
+        this_time = datetime.fromisoformat(timevar[:19])
+        obstime = np.int64(round((this_time - epoch).total_seconds()))
+
         ncd.close()
 
+        # Convert obstime from string to seconds since blah blah
+
         valKey = vName['chlor_a'], iconv.OvalName()
         errKey = vName['chlor_a'], iconv.OerrName()
         qcKey = vName['chlor_a'], iconv.OqcName()
@@ -81,7 +91,10 @@ def _read(self):
         self.VarAttrs[vName['chlor_a'], iconv.OqcName()]['_FillValue'] = -32767
         self.VarAttrs[vName['chlor_a'], iconv.OvalName()]['units'] = 'mg m^-3'
         self.VarAttrs[vName['chlor_a'], iconv.OerrName()]['units'] = 'mg m^-3'
-        self.VarAttrs[vName['chlor_a'], iconv.OqcName()]['units'] = 'unitless'
+
+        self.VarAttrs[('dateTime', 'MetaData')]['units'] = 'seconds since ' + iso8601_string
+        self.VarAttrs[('latitude', 'MetaData')]['units'] = 'degrees_north'
+        self.VarAttrs[('longitude', 'MetaData')]['units'] = 'degrees_east'
 
         # apply thinning mask
         if self.thin > 0.0:
@@ -91,7 +104,7 @@ def _read(self):
             vals = vals[mask_thin]
 
         for i in range(len(vals)):
-            locKey = lats[i], lons[i], GlobalAttrs['time_coverage_start']
+            locKey = lats[i], lons[i], obstime
             self.data[locKey][valKey] = vals[i]
             self.data[locKey][errKey] = vals[i] * 0.25
             self.data[locKey][qcKey] = 0
@@ -123,12 +136,12 @@ def main():
     chl = OCL3(args.input, fdate, args.thin)
 
     # Extract the obs data
-    ObsVars, nlocs = iconv.ExtractObsData(chl.data, locationKeyList)
+    ObsVars, Location = iconv.ExtractObsData(chl.data, locationKeyList)
 
     # Set Attributes
     GlobalAttrs['thinning'] = args.thin
     GlobalAttrs['converter'] = os.path.basename(__file__)
-    DimDict['nlocs'] = nlocs
+    DimDict['Location'] = Location
 
     # Set up the writer
     writer = iconv.IodaWriter(args.output, locationKeyList, DimDict)
diff --git a/test/CMakeLists.txt b/test/CMakeLists.txt
index 712bd8b72..872c400a2 100644
--- a/test/CMakeLists.txt
+++ b/test/CMakeLists.txt
@@ -1082,6 +1082,7 @@ ecbuild_add_test( TARGET  test_${PROJECT_NAME}_aeronet_aaod
 
 ecbuild_add_test( TARGET  test_${PROJECT_NAME}_airnow
                   TYPE    SCRIPT
+		  ENVIRONMENT "PYTHONPATH=${IODACONV_PYTHONPATH}"
                   COMMAND bash
                   ARGS    ${CMAKE_BINARY_DIR}/bin/iodaconv_comp.sh
                           netcdf
@@ -1095,7 +1096,7 @@ ecbuild_add_test( TARGET  test_${PROJECT_NAME}_tropomi_co_total
                   TYPE    SCRIPT
                   ENVIRONMENT "PYTHONPATH=${IODACONV_PYTHONPATH}"
                   COMMAND bash
-                  ARGS    ${CMAKE_BINARY_DIR}/bin/iodaconv_comp.sh
+                  	ARGS    ${CMAKE_BINARY_DIR}/bin/iodaconv_comp.sh
                           netcdf
                           "${Python3_EXECUTABLE} ${CMAKE_BINARY_DIR}/bin/tropomi_no2_co_nc2ioda.py
                           -i testinput/tropomi_co.nc
@@ -1103,7 +1104,7 @@ ecbuild_add_test( TARGET  test_${PROJECT_NAME}_tropomi_co_total
                           -v co
                           -q 0.5
                           -c total"
-                          tropomi_co_total.nc ${IODA_CONV_COMP_TOL_ZERO})
+	                   tropomi_co_total.nc ${IODA_CONV_COMP_TOL_ZERO})
 
 #==============================================================================
 # Bufr Ingester tests
@@ -1537,7 +1538,7 @@ if( iodaconv_eccodes_ENABLED )
                    COMMAND bash
                    ARGS    ${CMAKE_BINARY_DIR}/bin/iodaconv_comp.sh
                            netcdf
-                           "${Python3_EXECUTABLE} ${CMAKE_BINARY_DIR}/bin/decode_bufr_LDM_raob.py
+                           "${Python3_EXECUTABLE} ${CMAKE_BINARY_DIR}/bin/sonde_bufr2ioda.py
                            -i testinput/sonde_wmo_double.bufr
                            -o testrun/wmo_raob_double.nc4"
                            wmo_raob_double.nc4 ${IODA_CONV_COMP_TOL_ZERO})
diff --git a/test/testinput/SNDR.SNPP.ATMS.20211206T0100.m06.g011.L1B.std.v03_15.G.211206074531.nc4 b/test/testinput/SNDR.SNPP.ATMS.20211206T0100.m06.g011.L1B.std.v03_15.G.211206074531.nc4
deleted file mode 100644
index 6b49d9c87..000000000
--- a/test/testinput/SNDR.SNPP.ATMS.20211206T0100.m06.g011.L1B.std.v03_15.G.211206074531.nc4
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:407cd2434710ce14c726085ea659cc0ba5f68cb84dcefc3b2410383fe0f165db
-size 7697499
diff --git a/test/testinput/adpupa_prepbufr.yaml b/test/testinput/adpupa_prepbufr.yaml
index 17381a260..eb3c4291b 100644
--- a/test/testinput/adpupa_prepbufr.yaml
+++ b/test/testinput/adpupa_prepbufr.yaml
@@ -129,17 +129,17 @@ observations:
           path: "*/PRSLEVEL"
         - name: Depth
           path: "*/SST_INFO/SSTEVENT"
-        - name: cloudseq_Dim
+        - name: CloudSequence
           path: "*/CLOUDSEQ"
-        - name: pevent_Dim
+        - name: PressureEvent
           path: "*/PRSLEVEL/P___INFO/P__EVENT"
-        - name: qevent_Dim
+        - name: HumidityEvent
           path: "*/PRSLEVEL/Q___INFO/Q__EVENT"
-        - name: tevent_Dim
+        - name: TemperatureEvent
           path: "*/PRSLEVEL/T___INFO/T__EVENT"
-        - name: zevent_Dim
+        - name: HeightEvent
           path: "*/PRSLEVEL/Z___INFO/Z__EVENT"
-        - name: wevent_Dim
+        - name: WindEvent
           path: "*/PRSLEVEL/W___INFO/W__EVENT"
 
       variables:
@@ -178,7 +178,7 @@ observations:
           longName: "Station elevation"
           units: "m"
 
-        - name: "MetaData/air_pressure"
+        - name: "MetaData/pressure"
           coordinates: "longitude latitude Level"
           source: variables/pressure
           longName: "Pressure"
@@ -190,43 +190,43 @@ observations:
           longName: "Height"
           units: "m"
 
-        - name: "ObsValue/air_temperature"
+        - name: "ObsValue/airTemperature"
           coordinates: "longitude latitude Level"
           source: variables/airTemperature
           longName: "Temperature"
           units: "K"
 
-        - name: "ObsValue/dewpoint_temperature"
+        - name: "ObsValue/dewPointTemperature"
           coordinates: "longitude latitude Level"
           source: variables/dewpointTemperature
           longName: "Dewpoint temperature"
           units: "K"
 
-        - name: "ObsValue/virtual_temperature"
+        - name: "ObsValue/virtualTemperature"
           coordinates: "longitude latitude Level"
           source: variables/virtualTemperature
           longName: "Virtual temperature"
           units: "K"
 
-        - name: "ObsValue/specific_humidity"
+        - name: "ObsValue/specificHumidity"
           coordinates: "longitude latitude Level"
           source: variables/specificHumidity
           longName: "Specific humidity"
           units: "kg kg-1"
 
-        - name: "ObsValue/eastward_wind"
+        - name: "ObsValue/windEastward"
           coordinates: "longitude latitude Level"
           source: variables/windEastward
           longName: "Eastward wind"
           units: "m s-1"
 
-        - name: "ObsValue/northward_wind"
+        - name: "ObsValue/windNorthward"
           coordinates: "longitude latitude Level"
           source: variables/windNorthward
           longName: "Northward wind"
           units: "m s-1"
 
-        - name: "ObsValue/sea_surface_temperature"
+        - name: "ObsValue/seaSurfaceTemperature"
           coordinates: "longitude latitude Depth"
           source: variables/seaSurfaceTemperature
           longName: "Sea surface temperature"
@@ -243,27 +243,27 @@ observations:
           source: variables/heightQM
           longName: "Height quality marker"
 
-        - name: "QualityMarker/air_temperature"
+        - name: "QualityMarker/airTemperature"
           coordinates: "longitude latitude Level"
           source: variables/airTemperatureQM
           longName: "Temperature quality marker"
 
-        - name: "QualityMarker/specific_humidity"
+        - name: "QualityMarker/specificHumidity"
           coordinates: "longitude latitude Level"
           source: variables/specificHumidityQM
           longName: "Moisture quality marker"
 
-        - name: "QualityMarker/eastward_wind"
+        - name: "QualityMarker/windEastward"
           coordinates: "longitude latitude Level"
           source: variables/windQM
           longName: "U-Component of wind quality marker"
 
-        - name: "QualityMarker/northward_wind"
+        - name: "QualityMarker/windNorthward"
           coordinates: "longitude latitude Level"
           source: variables/windQM
           longName: "V-Component of wind quality marker"
 
-        - name: "QualityMarker/sea_surface_temperature"
+        - name: "QualityMarker/seaSurfaceTemperature"
           coordinates: "longitude latitude Depth"
           source: variables/seaSurfaceTemperatureQM
           longName: "Sea surface temperature quality marker"
@@ -275,61 +275,61 @@ observations:
           longName: "Pressure ObsError"
           units: "Pa"
 
-        - name: "ObsError/air_temperature"
+        - name: "ObsError/airTemperature"
           coordinates: "longitude latitude Level"
           source: variables/airTemperatureError
           longName: "Temperature ObsError"
           units: "K"
 
-        - name: "ObsError/relative_humidity"
+        - name: "ObsError/relativeHumidity"
           coordinates: "longitude latitude Level"
           source: variables/relativeHumidityError
           longName: "Relative Humidity ObsError"
           units: "1"
 
-        - name: "ObsError/eastward_wind"
+        - name: "ObsError/windEastward"
           coordinates: "longitude latitude Level"
           source: variables/windError
           longName: "Easthward wind ObsError"
           units: "m s-1"
 
-        - name: "ObsError/northward_wind"
+        - name: "ObsError/windNorthward"
           coordinates: "longitude latitude Level"
           source: variables/windError
           longName: "Northward wind ObsError"
           units: "m s-1"
 
-        - name: "ObsError/sea_surface_temperature"
+        - name: "ObsError/seaSurfaceTemperature"
           coordinates: "longitude latitude Depth"
           source: variables/seaSurfaceTemperatureError
           longName: "Sea surface temperature ObsError"
           units: "K"
 
 # Extra Info
-        - name: "MetaData/verticalSignificance"
-          coordinates: "longitude latitude"
-          source: variables/verticalSignificance
-          longName: "Vertical Significance"
-
-        - name: "MetaData/prepbufrType"
-          coordinates: "longitude latitude"
-          source: variables/prepbufrReportType
-          longName: "Prepbufr report type"
-
-        - name: "MetaData/dumpReportType"
-          coordinates: "longitude latitude"
-          source: variables/dumpReportType
-          longName: "Data dump report type"
-
-        - name: "MetaData/prepbufrDataLvlCat"
-          coordinates: "longitude latitude Level"
-          source: variables/prepbufrDataLvlCat
-          longName: "Prepbufr data level category"
-
-        - name: "MetaData/waterTemperatureMethod"
-          coordinates: "longitude latitude"
-          source: variables/waterTemperatureMethod
-          longName: "Method of sea surface temperature measurement"
+        # - name: "MetaData/verticalSignificance"
+        #   coordinates: "longitude latitude"
+        #   source: variables/verticalSignificance
+        #   longName: "Vertical Significance"
+
+        # - name: "MetaData/prepbufrType"
+        #   coordinates: "longitude latitude"
+        #   source: variables/prepbufrReportType
+        #   longName: "Prepbufr report type"
+
+        # - name: "MetaData/dumpReportType"
+        #   coordinates: "longitude latitude"
+        #   source: variables/dumpReportType
+        #   longName: "Data dump report type"
+
+        # - name: "MetaData/prepbufrDataLvlCat"
+        #   coordinates: "longitude latitude Level"
+        #   source: variables/prepbufrDataLvlCat
+        #   longName: "Prepbufr data level category"
+
+        # - name: "MetaData/waterTemperatureMethod"
+        #   coordinates: "longitude latitude"
+        #   source: variables/waterTemperatureMethod
+        #   longName: "Method of sea surface temperature measurement"
 
         - name: "ObsValue/presentWeather"
           coordinates: "longitude latitude"
@@ -340,6 +340,7 @@ observations:
           coordinates: "longitude latitude"
           source: variables/cloudAmount
           longName: "Cloud Amount"
+          units: "1"
 
         - name: "ObsValue/cloudType"
           coordinates: "longitude latitude"
@@ -358,7 +359,7 @@ observations:
           longName: "Cloud Cover"
           units: "1"
 
-        - name: "MetaData/depthBelowSeaSurface"
+        - name: "MetaData/depthBelowWaterSurface"
           coordinates: "longitude latitude Depth"
           source: variables/depthBelowSeaSurface
           longName: "Depth below sea surface"
diff --git a/test/testinput/afwa_snod_24km.grib b/test/testinput/afwa_snod_24km.grib
deleted file mode 100644
index 4a831391c..000000000
--- a/test/testinput/afwa_snod_24km.grib
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:b137f42aa86c587dbcbd9f194789fd4df70d62af6c3628be9051531954f988a3
-size 2679
diff --git a/test/testinput/aircar_BUFR2ioda.yaml b/test/testinput/aircar_BUFR2ioda.yaml
index 71d37d752..c557ea6bb 100644
--- a/test/testinput/aircar_BUFR2ioda.yaml
+++ b/test/testinput/aircar_BUFR2ioda.yaml
@@ -14,7 +14,7 @@ observations:
         - mnemonics: [YEAR, MNTH, DAYS, HOUR, MINU, SECO]
         - mnemonics: [ACID, ACRN]
         - mnemonics: [CLAT, CLON]
-        - mnemonics: [IALT, DPOF, ROLQ]
+        - mnemonics: [IALT, DPOF, ROLL, ROLQ]
         - mnemonics: [MIXR, TMDB, WDIR, WSPD]
         - mnemonics: [TASP, ACTH]
 
@@ -34,19 +34,21 @@ observations:
             mnemonic: CLON
           height:
             mnemonic: IALT
-          aircraftFlightNum:
+          aircraftIdentifier:
             mnemonic: ACID
-          aircraftRegistrationNum:
+          aircraftTailNumber:
             mnemonic: ACRN
           aircraftFlightPhase:
             mnemonic: DPOF
-          aircraftTrueAirspeed:
+          aircraftVelocity:
             mnemonic: TASP
           aircraftHeading:
             mnemonic: ACTH
           aircraftRollAngle:
+            mnemonic: ROLL
+          aircraftRollAngleQuality:
             mnemonic: ROLQ
-          temperatureAir:
+          airTemperature:
             mnemonic: TMDB
           waterVaporMixingRatio:
             mnemonic: MIXR
@@ -60,94 +62,100 @@ observations:
       obsdataout: "./testrun/gdas.aircar.t00z.20210801.nc"
 
       dimensions:
-        - name: "nlocs"
+        - name: "Location"
           size: variables/latitude.nrows
 
       variables:
         - name: "MetaData/dateTime"
           source: variables/timestamp
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
         - name: "MetaData/latitude"
           source: variables/latitude
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Latitude"
           units: "degrees_north"
 
         - name: "MetaData/longitude"
           source: variables/longitude
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Longitude"
           units: "degrees_east"
 
         - name: "MetaData/height"
           source: variables/height
-          dimensions: [ "nlocs" ]
-          longName: "Pressure altitude"
+          dimensions: [ "Location" ]
+          longName: "Height"
           units: "m"
 
-        - name: "MetaData/aircraftRegistrationNum"
-          source: variables/aircraftRegistrationNum
-          dimensions: [ "nlocs" ]
+        - name: "MetaData/aircraftTailNumber"
+          source: variables/aircraftTailNumber
+          dimensions: [ "Location" ]
           longName: "Aircraft registration number or other ID"
           units: "none"
 
-        - name: "MetaData/aircraftFlightNum"
-          source: variables/aircraftFlightNum
-          dimensions: [ "nlocs" ]
+        - name: "MetaData/aircraftIdentifier"
+          source: variables/aircraftIdentifier
+          dimensions: [ "Location" ]
           longName: "Aircraft flight number"
           units: "none"
 
         - name: "MetaData/aircraftFlightPhase"
           source: variables/aircraftFlightPhase
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Aircraft flight phase (ascending/descending/level)"
           units: "none"
 
-        - name: "MetaData/aircraftTrueAirspeed"
-          source: variables/aircraftTrueAirspeed
-          dimensions: [ "nlocs" ]
-          longName: "Aircraft true airspeed"
+        - name: "MetaData/aircraftVelocity"
+          source: variables/aircraftVelocity
+          dimensions: [ "Location" ]
+          longName: "Aircraft velocity"
           units: "m s-1"
 
         - name: "MetaData/aircraftHeading"
           source: variables/aircraftHeading
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Aircraft heading"
-          units: "deg"
+          units: "degrees"
 
         - name: "MetaData/aircraftRollAngle"
           source: variables/aircraftRollAngle
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
+          longName: "Aircraft roll angle"
+          units: "degrees"
+
+        - name: "MetaData/aircraftRollAngleQuality"
+          source: variables/aircraftRollAngleQuality
+          dimensions: [ "Location" ]
           longName: "Aircraft roll angle quality"
           units: "none"
 
-        - name: "ObsValue/air_temperature"
+        - name: "ObsValue/airTemperature"
+          source: variables/airTemperature
           coordinates: "longitude latitude"
-          source: variables/temperatureAir
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Air Temperature"
           units: "K"
 
-        - name: "ObsValue/specific_humidity"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/waterVaporMixingRatio"
           source: variables/waterVaporMixingRatio
-          dimensions: [ "nlocs" ]
-          longName: "specific humidity"
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
+          longName: "Water Vapor Mixing Ratio"
           units: "kg kg-1"
 
-        - name: "ObsValue/wind_direction"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/windDirection"
           source: variables/windDirection
-          dimensions: [ "nlocs" ]
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
           longName: "Wind Direction"
           units: "degrees"
 
-        - name: "ObsValue/wind_speed"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/windSpeed"
           source: variables/windSpeed
-          dimensions: [ "nlocs" ]
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
           longName: "Wind Speed"
           units: "m s-1"
diff --git a/test/testinput/airep_wmoBUFR2ioda.yaml b/test/testinput/airep_wmoBUFR2ioda.yaml
index 3a7b989c0..659c21483 100644
--- a/test/testinput/airep_wmoBUFR2ioda.yaml
+++ b/test/testinput/airep_wmoBUFR2ioda.yaml
@@ -28,13 +28,13 @@ observations:
             mnemonic: CLATH
           longitude:
             mnemonic: CLONH
-          altitude:
+          height:
             mnemonic: HMSL
-          aircraftFlightNum:
+          aircraftIdentifier:
             mnemonic: ACID
           aircraftFlightPhase:
             mnemonic: POAF
-          temperatureAir:
+          airTemperature:
             mnemonic: TMDBST
           windDirection:
             mnemonic: WDIR
@@ -46,63 +46,63 @@ observations:
       obsdataout: "./testrun/airep_multi.nc"
 
       dimensions:
-        - name: "nlocs"
+        - name: "Location"
           size: variables/latitude.nrows
 
       variables:
         - name: "MetaData/dateTime"
           source: variables/timestamp
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
         - name: "MetaData/latitude"
           source: variables/latitude
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Latitude"
           units: "degrees_north"
 
         - name: "MetaData/longitude"
           source: variables/longitude
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Longitude"
           units: "degrees_east"
 
-        - name: "MetaData/altitude"
-          source: variables/altitude
-          dimensions: [ "nlocs" ]
-          longName: "Altitude"
+        - name: "MetaData/height"
+          source: variables/height
+          dimensions: [ "Location" ]
+          longName: "Height"
           units: "m"
 
-        - name: "MetaData/aircraftFlightNum"
-          source: variables/aircraftFlightNum
-          dimensions: [ "nlocs" ]
-          longName: "Aircraft flight number"
+        - name: "MetaData/aircraftIdentifier"
+          source: variables/aircraftIdentifier
+          dimensions: [ "Location" ]
+          longName: "Aircraft identifier"
           units: ""
 
         - name: "MetaData/aircraftFlightPhase"
           source: variables/aircraftFlightPhase
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Aircraft flight phase (ascending/descending/level)"
           units: ""
 
-        - name: "ObsValue/temperatureAir"
+        - name: "ObsValue/airTemperature"
+          source: variables/airTemperature
           coordinates: "longitude latitude"
-          source: variables/temperatureAir
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Air Temperature"
           units: "K"
 
         - name: "ObsValue/windDirection"
-          coordinates: "longitude latitude"
           source: variables/windDirection
-          dimensions: [ "nlocs" ]
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
           longName: "Wind Direction"
-          units: "degrees true"
+          units: "degrees"
 
         - name: "ObsValue/windSpeed"
-          coordinates: "longitude latitude"
           source: variables/windSpeed
-          dimensions: [ "nlocs" ]
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
           longName: "Wind Speed"
-          units: "m/s"
+          units: "m s-1"
diff --git a/test/testinput/bufr_airs_v2.yaml b/test/testinput/bufr_airs.yaml
similarity index 63%
rename from test/testinput/bufr_airs_v2.yaml
rename to test/testinput/bufr_airs.yaml
index 80126e211..6a554197f 100644
--- a/test/testinput/bufr_airs_v2.yaml
+++ b/test/testinput/bufr_airs.yaml
@@ -6,14 +6,16 @@
 observations:
   - obs space:
       name: bufr
-      obsdatain: "./testinput/gdas.t12z.airsev.tm00.bufr_d"
+      obsdatain: "./testinput/gdas.t00z.airsev.tm00.bufr_d"
       mnemonicSets:
-        - mnemonics: [YEAR, MNTH, DAYS, HOUR, MINU, CLATH, CLONH]
-        - mnemonics: [SAID, SIID, FOVN, SAZA, SOZA, BEARAZ, SOLAZI, TOCC]
-#       - mnemonics: [ALBD]
-#         channels: 1-4
-        - mnemonics: [CHNM, LOGRCW, TMBR]
-          channels: 1-10
+        - mnemonics: [SAID, SLNM, SOZA, SOLAZI]
+        - mnemonics: [YEAR, MNTH, DAYS, HOUR, MINU, SECO]
+        - mnemonics: [CLATH, CLONH, SAZA, BEARAZ, FOVN]
+        - mnemonics: [ALBD]
+          channels: 1-4
+        - mnemonics: [CHNM, TMBR]
+          channels: 1-15
+        - mnemonics: [TOCC]
 
       exports:
         variables:
@@ -24,18 +26,15 @@ observations:
               day: DAYS
               hour: HOUR
               minute: MINU
+              second: SECO
           latitude:
             mnemonic: CLATH
           longitude:
             mnemonic: CLONH
-          satelliteId:
+          satelliteIdentifier:
             mnemonic: SAID
-          sensorID:
-            mnemonic: SIID
-          channelNumber:
+          sensorChannelNumber:
             mnemonic: CHNM
-          centralWavenumber:
-            mnemonic: LOGRCW
           fieldOfViewNumber:
             mnemonic: FOVN
           solarZenithAngle:
@@ -48,127 +47,123 @@ observations:
             mnemonic: BEARAZ
           cloudAmount:
             mnemonic: TOCC
+            transforms:
+              - scale: 0.01
 #         albedo:
 #           mnemonic: ALBD
+#           transforms:
+#             - scale: 0.01
           brightnessTemperature:
             mnemonic: TMBR
 
     ioda:
       backend: netcdf
-      obsdataout: "./testrun/gdas.t12z.airsev.tm00.nc"
+      obsdataout: "./testrun/gdas.t00z.airsev.tm00.nc"
 
       dimensions:
-        - name: "nlocs"
-          size: variables/brightnessTemperature.nrows
-        - name: "nchans"
+        - name: "Location"
+          size: variables/latitude.nrows
+        - name: "Channel"
           size: variables/brightnessTemperature.ncols
-#       - name: "nchans_albedo"
-#         size: variables/albedo.ncols
 
       globals:
-        - name: "MetaData/platformCommonName"
+        - name: "platformCommonName"
           type: string
           value: "AIRS"
 
-        - name: "MetaData/platformLongDescription"
+        - name: "platformLongDescription"
           type: string
           value: "MTYP 021-249 EVERY FOV AIRS/AMSU-A/HSB 1B BTEMPS(AQUA)"
 
       variables:
-        - name: "MetaData/satelliteId"
-          source: variables/satelliteId
-          dimensions: ["nlocs"]
-          longName: "Satellite identification"
-          units: ""
-
-        - name: "MetaData/channelNumber"
-          source: variables/channelNumber
-          dimensions: ["nchans"]
-          longName: "Channel number"
-          units: ""
-
-        - name: "MetaData/centralWavenumber"
-          source: variables/centralWavenumber
-          dimensions: ["nchans"]
-          longName: "Central wavenumber (log10)"
+        - name: "MetaData/satelliteIdentifier"
+          source: variables/satelliteIdentifier
+          dimensions: ["Location"]
+          longName: "Satellite identifier"
           units: ""
 
         - name: "MetaData/latitude"
           source: variables/latitude
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Latitude"
           units: "degrees_north"
           range: [-90, 90]
 
         - name: "MetaData/longitude"
           source: variables/longitude
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Longitude"
           units: "degrees_east"
           range: [-180, 180]
 
         - name: "MetaData/dateTime"
           source: variables/timestamp
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
         - name: "MetaData/fieldOfViewNumber"
           source: variables/fieldOfViewNumber
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Field of view number"
           units: ""
 
         - name: "MetaData/solarZenithAngle"
           source: variables/solarZenithAngle
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Solar zenith angle"
           units: "degrees"
           range: [0, 180]
 
         - name: "MetaData/solarAzimuthAngle"
           source: variables/solarAzimuthAngle
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Solar azimuth angle"
           units: "degrees"
           range: [0, 360]
 
         - name: "MetaData/sensorZenithAngle"
           source: variables/sensorZenithAngle
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Sensor zenith angle"
           units: "degrees"
           range: [0, 90]
 
         - name: "MetaData/sensorAzimuthAngle"
           source: variables/sensorAzimuthAngle
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Sensor azimuth angle"
           units: "degrees"
           range: [0, 360]
 
-        - name: "MetaData/cloudAmount"
+        - name: "MetaData/sensorChannelNumber"
+          source: variables/sensorChannelNumber
+          dimensions: ["Channel"]
+          longName: "Channel number"
+          units: ""
+
+        - name: "ObsValue/cloudAmount"
           coordinates: "longitude latitude"
           source: variables/cloudAmount
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Cloud fraction"
-          units: "percent"
-          range: [0, 100]
+          units: "1"
+          range: [0, 1]
 
 #       - name: "ObsValue/albedo"
-#         coordinates: "longitude latitude nchans_albedo"
+#         coordinates: "longitude latitude Channel"
 #         source: variables/albedo
-#         dimensions: ["nlocs", "nchans_albedo"]
+#         dimensions: ["Location", "Channel"]
 #         longName: "albedo"
-#         units: "percent"
-#         range: [0, 100]
+#         units: "1"
+#         range: [0, 1]
 #         chunks: [1000, 15]
 #         compressionLevel: 4
 
         - name: "ObsValue/brightnessTemperature"
-          coordinates: "longitude latitude nchans"
+          coordinates: "longitude latitude Channel"
           source: variables/brightnessTemperature
-          dimensions: ["nlocs", "nchans"]
+          dimensions: ["Location", "Channel"]
           longName: "Brightness temperature"
           units: "K"
           range: [120, 500]
diff --git a/test/testinput/bufr_amsua_v2.yaml b/test/testinput/bufr_amsua.yaml
similarity index 71%
rename from test/testinput/bufr_amsua_v2.yaml
rename to test/testinput/bufr_amsua.yaml
index 16c179110..d7a898804 100644
--- a/test/testinput/bufr_amsua_v2.yaml
+++ b/test/testinput/bufr_amsua.yaml
@@ -8,8 +8,8 @@ observations:
       name: bufr
       obsdatain: "./testinput/gdas.t00z.1bamua.tm00.bufr_d"
       mnemonicSets:
-        - mnemonics: [YEAR, MNTH, DAYS, HOUR, MINU, CLAT, CLON]
-        - mnemonics: [SAID, SIID, FOVN, SAZA, SOZA, BEARAZ, SOLAZI]
+        - mnemonics: [YEAR, MNTH, DAYS, HOUR, MINU, SECO, CLAT, CLON]
+        - mnemonics: [SAID, FOVN, LSQL, SAZA, SOZA, SOLAZI, BEARAZ]
         - mnemonics: [CHNM, TMBR]
           channels: 1-15
 
@@ -22,16 +22,13 @@ observations:
               day: DAYS
               hour: HOUR
               minute: MINU
+              second: SECO
           latitude:
             mnemonic: CLAT
           longitude:
             mnemonic: CLON
-          satelliteId:
+          satelliteIdentifier:
             mnemonic: SAID
-          sensorID:
-            mnemonic: SIID
-          channelNumber:
-            mnemonic: CHNM
           fieldOfViewNumber:
             mnemonic: FOVN
           solarZenithAngle:
@@ -42,6 +39,8 @@ observations:
             mnemonic: SAZA
           sensorAzimuthAngle:
             mnemonic: BEARAZ
+          sensorChannelNumber:
+            mnemonic: CHNM
           brightnessTemperature:
             mnemonic: TMBR
 
@@ -50,96 +49,96 @@ observations:
       obsdataout: "./testrun/gdas.t00z.1bamsua.tm00.nc"
 
       dimensions:
-        - name: "nlocs"
-          size: variables/brightnessTemperature.nrows
-        - name: "nchans"
+        - name: "Location"
+          size: variables/latitude.nrows
+        - name: "Channel"
           size: variables/brightnessTemperature.ncols
 
       globals:
-        - name: "MetaData/platformCommonName"
+        - name: "platformCommonName"
           type: string
           value: "AMSUA"
 
-        - name: "MetaData/platformLongDescription"
+        - name: "platformLongDescription"
           type: string
           value: "MTYP 021-023 PROC AMSU-A 1B Tb (NOAA-15-19, METOP-1,2)"
 
-        - name: "MetaData/sensorCentralFrequency"
-          type: floatVector
-          value: [23.8, 31.4, 50.3, 52.8, 53.596, 54.4, 54.94, 55.5, 57.290,
-                  57.290, 57.290, 57.290, 57.290, 57.290, 89.0]
+#       - name: "sensorCentralFrequency"
+#         type: floatVector
+#         value: [23.8, 31.4, 50.3, 52.8, 53.596, 54.4, 54.94, 55.5, 57.290,
+#                 57.290, 57.290, 57.290, 57.290, 57.290, 89.0]
 
       variables:
-        - name: "MetaData/satelliteId"
-          source: variables/satelliteId
-          dimensions: ["nlocs"]
-          longName: "Satellite identification"
-          units: ""
-
-        - name: "MetaData/channelNumber"
-          source: variables/channelNumber
-          dimensions: ["nchans"]
-          longName: "Channel number"
+        - name: "MetaData/satelliteIdentifier"
+          source: variables/satelliteIdentifier
+          dimensions: ["Location"]
+          longName: "Satellite identifier"
           units: ""
 
         - name: "MetaData/latitude"
           source: variables/latitude
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Latitude"
           units: "degrees_north"
           range: [-90, 90]
 
         - name: "MetaData/longitude"
           source: variables/longitude
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Longitude"
           units: "degrees_east"
           range: [-180, 180]
 
         - name: "MetaData/dateTime"
           source: variables/timestamp
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
         - name: "MetaData/fieldOfViewNumber"
           source: variables/fieldOfViewNumber
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Field of view number"
           units: ""
 
         - name: "MetaData/solarZenithAngle"
           source: variables/solarZenithAngle
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Solar zenith angle"
           units: "degrees"
           range: [0, 180]
 
         - name: "MetaData/solarAzimuthAngle"
           source: variables/solarAzimuthAngle
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Solar azimuth angle"
           units: "degrees"
           range: [0, 360]
 
         - name: "MetaData/sensorZenithAngle"
           source: variables/sensorZenithAngle
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Sensor zenith angle"
           units: "degrees"
           range: [0, 90]
 
         - name: "MetaData/sensorAzimuthAngle"
           source: variables/sensorAzimuthAngle
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Sensor azimuth angle"
           units: "degrees"
           range: [0, 360]
 
+        - name: "MetaData/sensorChannelNumber"
+          source: variables/sensorChannelNumber
+          dimensions: ["Channel"]
+          longName: "Channel number"
+          units: ""
+
         - name: "ObsValue/brightnessTemperature"
-          coordinates: "longitude latitude nchans"
+          coordinates: "longitude latitude Channel"
           source: variables/brightnessTemperature
-          dimensions: ["nlocs", "nchans"]
+          dimensions: ["Location", "Channel"]
           longName: "Brightness temperature"
           units: "K"
           range: [120, 500]
diff --git a/test/testinput/bufr_atms_v2.yaml b/test/testinput/bufr_atms.yaml
similarity index 65%
rename from test/testinput/bufr_atms_v2.yaml
rename to test/testinput/bufr_atms.yaml
index afe99788a..0c5fb404c 100644
--- a/test/testinput/bufr_atms_v2.yaml
+++ b/test/testinput/bufr_atms.yaml
@@ -8,8 +8,10 @@ observations:
       name: bufr
       obsdatain: "./testinput/gdas.t00z.atms.tm00.bufr_d"
       mnemonicSets:
-        - mnemonics: [YEAR, MNTH, DAYS, HOUR, MINU, CLATH, CLONH]
-        - mnemonics: [SAID, SIID, FOVN, SAZA, SOZA, BEARAZ, SOLAZI]
+        - mnemonics: [SAID, YEAR, MNTH, DAYS, HOUR, MINU, SECO]
+        - mnemonics: [SLNM, FOVN, ATMSSQ]
+        - mnemonics: [CLATH, CLONH]
+        - mnemonics: [SAZA, BEARAZ, SOZA, SOLAZI]
         - mnemonics: [CHNM, TMBR]
           channels: 1-22
 
@@ -22,26 +24,29 @@ observations:
               day: DAYS
               hour: HOUR
               minute: MINU
+              second: SECO
           latitude:
             mnemonic: CLATH
           longitude:
             mnemonic: CLONH
-          satelliteId:
+          satelliteIdentifier:
             mnemonic: SAID
-          sensorID:
-            mnemonic: SIID
-          channelNumber:
-            mnemonic: CHNM
+          scanLineNumber:
+            mnemonic: SLNM
           fieldOfViewNumber:
             mnemonic: FOVN
-          solarZenithAngle:
-            mnemonic: SOZA
-          solarAzimuthAngle:
-            mnemonic: SOLAZI
+          qualityFlags:
+            mnemonic: ATMSSQ
           sensorZenithAngle:
             mnemonic: SAZA
           sensorAzimuthAngle:
             mnemonic: BEARAZ
+          solarZenithAngle:
+            mnemonic: SOZA
+          solarAzimuthAngle:
+            mnemonic: SOLAZI
+          sensorChannelNumber:
+            mnemonic: CHNM
           brightnessTemperature:
             mnemonic: TMBR
 
@@ -50,98 +55,104 @@ observations:
       obsdataout: "./testrun/gdas.t00z.atms.tm00.nc"
 
       dimensions:
-        - name: "nlocs"
+        - name: "Location"
           size: variables/brightnessTemperature.nrows
-        - name: "nchans"
+        - name: "Channel"
           size: variables/brightnessTemperature.ncols
 
       globals:
-        - name: "MetaData/platformCommonName"
+        - name: "platformCommonName"
           type: string
           value: "ATMS"
 
-        - name: "MetaData/platformLongDescription"
+        - name: "platformLongDescription"
           type: string
           value: "MTYP 021-203 ATMS BRIGHTNESS TEMPERATURE DATA"
 
-        - name: "MetaData/sensorCentralFrequency"
-          type: floatVector
-          value: [23.8, 31.4, 50.3, 51.76, 52.8, 53.596, 54.40, 54.94, 55.50,
-                  57.2903, 57.2903, 57.2903, 57.2903, 57.2903, 57.2903,
-                  88.20, 165.5, 183.31, 183.31, 183.31, 183.31, 183.31]
+#       - name: "sensorCentralFrequency"
+#         type: floatVector
+#         value: [23.8, 31.4, 50.3, 51.76, 52.8, 53.596, 54.40, 54.94, 55.50,
+#                 57.2903, 57.2903, 57.2903, 57.2903, 57.2903, 57.2903,
+#                 88.20, 165.5, 183.31, 183.31, 183.31, 183.31, 183.31]
 
       variables:
-        - name: "MetaData/satelliteId"
-          source: variables/satelliteId
-          dimensions: ["nlocs"]
-          longName: "Satellite identification"
-          units: ""
-
-        - name: "MetaData/channelNumber"
-          source: variables/channelNumber
-          dimensions: ["nchans"]
-          longName: "Channel number"
+        - name: "MetaData/satelliteIdentifier"
+          source: variables/satelliteIdentifier
+          dimensions: ["Location"]
+          longName: "Satellite identifier"
           units: ""
 
         - name: "MetaData/latitude"
           source: variables/latitude
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Latitude"
           units: "degrees_north"
           range: [-90, 90]
 
         - name: "MetaData/longitude"
           source: variables/longitude
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Longitude"
           units: "degrees_east"
           range: [-180, 180]
 
         - name: "MetaData/dateTime"
           source: variables/timestamp
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
         - name: "MetaData/fieldOfViewNumber"
           source: variables/fieldOfViewNumber
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Field of view number"
           units: ""
 
+        - name: "MetaData/scanLineNumber"
+          source: variables/scanLineNumber
+          dimensions: ["Location"]
+          longName: "Scan line number"
+          units: ""
+
         - name: "MetaData/solarZenithAngle"
           source: variables/solarZenithAngle
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Solar zenith angle"
           units: "degrees"
           range: [0, 180]
 
         - name: "MetaData/solarAzimuthAngle"
           source: variables/solarAzimuthAngle
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Solar azimuth angle"
           units: "degrees"
           range: [0, 360]
 
         - name: "MetaData/sensorZenithAngle"
           source: variables/sensorZenithAngle
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Sensor zenith angle"
           units: "degrees"
           range: [0, 90]
 
         - name: "MetaData/sensorAzimuthAngle"
           source: variables/sensorAzimuthAngle
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Sensor azimuth angle"
           units: "degrees"
           range: [0, 360]
 
+        - name: "MetaData/sensorChannelNumber"
+          source: variables/sensorChannelNumber
+          dimensions: ["Channel"]
+          longName: "Channel number"
+          units: ""
+
         - name: "ObsValue/brightnessTemperature"
-          coordinates: "longitude latitude nchans"
+          coordinates: "longitude latitude Channel"
           source: variables/brightnessTemperature
-          dimensions: ["nlocs", "nchans"]
+          dimensions: ["Location", "Channel"]
           longName: "Brightness temperature"
           units: "K"
           range: [120, 500]
-          chunks: [1000, 15]
+          chunks: [1000, 22]
diff --git a/test/testinput/bufr_avhrr_v2.yaml b/test/testinput/bufr_avhrr.yaml
similarity index 65%
rename from test/testinput/bufr_avhrr_v2.yaml
rename to test/testinput/bufr_avhrr.yaml
index 240b7d5d7..1f8b3ccea 100644
--- a/test/testinput/bufr_avhrr_v2.yaml
+++ b/test/testinput/bufr_avhrr.yaml
@@ -8,8 +8,9 @@ observations:
       name: bufr
       obsdatain: "./testinput/gdas.t00z.avcsam.tm00.bufr_d"
       mnemonicSets:
-        - mnemonics: [YEAR, MNTH, DAYS, HOUR, MINU, CLATH, CLONH]
-        - mnemonics: [SAID, FOVN, SAZA, SOZA]
+        - mnemonics: [YEAR, MNTH, DAYS, HOUR, MINU]
+        - mnemonics: [CLATH, CLONH, SAID]
+        - mnemonics: [FOVN, SAZA, SOZA]
         - mnemonics: [INCN, ALBD, TMBR]
           channels : 1-5
 
@@ -26,113 +27,115 @@ observations:
             mnemonic: CLATH
           longitude:
             mnemonic: CLONH
-          satelliteId:
+          satelliteIdentifier:
             mnemonic: SAID
-          channelNumber:
-            mnemonic: INCN
           fieldOfViewNumber:
             mnemonic: FOVN
           solarZenithAngle:
             mnemonic: SOZA
           sensorZenithAngle:
             mnemonic: SAZA
+          sensorChannelNumber:
+            mnemonic: INCN
           albedo:
             mnemonic: ALBD
+            transforms:
+              - scale: 0.01
           brightnessTemperature:
             mnemonic: TMBR
 
     ioda:
       backend: netcdf
-      obsdataout: "./testrun/gdas.t12z.avcsam.tm00.nc"
+      obsdataout: "./testrun/gdas.t00z.avcsam.tm00.nc"
 
       dimensions:
-        - name: "nlocs"
-          size: variables/brightnessTemperature.nrows
-        - name: "nchans"
+        - name: "Location"
+          size: variables/latitude.nrows
+        - name: "Channel"
           size: variables/brightnessTemperature.ncols
 
       globals: 
-        - name: "MetaData/platformCommonName"
+        - name: "platformCommonName"
           type: string
           value: "AVHRR"
 
-        - name: "MetaData/platformLongDescription"
+        - name: "platformLongDescription"
           type: string
           value: "MTYP 021-051 PROC AVHRR(GAC) 1B Tb-CLR & SEA (N-17,N-18,M-2)"
             
-        - name: "MetaData/sensorCentralWavelength"
-          type: floatVector
-          value: [0.630, 0.865, 3.74, 10.8, 12.0]    # μm
+#       - name: "sensorCentralWavelength"
+#         type: floatVector
+#         value: [0.630, 0.865, 3.74, 10.8, 12.0]    # μm
 
       variables:
-        - name: "MetaData/satelliteId"
-          source: variables/satelliteId
-          dimensions: ["nlocs"]
-          longName: "Satellite identification"
-          units: ""
-
-        - name: "MetaData/channelNumber"
-          source: variables/channelNumber
-          dimensions: ["nchans"]
-          longName: "Channel number"
+        - name: "MetaData/satelliteIdentifier"
+          source: variables/satelliteIdentifier
+          dimensions: ["Location"]
+          longName: "Satellite identifier"
           units: ""
 
         - name: "MetaData/latitude"
           source: variables/latitude
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Latitude"
           units: "degrees_north"
           range: [-90, 90]
 
         - name: "MetaData/longitude"
           source: variables/longitude
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Longitude"
           units: "degrees_east"
           range: [-180, 180]
 
         - name: "MetaData/dateTime"
           source: variables/timestamp
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
         - name: "MetaData/fieldOfViewNumber"
           source: variables/fieldOfViewNumber
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Field of view number"
           units: ""
 
         - name: "MetaData/solarZenithAngle"
           source: variables/solarZenithAngle
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Solar zenith angle"
           units: "degrees"
           range: [0, 180]
 
         - name: "MetaData/sensorZenithAngle"
           source: variables/sensorZenithAngle
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Sensor zenith angle"
           units: "degrees"
           range: [0, 90]
 
+        - name: "MetaData/sensorChannelNumber"
+          source: variables/sensorChannelNumber
+          dimensions: ["Channel"]
+          longName: "Channel number"
+          units: ""
+
         - name: "ObsValue/albedo"
-          coordinates: "longitude latitude nchans"
-          source: variables/brightnessTemperature
-          dimensions: ["nlocs", "nchans"]
+          source: variables/albedo
+          coordinates: "longitude latitude Channel"
+          dimensions: ["Location", "Channel"]
           longName: "Albedo"
-          units: ""
-          range: [120, 500]
-          chunks: [1000, 15]
+          units: "1"
+          range: [0, 1.0]
+          chunks: [1000, 5]
           compressionLevel: 4
 
         - name: "ObsValue/brightnessTemperature"
-          coordinates: "longitude latitude nchans"
           source: variables/brightnessTemperature
-          dimensions: ["nlocs", "nchans"]
+          coordinates: "longitude latitude Channel"
+          dimensions: ["Location", "Channel"]
           longName: "Brightness temperature"
           units: "K"
           range: [120, 500]
-          chunks: [1000, 15]
+          chunks: [1000, 5]
           compressionLevel: 4
diff --git a/test/testinput/bufr_cris.yaml b/test/testinput/bufr_cris.yaml
new file mode 100644
index 000000000..52119aee5
--- /dev/null
+++ b/test/testinput/bufr_cris.yaml
@@ -0,0 +1,189 @@
+# (C) Copyright 2021 UCAR
+#
+# This software is licensed under the terms of the Apache Licence Version 2.0
+# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
+
+observations:
+  - obs space:
+      name: bufr
+      obsdatain: "./testinput/gdas.t00z.crisf4.tm00.bufr_d"
+      mnemonicSets:
+        - mnemonics: [SAID, YEAR, MNTH, DAYS, HOUR, MINU, SECO, CLATH, CLONH]
+        - mnemonics: [SAZA, BEARAZ, SOZA, SOLAZI, STKO]
+        - mnemonics: [SLNM, FOVN, HOLS]
+        - mnemonics: [TOCC, HOCT, NSQF]
+        - mnemonics: [STCH, ENCH, CHSF]
+        - mnemonics: [CHNM, SRAD]
+          channels : 1-430
+#       - mnemonics: [CHNM, SCHRAD]      # VIIRS radiance
+#         channels : 1-16
+
+      exports:
+        variables:
+          timestamp:
+            datetime:
+              year: YEAR
+              month: MNTH
+              day: DAYS
+              hour: HOUR
+              minute: MINU
+              second: SECO
+          latitude:
+            mnemonic: CLATH
+          longitude:
+            mnemonic: CLONH
+          satelliteIdentifier:
+            mnemonic: SAID
+          scanLineNumber:
+            mnemonic: SLNM
+          satelliteAscendingFlag:
+            mnemonic: STKO
+          fieldOfViewNumber:
+            mnemonic: FOVN
+          solarZenithAngle:
+            mnemonic: SOZA
+          solarAzimuthAngle:
+            mnemonic: SOLAZI
+          sensorZenithAngle:
+            mnemonic: SAZA
+          sensorAzimuthAngle:
+            mnemonic: BEARAZ
+          cloudAmount:
+            mnemonic: TOCC
+            transforms:
+              - scale: 0.01
+          heightOfTopOfCloud:
+            mnemonic: HOCT
+          qualityFlags:
+            mnemonic: NSQF
+          sensorChannelStart:
+            mnemonic: STCH
+          sensorChannelEnd:
+            mnemonic: ENCH
+          channelScaleFactor:
+            mnemonic: CHSF
+          sensorChannelNumber:
+            mnemonic: CHNM
+          radiance:          # This is actually a scaled radiance, needs a fix
+            mnemonic: SRAD
+
+    ioda:
+      backend: netcdf
+      obsdataout: "./testrun/gdas.t00z.crisf4.tm00.nc"
+
+      dimensions:
+        - name: "Location"
+          size: variables/latitude.nrows
+        - name: "Channel"
+          size: variables/radiance.ncols
+
+      globals: 
+        - name: "platformCommonName"
+          type: string
+          value: "SNPP"
+
+        - name: "platformLongDescription"
+          type: string
+          value: "MTYP 021-206 CrIS FULL SPCTRL RADIANCE (431 CHN SUBSET)"
+
+      variables:
+        - name: "MetaData/satelliteIdentifier"
+          source: variables/satelliteIdentifier
+          dimensions: ["Location"]
+          longName: "Satellite identifier"
+          units: ""
+
+        - name: "MetaData/latitude"
+          source: variables/latitude
+          dimensions: ["Location"]
+          longName: "Latitude"
+          units: "degrees_north"
+          range: [-90, 90]
+
+        - name: "MetaData/longitude"
+          source: variables/longitude
+          dimensions: ["Location"]
+          longName: "Longitude"
+          units: "degrees_east"
+          range: [-180, 180]
+
+        - name: "MetaData/dateTime"
+          source: variables/timestamp
+          dimensions: ["Location"]
+          longName: "dateTime"
+          units: "seconds since 1970-01-01T00:00:00Z"
+
+        - name: "MetaData/fieldOfViewNumber"
+          source: variables/fieldOfViewNumber
+          dimensions: ["Location"]
+          longName: "Field of view number"
+          units: ""
+
+        - name: "MetaData/solarZenithAngle"
+          source: variables/solarZenithAngle
+          dimensions: ["Location"]
+          longName: "Solar zenith angle"
+          units: "degrees"
+          range: [0, 180]
+
+        - name: "MetaData/solarAzimuthAngle"
+          source: variables/solarAzimuthAngle
+          dimensions: ["Location"]
+          longName: "Solar azimuth angle"
+          units: "degrees"
+          range: [0, 360]
+
+        - name: "MetaData/sensorZenithAngle"
+          source: variables/sensorZenithAngle
+          dimensions: ["Location"]
+          longName: "Sensor zenith angle"
+          units: "degrees"
+          range: [0, 90]
+
+        - name: "MetaData/sensorAzimuthAngle"
+          source: variables/sensorAzimuthAngle
+          dimensions: ["Location"]
+          longName: "Sensor azimuth angle"
+          units: "degrees"
+          range: [0, 360]
+
+        - name: "MetaData/scanLineNumber"
+          source: variables/scanLineNumber
+          dimensions: ["Location"]
+          longName: "Sensor scan line number"
+          units: ""
+
+        - name: "MetaData/qualityFlags"
+          source: variables/qualityFlags
+          dimensions: ["Location"]
+          longName: "Scan level quality flags"
+          units: ""
+
+        - name: "MetaData/sensorChannelNumber"
+          source: variables/sensorChannelNumber
+          dimensions: ["Channel"]
+          longName: "Channel number"
+          units: ""
+
+        - name: "ObsValue/cloudAmount"
+          source: variables/cloudAmount
+          coordinates: "longitude latitude"
+          dimensions: ["Location"]
+          longName: "Cloud fraction"
+          units: "1"
+
+        - name: "ObsValue/heightOfTopOfCloud"
+          source: variables/heightOfTopOfCloud
+          coordinates: "longitude latitude"
+          dimensions: ["Location"]
+          longName: "Cloud top height"
+          units: "m"
+
+        - name: "ObsValue/radiance"
+          source: variables/radiance
+          coordinates: "longitude latitude Channel"
+          dimensions: ["Location", "Channel"]
+          longName: "radiance"
+          units: "W m-2 sr-1"
+          chunks: [1000, 430]
+          compressionLevel: 4
diff --git a/test/testinput/bufr_cris_v2.yaml b/test/testinput/bufr_cris_v2.yaml
deleted file mode 100644
index 54f8030d9..000000000
--- a/test/testinput/bufr_cris_v2.yaml
+++ /dev/null
@@ -1,234 +0,0 @@
-# (C) Copyright 2021 UCAR
-#
-# This software is licensed under the terms of the Apache Licence Version 2.0
-# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
-
-observations:
-  - obs space:
-      name: bufr
-      obsdatain: "./testinput/gdas.t00z.crisf4.tm00.bufr_d"
-      mnemonicSets:
-        - mnemonics: [YEAR, MNTH, DAYS, HOUR, MINU, CLAT, CLON]
-        - mnemonics: [SAID, SIID, MYPE, SLNM, FORN, FOVN, SAZA, SOZA, BEARAZ, SOLAZI]
-        - mnemonics: [TOCC, HOCT, SAZA, SOZA, BEARAZ, SOLAZI]
-        - mnemonics: [NSQF, QMRKH]
-        - mnemonics: [NCQF, NFQF]
-          channels : 1-3
-        - mnemonics: [CHNM, SRAD]
-          channels : 1-616
-        - mnemonics: [CHNM, SCHRAD]
-          channels : 1-16
-
-      exports:
-        variables:
-          timestamp:
-            datetime:
-              year: YEAR
-              month: MNTH
-              day: DAYS
-              hour: HOUR
-              minute: MINU
-          latitude:
-            mnemonic: CLAT
-          longitude:
-            mnemonic: CLON
-          satelliteId:
-            mnemonic: SAID
-          sensorID:
-            mnemonic: SIID
-          measurementType:
-            mnemonic: MTYP
-          channelNumber:
-            mnemonic: CHNM
-          sensorScanLineNumber:
-            mnemonic: SLNM
-          fieldOfRegardNumber:
-            mnemonic: FORN
-          fieldOfViewNumber:
-            mnemonic: FOVN
-          solarZenithAngle:
-            mnemonic: SOZA
-          solarAzimuthAngle:
-            mnemonic: SOLAZI
-          sensorZenithAngle:
-            mnemonic: SAZA
-          sensorAzimuthAngle:
-            mnemonic: BEARAZ
-          cloudAmount:
-            mnemonic: TOCC
-          cloudTopHeight:
-            mnemonic: HOCT
-          qualityInfo:
-            mnemonic: QMRKH
-          qualityFlagsScan:
-            mnemonic: NSQF
-          qualityFlagsCalibration:
-            mnemonic: NCQF
-          qualityFlagsFieldOfView:
-            mnemonic: NFQF
-          radiance:
-            mnemonic: SRAD
-          radianceVIIRS:
-            mnemonic: SCHRAD
-
-    ioda:
-      backend: netcdf
-      obsdataout: "./testrun/gdas.t00z.crisf4.tm00.nc"
-
-      dimensions:
-        - name: "nlocs"
-          size: variables/radiance.nrows
-        - name: "nchans"
-          size: variables/radiance.ncols
-        - name: "nchans2"
-          size: variables/radianceVIIRS.ncols
-        - name: "nqualityFlags"
-          size: variables/qualityFlagsCalibration.ncols
-
-      globals: 
-        - name: "MetaData/platformCommonName"
-          type: string
-          value: "SNPP"
-
-        - name: "MetaData/platformLongDescription"
-          type: string
-          value: "MTYP 021-206 CrIS FULL SPCTRL RADIANCE (431 CHN SUBSET)"
-
-      variables:
-        - name: "MetaData/satelliteId"
-          source: variables/satelliteId
-          dimensions: ["nlocs"]
-          longName: "Satellite identification"
-          units: ""
-
-        - name: "MetaData/channelNumber"
-          source: variables/channelNumber
-          dimensions: ["nchans"]
-          longName: "Channel number"
-          units: ""
-
-        - name: "MetaData/measurementType"
-          source: variables/measurementType
-          dimensions: ["nchans"]
-          longName: "Measurement type"
-          units: ""
-
-        - name: "MetaData/latitude"
-          source: variables/latitude
-          dimensions: ["nlocs"]
-          longName: "Latitude"
-          units: "degrees_north"
-          range: [-90, 90]
-
-        - name: "MetaData/longitude"
-          source: variables/longitude
-          dimensions: ["nlocs"]
-          longName: "Longitude"
-          units: "degrees_east"
-          range: [-180, 180]
-
-        - name: "MetaData/dateTime"
-          source: variables/timestamp
-          dimensions: ["nlocs"]
-          longName: "dateTime"
-          units: "seconds since 1970-01-01T00:00:00Z"
-
-        - name: "MetaData/fieldOfRegardNumber"
-          source: variables/fieldOfRegardNumber
-          dimensions: ["nlocs"]
-          longName: "Field of regard number"
-          units: ""
-
-        - name: "MetaData/fieldOfViewNumber"
-          source: variables/fieldOfViewNumber
-          dimensions: ["nlocs"]
-          longName: "Field of view number"
-          units: ""
-
-        - name: "MetaData/solarZenithAngle"
-          source: variables/solarZenithAngle
-          dimensions: ["nlocs"]
-          longName: "Solar zenith angle"
-          units: "degrees"
-          range: [0, 180]
-
-        - name: "MetaData/solarAzimuthAngle"
-          source: variables/solarAzimuthAngle
-          dimensions: ["nlocs"]
-          longName: "Solar azimuth angle"
-          units: "degrees"
-          range: [0, 360]
-
-        - name: "MetaData/sensorZenithAngle"
-          source: variables/sensorZenithAngle
-          dimensions: ["nlocs"]
-          longName: "Sensor zenith angle"
-          units: "degrees"
-          range: [0, 90]
-
-        - name: "MetaData/sensorAzimuthAngle"
-          source: variables/sensorAzimuthAngle
-          dimensions: ["nlocs"]
-          longName: "Sensor azimuth angle"
-          units: "degrees"
-          range: [0, 360]
-
-        - name: "MetaData/sensorScanLineNumber"
-          source: variables/sensorScanLineNumber
-          dimensions: ["nlocs"]
-          longName: "Sensor scan line number"
-          units: ""
-
-        - name: "MetaData/cloudAmount"
-          source: variables/cloudAmount
-          dimensions: ["nlocs"]
-          longName: "Cloud fraction"
-          units: "percent"
-
-        - name: "MetaData/cloudTopHeight"
-          source: variables/cloudTopHeight
-          dimensions: ["nlocs"]
-          longName: "Cloud top height"
-          units: "m"
-
-        - name: "MetaData/qualityInfo"
-          source: variables/qualityInfo
-          dimensions: ["nlocs"]
-          longName: "Quality information"
-          units: ""
-
-        - name: "MetaData/qualityFlagsScan"
-          source: variables/qualityFlagsScan
-          dimensions: ["nlocs"]
-          longName: "Scan level quality flags"
-          units: ""
-
-        - name: "MetaData/qualityFlagsCalibration"
-          source: variables/qualityFlagsCalibration
-          dimensions: ["nlocs", "nqualityFlags"]
-          longName: "Calibration quality flags"
-          units: ""
-
-        - name: "MetaData/qualityFlagsFieldOfView"
-          source: variables/qualityFlagsFieldOfView
-          dimensions: ["nlocs", "nqualityFlags"]
-          longName: "Field of view quality flags"
-          units: ""
-
-        - name: "ObsValue/radiance"
-          coordinates: "longitude latitude nchans"
-          source: variables/radiance
-          dimensions: ["nlocs", "nchans"]
-          longName: "radiance"
-          units: "W m-2 sr-1 cm"
-          chunks: [1000, 15]
-          compressionLevel: 4
-
-        - name: "ObsValue/radianceVIIRS"
-          coordinates: "longitude latitude nchans"
-          source: variables/radianceVIIRS
-          dimensions: ["nlocs", "nchans2"]
-          longName: "radiance"
-          units: "W m-2 sr-1 um-1"
-          chunks: [1000, 15]
-          compressionLevel: 4
diff --git a/test/testinput/bufr_empty_fields.yaml b/test/testinput/bufr_empty_fields.yaml
index f742dfd1f..b2e3f20f9 100644
--- a/test/testinput/bufr_empty_fields.yaml
+++ b/test/testinput/bufr_empty_fields.yaml
@@ -18,6 +18,10 @@ observations:
               day: "*/DAYS"
               hour: "*/HOUR"
               minute: "*/MINU"
+          lat:
+            query: "*/CLAT"
+          lon:
+            query: "*/CLON"
           swellWavesDirection:
             query: "NC000000/WAVSQ3/DOSW"
           heightOfSwellWaves:
@@ -31,26 +35,36 @@ observations:
       obsdataout: "./testrun/bufr_empty_fields.nc"
 
       variables:
-        - name: "MetaData/datetime"
+        - name: "MetaData/dateTime"
           source: variables/timestamp
           longName: "Datetime"
-          units: "datetime"
+          units: "seconds since 1970-01-01T00:00:00Z"
 
-        - name: "ObsValue/swellWavesDirection"
+        - name: "MetaData/latitude"
+          source: variables/lat
+          longName: "latitude"
+          units: "degree_north"
+
+        - name: "MetaData/longitude"
+          source: variables/lon
+          longName: "longitude"
+          units: "degree_east"
+
+        - name: "ObsValue/meanWavePropagationDirection"
           coordinates: "longitude latitude"
           source: variables/swellWavesDirection
           longName: "Swell Waves Direction"
-          units: "Degrees True"
+          units: "degree"
 
-        - name: "ObsValue/heightOfSwellWaves"
+        - name: "ObsValue/heightOfWaves"
           coordinates: "longitude latitude"
           source: variables/heightOfSwellWaves
           longName: "Height of Swell Waves"
-          units: "Meter"
+          units: "m"
 
-        - name: "ObsValue/periodOfSwellWaves"
+        - name: "ObsValue/meanPeriodOfWaves"
           coordinates: "longitude latitude"
           source: variables/periodOfSwellWaves
           longName: "Period of Swell Waves"
-          units: "Second"
+          units: "s"
 
diff --git a/test/testinput/bufr_filter_split.yaml b/test/testinput/bufr_filter_split.yaml
index 24b71b01b..5ef6f01aa 100644
--- a/test/testinput/bufr_filter_split.yaml
+++ b/test/testinput/bufr_filter_split.yaml
@@ -22,7 +22,7 @@ observations:
             query: "*/CLON"
           latitude:
             query: "*/CLAT"
-          radiance:
+          brightnessTemp:
             query: "[*/BRITCSTC/TMBR, */BRIT/TMBR]"
 
         filters:
@@ -56,27 +56,27 @@ observations:
             - "*/BRIT"
 
       variables:
-        - name: "dateTime@MetaData"
+        - name: "MetaData/dateTime"
           source: variables/timestamp
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
-        - name: "latitude@MetaData"
+        - name: "MetaData/latitude"
           source: variables/latitude
           longName: "Latitude"
           units: "degrees_north"
           range: [-90, 90]
 
-        - name: "longitude@MetaData"
+        - name: "MetaData/longitude"
           source: variables/longitude
           longName: "Longitude"
           units: "degrees_east"
           range: [-180, 180]
 
-        - name: "radiance@ObsValue"
+        - name: "ObsValue/brightnessTemperature"
           coordinates: "longitude latitude Channel"
-          source: variables/radiance
-          longName: "Radiance"
+          source: variables/brightnessTemp
+          longName: "Brightness temperature"
           units: "K"
           range: [120, 500]
           chunks: [1000, 15]
diff --git a/test/testinput/bufr_filtering.yaml b/test/testinput/bufr_filtering.yaml
index b16f1128e..463fd4466 100644
--- a/test/testinput/bufr_filtering.yaml
+++ b/test/testinput/bufr_filtering.yaml
@@ -48,18 +48,18 @@ observations:
             - "*/BRIT"
 
       variables:
-        - name: "dateTime@MetaData"
+        - name: "MetaData/dateTime"
           source: variables/timestamp
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
-        - name: "latitude@MetaData"
+        - name: "MetaData/latitude"
           source: variables/latitude
           longName: "Latitude"
           units: "degrees_north"
           range: [-90, 90]
 
-        - name: "longitude@MetaData"
+        - name: "MetaData/longitude"
           source: variables/longitude
           longName: "Longitude"
           units: "degrees_east"
diff --git a/test/testinput/bufr_hirs_v2.yaml b/test/testinput/bufr_hirs_v2.yaml
deleted file mode 100644
index 310acfa1b..000000000
--- a/test/testinput/bufr_hirs_v2.yaml
+++ /dev/null
@@ -1,147 +0,0 @@
-# (C) Copyright 2021 UCAR
-#
-# This software is licensed under the terms of the Apache Licence Version 2.0
-# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
-
-observations:
-  - obs space:
-      name: bufr
-      obsdatain: "./testinput/gdas.t00z.1bhrs4.tm00.bufr_d"
-      mnemonicSets:
-        - mnemonics: [YEAR, MNTH, DAYS, HOUR, MINU, CLAT, CLON]
-        - mnemonics: [SAID, SIID, FOVN, SAZA, SOZA, BEARAZ, SOLAZI]
-        - mnemonics: [CHNM, TMBR]
-          channels: 1-20
-
-      exports:
-        variables:
-          timestamp:
-            datetime:
-              year: YEAR
-              month: MNTH
-              day: DAYS
-              hour: HOUR
-              minute: MINU
-          latitude:
-            mnemonic: CLAT
-          longitude:
-            mnemonic: CLON
-          satelliteId:
-            mnemonic: SAID
-          sensorID:
-            mnemonic: SIID
-          channelNumber:
-            mnemonic: CHNM
-          fieldOfViewNumber:
-            mnemonic: FOVN
-          solarZenithAngle:
-            mnemonic: SOZA
-          solarAzimuthAngle:
-            mnemonic: SOLAZI
-          sensorZenithAngle:
-            mnemonic: SAZA
-          sensorAzimuthAngle:
-            mnemonic: BEARAZ
-          brightnessTemperature:
-            mnemonic: TMBR
-
-    ioda:
-      backend: netcdf
-      obsdataout: "./testrun/gdas.t00z.hirs.tm00.nc"
-
-      dimensions:
-        - name: "nlocs"
-          size: variables/brightnessTemperature.nrows
-        - name: "nchans"
-          size: variables/brightnessTemperature.ncols
-
-      globals:
-        - name: "MetaData/platformCommonName"
-          type: string
-          value: "HIRS"
-
-        - name: "MetaData/platformLongDescription"
-          type: string
-          value: "MTYP 021-028 PROC HIRS-4 1B Tb (NOAA-18-19, METOP-1,2)"
-
-#       - name: "MetaData/sensorCentralFrequency"
-#         type: floatVector
-#         value: [23.8, 31.4, 50.3, 51.76, 52.8, 53.596, 54.40, 54.94, 55.50,
-#                 57.2903, 57.2903, 57.2903, 57.2903, 57.2903, 57.2903,
-#                 88.20, 165.5, 183.31, 183.31, 183.31, 183.31, 183.31]
-
-      variables:
-        - name: "MetaData/satelliteId"
-          source: variables/satelliteId
-          dimensions: ["nlocs"]
-          longName: "Satellite identification"
-          units: ""
-
-        - name: "MetaData/channelNumber"
-          source: variables/channelNumber
-          dimensions: ["nchans"]
-          longName: "Channel number"
-          units: ""
-
-        - name: "MetaData/latitude"
-          source: variables/latitude
-          dimensions: ["nlocs"]
-          longName: "Latitude"
-          units: "degrees_north"
-          range: [-90, 90]
-
-        - name: "MetaData/longitude"
-          source: variables/longitude
-          dimensions: ["nlocs"]
-          longName: "Longitude"
-          units: "degrees_east"
-          range: [-180, 180]
-
-        - name: "MetaData/dateTime"
-          source: variables/timestamp
-          dimensions: ["nlocs"]
-          longName: "dateTime"
-          units: "seconds since 1970-01-01T00:00:00Z"
-
-        - name: "MetaData/fieldOfViewNumber"
-          source: variables/fieldOfViewNumber
-          dimensions: ["nlocs"]
-          longName: "Field of view number"
-          units: ""
-
-        - name: "MetaData/solarZenithAngle"
-          source: variables/solarZenithAngle
-          dimensions: ["nlocs"]
-          longName: "Solar zenith angle"
-          units: "degrees"
-          range: [0, 180]
-
-        - name: "MetaData/solarAzimuthAngle"
-          source: variables/solarAzimuthAngle
-          dimensions: ["nlocs"]
-          longName: "Solar azimuth angle"
-          units: "degrees"
-          range: [0, 360]
-
-        - name: "MetaData/sensorZenithAngle"
-          source: variables/sensorZenithAngle
-          dimensions: ["nlocs"]
-          longName: "Sensor zenith angle"
-          units: "degrees"
-          range: [0, 90]
-
-        - name: "MetaData/sensorAzimuthAngle"
-          source: variables/sensorAzimuthAngle
-          dimensions: ["nlocs"]
-          longName: "Sensor azimuth angle"
-          units: "degrees"
-          range: [0, 360]
-
-        - name: "ObsValue/brightnessTemperature"
-          coordinates: "longitude latitude nchans"
-          source: variables/brightnessTemperature
-          dimensions: ["nlocs", "nchans"]
-          longName: "Brightness temperature"
-          units: "K"
-          range: [120, 500]
-          chunks: [1000, 15]
diff --git a/test/testinput/bufr_hrs.yaml b/test/testinput/bufr_hrs.yaml
index 1c99f8988..e63d3199e 100644
--- a/test/testinput/bufr_hrs.yaml
+++ b/test/testinput/bufr_hrs.yaml
@@ -25,7 +25,7 @@ observations:
             query: "*/CLAT"
           channel:
             query: "[*/BRITCSTC/CHNM, */BRIT/CHNM]"
-          radiance:
+          brightnessTemp:
             query: "[*/BRITCSTC/TMBR, */BRIT/TMBR]"
 
     ioda:
@@ -37,29 +37,29 @@ observations:
           paths:
             - "*/BRIT"
             - "*/BRITCSTC"
-#          source: variables/channel
+          source: variables/channel
 
       variables:
-        - name: "dateTime@MetaData"
+        - name: "MetaData/dateTime"
           source: variables/timestamp
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
-        - name: "latitude@MetaData"
+        - name: "MetaData/latitude"
           source: variables/latitude
           longName: "Latitude"
           units: "degrees_north"
           range: [-90, 90]
 
-        - name: "longitude@MetaData"
+        - name: "MetaData/longitude"
           source: variables/longitude
           longName: "Longitude"
           units: "degrees_east"
           range: [-180, 180]
 
-        - name: "radiance@ObsValue"
+        - name: "ObsValue/brightnessTemperature"
           coordinates: "longitude latitude Channel"
-          source: variables/radiance
-          longName: "Radiance"
+          source: variables/brightnessTemp
+          longName: "Brightness temperature"
           units: "K"
           range: [120, 500]
diff --git a/test/testinput/bufr_iasi.yaml b/test/testinput/bufr_iasi.yaml
new file mode 100644
index 000000000..2bc2beed8
--- /dev/null
+++ b/test/testinput/bufr_iasi.yaml
@@ -0,0 +1,176 @@
+# (C) Copyright 2022 UCAR
+#
+# This software is licensed under the terms of the Apache Licence Version 2.0
+# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
+
+observations:
+  - obs space:
+      name: bufr
+      obsdatain: "./testinput/gdas.t00z.mtiasi.tm00.bufr_d"
+      mnemonicSets:
+        - mnemonics: [SAID, YEAR, MNTH, DAYS, HOUR, MINU, SECO]
+        - mnemonics: [CLATH, CLONH, SAZA, BEARAZ, SOZA, SOLAZI, FOVN, SLNM]
+        - mnemonics: [STCH, ENCH, CHSF]
+          channels: 1-10
+        - mnemonics: [CHNM, SCRA]
+          channels: 1-616
+
+      exports:
+        variables:
+          timestamp:
+            datetime:
+              year: YEAR
+              month: MNTH
+              day: DAYS
+              hour: HOUR
+              minute: MINU
+              second: SECO
+          latitude:
+            mnemonic: CLATH
+          longitude:
+            mnemonic: CLONH
+          satelliteIdentifier:
+            mnemonic: SAID
+          scanLineNumber:
+            mnemonic: SLNM
+          fieldOfViewNumber:
+            mnemonic: FOVN
+          solarZenithAngle:
+            mnemonic: SOZA
+          solarAzimuthAngle:
+            mnemonic: SOLAZI
+          sensorZenithAngle:
+            mnemonic: SAZA
+          sensorAzimuthAngle:
+            mnemonic: BEARAZ
+          sensorChannelStart:
+            mnemonic: STCH
+          sensorChannelEnd:
+            mnemonic: ENCH
+          channelScaleFactor:
+            mnemonic: CHSF
+          sensorChannelNumber:
+            mnemonic: CHNM
+          radiance:          # This is actually a scaled radiance, needs a fix
+            mnemonic: SCRA
+
+    ioda:
+      backend: netcdf
+      obsdataout: "./testrun/gdas.t00z.mtiasi.tm00.nc"
+
+      dimensions:
+        - name: "Location"
+          size: variables/latitude.nrows
+        - name: "Channel"
+          size: variables/radiance.ncols
+  #     - name: "ChannelBlock"
+  #       size: variables/sensorChannelStart.ncols
+
+      globals:
+        - name: "platformCommonName"
+          type: string
+          value: "IASI"
+
+        - name: "platformLongDescription"
+          type: string
+          value: "MTYP 021-241 IASI 1C RADIANCES (VARIABLE CHNS) (METOP)"
+
+      variables:
+        - name: "MetaData/satelliteIdentifier"
+          source: variables/satelliteIdentifier
+          dimensions: ["Location"]
+          longName: "Satellite identifier"
+          units: ""
+
+        - name: "MetaData/latitude"
+          source: variables/latitude
+          dimensions: ["Location"]
+          longName: "Latitude"
+          units: "degrees_north"
+          range: [-90, 90]
+
+        - name: "MetaData/longitude"
+          source: variables/longitude
+          dimensions: ["Location"]
+          longName: "Longitude"
+          units: "degrees_east"
+          range: [-180, 180]
+
+        - name: "MetaData/dateTime"
+          source: variables/timestamp
+          dimensions: ["Location"]
+          longName: "dateTime"
+          units: "seconds since 1970-01-01T00:00:00Z"
+
+        - name: "MetaData/fieldOfViewNumber"
+          source: variables/fieldOfViewNumber
+          dimensions: ["Location"]
+          longName: "Field of view number"
+          units: ""
+
+        - name: "MetaData/scanLineNumber"
+          source: variables/scanLineNumber
+          dimensions: ["Location"]
+          longName: "Scan line number"
+          units: ""
+
+        - name: "MetaData/solarZenithAngle"
+          source: variables/solarZenithAngle
+          dimensions: ["Location"]
+          longName: "Solar zenith angle"
+          units: "degrees"
+          range: [0, 180]
+
+        - name: "MetaData/solarAzimuthAngle"
+          source: variables/solarAzimuthAngle
+          dimensions: ["Location"]
+          longName: "Solar azimuth angle"
+          units: "degrees"
+          range: [0, 360]
+
+        - name: "MetaData/sensorZenithAngle"
+          source: variables/sensorZenithAngle
+          dimensions: ["Location"]
+          longName: "Sensor zenith angle"
+          units: "degrees"
+          range: [0, 90]
+
+        - name: "MetaData/sensorAzimuthAngle"
+          source: variables/sensorAzimuthAngle
+          dimensions: ["Location"]
+          longName: "Sensor azimuth angle"
+          units: "degrees"
+          range: [0, 360]
+
+#       - name: "MetaData/sensorChannelStart"
+#         source: variables/sensorChannelStart
+#         dimensions: ["ChannelBlock"]
+#         longName: "Starting channel number"
+#         units: ""
+
+#       - name: "MetaData/sensorChannelEnd"
+#         source: variables/sensorChannelEnd
+#         dimensions: ["ChannelBlock"]
+#         longName: "Ending channel number"
+#         units: ""
+
+#       - name: "MetaData/channelScaleFactor"
+#         source: variables/channelScaleFactor
+#         dimensions: ["ChannelBlock"]
+#         longName: "Channel scale factor"
+#         units: ""
+
+        - name: "MetaData/sensorChannelNumber"
+          source: variables/sensorChannelNumber
+          dimensions: ["Channel"]
+          longName: "Channel number"
+          units: ""
+
+        - name: "ObsValue/radiance"
+          source: variables/radiance
+          coordinates: "longitude latitude Channel"
+          dimensions: ["Location", "Channel"]
+          longName: "Scaled radiance"
+          units: "W m-2 sr-1"
+          chunks: [1000, 616]
+          compressionLevel: 4
diff --git a/test/testinput/bufr_mhs.yaml b/test/testinput/bufr_mhs.yaml
index 279526979..04e91c0fc 100644
--- a/test/testinput/bufr_mhs.yaml
+++ b/test/testinput/bufr_mhs.yaml
@@ -20,8 +20,10 @@ observations:
               second: "*/SECO"
           height:
             query: "*/HMSL"
+            type: float
           hols:
             query: "*/HOLS"
+            type: float
           fovn:
             query: "*/FOVN"
           lsql:
@@ -42,7 +44,7 @@ observations:
             query: "*/BEARAZ"
           channels:
             query: "[*/BRITCSTC/CHNM, */BRIT/CHNM]"
-          radiance:
+          brightnessTemp:
             query: "[*/BRITCSTC/TMBR, */BRIT/TMBR]"
     
     ioda:
@@ -57,82 +59,85 @@ observations:
           source: variables/channels
 
       globals: 
-        - name: "sensorCentralFrequency@MetaData"
-          type: floatVector
-          value: [89.0, 157.0, 183.311, 183.311, 190.311]
 
-        - name: "platformCommonName@MetaData"
+        - name: "platformCommonName"
           type: string
           value: "MHS"
-            
-      variables:
-
-        - name: "stationElevation@MetaData"
-          source: variables/height
-          longName: "Station Elevation"
-          units: "meters"
-
-        - name: "heightOfSurface@MetaData"
-          source: variables/hols
-          longName: "Height of Land Surface"
-          units: "meters"
 
-        - name: "fieldOfViewNumber@MetaData"
-          source: variables/fovn
-          longName: "Field of View Number"
-          units: "none"
+        - name: "platformLongDescription"
+          type: string
+          value: "MTYP 021-027 PROCESSED MHS Tb (NOAA-18-19, METOP-1,2)"
 
-        - name: "landSeaQualifier@MetaData"
-          source: variables/lsql
-          longName: "Land/Sea Qualifier"
-          units: "none"
+#       - name: "sensorCentralFrequency"
+#         type: floatVector
+#         value: [89.0, 157.0, 183.311, 183.311, 190.311]
+            
+      variables:
 
-        - name: "dateTime@MetaData"
+        - name: "MetaData/dateTime"
           source: variables/timestamp
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
-        - name: "latitude@MetaData"
+        - name: "MetaData/latitude"
           source: variables/latitude
           longName: "Latitude"
           units: "degrees_north"
           range: [-90, 90]
 
-        - name: "longitude@MetaData"
+        - name: "MetaData/longitude"
           source: variables/longitude
           longName: "Longitude"
           units: "degrees_east"
           range: [-180, 180]
 
-        - name: "solarZenithAngle@MetaData"
+        - name: "MetaData/height"
+          source: variables/height
+          longName: "height"
+          units: "m"
+
+        - name: "MetaData/heightOfSurface"
+          source: variables/hols
+          longName: "Height of Land Surface"
+          units: "m"
+
+        - name: "MetaData/fieldOfViewNumber"
+          source: variables/fovn
+          longName: "Field of View Number"
+
+        - name: "MetaData/landSeaQualifier"
+          source: variables/lsql
+          longName: "Land/Sea Qualifier"
+
+        - name: "MetaData/solarZenithAngle"
           source: variables/sza
           longName: "Solar Zenith Angle"
           units: "degrees"
           range: [0, 180]
 
-        - name: "solarAzimuthAngle@MetaData"
+        - name: "MetaData/solarAzimuthAngle"
           source: variables/saz
           longName: "Solar Azimuth Angle"
           units: "degrees"
           range: [-180, 180]
 
-        - name: "sensorZenithAngle@MetaData"
+        - name: "MetaData/sensorZenithAngle"
           source: variables/vza
           longName: "Sensor Zenith Angle"
           units: "degrees"
           range: [0, 180]
 
-        - name: "sensorAzimuthAngle@MetaData"
+        - name: "MetaData/sensorAzimuthAngle"
           source: variables/vaz
           longName: "Sensor Azimuth Angle"
           units: "degrees"
           range: [-180, 180]
 
-        - name: "brightnessTemperature@ObsValue"
+        - name: "ObsValue/brightnessTemperature"
           coordinates: "longitude latitude Channel"
-          source: variables/radiance
+          source: variables/brightnessTemp
           longName: "Brightness Temperature"
           units: "K"
           range: [120, 500]
-          chunks: [1000, 15]
+          chunks: [1000, 5]
           compressionLevel: 4
diff --git a/test/testinput/bufr_mhs_v2.yaml b/test/testinput/bufr_mhs_v2.yaml
deleted file mode 100644
index 52bbdfe23..000000000
--- a/test/testinput/bufr_mhs_v2.yaml
+++ /dev/null
@@ -1,146 +0,0 @@
-# (C) Copyright 2021 UCAR
-#
-# This software is licensed under the terms of the Apache Licence Version 2.0
-# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
-
-observations:
-  - obs space:
-      name: bufr
-      obsdatain: "./testinput/gdas.t18z.1bmhs.tm00.bufr_d"
-      mnemonicSets:
-        - mnemonics: [YEAR, MNTH, DAYS, HOUR, MINU, CLAT, CLON]
-        - mnemonics: [SAID, SIID, FOVN, SAZA, SOZA, BEARAZ, SOLAZI]
-        - mnemonics: [CHNM, TMBR]
-          channels : 1-5
-
-      exports:
-        variables:
-          timestamp:
-            datetime:
-              year: YEAR
-              month: MNTH
-              day: DAYS
-              hour: HOUR
-              minute: MINU
-          latitude:
-            mnemonic: CLAT
-          longitude:
-            mnemonic: CLON
-          satelliteId:
-            mnemonic: SAID
-          sensorID:
-            mnemonic: SIID
-          channelNumber:
-            mnemonic: CHNM
-          fieldOfViewNumber:
-            mnemonic: FOVN
-          solarZenithAngle:
-            mnemonic: SOZA
-          solarAzimuthAngle:
-            mnemonic: SOLAZI
-          sensorZenithAngle:
-            mnemonic: SAZA
-          sensorAzimuthAngle:
-            mnemonic: BEARAZ
-          brightnessTemperature:
-            mnemonic: TMBR
-
-    ioda:
-      backend: netcdf
-      obsdataout: "./testrun/gdas.t18z.1bmhs.tm00.nc"
-
-      dimensions:
-        - name: "nlocs"
-          size: variables/brightnessTemperature.nrows
-        - name: "nchans"
-          size: variables/brightnessTemperature.ncols
-
-      globals: 
-        - name: "MetaData/platformCommonName"
-          type: string
-          value: "MHS"
-
-        - name: "MetaData/platformLongDescription"
-          type: string
-          value: "MTYP 021-027 PROCESSED MHS Tb (NOAA-18-19, METOP-1,2)"
-            
-        - name: "MetaData/sensorCentralFrequency"
-          type: floatVector
-          value: [89.0, 157.0, 183.311, 183.311, 190.311]
-
-      variables:
-        - name: "MetaData/satelliteId"
-          source: variables/satelliteId
-          dimensions: ["nlocs"]
-          longName: "Satellite identification"
-          units: ""
-
-        - name: "MetaData/channelNumber"
-          source: variables/channelNumber
-          dimensions: ["nchans"]
-          longName: "Channel number"
-          units: ""
-
-        - name: "MetaData/latitude"
-          source: variables/latitude
-          dimensions: ["nlocs"]
-          longName: "Latitude"
-          units: "degrees_north"
-          range: [-90, 90]
-
-        - name: "MetaData/longitude"
-          source: variables/longitude
-          dimensions: ["nlocs"]
-          longName: "Longitude"
-          units: "degrees_east"
-          range: [-180, 180]
-
-        - name: "MetaData/dateTime"
-          source: variables/timestamp
-          dimensions: ["nlocs"]
-          longName: "dateTime"
-          units: "seconds since 1970-01-01T00:00:00Z"
-
-        - name: "MetaData/fieldOfViewNumber"
-          source: variables/fieldOfViewNumber
-          dimensions: ["nlocs"]
-          longName: "Field of view number"
-          units: ""
-
-        - name: "MetaData/solarZenithAngle"
-          source: variables/solarZenithAngle
-          dimensions: ["nlocs"]
-          longName: "Solar zenith angle"
-          units: "degrees"
-          range: [0, 180]
-
-        - name: "MetaData/solarAzimuthAngle"
-          source: variables/solarAzimuthAngle
-          dimensions: ["nlocs"]
-          longName: "Solar azimuth angle"
-          units: "degrees"
-          range: [0, 360]
-
-        - name: "MetaData/sensorZenithAngle"
-          source: variables/sensorZenithAngle
-          dimensions: ["nlocs"]
-          longName: "Sensor zenith angle"
-          units: "degrees"
-          range: [0, 90]
-
-        - name: "MetaData/sensorAzimuthAngle"
-          source: variables/sensorAzimuthAngle
-          dimensions: ["nlocs"]
-          longName: "Sensor azimuth angle"
-          units: "degrees"
-          range: [0, 360]
-
-        - name: "ObsValue/brightnessTemperature"
-          coordinates: "longitude latitude nchans"
-          source: variables/brightnessTemperature
-          dimensions: ["nlocs", "nchans"]
-          longName: "Brightness temperature"
-          units: "K"
-          range: [120, 500]
-          chunks: [1000, 15]
-          compressionLevel: 4
diff --git a/test/testinput/bufr_ncep_aircft_AMDAR103.yaml b/test/testinput/bufr_ncep_aircft_AMDAR103.yaml
index e48040922..83bad12f1 100644
--- a/test/testinput/bufr_ncep_aircft_AMDAR103.yaml
+++ b/test/testinput/bufr_ncep_aircft_AMDAR103.yaml
@@ -5,7 +5,7 @@
 # 
 observations:
   - obs space:
-      name: bufr
+      name: bufr_amdar
 
       obsdatain: "testinput/gdas.t12z.aircft.tm00.bufr_d"
 
@@ -88,15 +88,15 @@ observations:
           source: variables/aircraftFlightNumber
           longName: "Aircraft Flight Number"
 
-        - name: "MetaData/aircraftNavigationalSystem"
-          source: variables/aircraftNavigationalSystem
-          longName: "Aircraft Navigational System"
+        # - name: "MetaData/aircraftNavigationalSystem"
+        #   source: variables/aircraftNavigationalSystem
+        #   longName: "Aircraft Navigational System"
 
         - name: "MetaData/aircraftIdentifier"
           source: variables/aircraftIdentifier
           longName: "Aircraft Identifier (Station Identification)"
 
-        - name: "MetaData/aircraftAltitude"
+        - name: "MetaData/height"
           source: variables/aircraftAltitude
           longName: "Aircraft Altitude"
           units: "m"
@@ -107,7 +107,7 @@ observations:
           longName: "Air Temperature"
           units: "K"
 
-        - name: "ObsValue/dewpointTemperature"
+        - name: "ObsValue/dewPointTemperature"
           source: variables/dewpointTemperature
           longName: "Dewpoint Temperature"
           units: "K"
@@ -143,4 +143,3 @@ observations:
         - name: "QualityMarker/windDirection"
           source: variables/windQM
           longName: "Quality Indicator for Wind Direction"
-
diff --git a/test/testinput/bufr_ncep_aircft_noAMDAR103.yaml b/test/testinput/bufr_ncep_aircft_noAMDAR103.yaml
index 07f7075d4..f55f3a8ef 100644
--- a/test/testinput/bufr_ncep_aircft_noAMDAR103.yaml
+++ b/test/testinput/bufr_ncep_aircft_noAMDAR103.yaml
@@ -5,7 +5,7 @@
 # 
 observations:
   - obs space:
-      name: bufr
+      name: bufr_aircft_no_amdar
 
       obsdatain: "testinput/gdas.t12z.aircft.tm00.bufr_d"
 
@@ -128,13 +128,13 @@ observations:
           source: variables/aircraftFlightNumber
           longName: "Aircraft Flight Number"
 
-        - name: "MetaData/aircraftNavigationalSystem"
-          source: variables/aircraftNavigationalSystem
-          longName: "Aircraft Navigational System"
+        # - name: "MetaData/aircraftNavigationalSystem"
+        #   source: variables/aircraftNavigationalSystem
+        #   longName: "Aircraft Navigational System"
 
-        - name: "MetaData/commercialAircraftType"
-          source: variables/commercialAircraftType
-          longName: "Commercial Aircraft Type"
+        # - name: "MetaData/commercialAircraftType"
+        #   source: variables/commercialAircraftType
+        #   longName: "Commercial Aircraft Type"
 
         - name: "MetaData/aircraftFlightPhase"
           source: variables/aircraftFlightPhase
@@ -148,31 +148,31 @@ observations:
           source: variables/dataProviderRestricted
           longName: "Data Provider Restricted"
 
-        - name: "MetaData/dataRestrictedExpiration"
-          source: variables/dataRestrictedExpiration
-          longName: "Restricted Data Expiration"
-          units: "Hour"
+        # - name: "MetaData/dataRestrictedExpiration"
+        #   source: variables/dataRestrictedExpiration
+        #   longName: "Restricted Data Expiration"
+        #   units: "Hour"
 
-        - name: "MetaData/dataReceiptTimeHour"
-          source: variables/dataReceiptTimeHour
-          longName: "Receipt Time (Hour)"
-          units: "Hour"
+        # - name: "MetaData/dataReceiptTimeHour"
+        #   source: variables/dataReceiptTimeHour
+        #   longName: "Receipt Time (Hour)"
+        #   units: "Hour"
 
-        - name: "MetaData/dataReceiptTimeMinute"
-          source: variables/dataReceiptTimeMinute
-          longName: "Data Receipt Time (Minute)"
-          units: "Minute"
+        # - name: "MetaData/dataReceiptTimeMinute"
+        #   source: variables/dataReceiptTimeMinute
+        #   longName: "Data Receipt Time (Minute)"
+        #   units: "Minute"
 
-        - name: "MetaData/dataReceiptTimeSignificance"
-          source: variables/dataReceiptTimeSignificance
-          longName: "Data Receipt Time Significance"
+        # - name: "MetaData/dataReceiptTimeSignificance"
+        #   source: variables/dataReceiptTimeSignificance
+        #   longName: "Data Receipt Time Significance"
 
-        - name: "MetaData/aircraftAltitude"
+        - name: "MetaData/height"
           source: variables/aircraftAltitude
           longName: "Aircraft Altitude"
           units: "m"
 
-        - name: "MetaData/relativeHumidityPercentConfidence"
+        - name: "MetaData/humidityPercentConfidence"
           source: variables/percentConfidenceRH
           longName: "Percent Confidence of Relative Humidity Quality"
           units: "percent"
@@ -236,4 +236,3 @@ observations:
         - name: "QualityMarker/windDirection"
           source: variables/windQM
           longName: "Quality Indicator for Wind Direction"
-
diff --git a/test/testinput/bufr_ncep_sevcsr.yaml b/test/testinput/bufr_ncep_sevcsr.yaml
index 93cfaf048..d2bd27687 100644
--- a/test/testinput/bufr_ncep_sevcsr.yaml
+++ b/test/testinput/bufr_ncep_sevcsr.yaml
@@ -6,7 +6,7 @@
 
 observations:
   - obs space:
-      name: bufr
+      name: bufr_sevcsr
       obsdatain: "./testinput/gdas.t00z.sevcsr.tm00.bufr_d"
 
       exports:
@@ -104,7 +104,7 @@ observations:
           longName: "Brightness temperature"
           units: "K"
           range: [150, 350]
-          chunks: [1000, 15]
+          chunks: [1000, 12]
 
         - name: "ObsValue/brightnessTemperatureStandardDeviation"
           coordinates: "longitude latitude Channel"
diff --git a/test/testinput/bufr_read_wmo_radiosonde.yaml b/test/testinput/bufr_read_wmo_radiosonde.yaml
index 43da84ef2..4e2587b1b 100644
--- a/test/testinput/bufr_read_wmo_radiosonde.yaml
+++ b/test/testinput/bufr_read_wmo_radiosonde.yaml
@@ -5,13 +5,20 @@
 
 observations:
   - obs space:
-      name: bufr
+      name: bufr_wmo_sonde
       obsdatain: "./testinput/bufr_read_wmo_radiosonde.bufr"
       isWmoFormat: true
       tablepath: "./testinput/bufr_tables"
 
       exports:
         variables:
+          timestamp:
+            datetime:
+              year: "*/YEAR"
+              month: "*/MNTH"
+              day: "*/DAYS"
+              hour: "*/HOUR"
+              minute: "*/MINU"
           latitude:
             query: "*/CLATH"
           longitude:
@@ -30,41 +37,45 @@ observations:
       obsdataout: "./testrun/bufr_read_wmo_radiosonde.nc"
 
       dimensions:
-        - name: Channel
+        - name: Level
           path: "*/TDWPRAOB"
 
-
       variables:
-        - name: "latitude@MetaData"
+        - name: "MetaData/dateTime"
+          source: variables/timestamp
+          longName: "dateTime"
+          units: "seconds since 1970-01-01T00:00:00Z"
+
+        - name: "MetaData/latitude"
           source: variables/latitude
           longName: "Latitude"
           units: "degrees_north"
 
-        - name: "longitude@MetaData"
+        - name: "MetaData/longitude"
           source: variables/longitude
           longName: "Longitude"
           units: "degrees_east"
 
-        - name: "air_temperature@ObsValue"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/airTemperature"
+          coordinates: "longitude latitude Level"
           source: variables/air_temperature
           longName: "Air Temperature"
           units: "K"
 
-        - name: "dewpoint_temperature@ObsValue"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/dewPointTemperature"
+          coordinates: "longitude latitude Level"
           source: variables/dewpoint_temperature
           longName: "Dewpoint Temperature"
           units: "K"
 
-        - name: "wind_direction@ObsValue"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/windDirection"
+          coordinates: "longitude latitude Level"
           source: variables/wind_direction
           longName: "Wind Direction"
-          units: "degrees true"
+          units: "degree"
 
-        - name: "wind_speed@ObsValue"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/windSpeed"
+          coordinates: "longitude latitude Level"
           source: variables/wind_speed
           longName: "Wind Speed"
-          units: "m/s"
+          units: "m s-1"
diff --git a/test/testinput/bufr_satwnd_new_format.yaml b/test/testinput/bufr_satwnd_new_format.yaml
index 29e059fea..3caeb0459 100644
--- a/test/testinput/bufr_satwnd_new_format.yaml
+++ b/test/testinput/bufr_satwnd_new_format.yaml
@@ -38,8 +38,10 @@ observations:
             query: "*/EHAM"
           pressure:
             query: "*/PRLC[1]"
+            type: float
           wind_direction:
             query: "*/WDIR"
+            type: float
           wind_speed:
             query: "*/WSPD"
           tracking_correlation_of_vector:
@@ -60,96 +62,88 @@ observations:
       backend: netcdf
       obsdataout: "./testrun/NC005031.nc"
 
+      dimensions:
+        - name: "Confidence"
+          path: "*/AMVQIC"
+
       variables:
-        - name: "satellite@MetaData"
+        - name: "MetaData/satelliteIdentifier"
           source: variables/satellite
           longName: "Satellite ID"
-          units: "id"
 
-        - name: "dateTime@MetaData"
+        - name: "MetaData/dateTime"
           source: variables/timestamp
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
-        - name: "longitude@MetaData"
+        - name: "MetaData/longitude"
           source: variables/longitude
           longName: "Longitude"
-          units: "degrees"
+          units: "degree_east"
           range: [-180, 180]
 
-        - name: "latitude@MetaData"
+        - name: "MetaData/latitude"
           source: variables/latitude
           longName: "Latitude"
-          units: "degrees"
+          units: "degree_north"
           range: [-90, 90]
 
-        - name: "satellite_wind_calculation_method@MetaData"
+        - name: "MetaData/windComputationMethod"
           source: variables/satellite_wind_calculation_method
           longName: "Satellite Wind Calculation Method"
-          units: "id"
 
-        - name: "satellite_zenith_angle@MetaData"
+        - name: "MetaData/satelliteZenithAngle"
           source: variables/satellite_zenith_angle
           longName: "Satellite Zenith Angle"
-          units: "degrees"
+          units: "degree"
 
-        - name: "satellite_channel_center_frequency@MetaData"
+        - name: "MetaData/sensorCentralFrequency"
           source: variables/satellite_channel_center_frequency
           longName: "Satellite Channel Center Frequency"
-          units: "hz"
+          units: "Hz"
 
-        - name: "originating_generating_center@MetaData"
+        - name: "MetaData/dataProviderOrigin"
           source: variables/originating_generating_center
           longName: "Originating/Generating Center"
-          units: "id"
 
-        - name: "satellite_wind_quality_mark@MetaData"
+        - name: "QualityMarker/qualityFlags"
           source: variables/satellite_wind_quality_mark
           longName: "Satellite Wind Quality Mark"
-          units: "id"
 
-        - name: "extended_height_assignment_method@MetaData"
+        - name: "MetaData/windHeightAssignMethod"
           source: variables/extended_height_assignment_method
           longName: "Height Assignment Method"
-          units: "id"
 
-        - name: "pressure@ObsValue"
+        - name: "MetaData/windTrackingCorrelation"
+          coordinates: "longitude latitude"
+          source: variables/tracking_correlation_of_vector
+          longName: "Tracking Correlation of Vector"
+          units: "1"
+
+        - name: "MetaData/windGeneratingApplication"
+          source: variables/generating_application
+          longName: "Generating Application"
+
+        - name: "MetaData/windPercentConfidence"
+          coordinates: "longitude latitude Confidence"
+          source: variables/percent_confidence
+          longName: "Percent Confidence"
+          units: "percent"
+
+        - name: "MetaData/pressure"
           coordinates: "longitude latitude"
           source: variables/pressure
           longName: "Pressure"
-          units: "pascals"
+          units: "Pa"
 
-        - name: "wind_direction@ObsValue"
+        - name: "ObsValue/windDirection"
           coordinates: "longitude latitude"
           source: variables/wind_direction
           longName: "Wind Direction"
-          units: "degrees true"
+          units: "degree"
 
-        - name: "wind_speed@ObsValue"
+        - name: "ObsValue/windSpeed"
           coordinates: "longitude latitude"
           source: variables/wind_speed
           longName: "Wind Speed"
-          units: "meters per second"
-
-        - name: "tracking_correlation_of_vector@ObsValue"
-          coordinates: "longitude latitude"
-          source: variables/tracking_correlation_of_vector
-          longName: "Tracking Correlation of Vector"
-          units: "numeric"
-
-        - name: "coefficient_of_variation@ObsValue"
-          coordinates: "longitude latitude"
-          source: variables/coefficient_of_variation
-          longName: "Coefficient of Variation"
-          units: "numeric"
-
-        - name: "generating_application@MetaData"
-          source: variables/generating_application
-          longName: "Generating Application"
-          units: "id"
-
-        - name: "percent_confidence@ObsValue"
-          coordinates: "longitude latitude"
-          source: variables/percent_confidence
-          longName: "Percent Confidence"
-          units: "percent"
+          units: "m s-1"
diff --git a/test/testinput/bufr_satwnd_old_format.yaml b/test/testinput/bufr_satwnd_old_format.yaml
index abebb783d..8bc45f74b 100644
--- a/test/testinput/bufr_satwnd_old_format.yaml
+++ b/test/testinput/bufr_satwnd_old_format.yaml
@@ -38,8 +38,10 @@ observations:
             query: "*/MDPT/HAMD"
           pressure:
             query: "*/PRLC"
+            type: float
           wind_direction:
             query: "*/WDIR"
+            type: float
           wind_speed:
             query: "*/WSPD"
           generating_application:
@@ -57,86 +59,83 @@ observations:
       backend: netcdf
       obsdataout: "./testrun/NC005066.nc"
 
+      dimensions:
+        - name: "Confidence"
+          path: "*/QCPRMS"
 
       variables:
-        - name: "satellite@MetaData"
+        - name: "MetaData/satelliteIdentifier"
           source: variables/satellite
           longName: "Satellite ID"
-          units: "id"
 
-        - name: "dateTime@MetaData"
+        - name: "MetaData/dateTime"
           source: variables/timestamp
-          dimensions: [ "nlocs" ]
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
-        - name: "longitude@MetaData"
+        - name: "MetaData/longitude"
           source: variables/longitude
           longName: "Longitude"
-          units: "degrees"
+          units: "degree_east"
           range: [-180, 180]
 
-        - name: "latitude@MetaData"
+        - name: "MetaData/latitude"
           source: variables/latitude
           longName: "Latitude"
-          units: "degrees"
+          units: "degree_north"
           range: [-90, 90]
 
-        - name: "satellite_wind_calculation_method@MetaData"
+        - name: "MetaData/windComputationMethod"
           source: variables/satellite_wind_calculation_method
           longName: "Satellite Wind Calculation Method"
-          units: "id"
 
-        - name: "satellite_channel_center_frequency@MetaData"
+        - name: "MetaData/sensorCentralFrequency"
           source: variables/satellite_channel_center_frequency
           longName: "Satellite Channel Center Frequency"
-          units: "hz"
+          units: "Hz"
 
-        - name: "satellite_zenith_angle@MetaData"
+        - name: "MetaData/satelliteZenithAngle"
           source: variables/satellite_zenith_angle
           longName: "Satellite Zenith Angle"
-          units: "degrees"
+          units: "degree"
 
-        - name: "originating_generating_center@MetaData"
+        - name: "MetaData/dataProviderOrigin"
           source: variables/originating_generating_center
           longName: "Originating/Generating Center"
-          units: "id"
 
-        - name: "satellite_wind_quality_mark@MetaData"
+        - name: "QualityMarker/qualityFlags"
           source: variables/satellite_wind_quality_mark
           longName: "Satellite Wind Quality Mark"
-          units: "id"
 
-        - name: "height_assignment_method@MetaData"
+        - name: "MetaData/windHeightAssignMethod"
           source: variables/height_assignment_method
           longName: "Height Assignment Method"
-          units: "id"
 
-        - name: "generating_application@MetaData"
+        - name: "MetaData/windGeneratingApplication"
+          coordinates: "longitude latitude Confidence"
           source: variables/generating_application
           longName: "Generating Application"
-          units: "id"
 
-        - name: "pressure@ObsValue"
+        - name: "MetaData/pressure"
           coordinates: "longitude latitude"
           source: variables/pressure
           longName: "Pressure"
-          units: "pascals"
+          units: "Pa"
 
-        - name: "wind_direction@ObsValue"
+        - name: "ObsValue/windDirection"
           coordinates: "longitude latitude"
           source: variables/wind_direction
           longName: "Wind Direction"
-          units: "degrees true"
+          units: "degree"
 
-        - name: "wind_speed@ObsValue"
+        - name: "ObsValue/windSpeed"
           coordinates: "longitude latitude"
           source: variables/wind_speed
           longName: "Wind Speed"
-          units: "meters per second"
+          units: "m s-1"
 
-        - name: "percent_confidence@ObsValue"
-          coordinates: "longitude latitude"
+        - name: "MetaData/windPercentConfidence"
+          coordinates: "longitude latitude Confidence"
           source: variables/percent_confidence
           longName: "Percent Confidence"
           units: "percent"
diff --git a/test/testinput/bufr_simple_groupby.yaml b/test/testinput/bufr_simple_groupby.yaml
index b6bdb563c..3f9e4cc9d 100644
--- a/test/testinput/bufr_simple_groupby.yaml
+++ b/test/testinput/bufr_simple_groupby.yaml
@@ -34,34 +34,34 @@ observations:
 
       variables:
 
-        - name: "datetime@MetaData"
+        - name: "MetaData/dateTime"
           source: variables/timestamp
-          longName: "Datetime"
-          units: "datetime"
+          longName: "dateTime"
+          units: "seconds since 1970-01-01T00:00:00Z"
 
-        - name: "latitude@MetaData"
+        - name: "MetaData/latitude"
           source: variables/latitude
           longName: "Latitude"
           units: "degrees_north"
           range: [-90, 90]
 
-        - name: "longitude@MetaData"
+        - name: "MetaData/longitude"
           source: variables/longitude
           longName: "Longitude"
           units: "degrees_east"
           range: [-180, 180]
 
-        - name: "depth@MetaData"
+        - name: "MetaData/depthBelowWaterSurface"
           source: variables/depth
-          longName: "Depth below sea surface"
+          longName: "Depth below water surface"
           units: "m"
 
-        - name: "sea_water_temperature@ObsValue"
+        - name: "ObsValue/waterTemperature"
           source: variables/temp
-          longName: "Temperature at depth"
-          units: "deg K"
+          longName: "water temperature at depth"
+          units: "K"
 
-        - name: "sea_water_salinity@ObsValue"
+        - name: "ObsValue/salinity"
           source: variables/saln
           longName: "Salinity at depth"
           units: "PSU"
diff --git a/test/testinput/bufr_splitting.yaml b/test/testinput/bufr_splitting.yaml
index 4b6a45948..c87b0d5c7 100644
--- a/test/testinput/bufr_splitting.yaml
+++ b/test/testinput/bufr_splitting.yaml
@@ -46,18 +46,18 @@ observations:
           path: "*/BRITCSTC"
 
       variables:
-        - name: "dateTime@MetaData"
+        - name: "MetaData/dateTime"
           source: variables/timestamp
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
-        - name: "latitude@MetaData"
+        - name: "MetaData/latitude"
           source: variables/latitude
           longName: "Latitude"
           units: "degrees_north"
           range: [-90, 90]
 
-        - name: "longitude@MetaData"
+        - name: "MetaData/longitude"
           source: variables/longitude
           longName: "Longitude"
           units: "degrees_east"
diff --git a/test/testinput/bufr_ssmis_v2.yaml b/test/testinput/bufr_ssmis.yaml
similarity index 55%
rename from test/testinput/bufr_ssmis_v2.yaml
rename to test/testinput/bufr_ssmis.yaml
index 67b5c0dbc..7e24e2c15 100644
--- a/test/testinput/bufr_ssmis_v2.yaml
+++ b/test/testinput/bufr_ssmis.yaml
@@ -8,8 +8,10 @@ observations:
       name: bufr
       obsdatain: "./testinput/gdas.t00z.ssmisu.tm00.bufr_d"
       mnemonicSets:
-        - mnemonics: [YEAR, MNTH, DAYS, HOUR, MINU, CLAT, CLON]
-        - mnemonics: [SAID, FOVN, BEARAZ, SFLG, RFLAG]
+        - mnemonics: [SAID, YEAR, MNTH, DAYS, HOUR, MINU, SECO]
+        - mnemonics: [SLNM, FOVN]
+        - mnemonics: [CLAT, CLON]
+        - mnemonics: [SFLG, RFLAG]
         - mnemonics: [CHNM, TMBR]
           channels: 1-24
 
@@ -22,22 +24,23 @@ observations:
               day: DAYS
               hour: HOUR
               minute: MINU
+              second: SECO
+          satelliteIdentifier:
+            mnemonic: SAID
           latitude:
             mnemonic: CLAT
           longitude:
             mnemonic: CLON
-          satelliteId:
-            mnemonic: SAID
-          channelNumber:
-            mnemonic: CHNM
+          scanLineNumber:
+            mnemonic: SLNM
           fieldOfViewNumber:
             mnemonic: FOVN
-          sensorAzimuthAngle:
-            mnemonic: BEARAZ
-          surfaceFlag:
+          earthSurfaceType:
             mnemonic: SFLG
-          rainFlag:
+          qualityFlags:
             mnemonic: RFLAG
+          sensorChannelNumber:
+            mnemonic: CHNM
           brightnessTemperature:
             mnemonic: TMBR
 
@@ -46,92 +49,90 @@ observations:
       obsdataout: "./testrun/gdas.t00z.ssmisu.tm00.nc"
 
       dimensions:
-        - name: "nlocs"
-          size: variables/brightnessTemperature.nrows
-        - name: "nchans"
+        - name: "Location"
+          size: variables/latitude.nrows
+        - name: "Channel"
           size: variables/brightnessTemperature.ncols
 
       globals:
-        - name: "MetaData/platformCommonName"
+        - name: "platformCommonName"
           type: string
-          value: "SSMIS"
+          value: "SSMIS-DMSP18"
 
-        - name: "MetaData/platformLongDescription"
+        - name: "platformLongDescription"
           type: string
           value: "MTYP 021-201 DMSP SSM/IS Tb (UNIFIED PRE-PROCESSOR)"
 
-        - name: "MetaData/sensorCentralFrequency"
-          type: floatVector
-          value: [19.35, 19.35, 22.235, 37.0, 37.0, 50.3, 52.8, 53.596,
-                  54.4, 55.5, 57.29, 59.4, 63.283248, 60.792668, 60.792668, 60.792668, 
-                  60.792668, 60.792668, 91.665, 91.665, 150, 183.311, 183.311, 183.311]
+#       - name: "sensorCentralFrequency"
+#         type: floatVector
+#         dimensions: ["Channel"]
+#         value: [19.35, 19.35, 22.235, 37.0, 37.0, 50.3, 52.8, 53.596,
+#                 54.4, 55.5, 57.29, 59.4, 63.283248, 60.792668, 60.792668, 60.792668, 
+#                 60.792668, 60.792668, 91.665, 91.665, 150, 183.311, 183.311, 183.311]
 
       variables:
-        - name: "MetaData/satelliteId"
-          source: variables/satelliteId
-          dimensions: ["nlocs"]
+        - name: "MetaData/satelliteIdentifier"
+          source: variables/satelliteIdentifier
+          dimensions: ["Location"]
           longName: "Satellite identification"
           units: ""
 
-        - name: "MetaData/channelNumber"
-          source: variables/channelNumber
-          dimensions: ["nchans"]
-          longName: "Channel number"
-          units: ""
-
         - name: "MetaData/latitude"
           source: variables/latitude
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Latitude"
           units: "degrees_north"
           range: [-90, 90]
 
         - name: "MetaData/longitude"
           source: variables/longitude
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Longitude"
           units: "degrees_east"
           range: [-180, 180]
 
         - name: "MetaData/dateTime"
           source: variables/timestamp
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
+        - name: "MetaData/scanLineNumber"
+          source: variables/scanLineNumber
+          dimensions: ["Location"]
+          longName: "Scan line number"
+          units: ""
+
         - name: "MetaData/fieldOfViewNumber"
           source: variables/fieldOfViewNumber
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Field of view number"
           units: ""
 
-        - name: "MetaData/sensorAzimuthAngle"
-          source: variables/sensorAzimuthAngle
-          dimensions: ["nlocs"]
-          longName: "Sensor azimuth angle"
-          units: "degrees"
-          range: [0, 360]
-
-        - name: "MetaData/surfaceFlag"
-          coordinates: "longitude latitude"
-          source: variables/surfaceFlag
-          dimensions: ["nlocs"]
+        - name: "MetaData/earthSurfaceType"
+          source: variables/earthSurfaceType
+          dimensions: ["Location"]
           longName: "Suface flag"
-          units: "code"
+          units: ""
 
-        - name: "MetaData/rainFlag"
-          coordinates: "longitude latitude"
-          source: variables/rainFlag
-          dimensions: ["nlocs"]
+        - name: "MetaData/qualityFlags"
+          source: variables/qualityFlags
+          dimensions: ["Location"]
           longName: "Rain flag"
-          units: "code"
+          units: ""
+
+        - name: "MetaData/sensorChannelNumber"
+          source: variables/sensorChannelNumber
+          dimensions: ["Channel"]
+          longName: "Channel number"
+          units: ""
 
         - name: "ObsValue/brightnessTemperature"
-          coordinates: "longitude latitude nchans"
           source: variables/brightnessTemperature
-          dimensions: ["nlocs", "nchans"]
+          coordinates: "longitude latitude Channel"
+          dimensions: ["Location", "Channel"]
           longName: "Brightness temperature"
           units: "K"
           range: [120, 500]
-          chunks: [1000, 15]
+          chunks: [1000, 24]
           compressionLevel: 4
diff --git a/test/testinput/bufr_wmo_amdar_multi.yaml b/test/testinput/bufr_wmo_amdar_multi.yaml
index 75019aeb8..eff8cfc0a 100644
--- a/test/testinput/bufr_wmo_amdar_multi.yaml
+++ b/test/testinput/bufr_wmo_amdar_multi.yaml
@@ -26,6 +26,7 @@ observations:
             query: "*/CLONH"
           pressureAltitude:
             query: "[*/FLVLST, */AMDARNOL/FLVLST]"
+            type: float
           aircraftRegistrationNum:
             query: "*/ACRN"
           aircraftFlightNum:
@@ -40,7 +41,7 @@ observations:
             query: "*/TASP"
           aircraftHeading:
             query: "*/ACTH"
-          aircraftRollAngle:
+          aircraftRollAngleQuality:
             query: "[*/ROLQ, */AMDARNOL/ROLQ]"
           temperatureAir:
             query: "[*/TMDB, */AMDARNOL/TMDB, */TMDBST]"
@@ -55,6 +56,10 @@ observations:
       backend: netcdf
       obsdataout: "./testrun/bufr_wmo_amdar_multi.nc"
 
+      dimensions:
+        - name: AmdarSequence
+          path: "*/AMDARNOL"
+
       variables:
         - name: "MetaData/dateTime"
           source: variables/timestamp
@@ -72,23 +77,24 @@ observations:
           units: "degrees_east"
 
         - name: "MetaData/height"
+          coordinates: "longitude latitude AmdarSequence"
           source: variables/pressureAltitude
           longName: "Pressure altitude"
           units: "m"
 
-        - name: "MetaData/aircraftRegistrationNum"
+        - name: "MetaData/aircraftIdentifier"
           source: variables/aircraftRegistrationNum
           longName: "Aircraft registration number or other ID"
 
-        - name: "MetaData/aircraftFlightNum"
+        - name: "MetaData/aircraftFlightNumber"
           source: variables/aircraftFlightNum
           longName: "Aircraft flight number"
 
-        - name: "MetaData/aircraftTailNum"
+        - name: "MetaData/aircraftTailNumber"
           source: variables/aircraftTailNum
           longName: "Aircraft tail number"
 
-        - name: "MetaData/observationSequenceNum"
+        - name: "MetaData/sequenceNumber"
           source: variables/observationSequenceNum
           longName: "Observation sequence number"
 
@@ -96,7 +102,7 @@ observations:
           source: variables/aircraftFlightPhase
           longName: "Aircraft flight phase (ascending/descending/level)"
 
-        - name: "MetaData/aircraftTrueAirspeed"
+        - name: "MetaData/aircraftVelocity"
           source: variables/aircraftTrueAirspeed
           longName: "Aircraft true airspeed"
           units: "m s-1"
@@ -104,32 +110,33 @@ observations:
         - name: "MetaData/aircraftHeading"
           source: variables/aircraftHeading
           longName: "Aircraft heading"
-          units: "deg"
+          units: "degree"
 
-        - name: "MetaData/aircraftRollAngle"
-          source: variables/aircraftRollAngle
-          longName: "Aircraft roll angle quality"
+        # - name: "MetaData/aircraftRollAngleQuality"
+        #   coordinates: "longitude latitude AmdarSequence"
+        #   source: variables/aircraftRollAngleQuality
+        #   longName: "Aircraft roll angle quality"
 
-        - name: "ObsValue/air_temperature"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/airTemperature"
+          coordinates: "longitude latitude AmdarSequence"
           source: variables/temperatureAir
           longName: "Air Temperature"
           units: "K"
 
-        - name: "ObsValue/specific_humidity"
+        - name: "ObsValue/specificHumidity"
           coordinates: "longitude latitude"
           source: variables/waterVaporMixingRatio
           longName: "specific humidity"
           units: "kg kg-1"
 
-        - name: "ObsValue/wind_direction"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/windDirection"
+          coordinates: "longitude latitude AmdarSequence"
           source: variables/windDirection
           longName: "Wind Direction"
           units: "degrees"
 
-        - name: "ObsValue/wind_speed"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/windSpeed"
+          coordinates: "longitude latitude AmdarSequence"
           source: variables/windSpeed
           longName: "Wind Speed"
           units: "m s-1"
diff --git a/test/testinput/buoy_wmoBUFR2ioda.yaml b/test/testinput/buoy_wmoBUFR2ioda.yaml
index 3fc9fc9e4..d7a9e7dc8 100644
--- a/test/testinput/buoy_wmoBUFR2ioda.yaml
+++ b/test/testinput/buoy_wmoBUFR2ioda.yaml
@@ -37,19 +37,19 @@ observations:
             mnemonic: CLONH
           stationElevation:
             mnemonic: HSAWS
-          temperatureAir:
+          airTemperature:
             mnemonic: TMDB
-          temperatureDewpoint:
+          dewpointTemperature:
             mnemonic: TMDP
           windDirection:
             mnemonic: WDIR
           windSpeed:
             mnemonic: WSPD
-          pressureStation:
+          stationPressure:
             mnemonic: PRES
-          meanSeaLevelPressure:
+          pressureReducedToMeanSeaLevel:
             mnemonic: PMSL
-          temperatureSeaSurface:
+          seaSurfaceTemperature:
             mnemonic: SST0
 
     ioda:
@@ -57,97 +57,97 @@ observations:
       obsdataout: "./testrun/buoy_wmo_multi.nc"
 
       dimensions:
-        - name: "nlocs"
+        - name: "Location"
           size: variables/latitude.nrows
 
       variables:
         - name: "MetaData/dateTime"
           source: variables/timestamp
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
         - name: "MetaData/latitude"
           source: variables/latitude
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Latitude"
           units: "degrees_north"
 
         - name: "MetaData/longitude"
           source: variables/longitude
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Longitude"
           units: "degrees_east"
 
-        - name: "MetaData/station_id"
+        - name: "MetaData/stationIdentification"
           source: variables/stationIdentification
-          dimensions: [ "nlocs" ]
-          longName: "Station Identification"
+          dimensions: [ "Location" ]
+          longName: "Station Identifier"
           units: "none"
 
         - name: "MetaData/stationLongName"
           source: variables/stationLongName
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Station long name"
           units: "none"
 
-        - name: "MetaData/station_elevation"
+        - name: "MetaData/stationElevation"
           source: variables/stationElevation
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Station Elevation"
           units: "m"
 
         - name: "MetaData/height"
           source: variables/stationElevation
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Height"
           units: "m"
 
-        - name: "ObsValue/air_temperature"
+        - name: "ObsValue/airTemperature"
+          source: variables/airTemperature
           coordinates: "longitude latitude"
-          source: variables/temperatureAir
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Air Temperature"
           units: "K"
 
-        - name: "ObsValue/dewpoint_temperature"
+        - name: "ObsValue/dewpointTemperature"
+          source: variables/dewpointTemperature
           coordinates: "longitude latitude"
-          source: variables/temperatureDewpoint
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Dewpoint Temperature"
           units: "K"
 
-        - name: "ObsValue/wind_direction"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/windDirection"
           source: variables/windDirection
-          dimensions: [ "nlocs" ]
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
           longName: "Wind Direction"
           units: "degrees"
 
-        - name: "ObsValue/wind_speed"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/windSpeed"
           source: variables/windSpeed
-          dimensions: [ "nlocs" ]
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
           longName: "Wind Speed"
           units: "m s-1"
 
-        - name: "ObsValue/surface_pressure"
+        - name: "ObsValue/stationPressure"
+          source: variables/stationPressure
           coordinates: "longitude latitude"
-          source: variables/pressureStation
-          dimensions: [ "nlocs" ]
-          longName: "Surface Pressure"
+          dimensions: [ "Location" ]
+          longName: "Surface station pressure"
           units: "Pa"
 
-        - name: "ObsValue/sea_level_pressure"
+        - name: "ObsValue/pressureReducedToMeanSeaLevel"
+          source: variables/pressureReducedToMeanSeaLevel
           coordinates: "longitude latitude"
-          source: variables/meanSeaLevelPressure
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Mean Sea Level Pressure"
           units: "Pa"
 
-        - name: "ObsValue/sea_surface_temperature"
+        - name: "ObsValue/seaSurfaceTemperature"
+          source: variables/seaSurfaceTemperature
           coordinates: "longitude latitude"
-          source: variables/temperatureSeaSurface
-          dimensions: [ "nlocs" ]
-          longName: "Sea Surface Temperature"
+          dimensions: [ "Location" ]
+          longName: "Sea-surface temperature"
           units: "K"
diff --git a/test/testinput/gdas.t00z.1bamua.tm00.bufr_d b/test/testinput/gdas.t00z.1bamua.tm00.bufr_d
new file mode 100644
index 000000000..2b53e63f3
--- /dev/null
+++ b/test/testinput/gdas.t00z.1bamua.tm00.bufr_d
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:abd06cad28d4bb5d18ee03ffd90a78bc6099ba543f76d6cdb99b0f8b90f6a5d8
+size 492555
diff --git a/test/testinput/gdas.t00z.1bhrs4.tm00.bufr_d b/test/testinput/gdas.t00z.1bhrs4.tm00.bufr_d
index cdc7fe9d2..bbc30b310 100644
--- a/test/testinput/gdas.t00z.1bhrs4.tm00.bufr_d
+++ b/test/testinput/gdas.t00z.1bhrs4.tm00.bufr_d
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6aa27e06ca5cca41952f6a39728001b138c2079d41bc2a1f59cad2a436417eb4
-size 501104
+oid sha256:dda9ac9eda2e1c5dffcce9b3774a1836e1d46181003e93984a20abe443b8b74c
+size 271749
diff --git a/test/testinput/gdas.t00z.1bmhs.tm00.bufr_d b/test/testinput/gdas.t00z.1bmhs.tm00.bufr_d
new file mode 100644
index 000000000..e91430c52
--- /dev/null
+++ b/test/testinput/gdas.t00z.1bmhs.tm00.bufr_d
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c91f1d846f75c808a3944c6f6c2bb126f3632920dbdd0e167f3178f9e83f11c8
+size 941961
diff --git a/test/testinput/gdas.t00z.airsev.tm00.bufr_d b/test/testinput/gdas.t00z.airsev.tm00.bufr_d
new file mode 100644
index 000000000..37b9ad514
--- /dev/null
+++ b/test/testinput/gdas.t00z.airsev.tm00.bufr_d
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2f929d61d06c3ec8612cb56a21c9ae391c9d79376d356bb52c49b67f2131a574
+size 380537
diff --git a/test/testinput/gdas.t00z.atms.tm00.bufr_d b/test/testinput/gdas.t00z.atms.tm00.bufr_d
new file mode 100644
index 000000000..b0cd69743
--- /dev/null
+++ b/test/testinput/gdas.t00z.atms.tm00.bufr_d
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:982c56d7173d765dde58797bfac37bbcfe28b8c2d22bdcf92ef4b7520607f679
+size 584798
diff --git a/test/testinput/gdas.t00z.avcsam.tm00.bufr_d b/test/testinput/gdas.t00z.avcsam.tm00.bufr_d
new file mode 100644
index 000000000..445dc3989
--- /dev/null
+++ b/test/testinput/gdas.t00z.avcsam.tm00.bufr_d
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:20f37fe4b9b0b7f0eca694c562696540f1b84e6851909651cbb466cf0aed41d5
+size 405237
diff --git a/test/testinput/gdas.t00z.crisf4.tm00.bufr_d b/test/testinput/gdas.t00z.crisf4.tm00.bufr_d
new file mode 100644
index 000000000..024d7a5fa
--- /dev/null
+++ b/test/testinput/gdas.t00z.crisf4.tm00.bufr_d
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3bb2ebff85458875644569f2a503e0dcfa5da6fa344b8876ec409972c8e64af0
+size 792000
diff --git a/test/testinput/gdas.t00z.mtiasi.tm00.bufr_d b/test/testinput/gdas.t00z.mtiasi.tm00.bufr_d
new file mode 100644
index 000000000..9fb5902dc
--- /dev/null
+++ b/test/testinput/gdas.t00z.mtiasi.tm00.bufr_d
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:521fd7f05f1fa15a95386b74cf856dba340180587d4d4d4f2ac43b095cfa242b
+size 574611
diff --git a/test/testinput/gdas.t00z.ssmisu.tm00.bufr_d b/test/testinput/gdas.t00z.ssmisu.tm00.bufr_d
new file mode 100644
index 000000000..c01801747
--- /dev/null
+++ b/test/testinput/gdas.t00z.ssmisu.tm00.bufr_d
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bd00bffeef1f3d3a4a5fb8275310a426e97fb77ba87adfdd007d29ba08696868
+size 604509
diff --git a/test/testinput/gdas.t12z.aircft.tm00.bufr_d b/test/testinput/gdas.t12z.aircft.tm00.bufr_d
index e1a2a7e89..704f6fa51 100644
--- a/test/testinput/gdas.t12z.aircft.tm00.bufr_d
+++ b/test/testinput/gdas.t12z.aircft.tm00.bufr_d
@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f6d73827ee889642bb30366eade2a4dfbee134ff2f2c6d93bcd9d123071419bb
-size 331688
+oid sha256:41b1ee8552c02f8015a32fe3eea1708fa3fd39c8bf02bd5cd4a7a42d50c2adf9
+size 123088
diff --git a/test/testinput/gmao-obs-20180415.nc b/test/testinput/gmao-obs-20180415.nc
new file mode 100644
index 000000000..8045a2450
--- /dev/null
+++ b/test/testinput/gmao-obs-20180415.nc
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:55bb4525755dcf3b76667b5e1ea276d4b67df3f790a343084d93df4971fd88e4
+size 192616
diff --git a/test/testinput/gnssro_wmoBUFR2ioda.yaml b/test/testinput/gnssro_wmoBUFR2ioda.yaml
index 8cf315c04..0bfc57cfc 100644
--- a/test/testinput/gnssro_wmoBUFR2ioda.yaml
+++ b/test/testinput/gnssro_wmoBUFR2ioda.yaml
@@ -37,7 +37,7 @@ observations:
             mnemonic: HEIT
           geopotentialHeight:
             mnemonic: GPHTST
-          airPressure:
+          pressure:
             mnemonic: PRES
           airTemperature:
             mnemonic: TMDBST
@@ -48,28 +48,26 @@ observations:
             mnemonic: SAID
           instrumentIdentifier:
             mnemonic: SIID
-          satelliteClassification:
-            mnemonic: SCLF
           platformTransmitterId:
             mnemonic: PTID
-          originatingCenter:
+          dataProviderOrigin:
             mnemonic: OGCE
           qualityFlags:
             mnemonic: QFRO
           percentConfidence:
             mnemonic: PCCF
-          impactParameter:
+          impactParameterRO:
             mnemonic: IMPP
           geoidUndulation:
             mnemonic: GEODU
-          azimuth:
+          sensorAzimuthAngle:
             mnemonic: BEARAZ
           earthRadiusCurvature:
             mnemonic: ELRC
 
           bendingAngle:
             mnemonic: BNDA
-          refractivity:
+          atmosphericRefractivity:
             mnemonic: ARFR
 
     ioda:
@@ -77,141 +75,124 @@ observations:
       obsdataout: "./testrun/gnssro_2020-306-2358C2E6.nc"
 
       dimensions:
-        - name: "nlocs"
+        - name: "Location"
           size: variables/latitude.nrows
 
       variables:
         - name: "MetaData/dateTime"
           source: variables/timestamp
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
         - name: "MetaData/latitude"
           source: variables/latitude
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Latitude"
           units: "degrees_north"
 
         - name: "MetaData/longitude"
           source: variables/longitude
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Longitude"
           units: "degrees_east"
 
         - name: "MetaData/height"
           source: variables/height
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Height"
           units: "m"
 
         - name: "MetaData/geopotentialHeight"
           source: variables/geopotentialHeight
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Geopotential height"
           units: "m"
 
-        - name: "MetaData/airPressure"
-          coordinates: "longitude latitude"
-          source: variables/airPressure
-          dimensions: [ "nlocs" ]
+        - name: "MetaData/pressure"
+          source: variables/pressure
+          dimensions: [ "Location" ]
           longName: "Air pressure"
           units: "Pa"
 
-        - name: "MetaData/process_center
-          coordinates: "longitude latitude"
-          source: variables/originatingCenter
-          dimensions: [ "nlocs" ]
+        - name: "MetaData/dataProviderOrigin"
+          source: variables/dataProviderOrigin
+          dimensions: [ "Location" ]
           longName: "Originating center"
-          units: "unitless"
+          units: ""
 
-        - name: "MetaData/gnss_sat_class
-          coordinates: "longitude latitude"
-          source: variables/satelliteClassification
-          dimensions: [ "nlocs" ]
-          longName: "GNSS satellite classification"
-          units: "unitless"
-
-        - name: "MetaData/reference_sat_id
-          coordinates: "longitude latitude"
+        - name: "MetaData/satelliteIdentifier"
           source: variables/satelliteIdentifier
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "GNSS satellite ID"
-          units: "unitless"
+          units: ""
 
-        - name: "MetaData/occulting_sat_is
-          coordinates: "longitude latitude"
+        - name: "MetaData/instrumentIdentifier"
           source: variables/instrumentIdentifier
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Instrument ID"
-          units: "unitless"
+          units: ""
 
-        - name: "MetaData/occulting_sat_id
-          coordinates: "longitude latitude"
+        - name: "MetaData/platformTransmitterId"
           source: variables/platformTransmitterId
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "GNSS platform transmitter ID"
-          units: "unitless"
+          units: ""
 
-        - name: "MetaData/qualityFlags
-          coordinates: "longitude latitude"
+        - name: "QualityMarker/qualityFlags"
           source: variables/qualityFlags
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Quality flags"
-          units: "unitless"
+          units: ""
 
-        - name: "MetaData/earth_radius_of_curvature"
-          coordinates: "longitude latitude"
+        - name: "MetaData/earthRadiusCurvature"
           source: variables/earthRadiusCurvature
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Earth local radius of curvature"
           units: "m"
 
-        - name: "MetaData/geoid_height_above_reference_ellipsoid
-          coordinates: "longitude latitude"
+        - name: "MetaData/geoidUndulation"
           source: variables/geoidUndulation
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Geoid undulation"
           units: "m"
 
-        - name: "MetaData/impact_parameter
-          coordinates: "longitude latitude"
-          source: variables/impactParameter
-          dimensions: [ "nlocs" ]
+        - name: "MetaData/impactParameterRO"
+          source: variables/impactParameterRO
+          dimensions: [ "Location" ]
           longName: "Impact parameter"
-          units: "m"
+          units: ""
 
-        - name: "MetaData/sensor_azimuth_angle
-          coordinates: "longitude latitude"
-          source: variables/azimuth
-          dimensions: [ "nlocs" ]
+        - name: "MetaData/sensorAzimuthAngle"
+          source: variables/sensorAzimuthAngle
+          dimensions: [ "Location" ]
           longName: "Sensor azimuth angle"
           units: "degrees"
 
         - name: "ObsValue/airTemperature"
-          coordinates: "longitude latitude"
           source: variables/airTemperature
-          dimensions: [ "nlocs" ]
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
           longName: "Air temperature"
           units: "K"
 
         - name: "ObsValue/specificHumidity"
-          coordinates: "longitude latitude"
           source: variables/specificHumidity
-          dimensions: [ "nlocs" ]
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
           longName: "Specific humidity"
           units: "kg kg-1"
 
-        - name: "ObsValue/bending_angle"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/bendingAngle"
           source: variables/bendingAngle
-          dimensions: [ "nlocs" ]
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
           longName: "Bending angle"
           units: "radians"
 
-        - name: "ObsValue/refractivity"
+        - name: "ObsValue/atmosphericRefractivity"
+          source: variables/atmosphericRefractivity
           coordinates: "longitude latitude"
-          source: variables/refractivity
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Refractivity"
-          units: "N units"
+          units: "INVALID N units"
diff --git a/test/testinput/imssnow_24km.grib2 b/test/testinput/imssnow_24km.grib2
deleted file mode 100644
index a15cd5705..000000000
--- a/test/testinput/imssnow_24km.grib2
+++ /dev/null
@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:98e353147e3375927fcdfe9e976e9d19c4a2b3881990fd7c23ae4f25eb443462
-size 7241
diff --git a/test/testinput/rass_wmoBUFR2ioda.yaml b/test/testinput/rass_wmoBUFR2ioda.yaml
index e8b793fc2..d9b190a65 100644
--- a/test/testinput/rass_wmoBUFR2ioda.yaml
+++ b/test/testinput/rass_wmoBUFR2ioda.yaml
@@ -26,9 +26,9 @@ observations:
               day: DAYS
               hour: HOUR
               minute: MINU
-          stationIdWMOblock:
+          wmoBlockNumber:
             mnemonic: WMOB
-          stationIdWMOstation:
+          wmoStationNumber:
             mnemonic: WMOS
           latitude:
             mnemonic: CLAT
@@ -50,68 +50,69 @@ observations:
       obsdataout: "./testrun/rass_wmo_multi.nc"
 
       dimensions:
-        - name: "nlocs"
+        - name: "Location"
           size: variables/latitude.nrows
 
       variables:
         - name: "MetaData/dateTime"
           source: variables/timestamp
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
         - name: "MetaData/latitude"
           source: variables/latitude
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Latitude"
           units: "degrees_north"
 
         - name: "MetaData/longitude"
           source: variables/longitude
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Longitude"
           units: "degrees_east"
 
-        - name: "MetaData/stationIdWMOblock"
-          source: variables/stationIdWMOblock
-          dimensions: [ "nlocs" ]
+        - name: "MetaData/wmoBlockNumber"
+          source: variables/wmoBlockNumber
+          dimensions: [ "Location" ]
           longName: "Station Identification WMO block number"
-          units: "none"
+          units: ""
 
-        - name: "MetaData/stationIdWMOstation"
-          source: variables/stationIdWMOstation
-          dimensions: [ "nlocs" ]
+        - name: "MetaData/wmoStationNumber"
+          source: variables/wmoStationNumber
+          dimensions: [ "Location" ]
           longName: "Station Identification WMO station number"
-          units: "none"
+          units: ""
 
-        - name: "MetaData/station_elevation"
+        - name: "MetaData/stationElevation"
           source: variables/stationElevation
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Station Elevation"
           units: "m"
 
         - name: "MetaData/height"
           source: variables/height
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Height"
           units: "m"
 
         # ADD this in later
         # - name: "MetaData/qualityIndicator"
         #   source: variables/qualityIndicator
-        #   dimensions: [ "nlocs" ]
+        #   dimensions: [ "Location" ]
         #   longName: "Quality Indicator (0=good, 1=no-good)"
         #   units: "unitless"
 
-        - name: "MetaData/signalToNoiseRatio"
+        - name: "ObsValue/signalToNoiseRatio"
           source: variables/signalToNoiseRatio
-          dimensions: [ "nlocs" ]
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
           longName: "Signal-to-noise Ratio"
-          units: "unitless"
+          units: "0.1 lg(re 0.001 m2 kg s-3)"
 
-        - name: "ObsValue/virtual_temperature"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/virtualTemperature"
           source: variables/virtualTemperature
-          dimensions: [ "nlocs" ]
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
           longName: "Virtual Temperature"
           units: "K"
diff --git a/test/testinput/satwind_EUMet_wmoBUFR2ioda.yaml b/test/testinput/satwind_EUMet_wmoBUFR2ioda.yaml
index 2bf8b503e..7c539a97a 100644
--- a/test/testinput/satwind_EUMet_wmoBUFR2ioda.yaml
+++ b/test/testinput/satwind_EUMet_wmoBUFR2ioda.yaml
@@ -38,7 +38,7 @@ observations:
             mnemonic: CLATH
           longitude:
             mnemonic: CLONH
-          satelliteId:
+          satelliteIdentifier:
             mnemonic: SAID
           generatingApplication:
             mnemonic: GNAPS
@@ -54,7 +54,7 @@ observations:
             mnemonic: AMVQ
           sensorZenithAngle:
             mnemonic: SAZA
-          pressureAir:
+          pressure:
             mnemonic: PRLC
           windEastward:
             mnemonic: UWND
@@ -68,103 +68,97 @@ observations:
       obsdataout: "./testrun/satwind_EUMet.nc"
 
       dimensions:
-        - name: "nlocs"
+        - name: "Location"
           size: variables/latitude.nrows
-        - name: "nconfidences"
+        - name: "Confidence"
           size: variables/windPercentConfidence.ncols
 
       globals:
-        - name: "MetaData/platformCommonName"
+        - name: "platform"
           type: string
           value: "EUMetSat_AMV"
 
-        - name: "MetaData/platformLongDescription"
-          type: string
-          value: "EUMetSat AMV from IR cloudy regions"
-
       variables:
-        - name: "MetaData/satelliteId"
-          source: variables/satelliteId
-          dimensions: ["nlocs"]
-          longName: "Satellite identification"
+        - name: "MetaData/satelliteIdentifier"
+          source: variables/satelliteIdentifier
+          dimensions: ["Location"]
+          longName: "Satellite identifier"
           units: ""
 
         - name: "MetaData/latitude"
           source: variables/latitude
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Latitude"
           units: "degrees"
           range: [-90, 90]
 
         - name: "MetaData/longitude"
           source: variables/longitude
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Longitude"
           units: "degrees"
           range: [-180, 180]
 
         - name: "MetaData/dateTime"
           source: variables/timestamp
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
         - name: "MetaData/generatingApplication"
           source: variables/generatingApplication
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Generating application"
-          units: "unitless"
+          units: ""
 
         - name: "MetaData/windComputationMethod"
           source: variables/windComputationMethod
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Satellite wind calculation method"
-          units: "unitless"
+          units: ""
 
         - name: "MetaData/windHeightAssignMethod"
           source: variables/windHeightAssignMethod
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Satellite wind height assignment method"
-          units: "unitless"
+          units: ""
 
         - name: "MetaData/sensorZenithAngle"
-          coordinates: "longitude latitude"
           source: variables/sensorZenithAngle
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Satellite zenith angle"
           units: "degrees"
 
-        - name: "MetaData/pressureAir"
-          coordinates: "longitude latitude"
-          source: variables/pressureAir
-          dimensions: ["nlocs"]
+        - name: "MetaData/pressure"
+          source: variables/pressure
+          dimensions: ["Location"]
           longName: "Pressure"
           units: "Pa"
 
         - name: "ObsValue/windEastward"
-          coordinates: "longitude latitude"
           source: variables/windEastward
-          dimensions: ["nlocs"]
+          coordinates: "longitude latitude"
+          dimensions: ["Location"]
           longName: "Wind eastward component"
           units: "m s-1"
 
         - name: "ObsValue/windNorthward"
-          coordinates: "longitude latitude"
           source: variables/windNorthward
-          dimensions: ["nlocs"]
+          coordinates: "longitude latitude"
+          dimensions: ["Location"]
           longName: "Wind northward component"
           units: "m s-1"
 
         - name: "MetaData/windPercentConfidence"
-          coordinates: "longitude latitude nconfidences"
           source: variables/windPercentConfidence
-          dimensions: ["nlocs", "nconfidences"]
+          coordinates: "longitude latitude Confidence"
+          dimensions: ["Location", "Confidence"]
           longName: "Percent confidence"
           units: "percent"
 
-        - name: "MetaData/sensorCentralFrequency"
-          coordinates: "longitude latitude nconfidences"
-          source: variables/sensorCentralFrequency
-          dimensions: ["nlocs"]
-          longName: "Sensor Central Frequency"
-          units: "hz"
+#       - name: "MetaData/sensorCentralFrequency"
+#         source: variables/sensorCentralFrequency
+#         coordinates: "longitude latitude Confidence"
+#         dimensions: ["Location", "Confidence"]
+#         longName: "Sensor Central Frequency"
+#         units: "Hz"
diff --git a/test/testinput/satwind_Himawari_wmoBUFR2ioda.yaml b/test/testinput/satwind_Himawari_wmoBUFR2ioda.yaml
index 1059bc7e5..f4f041c43 100644
--- a/test/testinput/satwind_Himawari_wmoBUFR2ioda.yaml
+++ b/test/testinput/satwind_Himawari_wmoBUFR2ioda.yaml
@@ -40,7 +40,7 @@ observations:
             mnemonic: CLATH
           longitude:
             mnemonic: CLONH
-          satelliteId:
+          satelliteIdentifier:
             mnemonic: SAID
           dataProviderOrigin:
             mnemonic: GCLONG
@@ -56,7 +56,7 @@ observations:
             mnemonic: TCMD
           sensorZenithAngle:
             mnemonic: SAZA
-          pressureAir:
+          pressure:
             mnemonic: PRLC
           windDirection:
             mnemonic: WDIR
@@ -70,109 +70,103 @@ observations:
       obsdataout: "./testrun/satwind_Himawari.nc"
 
       dimensions:
-        - name: "nlocs"
+        - name: "Location"
           size: variables/latitude.nrows
-        - name: "nconfidences"
+        - name: "Confidence"
           size: variables/windPercentConfidence.ncols
 
       globals:
-        - name: "MetaData/platformCommonName"
+        - name: "platform"
           type: string
           value: "Himiwari_AMV"
 
-        - name: "MetaData/platformLongDescription"
-          type: string
-          value: "Himiwari AMV from IR cloudy regions"
-
       variables:
-        - name: "MetaData/satelliteId"
-          source: variables/satelliteId
-          dimensions: ["nlocs"]
+        - name: "MetaData/satelliteIdentifier"
+          source: variables/satelliteIdentifier
+          dimensions: ["Location"]
           longName: "Satellite identification"
           units: ""
 
         - name: "MetaData/latitude"
           source: variables/latitude
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Latitude"
           units: "degrees"
           range: [-90, 90]
 
         - name: "MetaData/longitude"
           source: variables/longitude
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Longitude"
           units: "degrees"
           range: [-180, 180]
 
         - name: "MetaData/dateTime"
           source: variables/timestamp
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
         - name: "MetaData/dataProviderOrigin"
           source: variables/dataProviderOrigin
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Data provider origin"
           units: ""
 
         - name: "MetaData/generatingApplication"
           source: variables/generatingApplication
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Generating application"
           units: ""
 
         - name: "MetaData/windComputationMethod"
           source: variables/windComputationMethod
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Satellite wind calculation method"
-          units: " "
+          units: ""
 
         - name: "MetaData/windHeightAssignMethod"
           source: variables/windHeightAssignMethod
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Satellite wind height assignment method"
-          units: " "
+          units: ""
 
         - name: "MetaData/sensorZenithAngle"
-          coordinates: "longitude latitude"
           source: variables/sensorZenithAngle
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Satellite zenith angle"
           units: "degrees"
 
-        - name: "MetaData/pressureAir"
-          coordinates: "longitude latitude"
-          source: variables/pressureAir
-          dimensions: ["nlocs"]
+        - name: "MetaData/pressure"
+          source: variables/pressure
+          dimensions: ["Location"]
           longName: "Pressure"
           units: "Pa"
 
         - name: "ObsValue/windDirection"
-          coordinates: "longitude latitude"
           source: variables/windDirection
-          dimensions: ["nlocs"]
+          coordinates: "longitude latitude"
+          dimensions: ["Location"]
           longName: "Wind direction"
-          units: "degrees true"
+          units: "degrees"
 
         - name: "ObsValue/windSpeed"
-          coordinates: "longitude latitude"
           source: variables/windSpeed
-          dimensions: ["nlocs"]
+          coordinates: "longitude latitude"
+          dimensions: ["Location"]
           longName: "Wind Speed"
           units: "m s-1"
 
         - name: "MetaData/windPercentConfidence"
-          coordinates: "longitude latitude nconfidences"
           source: variables/windPercentConfidence
-          dimensions: ["nlocs", "nconfidences"]
+          coordinates: "longitude latitude Confidence"
+          dimensions: ["Location", "Confidence"]
           longName: "Percent confidence"
           units: "percent"
 
-        - name: "MetaData/sensorCentralFrequency"
-          coordinates: "longitude latitude nconfidences"
-          source: variables/sensorCentralFrequency
-          dimensions: ["nlocs"]
-          longName: "Sensor Central Frequency"
-          units: "hz"
+#       - name: "MetaData/sensorCentralFrequency"
+#         source: variables/sensorCentralFrequency
+#         coordinates: "longitude latitude nconfidences"
+#         dimensions: ["Location"]
+#         longName: "Sensor Central Frequency"
+#         units: "Hz"
diff --git a/test/testinput/satwind_Insat_wmoBUFR2ioda.yaml b/test/testinput/satwind_Insat_wmoBUFR2ioda.yaml
index 078970ad5..c35f816ba 100644
--- a/test/testinput/satwind_Insat_wmoBUFR2ioda.yaml
+++ b/test/testinput/satwind_Insat_wmoBUFR2ioda.yaml
@@ -39,7 +39,7 @@ observations:
             mnemonic: CLATH
           longitude:
             mnemonic: CLONH
-          satelliteId:
+          satelliteIdentifier:
             mnemonic: SAID
           dataProviderOrigin:
             mnemonic: GCLONG
@@ -55,7 +55,7 @@ observations:
             mnemonic: TCMD
           sensorZenithAngle:
             mnemonic: SAZA
-          pressureAir:
+          pressure:
             mnemonic: PRLC
           windDirection:
             mnemonic: WDIR
@@ -69,109 +69,103 @@ observations:
       obsdataout: "./testrun/satwind_Insat.nc"
 
       dimensions:
-        - name: "nlocs"
+        - name: "Location"
           size: variables/latitude.nrows
-        - name: "nconfidences"
+        - name: "Confidence"
           size: variables/windPercentConfidence.ncols
 
       globals:
-        - name: "MetaData/platformCommonName"
+        - name: "platform"
           type: string
           value: "Insat_AMV"
 
-        - name: "MetaData/platformLongDescription"
-          type: string
-          value: "Insat (Indian) AMV from IR cloudy regions"
-
       variables:
-        - name: "MetaData/satelliteId"
-          source: variables/satelliteId
-          dimensions: ["nlocs"]
+        - name: "MetaData/satelliteIdentifier"
+          source: variables/satelliteIdentifier
+          dimensions: ["Location"]
           longName: "Satellite identification"
           units: ""
 
         - name: "MetaData/latitude"
           source: variables/latitude
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Latitude"
           units: "degrees"
           range: [-90, 90]
 
         - name: "MetaData/longitude"
           source: variables/longitude
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Longitude"
           units: "degrees"
           range: [-180, 180]
 
         - name: "MetaData/dateTime"
           source: variables/timestamp
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
         - name: "MetaData/dataProviderOrigin"
           source: variables/dataProviderOrigin
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Data provider origin"
           units: ""
 
         - name: "MetaData/generatingApplication"
           source: variables/generatingApplication
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Generating application"
           units: ""
 
         - name: "MetaData/windComputationMethod"
           source: variables/windComputationMethod
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Satellite wind calculation method"
-          units: " "
+          units: ""
 
         - name: "MetaData/windHeightAssignMethod"
           source: variables/windHeightAssignMethod
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Satellite wind height assignment method"
-          units: " "
+          units: ""
 
         - name: "MetaData/sensorZenithAngle"
-          coordinates: "longitude latitude"
           source: variables/sensorZenithAngle
-          dimensions: ["nlocs"]
+          dimensions: ["Location"]
           longName: "Satellite zenith angle"
           units: "degrees"
 
-        - name: "MetaData/air_pressure"
-          coordinates: "longitude latitude"
-          source: variables/pressureAir
-          dimensions: ["nlocs"]
+        - name: "MetaData/pressure"
+          source: variables/pressure
+          dimensions: ["Location"]
           longName: "Pressure"
           units: "Pa"
 
+        - name: "MetaData/windPercentConfidence"
+          source: variables/windPercentConfidence
+          coordinates: "longitude latitude Confidence"
+          dimensions: ["Location", "Confidence"]
+          longName: "Percent confidence"
+          units: "percent"
+
+#       - name: "MetaData/sensorCentralFrequency"
+#         source: variables/sensorCentralFrequency
+#         coordinates: "longitude latitude Confidence"
+#         dimensions: ["Location"]
+#         longName: "Sensor Central Frequency"
+#         units: "Hz"
+
         - name: "ObsValue/windDirection"
-          coordinates: "longitude latitude"
           source: variables/windDirection
-          dimensions: ["nlocs"]
+          coordinates: "longitude latitude"
+          dimensions: ["Location"]
           longName: "Wind direction"
-          units: "degrees true"
+          units: "degrees"
 
         - name: "ObsValue/windSpeed"
-          coordinates: "longitude latitude"
           source: variables/windSpeed
-          dimensions: ["nlocs"]
+          coordinates: "longitude latitude"
+          dimensions: ["Location"]
           longName: "Wind Speed"
           units: "m s-1"
-
-        - name: "MetaData/windPercentConfidence"
-          coordinates: "longitude latitude nconfidences"
-          source: variables/windPercentConfidence
-          dimensions: ["nlocs", "nconfidences"]
-          longName: "Percent confidence"
-          units: "percent"
-
-        - name: "MetaData/sensorCentralFrequency"
-          coordinates: "longitude latitude nconfidences"
-          source: variables/sensorCentralFrequency
-          dimensions: ["nlocs"]
-          longName: "Sensor Central Frequency"
-          units: "hz"
diff --git a/test/testinput/ship_wmoBUFR2ioda.yaml b/test/testinput/ship_wmoBUFR2ioda.yaml
index 6e4522076..12f079466 100644
--- a/test/testinput/ship_wmoBUFR2ioda.yaml
+++ b/test/testinput/ship_wmoBUFR2ioda.yaml
@@ -40,21 +40,21 @@ observations:
             mnemonic: CLON
           stationElevation:
             mnemonic: HBMSL
-          temperatureAir:
+          airTemperature:
             mnemonic: TMDB
-          temperatureDewpoint:
+          dewpointTemperature:
             mnemonic: TMDP
-          temperatureWetbulb:
+          wetBulbTemperature:
             mnemonic: TMWB
           windDirection:
             mnemonic: WDIR
           windSpeed:
             mnemonic: WSPD
-          pressureStation:
+          stationPressure:
             mnemonic: PRES
-          pressureMeanSeaLevel:
+          pressureReducedToMeanSeaLevel:
             mnemonic: PMSL
-          temperatureSeaSurface:
+          seaSurfaceTemperature:
             mnemonic: SST1
 
     ioda:
@@ -62,97 +62,104 @@ observations:
       obsdataout: "./testrun/ship_wmo_multi.nc"
 
       dimensions:
-        - name: "nlocs"
+        - name: "Location"
           size: variables/latitude.nrows
 
       variables:
         - name: "MetaData/dateTime"
           source: variables/timestamp
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
         - name: "MetaData/latitude"
           source: variables/latitude
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Latitude"
           units: "degrees_north"
 
         - name: "MetaData/longitude"
           source: variables/longitude
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Longitude"
           units: "degrees_east"
 
         - name: "MetaData/stationIdentification"
           source: variables/stationIdentification
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Station Identification"
           units: "none"
 
         - name: "MetaData/stationType"
           source: variables/stationType
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Station type"
           units: "none"
 
-        - name: "MetaData/station_elevation"
+        - name: "MetaData/stationElevation"
           source: variables/stationElevation
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Station Elevation"
           units: "m"
 
         - name: "MetaData/height"
           source: variables/stationElevation
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Height"
           units: "m"
 
-        - name: "ObsValue/air_temperature"
+        - name: "ObsValue/airTemperature"
+          source: variables/airTemperature
           coordinates: "longitude latitude"
-          source: variables/temperatureAir
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Air Temperature"
           units: "K"
 
-        - name: "ObsValue/dewpoint_temperature"
+        - name: "ObsValue/dewpointTemperature"
+          source: variables/dewpointTemperature
           coordinates: "longitude latitude"
-          source: variables/temperatureDewpoint
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Dewpoint Temperature"
           units: "K"
 
-        - name: "ObsValue/wetbulb_temperature"
+        - name: "ObsValue/wetBulbTemperature"
+          source: variables/wetBulbTemperature
           coordinates: "longitude latitude"
-          source: variables/temperatureWetbulb
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Wetbulb Temperature"
           units: "K"
 
-        - name: "ObsValue/wind_direction"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/windDirection"
           source: variables/windDirection
-          dimensions: [ "nlocs" ]
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
           longName: "Wind Direction"
           units: "degrees"
 
-        - name: "ObsValue/wind_speed"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/windSpeed"
           source: variables/windSpeed
-          dimensions: [ "nlocs" ]
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
           longName: "Wind Speed"
           units: "m s-1"
 
-        - name: "ObsValue/surface_pressure"
+        - name: "ObsValue/pressureReducedToMeanSeaLevel"
+          source: variables/pressureReducedToMeanSeaLevel
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
+          longName: "Mean sea-level pressure"
+          units: "Pa"
+
+        - name: "ObsValue/stationPressure"
+          source: variables/stationPressure
           coordinates: "longitude latitude"
-          source: variables/pressureStation
-          dimensions: [ "nlocs" ]
-          longName: "Surface Pressure"
+          dimensions: [ "Location" ]
+          longName: "Surface station Pressure"
           units: "Pa"
 
-        - name: "ObsValue/sea_surface_temperature"
+        - name: "ObsValue/seaSurfaceTemperature"
+          source: variables/seaSurfaceTemperature
           coordinates: "longitude latitude"
-          source: variables/temperatureSeaSurface
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Sea Surface Temperature"
           units: "K"
diff --git a/test/testinput/sonde_wmo_multi.bufr b/test/testinput/sonde_wmo_multi.bufr
new file mode 100644
index 000000000..f619a0dc6
--- /dev/null
+++ b/test/testinput/sonde_wmo_multi.bufr
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:988697588688cd7074c535b7e0ff399a230800f5af753ea79a6bed2a41cffbeb
+size 147187
diff --git a/test/testinput/synop_wmoBUFR2ioda.yaml b/test/testinput/synop_wmoBUFR2ioda.yaml
index fd1747eb5..3997e9f93 100644
--- a/test/testinput/synop_wmoBUFR2ioda.yaml
+++ b/test/testinput/synop_wmoBUFR2ioda.yaml
@@ -25,9 +25,9 @@ observations:
               day: DAYS
               hour: HOUR
               minute: MINU
-          stationIdWMOblock:
+          wmoBlockNumber:
             mnemonic: WMOB
-          stationIdWMOstation:
+          wmoStationNumber:
             mnemonic: WMOS
           stationLongName:
             mnemonic: STSN
@@ -37,15 +37,15 @@ observations:
             mnemonic: CLONH
           stationElevation:
             mnemonic: HSMSL
-          temperatureAir:
+          airTemperature:
             mnemonic: TMDB
-          temperatureDewpoint:
+          dewpointTemperature:
             mnemonic: TMDP
           windDirection:
             mnemonic: WDIR
           windSpeed:
             mnemonic: WSPD
-          pressureStation:
+          stationPressure:
             mnemonic: PRES
 
     ioda:
@@ -53,83 +53,83 @@ observations:
       obsdataout: "./testrun/synop_wmo_multi.nc"
 
       dimensions:
-        - name: "nlocs"
+        - name: "Location"
           size: variables/latitude.nrows
 
       variables:
         - name: "MetaData/dateTime"
           source: variables/timestamp
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
         - name: "MetaData/latitude"
           source: variables/latitude
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Latitude"
           units: "degrees_north"
 
         - name: "MetaData/longitude"
           source: variables/longitude
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Longitude"
           units: "degrees_east"
 
-        - name: "MetaData/stationIdWMOblock"
-          source: variables/stationIdWMOblock
-          dimensions: [ "nlocs" ]
+        - name: "MetaData/wmoBlockNumber"
+          source: variables/wmoBlockNumber
+          dimensions: [ "Location" ]
           longName: "Station Identification WMO block number"
           units: "none"
 
-        - name: "MetaData/stationIdWMOstation"
-          source: variables/stationIdWMOstation
-          dimensions: [ "nlocs" ]
+        - name: "MetaData/wmoStationNumber"
+          source: variables/wmoStationNumber
+          dimensions: [ "Location" ]
           longName: "Station Identification WMO station number"
           units: "none"
 
-        - name: "MetaData/station_elevation"
+        - name: "MetaData/stationElevation"
           source: variables/stationElevation
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Station Elevation"
           units: "m"
 
         - name: "MetaData/height"
           source: variables/stationElevation
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Height"
           units: "m"
 
-        - name: "ObsValue/air_temperature"
+        - name: "ObsValue/airTemperature"
+          source: variables/airTemperature
           coordinates: "longitude latitude"
-          source: variables/temperatureAir
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Air Temperature"
           units: "K"
 
-        - name: "ObsValue/dewpoint_temperature"
+        - name: "ObsValue/dewpointTemperature"
+          source: variables/dewpointTemperature
           coordinates: "longitude latitude"
-          source: variables/temperatureDewpoint
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Dewpoint Temperature"
           units: "K"
 
-        - name: "ObsValue/wind_direction"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/windDirection"
           source: variables/windDirection
-          dimensions: [ "nlocs" ]
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
           longName: "Wind Direction"
           units: "degrees"
 
-        - name: "ObsValue/wind_speed"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/windSpeed"
           source: variables/windSpeed
-          dimensions: [ "nlocs" ]
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
           longName: "Wind Speed"
           units: "m s-1"
 
-        - name: "ObsValue/surface_pressure"
+        - name: "ObsValue/stationPressure"
+          source: variables/stationPressure
           coordinates: "longitude latitude"
-          source: variables/pressureStation
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Surface Pressure"
           units: "Pa"
diff --git a/test/testinput/vadwinds_wmoBUFR2ioda.yaml b/test/testinput/vadwinds_wmoBUFR2ioda.yaml
index 49e546617..44b3c8be8 100644
--- a/test/testinput/vadwinds_wmoBUFR2ioda.yaml
+++ b/test/testinput/vadwinds_wmoBUFR2ioda.yaml
@@ -25,9 +25,9 @@ observations:
               day: DAYS
               hour: HOUR
               minute: MINU
-          stationIdWMOblock:
+          wmoBlockNumber:
             mnemonic: WMOB
-          stationIdWMOstation:
+          wmoStationNumber:
             mnemonic: WMOS
           latitude:
             mnemonic: CLAT
@@ -49,69 +49,69 @@ observations:
       obsdataout: "./testrun/vadwinds_wmo_multi.nc"
 
       dimensions:
-        - name: "nlocs"
+        - name: "Location"
           size: variables/latitude.nrows
 
       variables:
         - name: "MetaData/dateTime"
           source: variables/timestamp
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "dateTime"
           units: "seconds since 1970-01-01T00:00:00Z"
 
         - name: "MetaData/latitude"
           source: variables/latitude
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Latitude"
           units: "degrees_north"
 
         - name: "MetaData/longitude"
           source: variables/longitude
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Longitude"
           units: "degrees_east"
 
-        - name: "MetaData/stationIdWMOblock"
-          source: variables/stationIdWMOblock
-          dimensions: [ "nlocs" ]
+        - name: "MetaData/wmoBlockNumber"
+          source: variables/wmoBlockNumber
+          dimensions: [ "Location" ]
           longName: "Station Identification WMO block number"
           units: "none"
 
-        - name: "MetaData/stationIdWMOstation"
-          source: variables/stationIdWMOstation
-          dimensions: [ "nlocs" ]
+        - name: "MetaData/wmoStationNumber"
+          source: variables/wmoStationNumber
+          dimensions: [ "Location" ]
           longName: "Station Identification WMO station number"
           units: "none"
 
-        - name: "MetaData/station_elevation"
+        - name: "MetaData/stationElevation"
           source: variables/stationElevation
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Station Elevation"
           units: "m"
 
         - name: "MetaData/height"
           source: variables/height
-          dimensions: [ "nlocs" ]
+          dimensions: [ "Location" ]
           longName: "Height"
           units: "m"
 
         # ADD this in later
         # - name: "MetaData/qualityIndicator"
         #   source: variables/qualityIndicator
-        #   dimensions: [ "nlocs" ]
+        #   dimensions: [ "Location" ]
         #   longName: "Quality Indicator"
         #   units: "unitless"
 
-        - name: "ObsValue/wind_direction"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/windDirection"
           source: variables/windDirection
-          dimensions: [ "nlocs" ]
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
           longName: "Wind Direction"
           units: "degrees"
 
-        - name: "ObsValue/wind_speed"
-          coordinates: "longitude latitude"
+        - name: "ObsValue/windSpeed"
           source: variables/windSpeed
-          dimensions: [ "nlocs" ]
+          coordinates: "longitude latitude"
+          dimensions: [ "Location" ]
           longName: "Wind Speed"
           units: "m s-1"
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