05_example_workflow.ipynb

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    "# Example workflow: IOOS gliders in the Gulf Stream\n",
    "\n",
    "In this example workflow we go through the steps of finding Gulf Stream gliders on the IOOS glider ERDDAP and plotting their tracks on a map. This notebooks is inteded as a template for using an ERDDAP to answer a scientific question."
   ]
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   "source": [
    "import matplotlib.pyplot as plt\n",
    "import xarray as xr\n",
    "import datetime\n",
    "import numpy as np\n",
    "import cartopy\n",
    "from erddapy import ERDDAP\n",
    "import pandas as pd\n",
    "from tqdm.notebook import tqdm\n",
    "import cartopy\n",
    "import cartopy.crs as ccrs"
   ]
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   "cell_type": "markdown",
   "id": "8297314b-6333-48c4-9920-3ce91afd4283",
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   "source": [
    "### 1. Setup the ERDDAP connection\n",
    "In this case, we use the IOOS gliders ERDDAP https://gliders.ioos.us/erddap/index.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2a01958f-d6ef-4fa7-8940-2b81bffc61e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "e = ERDDAP(\n",
    "    server=\"https://gliders.ioos.us/erddap\", \n",
    "    protocol=\"tabledap\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "100c2f73-88ac-432d-a324-556dbe9250ce",
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   "source": [
    "### 2. Search for datasets of interest\n",
    "\n",
    "Simple search. Let's look for datasets with \"gulf stream\" in the description"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f7a3b40b-de5a-4642-a94d-c9004e5ee2f9",
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     "text": [
      "['sg658-20220408T0000' 'sp066-20210624T1332' 'sp069-20210408T1555'\n",
      " 'sp062-20210624T1335' 'sp022-20201113T1549' 'sp065-20210616T1430'\n",
      " 'sp007-20220330T1436' 'sp071-20220602T1317' 'sp071-20211215T2041'\n",
      " 'sp007-20210818T1548' 'ng665-20220713T0000' 'ng427-20220713T0000'\n",
      " 'sp070-20220824T1510' 'sp062-20211014T1515' 'sp065-20220202T1520'\n",
      " 'sp062-20220623T1419' 'sp066-20221012T1417' 'sp065-20221116T1552'\n",
      " 'bass-20200203T0000' 'gp_363-20220703T1913' 'ng734-20220803T0000'\n",
      " 'cp_339-20210131T1640-delayed' 'cp_339-20210402T1334-delayed'\n",
      " 'silbo-20180525T1016' 'cp_388-20151022T1232-delayed' 'bass-20180808T0000'\n",
      " 'bass-20180301T0000' 'ng617-20200804T1442' 'gp_361-20140220T2049'\n",
      " 'gp_362-20140830T0240' 'gp_453-20140830T0051'\n",
      " 'gp_363-20160630T0230-delayed' 'gp_469-20180821T1804-delayed'\n",
      " 'gp_537-20150602T1105-delayed' 'gp_363-20130719T2300-delayed'\n",
      " 'gp_364-20130719T2033-delayed' 'gp_365-20130719T2017-delayed'\n",
      " 'gp_365-20160627T1535-delayed' 'gp_523-20150602T0440-delayed'\n",
      " 'gp_525-20150602T1125-delayed' 'gp_514-20150602T1000-delayed'\n",
      " 'gp_276-20140615T0533-delayed' 'gp_276-20180723T0633-delayed'\n",
      " 'gp_515-20150602T0955-delayed' 'gp_537-20190930T0140-delayed'\n",
      " 'gp_566-20201002T1245-delayed' 'gp_575-20160627T1858-delayed'\n",
      " 'gp_575-20190930T0147-delayed']\n"
     ]
    }
   ],
   "source": [
    "url = e.get_search_url(search_for=\"gulf stream\", response=\"csv\")\n",
    "\n",
    "df = pd.read_csv(url)\n",
    "datasets_to_download = df[\"Dataset ID\"].values\n",
    "print(datasets_to_download)"
   ]
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  {
   "cell_type": "markdown",
   "id": "053ce98d-d394-47b7-be81-cf54edf88e37",
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   "source": [
    "Let's focus on the nrt datasets, drop the delayed ones"
   ]
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   "source": [
    "datasets_nrt = [i for i in datasets_to_download if \"delayed\" not in i]"
   ]
  },
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   "execution_count": 5,
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       "['sg658-20220408T0000',\n",
       " 'sp066-20210624T1332',\n",
       " 'sp069-20210408T1555',\n",
       " 'sp062-20210624T1335',\n",
       " 'sp022-20201113T1549',\n",
       " 'sp065-20210616T1430',\n",
       " 'sp007-20220330T1436',\n",
       " 'sp071-20220602T1317',\n",
       " 'sp071-20211215T2041',\n",
       " 'sp007-20210818T1548',\n",
       " 'ng665-20220713T0000',\n",
       " 'ng427-20220713T0000',\n",
       " 'sp070-20220824T1510',\n",
       " 'sp062-20211014T1515',\n",
       " 'sp065-20220202T1520',\n",
       " 'sp062-20220623T1419',\n",
       " 'sp066-20221012T1417',\n",
       " 'sp065-20221116T1552',\n",
       " 'bass-20200203T0000',\n",
       " 'gp_363-20220703T1913',\n",
       " 'ng734-20220803T0000',\n",
       " 'silbo-20180525T1016',\n",
       " 'bass-20180808T0000',\n",
       " 'bass-20180301T0000',\n",
       " 'ng617-20200804T1442',\n",
       " 'gp_361-20140220T2049',\n",
       " 'gp_362-20140830T0240',\n",
       " 'gp_453-20140830T0051']"
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    "datasets_nrt"
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   "cell_type": "markdown",
   "id": "2bb7deeb-dc86-4124-85a6-e8ab26b827da",
   "metadata": {},
   "source": [
    "### 3. Refine dataset subset commands\n",
    "\n",
    "Let's download a dataset, then use data from this to refine our subset arguments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "922be8e5-1a24-4f03-b539-dcbee8c725cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "e.dataset_id = datasets_nrt[0]\n",
    "ds_example = e.to_xarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "97587587-958c-45b6-a037-dbb493c9aa84",
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       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:          (trajectory: 2, profile: 1280, obs: 1471982)\n",
       "Coordinates:\n",
       "  * trajectory       (trajectory) object &#x27;&#x27; &#x27;sg658-20220408T0&#x27;\n",
       "    time             (profile) datetime64[ns] ...\n",
       "    latitude         (profile) float64 ...\n",
       "    longitude        (profile) float64 ...\n",
       "    lat_uv           (profile) float64 ...\n",
       "    lon_uv           (profile) float64 ...\n",
       "    time_uv          (profile) datetime64[ns] ...\n",
       "    depth            (obs) float32 ...\n",
       "Dimensions without coordinates: profile, obs\n",
       "Data variables: (12/35)\n",
       "    wmo_id           (trajectory) object ...\n",
       "    profile_id       (profile) float64 ...\n",
       "    u                (profile) float64 ...\n",
       "    v                (profile) float64 ...\n",
       "    trajectoryIndex  (profile) int32 ...\n",
       "    rowSize          (profile) int32 ...\n",
       "    ...               ...\n",
       "    temperature      (obs) float32 ...\n",
       "    temperature_qc   (obs) float32 ...\n",
       "    time_qc          (obs) float32 ...\n",
       "    time_uv_qc       (obs) float32 ...\n",
       "    u_qc             (obs) float32 ...\n",
       "    v_qc             (obs) float32 ...\n",
       "Attributes: (12/62)\n",
       "    acknowledgment:                This project is funded by Shell Exploratio...\n",
       "    cdm_data_type:                 TrajectoryProfile\n",
       "    cdm_profile_variables:         time_uv,lat_uv,lon_uv,u,v,profile_id,time,...\n",
       "    cdm_trajectory_variables:      trajectory,wmo_id\n",
       "    comment:                       Underwater glider temperature and salinity...\n",
       "    contributor_name:              Palter J, Gray A, Currier R\n",
       "    ...                            ...\n",
       "    subsetVariables:               wmo_id,trajectory,profile_id,time,latitude...\n",
       "    summary:                       Collaborative Research: Investigating meso...\n",
       "    time_coverage_end:             2022-08-16T18:52:09Z\n",
       "    time_coverage_start:           2022-04-09T01:37:13Z\n",
       "    title:                         sg658-20220408T0000\n",
       "    Westernmost_Easting:           -72.38884713321431</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-7785c920-9147-4693-86b6-81db19bb98fe' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7785c920-9147-4693-86b6-81db19bb98fe' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>trajectory</span>: 2</li><li><span>profile</span>: 1280</li><li><span>obs</span>: 1471982</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-798eab9d-7ddf-4e7b-be5b-c61f9c3f2daa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-798eab9d-7ddf-4e7b-be5b-c61f9c3f2daa' class='xr-section-summary' >Coordinates: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>trajectory</span></div><div class='xr-var-dims'>(trajectory)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;&#x27; &#x27;sg658-20220408T0&#x27;</div><input id='attrs-70d12940-6410-46bd-838c-51973cba93b7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-70d12940-6410-46bd-838c-51973cba93b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef08e58d-633d-4704-b1a2-e11147273563' class='xr-var-data-in' type='checkbox'><label for='data-ef08e58d-633d-4704-b1a2-e11147273563' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cf_role :</span></dt><dd>trajectory_id</dd><dt><span>comment :</span></dt><dd>A trajectory is one deployment of a glider.</dd><dt><span>ioos_category :</span></dt><dd>Identifier</dd><dt><span>long_name :</span></dt><dd>Trajectory Name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;&#x27;, &#x27;sg658-20220408T0&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time</span></div><div class='xr-var-dims'>(profile)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6eca3f3c-0629-4f05-9332-9fff731586ee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6eca3f3c-0629-4f05-9332-9fff731586ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86f20ad9-f3d1-4bad-9333-12fffa979397' class='xr-var-data-in' type='checkbox'><label for='data-86f20ad9-f3d1-4bad-9333-12fffa979397' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Time</dd><dt><span>actual_range :</span></dt><dd>[1.64946823e+09 1.66067593e+09]</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>comment :</span></dt><dd>Timestamp corresponding to the mid-point of the profile.</dd><dt><span>ioos_category :</span></dt><dd>Time</dd><dt><span>long_name :</span></dt><dd>Profile Time</dd><dt><span>observation_type :</span></dt><dd>calculated</dd><dt><span>platform :</span></dt><dd>glider</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>time_origin :</span></dt><dd>01-JAN-1970 00:00:00</dd></dl></div><div class='xr-var-data'><pre>[1280 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(profile)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-078063c1-8631-448c-83ec-e3a967ca1f43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-078063c1-8631-448c-83ec-e3a967ca1f43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7de99c5-e9b5-4574-a33f-74c33f3bb7c4' class='xr-var-data-in' type='checkbox'><label for='data-e7de99c5-e9b5-4574-a33f-74c33f3bb7c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>actual_range :</span></dt><dd>[38.40409628 40.28010559]</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>colorBarMaximum :</span></dt><dd>90.0</dd><dt><span>colorBarMinimum :</span></dt><dd>-90.0</dd><dt><span>comment :</span></dt><dd>Value is interpolated to provide an estimate of the latitude at the mid-point of the profile.</dd><dt><span>ioos_category :</span></dt><dd>Location</dd><dt><span>long_name :</span></dt><dd>Profile Latitude</dd><dt><span>observation_type :</span></dt><dd>calculated</dd><dt><span>platform :</span></dt><dd>glider</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>[1280 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(profile)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-98dc94d6-318a-4e16-864c-e9f79cf40853' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98dc94d6-318a-4e16-864c-e9f79cf40853' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42592ee7-6889-44cb-8ac8-5ef129a730d1' class='xr-var-data-in' type='checkbox'><label for='data-42592ee7-6889-44cb-8ac8-5ef129a730d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>actual_range :</span></dt><dd>[-72.38884713 -69.16772674]</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>colorBarMaximum :</span></dt><dd>180.0</dd><dt><span>colorBarMinimum :</span></dt><dd>-180.0</dd><dt><span>comment :</span></dt><dd>Value is interpolated to provide an estimate of the longitude at the mid-point of the profile.</dd><dt><span>ioos_category :</span></dt><dd>Location</dd><dt><span>long_name :</span></dt><dd>Profile Longitude</dd><dt><span>observation_type :</span></dt><dd>calculated</dd><dt><span>platform :</span></dt><dd>glider</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>[1280 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_uv</span></div><div class='xr-var-dims'>(profile)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4f3013e1-5e08-497f-a91f-d5ffd4848762' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f3013e1-5e08-497f-a91f-d5ffd4848762' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85200971-2538-4d25-9b8a-47aa0c8e40c2' class='xr-var-data-in' type='checkbox'><label for='data-85200971-2538-4d25-9b8a-47aa0c8e40c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>colorBarMaximum :</span></dt><dd>90.0</dd><dt><span>colorBarMinimum :</span></dt><dd>-90.0</dd><dt><span>comment :</span></dt><dd>The depth-averaged current is an estimate of the net current measured while the glider is underwater. The value is calculated over the entire underwater segment, which may consist of 1 or more dives.</dd><dt><span>ioos_category :</span></dt><dd>Location</dd><dt><span>long_name :</span></dt><dd>Depth-averaged Latitude</dd><dt><span>observation_type :</span></dt><dd>calculated</dd><dt><span>platform :</span></dt><dd>glider</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>[1280 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_uv</span></div><div class='xr-var-dims'>(profile)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1d211d6b-6ec6-4888-9e93-8a9520e8b5c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1d211d6b-6ec6-4888-9e93-8a9520e8b5c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2d6fc37-c72b-4835-98c9-0def95d6b89f' class='xr-var-data-in' type='checkbox'><label for='data-c2d6fc37-c72b-4835-98c9-0def95d6b89f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>colorBarMaximum :</span></dt><dd>180.0</dd><dt><span>colorBarMinimum :</span></dt><dd>-180.0</dd><dt><span>comment :</span></dt><dd>The depth-averaged current is an estimate of the net current measured while the glider is underwater. The value is calculated over the entire underwater segment, which may consist of 1 or more dives.</dd><dt><span>ioos_category :</span></dt><dd>Location</dd><dt><span>long_name :</span></dt><dd>Depth-averaged Longitude</dd><dt><span>observation_type :</span></dt><dd>calculated</dd><dt><span>platform :</span></dt><dd>glider</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>[1280 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_uv</span></div><div class='xr-var-dims'>(profile)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e720ed92-cdf3-4943-b50d-5d0c710a64ee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e720ed92-cdf3-4943-b50d-5d0c710a64ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43b105d0-4798-42b6-9475-cb3cd0af7e8a' class='xr-var-data-in' type='checkbox'><label for='data-43b105d0-4798-42b6-9475-cb3cd0af7e8a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>comment :</span></dt><dd>The depth-averaged current is an estimate of the net current measured while the glider is underwater. The value is calculated over the entire underwater segment, which may consist of 1 or more dives.</dd><dt><span>ioos_category :</span></dt><dd>Time</dd><dt><span>long_name :</span></dt><dd>Depth-averaged Time</dd><dt><span>observation_type :</span></dt><dd>calculated</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>time_origin :</span></dt><dd>01-JAN-1970 00:00:00</dd></dl></div><div class='xr-var-data'><pre>[1280 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a144d109-4fa7-4b7a-a118-ac85c27269ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a144d109-4fa7-4b7a-a118-ac85c27269ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94297f86-1823-49bd-a322-d4726578adfc' class='xr-var-data-in' type='checkbox'><label for='data-94297f86-1823-49bd-a322-d4726578adfc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Height</dd><dt><span>_CoordinateZisPositive :</span></dt><dd>down</dd><dt><span>accuracy :</span></dt><dd>2</dd><dt><span>actual_range :</span></dt><dd>[-3.233113e-01  9.962955e+02]</dd><dt><span>ancillary_variables :</span></dt><dd>depth_qc</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>colorBarMaximum :</span></dt><dd>2000.0</dd><dt><span>colorBarMinimum :</span></dt><dd>0.0</dd><dt><span>colorBarPalette :</span></dt><dd>OceanDepth</dd><dt><span>comment :</span></dt><dd>Depth below the surface, corrected for average latitude</dd><dt><span>instrument :</span></dt><dd>instrument_ctd</dd><dt><span>ioos_category :</span></dt><dd>Location</dd><dt><span>long_name :</span></dt><dd>Depth</dd><dt><span>observation_type :</span></dt><dd>calculated</dd><dt><span>platform :</span></dt><dd>glider</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>precision :</span></dt><dd>2</dd><dt><span>ref_variable :</span></dt><dd>time</dd><dt><span>reference_datum :</span></dt><dd>sea-surface</dd><dt><span>resolution :</span></dt><dd>2</dd><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>valid_max :</span></dt><dd>2000.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7a85ef45-eee4-468b-8327-e8d71cd81580' class='xr-section-summary-in' type='checkbox'  ><label for='section-7a85ef45-eee4-468b-8327-e8d71cd81580' class='xr-section-summary' >Data variables: <span>(35)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>wmo_id</span></div><div class='xr-var-dims'>(trajectory)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b43dfd6a-2c7b-4de6-9bb5-6f74e093658f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b43dfd6a-2c7b-4de6-9bb5-6f74e093658f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71f848ff-8cc5-435b-9f23-25f293d8286b' class='xr-var-data-in' type='checkbox'><label for='data-71f848ff-8cc5-435b-9f23-25f293d8286b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>ioos_category :</span></dt><dd>Identifier</dd><dt><span>long_name :</span></dt><dd>WMO ID</dd></dl></div><div class='xr-var-data'><pre>[2 values with dtype=object]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>profile_id</span></div><div class='xr-var-dims'>(profile)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cd6b268c-8252-414a-a6be-7d53fccb3c92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd6b268c-8252-414a-a6be-7d53fccb3c92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd91feb0-b455-42b9-b6a2-6f2e5f34baa9' class='xr-var-data-in' type='checkbox'><label for='data-dd91feb0-b455-42b9-b6a2-6f2e5f34baa9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[   1 1290]</dd><dt><span>cf_role :</span></dt><dd>profile_id</dd><dt><span>comment :</span></dt><dd>Sequential profile number within the trajectory. This value is unique in each file that is part of a single trajectory/deployment.</dd><dt><span>ioos_category :</span></dt><dd>Identifier</dd><dt><span>long_name :</span></dt><dd>Profile ID</dd><dt><span>standard_name :</span></dt><dd>profile_id</dd><dt><span>valid_max :</span></dt><dd>2147483647</dd><dt><span>valid_min :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[1280 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(profile)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ee99f4da-dae0-43c4-bbbd-da375862edd3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee99f4da-dae0-43c4-bbbd-da375862edd3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50140fd4-27af-4a97-81ab-98f6fd440a4b' class='xr-var-data-in' type='checkbox'><label for='data-50140fd4-27af-4a97-81ab-98f6fd440a4b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[-0.37468805  0.20334951]</dd><dt><span>colorBarMaximum :</span></dt><dd>0.5</dd><dt><span>colorBarMinimum :</span></dt><dd>-0.5</dd><dt><span>comment :</span></dt><dd>The depth-averaged current is an estimate of the net current measured while the glider is underwater. The value is calculated over the entire underwater segment, which may consist of 1 or more dives.</dd><dt><span>ioos_category :</span></dt><dd>Currents</dd><dt><span>long_name :</span></dt><dd>Depth-averaged Eastward Sea Water Velocity</dd><dt><span>observation_type :</span></dt><dd>calculated</dd><dt><span>platform :</span></dt><dd>glider</dd><dt><span>standard_name :</span></dt><dd>eastward_sea_water_velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>valid_max :</span></dt><dd>10.0</dd><dt><span>valid_min :</span></dt><dd>-10.0</dd></dl></div><div class='xr-var-data'><pre>[1280 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(profile)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4e96bd66-2b88-4cfb-a1fe-d95ec842fe7d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e96bd66-2b88-4cfb-a1fe-d95ec842fe7d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-047f3679-794f-49c1-a4b5-446b75acc092' class='xr-var-data-in' type='checkbox'><label for='data-047f3679-794f-49c1-a4b5-446b75acc092' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[-0.22746372  0.22401356]</dd><dt><span>colorBarMaximum :</span></dt><dd>0.5</dd><dt><span>colorBarMinimum :</span></dt><dd>-0.5</dd><dt><span>comment :</span></dt><dd>The depth-averaged current is an estimate of the net current measured while the glider is underwater. The value is calculated over the entire underwater segment, which may consist of 1 or more dives.</dd><dt><span>ioos_category :</span></dt><dd>Currents</dd><dt><span>long_name :</span></dt><dd>Depth-averaged Northward Sea Water Velocity</dd><dt><span>observation_type :</span></dt><dd>calculated</dd><dt><span>platform :</span></dt><dd>glider</dd><dt><span>standard_name :</span></dt><dd>northward_sea_water_velocity</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>valid_max :</span></dt><dd>10.0</dd><dt><span>valid_min :</span></dt><dd>-10.0</dd></dl></div><div class='xr-var-data'><pre>[1280 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>trajectoryIndex</span></div><div class='xr-var-dims'>(profile)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5107e63c-142b-47c5-9b7f-22bd9c929cd7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5107e63c-142b-47c5-9b7f-22bd9c929cd7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5703a112-49ac-46fb-8076-c03f04d45edb' class='xr-var-data-in' type='checkbox'><label for='data-5703a112-49ac-46fb-8076-c03f04d45edb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>instance_dimension :</span></dt><dd>trajectory</dd><dt><span>ioos_category :</span></dt><dd>Identifier</dd><dt><span>long_name :</span></dt><dd>The trajectory to which this profile is associated.</dd></dl></div><div class='xr-var-data'><pre>[1280 values with dtype=int32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rowSize</span></div><div class='xr-var-dims'>(profile)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-460572d3-d81d-4dcd-8b5a-9ec202364ab0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-460572d3-d81d-4dcd-8b5a-9ec202364ab0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e342cbe-3cd4-4ffc-9a72-aabb2c684e84' class='xr-var-data-in' type='checkbox'><label for='data-8e342cbe-3cd4-4ffc-9a72-aabb2c684e84' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>ioos_category :</span></dt><dd>Identifier</dd><dt><span>long_name :</span></dt><dd>Number of Observations for this Profile</dd><dt><span>sample_dimension :</span></dt><dd>obs</dd></dl></div><div class='xr-var-data'><pre>[1280 values with dtype=int32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>conductivity</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-073e7e7b-a54c-4ddc-9967-f210bdee0eed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-073e7e7b-a54c-4ddc-9967-f210bdee0eed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06dccc76-ec41-45eb-bb4e-9b4c27852f97' class='xr-var-data-in' type='checkbox'><label for='data-06dccc76-ec41-45eb-bb4e-9b4c27852f97' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>accuracy :</span></dt><dd>4</dd><dt><span>actual_range :</span></dt><dd>[2.943311 5.624693]</dd><dt><span>ancillary_variables :</span></dt><dd>conductivity_qc</dd><dt><span>colorBarMaximum :</span></dt><dd>9.0</dd><dt><span>colorBarMinimum :</span></dt><dd>0.0</dd><dt><span>comment :</span></dt><dd>Conductivity corrected for anomalies</dd><dt><span>instrument :</span></dt><dd>instrument_ctd</dd><dt><span>ioos_category :</span></dt><dd>Salinity</dd><dt><span>long_name :</span></dt><dd>Sea Water Electrical Conductivity</dd><dt><span>observation_type :</span></dt><dd>measured</dd><dt><span>platform :</span></dt><dd>glider</dd><dt><span>precision :</span></dt><dd>4</dd><dt><span>ref_variable :</span></dt><dd>time</dd><dt><span>resolution :</span></dt><dd>4</dd><dt><span>standard_name :</span></dt><dd>sea_water_electrical_conductivity</dd><dt><span>units :</span></dt><dd>S m-1</dd><dt><span>valid_max :</span></dt><dd>10.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>conductivity_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-59da1f37-746b-4272-9b5f-6ccb285eed8e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59da1f37-746b-4272-9b5f-6ccb285eed8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-76fa6256-fb81-470a-a8de-c488ed81b634' class='xr-var-data-in' type='checkbox'><label for='data-76fa6256-fb81-470a-a8de-c488ed81b634' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[1 8]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used not_used interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>qc_val</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>conductivity Variable Quality Flag</dd><dt><span>standard_name :</span></dt><dd>sea_water_electrical_conductivity status_flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>density</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9458d58f-62e0-4cdb-af6c-2797355cdca6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9458d58f-62e0-4cdb-af6c-2797355cdca6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a691b06-a7dc-4443-922e-13b8d315ef76' class='xr-var-data-in' type='checkbox'><label for='data-3a691b06-a7dc-4443-922e-13b8d315ef76' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>accuracy :</span></dt><dd>2</dd><dt><span>actual_range :</span></dt><dd>[1013.971 1030.576]</dd><dt><span>ancillary_variables :</span></dt><dd>density_qc</dd><dt><span>colorBarMaximum :</span></dt><dd>1032.0</dd><dt><span>colorBarMinimum :</span></dt><dd>1020.0</dd><dt><span>comment :</span></dt><dd>Sea water potential density</dd><dt><span>instrument :</span></dt><dd>instrument_ctd</dd><dt><span>ioos_category :</span></dt><dd>Other</dd><dt><span>long_name :</span></dt><dd>Sea Water Density</dd><dt><span>observation_type :</span></dt><dd>calculated</dd><dt><span>platform :</span></dt><dd>glider</dd><dt><span>precision :</span></dt><dd>2</dd><dt><span>resolution :</span></dt><dd>2</dd><dt><span>standard_name :</span></dt><dd>sea_water_density</dd><dt><span>units :</span></dt><dd>kg m-3</dd><dt><span>valid_max :</span></dt><dd>1040.0</dd><dt><span>valid_min :</span></dt><dd>1015.0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>density_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-67951bd6-34a4-4026-95af-eca0557146b7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-67951bd6-34a4-4026-95af-eca0557146b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47c52e35-b24f-4ba7-b93f-0c309473bf64' class='xr-var-data-in' type='checkbox'><label for='data-47c52e35-b24f-4ba7-b93f-0c309473bf64' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[0 0]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used not_used interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>qc_val</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>density Variable Quality Flag</dd><dt><span>standard_name :</span></dt><dd>sea_water_density status_flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c99e5ac1-8899-4a41-b61f-42d21f1aca61' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c99e5ac1-8899-4a41-b61f-42d21f1aca61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1807bf5-7abb-4ef2-9336-a60ab12f6096' class='xr-var-data-in' type='checkbox'><label for='data-a1807bf5-7abb-4ef2-9336-a60ab12f6096' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[0 0]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used not_used interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>qc_val</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>depth Variable Quality Flag</dd><dt><span>standard_name :</span></dt><dd>depth status_flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>instrument_ctd</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3c4ce822-f2e1-4fed-97af-fbee5cdfa73a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c4ce822-f2e1-4fed-97af-fbee5cdfa73a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-806d27f5-875d-4926-a515-3c57d7f9a515' class='xr-var-data-in' type='checkbox'><label for='data-806d27f5-875d-4926-a515-3c57d7f9a515' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>calibration_date :</span></dt><dd>2020-01-20</dd><dt><span>calibration_report :</span></dt><dd>2020-01-20</dd><dt><span>comment :</span></dt><dd>CTD</dd><dt><span>factory_calibrated :</span></dt><dd>2020-01-20</dd><dt><span>ioos_category :</span></dt><dd>Identifier</dd><dt><span>long_name :</span></dt><dd>CTD Metadata</dd><dt><span>make_model :</span></dt><dd>Seabird SBE41</dd><dt><span>platform :</span></dt><dd>glider</dd><dt><span>serial_number :</span></dt><dd>0344</dd><dt><span>type :</span></dt><dd>thermosalinograph</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1d45cdf8-4911-4026-9dfb-f9a066e02591' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1d45cdf8-4911-4026-9dfb-f9a066e02591' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-371a601c-8578-4a6f-a03e-d74bd1100c65' class='xr-var-data-in' type='checkbox'><label for='data-371a601c-8578-4a6f-a03e-d74bd1100c65' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[0 0]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used not_used interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>qc_val</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>latitude Quality Flag</dd><dt><span>qc_val :</span></dt><dd>0</dd><dt><span>standard_name :</span></dt><dd>latitude status_flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_uv_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7bc45da2-90f4-47ae-b991-a6b0bd288d69' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7bc45da2-90f4-47ae-b991-a6b0bd288d69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-610105b2-0618-4ac3-b835-7ac6282aa47e' class='xr-var-data-in' type='checkbox'><label for='data-610105b2-0618-4ac3-b835-7ac6282aa47e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[0 0]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used not_used interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>qc_val</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>lat_uv Variable Quality Flag</dd><dt><span>qc_val :</span></dt><dd>0</dd><dt><span>standard_name :</span></dt><dd>latitude status_flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e6dad5ec-a7a1-45f9-9222-4e3d7c3fe0a2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e6dad5ec-a7a1-45f9-9222-4e3d7c3fe0a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d43af6b0-e2dc-4302-9672-4ed109c40eca' class='xr-var-data-in' type='checkbox'><label for='data-d43af6b0-e2dc-4302-9672-4ed109c40eca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[0 0]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used not_used interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>qc_val</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>latitude Variable Quality Flag</dd><dt><span>qc_val :</span></dt><dd>0</dd><dt><span>standard_name :</span></dt><dd>latitude status_flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d1011484-8e8d-44e5-a1e9-b5c351694a8f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d1011484-8e8d-44e5-a1e9-b5c351694a8f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af1e5eb6-b36f-4149-bfb7-967ff652b9e9' class='xr-var-data-in' type='checkbox'><label for='data-af1e5eb6-b36f-4149-bfb7-967ff652b9e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[0 0]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used not_used interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>qc_val</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>longitude Quality Flag</dd><dt><span>qc_val :</span></dt><dd>0</dd><dt><span>standard_name :</span></dt><dd>longitude status_flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_uv_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-19db7ef8-19ef-4463-b3a4-dfc3ff52a200' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-19db7ef8-19ef-4463-b3a4-dfc3ff52a200' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71476af4-73c5-423b-a5bc-27a65d78cf6b' class='xr-var-data-in' type='checkbox'><label for='data-71476af4-73c5-423b-a5bc-27a65d78cf6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[0 0]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used not_used interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>qc_val</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>lon_uv Variable Quality Flag</dd><dt><span>qc_val :</span></dt><dd>0</dd><dt><span>standard_name :</span></dt><dd>longitude status_flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-80d21fda-1f5f-491c-b2ca-0c74f46f2eb6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-80d21fda-1f5f-491c-b2ca-0c74f46f2eb6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9bb04c54-49c1-4632-bec3-c6674b5b200a' class='xr-var-data-in' type='checkbox'><label for='data-9bb04c54-49c1-4632-bec3-c6674b5b200a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[0 0]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used not_used interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>qc_val</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>longitude Variable Quality Flag</dd><dt><span>qc_val :</span></dt><dd>0</dd><dt><span>standard_name :</span></dt><dd>longitude status_flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>platform_meta</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bf16356e-0ad8-4f26-a555-2aa493b87962' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf16356e-0ad8-4f26-a555-2aa493b87962' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c05b1d18-9132-4bd2-8a03-a9db76bc5bf2' class='xr-var-data-in' type='checkbox'><label for='data-c05b1d18-9132-4bd2-8a03-a9db76bc5bf2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>comment :</span></dt><dd>Seaglider</dd><dt><span>id :</span></dt><dd>sg658</dd><dt><span>instrument :</span></dt><dd>instrument_ctd</dd><dt><span>ioos_category :</span></dt><dd>Identifier</dd><dt><span>long_name :</span></dt><dd>Platform Metadata</dd><dt><span>type :</span></dt><dd>glider</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>wmo_id :</span></dt><dd>4803953</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>precise_lat</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5dc7b011-2ee4-4040-9908-4e9800f9e59c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5dc7b011-2ee4-4040-9908-4e9800f9e59c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e2e0e43-7e52-455b-8002-81dbfa751876' class='xr-var-data-in' type='checkbox'><label for='data-0e2e0e43-7e52-455b-8002-81dbfa751876' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[38.40290106 40.28092544]</dd><dt><span>ancillary_variables :</span></dt><dd>lat_qc</dd><dt><span>ancillary_varibles :</span></dt><dd>precise_lat_qc</dd><dt><span>colorBarMaximum :</span></dt><dd>90.0</dd><dt><span>colorBarMinimum :</span></dt><dd>-90.0</dd><dt><span>comment :</span></dt><dd>Interpolated latitude at each point in the time-series</dd><dt><span>coordinate_reference_frame :</span></dt><dd>urn:ogc:crs:EPSG::4326</dd><dt><span>ioos_category :</span></dt><dd>Location</dd><dt><span>long_name :</span></dt><dd>Precise Latitude</dd><dt><span>observation_type :</span></dt><dd>measured</dd><dt><span>platform :</span></dt><dd>glider</dd><dt><span>ref_variable :</span></dt><dd>time</dd><dt><span>reference :</span></dt><dd>WGS84</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>precise_lat_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-859d80ac-ccb2-4458-8d40-070f0357f687' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-859d80ac-ccb2-4458-8d40-070f0357f687' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-827c734e-91df-4852-b572-c8566f7d3bed' class='xr-var-data-in' type='checkbox'><label for='data-827c734e-91df-4852-b572-c8566f7d3bed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>precise_lat Variable Quality Flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>precise_lon</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1cdac751-b153-4c2f-9256-5a943bcc1c6d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1cdac751-b153-4c2f-9256-5a943bcc1c6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-721c5f37-886c-481f-a6a0-d7ef624f67b7' class='xr-var-data-in' type='checkbox'><label for='data-721c5f37-886c-481f-a6a0-d7ef624f67b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[-72.39085452 -69.15817393]</dd><dt><span>ancillary_variables :</span></dt><dd>lon_qc</dd><dt><span>ancillary_varibles :</span></dt><dd>precise_lon_qc</dd><dt><span>colorBarMaximum :</span></dt><dd>180.0</dd><dt><span>colorBarMinimum :</span></dt><dd>-180.0</dd><dt><span>comment :</span></dt><dd>Interpolated longitude at each point in the time-series</dd><dt><span>coordinate_reference_frame :</span></dt><dd>urn:ogc:crs:EPSG::4326</dd><dt><span>ioos_category :</span></dt><dd>Location</dd><dt><span>long_name :</span></dt><dd>Precise Longitude</dd><dt><span>observation_type :</span></dt><dd>measured</dd><dt><span>platform :</span></dt><dd>glider</dd><dt><span>ref_variable :</span></dt><dd>time</dd><dt><span>reference :</span></dt><dd>WGS84</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>precise_lon_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ebb4ba30-9de8-47b3-ab99-62ea6da9394e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ebb4ba30-9de8-47b3-ab99-62ea6da9394e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5588a71f-6fa2-430a-81e5-46d4c818c991' class='xr-var-data-in' type='checkbox'><label for='data-5588a71f-6fa2-430a-81e5-46d4c818c991' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>[0 1 2 3 4 5 6 7 8 9]</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>precise_lon Variable Quality Flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>precise_time</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9576d6ba-4e8c-47d0-b06a-fc8d710c7dcf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9576d6ba-4e8c-47d0-b06a-fc8d710c7dcf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a8196c5-dabf-4724-82e9-518668c1ca15' class='xr-var-data-in' type='checkbox'><label for='data-9a8196c5-dabf-4724-82e9-518668c1ca15' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[1.64946801e+09 1.66067644e+09]</dd><dt><span>ancillary_variables :</span></dt><dd>time_qc</dd><dt><span>comment :</span></dt><dd>Timestamp at each point in the time-series</dd><dt><span>ioos_category :</span></dt><dd>Time</dd><dt><span>long_name :</span></dt><dd>Precise Time</dd><dt><span>observation_type :</span></dt><dd>measured</dd><dt><span>ref_variable :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>time_origin :</span></dt><dd>01-JAN-1970 00:00:00</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>precise_time_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c29c5bf6-17ac-48c1-8160-07142c583112' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c29c5bf6-17ac-48c1-8160-07142c583112' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc8b015d-091f-4c64-9ee2-53132ca17ef3' class='xr-var-data-in' type='checkbox'><label for='data-bc8b015d-091f-4c64-9ee2-53132ca17ef3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[0 0]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used not_used interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>qc_val</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>precise_time Variable Quality Flag</dd><dt><span>qc_val :</span></dt><dd>0</dd><dt><span>standard_name :</span></dt><dd>time status_flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e619223c-b3f3-4375-aea6-235d6978a8c7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e619223c-b3f3-4375-aea6-235d6978a8c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb6f8bfa-a54f-4785-9ac6-705fb09a96bd' class='xr-var-data-in' type='checkbox'><label for='data-fb6f8bfa-a54f-4785-9ac6-705fb09a96bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>accuracy :</span></dt><dd>2</dd><dt><span>actual_range :</span></dt><dd>[-7.045737e-02  1.006423e+03]</dd><dt><span>ancillary_variables :</span></dt><dd>pressure_qc</dd><dt><span>colorBarMaximum :</span></dt><dd>2000.0</dd><dt><span>colorBarMinimum :</span></dt><dd>0.0</dd><dt><span>comment :</span></dt><dd>Uncorrected sea-water pressure</dd><dt><span>instrument :</span></dt><dd>instrument_ctd</dd><dt><span>ioos_category :</span></dt><dd>Pressure</dd><dt><span>long_name :</span></dt><dd>Sea Water Pressure</dd><dt><span>observation_type :</span></dt><dd>measured</dd><dt><span>platform :</span></dt><dd>glider</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>precision :</span></dt><dd>2</dd><dt><span>ref_variable :</span></dt><dd>time</dd><dt><span>reference_datum :</span></dt><dd>sea-surface</dd><dt><span>resolution :</span></dt><dd>2</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd><dt><span>units :</span></dt><dd>dbar</dd><dt><span>valid_max :</span></dt><dd>2000.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8c51b7e9-021e-48ad-b2a1-b4941aa4319a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c51b7e9-021e-48ad-b2a1-b4941aa4319a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15112718-74ad-4c26-b3d6-04a04e4d1b5a' class='xr-var-data-in' type='checkbox'><label for='data-15112718-74ad-4c26-b3d6-04a04e4d1b5a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[0 0]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used not_used interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>qc_val</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>pressure Variable Quality Flag</dd><dt><span>qc_val :</span></dt><dd>0</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure status_flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>salinity</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7fe706b0-497e-46b6-8530-838ed65f36d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7fe706b0-497e-46b6-8530-838ed65f36d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-849927be-8d70-4909-bfd0-809f81d41d5b' class='xr-var-data-in' type='checkbox'><label for='data-849927be-8d70-4909-bfd0-809f81d41d5b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>accuracy :</span></dt><dd>2</dd><dt><span>actual_range :</span></dt><dd>[31.08879 38.64265]</dd><dt><span>ancillary_variables :</span></dt><dd>salinity_qc</dd><dt><span>colorBarMaximum :</span></dt><dd>37.0</dd><dt><span>colorBarMinimum :</span></dt><dd>30.0</dd><dt><span>comment :</span></dt><dd>Salinity corrected for thermal-inertia effects (PSU)</dd><dt><span>instrument :</span></dt><dd>instrument_ctd</dd><dt><span>ioos_category :</span></dt><dd>Salinity</dd><dt><span>long_name :</span></dt><dd>Sea Water Practical Salinity</dd><dt><span>observation_type :</span></dt><dd>calculated</dd><dt><span>platform :</span></dt><dd>glider</dd><dt><span>precision :</span></dt><dd>2</dd><dt><span>resolution :</span></dt><dd>2</dd><dt><span>standard_name :</span></dt><dd>sea_water_practical_salinity</dd><dt><span>units :</span></dt><dd>1e-3</dd><dt><span>valid_max :</span></dt><dd>40.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>salinity_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3ba11a15-f62e-406f-9cfa-630de9d77859' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ba11a15-f62e-406f-9cfa-630de9d77859' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0cbc88c3-2a51-4f19-84f2-d0b2bfe52ab1' class='xr-var-data-in' type='checkbox'><label for='data-0cbc88c3-2a51-4f19-84f2-d0b2bfe52ab1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[1 8]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used not_used interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>qc_val</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>salinity Variable Quality Flag</dd><dt><span>standard_name :</span></dt><dd>sea_water_salinity status_flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cd56fbbd-1d19-4d28-879c-86993f9a6281' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd56fbbd-1d19-4d28-879c-86993f9a6281' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a7f49f7-5939-4076-9392-58d4a80bab58' class='xr-var-data-in' type='checkbox'><label for='data-3a7f49f7-5939-4076-9392-58d4a80bab58' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>accuracy :</span></dt><dd>3</dd><dt><span>actual_range :</span></dt><dd>[ 4.13572 27.50763]</dd><dt><span>ancillary_variables :</span></dt><dd>temperature_qc</dd><dt><span>colorBarMaximum :</span></dt><dd>32.0</dd><dt><span>colorBarMinimum :</span></dt><dd>0.0</dd><dt><span>comment :</span></dt><dd>Temperature (in situ) corrected for thermistor first-order lag</dd><dt><span>instrument :</span></dt><dd>instrument_ctd</dd><dt><span>ioos_category :</span></dt><dd>Temperature</dd><dt><span>long_name :</span></dt><dd>Sea Water Temperature</dd><dt><span>observation_type :</span></dt><dd>measured</dd><dt><span>platform :</span></dt><dd>glider</dd><dt><span>precision :</span></dt><dd>3</dd><dt><span>ref_variable :</span></dt><dd>time</dd><dt><span>resolution :</span></dt><dd>3</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd><dt><span>units :</span></dt><dd>Celsius</dd><dt><span>valid_max :</span></dt><dd>40.0</dd><dt><span>valid_min :</span></dt><dd>-5.0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2b583806-9b0d-4c93-86e5-0e2f0d8afaf0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b583806-9b0d-4c93-86e5-0e2f0d8afaf0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99dfed28-e0aa-43b1-98e6-8277194e9679' class='xr-var-data-in' type='checkbox'><label for='data-99dfed28-e0aa-43b1-98e6-8277194e9679' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[1 8]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used not_used interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>qc_val</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>temperature Variable Quality Flag</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature status_flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dba378cb-1687-43da-9792-89055921092f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dba378cb-1687-43da-9792-89055921092f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0bff3a5e-520b-47c1-b171-922261327172' class='xr-var-data-in' type='checkbox'><label for='data-0bff3a5e-520b-47c1-b171-922261327172' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[0 0]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used not_used interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>qc_val</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>time Variable Quality Flag</dd><dt><span>qc_val :</span></dt><dd>0</dd><dt><span>standard_name :</span></dt><dd>time status_flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_uv_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ad7a90bc-ef53-4a40-a452-950c14d70f1f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad7a90bc-ef53-4a40-a452-950c14d70f1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-225f49dc-e1e2-4c9d-b2cc-a5a49325a5cb' class='xr-var-data-in' type='checkbox'><label for='data-225f49dc-e1e2-4c9d-b2cc-a5a49325a5cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[0 0]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used not_used interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>qc_val</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>time_uv Variable Quality Flag</dd><dt><span>qc_val :</span></dt><dd>0</dd><dt><span>standard_name :</span></dt><dd>time status_flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5ab0f0f3-7292-4e98-9711-111b38df535f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ab0f0f3-7292-4e98-9711-111b38df535f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01ce4ae3-66bd-4ba0-a0d4-6abd8a81e2ef' class='xr-var-data-in' type='checkbox'><label for='data-01ce4ae3-66bd-4ba0-a0d4-6abd8a81e2ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[1 1]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used not_used interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>qc_val</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>u Variable Quality Flag</dd><dt><span>standard_name :</span></dt><dd>eastward_sea_water_velocity status_flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v_qc</span></div><div class='xr-var-dims'>(obs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-08216f69-edcc-4a1e-8c97-9636ff7444eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-08216f69-edcc-4a1e-8c97-9636ff7444eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec567965-0db2-428d-a51d-128739fe5593' class='xr-var-data-in' type='checkbox'><label for='data-ec567965-0db2-428d-a51d-128739fe5593' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[1 1]</dd><dt><span>flag_meanings :</span></dt><dd>no_qc_performed good_data probably_good_data bad_data_that_are_potentially_correctable bad_data value_changed not_used not_used interpolated_value missing_value</dd><dt><span>flag_values :</span></dt><dd>qc_val</dd><dt><span>ioos_category :</span></dt><dd>Quality</dd><dt><span>long_name :</span></dt><dd>v Variable Quality Flag</dd><dt><span>standard_name :</span></dt><dd>northward_sea_water_velocity status_flag</dd><dt><span>valid_max :</span></dt><dd>9</dd><dt><span>valid_min :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>[1471982 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-44a462ee-b62d-477c-ac00-8d135118d3c0' class='xr-section-summary-in' type='checkbox'  ><label for='section-44a462ee-b62d-477c-ac00-8d135118d3c0' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>trajectory</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3f0a2ed4-39b2-438a-a213-fc7b1dbcc949' class='xr-index-data-in' type='checkbox'/><label for='index-3f0a2ed4-39b2-438a-a213-fc7b1dbcc949' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;&#x27;, &#x27;sg658-20220408T0&#x27;], dtype=&#x27;object&#x27;, name=&#x27;trajectory&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5e680825-ae0e-46c5-bd5d-414e372ce5f5' class='xr-section-summary-in' type='checkbox'  ><label for='section-5e680825-ae0e-46c5-bd5d-414e372ce5f5' class='xr-section-summary' >Attributes: <span>(62)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>acknowledgment :</span></dt><dd>This project is funded by Shell Exploration &amp; Production Company</dd><dt><span>cdm_data_type :</span></dt><dd>TrajectoryProfile</dd><dt><span>cdm_profile_variables :</span></dt><dd>time_uv,lat_uv,lon_uv,u,v,profile_id,time,latitude,longitude</dd><dt><span>cdm_trajectory_variables :</span></dt><dd>trajectory,wmo_id</dd><dt><span>comment :</span></dt><dd>Underwater glider temperature and salinity profiles</dd><dt><span>contributor_name :</span></dt><dd>Palter J, Gray A, Currier R</dd><dt><span>contributor_role :</span></dt><dd>Principal Investigator, Principal Investigator, Data Manager</dd><dt><span>Conventions :</span></dt><dd>Unidata Dataset Discovery v1.0, COARDS, CF-1.6</dd><dt><span>creator_email :</span></dt><dd>bob.currier@gcoos.org</dd><dt><span>creator_name :</span></dt><dd>Bob Currier</dd><dt><span>creator_url :</span></dt><dd>https://gandalf.gcoos.org</dd><dt><span>date_created :</span></dt><dd>2022-08-16T06:46:16Z</dd><dt><span>date_issued :</span></dt><dd>2022-08-16T06:46:16Z</dd><dt><span>date_modified :</span></dt><dd>2022-08-16T06:46:16Z</dd><dt><span>Easternmost_Easting :</span></dt><dd>-69.16772673599277</dd><dt><span>featureType :</span></dt><dd>TrajectoryProfile</dd><dt><span>format_version :</span></dt><dd>gandalf_sg2gdac.py V1</dd><dt><span>geospatial_lat_max :</span></dt><dd>40.28010559436991</dd><dt><span>geospatial_lat_min :</span></dt><dd>38.40409628101434</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_max :</span></dt><dd>-69.16772673599277</dd><dt><span>geospatial_lon_min :</span></dt><dd>-72.38884713321431</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>geospatial_vertical_max :</span></dt><dd>996.2955</dd><dt><span>geospatial_vertical_min :</span></dt><dd>-0.3233113</dd><dt><span>geospatial_vertical_positive :</span></dt><dd>down</dd><dt><span>geospatial_vertical_units :</span></dt><dd>m</dd><dt><span>gts_ingest :</span></dt><dd>true</dd><dt><span>history :</span></dt><dd>Created on 2022-08-16T06:46:16Z using gandalf_sg2gdac.py V1\n",
       "2023-01-13T13:51:05Z (local files)\n",
       "2023-01-13T13:51:05Z https://gliders.ioos.us/erddap/tabledap/sg658-20220408T0000.ncCF</dd><dt><span>id :</span></dt><dd>sg658-20220816T064616</dd><dt><span>infoUrl :</span></dt><dd>https://gliders.ioos.us/erddap/</dd><dt><span>institution :</span></dt><dd>University of Rhode Island, University of Washington and Gulf of Mexico Ocean Observing System (GCOOS)</dd><dt><span>instrument_ctd :</span></dt><dd>SBE41</dd><dt><span>ioos_dac_checksum :</span></dt><dd>fbb179fbc9d1c5acaee883b7593563e6</dd><dt><span>ioos_dac_completed :</span></dt><dd>True</dd><dt><span>keywords :</span></dt><dd>AUVS &gt; Autonomous Underwater Vehicles, Earth Science &gt; Oceans &gt; Ocean Pressure &gt; Water Pressure, Earth Science &gt; Oceans &gt; Ocean Temperature &gt; Water Temperature, Earth Science &gt; Oceans &gt; Salinity/Density &gt; Conductivity, Earth Science &gt; Oceans &gt; Salinity/Density &gt; Density, Earth Science &gt; Oceans &gt; Salinity/Density &gt; Salinity, glider, In Situ Ocean-based platforms &gt; Seaglider, Slocum, Spray, trajectory, underwater glider, water, wmo</dd><dt><span>keywords_vocabulary :</span></dt><dd>GCMD Science Keywords</dd><dt><span>license :</span></dt><dd>These datinstrument_ctda may be redistributed and used without restrictions. Data provided as is with no expressed or implied warranty of quality control or quality assurance</dd><dt><span>Metadata_Conventions :</span></dt><dd>Unidata Dataset Discovery v1.0, COARDS, CF-1.6</dd><dt><span>metadata_link :</span></dt><dd>None</dd><dt><span>naming_authority :</span></dt><dd>None</dd><dt><span>Northernmost_Northing :</span></dt><dd>40.28010559436991</dd><dt><span>platform :</span></dt><dd>0</dd><dt><span>platform_type :</span></dt><dd>Seaglider</dd><dt><span>processing_level :</span></dt><dd>Data provided as is with no expressed or implied assurance of quality assurance or quality control.</dd><dt><span>project :</span></dt><dd>Sustained Underwater Glider Observations for Improving Atlantic Tropical Cyclone Intensity Forecasts</dd><dt><span>publisher_email :</span></dt><dd>bob.currier@gcoos.org</dd><dt><span>publisher_name :</span></dt><dd>Bob Currier</dd><dt><span>publisher_url :</span></dt><dd>https://gandalf.gcoos.org</dd><dt><span>qc_val :</span></dt><dd>[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]</dd><dt><span>references :</span></dt><dd>GCOOS</dd><dt><span>sea_name :</span></dt><dd>Gulf of Mexico</dd><dt><span>source :</span></dt><dd>Observational data from a profiling underwater glider</dd><dt><span>sourceUrl :</span></dt><dd>(local files)</dd><dt><span>Southernmost_Northing :</span></dt><dd>38.40409628101434</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF-v25</dd><dt><span>subsetVariables :</span></dt><dd>wmo_id,trajectory,profile_id,time,latitude,longitude</dd><dt><span>summary :</span></dt><dd>Collaborative Research: Investigating meso- and submesoscale variability in air-sea CO2 exchange in the Gulf Stream region with autonomous platforms.</dd><dt><span>time_coverage_end :</span></dt><dd>2022-08-16T18:52:09Z</dd><dt><span>time_coverage_start :</span></dt><dd>2022-04-09T01:37:13Z</dd><dt><span>title :</span></dt><dd>sg658-20220408T0000</dd><dt><span>Westernmost_Easting :</span></dt><dd>-72.38884713321431</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:          (trajectory: 2, profile: 1280, obs: 1471982)\n",
       "Coordinates:\n",
       "  * trajectory       (trajectory) object '' 'sg658-20220408T0'\n",
       "    time             (profile) datetime64[ns] ...\n",
       "    latitude         (profile) float64 ...\n",
       "    longitude        (profile) float64 ...\n",
       "    lat_uv           (profile) float64 ...\n",
       "    lon_uv           (profile) float64 ...\n",
       "    time_uv          (profile) datetime64[ns] ...\n",
       "    depth            (obs) float32 ...\n",
       "Dimensions without coordinates: profile, obs\n",
       "Data variables: (12/35)\n",
       "    wmo_id           (trajectory) object ...\n",
       "    profile_id       (profile) float64 ...\n",
       "    u                (profile) float64 ...\n",
       "    v                (profile) float64 ...\n",
       "    trajectoryIndex  (profile) int32 ...\n",
       "    rowSize          (profile) int32 ...\n",
       "    ...               ...\n",
       "    temperature      (obs) float32 ...\n",
       "    temperature_qc   (obs) float32 ...\n",
       "    time_qc          (obs) float32 ...\n",
       "    time_uv_qc       (obs) float32 ...\n",
       "    u_qc             (obs) float32 ...\n",
       "    v_qc             (obs) float32 ...\n",
       "Attributes: (12/62)\n",
       "    acknowledgment:                This project is funded by Shell Exploratio...\n",
       "    cdm_data_type:                 TrajectoryProfile\n",
       "    cdm_profile_variables:         time_uv,lat_uv,lon_uv,u,v,profile_id,time,...\n",
       "    cdm_trajectory_variables:      trajectory,wmo_id\n",
       "    comment:                       Underwater glider temperature and salinity...\n",
       "    contributor_name:              Palter J, Gray A, Currier R\n",
       "    ...                            ...\n",
       "    subsetVariables:               wmo_id,trajectory,profile_id,time,latitude...\n",
       "    summary:                       Collaborative Research: Investigating meso...\n",
       "    time_coverage_end:             2022-08-16T18:52:09Z\n",
       "    time_coverage_start:           2022-04-09T01:37:13Z\n",
       "    title:                         sg658-20220408T0000\n",
       "    Westernmost_Easting:           -72.38884713321431"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_example"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab1584b3-8628-4e09-816e-bd9a45f8cca3",
   "metadata": {},
   "source": [
    "Let's focus just on glider location for now. We'll take longitude, latitude, depth and time. We will download the data as pandas dataframes to keep memory usage down. We're not interested in metadata. We will look at surface data only using the `depth<=` kwarg in `e.constraints`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e0c487da-e2af-4ef3-bc61-3d19987646fe",
   "metadata": {},
   "outputs": [],
   "source": [
    "e.variables = [\"longitude\", \"latitude\", \"depth\", \"time\"]\n",
    "e.constraints = {\"depth<=\": 5}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b57f4073-187f-498b-b95c-02da6edc6b56",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>longitude (degrees_east)</th>\n",
       "      <th>latitude (degrees_north)</th>\n",
       "      <th>depth (m)</th>\n",
       "      <th>time (UTC)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-70.731646</td>\n",
       "      <td>39.847202</td>\n",
       "      <td>0.378375</td>\n",
       "      <td>2022-04-09T01:37:13Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-70.731646</td>\n",
       "      <td>39.847202</td>\n",
       "      <td>0.411714</td>\n",
       "      <td>2022-04-09T01:37:13Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-70.731646</td>\n",
       "      <td>39.847202</td>\n",
       "      <td>0.329309</td>\n",
       "      <td>2022-04-09T01:37:13Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-70.731646</td>\n",
       "      <td>39.847202</td>\n",
       "      <td>0.524400</td>\n",
       "      <td>2022-04-09T01:37:13Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-70.731646</td>\n",
       "      <td>39.847202</td>\n",
       "      <td>0.465898</td>\n",
       "      <td>2022-04-09T01:37:13Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17164</th>\n",
       "      <td>-71.199379</td>\n",
       "      <td>40.278881</td>\n",
       "      <td>1.443916</td>\n",
       "      <td>2022-08-16T17:45:40Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17165</th>\n",
       "      <td>-71.199379</td>\n",
       "      <td>40.278881</td>\n",
       "      <td>1.713398</td>\n",
       "      <td>2022-08-16T17:45:40Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17166</th>\n",
       "      <td>-71.199379</td>\n",
       "      <td>40.278881</td>\n",
       "      <td>2.294517</td>\n",
       "      <td>2022-08-16T17:45:40Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17167</th>\n",
       "      <td>-71.199379</td>\n",
       "      <td>40.278881</td>\n",
       "      <td>3.118471</td>\n",
       "      <td>2022-08-16T17:45:40Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17168</th>\n",
       "      <td>-71.199379</td>\n",
       "      <td>40.278881</td>\n",
       "      <td>4.239901</td>\n",
       "      <td>2022-08-16T17:45:40Z</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>17169 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       longitude (degrees_east)  latitude (degrees_north)  depth (m)  \\\n",
       "0                    -70.731646                 39.847202   0.378375   \n",
       "1                    -70.731646                 39.847202   0.411714   \n",
       "2                    -70.731646                 39.847202   0.329309   \n",
       "3                    -70.731646                 39.847202   0.524400   \n",
       "4                    -70.731646                 39.847202   0.465898   \n",
       "...                         ...                       ...        ...   \n",
       "17164                -71.199379                 40.278881   1.443916   \n",
       "17165                -71.199379                 40.278881   1.713398   \n",
       "17166                -71.199379                 40.278881   2.294517   \n",
       "17167                -71.199379                 40.278881   3.118471   \n",
       "17168                -71.199379                 40.278881   4.239901   \n",
       "\n",
       "                 time (UTC)  \n",
       "0      2022-04-09T01:37:13Z  \n",
       "1      2022-04-09T01:37:13Z  \n",
       "2      2022-04-09T01:37:13Z  \n",
       "3      2022-04-09T01:37:13Z  \n",
       "4      2022-04-09T01:37:13Z  \n",
       "...                     ...  \n",
       "17164  2022-08-16T17:45:40Z  \n",
       "17165  2022-08-16T17:45:40Z  \n",
       "17166  2022-08-16T17:45:40Z  \n",
       "17167  2022-08-16T17:45:40Z  \n",
       "17168  2022-08-16T17:45:40Z  \n",
       "\n",
       "[17169 rows x 4 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_example = e.to_pandas()\n",
    "df_example"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba97498b-9138-471b-83dd-b21bf830fcee",
   "metadata": {},
   "source": [
    "### 4. Download all datasets\n",
    "\n",
    "We will download the datasets and combine them into a single dataframe for convenience"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "acd41c58-ae9b-4001-ac5f-9a5c8002c43c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4d1fcfbe86c242039d092544a17b7734",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/28 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_all = pd.DataFrame()\n",
    "for i, ds_name in enumerate(tqdm(datasets_nrt)):\n",
    "    e.dataset_id = ds_name\n",
    "    df = e.to_pandas()\n",
    "    df[\"dataset_id\"] = ds_name\n",
    "    df[\"dataset_num\"] = i\n",
    "    df_all = pd.concat((df_all, df))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3770b40c-b29e-4499-b25a-4f5fd9fb1b5e",
   "metadata": {},
   "source": [
    "That download took a while, so I will save the resulting output to a file that I can load next time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8bd891ed-a51d-457e-bd4d-313f7ac7909a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_all.to_csv(\"gulf_stream_gliders.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "74e3fac1-14d7-416d-b260-209ba220a0ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_all = pd.read_csv(\"gulf_stream_gliders.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3077c9c3-571e-4ab8-9f06-3b56ff4ece81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<cartopy.mpl.gridliner.Gridliner at 0x7f25dc080790>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8, 8))\n",
    "ax = fig.add_subplot(1, 1, 1, projection=ccrs.Robinson())\n",
    "for ds_id in datasets_nrt:\n",
    "    df_sub =df_all[df_all[\"dataset_id\"]==ds_id]\n",
    "    ax.plot(df_sub[\"longitude (degrees_east)\"][::10],\n",
    "            df_sub[\"latitude (degrees_north)\"][::10],\n",
    "           label=ds_id, transform=ccrs.PlateCarree())\n",
    "ax.coastlines()\n",
    "ax.stock_img()\n",
    "#ax.set_extent([-85, -58, 20, 45], crs=ccrs.PlateCarree())\n",
    "ax.gridlines()\n",
    "#ax.legend()\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}