Add pymt lesson material

These have been adapted from the Notebooks used in the 2020 CSDMS Annual Meeting.
csdms · Jul 9, 2020 · d76e61c · d76e61c
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diff --git a/lessons/pymt/cem.ipynb b/lessons/pymt/cem.ipynb
diff --git a/lessons/pymt/cem_and_waves.ipynb b/lessons/pymt/cem_and_waves.ipynb
diff --git a/lessons/pymt/cem_and_waves_and_hydrotrend.ipynb b/lessons/pymt/cem_and_waves_and_hydrotrend.ipynb
diff --git a/lessons/pymt/child.ipynb b/lessons/pymt/child.ipynb
diff --git a/lessons/pymt/ecsimplesnow.ipynb b/lessons/pymt/ecsimplesnow.ipynb
@@ -0,0 +1,169 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# ECSimpleSnow component\n",
+    "\n",
+    "ECSimpleSnow is an empirical algorithm to melt snow according to the surface temperature and increase snow depth according to the precipitation that has fallen since the last time step.\n",
+    "\n",
+    "## Details: \n",
+    "\n",
+    "**Brown, R. D., Brasnett, B., & Robinson, D. (2003). Gridded North American monthly snow depth and snow water equivalent for GCM evaluation. Atmosphere-Ocean, 41(1), 1-14.**\n",
+    "\n",
+    "**URL:** https://www.tandfonline.com/doi/abs/10.3137/ao.410101\n",
+    "\n",
+    "## Source code in Fortran:\n",
+    "\n",
+    "**URL:** https://github.com/permamodel/Snow_BMI_Fortran\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### load module"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "from scipy.optimize import curve_fit\n",
+    "from tqdm import tqdm\n",
+    "\n",
+    "import pymt.models\n",
+    "ec = pymt.models.ECSimpleSnow()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### load example configuration and inputs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "config_file, config_dir = ec.setup('.')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### initialize by using default example data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ec.initialize(config_file, config_dir)\n",
+    "ec.set_value('snow_class', 2)\n",
+    "ec.set_value('open_area_or_not', 1)\n",
+    "\n",
+    "# List input and output variable names.\n",
+    "print(ec.get_output_var_names())\n",
+    "print(ec.get_input_var_names())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Implement the simple snow model for the first year as an example"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plt.figure(figsize=[4,9])\n",
+    "h0 = plt.subplot(3,1,1)\n",
+    "h1 = plt.subplot(3,1,2)\n",
+    "h2 = plt.subplot(3,1,3)\n",
+    "\n",
+    "h0.title.set_text('Snow Depth')\n",
+    "h1.title.set_text('Snow Density')\n",
+    "h2.title.set_text('Air Temperature')\n",
+    "\n",
+    "print('Air Temperature Unit:', ec.var_units('land_surface_air__temperature'))\n",
+    "print('Snow Depth Unit:'     , ec.var_units('snowpack__depth'))\n",
+    "print('Snow Density Unit:'   , ec.var_units('snowpack__mass-per-volume_density'))\n",
+    "\n",
+    "for i in tqdm(np.arange(365)):\n",
+    "\n",
+    "    ec.update()\n",
+    "    \n",
+    "    tair  = ec.get_value('land_surface_air__temperature')    \n",
+    "    snd   = ec.get_value('snowpack__depth', units='m')\n",
+    "    rsn   = ec.get_value('snowpack__mass-per-volume_density')\n",
+    "    \n",
+    "    units = ec.var_units('snowpack__depth')\n",
+    "    \n",
+    "    h0.scatter(ec.time, snd, c='k')    \n",
+    "    h1.scatter(ec.time, rsn, c='k')\n",
+    "    h2.scatter(ec.time,tair, c='k')\n",
+    "    \n",
+    "    \n",
+    "# ec.finalize()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Comparison with Observations at Barrow"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![Comparison](https://github.com/permamodel/Snow_BMI_Fortran/blob/master/data/Barrow.png?raw=true)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.7.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}