{
 "cells": [
  {
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# NLDAS2 Forcing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-12T23:05:08.325945Z",
     "iopub.status.busy": "2021-11-12T23:05:08.325171Z",
     "iopub.status.idle": "2021-11-12T23:05:09.703892Z",
     "shell.execute_reply": "2021-11-12T23:05:09.704334Z"
    }
   },
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "\n",
    "import pynldas2 as nldas\n",
    "from pygeohydro import WBD"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The NLDAS2 database provides forcing data at 1/8th-degree grid spacing and range from 01 Jan 1979 to present. Let's take a look at NLDAS2 grid mask that includes land, water, soil, and vegetation masks:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:      (lon: 464, lat: 224, time: 1, bnds: 2)\n",
       "Coordinates:\n",
       "  * lon          (lon) float32 -124.9 -124.8 -124.7 ... -67.31 -67.19 -67.06\n",
       "  * lat          (lat) float32 25.06 25.19 25.31 25.44 ... 52.69 52.81 52.94\n",
       "  * time         (time) datetime64[ns] 2000-01-01\n",
       "    spatial_ref  int64 0\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds    (time, bnds) datetime64[ns] ...\n",
       "    NLDAS_mask   (time, lat, lon) float32 ...\n",
       "    CONUS_mask   (time, lat, lon) float32 ...\n",
       "    NLDAS_veg    (time, lat, lon) float32 ...\n",
       "    NLDAS_soil   (time, lat, lon) float32 ...\n",
       "Attributes: (12/13)\n",
       "    missing_value:          -9999.0\n",
       "    time_definition:        constant\n",
       "    title:                  NLDAS masks and predominant vegetation/soil\n",
       "    institution:            NASA GSFC\n",
       "    history:                created on date: Fri Mar  8 15:58:50 2019\n",
       "    references:             Mitchell_etal_JGR_2004; Xia_etal_JGR_2012\n",
       "    ...                     ...\n",
       "    website:                https://ldas.gsfc.nasa.gov/nldas/\n",
       "    MAP_PROJECTION:         EQUIDISTANT CYLINDRICAL\n",
       "    SOUTH_WEST_CORNER_LAT:  25.0625\n",
       "    SOUTH_WEST_CORNER_LON:  -124.9375\n",
       "    DX:                     0.125\n",
       "    DY:                     0.125</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-d850483e-c6dd-442c-99a6-a3dd43598bba' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d850483e-c6dd-442c-99a6-a3dd43598bba' 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'>lon</span>: 464</li><li><span class='xr-has-index'>lat</span>: 224</li><li><span class='xr-has-index'>time</span>: 1</li><li><span>bnds</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-30c67e4d-7703-4d3b-ad99-86f4ba689456' class='xr-section-summary-in' type='checkbox'  checked><label for='section-30c67e4d-7703-4d3b-ad99-86f4ba689456' class='xr-section-summary' >Coordinates: <span>(4)</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'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-124.9 -124.8 ... -67.19 -67.06</div><input id='attrs-becb6163-68ed-4cb9-9b39-7e235620145d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-becb6163-68ed-4cb9-9b39-7e235620145d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35c54abb-56ba-46db-9c0d-4a03f10d8911' class='xr-var-data-in' type='checkbox'><label for='data-35c54abb-56ba-46db-9c0d-4a03f10d8911' 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>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>vmin :</span></dt><dd>-124.9375</dd><dt><span>vmax :</span></dt><dd>-67.0625</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-124.9375, -124.8125, -124.6875, ...,  -67.3125,  -67.1875,  -67.0625],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>25.06 25.19 25.31 ... 52.81 52.94</div><input id='attrs-4c3c060a-7261-40ae-b5ee-f17882e17a95' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c3c060a-7261-40ae-b5ee-f17882e17a95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3dd2191-5568-453d-af25-42427d2a1b87' class='xr-var-data-in' type='checkbox'><label for='data-c3dd2191-5568-453d-af25-42427d2a1b87' 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>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>vmin :</span></dt><dd>25.0625</dd><dt><span>vmax :</span></dt><dd>52.9375</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([25.0625, 25.1875, 25.3125, ..., 52.6875, 52.8125, 52.9375],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2000-01-01</div><input id='attrs-98f70284-4703-4710-97a6-2da90162342b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98f70284-4703-4710-97a6-2da90162342b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7cb573b-d76d-41a4-8baf-39147813f9eb' class='xr-var-data-in' type='checkbox'><label for='data-c7cb573b-d76d-41a4-8baf-39147813f9eb' 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>long_name :</span></dt><dd>time</dd><dt><span>time_increment :</span></dt><dd>1</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2000-01-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-31bbf53b-a247-44d7-985c-a7ad649b859c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31bbf53b-a247-44d7-985c-a7ad649b859c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04ee3f8e-2ae2-4ff7-970e-d3d74d7403ca' class='xr-var-data-in' type='checkbox'><label for='data-04ee3f8e-2ae2-4ff7-970e-d3d74d7403ca' 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>crs_wkt :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>WGS 84</dd><dt><span>horizontal_datum_name :</span></dt><dd>World Geodetic System 1984</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>-125.0 0.125 0.0 25.0 0.0 0.125</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bd961363-f63b-4f3c-8c9e-7b279b60f830' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bd961363-f63b-4f3c-8c9e-7b279b60f830' class='xr-section-summary' >Data variables: <span>(5)</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>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-42abb4f2-a137-4cdc-a5f6-fce10abaf307' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-42abb4f2-a137-4cdc-a5f6-fce10abaf307' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d782922-6b1d-4904-8286-90b3ced0d2f3' class='xr-var-data-in' type='checkbox'><label for='data-4d782922-6b1d-4904-8286-90b3ced0d2f3' 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'></dl></div><div class='xr-var-data'><pre>[2 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NLDAS_mask</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c4771759-bf38-4243-9ad4-a1ecf897e1f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c4771759-bf38-4243-9ad4-a1ecf897e1f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e198af4-7cad-4eb1-b816-854b529885f7' class='xr-var-data-in' type='checkbox'><label for='data-2e198af4-7cad-4eb1-b816-854b529885f7' 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>units :</span></dt><dd>0 = water; 1 = land</dd><dt><span>standard_name :</span></dt><dd>land mask</dd><dt><span>long_name :</span></dt><dd>NLDAS UMD unified land mask</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>vmin :</span></dt><dd>0.0</dd><dt><span>vmax :</span></dt><dd>1.0</dd></dl></div><div class='xr-var-data'><pre>[103936 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CONUS_mask</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d421640e-194c-48c6-9da7-d2228ed452a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d421640e-194c-48c6-9da7-d2228ed452a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22cd920f-c652-4835-b063-65534956a382' class='xr-var-data-in' type='checkbox'><label for='data-22cd920f-c652-4835-b063-65534956a382' 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>units :</span></dt><dd>0 = water; 1 = land</dd><dt><span>standard_name :</span></dt><dd>CONUS mask</dd><dt><span>long_name :</span></dt><dd>NLDAS CONUS mask</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>vmin :</span></dt><dd>0.0</dd><dt><span>vmax :</span></dt><dd>1.0</dd></dl></div><div class='xr-var-data'><pre>[103936 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NLDAS_veg</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-80130b8d-df0a-47d0-9c41-8ad26b5e0eb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-80130b8d-df0a-47d0-9c41-8ad26b5e0eb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2175f62d-b575-4aca-9326-63ae44e8a2d8' class='xr-var-data-in' type='checkbox'><label for='data-2175f62d-b575-4aca-9326-63ae44e8a2d8' 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>units :</span></dt><dd>0 - 13</dd><dt><span>standard_name :</span></dt><dd>vegetation class</dd><dt><span>long_name :</span></dt><dd>NLDAS UMD predominant vegetation class</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>vmin :</span></dt><dd>0.0</dd><dt><span>vmax :</span></dt><dd>13.0</dd></dl></div><div class='xr-var-data'><pre>[103936 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NLDAS_soil</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0c82683b-253e-4ee3-94b9-9c65e015d6dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c82683b-253e-4ee3-94b9-9c65e015d6dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f7f3c50-7e5d-48a1-8ae2-0ffcccbfe85c' class='xr-var-data-in' type='checkbox'><label for='data-9f7f3c50-7e5d-48a1-8ae2-0ffcccbfe85c' 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>units :</span></dt><dd>0 - 14</dd><dt><span>standard_name :</span></dt><dd>soil texture type</dd><dt><span>long_name :</span></dt><dd>NLDAS STATSGO predominant soil texture type</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>vmin :</span></dt><dd>0.0</dd><dt><span>vmax :</span></dt><dd>14.0</dd></dl></div><div class='xr-var-data'><pre>[103936 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e4f0dac4-a012-462a-935d-fb5f29508b9f' class='xr-section-summary-in' type='checkbox'  ><label for='section-e4f0dac4-a012-462a-935d-fb5f29508b9f' class='xr-section-summary' >Indexes: <span>(3)</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>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-49a37856-5713-4ccd-809c-94e9fd30fb25' class='xr-index-data-in' type='checkbox'/><label for='index-49a37856-5713-4ccd-809c-94e9fd30fb25' 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([-124.9375, -124.8125, -124.6875, -124.5625, -124.4375, -124.3125,\n",
       "       -124.1875, -124.0625, -123.9375, -123.8125,\n",
       "       ...\n",
       "        -68.1875,  -68.0625,  -67.9375,  -67.8125,  -67.6875,  -67.5625,\n",
       "        -67.4375,  -67.3125,  -67.1875,  -67.0625],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;lon&#x27;, length=464))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f7edac73-49b1-439b-a1ed-84f3b3c1c44c' class='xr-index-data-in' type='checkbox'/><label for='index-f7edac73-49b1-439b-a1ed-84f3b3c1c44c' 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([25.0625, 25.1875, 25.3125, 25.4375, 25.5625, 25.6875, 25.8125, 25.9375,\n",
       "       26.0625, 26.1875,\n",
       "       ...\n",
       "       51.8125, 51.9375, 52.0625, 52.1875, 52.3125, 52.4375, 52.5625, 52.6875,\n",
       "       52.8125, 52.9375],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;lat&#x27;, length=224))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7d254bba-be5f-4324-9698-7be38e53aafb' class='xr-index-data-in' type='checkbox'/><label for='index-7d254bba-be5f-4324-9698-7be38e53aafb' 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(DatetimeIndex([&#x27;2000-01-01&#x27;], dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-154e882d-79ab-4179-b237-648e3a8e0141' class='xr-section-summary-in' type='checkbox'  ><label for='section-154e882d-79ab-4179-b237-648e3a8e0141' class='xr-section-summary' >Attributes: <span>(13)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>missing_value :</span></dt><dd>-9999.0</dd><dt><span>time_definition :</span></dt><dd>constant</dd><dt><span>title :</span></dt><dd>NLDAS masks and predominant vegetation/soil</dd><dt><span>institution :</span></dt><dd>NASA GSFC</dd><dt><span>history :</span></dt><dd>created on date: Fri Mar  8 15:58:50 2019</dd><dt><span>references :</span></dt><dd>Mitchell_etal_JGR_2004; Xia_etal_JGR_2012</dd><dt><span>conventions :</span></dt><dd>CF-1.6</dd><dt><span>website :</span></dt><dd>https://ldas.gsfc.nasa.gov/nldas/</dd><dt><span>MAP_PROJECTION :</span></dt><dd>EQUIDISTANT CYLINDRICAL</dd><dt><span>SOUTH_WEST_CORNER_LAT :</span></dt><dd>25.0625</dd><dt><span>SOUTH_WEST_CORNER_LON :</span></dt><dd>-124.9375</dd><dt><span>DX :</span></dt><dd>0.125</dd><dt><span>DY :</span></dt><dd>0.125</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:      (lon: 464, lat: 224, time: 1, bnds: 2)\n",
       "Coordinates:\n",
       "  * lon          (lon) float32 -124.9 -124.8 -124.7 ... -67.31 -67.19 -67.06\n",
       "  * lat          (lat) float32 25.06 25.19 25.31 25.44 ... 52.69 52.81 52.94\n",
       "  * time         (time) datetime64[ns] 2000-01-01\n",
       "    spatial_ref  int64 0\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds    (time, bnds) datetime64[ns] ...\n",
       "    NLDAS_mask   (time, lat, lon) float32 ...\n",
       "    CONUS_mask   (time, lat, lon) float32 ...\n",
       "    NLDAS_veg    (time, lat, lon) float32 ...\n",
       "    NLDAS_soil   (time, lat, lon) float32 ...\n",
       "Attributes: (12/13)\n",
       "    missing_value:          -9999.0\n",
       "    time_definition:        constant\n",
       "    title:                  NLDAS masks and predominant vegetation/soil\n",
       "    institution:            NASA GSFC\n",
       "    history:                created on date: Fri Mar  8 15:58:50 2019\n",
       "    references:             Mitchell_etal_JGR_2004; Xia_etal_JGR_2012\n",
       "    ...                     ...\n",
       "    website:                https://ldas.gsfc.nasa.gov/nldas/\n",
       "    MAP_PROJECTION:         EQUIDISTANT CYLINDRICAL\n",
       "    SOUTH_WEST_CORNER_LAT:  25.0625\n",
       "    SOUTH_WEST_CORNER_LON:  -124.9375\n",
       "    DX:                     0.125\n",
       "    DY:                     0.125"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid = nldas.get_grid_mask()\n",
    "grid"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For example, let's plot the vegetation mask."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = grid.NLDAS_veg.plot()\n",
    "ax.figure.savefig(Path(\"_static\", \"nldas_grid.png\"), facecolor=\"w\", bbox_inches=\"tight\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we use [PyGeoHydro](https://github.com/hyriver/pygeohydro) to get the geometry of a HUC8 with ID of 1306003:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-11-12T23:05:09.708922Z",
     "iopub.status.busy": "2021-11-12T23:05:09.708051Z",
     "iopub.status.idle": "2021-11-12T23:05:10.262066Z",
     "shell.execute_reply": "2021-11-12T23:05:10.262509Z"
    }
   },
   "outputs": [],
   "source": [
    "huc8 = WBD(\"huc8\")\n",
    "geometry = huc8.byids(\"huc8\", \"13060003\").geometry.iloc[0]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[PyNLDAS2](https://github.com/hyriver/pynldas2) allows us to get the data for a list of coordinates using `pynldas2.get_bycoords` or for a region as gridded data using `pynldas2.get_bygeom`. Here, we use the latter. Note that if we don't pass any variables, all variables will be downloaded. Additionally, we can pass ``snow=True`` to separate snow portion of precipitation using temperature. PyNLDAS2 provides access to NLDAS2 data from two sources: `grib` and `netcdf`. They are mostly similar so if for some reason one of the sources is not temporarly available, you can use the other one. The default source is `grib`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "clm = nldas.get_bygeom(geometry, \"2010-01-08\", \"2010-01-08\", 4326, variables=\"prcp\", snow=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 7 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = clm.snow.sel(time=slice(\"2010-01-08T05:00:00\", \"2010-01-08T010:00:00\")).plot(\n",
    "    col=\"time\", col_wrap=3\n",
    ")\n",
    "ax.fig.savefig(Path(\"_static\", \"nldas_snow.png\"), facecolor=\"w\", bbox_inches=\"tight\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "hyriver-dev",
   "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": "3.11.7"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "003c82ad5971cfdf345b67bc4c483230f4144cd11e9aff06d93cf3af71d62f25"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}