regrid-example.ipynb

{
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   "cell_type": "markdown",
   "id": "716d2fbb-f0d4-432c-8bbb-3cfe3e6ab8fc",
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    "Purpose: create monthly albedo files from daily albedo files and put in new directory\n",
    "- \"regrid_geo_sinu\" kernel used on HPC "
   ]
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   "id": "9ef61222-a364-4cd2-aa6b-754bf19e2b45",
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   "source": [
    "import os\n",
    "import datetime\n",
    "from dateutil.relativedelta import relativedelta\n",
    "import xarray as xr\n",
    "import rioxarray as rxr\n",
    "import numpy as np\n",
    "import numpy.ma as ma\n",
    "from netCDF4 import Dataset\n",
    "import pandas as pd\n",
    "import rasterio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "468ab561-497c-4da0-a67a-38ba5f21e842",
   "metadata": {},
   "outputs": [],
   "source": [
    "# user input data\n",
    "modis_directory = '/scratch/kojoseph/modis/mcd43gf/bsa_only'\n",
    "output_directory = '/scratch/kojoseph/modis/mcd43gf/bsa_only/monthly'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ebc2b401-1fec-443f-9e11-b891fa540724",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (band: 1, y: 21600, x: 43200)&gt;\n",
       "[933120000 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * band         (band) int64 1\n",
       "  * x            (x) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
       "  * y            (y) float64 90.0 89.99 89.98 89.97 ... -89.98 -89.99 -90.0\n",
       "    spatial_ref  int64 0\n",
       "Attributes:\n",
       "    scale_factor:  0.001\n",
       "    add_offset:    0.0\n",
       "    long_name:     Gapfilled BRDF/Albedo data from V006 MCD43D</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>band</span>: 1</li><li><span class='xr-has-index'>y</span>: 21600</li><li><span class='xr-has-index'>x</span>: 43200</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e60b1184-8c98-446d-8d6a-61599a1b0567' class='xr-array-in' type='checkbox' checked><label for='section-e60b1184-8c98-446d-8d6a-61599a1b0567' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[933120000 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-30a04f12-8486-4934-b6c4-8fed5f5957dd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-30a04f12-8486-4934-b6c4-8fed5f5957dd' 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'>band</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-0af03bd9-3006-4c84-8e06-3d3320036ca8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0af03bd9-3006-4c84-8e06-3d3320036ca8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1dc59b4-0b98-475a-902a-5442265bd79e' class='xr-var-data-in' type='checkbox'><label for='data-f1dc59b4-0b98-475a-902a-5442265bd79e' 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>array([1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-a6916f34-3e5d-432d-b2e4-3cd8a58bf143' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a6916f34-3e5d-432d-b2e4-3cd8a58bf143' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1801505-bbf3-4079-a9fb-eff054971cd1' class='xr-var-data-in' type='checkbox'><label for='data-b1801505-bbf3-4079-a9fb-eff054971cd1' 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>array([-179.995833, -179.9875  , -179.979167, ...,  179.979167,  179.9875  ,\n",
       "        179.995833])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>90.0 89.99 89.98 ... -89.99 -90.0</div><input id='attrs-7ee58c06-9e86-4a6a-aff0-c398852f807e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7ee58c06-9e86-4a6a-aff0-c398852f807e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38a04093-06ac-496f-aeb5-a2e3cc16d5f6' class='xr-var-data-in' type='checkbox'><label for='data-38a04093-06ac-496f-aeb5-a2e3cc16d5f6' 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>array([ 89.995833,  89.9875  ,  89.979167, ..., -89.979167, -89.9875  ,\n",
       "       -89.995833])</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-8b79e8cc-2960-450e-a98a-860c074951d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b79e8cc-2960-450e-a98a-860c074951d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d552277-a120-46fb-955c-b58976cc6ddc' class='xr-var-data-in' type='checkbox'><label for='data-7d552277-a120-46fb-955c-b58976cc6ddc' 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;Unknown datum based upon the Clarke 1866 ellipsoid&quot;,DATUM[&quot;Not specified (based on Clarke 1866 spheroid)&quot;,SPHEROID[&quot;Clarke 1866&quot;,6378206.4,294.978698213898,AUTHORITY[&quot;EPSG&quot;,&quot;7008&quot;]]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378206.4</dd><dt><span>semi_minor_axis :</span></dt><dd>6356583.8</dd><dt><span>inverse_flattening :</span></dt><dd>294.978698213898</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>Clarke 1866</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>Unknown datum based upon the Clarke 1866 ellipsoid</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;Unknown datum based upon the Clarke 1866 ellipsoid&quot;,DATUM[&quot;Not specified (based on Clarke 1866 spheroid)&quot;,SPHEROID[&quot;Clarke 1866&quot;,6378206.4,294.978698213898,AUTHORITY[&quot;EPSG&quot;,&quot;7008&quot;]]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST]]</dd><dt><span>GeoTransform :</span></dt><dd>-180.0 0.008333333333333333 0.0 90.0 0.0 -0.008333333333333333</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-78658a57-cbf4-4a8c-9e04-3730db4abfd1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-78658a57-cbf4-4a8c-9e04-3730db4abfd1' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>scale_factor :</span></dt><dd>0.001</dd><dt><span>add_offset :</span></dt><dd>0.0</dd><dt><span>long_name :</span></dt><dd>Gapfilled BRDF/Albedo data from V006 MCD43D</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (band: 1, y: 21600, x: 43200)>\n",
       "[933120000 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * band         (band) int64 1\n",
       "  * x            (x) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
       "  * y            (y) float64 90.0 89.99 89.98 89.97 ... -89.98 -89.99 -90.0\n",
       "    spatial_ref  int64 0\n",
       "Attributes:\n",
       "    scale_factor:  0.001\n",
       "    add_offset:    0.0\n",
       "    long_name:     Gapfilled BRDF/Albedo data from V006 MCD43D"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file1 = 'MCD43GF_bsa_shortwave_183_2015_V006.hdf'\n",
    "#ds1 = rxr.open_rasterio(modis_directory + '/' + file1, masked = True)\n",
    "ds1 = rxr.open_rasterio(modis_directory + '/' + file1, masked = True) \n",
    "ds1"
   ]
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       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
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       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (y: 360, x: 408)&gt;\n",
       "[146880 values with dtype=float32]\n",
       "Coordinates:\n",
       "    band         int64 1\n",
       "  * x            (x) float64 -119.6 -119.6 -119.6 ... -116.2 -116.2 -116.2\n",
       "  * y            (y) float64 35.2 35.19 35.18 35.17 ... 32.23 32.22 32.21 32.2\n",
       "    spatial_ref  int64 0\n",
       "Attributes:\n",
       "    scale_factor:  0.001\n",
       "    add_offset:    0.0\n",
       "    long_name:     Gapfilled BRDF/Albedo data from V006 MCD43D</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 360</li><li><span class='xr-has-index'>x</span>: 408</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-9909b80f-838e-4746-8912-b0ba49926487' class='xr-array-in' type='checkbox' checked><label for='section-9909b80f-838e-4746-8912-b0ba49926487' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[146880 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-6d1aae41-7df6-4675-812b-8823ad02d7b0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6d1aae41-7df6-4675-812b-8823ad02d7b0' 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>band</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-9d6f22d4-ed33-4cc6-b8bb-4afce6c32ab1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9d6f22d4-ed33-4cc6-b8bb-4afce6c32ab1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24cf0550-98aa-4571-af52-073427ac3792' class='xr-var-data-in' type='checkbox'><label for='data-24cf0550-98aa-4571-af52-073427ac3792' 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>array(1)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-119.6 -119.6 ... -116.2 -116.2</div><input id='attrs-e63407b5-ff66-456c-b30b-05641e606235' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e63407b5-ff66-456c-b30b-05641e606235' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c5a6d84-f7b0-4561-bfc6-a89a08cedbac' class='xr-var-data-in' type='checkbox'><label for='data-9c5a6d84-f7b0-4561-bfc6-a89a08cedbac' 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>array([-119.595833, -119.5875  , -119.579167, ..., -116.220833, -116.2125  ,\n",
       "       -116.204167])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>35.2 35.19 35.18 ... 32.21 32.2</div><input id='attrs-937ad99b-4226-4639-acc9-2fe4f85e1115' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-937ad99b-4226-4639-acc9-2fe4f85e1115' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c03851dd-020c-4fd4-8658-a625bdf99a59' class='xr-var-data-in' type='checkbox'><label for='data-c03851dd-020c-4fd4-8658-a625bdf99a59' 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>array([35.195833, 35.1875  , 35.179167, ..., 32.220833, 32.2125  , 32.204167])</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-bd97a655-7cb0-4dfc-b3f6-96f815b17940' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd97a655-7cb0-4dfc-b3f6-96f815b17940' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6caca9d-5f17-45b3-a2cb-b7e5e1e0bf46' class='xr-var-data-in' type='checkbox'><label for='data-d6caca9d-5f17-45b3-a2cb-b7e5e1e0bf46' 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;Unknown datum based upon the Clarke 1866 ellipsoid&quot;,DATUM[&quot;Not specified (based on Clarke 1866 spheroid)&quot;,SPHEROID[&quot;Clarke 1866&quot;,6378206.4,294.978698213898,AUTHORITY[&quot;EPSG&quot;,&quot;7008&quot;]]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378206.4</dd><dt><span>semi_minor_axis :</span></dt><dd>6356583.8</dd><dt><span>inverse_flattening :</span></dt><dd>294.978698213898</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>Clarke 1866</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>Unknown datum based upon the Clarke 1866 ellipsoid</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;Unknown datum based upon the Clarke 1866 ellipsoid&quot;,DATUM[&quot;Not specified (based on Clarke 1866 spheroid)&quot;,SPHEROID[&quot;Clarke 1866&quot;,6378206.4,294.978698213898,AUTHORITY[&quot;EPSG&quot;,&quot;7008&quot;]]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST]]</dd><dt><span>GeoTransform :</span></dt><dd>-180.0 0.008333333333333333 0.0 90.0 0.0 -0.008333333333333333</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-7d02b1b0-007a-4fbc-80d2-994df0b3fa62' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7d02b1b0-007a-4fbc-80d2-994df0b3fa62' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>scale_factor :</span></dt><dd>0.001</dd><dt><span>add_offset :</span></dt><dd>0.0</dd><dt><span>long_name :</span></dt><dd>Gapfilled BRDF/Albedo data from V006 MCD43D</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (y: 360, x: 408)>\n",
       "[146880 values with dtype=float32]\n",
       "Coordinates:\n",
       "    band         int64 1\n",
       "  * x            (x) float64 -119.6 -119.6 -119.6 ... -116.2 -116.2 -116.2\n",
       "  * y            (y) float64 35.2 35.19 35.18 35.17 ... 32.23 32.22 32.21 32.2\n",
       "    spatial_ref  int64 0\n",
       "Attributes:\n",
       "    scale_factor:  0.001\n",
       "    add_offset:    0.0\n",
       "    long_name:     Gapfilled BRDF/Albedo data from V006 MCD43D"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds1_slice = ds1.sel(band=1, x=slice(-119.6,-116.2), y=slice(35.2,32.2))\n",
    "ds1_slice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7147d14d-9550-4eb3-af91-6c05ad5a6aaa",
   "metadata": {},
   "outputs": [
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       "\n",
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       "\n",
       ".xr-attrs dt:hover span {\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (band: 1, y: 21600, x: 43200)&gt;\n",
       "[933120000 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * band         (band) int64 1\n",
       "  * x            (x) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
       "  * y            (y) float64 90.0 89.99 89.98 89.97 ... -89.98 -89.99 -90.0\n",
       "    spatial_ref  int64 0\n",
       "Attributes:\n",
       "    scale_factor:  0.001\n",
       "    add_offset:    0.0\n",
       "    long_name:     Gapfilled BRDF/Albedo data from V006 MCD43D</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>band</span>: 1</li><li><span class='xr-has-index'>y</span>: 21600</li><li><span class='xr-has-index'>x</span>: 43200</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-c2fb3b7c-de28-4646-865c-df4b23216e9e' class='xr-array-in' type='checkbox' checked><label for='section-c2fb3b7c-de28-4646-865c-df4b23216e9e' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[933120000 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-37a99e2d-7f87-44f7-b7f1-2a2da7540c16' class='xr-section-summary-in' type='checkbox'  checked><label for='section-37a99e2d-7f87-44f7-b7f1-2a2da7540c16' 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'>band</span></div><div class='xr-var-dims'>(band)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-8a470f3f-4131-4f5e-86e2-57a8df1c8a23' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8a470f3f-4131-4f5e-86e2-57a8df1c8a23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2e436e4-e1e2-49a8-af3f-9637eac47141' class='xr-var-data-in' type='checkbox'><label for='data-d2e436e4-e1e2-49a8-af3f-9637eac47141' 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>array([1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -180.0 ... 180.0 180.0</div><input id='attrs-6a6a967a-941b-4302-9f79-0a7522aa42a1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6a6a967a-941b-4302-9f79-0a7522aa42a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a205bc7e-ea6b-45f7-8e54-eae34e21b708' class='xr-var-data-in' type='checkbox'><label for='data-a205bc7e-ea6b-45f7-8e54-eae34e21b708' 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>array([-179.995833, -179.9875  , -179.979167, ...,  179.979167,  179.9875  ,\n",
       "        179.995833])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>90.0 89.99 89.98 ... -89.99 -90.0</div><input id='attrs-212b1037-5404-46d1-bc8c-283131128c63' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-212b1037-5404-46d1-bc8c-283131128c63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55fa271b-0ffb-4219-ac60-c461e9d248f9' class='xr-var-data-in' type='checkbox'><label for='data-55fa271b-0ffb-4219-ac60-c461e9d248f9' 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>array([ 89.995833,  89.9875  ,  89.979167, ..., -89.979167, -89.9875  ,\n",
       "       -89.995833])</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-7e240e4f-35c4-4c1e-9739-ff02f1f76199' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e240e4f-35c4-4c1e-9739-ff02f1f76199' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-344c499b-ca22-4085-8260-8976fab294de' class='xr-var-data-in' type='checkbox'><label for='data-344c499b-ca22-4085-8260-8976fab294de' 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;Unknown datum based upon the Clarke 1866 ellipsoid&quot;,DATUM[&quot;Not specified (based on Clarke 1866 spheroid)&quot;,SPHEROID[&quot;Clarke 1866&quot;,6378206.4,294.978698213898,AUTHORITY[&quot;EPSG&quot;,&quot;7008&quot;]]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378206.4</dd><dt><span>semi_minor_axis :</span></dt><dd>6356583.8</dd><dt><span>inverse_flattening :</span></dt><dd>294.978698213898</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>Clarke 1866</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>Unknown datum based upon the Clarke 1866 ellipsoid</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;Unknown datum based upon the Clarke 1866 ellipsoid&quot;,DATUM[&quot;Not specified (based on Clarke 1866 spheroid)&quot;,SPHEROID[&quot;Clarke 1866&quot;,6378206.4,294.978698213898,AUTHORITY[&quot;EPSG&quot;,&quot;7008&quot;]]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST]]</dd><dt><span>GeoTransform :</span></dt><dd>-180.0 0.008333333333333333 0.0 90.0 0.0 -0.008333333333333333</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-4c885d4d-aa9c-4b85-87e9-3665228b1324' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4c885d4d-aa9c-4b85-87e9-3665228b1324' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>scale_factor :</span></dt><dd>0.001</dd><dt><span>add_offset :</span></dt><dd>0.0</dd><dt><span>long_name :</span></dt><dd>Gapfilled BRDF/Albedo data from V006 MCD43D</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (band: 1, y: 21600, x: 43200)>\n",
       "[933120000 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * band         (band) int64 1\n",
       "  * x            (x) float64 -180.0 -180.0 -180.0 -180.0 ... 180.0 180.0 180.0\n",
       "  * y            (y) float64 90.0 89.99 89.98 89.97 ... -89.98 -89.99 -90.0\n",
       "    spatial_ref  int64 0\n",
       "Attributes:\n",
       "    scale_factor:  0.001\n",
       "    add_offset:    0.0\n",
       "    long_name:     Gapfilled BRDF/Albedo data from V006 MCD43D"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file2 = 'MCD43GF_bsa_shortwave_182_2016_V006.hdf'\n",
    "ds2 = rxr.open_rasterio(modis_directory + '/' + file2, masked = True) \n",
    "ds2"
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  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "90a315ea-6d36-4490-b021-c078d7160341",
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       "}\n",
       "\n",
       ".xr-var-list,\n",
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       "\n",
       ".xr-var-item > div,\n",
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       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
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       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
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       "\n",
       ".xr-var-name {\n",
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       "\n",
       ".xr-var-dims {\n",
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       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
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       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-var-preview {\n",
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       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
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       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
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       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
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       "\n",
       ".xr-icon-database,\n",
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       "  display: inline-block;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (y: 360, x: 408)&gt;\n",
       "[146880 values with dtype=float32]\n",
       "Coordinates:\n",
       "    band         int64 1\n",
       "  * x            (x) float64 -119.6 -119.6 -119.6 ... -116.2 -116.2 -116.2\n",
       "  * y            (y) float64 35.2 35.19 35.18 35.17 ... 32.23 32.22 32.21 32.2\n",
       "    spatial_ref  int64 0\n",
       "Attributes:\n",
       "    scale_factor:  0.001\n",
       "    add_offset:    0.0\n",
       "    long_name:     Gapfilled BRDF/Albedo data from V006 MCD43D</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 360</li><li><span class='xr-has-index'>x</span>: 408</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e27f47fa-98de-435a-83a0-debc311e5ae1' class='xr-array-in' type='checkbox' checked><label for='section-e27f47fa-98de-435a-83a0-debc311e5ae1' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[146880 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-d7532b7c-24f4-4974-a94f-267e8981c83a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d7532b7c-24f4-4974-a94f-267e8981c83a' 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>band</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-1c793338-c655-4f35-a8a9-3cd6a5e2abb7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1c793338-c655-4f35-a8a9-3cd6a5e2abb7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99d2a923-0ec4-41f3-868c-7920bba7f245' class='xr-var-data-in' type='checkbox'><label for='data-99d2a923-0ec4-41f3-868c-7920bba7f245' 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>array(1)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-119.6 -119.6 ... -116.2 -116.2</div><input id='attrs-8ddb5b3e-4c1f-406f-ba72-46f382463b89' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8ddb5b3e-4c1f-406f-ba72-46f382463b89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e14ac737-61f6-4f3a-a351-fa5d1979a844' class='xr-var-data-in' type='checkbox'><label for='data-e14ac737-61f6-4f3a-a351-fa5d1979a844' 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>array([-119.595833, -119.5875  , -119.579167, ..., -116.220833, -116.2125  ,\n",
       "       -116.204167])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>35.2 35.19 35.18 ... 32.21 32.2</div><input id='attrs-ffc00b52-e8f1-4d88-b47a-78ab132f49f4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ffc00b52-e8f1-4d88-b47a-78ab132f49f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a24d8368-30f1-491d-8319-3a4fdfc85e90' class='xr-var-data-in' type='checkbox'><label for='data-a24d8368-30f1-491d-8319-3a4fdfc85e90' 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>array([35.195833, 35.1875  , 35.179167, ..., 32.220833, 32.2125  , 32.204167])</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-a3ad8f0b-8d15-41ff-a5e0-3cc30c76c68e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3ad8f0b-8d15-41ff-a5e0-3cc30c76c68e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03000e83-a24d-4120-9a8e-83b6d9e9679b' class='xr-var-data-in' type='checkbox'><label for='data-03000e83-a24d-4120-9a8e-83b6d9e9679b' 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;Unknown datum based upon the Clarke 1866 ellipsoid&quot;,DATUM[&quot;Not specified (based on Clarke 1866 spheroid)&quot;,SPHEROID[&quot;Clarke 1866&quot;,6378206.4,294.978698213898,AUTHORITY[&quot;EPSG&quot;,&quot;7008&quot;]]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378206.4</dd><dt><span>semi_minor_axis :</span></dt><dd>6356583.8</dd><dt><span>inverse_flattening :</span></dt><dd>294.978698213898</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>Clarke 1866</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>Unknown datum based upon the Clarke 1866 ellipsoid</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;Unknown datum based upon the Clarke 1866 ellipsoid&quot;,DATUM[&quot;Not specified (based on Clarke 1866 spheroid)&quot;,SPHEROID[&quot;Clarke 1866&quot;,6378206.4,294.978698213898,AUTHORITY[&quot;EPSG&quot;,&quot;7008&quot;]]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST]]</dd><dt><span>GeoTransform :</span></dt><dd>-180.0 0.008333333333333333 0.0 90.0 0.0 -0.008333333333333333</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-541314c1-de09-4929-a13b-4886e00129b3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-541314c1-de09-4929-a13b-4886e00129b3' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>scale_factor :</span></dt><dd>0.001</dd><dt><span>add_offset :</span></dt><dd>0.0</dd><dt><span>long_name :</span></dt><dd>Gapfilled BRDF/Albedo data from V006 MCD43D</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (y: 360, x: 408)>\n",
       "[146880 values with dtype=float32]\n",
       "Coordinates:\n",
       "    band         int64 1\n",
       "  * x            (x) float64 -119.6 -119.6 -119.6 ... -116.2 -116.2 -116.2\n",
       "  * y            (y) float64 35.2 35.19 35.18 35.17 ... 32.23 32.22 32.21 32.2\n",
       "    spatial_ref  int64 0\n",
       "Attributes:\n",
       "    scale_factor:  0.001\n",
       "    add_offset:    0.0\n",
       "    long_name:     Gapfilled BRDF/Albedo data from V006 MCD43D"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds2_slice = ds2.sel(band=1, x=slice(-119.6,-116.2), y=slice(35.2,32.2))\n",
    "ds2_slice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "66be295a-736d-4c5c-9786-b03bca5b213b",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_1_2 = xr.concat([ds1_slice, ds2_slice], dim='day')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b73ecdf6-a842-48e2-82fb-ab0d479e925b",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (y: 360, x: 408)&gt;\n",
       "array([[245., 251., 252., ..., 143., 145., 144.],\n",
       "       [231., 225., 237., ..., 137., 147., 159.],\n",
       "       [233., 228., 234., ..., 135., 151., 165.],\n",
       "       ...,\n",
       "       [ nan,  nan,  nan, ..., 116., 123., 118.],\n",
       "       [ nan,  nan,  nan, ..., 103., 118., 126.],\n",
       "       [ nan,  nan,  nan, ...,  98., 104., 114.]], dtype=float32)\n",
       "Coordinates:\n",
       "    band         int64 1\n",
       "  * x            (x) float64 -119.6 -119.6 -119.6 ... -116.2 -116.2 -116.2\n",
       "  * y            (y) float64 35.2 35.19 35.18 35.17 ... 32.23 32.22 32.21 32.2\n",
       "    spatial_ref  int64 0\n",
       "Attributes:\n",
       "    scale_factor:  0.001\n",
       "    add_offset:    0.0\n",
       "    long_name:     Gapfilled BRDF/Albedo data from V006 MCD43D</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 360</li><li><span class='xr-has-index'>x</span>: 408</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-3067ca08-1bd9-4174-951b-f63194bc9c74' class='xr-array-in' type='checkbox' checked><label for='section-3067ca08-1bd9-4174-951b-f63194bc9c74' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>245.0 251.0 252.0 251.0 250.0 250.0 ... 100.0 100.0 98.0 104.0 114.0</span></div><div class='xr-array-data'><pre>array([[245., 251., 252., ..., 143., 145., 144.],\n",
       "       [231., 225., 237., ..., 137., 147., 159.],\n",
       "       [233., 228., 234., ..., 135., 151., 165.],\n",
       "       ...,\n",
       "       [ nan,  nan,  nan, ..., 116., 123., 118.],\n",
       "       [ nan,  nan,  nan, ..., 103., 118., 126.],\n",
       "       [ nan,  nan,  nan, ...,  98., 104., 114.]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-dafbfe8a-984a-4c9e-b01d-8823b8b24b53' class='xr-section-summary-in' type='checkbox'  checked><label for='section-dafbfe8a-984a-4c9e-b01d-8823b8b24b53' 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>band</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-44d9855a-0b40-4f68-9215-63998b6ecc6f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-44d9855a-0b40-4f68-9215-63998b6ecc6f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a66747b-04c9-464c-80a7-6e39ec319b8a' class='xr-var-data-in' type='checkbox'><label for='data-6a66747b-04c9-464c-80a7-6e39ec319b8a' 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>array(1)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-119.6 -119.6 ... -116.2 -116.2</div><input id='attrs-f811b72a-e9c3-4fa1-b284-3c7f4998e7b1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f811b72a-e9c3-4fa1-b284-3c7f4998e7b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b73fc5e9-6c18-4d52-b802-1cfafdfb39da' class='xr-var-data-in' type='checkbox'><label for='data-b73fc5e9-6c18-4d52-b802-1cfafdfb39da' 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>array([-119.595833, -119.5875  , -119.579167, ..., -116.220833, -116.2125  ,\n",
       "       -116.204167])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>35.2 35.19 35.18 ... 32.21 32.2</div><input id='attrs-150be339-9d88-4b58-b298-e474f29e8043' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-150be339-9d88-4b58-b298-e474f29e8043' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ced53b9f-c4c6-425c-8c1d-c952d8346b2b' class='xr-var-data-in' type='checkbox'><label for='data-ced53b9f-c4c6-425c-8c1d-c952d8346b2b' 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>array([35.195833, 35.1875  , 35.179167, ..., 32.220833, 32.2125  , 32.204167])</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-7f1a7bc9-c557-4745-82b1-3aaf375e13ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f1a7bc9-c557-4745-82b1-3aaf375e13ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ac5357c-21d8-457f-a1d7-c1976f171a41' class='xr-var-data-in' type='checkbox'><label for='data-1ac5357c-21d8-457f-a1d7-c1976f171a41' 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;Unknown datum based upon the Clarke 1866 ellipsoid&quot;,DATUM[&quot;Not specified (based on Clarke 1866 spheroid)&quot;,SPHEROID[&quot;Clarke 1866&quot;,6378206.4,294.978698213898,AUTHORITY[&quot;EPSG&quot;,&quot;7008&quot;]]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378206.4</dd><dt><span>semi_minor_axis :</span></dt><dd>6356583.8</dd><dt><span>inverse_flattening :</span></dt><dd>294.978698213898</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>Clarke 1866</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>Unknown datum based upon the Clarke 1866 ellipsoid</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;Unknown datum based upon the Clarke 1866 ellipsoid&quot;,DATUM[&quot;Not specified (based on Clarke 1866 spheroid)&quot;,SPHEROID[&quot;Clarke 1866&quot;,6378206.4,294.978698213898,AUTHORITY[&quot;EPSG&quot;,&quot;7008&quot;]]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST]]</dd><dt><span>GeoTransform :</span></dt><dd>-180.0 0.008333333333333333 0.0 90.0 0.0 -0.008333333333333333</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-be55f124-c495-4dc7-a4a3-ae7dbb4e4d72' class='xr-section-summary-in' type='checkbox'  checked><label for='section-be55f124-c495-4dc7-a4a3-ae7dbb4e4d72' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>scale_factor :</span></dt><dd>0.001</dd><dt><span>add_offset :</span></dt><dd>0.0</dd><dt><span>long_name :</span></dt><dd>Gapfilled BRDF/Albedo data from V006 MCD43D</dd></dl></div></li></ul></div></div>"
      ],
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       "<xarray.DataArray (y: 360, x: 408)>\n",
       "array([[245., 251., 252., ..., 143., 145., 144.],\n",
       "       [231., 225., 237., ..., 137., 147., 159.],\n",
       "       [233., 228., 234., ..., 135., 151., 165.],\n",
       "       ...,\n",
       "       [ nan,  nan,  nan, ..., 116., 123., 118.],\n",
       "       [ nan,  nan,  nan, ..., 103., 118., 126.],\n",
       "       [ nan,  nan,  nan, ...,  98., 104., 114.]], dtype=float32)\n",
       "Coordinates:\n",
       "    band         int64 1\n",
       "  * x            (x) float64 -119.6 -119.6 -119.6 ... -116.2 -116.2 -116.2\n",
       "  * y            (y) float64 35.2 35.19 35.18 35.17 ... 32.23 32.22 32.21 32.2\n",
       "    spatial_ref  int64 0\n",
       "Attributes:\n",
       "    scale_factor:  0.001\n",
       "    add_offset:    0.0\n",
       "    long_name:     Gapfilled BRDF/Albedo data from V006 MCD43D"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "ds_1_2.sel(day=0)"
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  {
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   "execution_count": 9,
   "id": "33f63d24-b278-42f2-9dca-ff82cb06dce8",
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       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (y: 360, x: 408)&gt;\n",
       "array([[231., 252., 255., ..., 148., 149., 153.],\n",
       "       [215., 217., 237., ..., 140., 148., 168.],\n",
       "       [225., 223., 229., ..., 139., 152., 168.],\n",
       "       ...,\n",
       "       [ nan,  nan,  nan, ..., 119., 125., 121.],\n",
       "       [ nan,  nan,  nan, ..., 103., 117., 127.],\n",
       "       [ nan,  nan,  nan, ..., 100., 106., 118.]], dtype=float32)\n",
       "Coordinates:\n",
       "    band         int64 1\n",
       "  * x            (x) float64 -119.6 -119.6 -119.6 ... -116.2 -116.2 -116.2\n",
       "  * y            (y) float64 35.2 35.19 35.18 35.17 ... 32.23 32.22 32.21 32.2\n",
       "    spatial_ref  int64 0\n",
       "Attributes:\n",
       "    scale_factor:  0.001\n",
       "    add_offset:    0.0\n",
       "    long_name:     Gapfilled BRDF/Albedo data from V006 MCD43D</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 360</li><li><span class='xr-has-index'>x</span>: 408</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-1691b10a-327a-4889-a3be-67e674db930d' class='xr-array-in' type='checkbox' checked><label for='section-1691b10a-327a-4889-a3be-67e674db930d' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>231.0 252.0 255.0 251.0 250.0 250.0 ... 101.0 101.0 100.0 106.0 118.0</span></div><div class='xr-array-data'><pre>array([[231., 252., 255., ..., 148., 149., 153.],\n",
       "       [215., 217., 237., ..., 140., 148., 168.],\n",
       "       [225., 223., 229., ..., 139., 152., 168.],\n",
       "       ...,\n",
       "       [ nan,  nan,  nan, ..., 119., 125., 121.],\n",
       "       [ nan,  nan,  nan, ..., 103., 117., 127.],\n",
       "       [ nan,  nan,  nan, ..., 100., 106., 118.]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-d9e9eccc-0a65-4892-99ad-894b2d62c3df' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d9e9eccc-0a65-4892-99ad-894b2d62c3df' 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>band</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-fd5dc30b-2b0c-44e1-b2d6-568e59123c60' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fd5dc30b-2b0c-44e1-b2d6-568e59123c60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dcfd9ea1-6b3f-4e40-82ff-a0b1e70d4e2b' class='xr-var-data-in' type='checkbox'><label for='data-dcfd9ea1-6b3f-4e40-82ff-a0b1e70d4e2b' 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>array(1)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-119.6 -119.6 ... -116.2 -116.2</div><input id='attrs-bd6bad7c-0af9-48e1-8b36-3385f87fd357' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bd6bad7c-0af9-48e1-8b36-3385f87fd357' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78395514-7ea9-489d-9b9b-c79be0d11a8c' class='xr-var-data-in' type='checkbox'><label for='data-78395514-7ea9-489d-9b9b-c79be0d11a8c' 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>array([-119.595833, -119.5875  , -119.579167, ..., -116.220833, -116.2125  ,\n",
       "       -116.204167])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>35.2 35.19 35.18 ... 32.21 32.2</div><input id='attrs-78ed5eeb-d1d9-4bcc-95f0-42cb24144443' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-78ed5eeb-d1d9-4bcc-95f0-42cb24144443' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a6f6caa-c8ec-4273-a008-23a06ee3642a' class='xr-var-data-in' type='checkbox'><label for='data-1a6f6caa-c8ec-4273-a008-23a06ee3642a' 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>array([35.195833, 35.1875  , 35.179167, ..., 32.220833, 32.2125  , 32.204167])</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-5d20c06f-ac73-46be-8553-2d0b1302e0d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d20c06f-ac73-46be-8553-2d0b1302e0d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2d0ef76-a888-43bf-afda-eb4bd447ef29' class='xr-var-data-in' type='checkbox'><label for='data-f2d0ef76-a888-43bf-afda-eb4bd447ef29' 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;Unknown datum based upon the Clarke 1866 ellipsoid&quot;,DATUM[&quot;Not specified (based on Clarke 1866 spheroid)&quot;,SPHEROID[&quot;Clarke 1866&quot;,6378206.4,294.978698213898,AUTHORITY[&quot;EPSG&quot;,&quot;7008&quot;]]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378206.4</dd><dt><span>semi_minor_axis :</span></dt><dd>6356583.8</dd><dt><span>inverse_flattening :</span></dt><dd>294.978698213898</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>Clarke 1866</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>Unknown datum based upon the Clarke 1866 ellipsoid</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;Unknown datum based upon the Clarke 1866 ellipsoid&quot;,DATUM[&quot;Not specified (based on Clarke 1866 spheroid)&quot;,SPHEROID[&quot;Clarke 1866&quot;,6378206.4,294.978698213898,AUTHORITY[&quot;EPSG&quot;,&quot;7008&quot;]]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST]]</dd><dt><span>GeoTransform :</span></dt><dd>-180.0 0.008333333333333333 0.0 90.0 0.0 -0.008333333333333333</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-94119263-aa54-4272-a831-886fa8bb40ba' class='xr-section-summary-in' type='checkbox'  checked><label for='section-94119263-aa54-4272-a831-886fa8bb40ba' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>scale_factor :</span></dt><dd>0.001</dd><dt><span>add_offset :</span></dt><dd>0.0</dd><dt><span>long_name :</span></dt><dd>Gapfilled BRDF/Albedo data from V006 MCD43D</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (y: 360, x: 408)>\n",
       "array([[231., 252., 255., ..., 148., 149., 153.],\n",
       "       [215., 217., 237., ..., 140., 148., 168.],\n",
       "       [225., 223., 229., ..., 139., 152., 168.],\n",
       "       ...,\n",
       "       [ nan,  nan,  nan, ..., 119., 125., 121.],\n",
       "       [ nan,  nan,  nan, ..., 103., 117., 127.],\n",
       "       [ nan,  nan,  nan, ..., 100., 106., 118.]], dtype=float32)\n",
       "Coordinates:\n",
       "    band         int64 1\n",
       "  * x            (x) float64 -119.6 -119.6 -119.6 ... -116.2 -116.2 -116.2\n",
       "  * y            (y) float64 35.2 35.19 35.18 35.17 ... 32.23 32.22 32.21 32.2\n",
       "    spatial_ref  int64 0\n",
       "Attributes:\n",
       "    scale_factor:  0.001\n",
       "    add_offset:    0.0\n",
       "    long_name:     Gapfilled BRDF/Albedo data from V006 MCD43D"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_1_2.sel(day=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e397bd95-047d-403d-81e2-000397ebe12a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (y: 360, x: 408)&gt;\n",
       "array([[238. , 251.5, 253.5, ..., 145.5, 147. , 148.5],\n",
       "       [223. , 221. , 237. , ..., 138.5, 147.5, 163.5],\n",
       "       [229. , 225.5, 231.5, ..., 137. , 151.5, 166.5],\n",
       "       ...,\n",
       "       [  nan,   nan,   nan, ..., 117.5, 124. , 119.5],\n",
       "       [  nan,   nan,   nan, ..., 103. , 117.5, 126.5],\n",
       "       [  nan,   nan,   nan, ...,  99. , 105. , 116. ]], dtype=float32)\n",
       "Coordinates:\n",
       "    band         int64 1\n",
       "  * x            (x) float64 -119.6 -119.6 -119.6 ... -116.2 -116.2 -116.2\n",
       "  * y            (y) float64 35.2 35.19 35.18 35.17 ... 32.23 32.22 32.21 32.2\n",
       "    spatial_ref  int64 0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 360</li><li><span class='xr-has-index'>x</span>: 408</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-b743c166-2a26-49bd-8443-2c02e09f804c' class='xr-array-in' type='checkbox' checked><label for='section-b743c166-2a26-49bd-8443-2c02e09f804c' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>238.0 251.5 253.5 251.0 250.0 250.0 ... 100.5 100.5 99.0 105.0 116.0</span></div><div class='xr-array-data'><pre>array([[238. , 251.5, 253.5, ..., 145.5, 147. , 148.5],\n",
       "       [223. , 221. , 237. , ..., 138.5, 147.5, 163.5],\n",
       "       [229. , 225.5, 231.5, ..., 137. , 151.5, 166.5],\n",
       "       ...,\n",
       "       [  nan,   nan,   nan, ..., 117.5, 124. , 119.5],\n",
       "       [  nan,   nan,   nan, ..., 103. , 117.5, 126.5],\n",
       "       [  nan,   nan,   nan, ...,  99. , 105. , 116. ]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-3f2c4586-4642-4f9c-9dc9-cf6da7aeb5f4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3f2c4586-4642-4f9c-9dc9-cf6da7aeb5f4' 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>band</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-5aede431-7b97-4973-8b24-495ee360a89f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5aede431-7b97-4973-8b24-495ee360a89f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3cac36f-06e8-44da-9d17-14719932a6bd' class='xr-var-data-in' type='checkbox'><label for='data-d3cac36f-06e8-44da-9d17-14719932a6bd' 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>array(1)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-119.6 -119.6 ... -116.2 -116.2</div><input id='attrs-1c6142df-ee87-43a0-9bee-a88e9579fef2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1c6142df-ee87-43a0-9bee-a88e9579fef2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb678b87-842a-499f-b398-e7f9215aae60' class='xr-var-data-in' type='checkbox'><label for='data-cb678b87-842a-499f-b398-e7f9215aae60' 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>array([-119.595833, -119.5875  , -119.579167, ..., -116.220833, -116.2125  ,\n",
       "       -116.204167])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>35.2 35.19 35.18 ... 32.21 32.2</div><input id='attrs-f260c382-bd24-451f-b3f8-d97d438df0b1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f260c382-bd24-451f-b3f8-d97d438df0b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f08ff0a2-9f2f-439e-8a40-65d77e8f8825' class='xr-var-data-in' type='checkbox'><label for='data-f08ff0a2-9f2f-439e-8a40-65d77e8f8825' 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>array([35.195833, 35.1875  , 35.179167, ..., 32.220833, 32.2125  , 32.204167])</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-d296df1c-c273-42ad-a438-031ac22cf49f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d296df1c-c273-42ad-a438-031ac22cf49f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cd4fc48-8010-4c09-b52f-1dbf472eb79b' class='xr-var-data-in' type='checkbox'><label for='data-2cd4fc48-8010-4c09-b52f-1dbf472eb79b' 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;Unknown datum based upon the Clarke 1866 ellipsoid&quot;,DATUM[&quot;Not specified (based on Clarke 1866 spheroid)&quot;,SPHEROID[&quot;Clarke 1866&quot;,6378206.4,294.978698213898,AUTHORITY[&quot;EPSG&quot;,&quot;7008&quot;]]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378206.4</dd><dt><span>semi_minor_axis :</span></dt><dd>6356583.8</dd><dt><span>inverse_flattening :</span></dt><dd>294.978698213898</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>Clarke 1866</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>Unknown datum based upon the Clarke 1866 ellipsoid</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;Unknown datum based upon the Clarke 1866 ellipsoid&quot;,DATUM[&quot;Not specified (based on Clarke 1866 spheroid)&quot;,SPHEROID[&quot;Clarke 1866&quot;,6378206.4,294.978698213898,AUTHORITY[&quot;EPSG&quot;,&quot;7008&quot;]]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST]]</dd><dt><span>GeoTransform :</span></dt><dd>-180.0 0.008333333333333333 0.0 90.0 0.0 -0.008333333333333333</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-1a0f2408-8563-423a-894b-3c72aebf6dfa' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1a0f2408-8563-423a-894b-3c72aebf6dfa' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (y: 360, x: 408)>\n",
       "array([[238. , 251.5, 253.5, ..., 145.5, 147. , 148.5],\n",
       "       [223. , 221. , 237. , ..., 138.5, 147.5, 163.5],\n",
       "       [229. , 225.5, 231.5, ..., 137. , 151.5, 166.5],\n",
       "       ...,\n",
       "       [  nan,   nan,   nan, ..., 117.5, 124. , 119.5],\n",
       "       [  nan,   nan,   nan, ..., 103. , 117.5, 126.5],\n",
       "       [  nan,   nan,   nan, ...,  99. , 105. , 116. ]], dtype=float32)\n",
       "Coordinates:\n",
       "    band         int64 1\n",
       "  * x            (x) float64 -119.6 -119.6 -119.6 ... -116.2 -116.2 -116.2\n",
       "  * y            (y) float64 35.2 35.19 35.18 35.17 ... 32.23 32.22 32.21 32.2\n",
       "    spatial_ref  int64 0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# test: compute average of ds_1_2 over \"day\" variable \n",
    "ds_mean = ds_1_2.mean(dim = 'day')\n",
    "ds_mean"
   ]
  },
  {
   "cell_type": "code",
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     "text": [
      "2015\n",
      "<class 'str'>\n",
      "2016\n",
      "<class 'str'>\n"
     ]
    }
   ],
   "source": [
    "years = ['2015', '2016']\n",
    "for year in years:\n",
    "    print(year)\n",
    "    print(type(year))"
   ]
  },
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     "text": [
      "24\n",
      "['MCD43GF_bsa_shortwave_336_2016_V006.hdf', 'MCD43GF_bsa_shortwave_337_2016_V006.hdf', 'MCD43GF_bsa_shortwave_338_2016_V006.hdf', 'MCD43GF_bsa_shortwave_339_2016_V006.hdf', 'MCD43GF_bsa_shortwave_340_2016_V006.hdf', 'MCD43GF_bsa_shortwave_341_2016_V006.hdf', 'MCD43GF_bsa_shortwave_342_2016_V006.hdf', 'MCD43GF_bsa_shortwave_343_2016_V006.hdf', 'MCD43GF_bsa_shortwave_344_2016_V006.hdf', 'MCD43GF_bsa_shortwave_345_2016_V006.hdf', 'MCD43GF_bsa_shortwave_346_2016_V006.hdf', 'MCD43GF_bsa_shortwave_347_2016_V006.hdf', 'MCD43GF_bsa_shortwave_348_2016_V006.hdf', 'MCD43GF_bsa_shortwave_349_2016_V006.hdf', 'MCD43GF_bsa_shortwave_350_2016_V006.hdf', 'MCD43GF_bsa_shortwave_351_2016_V006.hdf', 'MCD43GF_bsa_shortwave_352_2016_V006.hdf', 'MCD43GF_bsa_shortwave_353_2016_V006.hdf', 'MCD43GF_bsa_shortwave_354_2016_V006.hdf', 'MCD43GF_bsa_shortwave_355_2016_V006.hdf', 'MCD43GF_bsa_shortwave_356_2016_V006.hdf', 'MCD43GF_bsa_shortwave_357_2016_V006.hdf', 'MCD43GF_bsa_shortwave_358_2016_V006.hdf', 'MCD43GF_bsa_shortwave_359_2016_V006.hdf', 'MCD43GF_bsa_shortwave_360_2016_V006.hdf', 'MCD43GF_bsa_shortwave_361_2016_V006.hdf', 'MCD43GF_bsa_shortwave_362_2016_V006.hdf', 'MCD43GF_bsa_shortwave_363_2016_V006.hdf', 'MCD43GF_bsa_shortwave_364_2016_V006.hdf', 'MCD43GF_bsa_shortwave_365_2016_V006.hdf', 'MCD43GF_bsa_shortwave_366_2016_V006.hdf']\n"
     ]
    }
   ],
   "source": [
    "'''\n",
    "Create a list of lists\n",
    "- lists of files grouped by month\n",
    "- this code will only work if list_of_files is SORTED!!!\n",
    "'''\n",
    "list_of_years = ['2015', '2016']\n",
    "# get ordered list of all files in modis directory\n",
    "list_of_files = sorted(filter(lambda x: os.path.isfile(os.path.join(modis_directory, x)), os.listdir(modis_directory)))\n",
    "first_file = True\n",
    "files_by_month = []\n",
    "file_group = []\n",
    "for this_year in list_of_years:\n",
    "    for file in list_of_files:\n",
    "        # check if file is of current year\n",
    "        year_tag = \"_\" + this_year + \"_\"\n",
    "        if year_tag in file:\n",
    "            # extract year and month of file\n",
    "            year_string = file[26:30]\n",
    "            julian_day_string = file[22:25]\n",
    "            date = datetime.datetime.strptime(\"1/1/\" + year_string, \"%m/%d/%Y\") + \\\n",
    "                datetime.timedelta(int(julian_day_string) - 1)\n",
    "            date_string = str(date)\n",
    "            month_string = date_string[5:7]\n",
    "            month = int(month_string)\n",
    "            year = int(year_string)\n",
    "            julian_day = int(julian_day_string)\n",
    "\n",
    "            # append row to dataframe\n",
    "            if first_file:\n",
    "                file_group.append(file)\n",
    "                first_file = False\n",
    "                current_month = month\n",
    "            else:\n",
    "                if month == current_month:\n",
    "                    file_group.append(file)\n",
    "                    current_month = month\n",
    "                else:\n",
    "                    files_by_month.append(file_group)\n",
    "                    file_group = []\n",
    "                    file_group.append(file)\n",
    "                    current_month = month\n",
    "        # if file is not of current year\n",
    "        else:\n",
    "            pass\n",
    "\n",
    "# append file group of files\n",
    "files_by_month.append(file_group)\n",
    "\n",
    "# # test print files_by_month list\n",
    "# print(len(files_by_month))\n",
    "# print(files_by_month[23])"
   ]
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   "id": "646769b5-002d-494e-9794-9dd0cc5a2a60",
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   "source": [
    "'''\n",
    "Now that we have files_by_month, we can iterate through the list of list\n",
    "and then create a grouped xarray object for each iteration\n",
    "\n",
    "Then save each xarray as monthly averages:\n",
    "e.g., 'albedo_modis_2015_01'\n",
    "\n",
    "Output will be monthly average in MODIS grid. Still need to regrid in further code below.\n",
    "'''\n",
    "# variable_list = ['Albedo_WSA_shortwave', 'Albedo_BSA_shortwave'] # variables we want to extract\n",
    "for group in files_by_month:\n",
    "    ds_list = []\n",
    "    for file in group:\n",
    "        ds = rxr.open_rasterio(modis_directory + '/' + file, masked = True)\n",
    "        ds_slice = ds.sel(band=1, x=slice(-119.6,-116.2), y=slice(35.2,32.2)) # subset of global domain (i.e., just socal)\n",
    "        ds_list.append(ds_slice) # append data to list\n",
    "    \n",
    "    # calculate the monthly mean excluding NaNs\n",
    "    ds_concat = xr.concat(ds_list, dim = 'day_index')\n",
    "    monthly_mean = ds_concat.mean(dim = 'day_index', skipna = True)\n",
    "    \n",
    "    # save monthly average as netcdf file\n",
    "    year_string = file[26:30]\n",
    "    julian_day_string = file[22:25]\n",
    "    date = datetime.datetime.strptime(\"1/1/\" + year_string, \"%m/%d/%Y\") + \\\n",
    "        datetime.timedelta(int(julian_day_string) - 1)\n",
    "    date_string = str(date)\n",
    "    month_string = date_string[5:7]\n",
    "    monthly_mean.to_netcdf(output_directory + '/albedo_modis_' +\n",
    "                           year_string + '_' + month_string + '.nc', engine='netcdf4')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6cbbd196-33f0-419b-b9e8-74e281962042",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/scratch/kojoseph/modis/mcd43gf/bsa_only/monthly/albedo_modis_2015_01.nc\n"
     ]
    }
   ],
   "source": [
    "monthly_albedo_list = []\n",
    "for file in sorted(filter(lambda x: os.path.isfile(os.path.join(output_directory, x)), os.listdir(output_directory))):\n",
    "    full_path = output_directory + \"/\" + file\n",
    "    monthly_albedo_list.append(full_path)\n",
    "print(monthly_albedo_list[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "96584624-6c91-47c7-af59-4a51e41c4ad6",
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   "outputs": [
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       "  * x                              (x) float64 -119.6 -119.6 ... -116.2 -116.2\n",
       "  * y                              (y) float64 35.2 35.19 35.18 ... 32.21 32.2\n",
       "    spatial_ref                    int64 ...\n",
       "Data variables:\n",
       "    __xarray_dataarray_variable__  (y, x) float32 dask.array&lt;chunksize=(360, 408), meta=np.ndarray&gt;</pre><div class='xr-wrap' hidden><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-3c396af2-da4a-41a4-b805-64ed3435bcbc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3c396af2-da4a-41a4-b805-64ed3435bcbc' 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'>x</span>: 408</li><li><span class='xr-has-index'>y</span>: 360</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-004e9aa3-2c4b-4f14-b641-570ddd33bf76' class='xr-section-summary-in' type='checkbox'  checked><label for='section-004e9aa3-2c4b-4f14-b641-570ddd33bf76' 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>band</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c6628b84-f60c-4c10-a690-a1b7c4349dfa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c6628b84-f60c-4c10-a690-a1b7c4349dfa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8821adf-e152-4cdc-bae2-db60d2e83c27' class='xr-var-data-in' type='checkbox'><label for='data-a8821adf-e152-4cdc-bae2-db60d2e83c27' 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>array(1)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-119.6 -119.6 ... -116.2 -116.2</div><input id='attrs-1d15f12b-956b-4c3f-a5a8-543bb0992cf7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1d15f12b-956b-4c3f-a5a8-543bb0992cf7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d631eb4-8cfd-42e0-aa56-18f8cc307867' class='xr-var-data-in' type='checkbox'><label for='data-1d631eb4-8cfd-42e0-aa56-18f8cc307867' 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>array([-119.595833, -119.5875  , -119.579167, ..., -116.220833, -116.2125  ,\n",
       "       -116.204167])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>35.2 35.19 35.18 ... 32.21 32.2</div><input id='attrs-17cf65f2-d87c-46b8-8c1d-d7eedb24fc50' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-17cf65f2-d87c-46b8-8c1d-d7eedb24fc50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c858b22c-f7ba-47b5-9ef4-c5b54e1da47e' class='xr-var-data-in' type='checkbox'><label for='data-c858b22c-f7ba-47b5-9ef4-c5b54e1da47e' 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>array([35.195833, 35.1875  , 35.179167, ..., 32.220833, 32.2125  , 32.204167])</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'>...</div><input id='attrs-ecbc8ab3-57e2-435c-8ea1-0ab8fd7d6b0f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ecbc8ab3-57e2-435c-8ea1-0ab8fd7d6b0f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-508e3868-6dcc-4431-9129-422a74f0d808' class='xr-var-data-in' type='checkbox'><label for='data-508e3868-6dcc-4431-9129-422a74f0d808' 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;Unknown datum based upon the Clarke 1866 ellipsoid&quot;,DATUM[&quot;Not specified (based on Clarke 1866 spheroid)&quot;,SPHEROID[&quot;Clarke 1866&quot;,6378206.4,294.978698213898,AUTHORITY[&quot;EPSG&quot;,&quot;7008&quot;]]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378206.4</dd><dt><span>semi_minor_axis :</span></dt><dd>6356583.8</dd><dt><span>inverse_flattening :</span></dt><dd>294.978698213898</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>Clarke 1866</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>Unknown datum based upon the Clarke 1866 ellipsoid</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;Unknown datum based upon the Clarke 1866 ellipsoid&quot;,DATUM[&quot;Not specified (based on Clarke 1866 spheroid)&quot;,SPHEROID[&quot;Clarke 1866&quot;,6378206.4,294.978698213898,AUTHORITY[&quot;EPSG&quot;,&quot;7008&quot;]]],PRIMEM[&quot;Greenwich&quot;,0],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST]]</dd><dt><span>GeoTransform :</span></dt><dd>-180.0 0.008333333333333333 0.0 90.0 0.0 -0.008333333333333333</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-511cad01-0fee-4875-bef7-ae426197deb6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-511cad01-0fee-4875-bef7-ae426197deb6' class='xr-section-summary' >Data variables: <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-var-name'><span>__xarray_dataarray_variable__</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(360, 408), meta=np.ndarray&gt;</div><input id='attrs-a251f0c4-4aaf-46f7-b456-5b68e118184d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a251f0c4-4aaf-46f7-b456-5b68e118184d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-419fde6c-ebcc-4ac1-b7c5-49751255bd89' class='xr-var-data-in' type='checkbox'><label for='data-419fde6c-ebcc-4ac1-b7c5-49751255bd89' 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'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 573.75 kiB </td>\n",
       "                        <td> 573.75 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (360, 408) </td>\n",
       "                        <td> (360, 408) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"155\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"120\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"105\" x2=\"120\" y2=\"105\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"105\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"105\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,105.88235294117648 0.0,105.88235294117648\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"60.000000\" y=\"125.882353\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >408</text>\n",
       "  <text x=\"140.000000\" y=\"52.941176\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,52.941176)\">360</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-35741ae8-d733-489c-bcb1-9e05d33f24a2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-35741ae8-d733-489c-bcb1-9e05d33f24a2' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                        (x: 408, y: 360)\n",
       "Coordinates:\n",
       "    band                           int64 ...\n",
       "  * x                              (x) float64 -119.6 -119.6 ... -116.2 -116.2\n",
       "  * y                              (y) float64 35.2 35.19 35.18 ... 32.21 32.2\n",
       "    spatial_ref                    int64 ...\n",
       "Data variables:\n",
       "    __xarray_dataarray_variable__  (y, x) float32 dask.array<chunksize=(360, 408), meta=np.ndarray>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# test open one of the netcdf files\n",
    "ds = xr.open_mfdataset(monthly_albedo_list[0])\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "81b69a28-26c6-4528-9788-e2cf1cdadc30",
   "metadata": {},
   "outputs": [],
   "source": [
    "# concatenate all monthly averages into on netcdf file\n",
    "ds = xr.open_mfdataset(monthly_albedo_list, combine = \"nested\", concat_dim = \"time\")\n",
    "ds.to_netcdf(output_directory + '/monthly_albedo_combined.nc', engine = 'netcdf4')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d23db10-3424-4e73-8c0d-cfcfa21e05f8",
   "metadata": {},
   "source": [
    "## Regrid to WRF grid \n",
    "\n",
    "hdf-eos to net-cdf\n",
    "\n",
    "@author: joseph ko"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "985f8fd3-65fe-48d4-98d0-02824d8565b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "Regrid to WRF grid \n",
    "\n",
    "hdf-eos to net-cdf\n",
    "\n",
    "@author: joseph ko\n",
    "\"\"\"\n",
    "import xesmf as xe\n",
    "import re\n",
    "import pyproj\n",
    "import shutil\n",
    "import glob\n",
    "import matplotlib.pyplot as plt\n",
    "import cartopy.crs as ccrs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "efcd01c8-e275-43e4-bb1c-0fd9acc43a4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# testing cartopy and matplotlib\n",
    "ax = plt.axes(projection=ccrs.Mollweide())\n",
    "ax.stock_img()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "45907790-9c54-467f-a5af-b666cc32edcb",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# ======================================================================\n",
    "# User input data\n",
    "# ======================================================================\n",
    "modis_directory = '/scratch/kojoseph/modis/mcd43gf/bsa_only/monthly'\n",
    "wrf_input_directory = '/project/banweiss_274/kojoseph/wrfinputs_2015'\n",
    "output_directory = '/scratch/kojoseph/modis/mcd43gf/bsa_only/regridded'\n",
    "#regridder_file = 'mod13_to_wrf_regrid_weights.nc'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a798fcce-b27f-448f-bc2b-73a96e4060ee",
   "metadata": {},
   "source": [
    "## Regrid MCD43GF files to WRF grid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bae64fac-4e73-45d9-a7f9-883e193f8709",
   "metadata": {},
   "outputs": [],
   "source": [
    "# create list of all modis files and wrf files\n",
    "modis_path_list = glob.glob(modis_directory + '/albedo*')\n",
    "wrf_path_list = glob.glob(wrf_input_directory + '/*')\n",
    "\n",
    "# create regrid weights and save to file for re-use later\n",
    "regridder_output_path = '/scratch/kojoseph/modis/mcd43gf_to_wrf_regrid_weights.nc'\n",
    "tmp_albedo_file = xr.open_dataarray(modis_path_list[0])\n",
    "lon, lat = np.meshgrid(tmp_albedo_file['x'], tmp_albedo_file['y'])\n",
    "tmp_albedo_file = tmp_albedo_file.assign_coords({'lon': (['y', 'x'], lon),\n",
    "                       'lat': (['y', 'x'], lat)})\n",
    "tmp_wrf_file = xr.open_dataset(wrf_path_list[0])\n",
    "tmp_wrf_file = tmp_wrf_file.rename({'XLAT':'lat', 'XLONG':'lon'})\n",
    "tmp_wrf_file = tmp_wrf_file.squeeze('Time')\n",
    "# print(tmp_albedo_file)\n",
    "# print(tmp_wrf_file)\n",
    "\n",
    "regridder = xe.Regridder(tmp_albedo_file, tmp_wrf_file, 'bilinear', \n",
    "                         filename = regridder_output_path)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "fab05dc7-f131-4a6c-b973-5e71f3ddbbf3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'09'"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "modis_path_list[0][-5:-3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "bccbef5d-7686-4604-9575-6812ea6b966d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# loop through and regrid all files in directory\n",
    "for file in modis_path_list:\n",
    "    year_str = file[-10:-6]\n",
    "    month_str = file[-5:-3]\n",
    "    modis_albedo = xr.open_dataarray(file)\n",
    "    modis_albedo = modis_albedo*0.001\n",
    "    lon, lat = np.meshgrid(modis_albedo['x'], modis_albedo['y'])\n",
    "    modis_albedo = modis_albedo.assign_coords({'lon': (['y', 'x'], lon),\n",
    "                       'lat': (['y', 'x'], lat)})\n",
    "    # regrid to WRF grid\n",
    "    regridder_reuse = xe.Regridder(modis_albedo, tmp_wrf_file,'bilinear', periodic=False, \n",
    "                                   reuse_weights=True, filename = regridder_output_path)\n",
    "\n",
    "    modis_albedo_out = regridder_reuse(modis_albedo)\n",
    "    # print(modis_albedo_out)\n",
    "\n",
    "    # write regridded data as netcdf file\n",
    "    modis_albedo_out.to_netcdf(path = output_directory + \"/albedo_regridded_\" +\n",
    "                               year_str + \"_\" + month_str + \".nc\", mode = 'w')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ee03bb8-9b92-4252-b656-eee652788916",
   "metadata": {},
   "source": [
    "## Replace default albedo and GVF in WRF input files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "40f33fe8-7025-4cee-86b6-304ba73d3e16",
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "Example of files names:\n",
    "regridded albedo -> albedo_regridded_2015_01.nc\n",
    "regridded gvf -> wrfinput_d03_2015_01.nc\n",
    "wrf input -> wrfinput_d03_201501\n",
    "'''\n",
    "wrf_output_directory = '/project/banweiss_274/kojoseph/wrfinputs_2015/modis_albedo_gvf'\n",
    "regridded_albedo_dir = '/scratch/kojoseph/modis/mcd43gf/bsa_only/regridded'\n",
    "regridded_gvf_dir = '/scratch/kojoseph/modis/mod13a3/regridded'\n",
    "for file in os.listdir(wrf_output_directory):    \n",
    "    # year/month of current file\n",
    "    month_str = file[-2:]\n",
    "    year_str = file[-6:-2]\n",
    "    wrf_ds = xr.open_dataset(wrf_output_directory + '/' + file, engine = 'netcdf4')\n",
    "    albedo_default = wrf_ds['ALBBCK']\n",
    "    landmask = wrf_ds['LANDMASK']\n",
    "    gvf_file = regridded_gvf_dir + '/wrfinput_d03_' + year_str + '_' + month_str + '.nc'\n",
    "    albedo_file = regridded_albedo_dir + '/albedo_regridded_' + year_str + '_' + month_str + '.nc'\n",
    "    wrf_modis_gvf = xr.open_dataset(gvf_file)\n",
    "    modis_gvf = wrf_modis_gvf['VEGFRA'][:]\n",
    "    modis_albedo = xr.open_dataarray(albedo_file)\n",
    "    modis_albedo = modis_albedo.where(landmask!=0)\n",
    "    modis_albedo = modis_albedo.combine_first(albedo_default) # replace with default values if NA\n",
    "    # replace default values \n",
    "    wrf_input_new = Dataset(wrf_output_directory + '/' + file, 'r+')\n",
    "    # print(modis_gvf.shape)\n",
    "    # print(wrf_input_new['VEGFRA'][:].shape)\n",
    "    # print(wrf_input_new['ALBBCK'][:].shape)\n",
    "    # print(modis_albedo[:,:,0].shape)\n",
    "    wrf_input_new['VEGFRA'][:] = modis_gvf\n",
    "    wrf_input_new['ALBBCK'][0,:] = modis_albedo[:,:,0]\n",
    "    wrf_input_new.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0f07d71e-30b8-4c85-8ff4-275149c75d3c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # iterate through all daily modis files in directory\n",
    "# count = 1\n",
    "# for entry in os.scandir(modis_directory):\n",
    "#     if count < 2:\n",
    "#         # extract year and month of file\n",
    "#         print(file)\n",
    "#         year_string = entry.name[9:13]\n",
    "#         julian_day_string = entry.name[13:16]\n",
    "#         date_temp = datetime.datetime.strptime(\"1/1/\" + year_string, \"%m/%d/%Y\") + \\\n",
    "#             datetime.timedelta(int(julian_day_string) - 1)\n",
    "#         date_temp_string = str(date_temp)\n",
    "#         print(date_temp_string)\n",
    "#         month_string = date_temp_string[5:7]\n",
    "#         print(year_string)\n",
    "#         print(month_string)\n",
    "        \n",
    "#         # open modis file \n",
    "#         modis_ds = rxr.open_rasterio(entry.path, masked = True) \n",
    "#         print(list(modis_ds))\n",
    "        \n",
    "#         # name of monthly average file\n",
    "#         monthly_avg_file = output_directory + '/mcd43a4_' + year_string + '_' + month_string + '.nc'\n",
    "#         print(monthly_avg_file)\n",
    "        \n",
    "#         if os.path.exists(monthly_avg_file):\n",
    "#             # open existing file and update running average\n",
    "#             pass\n",
    "#         else:\n",
    "#             # create xarray and then save as netcdf file\n",
    "#             pass\n",
    "            \n",
    "        \n",
    "#     count += 1"
   ]
  }
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