{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Testing Providentia Interpolation and NES Interpolation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from nes import *\n",
    "import geopandas as gpd\n",
    "import xarray as xr\n",
    "import matplotlib.pyplot as plt\n",
    "import copy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Original model (a4s2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.1. Read data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "path_0 = '/esarchive/exp/monarch/a4s2/global/hourly/od550du/od550du-000_2020060100.nc'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 25, lev: 1, lat: 181, lon: 257)\n",
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       "    comment:      Generated on marenostrum4</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-58dd96f1-77c1-4484-b8c6-3e7681cbc60f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-58dd96f1-77c1-4484-b8c6-3e7681cbc60f' 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'>time</span>: 25</li><li><span class='xr-has-index'>lev</span>: 1</li><li><span class='xr-has-index'>lat</span>: 181</li><li><span class='xr-has-index'>lon</span>: 257</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-87f46cb0-2290-4398-9323-e199989e90d8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-87f46cb0-2290-4398-9323-e199989e90d8' 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'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-06-01 ... 2020-06-02</div><input id='attrs-a67554ef-7979-4d38-9a1b-93e1b61cc393' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a67554ef-7979-4d38-9a1b-93e1b61cc393' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26c6b4f4-d517-475c-a441-06278222ce17' class='xr-var-data-in' type='checkbox'><label for='data-26c6b4f4-d517-475c-a441-06278222ce17' 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>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-06-01T00:00:00.000000000&#x27;, &#x27;2020-06-01T01:00:00.000000000&#x27;,\n",
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       "       &#x27;2020-06-01T06:00:00.000000000&#x27;, &#x27;2020-06-01T07:00:00.000000000&#x27;,\n",
       "       &#x27;2020-06-01T08:00:00.000013000&#x27;, &#x27;2020-06-01T09:00:00.000000000&#x27;,\n",
       "       &#x27;2020-06-01T10:00:00.000000000&#x27;, &#x27;2020-06-01T11:00:00.000012999&#x27;,\n",
       "       &#x27;2020-06-01T12:00:00.000000000&#x27;, &#x27;2020-06-01T13:00:00.000000000&#x27;,\n",
       "       &#x27;2020-06-01T14:00:00.000012999&#x27;, &#x27;2020-06-01T15:00:00.000000000&#x27;,\n",
       "       &#x27;2020-06-01T16:00:00.000000000&#x27;, &#x27;2020-06-01T17:00:00.000012999&#x27;,\n",
       "       &#x27;2020-06-01T18:00:00.000000000&#x27;, &#x27;2020-06-01T19:00:00.000000000&#x27;,\n",
       "       &#x27;2020-06-01T20:00:00.000013000&#x27;, &#x27;2020-06-01T21:00:00.000000000&#x27;,\n",
       "       &#x27;2020-06-01T22:00:00.000000000&#x27;, &#x27;2020-06-01T23:00:00.000013000&#x27;,\n",
       "       &#x27;2020-06-02T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-a7dea364-d088-454e-91f4-5ce62e67cfcb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a7dea364-d088-454e-91f4-5ce62e67cfcb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-61e19c2a-9683-4116-aa64-e74c343aeb29' class='xr-var-data-in' type='checkbox'><label for='data-61e19c2a-9683-4116-aa64-e74c343aeb29' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>-</dd><dt><span>positive :</span></dt><dd>up</dd></dl></div><div class='xr-var-data'><pre>array([0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.0 -88.0 ... 89.0 90.0</div><input id='attrs-09ec6052-ce27-4669-8147-876580838416' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-09ec6052-ce27-4669-8147-876580838416' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ae8104d-16eb-4594-b6bf-883e22925c5c' class='xr-var-data-in' type='checkbox'><label for='data-4ae8104d-16eb-4594-b6bf-883e22925c5c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude coordinate</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-90., -89., -88., -87., -86., -85., -84., -83., -82., -81., -80., -79.,\n",
       "       -78., -77., -76., -75., -74., -73., -72., -71., -70., -69., -68., -67.,\n",
       "       -66., -65., -64., -63., -62., -61., -60., -59., -58., -57., -56., -55.,\n",
       "       -54., -53., -52., -51., -50., -49., -48., -47., -46., -45., -44., -43.,\n",
       "       -42., -41., -40., -39., -38., -37., -36., -35., -34., -33., -32., -31.,\n",
       "       -30., -29., -28., -27., -26., -25., -24., -23., -22., -21., -20., -19.,\n",
       "       -18., -17., -16., -15., -14., -13., -12., -11., -10.,  -9.,  -8.,  -7.,\n",
       "        -6.,  -5.,  -4.,  -3.,  -2.,  -1.,   0.,   1.,   2.,   3.,   4.,   5.,\n",
       "         6.,   7.,   8.,   9.,  10.,  11.,  12.,  13.,  14.,  15.,  16.,  17.,\n",
       "        18.,  19.,  20.,  21.,  22.,  23.,  24.,  25.,  26.,  27.,  28.,  29.,\n",
       "        30.,  31.,  32.,  33.,  34.,  35.,  36.,  37.,  38.,  39.,  40.,  41.,\n",
       "        42.,  43.,  44.,  45.,  46.,  47.,  48.,  49.,  50.,  51.,  52.,  53.,\n",
       "        54.,  55.,  56.,  57.,  58.,  59.,  60.,  61.,  62.,  63.,  64.,  65.,\n",
       "        66.,  67.,  68.,  69.,  70.,  71.,  72.,  73.,  74.,  75.,  76.,  77.,\n",
       "        78.,  79.,  80.,  81.,  82.,  83.,  84.,  85.,  86.,  87.,  88.,  89.,\n",
       "        90.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -178.6 ... 178.6 180.0</div><input id='attrs-a53342fa-ab24-47f8-81da-f610fd3e681a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a53342fa-ab24-47f8-81da-f610fd3e681a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-382377f1-b842-4c83-a560-3f71ce05a574' class='xr-var-data-in' type='checkbox'><label for='data-382377f1-b842-4c83-a560-3f71ce05a574' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude coordinate</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-180.     , -178.59375, -177.1875 , ...,  177.1875 ,  178.59375,\n",
       "        180.     ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-98a311b9-ef4c-4849-8d41-565195ae7b0a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-98a311b9-ef4c-4849-8d41-565195ae7b0a' class='xr-section-summary' >Data variables: <span>(2)</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>od550du</span></div><div class='xr-var-dims'>(time, lev, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9ba49c0f-10b5-40f4-8d9a-ba76c88bc9b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ba49c0f-10b5-40f4-8d9a-ba76c88bc9b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c7ede4b-69c5-4d3f-861e-95f8ee3f1e4f' class='xr-var-data-in' type='checkbox'><label for='data-0c7ede4b-69c5-4d3f-861e-95f8ee3f1e4f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>-</dd><dt><span>long_name :</span></dt><dd>Aerosol optical depth</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd></dl></div><div class='xr-var-data'><pre>[1162925 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-22834f57-8cc2-4424-984d-a413816e9de8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22834f57-8cc2-4424-984d-a413816e9de8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5aacbe9-3b67-4236-8866-848b97a3e73f' class='xr-var-data-in' type='checkbox'><label for='data-f5aacbe9-3b67-4236-8866-848b97a3e73f' 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>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>semi_major_axis :</span></dt><dd>6371000.0</dd><dt><span>inverse_flattening :</span></dt><dd>0</dd></dl></div><div class='xr-var-data'><pre>array(-2147483647, dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-eb37a6d6-0411-4ba6-8afa-29b6609dbec0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-eb37a6d6-0411-4ba6-8afa-29b6609dbec0' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>comment :</span></dt><dd>Generated on marenostrum4</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 25, lev: 1, lat: 181, lon: 257)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2020-06-01 2020-06-01T01:00:00 ... 2020-06-02\n",
       "  * lev      (lev) float64 0.0\n",
       "  * lat      (lat) float64 -90.0 -89.0 -88.0 -87.0 -86.0 ... 87.0 88.0 89.0 90.0\n",
       "  * lon      (lon) float64 -180.0 -178.6 -177.2 -175.8 ... 177.2 178.6 180.0\n",
       "Data variables:\n",
       "    od550du  (time, lev, lat, lon) float32 ...\n",
       "    crs      int32 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.7\n",
       "    comment:      Generated on marenostrum4"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xr.open_dataset(path_0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<nes.nc_projections.latlon_nes.LatLonNes at 0x7f510113d4d0>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_model = open_netcdf(path=path_0, info=True)\n",
    "data_model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rank 000: Loading od550du var (1/1)\n",
      "Rank 000: Loaded od550du var ((25, 1, 181, 257))\n"
     ]
    }
   ],
   "source": [
    "data_model.keep_vars(['od550du'])\n",
    "data_model.load()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.2. Create shapefile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "      <th>od550du</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POLYGON ((-180.70312 -90.50000, -179.29688 -90...</td>\n",
       "      <td>0.000144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>POLYGON ((-179.29688 -90.50000, -177.89062 -90...</td>\n",
       "      <td>0.000144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>POLYGON ((-177.89062 -90.50000, -176.48438 -90...</td>\n",
       "      <td>0.000144</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POLYGON ((-176.48438 -90.50000, -175.07812 -90...</td>\n",
       "      <td>0.000144</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>POLYGON ((-175.07812 -90.50000, -173.67188 -90...</td>\n",
       "      <td>0.000144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>46512</th>\n",
       "      <td>POLYGON ((173.67188 89.50000, 175.07812 89.500...</td>\n",
       "      <td>0.023041</td>\n",
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       "    <tr>\n",
       "      <th>46513</th>\n",
       "      <td>POLYGON ((175.07812 89.50000, 176.48438 89.500...</td>\n",
       "      <td>0.023041</td>\n",
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       "    <tr>\n",
       "      <th>46514</th>\n",
       "      <td>POLYGON ((176.48438 89.50000, 177.89062 89.500...</td>\n",
       "      <td>0.023041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46515</th>\n",
       "      <td>POLYGON ((177.89062 89.50000, 179.29688 89.500...</td>\n",
       "      <td>0.023041</td>\n",
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       "    <tr>\n",
       "      <th>46516</th>\n",
       "      <td>POLYGON ((179.29688 89.50000, 180.70312 89.500...</td>\n",
       "      <td>0.023041</td>\n",
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       "<p>46517 rows × 2 columns</p>\n",
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      ],
      "text/plain": [
       "                                                geometry   od550du\n",
       "FID                                                               \n",
       "0      POLYGON ((-180.70312 -90.50000, -179.29688 -90...  0.000144\n",
       "1      POLYGON ((-179.29688 -90.50000, -177.89062 -90...  0.000144\n",
       "2      POLYGON ((-177.89062 -90.50000, -176.48438 -90...  0.000144\n",
       "3      POLYGON ((-176.48438 -90.50000, -175.07812 -90...  0.000144\n",
       "4      POLYGON ((-175.07812 -90.50000, -173.67188 -90...  0.000144\n",
       "...                                                  ...       ...\n",
       "46512  POLYGON ((173.67188 89.50000, 175.07812 89.500...  0.023041\n",
       "46513  POLYGON ((175.07812 89.50000, 176.48438 89.500...  0.023041\n",
       "46514  POLYGON ((176.48438 89.50000, 177.89062 89.500...  0.023041\n",
       "46515  POLYGON ((177.89062 89.50000, 179.29688 89.500...  0.023041\n",
       "46516  POLYGON ((179.29688 89.50000, 180.70312 89.500...  0.023041\n",
       "\n",
       "[46517 rows x 2 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_model.create_shapefile()\n",
    "data_model.shapefile['od550du'] = data_model.variables['od550du']['data'][0, 0, :].ravel()\n",
    "data_model.shapefile"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.3. Plot data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "[encoded data, 204848 characters]",
      "text/plain": [
       "<Figure size 1440x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, figsize=(20, 7))\n",
    "\n",
    "gdf_model = data_model.shapefile\n",
    "gdf_model.plot(ax=ax, column='od550du', cmap='viridis', legend=True)\n",
    "\n",
    "gdf_earth = gpd.read_file('/gpfs/projects/bsc32/models/NES_tutorial_data/timezones_2021c/timezones_2021c.shp')\n",
    "gdf_earth.plot(ax=ax, facecolor=\"none\", edgecolor='white', lw=0.5)\n",
    "\n",
    "ax.margins(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Observations (AERONET_v3_lev1.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.1. Read data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "path_obs = '/esarchive/obs/ghost/AERONET_v3_lev1.5/1.4/hourly/od550aero/od550aero_202006.nc'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       "  --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.Dataset&gt;\n",
       "Dimensions:                                                           (station: 366, time: 720, N_flag_codes: 190, N_qa_codes: 77)\n",
       "Coordinates:\n",
       "  * time                                                              (time) datetime64[ns] ...\n",
       "Dimensions without coordinates: station, N_flag_codes, N_qa_codes\n",
       "Data variables: (12/180)\n",
       "    ASTER_v3_altitude                                                 (station) float32 ...\n",
       "    EDGAR_v4.3.2_annual_average_BC_emissions                          (station) float32 ...\n",
       "    EDGAR_v4.3.2_annual_average_CO_emissions                          (station) float32 ...\n",
       "    EDGAR_v4.3.2_annual_average_NH3_emissions                         (station) float32 ...\n",
       "    EDGAR_v4.3.2_annual_average_NMVOC_emissions                       (station) float32 ...\n",
       "    EDGAR_v4.3.2_annual_average_NOx_emissions                         (station) float32 ...\n",
       "    ...                                                                ...\n",
       "    station_timezone                                                  (station) object ...\n",
       "    street_type                                                       (station) object ...\n",
       "    street_width                                                      (station) float32 ...\n",
       "    terrain                                                           (station) object ...\n",
       "    vertical_datum                                                    (station) object ...\n",
       "    weekday_weekend_code                                              (station, time) uint8 ...\n",
       "Attributes:\n",
       "    title:          Surface aerosol optical depth at 550nm data in the AERONE...\n",
       "    institution:    Barcelona Supercomputing Center\n",
       "    source:         Surface observations\n",
       "    creator_name:   Dene R. Bowdalo\n",
       "    creator_email:  dene.bowdalo@bsc.es\n",
       "    version:        1.4</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-916e7689-c413-4c50-9a5b-780f75e766af' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-916e7689-c413-4c50-9a5b-780f75e766af' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>station</span>: 366</li><li><span class='xr-has-index'>time</span>: 720</li><li><span>N_flag_codes</span>: 190</li><li><span>N_qa_codes</span>: 77</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ff2453df-b509-42cb-a86f-f7072ca5fd8c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ff2453df-b509-42cb-a86f-f7072ca5fd8c' class='xr-section-summary' >Coordinates: <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 class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-06-01 ... 2020-06-30T23:00:00</div><input id='attrs-64f43cec-3aaa-4fba-bc45-705ee7841923' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64f43cec-3aaa-4fba-bc45-705ee7841923' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9f52496-ddea-45fc-abea-5c330ffab7f7' class='xr-var-data-in' type='checkbox'><label for='data-d9f52496-ddea-45fc-abea-5c330ffab7f7' 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>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>description :</span></dt><dd>Time in hours since 2020-06-01 00:00 UTC. Time given refers to the start of the time window the measurement is representative of (temporal resolution).</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>tz :</span></dt><dd>UTC</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-06-01T00:00:00.000000000&#x27;, &#x27;2020-06-01T01:00:00.000000000&#x27;,\n",
       "       &#x27;2020-06-01T02:00:00.000000000&#x27;, ..., &#x27;2020-06-30T21:00:00.000000000&#x27;,\n",
       "       &#x27;2020-06-30T22:00:00.000000000&#x27;, &#x27;2020-06-30T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9b35fe32-7bae-4797-a708-e7d3d447984b' class='xr-section-summary-in' type='checkbox'  ><label for='section-9b35fe32-7bae-4797-a708-e7d3d447984b' class='xr-section-summary' >Data variables: <span>(180)</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>ASTER_v3_altitude</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-258e633a-7690-405f-870f-92a2628302bf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-258e633a-7690-405f-870f-92a2628302bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-68e6b0f3-66ac-4b5f-b6a5-ac9dfb80da8d' class='xr-var-data-in' type='checkbox'><label for='data-68e6b0f3-66ac-4b5f-b6a5-ac9dfb80da8d' 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>standard_name :</span></dt><dd>ASTER v3 altitude</dd><dt><span>long_name :</span></dt><dd>ASTER v3 altitude, relative to EGM96 geoid datum</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>description :</span></dt><dd>Altitude from ASTER v3 digital elevation model, relative to EGM96 geoid vertical datum, in metres. The dataset was generated using 1,880,306 Level-1A scenes (taken from the NASA TERRA spacecraft) acquired between March 1, 2000 and November 30, 2013. The ASTER GDEM was created by stacking all individual cloud-masked scene DEMs and non-cloud-masked scene DEMs, then applying various algorithms to remove abnormal data. A statistical approach is not always effective for anomaly removal in areas with a limited number of images. Several existing reference DEMs were used to replace residual anomalies caused by the insufficient number of stacked scenes. In addition to ASTER GDEM, the ASTER Global Water Body Database (ASTWBD) was generated as a by-product to correct elevation values of water body surfaces like sea, rivers, and lakes. The ASTWBD was applied to GDEM to provide proper elevation values for water body surfaces. The sea and lake have a flattened elevation value. The river has a stepped-down elevation value from the upper stream to the lower stream. Native resolution of 1 arc second ~= 30m at the equator.</dd></dl></div><div class='xr-var-data'><pre>array([1313.,   18.,   15., ...,  234.,  454.,  179.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EDGAR_v4.3.2_annual_average_BC_emissions</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a224d7c8-9ea3-424b-acd9-5e6142877552' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a224d7c8-9ea3-424b-acd9-5e6142877552' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43525cc0-b329-4da3-96d4-9930bc4f09b1' class='xr-var-data-in' type='checkbox'><label for='data-43525cc0-b329-4da3-96d4-9930bc4f09b1' 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>standard_name :</span></dt><dd>EDGAR v4.3.2 annual average BC emissions</dd><dt><span>long_name :</span></dt><dd>EDGAR v4.3.2 annual average black carbon emissions</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>description :</span></dt><dd>EDGAR v4.3.2 annual average BC emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees.</dd></dl></div><div class='xr-var-data'><pre>array([2.489332e-13, 0.000000e+00, 0.000000e+00, ..., 0.000000e+00,\n",
       "       0.000000e+00, 2.421291e-13], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EDGAR_v4.3.2_annual_average_CO_emissions</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b0294f7f-0675-4338-b008-b1710af4e022' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0294f7f-0675-4338-b008-b1710af4e022' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5106c750-491a-4e5c-bf75-64c4559c74ec' class='xr-var-data-in' type='checkbox'><label for='data-5106c750-491a-4e5c-bf75-64c4559c74ec' 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>standard_name :</span></dt><dd>EDGAR v4.3.2 annual average CO emissions</dd><dt><span>long_name :</span></dt><dd>EDGAR v4.3.2 annual average carbon monoxide emissions</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>description :</span></dt><dd>EDGAR v4.3.2 annual average CO emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees.</dd></dl></div><div class='xr-var-data'><pre>array([3.161767e-11, 0.000000e+00, 0.000000e+00, ..., 0.000000e+00,\n",
       "       0.000000e+00, 6.931332e-13], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EDGAR_v4.3.2_annual_average_NH3_emissions</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f1652db6-8d3b-4708-bb11-1806ed5433ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1652db6-8d3b-4708-bb11-1806ed5433ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-027ca82f-b6ab-4a0c-bee1-d27b876e872c' class='xr-var-data-in' type='checkbox'><label for='data-027ca82f-b6ab-4a0c-bee1-d27b876e872c' 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>standard_name :</span></dt><dd>EDGAR v4.3.2 annual average NH3 emissions</dd><dt><span>long_name :</span></dt><dd>EDGAR v4.3.2 annual average ammonia emissions</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>description :</span></dt><dd>EDGAR v4.3.2 annual average NH3 emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees.</dd></dl></div><div class='xr-var-data'><pre>array([9.423107e-16, 0.000000e+00, 0.000000e+00, ..., 0.000000e+00,\n",
       "       0.000000e+00, 1.087701e-15], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EDGAR_v4.3.2_annual_average_NMVOC_emissions</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6196dbd9-d01f-411a-b0a7-51c546bb9c27' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6196dbd9-d01f-411a-b0a7-51c546bb9c27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6cc630b3-69d5-482b-9999-7d74958241e6' class='xr-var-data-in' type='checkbox'><label for='data-6cc630b3-69d5-482b-9999-7d74958241e6' 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>standard_name :</span></dt><dd>EDGAR v4.3.2 annual average NMVOC emissions</dd><dt><span>long_name :</span></dt><dd>EDGAR v4.3.2 annual average non-methane volatile organic compound emissions</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>description :</span></dt><dd>EDGAR v4.3.2 annual average NMVOC emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees.</dd></dl></div><div class='xr-var-data'><pre>array([6.275388e-12, 0.000000e+00, 0.000000e+00, ..., 0.000000e+00,\n",
       "       0.000000e+00, 4.111606e-12], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EDGAR_v4.3.2_annual_average_NOx_emissions</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-42abfc4b-a1b6-4862-8401-0bfeb1fecad7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42abfc4b-a1b6-4862-8401-0bfeb1fecad7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0975fbce-9d48-4cd5-a9b0-d67fab635eaf' class='xr-var-data-in' type='checkbox'><label for='data-0975fbce-9d48-4cd5-a9b0-d67fab635eaf' 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>standard_name :</span></dt><dd>EDGAR v4.3.2 annual average NOx emissions</dd><dt><span>long_name :</span></dt><dd>EDGAR v4.3.2 annual average emissions of nitrogen oxides</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>description :</span></dt><dd>EDGAR v4.3.2 annual average NOx emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees.</dd></dl></div><div class='xr-var-data'><pre>array([6.169598e-12, 0.000000e+00, 0.000000e+00, ..., 0.000000e+00,\n",
       "       0.000000e+00, 1.253201e-11], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EDGAR_v4.3.2_annual_average_OC_emissions</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cab87eae-e41f-4ff5-b60f-73400abfee3b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cab87eae-e41f-4ff5-b60f-73400abfee3b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6cb839bb-faf6-4eac-87db-f2c3a7854553' class='xr-var-data-in' type='checkbox'><label for='data-6cb839bb-faf6-4eac-87db-f2c3a7854553' 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>standard_name :</span></dt><dd>EDGAR v4.3.2 annual average OC emissions</dd><dt><span>long_name :</span></dt><dd>EDGAR v4.3.2 annual average organic carbon emissions</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>description :</span></dt><dd>EDGAR v4.3.2 annual average OC emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees.</dd></dl></div><div class='xr-var-data'><pre>array([1.244637e-13, 0.000000e+00, 0.000000e+00, ..., 0.000000e+00,\n",
       "       0.000000e+00, 1.210442e-13], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EDGAR_v4.3.2_annual_average_PM10_emissions</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ad3e5cb9-ee6c-4a41-8fd1-da444978befa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad3e5cb9-ee6c-4a41-8fd1-da444978befa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-76b7d786-4260-4c37-a969-4fdf9d9ff407' class='xr-var-data-in' type='checkbox'><label for='data-76b7d786-4260-4c37-a969-4fdf9d9ff407' 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>standard_name :</span></dt><dd>EDGAR v4.3.2 annual average PM10 emissions</dd><dt><span>long_name :</span></dt><dd>EDGAR v4.3.2 annual average PM10 emissions</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>description :</span></dt><dd>EDGAR v4.3.2 annual average PM10 emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees.</dd></dl></div><div class='xr-var-data'><pre>array([1.244739e-12, 0.000000e+00, 0.000000e+00, ..., 0.000000e+00,\n",
       "       0.000000e+00, 1.211099e-12], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EDGAR_v4.3.2_annual_average_SO2_emissions</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e93e2f6d-7d6a-43c8-a1b0-d5586bb9e4d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e93e2f6d-7d6a-43c8-a1b0-d5586bb9e4d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d7de53a-33d5-4c65-97e5-cda7914bf533' class='xr-var-data-in' type='checkbox'><label for='data-5d7de53a-33d5-4c65-97e5-cda7914bf533' 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>standard_name :</span></dt><dd>EDGAR v4.3.2 annual average SO2 emissions</dd><dt><span>long_name :</span></dt><dd>EDGAR v4.3.2 annual average sulphur dioxide emissions</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>description :</span></dt><dd>EDGAR v4.3.2 annual average SO2 emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees.</dd></dl></div><div class='xr-var-data'><pre>array([4.236494e-12, 0.000000e+00, 0.000000e+00, ..., 0.000000e+00,\n",
       "       0.000000e+00, 7.338124e-12], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EDGAR_v4.3.2_annual_average_biogenic_PM2.5_emissions</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-aae7e157-ee53-446a-93f5-0f4b5aabaec2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aae7e157-ee53-446a-93f5-0f4b5aabaec2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3d376ac-e642-4b04-b51e-1a5fbac1d4e3' class='xr-var-data-in' type='checkbox'><label for='data-b3d376ac-e642-4b04-b51e-1a5fbac1d4e3' 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>standard_name :</span></dt><dd>EDGAR v4.3.2 annual average biogenic PM2.5 emissions</dd><dt><span>long_name :</span></dt><dd>EDGAR v4.3.2 annual average biogenic PM2.5 emissions</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>description :</span></dt><dd>EDGAR v4.3.2 annual average biogenic PM2.5 emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees.</dd></dl></div><div class='xr-var-data'><pre>array([3.510429e-17, 0.000000e+00, 0.000000e+00, ..., 0.000000e+00,\n",
       "       0.000000e+00, 3.058946e-16], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EDGAR_v4.3.2_annual_average_fossilfuel_PM2.5_emissions</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d47f1bd3-f86f-4846-9698-91abd0a637ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d47f1bd3-f86f-4846-9698-91abd0a637ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-048ac5ca-c4e2-43f6-9c67-2619eef17a81' class='xr-var-data-in' type='checkbox'><label for='data-048ac5ca-c4e2-43f6-9c67-2619eef17a81' 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>standard_name :</span></dt><dd>EDGAR v4.3.2 annual average fossil fuel PM2.5 emissions</dd><dt><span>long_name :</span></dt><dd>EDGAR v4.3.2 annual average fossil fuel PM2.5 emissions</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>description :</span></dt><dd>EDGAR v4.3.2 annual average fossil fuel PM2.5 emissions, in kilograms per squared metre per second. Native resolution of 0.1 x 0.1 degrees.</dd></dl></div><div class='xr-var-data'><pre>array([1.244664e-12, 0.000000e+00, 0.000000e+00, ..., 0.000000e+00,\n",
       "       0.000000e+00, 1.210459e-12], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ESDAC_Iwahashi_landform_classification</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-89eb76f9-2efd-4daf-8abb-480f15c09d1d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89eb76f9-2efd-4daf-8abb-480f15c09d1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d22897af-0705-47f4-a79c-2451b3725445' class='xr-var-data-in' type='checkbox'><label for='data-d22897af-0705-47f4-a79c-2451b3725445' 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>standard_name :</span></dt><dd>ESDAC Iwahashi landform classification</dd><dt><span>long_name :</span></dt><dd>ESDAC Iwahashi landform classification</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>European Soil Data Centre (ESDAC) Iwahashi landform classification. The classification presents relief classes which are classified using an unsupervised nested-means algorithms and a three part geometric signature. Slope gradient, surface texture and local convexity are calculated based on the SRTM30 digital elevation model, within a given window size and classified according to the inherent data set properties. This is a dynamic landform classification method. Native resolution of 0.0083 x 0.0083 degrees. A correction for costal sites is made: if the native class is &quot;water&quot;, then the modal classification of the neighbouring grid boxes is used instead (lowest code kept preferentially in case of a tie). If the site is truly an &quot;ocean&quot; site, all the surrounding gridcells will be water also, and therefore the class will be maintained as &quot;water&quot;.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;medium steep - coarse texture - low convexity&#x27;,\n",
       "       &#x27;medium steep - fine texture - low convexity&#x27;,\n",
       "       &#x27;gentle - coarse texture - low convexity&#x27;, ...,\n",
       "       &#x27;medium steep - coarse texture - low convexity&#x27;,\n",
       "       &#x27;medium gentle - fine texture - low convexity&#x27;,\n",
       "       &#x27;medium gentle - fine texture - high convexity&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ESDAC_Meybeck_landform_classification</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-61b5a512-2748-48c6-b077-ab473216e126' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-61b5a512-2748-48c6-b077-ab473216e126' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-717c7911-7789-4027-9d52-1c773c43eb08' class='xr-var-data-in' type='checkbox'><label for='data-717c7911-7789-4027-9d52-1c773c43eb08' 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>standard_name :</span></dt><dd>ESDAC Meybeck landform classification</dd><dt><span>long_name :</span></dt><dd>ESDAC Meybeck landform classification</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>European Soil Data Centre (ESDAC) Meybeck landform classification. The classification presents relief classes which are calculated based on the relief roughness. Roughness and elevation are classified based on a digital elevation model according to static thresholds, with a given window size. This is a static landform classification method. Native resolution of 0.0083 x 0.0083 degrees. A correction for costal sites is made: if the native class is &quot;water&quot;, then the modal classification of the neighbouring grid boxes is used instead (lowest code kept preferentially in case of a tie). If the site is truly an &quot;ocean&quot; site, all the surrounding gridcells will be water also, and therefore the class will be maintained as &quot;water&quot;.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;high altitude plains&#x27;, &#x27;water&#x27;, &#x27;nan&#x27;, ..., &#x27;very low plateaus&#x27;,\n",
       "       &#x27;mid altitude plains&#x27;, &#x27;lowlands&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ESDAC_modal_Iwahashi_landform_classification_25km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-41269783-a640-4d0c-84ab-08d0bc3879ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-41269783-a640-4d0c-84ab-08d0bc3879ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8b11ba7-8d43-4668-b676-b891f2f0b893' class='xr-var-data-in' type='checkbox'><label for='data-b8b11ba7-8d43-4668-b676-b891f2f0b893' 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>standard_name :</span></dt><dd>ESDAC modal Iwahashi landform classification 25km</dd><dt><span>long_name :</span></dt><dd>ESDAC modal Iwahashi landform classification in 25km radius</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Modal European Soil Data Centre (ESDAC) Iwahashi landform classification in radius of 25km around station location.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;medium steep - coarse texture - low convexity&#x27;, &#x27;water&#x27;, &#x27;water&#x27;, ...,\n",
       "       &#x27;medium steep - fine texture - high convexity&#x27;,\n",
       "       &#x27;medium gentle - fine texture - high convexity&#x27;,\n",
       "       &#x27;medium steep - fine texture - high convexity&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ESDAC_modal_Iwahashi_landform_classification_5km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-25a24290-76ed-4937-ab6f-b388a17ce66e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25a24290-76ed-4937-ab6f-b388a17ce66e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44f05587-92a0-4ca8-b82d-3c38d315651b' class='xr-var-data-in' type='checkbox'><label for='data-44f05587-92a0-4ca8-b82d-3c38d315651b' 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>standard_name :</span></dt><dd>ESDAC modal Iwahashi landform classification 5km</dd><dt><span>long_name :</span></dt><dd>ESDAC modal Iwahashi landform classification in 5km radius</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Modal European Soil Data Centre (ESDAC) Iwahashi landform classification in radius of 5km around station location.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;medium steep - coarse texture - low convexity&#x27;, &#x27;water&#x27;, &#x27;water&#x27;, ...,\n",
       "       &#x27;medium steep - coarse texture - low convexity&#x27;,\n",
       "       &#x27;medium gentle - fine texture - low convexity&#x27;,\n",
       "       &#x27;medium steep - fine texture - high convexity&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ESDAC_modal_Meybeck_landform_classification_25km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a0c14ca9-7349-46e7-a952-724a5dcbf37c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0c14ca9-7349-46e7-a952-724a5dcbf37c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04a47689-33d4-44f2-b3e0-b3ea78451993' class='xr-var-data-in' type='checkbox'><label for='data-04a47689-33d4-44f2-b3e0-b3ea78451993' 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>standard_name :</span></dt><dd>ESDAC modal Meybeck landform classification 25km</dd><dt><span>long_name :</span></dt><dd>ESDAC modal Meybeck landform classification in 25km radius</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Modal European Soil Data Centre (ESDAC) Meybeck landform classification in radius of 25km around station location.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;mid altitude plateaus&#x27;, &#x27;water&#x27;, &#x27;nan&#x27;, ..., &#x27;very low plateaus&#x27;,\n",
       "       &#x27;mid altitude plains&#x27;, &#x27;plains&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ESDAC_modal_Meybeck_landform_classification_5km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d13d8479-1e5a-406b-b8d5-9dbb39d76393' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d13d8479-1e5a-406b-b8d5-9dbb39d76393' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b110be06-6857-46cf-a0ad-aae724465f05' class='xr-var-data-in' type='checkbox'><label for='data-b110be06-6857-46cf-a0ad-aae724465f05' 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>standard_name :</span></dt><dd>ESDAC modal Meybeck landform classification 5km</dd><dt><span>long_name :</span></dt><dd>ESDAC modal Meybeck landform classification in 5km radius</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Modal European Soil Data Centre (ESDAC) Meybeck landform classification in radius of 5km around station location.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;high altitude plains&#x27;, &#x27;water&#x27;, &#x27;nan&#x27;, ..., &#x27;very low plateaus&#x27;,\n",
       "       &#x27;mid altitude plains&#x27;, &#x27;plains&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ETOPO1_altitude</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0235f8ac-6292-4470-9d43-3c1bbba6bb16' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0235f8ac-6292-4470-9d43-3c1bbba6bb16' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd427960-7d06-4efb-b7e5-0cf84b434b3d' class='xr-var-data-in' type='checkbox'><label for='data-fd427960-7d06-4efb-b7e5-0cf84b434b3d' 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>standard_name :</span></dt><dd>ETOPO1 altitude</dd><dt><span>long_name :</span></dt><dd>ETOPO1 altitude, relative to sea level datum</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>description :</span></dt><dd>Altitude from ETOPO1 digital elevation model, relative to sea level vertical datum, in metres. Over Antarctica and Greenland the elevation given is on top of the ice sheets. Native resolution of 1 arc minute. A correction for coastal sites is made: if the derived altitude is &lt;= -5 m, the maximum altitude of the neighbouring grid boxes will be used instead. If all neighbouring grid boxes have altitudes &lt;= -5 m, the original value will be retained.</dd></dl></div><div class='xr-var-data'><pre>array([1299.,   26.,    2., ...,  216.,  456.,  176.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ETOPO1_max_altitude_difference_5km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4964a76e-86cc-4b95-8c88-09d89c05cacd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4964a76e-86cc-4b95-8c88-09d89c05cacd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48159f6a-4528-4089-88dc-9e8d4a460a7e' class='xr-var-data-in' type='checkbox'><label for='data-48159f6a-4528-4089-88dc-9e8d4a460a7e' 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>standard_name :</span></dt><dd>ETOPO1 max altitude difference 5km</dd><dt><span>long_name :</span></dt><dd>ETOPO1 maximum altitude difference between the ETOPO1_altitude and all ETOPO1 altitudes in 5km radius</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>description :</span></dt><dd>Altitude difference between the ETOPO1_altitude, and the minimum ETOP1 altitude in a radius of 5 km around the station location, in metres.</dd></dl></div><div class='xr-var-data'><pre>array([ 24., 145.,   5., ...,  31.,   9.,  26.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GHOST_version</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5dd27336-4942-48ae-b936-67c464c23b40' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5dd27336-4942-48ae-b936-67c464c23b40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-913ffb72-dbf6-4125-8eef-601f4043687e' class='xr-var-data-in' type='checkbox'><label for='data-913ffb72-dbf6-4125-8eef-601f4043687e' 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>standard_name :</span></dt><dd>GHOST version</dd><dt><span>long_name :</span></dt><dd>Globally Harmonised Observational Surface Treatment (GHOST) version</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Version of the Globally Harmonised Observational Surface Treatment (GHOST).</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1.4&#x27;, &#x27;1.4&#x27;, &#x27;1.4&#x27;, ..., &#x27;1.4&#x27;, &#x27;1.4&#x27;, &#x27;1.4&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GHSL_average_built_up_area_density_25km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-15a4a0ed-1a62-4fdf-ac4a-6f3dae67f80e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15a4a0ed-1a62-4fdf-ac4a-6f3dae67f80e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0943439-aa70-4ec3-aec1-efd5311083e8' class='xr-var-data-in' type='checkbox'><label for='data-a0943439-aa70-4ec3-aec1-efd5311083e8' 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>standard_name :</span></dt><dd>GHSL average built up area density 25km</dd><dt><span>long_name :</span></dt><dd>GHSL average built up area density in 25km radius</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>description :</span></dt><dd>Global Human Settlement Layer (GHSL) average built up area density in a radius of 25km around the station location.</dd></dl></div><div class='xr-var-data'><pre>array([ 0.973138,  0.069935,  0.118563, ...,  4.052589,  0.882098, 13.686182],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GHSL_average_built_up_area_density_5km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-22bed924-2fca-41bb-947a-a097c6cfdec5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22bed924-2fca-41bb-947a-a097c6cfdec5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c25912d3-a90b-4441-bb70-2e187c014e8e' class='xr-var-data-in' type='checkbox'><label for='data-c25912d3-a90b-4441-bb70-2e187c014e8e' 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>standard_name :</span></dt><dd>GHSL average built up area density 5km</dd><dt><span>long_name :</span></dt><dd>GHSL average built up area density in 5km radius</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>description :</span></dt><dd>Global Human Settlement Layer (GHSL) average built up area density in a radius of 5km around the station location.</dd></dl></div><div class='xr-var-data'><pre>array([ 0.779646,  1.149631,  0.344782, ..., 41.303318, 15.780167, 12.955944],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GHSL_average_population_density_25km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-66eac089-7748-4ff9-9df2-0ac71b99a894' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-66eac089-7748-4ff9-9df2-0ac71b99a894' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ab62db2-5c3f-48f2-979c-36a7fa081d7c' class='xr-var-data-in' type='checkbox'><label for='data-6ab62db2-5c3f-48f2-979c-36a7fa081d7c' 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>standard_name :</span></dt><dd>GHSL average population density 25km</dd><dt><span>long_name :</span></dt><dd>GHSL average population density in 25km radius</dd><dt><span>units :</span></dt><dd>xx km–2</dd><dt><span>description :</span></dt><dd>Global Human Settlement Layer (GHSL) average population density in a radius of 25km around the station location.</dd></dl></div><div class='xr-var-data'><pre>array([1.933994e+01, 2.114581e+00, 3.526324e-01, ..., 3.771514e+02,\n",
       "       3.493256e+02, 1.995498e+02], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GHSL_average_population_density_5km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-20c64045-9667-4798-a8a0-185906d984f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-20c64045-9667-4798-a8a0-185906d984f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6f2072b7-c00d-49ea-bcf4-ba7e8755e6f3' class='xr-var-data-in' type='checkbox'><label for='data-6f2072b7-c00d-49ea-bcf4-ba7e8755e6f3' 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>standard_name :</span></dt><dd>GHSL average population density 5km</dd><dt><span>long_name :</span></dt><dd>GHSL average population density in 5km radius</dd><dt><span>units :</span></dt><dd>xx km–2</dd><dt><span>description :</span></dt><dd>Global Human Settlement Layer (GHSL) average population density in a radius of 5km around the station location.</dd></dl></div><div class='xr-var-data'><pre>array([8.326788e+01, 3.396778e+01, 4.800151e-01, ..., 4.657755e+03,\n",
       "       6.104640e+03, 2.213394e+02], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GHSL_built_up_area_density</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f60ba6e9-e6ea-4da0-a277-4015bb0bc64f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f60ba6e9-e6ea-4da0-a277-4015bb0bc64f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdd16f5c-61ac-4e3b-8a7f-a11a176b7e73' class='xr-var-data-in' type='checkbox'><label for='data-fdd16f5c-61ac-4e3b-8a7f-a11a176b7e73' 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>standard_name :</span></dt><dd>GHSL built up area density</dd><dt><span>long_name :</span></dt><dd>GHSL built up area density</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>description :</span></dt><dd>Global Human Settlement Layer (GHSL) built up area density (technical label: GHS_BUILT_LDSMT_GLOBE_R2018A), in units of built-up area percent per gridcell (0-100). The product is a multitemporal information layer on built-up presence as derived from Landsat image collections (GLS1975, GLS1990, GLS2000, and ad-hoc Landsat 8 collection 2013/2014). Native resolution of 0.25 x 0.25 kilometres.</dd></dl></div><div class='xr-var-data'><pre>array([ 0.    ,  0.    ,  0.    , ..., 83.7568,  0.    , 33.7712],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GHSL_max_built_up_area_density_25km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8c9a7d99-bea7-4d24-8b0b-29a421813d78' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c9a7d99-bea7-4d24-8b0b-29a421813d78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f27ede1-592d-4da1-a907-5a199a06c252' class='xr-var-data-in' type='checkbox'><label for='data-5f27ede1-592d-4da1-a907-5a199a06c252' 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>standard_name :</span></dt><dd>GHSL max built up area density 25km</dd><dt><span>long_name :</span></dt><dd>GHSL max built up area density in 25km radius</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>description :</span></dt><dd>Global Human Settlement Layer (GHSL) max built up area density in a radius of 25km around the station location.</dd></dl></div><div class='xr-var-data'><pre>array([ 98.,  95.,  65., ..., 100., 100., 100.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GHSL_max_built_up_area_density_5km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-382ec1e7-a080-46d9-abaf-1b06be85a89f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-382ec1e7-a080-46d9-abaf-1b06be85a89f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99e60244-b67e-40f2-b97e-0e5110c65ca2' class='xr-var-data-in' type='checkbox'><label for='data-99e60244-b67e-40f2-b97e-0e5110c65ca2' 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>standard_name :</span></dt><dd>GHSL max built up area density 5km</dd><dt><span>long_name :</span></dt><dd>GHSL max built up area density in 5km radius</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>description :</span></dt><dd>Global Human Settlement Layer (GHSL) max built up area density in a radius of 5km around the station location.</dd></dl></div><div class='xr-var-data'><pre>array([ 87.,  95.,  26., ..., 100., 100.,  99.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GHSL_max_population_density_25km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8c8c3a53-ccd3-4f78-b37c-4e9d82d15960' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c8c3a53-ccd3-4f78-b37c-4e9d82d15960' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca1983f4-cc06-438d-81b4-459293d110f3' class='xr-var-data-in' type='checkbox'><label for='data-ca1983f4-cc06-438d-81b4-459293d110f3' 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>standard_name :</span></dt><dd>GHSL max population density 25km</dd><dt><span>long_name :</span></dt><dd>GHSL max population density in 25km radius</dd><dt><span>units :</span></dt><dd>xx km–2</dd><dt><span>description :</span></dt><dd>Global Human Settlement Layer (GHSL) max population density in a radius of 25km around the station location.</dd></dl></div><div class='xr-var-data'><pre>array([ 8958.,  2350.,   549., ..., 11219., 45549.,  9135.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GHSL_max_population_density_5km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fbad23e7-36c3-4a1e-9dca-86cd6883ea52' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fbad23e7-36c3-4a1e-9dca-86cd6883ea52' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7c3c71a-15c5-4278-ab7b-d43fa371e781' class='xr-var-data-in' type='checkbox'><label for='data-a7c3c71a-15c5-4278-ab7b-d43fa371e781' 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>standard_name :</span></dt><dd>GHSL max population density 5km</dd><dt><span>long_name :</span></dt><dd>GHSL max population density in 5km radius</dd><dt><span>units :</span></dt><dd>xx km–2</dd><dt><span>description :</span></dt><dd>Global Human Settlement Layer (GHSL) max population density in a radius of 5km around the station location.</dd></dl></div><div class='xr-var-data'><pre>array([8.9580e+03, 2.3500e+03, 4.3000e+01, ..., 1.1219e+04, 4.5549e+04,\n",
       "       1.7360e+03], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GHSL_modal_settlement_model_classification_25km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a5784f25-bd8c-439c-a36f-a5a267844906' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a5784f25-bd8c-439c-a36f-a5a267844906' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e5b44b1-b9dc-4d19-ac8e-53296f7547ae' class='xr-var-data-in' type='checkbox'><label for='data-1e5b44b1-b9dc-4d19-ac8e-53296f7547ae' 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>standard_name :</span></dt><dd>GHSL modal settlement model classification 25km</dd><dt><span>long_name :</span></dt><dd>GHSL modal settlement model classification in 25km radius</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Modal Global Human Settlement Layer (GHSL) settlement model classification in radius of 25km around station location.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;very low density rural&#x27;, &#x27;water&#x27;, &#x27;water&#x27;, ...,\n",
       "       &#x27;very low density rural&#x27;, &#x27;very low density rural&#x27;,\n",
       "       &#x27;very low density rural&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GHSL_modal_settlement_model_classification_5km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a0d9be7b-868d-4d56-a248-055e489004c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0d9be7b-868d-4d56-a248-055e489004c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24f4a177-9a0b-4111-aa99-ac8d5386b987' class='xr-var-data-in' type='checkbox'><label for='data-24f4a177-9a0b-4111-aa99-ac8d5386b987' 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>standard_name :</span></dt><dd>GHSL modal settlement model classification 5km</dd><dt><span>long_name :</span></dt><dd>GHSL modal settlement model classification in 5km radius</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Modal Global Human Settlement Layer (GHSL) settlement model classification in radius of 5km around station location.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;very low density rural&#x27;, &#x27;water&#x27;, &#x27;water&#x27;, ..., &#x27;urban centre&#x27;,\n",
       "       &#x27;very low density rural&#x27;, &#x27;low density rural&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GHSL_population_density</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-391db14c-0630-4ec6-8191-d9b01f828d4e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-391db14c-0630-4ec6-8191-d9b01f828d4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9b99bbc-96b3-4186-9295-9579f2bff679' class='xr-var-data-in' type='checkbox'><label for='data-c9b99bbc-96b3-4186-9295-9579f2bff679' 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>standard_name :</span></dt><dd>GHSL population density</dd><dt><span>long_name :</span></dt><dd>GHSL population density</dd><dt><span>units :</span></dt><dd>xx km–2</dd><dt><span>description :</span></dt><dd>Global Human Settlement Layer (GHSL) population density (technical label: GHS_POP_MT_GLOBE_R2019A), in populus per squared kilometre. It depicts the distribution of population, expressed as the number of people per cell. Residential population estimates for target years 1975, 1990, 2000 and 2015 provided by CIESIN GPWv4.10 were disaggregated from census or administrative units to grid cells, informed by the distribution and density of built-up as mapped in the GHSL global layer per corresponding epoch. Native resolution of 0.25 x 0.25 kilometres.</dd></dl></div><div class='xr-var-data'><pre>array([   0.    ,    0.    ,    0.    , ..., 9396.993 ,    0.    ,  556.0051],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GHSL_settlement_model_classification</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6c767ba4-bb59-44e4-904b-79a184a69fda' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c767ba4-bb59-44e4-904b-79a184a69fda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3dfcdd8f-e75b-45e2-825b-7f2a1c67f606' class='xr-var-data-in' type='checkbox'><label for='data-3dfcdd8f-e75b-45e2-825b-7f2a1c67f606' 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>standard_name :</span></dt><dd>GHSL settlement model classification</dd><dt><span>long_name :</span></dt><dd>GHSL settlement model classification</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Global Human Settlement Layer (GHSL) settlement model classification (technical label: GHS_SMOD_POPMT_GLOBE_R2019A). The classification delineates and classify settlement typologies via a logic of population size, population and built-up area densities as a refinement of the ‘degree of urbanization’ method described by EUROSTAT. The classification is derived by using the GHS_POP_MT_GLOBE_R2019A and GHS_BUILT_LDSMT_GLOBE_R2018A products. The GHS Settlement Model grid is an improvement of the GHS Settlement Grid (R2016A) introducing a more detailed classification of settlements in two levels, also called ‘refined degree of urbanization’. The Settlement Model is provided at detailed level (Second Level - L2). The First Level, as a porting of the Degree of Urbanization adopted by EUROSTAT can be obtained aggregating L2. Native resolution of 1.0 x 1.0 kilometres.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;very low density rural&#x27;, &#x27;very low density rural&#x27;,\n",
       "       &#x27;very low density rural&#x27;, ..., &#x27;urban centre&#x27;, &#x27;rural cluster&#x27;,\n",
       "       &#x27;low density rural&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GPW_average_population_density_25km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1025dc44-e7d4-4e2e-81da-ccd552eddb5b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1025dc44-e7d4-4e2e-81da-ccd552eddb5b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e96c70d-868e-4f54-9275-01b764ae6dab' class='xr-var-data-in' type='checkbox'><label for='data-1e96c70d-868e-4f54-9275-01b764ae6dab' 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>standard_name :</span></dt><dd>GPW average population density 25km</dd><dt><span>long_name :</span></dt><dd>GPW average population density in 25km radius</dd><dt><span>units :</span></dt><dd>xx km–2</dd><dt><span>description :</span></dt><dd>Gridded Population of the World (GPW), average population density in a radius of 25 km around the station location.</dd></dl></div><div class='xr-var-data'><pre>array([124.32709 ,   2.79323 ,   0.764419, ..., 357.12894 , 273.1742  ,\n",
       "       212.34114 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GPW_average_population_density_5km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-068c7dea-7b20-489b-a69d-437678708279' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-068c7dea-7b20-489b-a69d-437678708279' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29ce14cb-db57-4c57-98e0-0b4f60ef1697' class='xr-var-data-in' type='checkbox'><label for='data-29ce14cb-db57-4c57-98e0-0b4f60ef1697' 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>standard_name :</span></dt><dd>GPW average population density 5km</dd><dt><span>long_name :</span></dt><dd>GPW average population density in 5km radius</dd><dt><span>units :</span></dt><dd>xx km–2</dd><dt><span>description :</span></dt><dd>Gridded Population of the World (GPW), average population density in a radius of 5 km around the station location.</dd></dl></div><div class='xr-var-data'><pre>array([1.226605e+01, 4.290382e+01, 5.904162e-02, ..., 7.327646e+02,\n",
       "       4.929010e+02, 2.843317e+02], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GPW_max_population_density_25km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-17ddecd3-34f1-4121-908b-d106612bd6d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17ddecd3-34f1-4121-908b-d106612bd6d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99c8b85e-fcf1-4753-8c4a-b4b27b8c7b37' class='xr-var-data-in' type='checkbox'><label for='data-99c8b85e-fcf1-4753-8c4a-b4b27b8c7b37' 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>standard_name :</span></dt><dd>GPW max population density 25km</dd><dt><span>long_name :</span></dt><dd>GPW average population density in 25km radius</dd><dt><span>units :</span></dt><dd>xx km–2</dd><dt><span>description :</span></dt><dd>Gridded Population of the World (GPW), maximum population density in a radius of 25 km around the station location.</dd></dl></div><div class='xr-var-data'><pre>array([75960.96   ,   832.58167,   280.91034, ...,  1197.667  ,  2789.2234 ,\n",
       "        5616.408  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GPW_max_population_density_5km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e3f4a060-2478-449e-9b3e-c6b6fd176df8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e3f4a060-2478-449e-9b3e-c6b6fd176df8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d1eb20c-db52-4275-b608-4dc9f9d51785' class='xr-var-data-in' type='checkbox'><label for='data-5d1eb20c-db52-4275-b608-4dc9f9d51785' 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>standard_name :</span></dt><dd>GPW max population density 5km</dd><dt><span>long_name :</span></dt><dd>GPW average population density in 5km radius</dd><dt><span>units :</span></dt><dd>xx km–2</dd><dt><span>description :</span></dt><dd>Gridded Population of the World (GPW), maximum population density in a radius of 5 km around the station location.</dd></dl></div><div class='xr-var-data'><pre>array([1.226605e+01, 8.325817e+02, 9.681910e-01, ..., 1.085922e+03,\n",
       "       2.789223e+03, 3.627036e+02], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GPW_population_density</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7a6f71f0-ca26-4c66-9d15-5ddd569dd341' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a6f71f0-ca26-4c66-9d15-5ddd569dd341' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4f8136a-1f4a-441e-9d90-976fd9a29019' class='xr-var-data-in' type='checkbox'><label for='data-b4f8136a-1f4a-441e-9d90-976fd9a29019' 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>standard_name :</span></dt><dd>GPW population density</dd><dt><span>long_name :</span></dt><dd>GPW population density</dd><dt><span>units :</span></dt><dd>xx km–2</dd><dt><span>description :</span></dt><dd>Gridded Population of the World (GPW), population density, in populus per squared kilometre, from either version 3 and 4 of the provided gridded datasets, dependent on the data year: v3 (1990-2000), v4 (2000-2015). Native resolution of 0.04166 x 0.04166 for v3 data; native resolution of 0.0083 x 0.0083 degrees for v4 data.</dd></dl></div><div class='xr-var-data'><pre>array([1.226605e+01, 1.010118e+02, 8.580016e-02, ..., 7.309171e+02,\n",
       "       1.188315e+02, 2.668087e+02], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>GSFC_coastline_proximity</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4431cc6f-3932-4ec7-8388-559c5bee94e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4431cc6f-3932-4ec7-8388-559c5bee94e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0677357-3b3c-46ad-ae10-f0f5dca81a57' class='xr-var-data-in' type='checkbox'><label for='data-c0677357-3b3c-46ad-ae10-f0f5dca81a57' 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>standard_name :</span></dt><dd>GSFC coastline proximity</dd><dt><span>long_name :</span></dt><dd>GSFC proximity to the coastline</dd><dt><span>units :</span></dt><dd>km</dd><dt><span>description :</span></dt><dd>Proximity to the coastline provided by the NASA Goddard Space Flight Center (GSFC) Ocean Color Group, in kilometres, produced using the Generic Mapping Tools package. Native resolution of 0.01 x 0.01 degrees. Negative distances represent locations over land (including land-locked bodies of water), while positive distances represent locations over the ocean. There is an uncertainty of up to 1 km in the computed distance at any given point.</dd></dl></div><div class='xr-var-data'><pre>array([-718.,    0.,   -1., ..., -162., -950., -606.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Joly-Peuch_classification_code</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-58208105-a0dd-493d-ad87-8057694fc045' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58208105-a0dd-493d-ad87-8057694fc045' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15ca3116-a0fa-491a-9152-044411e02781' class='xr-var-data-in' type='checkbox'><label for='data-15ca3116-a0fa-491a-9152-044411e02781' 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>standard_name :</span></dt><dd>Joly-Peuch classification code</dd><dt><span>long_name :</span></dt><dd>Joly-Peuch classification code</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Joly-Peuch European classification code (range of 1-10) designed to objectively stratify stations between those diplaying rural and urban signatures (most rural == 1, most urban == 10). This classification is objectively made per species. The species that this is done for are: O3, NO2, SO2, CO, PM10, PM2.5. See reference here: https://www.sciencedirect.com/science/article/abs/pii/S1352231011012088</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Koppen-Geiger_classification</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1c85ad94-184d-4e5c-a8dc-df88aa33f4ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c85ad94-184d-4e5c-a8dc-df88aa33f4ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3c44c79-1829-416b-9660-f0a6f574f343' class='xr-var-data-in' type='checkbox'><label for='data-e3c44c79-1829-416b-9660-f0a6f574f343' 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>standard_name :</span></dt><dd>Koppen-Geiger classification</dd><dt><span>long_name :</span></dt><dd>Koppen-Geiger classification</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Koppen-Geiger classification, classifying the global climates into 5 main groups (30 total groups with subcategories). Native resolution of 0.0083 x 0.0083 degrees. A correction for costal sites is made: if the native class is &quot;water&quot;, then the modal classification of the neighbouring grid boxes is used instead (lowest code kept preferentially in case of a tie). If the site is truly an &quot;ocean&quot; site, all the surrounding gridcells will be water also, and therefore the class will be maintained as &quot;water&quot;. See citation: Beck, H.E., N.E. Zimmermann, T.R. McVicar, N. Vergopolan, A. Berg, E.F. Wood: Present and future Köppen-Geiger climate classification maps at 1-km resolution, Nature Scientific Data, 2018.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;arid - steppe - cold&#x27;, &#x27;temperate - dry summer - hot summer&#x27;,\n",
       "       &#x27;polar - tundra&#x27;, ..., &#x27;arid - steppe - cold&#x27;, &#x27;arid - desert - hot&#x27;,\n",
       "       &#x27;cold - no dry season - warm summer&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Koppen-Geiger_modal_classification_25km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fcb0cfd9-0012-4da1-9151-6cb70a5ccf51' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fcb0cfd9-0012-4da1-9151-6cb70a5ccf51' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d8d3787-2a7d-4853-9744-52c710a6feb1' class='xr-var-data-in' type='checkbox'><label for='data-2d8d3787-2a7d-4853-9744-52c710a6feb1' 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>standard_name :</span></dt><dd>Koppen-Geiger modal classification 25km</dd><dt><span>long_name :</span></dt><dd>Koppen-Geiger classification</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Modal Koppen-Geiger classification in radius of 25km around station location.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;arid - steppe - cold&#x27;, &#x27;water&#x27;, &#x27;water&#x27;, ..., &#x27;arid - steppe - cold&#x27;,\n",
       "       &#x27;arid - desert - hot&#x27;, &#x27;cold - no dry season - warm summer&#x27;],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Koppen-Geiger_modal_classification_5km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6e121279-fc8c-40c3-a4c6-8333108f7bd0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e121279-fc8c-40c3-a4c6-8333108f7bd0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2310cda-4abf-43df-ac30-78468ac3f11f' class='xr-var-data-in' type='checkbox'><label for='data-c2310cda-4abf-43df-ac30-78468ac3f11f' 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>standard_name :</span></dt><dd>Koppen-Geiger modal classification 5km</dd><dt><span>long_name :</span></dt><dd>Koppen-Geiger classification</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Modal Koppen-Geiger classification in radius of 5km around station location.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;arid - steppe - cold&#x27;, &#x27;water&#x27;, &#x27;water&#x27;, ..., &#x27;arid - steppe - cold&#x27;,\n",
       "       &#x27;arid - desert - hot&#x27;, &#x27;cold - no dry season - warm summer&#x27;],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MODIS_MCD12C1_v6_IGBP_land_use</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-874511db-0983-4e72-b15b-6b260375b833' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-874511db-0983-4e72-b15b-6b260375b833' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b8737a6-d068-4661-94a9-5d626541ea96' class='xr-var-data-in' type='checkbox'><label for='data-0b8737a6-d068-4661-94a9-5d626541ea96' 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>standard_name :</span></dt><dd>MODIS MCD12C1 v6 IGBP land use</dd><dt><span>long_name :</span></dt><dd>MODIS MCD12C1 v6 IGBP land use</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Majority land use class from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) MCD12C1 version 6, using the International Geosphere-Biosphere Programme (IGBP) classification. Native resolution of 0.05 x 0.05 degrees. See dataset user guide here: https://lpdaac.usgs.gov/documents/101/MCD12_User_Guide_V6.pd. A correction for costal sites is made: if the native class is &quot;water bodies&quot;, then the modal classification of the neighbouring grid boxes is used instead (lowest code kept preferentially in case of a tie). If the site is truly an &quot;ocean&quot; site, all the surrounding gridcells will be water also, and therefore the class will be maintained as &quot;water&quot;.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;grasslands&#x27;, &#x27;grasslands&#x27;, &#x27;permanent wetlands&#x27;, ...,\n",
       "       &#x27;urban and built-up lands&#x27;, &#x27;grasslands&#x27;, &#x27;woody savannas&#x27;],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MODIS_MCD12C1_v6_LAI</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0ccc4750-90c0-4e41-9020-d0ed490b287a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ccc4750-90c0-4e41-9020-d0ed490b287a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bde918e8-6069-481e-8b6c-9161777e6aa5' class='xr-var-data-in' type='checkbox'><label for='data-bde918e8-6069-481e-8b6c-9161777e6aa5' 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>standard_name :</span></dt><dd>MODIS MCD12C1 v6 LAI</dd><dt><span>long_name :</span></dt><dd>MODIS MCD12C1 v6 Leaf Area Index</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Majority Leaf Area Index class from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) MCD12C1 version 6. Native resolution of 0.05 x 0.05 degrees. See dataset user guide here: https://lpdaac.usgs.gov/documents/101/MCD12_User_Guide_V6.pd. A correction for costal sites is made: if the native class is &quot;water bodies&quot;, then the modal classification of the neighbouring grid boxes is used instead (lowest code kept preferentially in case of a tie). If the site is truly an &quot;ocean&quot; site, all the surrounding gridcells will be water also, and therefore the class will be maintained as &quot;water&quot;.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;grasslands&#x27;, &#x27;grasslands&#x27;, &#x27;grasslands&#x27;, ...,\n",
       "       &#x27;urban and built-up lands&#x27;, &#x27;grasslands&#x27;, &#x27;savannas&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MODIS_MCD12C1_v6_UMD_land_use</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f15b0dca-efc9-422b-b015-597bb6ef9fd1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f15b0dca-efc9-422b-b015-597bb6ef9fd1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c155b69-f7b6-4f7a-af8e-05c475fcc0d1' class='xr-var-data-in' type='checkbox'><label for='data-9c155b69-f7b6-4f7a-af8e-05c475fcc0d1' 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>standard_name :</span></dt><dd>MODIS MCD12C1 v6 UMD land use</dd><dt><span>long_name :</span></dt><dd>MODIS MCD12C1 v6 UMD land use</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Majority land use class from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) MCD12C1 version 6, using the University of Maryland (UMD) classification. Native resolution of 0.05 x 0.05 degrees. See dataset user guide here: https://lpdaac.usgs.gov/documents/101/MCD12_User_Guide_V6.pd. A correction for costal sites is made: if the native class is &quot;water bodies&quot;, then the modal classification of the neighbouring grid boxes is used instead (lowest code kept preferentially in case of a tie). If the site is truly an &quot;ocean&quot; site, all the surrounding gridcells will be water also, and therefore the class will be maintained as &quot;water&quot;.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;grasslands&#x27;, &#x27;grasslands&#x27;, &#x27;permanent wetlands&#x27;, ...,\n",
       "       &#x27;urban and built-up lands&#x27;, &#x27;grasslands&#x27;, &#x27;woody savannas&#x27;],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MODIS_MCD12C1_v6_modal_IGBP_land_use_25km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8040a9c5-4165-49bb-ae16-90e9d86a4876' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8040a9c5-4165-49bb-ae16-90e9d86a4876' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de1fc501-b9e0-4992-a87c-5a42a821c954' class='xr-var-data-in' type='checkbox'><label for='data-de1fc501-b9e0-4992-a87c-5a42a821c954' 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>standard_name :</span></dt><dd>MODIS MCD12C1 v6 IGBP modal land use 25km</dd><dt><span>long_name :</span></dt><dd>MODIS MCD12C1 v6 IGBP modal land use in 25km radius</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Modal land use in radius of 25km around the station location from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) MCD12C1 version 6, using the International Geosphere-Biosphere Programme (IGBP) classification.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;grasslands&#x27;, &#x27;water bodies&#x27;, &#x27;water bodies&#x27;, ..., &#x27;croplands&#x27;,\n",
       "       &#x27;grasslands&#x27;, &#x27;mixed forests&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MODIS_MCD12C1_v6_modal_IGBP_land_use_5km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7c818288-cdd4-4af7-9721-adc2f824cdbf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c818288-cdd4-4af7-9721-adc2f824cdbf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7a4bbcb-c28e-46d3-b2ca-37f981c65db5' class='xr-var-data-in' type='checkbox'><label for='data-c7a4bbcb-c28e-46d3-b2ca-37f981c65db5' 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>standard_name :</span></dt><dd>MODIS MCD12C1 v6 IGBP modal land use 5km</dd><dt><span>long_name :</span></dt><dd>MODIS MCD12C1 v6 IGBP modal land use in 5km radius</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Modal land use in radius of 5km around the station location from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) MCD12C1 version 6, using the International Geosphere-Biosphere Programme (IGBP) classification.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;grasslands&#x27;, &#x27;water bodies&#x27;, &#x27;water bodies&#x27;, ...,\n",
       "       &#x27;urban and built-up lands&#x27;, &#x27;grasslands&#x27;, &#x27;mixed forests&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MODIS_MCD12C1_v6_modal_LAI_25km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-702cfee1-9387-4c20-97a7-66aaaea03609' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-702cfee1-9387-4c20-97a7-66aaaea03609' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc96b9a0-1764-44a2-acec-1fd108470e8c' class='xr-var-data-in' type='checkbox'><label for='data-cc96b9a0-1764-44a2-acec-1fd108470e8c' 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>standard_name :</span></dt><dd>MODIS MCD12C1 v6 LAI modal 25km</dd><dt><span>long_name :</span></dt><dd>MODIS MCD12C1 v6 modal Leaf Area Index in 25km radius</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Modal Leaf Area Index in radius of 25km around the station location from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) MCD12C1 version 6.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;grasslands&#x27;, &#x27;water bodies&#x27;, &#x27;water bodies&#x27;, ...,\n",
       "       &#x27;broadleaf croplands&#x27;, &#x27;grasslands&#x27;, &#x27;savannas&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MODIS_MCD12C1_v6_modal_LAI_5km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2e1be4fb-cf25-4f0e-a26c-fe1705f24f82' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2e1be4fb-cf25-4f0e-a26c-fe1705f24f82' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab559bf0-4ef3-41bc-a2e1-efd2a35ec257' class='xr-var-data-in' type='checkbox'><label for='data-ab559bf0-4ef3-41bc-a2e1-efd2a35ec257' 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>standard_name :</span></dt><dd>MODIS MCD12C1 v6 LAI modal 5km</dd><dt><span>long_name :</span></dt><dd>MODIS MCD12C1 v6 modal Leaf Area Index in 5km radius</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Modal Leaf Area Index in radius of 5km around the station location from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) MCD12C1 version 6.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;grasslands&#x27;, &#x27;water bodies&#x27;, &#x27;water bodies&#x27;, ...,\n",
       "       &#x27;urban and built-up lands&#x27;, &#x27;grasslands&#x27;, &#x27;savannas&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MODIS_MCD12C1_v6_modal_UMD_land_use_25km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-52577ade-2e8a-40b3-8cd5-a52987298c67' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52577ade-2e8a-40b3-8cd5-a52987298c67' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1c63253-2e1f-4de4-abf6-1570f1aa8ed7' class='xr-var-data-in' type='checkbox'><label for='data-c1c63253-2e1f-4de4-abf6-1570f1aa8ed7' 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>standard_name :</span></dt><dd>MODIS MCD12C1 v6 UMD modal land use 25km</dd><dt><span>long_name :</span></dt><dd>MODIS MCD12C1 v6 UMD modal land use in 25km radius</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Modal land use in radius of 25km around the station location from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) MCD12C1 version 6, using the University of Maryland (UMD) classification.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;grasslands&#x27;, &#x27;water bodies&#x27;, &#x27;water bodies&#x27;, ..., &#x27;croplands&#x27;,\n",
       "       &#x27;grasslands&#x27;, &#x27;mixed forests&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MODIS_MCD12C1_v6_modal_UMD_land_use_5km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f589280a-48a3-46cf-adf1-bd5c75cbaf26' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f589280a-48a3-46cf-adf1-bd5c75cbaf26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5501e632-647b-49aa-b58f-21a4b4fde1a1' class='xr-var-data-in' type='checkbox'><label for='data-5501e632-647b-49aa-b58f-21a4b4fde1a1' 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>standard_name :</span></dt><dd>MODIS MCD12C1 v6 UMD modal land use 5km</dd><dt><span>long_name :</span></dt><dd>MODIS MCD12C1 v6 UMD modal land use in 5km radius</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Modal land use in radius of 5km around the station location from the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Climate Modeling Grid (CMG) MCD12C1 version 6, using the University of Maryland (UMD) classification.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;grasslands&#x27;, &#x27;water bodies&#x27;, &#x27;water bodies&#x27;, ...,\n",
       "       &#x27;urban and built-up lands&#x27;, &#x27;grasslands&#x27;, &#x27;mixed forests&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NOAA-DMSP-OLS_v4_average_nighttime_stable_lights_25km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a4446252-b340-4161-ab99-c58c38e97fda' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a4446252-b340-4161-ab99-c58c38e97fda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19cf3ca9-fa1d-4952-9540-c18d6c03d502' class='xr-var-data-in' type='checkbox'><label for='data-19cf3ca9-fa1d-4952-9540-c18d6c03d502' 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>standard_name :</span></dt><dd>NOAA-DMSP-OLS v4 average nighttime stable lights 25km</dd><dt><span>long_name :</span></dt><dd>NOAA DMSP-OLS version 4 average nighttime stable lights in 25km radius</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>National Oceanic and Atmospheric Administration (NOAA), Defense Meteorological Satellite Program - Operational Linescane System (DMSP-OLS) version 4 average nighttime stable lights in 25km radius of measurement station. The values represent a brightness index ranging from 0 to 63. The sensor saturates at a value of 63.</dd></dl></div><div class='xr-var-data'><pre>array([ 6.,  0., 17., ..., 24.,  1., 33.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NOAA-DMSP-OLS_v4_average_nighttime_stable_lights_5km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d50a776b-08da-4885-a0ee-0e177c23c83e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d50a776b-08da-4885-a0ee-0e177c23c83e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77c84d5e-0cc5-4bca-be77-f954c335313c' class='xr-var-data-in' type='checkbox'><label for='data-77c84d5e-0cc5-4bca-be77-f954c335313c' 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>standard_name :</span></dt><dd>NOAA-DMSP-OLS v4 average nighttime stable lights 5km</dd><dt><span>long_name :</span></dt><dd>NOAA DMSP-OLS version 4 average nighttime stable lights in 5km radius</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>National Oceanic and Atmospheric Administration (NOAA), Defense Meteorological Satellite Program - Operational Linescane System (DMSP-OLS) version 4 average nighttime stable lights in 5km radius of measurement station. The values represent a brightness index ranging from 0 to 63. The sensor saturates at a value of 63.</dd></dl></div><div class='xr-var-data'><pre>array([ 6.,  6., 37., ..., 61., 13., 34.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NOAA-DMSP-OLS_v4_max_nighttime_stable_lights_25km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-079192e1-2562-4d1e-9f4d-a7c69cdf869d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-079192e1-2562-4d1e-9f4d-a7c69cdf869d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7db49aa-7359-474c-bd9a-a65de6c6d880' class='xr-var-data-in' type='checkbox'><label for='data-b7db49aa-7359-474c-bd9a-a65de6c6d880' 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>standard_name :</span></dt><dd>NOAA-DMSP-OLS v4 max nighttime stable lights 25km</dd><dt><span>long_name :</span></dt><dd>NOAA DMSP-OLS version 4 maximum nighttime stable lights in 25km radius</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>National Oceanic and Atmospheric Administration (NOAA), Defense Meteorological Satellite Program - Operational Linescane System (DMSP-OLS) version 4 maximum nighttime stable lights in 25km radius of measurement station. The values represent a brightness index ranging from 0 to 63. The sensor saturates at a value of 63.</dd></dl></div><div class='xr-var-data'><pre>array([63., 16., 63., ..., 63., 56., 61.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NOAA-DMSP-OLS_v4_max_nighttime_stable_lights_5km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-aae93c6e-bd94-46a6-9b50-8c339777c817' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aae93c6e-bd94-46a6-9b50-8c339777c817' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c84c855e-12e2-4b33-9f59-1bfbc5a7d20e' class='xr-var-data-in' type='checkbox'><label for='data-c84c855e-12e2-4b33-9f59-1bfbc5a7d20e' 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>standard_name :</span></dt><dd>NOAA-DMSP-OLS v4 max nighttime stable lights 5km</dd><dt><span>long_name :</span></dt><dd>NOAA DMSP-OLS version 4 maximum nighttime stable lights in 5km radius</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>National Oceanic and Atmospheric Administration (NOAA), Defense Meteorological Satellite Program - Operational Linescane System (DMSP-OLS) version 4 maximum nighttime stable lights in 5km radius of measurement station. The values represent a brightness index ranging from 0 to 63. The sensor saturates at a value of 63.</dd></dl></div><div class='xr-var-data'><pre>array([26., 16., 60., ..., 63., 56., 56.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>NOAA-DMSP-OLS_v4_nighttime_stable_lights</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0164e13a-b3a3-4613-ac66-0e47de692d6e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0164e13a-b3a3-4613-ac66-0e47de692d6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-504de6b4-e836-455b-bd6b-58a8d8bb3218' class='xr-var-data-in' type='checkbox'><label for='data-504de6b4-e836-455b-bd6b-58a8d8bb3218' 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>standard_name :</span></dt><dd>NOAA-DMSP-OLS v4 nighttime stable lights</dd><dt><span>long_name :</span></dt><dd>NOAA DMSP-OLS version 4 nighttime stable lights</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>National Oceanic and Atmospheric Administration (NOAA), Defense Meteorological Satellite Program - Operational Linescane System (DMSP-OLS) version 4 nighttime stable lights. Native resolution of 0.0083 x 0.0083 degrees. The values represent a brightness index ranging from 0 to 63. The sensor saturates at a value of 63.</dd></dl></div><div class='xr-var-data'><pre>array([ 5., 11., 54., ..., 63.,  9., 28.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OMI_level3_column_annual_average_NO2</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-233e17bd-1810-45cb-8978-096855259fd1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-233e17bd-1810-45cb-8978-096855259fd1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5beadfa7-0ff4-4bb0-8d45-8eb1406b5917' class='xr-var-data-in' type='checkbox'><label for='data-5beadfa7-0ff4-4bb0-8d45-8eb1406b5917' 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>standard_name :</span></dt><dd>OMI level3 column annual average NO2</dd><dt><span>long_name :</span></dt><dd>OMI level3 column annual average nitrogen dioxide</dd><dt><span>units :</span></dt><dd>xx cm-2</dd><dt><span>description :</span></dt><dd>AURA Ozone monitoring instrument (OMI) level3 column annual average NO2, in molecules per squared centimetres. Native resolution of 0.25 x 0.25 degrees.</dd></dl></div><div class='xr-var-data'><pre>array([6.301160e+15, 3.021980e+15, 3.681956e+15, ..., 4.460874e+15,\n",
       "       2.814616e+15, 9.600188e+15], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OMI_level3_column_cloud_screened_annual_average_NO2</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-92296c37-3651-47fc-8e91-5cabd48aea6f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-92296c37-3651-47fc-8e91-5cabd48aea6f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c82182b7-fb7b-4181-b865-ede627fe6b6f' class='xr-var-data-in' type='checkbox'><label for='data-c82182b7-fb7b-4181-b865-ede627fe6b6f' 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>standard_name :</span></dt><dd>OMI level3 column cloud screened annual average NO2</dd><dt><span>long_name :</span></dt><dd>OMI level3 column cloud screened annual average nitrogen dioxide</dd><dt><span>units :</span></dt><dd>xx cm-2</dd><dt><span>description :</span></dt><dd>AURA Ozone monitoring instrument (OMI) level3 column cloud screened (where cloud fraction is less than 30 percent) annual average NO2, in molecules per squared centimetres. Native resolution of 0.25 x 0.25 degrees.</dd></dl></div><div class='xr-var-data'><pre>array([6.354764e+15, 3.141651e+15, 3.933728e+15, ..., 4.377470e+15,\n",
       "       2.837691e+15, 7.143090e+15], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OMI_level3_tropospheric_column_annual_average_NO2</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a3ce92a1-d092-4941-94af-21e518aebb9d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3ce92a1-d092-4941-94af-21e518aebb9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29befe96-dbd0-40dc-ae79-bb27ce396f1a' class='xr-var-data-in' type='checkbox'><label for='data-29befe96-dbd0-40dc-ae79-bb27ce396f1a' 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>standard_name :</span></dt><dd>OMI level3 tropospheric column annual average NO2</dd><dt><span>long_name :</span></dt><dd>OMI level3 tropospheric column annual average nitrogen dioxide</dd><dt><span>units :</span></dt><dd>xx cm-2</dd><dt><span>description :</span></dt><dd>AURA Ozone monitoring instrument (OMI) level3 tropospheric column annual average NO2, in molecules per squared centimetres. Native resolution of 0.25 x 0.25 degrees.</dd></dl></div><div class='xr-var-data'><pre>array([3.723849e+15, 4.691550e+14, 3.824027e+14, ..., 1.833370e+15,\n",
       "       6.993819e+14, 7.325085e+15], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>OMI_level3_tropospheric_column_cloud_screened_annual_average_NO2</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b16d2283-a58f-4d71-ac19-e8d5a1a6d28e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b16d2283-a58f-4d71-ac19-e8d5a1a6d28e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-417deb83-d7e4-4191-9e8b-0d6828e6806f' class='xr-var-data-in' type='checkbox'><label for='data-417deb83-d7e4-4191-9e8b-0d6828e6806f' 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>standard_name :</span></dt><dd>OMI level3 tropospheric column cloud screened annual average NO2</dd><dt><span>long_name :</span></dt><dd>OMI level3 tropospheric column cloud screened annual average nitrogen dioxide</dd><dt><span>units :</span></dt><dd>xx cm-2</dd><dt><span>description :</span></dt><dd>AURA Ozone monitoring instrument (OMI) level3 tropospheric column cloud screened (where cloud fraction is less than 30 percent) annual average NO2, in molecules per squared centimetres. Native resolution of 0.25 x 0.25 degrees.</dd></dl></div><div class='xr-var-data'><pre>array([3.713093e+15, 5.222752e+14, 5.292174e+14, ..., 1.688689e+15,\n",
       "       7.069353e+14, 4.294799e+15], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>UMBC_anthrome_classification</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4b8d3c99-4df3-4da1-bfd2-6819bdf64e45' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b8d3c99-4df3-4da1-bfd2-6819bdf64e45' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95e563bd-4150-4ca7-b68d-9d1a99157237' class='xr-var-data-in' type='checkbox'><label for='data-95e563bd-4150-4ca7-b68d-9d1a99157237' 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>standard_name :</span></dt><dd>UMBC anthrome classification</dd><dt><span>long_name :</span></dt><dd>UMBC anthrome classification</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>University of Maryland Baltimore County (UMBC) anthrome classification, describing the anthropogenic land use (for the year 2000). There are 20 distinct classifications. Native resolution of 0.0833 x 0.0833 degrees. A correction for costal sites is made: if the native anthrome class is &quot;water&quot;, then the modal classification of the neighbouring grid boxes is used instead (lowest code kept preferentially in case of a tie). If the site is truly an &quot;ocean&quot; site, all the surrounding gridcells will be water also, and therefore the class will be maintained as &quot;water&quot;.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;residential rangelands&#x27;, &#x27;water&#x27;, &#x27;wild treeless and barren lands&#x27;,\n",
       "       ..., &#x27;urban&#x27;, &#x27;urban&#x27;, &#x27;pastoral villages&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>UMBC_modal_anthrome_classification_25km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d3e063fe-f385-4130-a634-a7a75bad8399' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3e063fe-f385-4130-a634-a7a75bad8399' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8bb230d-2f13-4e2c-b4ff-0459310d7cef' class='xr-var-data-in' type='checkbox'><label for='data-a8bb230d-2f13-4e2c-b4ff-0459310d7cef' 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>standard_name :</span></dt><dd>UMBC modal anthrome classification 25km</dd><dt><span>long_name :</span></dt><dd>UMBC modal anthrome classification in 25km radius</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>University of Maryland Baltimore County (UMBC) modal anthrome classification in radius of 25km around station location.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;residential rangelands&#x27;, &#x27;water&#x27;, &#x27;water&#x27;, ..., &#x27;populated croplands&#x27;,\n",
       "       &#x27;residential rainfed croplands&#x27;, &#x27;residential rangelands&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>UMBC_modal_anthrome_classification_5km</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e253d62b-5cd6-4f0c-a3be-12b125285e18' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e253d62b-5cd6-4f0c-a3be-12b125285e18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ea9ed7a-8be5-47c0-8f5f-c2fc0123adb2' class='xr-var-data-in' type='checkbox'><label for='data-0ea9ed7a-8be5-47c0-8f5f-c2fc0123adb2' 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>standard_name :</span></dt><dd>UMBC modal anthrome classification 5km</dd><dt><span>long_name :</span></dt><dd>UMBC modal anthrome classification in 5km radius</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>University of Maryland Baltimore County (UMBC) modal anthrome classification in radius of 5km around station location.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;residential rangelands&#x27;, &#x27;water&#x27;, &#x27;wild treeless and barren lands&#x27;,\n",
       "       ..., &#x27;urban&#x27;, &#x27;urban&#x27;, &#x27;pastoral villages&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WMO_region</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-36047d69-5a0d-42eb-bb36-3e2fdd22a858' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36047d69-5a0d-42eb-bb36-3e2fdd22a858' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f0e65f4-a58c-42d5-8c5d-0262dda0bdcb' class='xr-var-data-in' type='checkbox'><label for='data-8f0e65f4-a58c-42d5-8c5d-0262dda0bdcb' 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>standard_name :</span></dt><dd>WMO region</dd><dt><span>long_name :</span></dt><dd>WMO region code</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>World Meteorological Organization (WMO) region of station. The available regions are: Africa, Asia, South America, &quot;Northern America, Central America and the Caribbean&quot;, South-West Pacific, Europe and Antarctica.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Asia&#x27;, &#x27;Europe&#x27;, &#x27;North America, Central America And The Caribbean&#x27;,\n",
       "       ..., &#x27;Europe&#x27;, &#x27;Africa&#x27;, &#x27;Europe&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WWF_TEOW_biogeographical_realm</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-79f52a6f-0278-4cb3-897d-25b39f8b60b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79f52a6f-0278-4cb3-897d-25b39f8b60b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c624f51-b99d-4d6d-bba1-472caa616719' class='xr-var-data-in' type='checkbox'><label for='data-3c624f51-b99d-4d6d-bba1-472caa616719' 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>standard_name :</span></dt><dd>WWF TEOW biogeographical realm</dd><dt><span>long_name :</span></dt><dd>WWF TEOW biogeographical realm</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Terrestrial Ecoregions of the World (TEOW) World Wildlife Foundation (WWF) classification. There are 8 biogeographical realms. See citation: Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D., Powell, G. V. N., Underwood, E. C., DAmico, J. A., Itoua, I., Strand, H. E., Morrison, J. C., Loucks, C. J., Allnutt, T. F., Ricketts, T. H., Kura, Y., Lamoreux, J. F., Wettengel, W. W., Hedao, P., Kassem, K. R. 2001. Terrestrial ecoregions of the world: a new map of life on Earth. Bioscience 51(11):933-938.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;palearctic&#x27;, &#x27;palearctic&#x27;, &#x27;nearctic&#x27;, ..., &#x27;palearctic&#x27;,\n",
       "       &#x27;afrotropics&#x27;, &#x27;palearctic&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WWF_TEOW_biome</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bb34a0b9-935f-4cc4-8248-efdbf5f22cbb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb34a0b9-935f-4cc4-8248-efdbf5f22cbb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-259f2ae5-d076-4908-801f-0f91811a5ca3' class='xr-var-data-in' type='checkbox'><label for='data-259f2ae5-d076-4908-801f-0f91811a5ca3' 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>standard_name :</span></dt><dd>WWF TEOW biome</dd><dt><span>long_name :</span></dt><dd>WWF TEOW biome</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Terrestrial Ecoregions of the World (TEOW) World Wildlife Foundation (WWF) classification. There are 14 biomes. See citation: Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D., Powell, G. V. N., Underwood, E. C., DAmico, J. A., Itoua, I., Strand, H. E., Morrison, J. C., Loucks, C. J., Allnutt, T. F., Ricketts, T. H., Kura, Y., Lamoreux, J. F., Wettengel, W. W., Hedao, P., Kassem, K. R. 2001. Terrestrial ecoregions of the world: a new map of life on Earth. Bioscience 51(11):933-938.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;temperate grasslands, savannas and shrublands&#x27;,\n",
       "       &#x27;temperate broadleaf and mixed forests&#x27;, &#x27;tundra&#x27;, ...,\n",
       "       &#x27;mediterranean forests, woodlands and scrub&#x27;,\n",
       "       &#x27;tropical and subtropical grasslands, savannas and shrublands&#x27;,\n",
       "       &#x27;temperate broadleaf and mixed forests&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WWF_TEOW_terrestrial_ecoregion</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-beba8ba4-82d3-4680-81ab-75811a786a7e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-beba8ba4-82d3-4680-81ab-75811a786a7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7dbf7d23-9ff6-4f04-91f8-ac3ff331f120' class='xr-var-data-in' type='checkbox'><label for='data-7dbf7d23-9ff6-4f04-91f8-ac3ff331f120' 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>standard_name :</span></dt><dd>WWF TEOW terrestrial ecoregion</dd><dt><span>long_name :</span></dt><dd>WWF TEOW terrestrial ecoregion</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Terrestrial Ecoregions of the World (TEOW) World Wildlife Foundation (WWF) classification. There are 825 terrestrial ecoregions. Ecoregions are relatively large units of land containing distinct assemblages of natural communities and species, with boundaries that approximate the original extent of natural communities prior to major land-use change. See citation: Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D., Powell, G. V. N., Underwood, E. C., DAmico, J. A., Itoua, I., Strand, H. E., Morrison, J. C., Loucks, C. J., Allnutt, T. F., Ricketts, T. H., Kura, Y., Lamoreux, J. F., Wettengel, W. W., Hedao, P., Kassem, K. R. 2001. Terrestrial ecoregions of the world: a new map of life on Earth. Bioscience 51(11):933-938.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;mongolian-manchurian grassland&#x27;, &#x27;azores temperate mixed forests&#x27;,\n",
       "       &#x27;arctic coastal tundra&#x27;, ...,\n",
       "       &#x27;iberian sclerophyllous and semi-deciduous forests&#x27;,\n",
       "       &#x27;west sudanian savanna&#x27;, &#x27;sarmatic mixed forests&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>administrative_country_division_1</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f3d20241-b5e9-4ac0-8859-6276e29ab9c5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f3d20241-b5e9-4ac0-8859-6276e29ab9c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b35fe006-efa8-40c4-ab5e-18588669d4b1' class='xr-var-data-in' type='checkbox'><label for='data-b35fe006-efa8-40c4-ab5e-18588669d4b1' 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>standard_name :</span></dt><dd>administrative country division 1</dd><dt><span>long_name :</span></dt><dd>administrative country division 1</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Name of the first (i.e. largest) country administrative division in which the station lies, e.g. countries within soverign state, state, province, county etc. These are defined for the purposes of managing of land and the affairs of people. This is automatically generated using Reverse Geocoder Python package (taking longitude and latitude as inputs).</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Inner Mongolia&#x27;, &#x27;Azores&#x27;, &#x27;Alaska&#x27;, ..., &#x27;Aragon&#x27;, &#x27;Zinder&#x27;,\n",
       "       &#x27;Moskovskaya&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>administrative_country_division_2</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-30460472-e54e-44ce-b087-47fc91f4cb74' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30460472-e54e-44ce-b087-47fc91f4cb74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25dad745-90ef-49c0-9793-4839cb7b40ca' class='xr-var-data-in' type='checkbox'><label for='data-25dad745-90ef-49c0-9793-4839cb7b40ca' 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>standard_name :</span></dt><dd>administrative country division 2</dd><dt><span>long_name :</span></dt><dd>administrative country division 2</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Name of the second (i.e. second largest) country administrative division in which the station lies, e.g. countries within soverign state, state, province, county etc. These are defined for the purposes of managing of land and the affairs of people. This is automatically generated using Reverse Geocoder Python package (taking longitude and latitude as inputs).</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;Santa Cruz Da Graciosa&#x27;, &#x27;North Slope Borough&#x27;, ...,\n",
       "       &#x27;Provincia De Zaragoza&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>altitude</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f84ee8f5-3128-4359-a3a3-95096b650fa3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f84ee8f5-3128-4359-a3a3-95096b650fa3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d2cf11f-aca0-4ae3-bb1c-77d861b6a0d0' class='xr-var-data-in' type='checkbox'><label for='data-9d2cf11f-aca0-4ae3-bb1c-77d861b6a0d0' 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>standard_name :</span></dt><dd>altitude</dd><dt><span>long_name :</span></dt><dd>altitude relative to mean sea level</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>description :</span></dt><dd>Altitude of the ground level at the station, relative to the stated vertical datum, in metres.</dd></dl></div><div class='xr-var-data'><pre>array([1314. ,   15.2,    2. , ...,  250. ,  456. ,  200. ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>annual_native_max_gap_percent</span></div><div class='xr-var-dims'>(station, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ac129433-b0cc-42f7-9a28-4f906e980ddf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac129433-b0cc-42f7-9a28-4f906e980ddf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2bb121e-6a19-4580-9199-43912069e013' class='xr-var-data-in' type='checkbox'><label for='data-e2bb121e-6a19-4580-9199-43912069e013' 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>standard_name :</span></dt><dd>annual native max gap percent</dd><dt><span>long_name :</span></dt><dd>annual native max gap percent</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>description :</span></dt><dd>Percentage of the maximum data gap in the annual averaged measurement UTC window filled by native resolution data, relative to the total window length.</dd></dl></div><div class='xr-var-data'><pre>[263520 values with dtype=uint8]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>annual_native_representativity_percent</span></div><div class='xr-var-dims'>(station, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1ab1525b-0356-4a48-adbe-cdeeb9f86dbb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ab1525b-0356-4a48-adbe-cdeeb9f86dbb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7bbaa80-3523-4ede-ab54-583b01f6b783' class='xr-var-data-in' type='checkbox'><label for='data-c7bbaa80-3523-4ede-ab54-583b01f6b783' 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>standard_name :</span></dt><dd>annual native representativity percent</dd><dt><span>long_name :</span></dt><dd>annual native representativity percent</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>description :</span></dt><dd>Percentage of the annual averaged measurement UTC window represented by native resolution data.</dd></dl></div><div class='xr-var-data'><pre>[263520 values with dtype=uint8]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area_classification</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ac967fcb-668d-49a2-9669-80e108f5054c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac967fcb-668d-49a2-9669-80e108f5054c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5dea1ff4-8373-4525-b45b-cd0e992c4691' class='xr-var-data-in' type='checkbox'><label for='data-5dea1ff4-8373-4525-b45b-cd0e992c4691' 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>standard_name :</span></dt><dd>area classification</dd><dt><span>long_name :</span></dt><dd>standardised network provided area classification</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Standardised network provided classification, describing type of area a measurement station is situated in.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>associated_networks</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c3aefb17-5bce-46a5-b3a9-c334dc57e31e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c3aefb17-5bce-46a5-b3a9-c334dc57e31e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7cd2107-9e87-4ee1-8464-6b297ef59441' class='xr-var-data-in' type='checkbox'><label for='data-e7cd2107-9e87-4ee1-8464-6b297ef59441' 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>standard_name :</span></dt><dd>other associated networks</dd><dt><span>long_name :</span></dt><dd>other associated networks</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>String pair of associated network name and station reference. Format: network1:station_reference1;network2:station_reference2</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>city</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cfddc6e8-4582-475f-b32b-b95e4daa071e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cfddc6e8-4582-475f-b32b-b95e4daa071e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eaa562d7-03c4-44ba-85e7-a463df2581be' class='xr-var-data-in' type='checkbox'><label for='data-eaa562d7-03c4-44ba-85e7-a463df2581be' 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>standard_name :</span></dt><dd>city</dd><dt><span>long_name :</span></dt><dd>city</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Name of the city the station is located in.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Baliang&#x27;, &#x27;Lagoa&#x27;, &#x27;Nuiqsut&#x27;, ..., &#x27;Zaragoza&#x27;, &#x27;Zinder&#x27;, &#x27;Karinskoye&#x27;],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>climatology</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-71ac59a7-a385-412d-989f-93cc9c4cfb73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-71ac59a7-a385-412d-989f-93cc9c4cfb73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66884964-dd1f-40e7-b0a5-4cde9942522a' class='xr-var-data-in' type='checkbox'><label for='data-66884964-dd1f-40e7-b0a5-4cde9942522a' 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>standard_name :</span></dt><dd>climatology</dd><dt><span>long_name :</span></dt><dd>climatology</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Name of the climatology of which the observations pertain to.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>contact_email_address</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-11221ec5-ea5b-4123-a7b8-7c2868a32a6f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11221ec5-ea5b-4123-a7b8-7c2868a32a6f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c926933-d6c3-4935-a1ca-512a37b62cd6' class='xr-var-data-in' type='checkbox'><label for='data-0c926933-d6c3-4935-a1ca-512a37b62cd6' 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>standard_name :</span></dt><dd>contact email address</dd><dt><span>long_name :</span></dt><dd>contact email address</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Email address of the principal data contact for the specific reported data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Brent.N.Holben@nasa.gov&#x27;, &#x27;Brent.N.Holben@nasa.gov&#x27;,\n",
       "       &#x27;Brent.N.Holben@nasa.gov&#x27;, ..., &#x27;Brent.N.Holben@nasa.gov&#x27;,\n",
       "       &#x27;Brent.N.Holben@nasa.gov&#x27;, &#x27;Brent.N.Holben@nasa.gov&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>contact_institution</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7979c18b-56f2-4ca0-a405-c584a57dc332' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7979c18b-56f2-4ca0-a405-c584a57dc332' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e8a7c92-1f39-4aec-ab11-2e3378d4c920' class='xr-var-data-in' type='checkbox'><label for='data-0e8a7c92-1f39-4aec-ab11-2e3378d4c920' 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>standard_name :</span></dt><dd>contact institution</dd><dt><span>long_name :</span></dt><dd>contact institution</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Institution of the principal data contact for the specific reported data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;NASA&#x27;, &#x27;NASA&#x27;, &#x27;NASA&#x27;, ..., &#x27;NASA&#x27;, &#x27;NASA&#x27;, &#x27;NASA&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>contact_name</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e392590d-e6bf-47c7-b9f2-215a6dcfc291' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e392590d-e6bf-47c7-b9f2-215a6dcfc291' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dae99c93-1afa-4b1e-b3b7-d1e4181959d2' class='xr-var-data-in' type='checkbox'><label for='data-dae99c93-1afa-4b1e-b3b7-d1e4181959d2' 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>standard_name :</span></dt><dd>contact name</dd><dt><span>long_name :</span></dt><dd>contact name</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Full name of the principal data contact for the specific reported data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Brent Holben&#x27;, &#x27;Brent Holben&#x27;, &#x27;Brent Holben&#x27;, ..., &#x27;Brent Holben&#x27;,\n",
       "       &#x27;Brent Holben&#x27;, &#x27;Brent Holben&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>country</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7b781899-fe55-4236-80f4-c5fd929518b6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b781899-fe55-4236-80f4-c5fd929518b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c15ea25b-7511-4a43-9c7a-254958ae88b1' class='xr-var-data-in' type='checkbox'><label for='data-c15ea25b-7511-4a43-9c7a-254958ae88b1' 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>standard_name :</span></dt><dd>country</dd><dt><span>long_name :</span></dt><dd>country</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Name of the country the station is located in.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;China&#x27;, &#x27;Portugal&#x27;, &#x27;United States&#x27;, ..., &#x27;Spain&#x27;, &#x27;Niger&#x27;, &#x27;Russia&#x27;],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>daily_native_max_gap_percent</span></div><div class='xr-var-dims'>(station, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1e0b3a68-9835-43fb-aeb7-287f554f9a33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e0b3a68-9835-43fb-aeb7-287f554f9a33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ba60500-0524-4a25-856c-5c0f8775ecc9' class='xr-var-data-in' type='checkbox'><label for='data-5ba60500-0524-4a25-856c-5c0f8775ecc9' 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>standard_name :</span></dt><dd>daily native max gap percent</dd><dt><span>long_name :</span></dt><dd>daily native max gap percent</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>description :</span></dt><dd>Percentage of the maximum data gap in the daily averaged measurement UTC window filled by native resolution data, relative to the total window length.</dd></dl></div><div class='xr-var-data'><pre>[263520 values with dtype=uint8]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>daily_native_representativity_percent</span></div><div class='xr-var-dims'>(station, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7d292adb-9e84-4564-af15-34842eb6e9a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d292adb-9e84-4564-af15-34842eb6e9a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3e6e057-4b3d-4d49-b544-6371b9154c51' class='xr-var-data-in' type='checkbox'><label for='data-e3e6e057-4b3d-4d49-b544-6371b9154c51' 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>standard_name :</span></dt><dd>daily native representativity percent</dd><dt><span>long_name :</span></dt><dd>daily native representativity percent</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>description :</span></dt><dd>Percentage of the daily averaged measurement UTC window represented by native resolution data.</dd></dl></div><div class='xr-var-data'><pre>[263520 values with dtype=uint8]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>daily_passing_vehicles</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1e8400d4-2013-4a57-9661-ad2f2f9c559e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e8400d4-2013-4a57-9661-ad2f2f9c559e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-569eceac-5bfc-4161-b44d-c740c7d4cd84' class='xr-var-data-in' type='checkbox'><label for='data-569eceac-5bfc-4161-b44d-c740c7d4cd84' 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>standard_name :</span></dt><dd>daily passing vehicles</dd><dt><span>long_name :</span></dt><dd>average daily number of passing vehicles</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Average number of vehicles passing daily.</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data_level</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d9d62c9f-bd6a-44bb-8649-af2c14fd65b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d9d62c9f-bd6a-44bb-8649-af2c14fd65b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0570e597-7abd-449d-8240-799d32015139' class='xr-var-data-in' type='checkbox'><label for='data-0570e597-7abd-449d-8240-799d32015139' 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>standard_name :</span></dt><dd>data level</dd><dt><span>long_name :</span></dt><dd>data level</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Data level of data reported. This varies per network. If data level is variable per measurement, and not static per reported file, then this is set as &quot;variable&quot;. If there is no reported data level this is set as &quot;none&quot;</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1.5&#x27;, &#x27;1.5&#x27;, &#x27;1.5&#x27;, ..., &#x27;1.5&#x27;, &#x27;1.5&#x27;, &#x27;1.5&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>data_licence</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0e3530c5-7430-4acf-834e-f9726b141797' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0e3530c5-7430-4acf-834e-f9726b141797' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adfa0006-dd9f-4940-a729-86753fe28625' class='xr-var-data-in' type='checkbox'><label for='data-adfa0006-dd9f-4940-a729-86753fe28625' 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>standard_name :</span></dt><dd>data licence</dd><dt><span>long_name :</span></dt><dd>data licence</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Information pertaining to the data licence governing the redistribution/publication of the ingested network data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Public domain: https://aeronet.gsfc.nasa.gov/new_web/data_usage.html&#x27;,\n",
       "       &#x27;Public domain: https://aeronet.gsfc.nasa.gov/new_web/data_usage.html&#x27;,\n",
       "       &#x27;Public domain: https://aeronet.gsfc.nasa.gov/new_web/data_usage.html&#x27;,\n",
       "       ...,\n",
       "       &#x27;Public domain: https://aeronet.gsfc.nasa.gov/new_web/data_usage.html&#x27;,\n",
       "       &#x27;Public domain: https://aeronet.gsfc.nasa.gov/new_web/data_usage.html&#x27;,\n",
       "       &#x27;Public domain: https://aeronet.gsfc.nasa.gov/new_web/data_usage.html&#x27;],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>day_night_code</span></div><div class='xr-var-dims'>(station, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b5d4e0d1-9921-4233-841d-e3396b70eaaf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b5d4e0d1-9921-4233-841d-e3396b70eaaf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-934e7f2f-9437-4c9d-a90e-abef1afdf35c' class='xr-var-data-in' type='checkbox'><label for='data-934e7f2f-9437-4c9d-a90e-abef1afdf35c' 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>standard_name :</span></dt><dd>day/night code</dd><dt><span>long_name :</span></dt><dd>day/night code per measurement</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Binary indication if measurement was made during the day or night. Day=0, Night=1. The classification is made by calculating the solar elevation angle for a latitude/longitude/measurement height at a mid-measurement window timestamp. If the solar elevation angle is &gt; 0, it is classed as daytime, otherwise it is nightime. Classification is 255 if cannot be made.</dd></dl></div><div class='xr-var-data'><pre>[263520 values with dtype=uint8]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>daytime_traffic_speed</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f28e8901-e96c-45fc-958d-14e80fd7a1d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f28e8901-e96c-45fc-958d-14e80fd7a1d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-903f0a3e-4cb0-4be4-a9ec-54c01a289227' class='xr-var-data-in' type='checkbox'><label for='data-903f0a3e-4cb0-4be4-a9ec-54c01a289227' 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>standard_name :</span></dt><dd>daytime traffic speed</dd><dt><span>long_name :</span></dt><dd>average daytime speed of passing traffic</dd><dt><span>units :</span></dt><dd>km hr-1</dd><dt><span>description :</span></dt><dd>Average daytime speed of the passing traffic where measurements are being made (if applicable), in kilometres per hour.</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>derived_uncertainty_per_measurement</span></div><div class='xr-var-dims'>(station, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e388cb13-78a3-4f09-a99b-240be46b8e82' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e388cb13-78a3-4f09-a99b-240be46b8e82' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3749b4d6-c0df-4e2f-ae1c-df31ddd6d995' class='xr-var-data-in' type='checkbox'><label for='data-3749b4d6-c0df-4e2f-ae1c-df31ddd6d995' 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>standard_name :</span></dt><dd>derived measurement uncertainty per measurement</dd><dt><span>long_name :</span></dt><dd>derived measurement uncertainty per measurement</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Derived measurement uncertainty (±) of methodology, for a specific measurement. This is calculated through the quadratic addition of reported (or if not available, documented) accuracy and precision metrics. This is given in absolute terms in unitless.</dd></dl></div><div class='xr-var-data'><pre>[263520 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>distance_to_building</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-25715e97-7368-41c1-a0b7-882a924f672a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25715e97-7368-41c1-a0b7-882a924f672a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf29f29e-3076-4f4e-b4e0-110424e67b73' class='xr-var-data-in' type='checkbox'><label for='data-cf29f29e-3076-4f4e-b4e0-110424e67b73' 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>standard_name :</span></dt><dd>distance to building</dd><dt><span>long_name :</span></dt><dd>distance to the nearest building</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>description :</span></dt><dd>Distance to the nearest building of the inlet/instrument/sampler, in metres.</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>distance_to_junction</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7d74289f-6b43-45f2-b078-e10ffcd66287' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d74289f-6b43-45f2-b078-e10ffcd66287' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5d25722-55fe-40bc-afeb-8b4e342ef066' class='xr-var-data-in' type='checkbox'><label for='data-f5d25722-55fe-40bc-afeb-8b4e342ef066' 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>standard_name :</span></dt><dd>distance to junction</dd><dt><span>long_name :</span></dt><dd>distance to the nearest road junction</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>description :</span></dt><dd>Distance to the nearest road junction of the inlet/instrument/sampler, in metres.</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>distance_to_kerb</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d8b724dc-bd56-44a7-8131-8e5f3134e83f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d8b724dc-bd56-44a7-8131-8e5f3134e83f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7874f97-7fb5-46f3-931a-4ad4424e269d' class='xr-var-data-in' type='checkbox'><label for='data-e7874f97-7fb5-46f3-931a-4ad4424e269d' 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>standard_name :</span></dt><dd>distance to kerb</dd><dt><span>long_name :</span></dt><dd>distance to the street kerb</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>description :</span></dt><dd>Distance to the street kerb of the inlet/instrument/sampler, in metres.</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>distance_to_source</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6c7ac979-faae-4c2e-8433-efbecd692810' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c7ac979-faae-4c2e-8433-efbecd692810' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-119f6690-bc51-4382-accd-fcbeb13093c2' class='xr-var-data-in' type='checkbox'><label for='data-119f6690-bc51-4382-accd-fcbeb13093c2' 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>standard_name :</span></dt><dd>distance to source</dd><dt><span>long_name :</span></dt><dd>distance to the main emission source</dd><dt><span>units :</span></dt><dd>km</dd><dt><span>description :</span></dt><dd>Distance to the main emission source (see variable: &quot;main_emission_source&quot;) of the inlet/instrument/sampler, in kilometres.</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ellipsoid</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b31fc229-f05b-4757-a46f-cdfde064a9f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b31fc229-f05b-4757-a46f-cdfde064a9f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa0e8fc3-5cf2-438f-86ce-5b111e86bdb5' class='xr-var-data-in' type='checkbox'><label for='data-fa0e8fc3-5cf2-438f-86ce-5b111e86bdb5' 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>standard_name :</span></dt><dd>ellipsoid</dd><dt><span>long_name :</span></dt><dd>ellipsoid</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>The ellipsoidal model of the earth used as a basis for 2D and 3D geographic coordinate systems.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WGS 84&#x27;, &#x27;WGS 84&#x27;, &#x27;WGS 84&#x27;, ..., &#x27;WGS 84&#x27;, &#x27;WGS 84&#x27;, &#x27;WGS 84&#x27;],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>flag</span></div><div class='xr-var-dims'>(station, time, N_flag_codes)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2cdb86cb-9667-4081-847c-3e64aa301d04' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2cdb86cb-9667-4081-847c-3e64aa301d04' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98d9f392-9452-455e-855a-46f91c811251' class='xr-var-data-in' type='checkbox'><label for='data-98d9f392-9452-455e-855a-46f91c811251' 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>standard_name :</span></dt><dd>flags</dd><dt><span>long_name :</span></dt><dd>data reporter provided standardised flags</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>List of associated data flag codes per measurement, indicating the data quality of a specific measurement, provided by the data reporter. Fill value code of 255.</dd></dl></div><div class='xr-var-data'><pre>[50068800 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>horizontal_datum</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-09a8f86f-6ccf-47b9-ab73-daa5af35e869' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-09a8f86f-6ccf-47b9-ab73-daa5af35e869' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df3f8242-bdc7-4a9f-be84-1e2011cc384b' class='xr-var-data-in' type='checkbox'><label for='data-df3f8242-bdc7-4a9f-be84-1e2011cc384b' 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>standard_name :</span></dt><dd>horizontal datum</dd><dt><span>long_name :</span></dt><dd>horizontal datum</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Name of the horizontal datum used in defining geodetic latitudes and longitudes on the Earth&#x27;s surface. The datum is set when positioning an ellipsoid model of the Earth to an anchor point. If not explicitely stated then this is assumed to be &#x27;World Geodetic System 1984&#x27;.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WORLD GEODETIC SYSTEM 1984&#x27;, &#x27;WORLD GEODETIC SYSTEM 1984&#x27;,\n",
       "       &#x27;WORLD GEODETIC SYSTEM 1984&#x27;, ..., &#x27;WORLD GEODETIC SYSTEM 1984&#x27;,\n",
       "       &#x27;WORLD GEODETIC SYSTEM 1984&#x27;, &#x27;WORLD GEODETIC SYSTEM 1984&#x27;],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hourly_native_max_gap_percent</span></div><div class='xr-var-dims'>(station, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dd45b4cd-6a1b-49da-b8d0-acacd79fc8fd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd45b4cd-6a1b-49da-b8d0-acacd79fc8fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2545da6-8c80-45a4-b54f-01f5f6061184' class='xr-var-data-in' type='checkbox'><label for='data-f2545da6-8c80-45a4-b54f-01f5f6061184' 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>standard_name :</span></dt><dd>hourly native max gap percent</dd><dt><span>long_name :</span></dt><dd>hourly native max gap percent</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>description :</span></dt><dd>Percentage of the maximum data gap in the hourly averaged measurement UTC window filled by native resolution data, relative to the total window length.</dd></dl></div><div class='xr-var-data'><pre>[263520 values with dtype=uint8]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hourly_native_representativity_percent</span></div><div class='xr-var-dims'>(station, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a382d3d5-eb45-497b-8b9a-58f6a0076898' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a382d3d5-eb45-497b-8b9a-58f6a0076898' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9946466b-55a0-4401-934d-e69889286280' class='xr-var-data-in' type='checkbox'><label for='data-9946466b-55a0-4401-934d-e69889286280' 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>standard_name :</span></dt><dd>hourly native representativity percent</dd><dt><span>long_name :</span></dt><dd>hourly native representativity percent</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>description :</span></dt><dd>Percentage of the hourly averaged measurement UTC window represented by native resolution data.</dd></dl></div><div class='xr-var-data'><pre>[263520 values with dtype=uint8]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>land_use</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-18860352-2630-4675-81c1-1e140eb86312' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18860352-2630-4675-81c1-1e140eb86312' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-130e278f-603e-49c7-a31a-59646f03ad1e' class='xr-var-data-in' type='checkbox'><label for='data-130e278f-603e-49c7-a31a-59646f03ad1e' 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>standard_name :</span></dt><dd>land use</dd><dt><span>long_name :</span></dt><dd>standardised network provided land use type</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Standardised network provided classification, describing the dominant land use in the area of the reporting station.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-754b8355-45ab-4232-9d24-b38bfb824e20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-754b8355-45ab-4232-9d24-b38bfb824e20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e157952-38ca-466c-8391-b2a41c0cddf9' class='xr-var-data-in' type='checkbox'><label for='data-8e157952-38ca-466c-8391-b2a41c0cddf9' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>decimal degrees North</dd><dt><span>description :</span></dt><dd>Geodetic latitude of measuring instrument, in decimal degrees North, following the stated horizontal datum.</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([40.8517  , 39.09109 , 70.4995  , ..., 41.6334  , 13.776683, 55.695   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>local_time</span></div><div class='xr-var-dims'>(station, time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1e0de103-5a67-4c61-b19c-430da9c705d3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e0de103-5a67-4c61-b19c-430da9c705d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72c29fc2-4347-4d26-ab3d-362e27760878' class='xr-var-data-in' type='checkbox'><label for='data-72c29fc2-4347-4d26-ab3d-362e27760878' 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>standard_name :</span></dt><dd>local time</dd><dt><span>long_name :</span></dt><dd>local time</dd><dt><span>description :</span></dt><dd>Time in minutes since 0001-01-01 00:00 local time. Time given refers to the start of the time window the measurement is representative of (temporal resolution).</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>tz :</span></dt><dd>local</dd></dl></div><div class='xr-var-data'><pre>[263520 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f13e2000-d72d-46b5-9b24-0edd11dba3de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f13e2000-d72d-46b5-9b24-0edd11dba3de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-68dceba4-7f60-41a6-9683-c45de3165a50' class='xr-var-data-in' type='checkbox'><label for='data-68dceba4-7f60-41a6-9683-c45de3165a50' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>decimal degrees East</dd><dt><span>description :</span></dt><dd>Geodetic longitude of measuring instrument, in decimal degrees East, following the stated horizontal datum.</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 109.6288  ,  -28.02917 , -149.88    , ...,   -0.88235 ,    8.990233,\n",
       "         36.775   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>main_emission_source</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0d9921fd-ce0f-4474-899f-db73d7f1f6b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d9921fd-ce0f-4474-899f-db73d7f1f6b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5137bd2-9e75-4621-9323-d6e98b88a78c' class='xr-var-data-in' type='checkbox'><label for='data-d5137bd2-9e75-4621-9323-d6e98b88a78c' 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>standard_name :</span></dt><dd>main emission source</dd><dt><span>long_name :</span></dt><dd>standardised network provided main emission source</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Standardised network provided classification, describing the main emission source influencing air measured at a station.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mean_solar_time</span></div><div class='xr-var-dims'>(station, time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3e02a39d-4736-4040-a7be-61452662effc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e02a39d-4736-4040-a7be-61452662effc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0001a742-22cb-4c7d-934e-64fa335cb276' class='xr-var-data-in' type='checkbox'><label for='data-0001a742-22cb-4c7d-934e-64fa335cb276' 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>standard_name :</span></dt><dd>mean solar time</dd><dt><span>long_name :</span></dt><dd>mean solar time</dd><dt><span>description :</span></dt><dd>Time in minutes since 0001-01-01 00:00 mean solar time. Time given refers to the start of the time window the measurement is representative of (temporal resolution).</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>tz :</span></dt><dd>mean solar</dd></dl></div><div class='xr-var-data'><pre>[263520 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measurement_altitude</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-70ca13f8-3acf-49e3-add0-b85cb0f36f68' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-70ca13f8-3acf-49e3-add0-b85cb0f36f68' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cac7f936-d7d3-4c7a-be7f-5580871551f2' class='xr-var-data-in' type='checkbox'><label for='data-cac7f936-d7d3-4c7a-be7f-5580871551f2' 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>standard_name :</span></dt><dd>measurement altitude</dd><dt><span>long_name :</span></dt><dd>measurement altitude relative to mean sea level</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>description :</span></dt><dd>Altitude of the inlet/instrument/sampler, relative to the stated vertical datum, in metres.</dd></dl></div><div class='xr-var-data'><pre>array([1314. ,   15.2,    2. , ...,  250. ,  456. ,  200. ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measurement_methodology</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1e297c92-dec6-42c8-a3c3-31fd776d65bb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e297c92-dec6-42c8-a3c3-31fd776d65bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93d4f780-8af2-447a-83ad-3bbd40fbd00b' class='xr-var-data-in' type='checkbox'><label for='data-93d4f780-8af2-447a-83ad-3bbd40fbd00b' 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>standard_name :</span></dt><dd>measurement methodology</dd><dt><span>long_name :</span></dt><dd>standardised measurement methodology</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Standardised name of the measurement methodology.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;photometry - direct&#x27;, &#x27;photometry - direct&#x27;, &#x27;photometry - direct&#x27;,\n",
       "       ..., &#x27;photometry - direct&#x27;, &#x27;photometry - direct&#x27;,\n",
       "       &#x27;photometry - direct&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measurement_scale</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ca31d330-985f-419c-a8ca-51caa6599a95' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca31d330-985f-419c-a8ca-51caa6599a95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17c5b7ff-8070-458b-a2c9-055a0578028f' class='xr-var-data-in' type='checkbox'><label for='data-17c5b7ff-8070-458b-a2c9-055a0578028f' 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>standard_name :</span></dt><dd>measurement scale</dd><dt><span>long_name :</span></dt><dd>standardised network provided measurement scale</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Standardised network provided classification, a denotation of the geographic scope of the air quality measurements made.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_calibration_scale</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ad00d914-104a-4cb0-9961-79b88d160ba4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad00d914-104a-4cb0-9961-79b88d160ba4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-882ea3c2-1c73-4420-8fe6-450edd600a04' class='xr-var-data-in' type='checkbox'><label for='data-882ea3c2-1c73-4420-8fe6-450edd600a04' 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>standard_name :</span></dt><dd>measuring instrument calibration scale</dd><dt><span>long_name :</span></dt><dd>measuring instrument calibration scale name</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Name of calibration scale used for the calibration of the measuring instrument.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_documented_absorption_cross_section</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c0bc5e25-15d1-4430-94e6-2073014ddca2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c0bc5e25-15d1-4430-94e6-2073014ddca2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6dd769dc-2a37-4004-9144-d441fc5c2ee4' class='xr-var-data-in' type='checkbox'><label for='data-6dd769dc-2a37-4004-9144-d441fc5c2ee4' 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>standard_name :</span></dt><dd>measuring instrument documented absorption cross section</dd><dt><span>long_name :</span></dt><dd>measuring instrument documented absorption cross section</dd><dt><span>units :</span></dt><dd>cm2</dd><dt><span>description :</span></dt><dd>Assumed molecule cross-section for parameter being measured (in cm2/molecule), as given in instrumental manual/documentation. This field is only used for parameters being measured using optical methods, where a molecule cross section is assumed for processing the measurement values. Physically it is the effective area of the molecule that photon needs to traverse in order to be absorbed. The larger the absorption cross section, the easier it is to photoexcite the molecule. Can be a range: e.g. 1e-15-1.5e-15.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_documented_accuracy</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-020b355e-20de-4f0e-9ae0-39abfe6827f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-020b355e-20de-4f0e-9ae0-39abfe6827f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-939288f1-3029-4522-9bc9-59a1334e144e' class='xr-var-data-in' type='checkbox'><label for='data-939288f1-3029-4522-9bc9-59a1334e144e' 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>standard_name :</span></dt><dd>measuring instrument documented measurement accuracy</dd><dt><span>long_name :</span></dt><dd>measuring instrument documented measurement accuracy</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Measurement accuracy (±), as given in the instrumental manual/documentation. Accuracy describes the difference between the measurement and the actual value of the part that is measured. It includes: Bias (a measure of the difference between the true value and the observed value of a part -- If the “true” value is unknown, it can be calculated by averaging several measurements with the most accurate measuring equipment available) and Linearity (a measure of how the size of the part affects the bias of a measurement system -- It is the difference in the observed bias values through the expected range of measurement). This can be given as in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%); or a percentage quantity after a fixed limit (i.e. 0.5%&gt;=50).</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_documented_flow_rate</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-10eaa0a7-73f6-43e7-89f6-b527792e7c36' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-10eaa0a7-73f6-43e7-89f6-b527792e7c36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adce0003-d183-4a86-8569-8cfd28f32a98' class='xr-var-data-in' type='checkbox'><label for='data-adce0003-d183-4a86-8569-8cfd28f32a98' 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>standard_name :</span></dt><dd>measuring instrument documented flow rate</dd><dt><span>long_name :</span></dt><dd>measuring instrument documented flow rate</dd><dt><span>units :</span></dt><dd>l min-1</dd><dt><span>description :</span></dt><dd>Volume (litres) of fluid which passes to the measuring instrument, per unit time (minutes), as given in instrumental manual/documentation. Can be a range: e.g. 1.0-3.0.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_documented_lower_limit_of_detection</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2452b8c0-c06c-42f7-a5e7-690843b4a1cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2452b8c0-c06c-42f7-a5e7-690843b4a1cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8bfbafd-a865-40b1-b3c9-934f9c69f80e' class='xr-var-data-in' type='checkbox'><label for='data-c8bfbafd-a865-40b1-b3c9-934f9c69f80e' 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>standard_name :</span></dt><dd>measuring instrument documented lower limit of detection</dd><dt><span>long_name :</span></dt><dd>measuring instrument documented lower limit of detection</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Lower limit of detection of measurement methodology, as given in the instrumental manual/documentation.</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_documented_measurement_resolution</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b135c315-e11b-42b8-be9d-a825c772975a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b135c315-e11b-42b8-be9d-a825c772975a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-525d7fbd-2535-4a70-a002-89aa16bc849b' class='xr-var-data-in' type='checkbox'><label for='data-525d7fbd-2535-4a70-a002-89aa16bc849b' 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>standard_name :</span></dt><dd>measuring instrument documented measurement resolution</dd><dt><span>long_name :</span></dt><dd>measuring instrument documented measurement resolution</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Measurement resolution, as given in instrumental manual/documentation. The measurement resolution is defined as the smallest change or increment in the measured quantity that the instrument can detect. However it is often reported inconsistently, often being simply the number of digits an instrument can display, which does not relate to the actual physical resolution of the instrument.</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_documented_precision</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c88da717-7a8c-47ac-b235-0b59a500e443' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c88da717-7a8c-47ac-b235-0b59a500e443' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3e62f9a-37b6-46bf-b81d-0e3256117073' class='xr-var-data-in' type='checkbox'><label for='data-e3e62f9a-37b6-46bf-b81d-0e3256117073' 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>standard_name :</span></dt><dd>measuring instrument documented measurement precision</dd><dt><span>long_name :</span></dt><dd>measuring instrument documented measurement precision</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Measurement precision (±), as given in instrumental manual/documentation. Precision describes the variation you see when you measure the same part repeatedly with the same device. It includes the following two types of variation: Repeatability (variation due to the measuring device -- it is the variation observed when the same operator measures the same part repeatedly with the same device) and Reproducibility (variation due to the operators and the interaction between operator and part -- It is the variation of the bias observed when different operators measure the same parts using the same device). This can be given as in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%); or a percentage quantity after a fixed limit (i.e. 0.5%&gt;=50).</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;0.1%&#x27;, &#x27;0.1%&#x27;, &#x27;0.1%&#x27;, ..., &#x27;0.1%&#x27;, &#x27;0.1%&#x27;, &#x27;0.1%&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_documented_span_drift</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4004acfb-c0b0-49ba-85ac-113383340adc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4004acfb-c0b0-49ba-85ac-113383340adc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82f72a3b-40ad-44f5-8730-06af84526a4c' class='xr-var-data-in' type='checkbox'><label for='data-82f72a3b-40ad-44f5-8730-06af84526a4c' 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>standard_name :</span></dt><dd>measuring instrument documented span drift</dd><dt><span>long_name :</span></dt><dd>measuring instrument documented span drift</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Span drift of measuring instrument per unit of time, as given in instrumental manual/documentation. Span drift (or sensitivity drift) refers to when there is proportional change in the indication of an instrument all along the upward scale, hence higher calibrations end up being shifted more than lower calibrations. It is reported as the maximum possible drift per unit of time in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%/day); or a percentage quantity after a fixed limit (i.e. 0.5%&gt;=50/day).</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_documented_uncertainty</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-88dcf3de-d34d-461f-954d-368548ba8a36' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88dcf3de-d34d-461f-954d-368548ba8a36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1256c0c-27cf-42d7-9ab7-15663e9bc314' class='xr-var-data-in' type='checkbox'><label for='data-c1256c0c-27cf-42d7-9ab7-15663e9bc314' 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>standard_name :</span></dt><dd>measuring instrument documented measurement uncertainty</dd><dt><span>long_name :</span></dt><dd>measuring instrument documented measurement uncertainty</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Measurement uncertainty (±), as given in the instrumental manual/documentation. In principal this refers to the inherent uncertainty on every measurement as a function of the quadratic addition of the accuracy and precision metrics (at the same confidence interval), but is often reported incosistently e.g. being solely determined from random errors (i.e. just the measuremental precision). This can be given in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%); or a percentage quantity after a fixed limit (i.e. 0.5%&gt;=50).</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_documented_upper_limit_of_detection</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4aa0c361-e59e-47d7-976b-afbd71e6215d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4aa0c361-e59e-47d7-976b-afbd71e6215d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb5f3491-bd88-4574-bab8-caeb33e4932f' class='xr-var-data-in' type='checkbox'><label for='data-cb5f3491-bd88-4574-bab8-caeb33e4932f' 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>standard_name :</span></dt><dd>measuring instrument documented upper limit of detection</dd><dt><span>long_name :</span></dt><dd>measuring instrument documented upper limit of detection</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Upper limit of detection of measurement methodology, as given in the instrumental manual/documentation.</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_documented_zero_drift</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ce8b476b-badf-4aeb-8445-e2be662e2e99' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce8b476b-badf-4aeb-8445-e2be662e2e99' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-552cd8be-5469-4252-9dc3-d2804fc578a2' class='xr-var-data-in' type='checkbox'><label for='data-552cd8be-5469-4252-9dc3-d2804fc578a2' 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>standard_name :</span></dt><dd>measuring instrument documented zero drift</dd><dt><span>long_name :</span></dt><dd>measuring instrument documented zero drift</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Zero drift of measuring instrument per unit of time, as given in instrumental manual/documentation. Zero drift (or baseline drift) refers to the shifting of the whole calibration by the same amount caused by slippage or due to undue warming up of the electronic circuits. It is reported as the maximum possible drift per unit of time in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%/day); or a percentage quantity after a fixed limit (i.e. 0.5%&gt;=50/day).</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_documented_zonal_drift</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b4d807aa-837f-4125-8f38-59b73beb7035' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b4d807aa-837f-4125-8f38-59b73beb7035' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17ddba94-2245-4fbc-9220-62f479752d63' class='xr-var-data-in' type='checkbox'><label for='data-17ddba94-2245-4fbc-9220-62f479752d63' 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>standard_name :</span></dt><dd>measuring instrument documented zonal drift</dd><dt><span>long_name :</span></dt><dd>measuring instrument documented zonal drift</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Zonal drift of measuring instrument per unit of time, as given in instrumental manual/documentation. Zonal drift refers to when drift occurs only over a portion of the full scale or span of an instrument, while the remaining portion of the scale remains unaffected. It is reported as the maximum possible drift per unit of time in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%/day); or a percentage quantity after a fixed limit (i.e. 0.5%&gt;=50/day).</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_further_details</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0aa8863c-7c25-4619-991a-d858c43511c6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0aa8863c-7c25-4619-991a-d858c43511c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2fac3a17-f651-44bd-8bda-df52a5be47a6' class='xr-var-data-in' type='checkbox'><label for='data-2fac3a17-f651-44bd-8bda-df52a5be47a6' 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>standard_name :</span></dt><dd>measuring instrument further details</dd><dt><span>long_name :</span></dt><dd>measuring instrument further details</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Further associated details regarding the specifics of the measurement methodology/instrument.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_inlet_information</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7865f866-422b-459d-9ca6-7cb76fe96265' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7865f866-422b-459d-9ca6-7cb76fe96265' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f963e21-ea6d-4b0d-bcee-7acd976c0f4e' class='xr-var-data-in' type='checkbox'><label for='data-0f963e21-ea6d-4b0d-bcee-7acd976c0f4e' 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>standard_name :</span></dt><dd>measuring instrument inlet information</dd><dt><span>long_name :</span></dt><dd>measuring instrument measurement inlet information</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Description of sampling inlet of the measuring instrument.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_manual_name</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5c72d380-bed8-4357-96bb-cfb6cc3a1c7a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c72d380-bed8-4357-96bb-cfb6cc3a1c7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0628431f-b8f8-49ea-b726-0be2af0863a4' class='xr-var-data-in' type='checkbox'><label for='data-0628431f-b8f8-49ea-b726-0be2af0863a4' 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>standard_name :</span></dt><dd>measuring instrument manual name</dd><dt><span>long_name :</span></dt><dd>measuring instrument manual name</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Path to the location in the esarchive of the manual for the specific measuring instrument.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Cimel_CE318T_Manual.pdf&#x27;, &#x27;Cimel_CE318T_Manual.pdf&#x27;,\n",
       "       &#x27;Cimel_CE318T_Manual.pdf&#x27;, ..., &#x27;Cimel_CE318T_Manual.pdf&#x27;,\n",
       "       &#x27;Cimel_CE318T_Manual.pdf&#x27;, &#x27;Cimel_CE318T_Manual.pdf&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_name</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d5713526-d243-428c-8074-38345b5f7517' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d5713526-d243-428c-8074-38345b5f7517' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bcbecfa8-6371-4135-8a99-7bf35af8a491' class='xr-var-data-in' type='checkbox'><label for='data-bcbecfa8-6371-4135-8a99-7bf35af8a491' 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>standard_name :</span></dt><dd>measuring instrument name</dd><dt><span>long_name :</span></dt><dd>standardised measuring instrument name</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Standardised name of the measuring instrument.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Cimel CE318-T&#x27;, &#x27;Cimel CE318-T&#x27;, &#x27;Cimel CE318-T&#x27;, ..., &#x27;Cimel CE318-T&#x27;,\n",
       "       &#x27;Cimel CE318-T&#x27;, &#x27;Cimel CE318-T&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_process_details</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c3675874-e405-41f0-b0a3-91ad91316180' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c3675874-e405-41f0-b0a3-91ad91316180' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2794489d-4787-498a-bdd7-22a356735234' class='xr-var-data-in' type='checkbox'><label for='data-2794489d-4787-498a-bdd7-22a356735234' 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>standard_name :</span></dt><dd>measuring instrument process details</dd><dt><span>long_name :</span></dt><dd>measuring instrument process details</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Miscellaneous details regarding assumptions made in the standardisation of the measurement methodology/instrument.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_reported_absorption_cross_section</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ab52d60c-b33e-4f2c-8d7d-dcc593d47f56' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ab52d60c-b33e-4f2c-8d7d-dcc593d47f56' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07efdf60-e6a0-4d36-81b6-c258dc087037' class='xr-var-data-in' type='checkbox'><label for='data-07efdf60-e6a0-4d36-81b6-c258dc087037' 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>standard_name :</span></dt><dd>measuring instrument reported absorption cross section</dd><dt><span>long_name :</span></dt><dd>measuring instrument reported absorption cross section</dd><dt><span>units :</span></dt><dd>cm2</dd><dt><span>description :</span></dt><dd>Assumed molecule cross-section for parameter being measured (in cm2/molecule), as given in metadata. This field is only used for parameters being measured using optical methods, where a molecule cross section is assumed for processing the measurement values. Physically it is the effective area of the molecule that photon needs to traverse in order to be absorbed. The larger the absorption cross section, the easier it is to photoexcite the molecule. Can be a range: e.g. 1e-15-1.5e-15.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_reported_accuracy</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9b09f7d7-7c4c-4ba0-832d-87d087608fea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b09f7d7-7c4c-4ba0-832d-87d087608fea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a78dd1ad-46ca-43a9-a52b-e079de6ee56a' class='xr-var-data-in' type='checkbox'><label for='data-a78dd1ad-46ca-43a9-a52b-e079de6ee56a' 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>standard_name :</span></dt><dd>measuring instrument reported measurement accuracy</dd><dt><span>long_name :</span></dt><dd>measuring instrument reported measurement accuracy</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Measurement accuracy (±), as given in metadata. Accuracy describes the difference between the measurement and the actual value of the part that is measured. It includes: Bias (a measure of the difference between the true value and the observed value of a part -- If the “true” value is unknown, it can be calculated by averaging several measurements with the most accurate measuring equipment available) and Linearity (a measure of how the size of the part affects the bias of a measurement system -- It is the difference in the observed bias values through the expected range of measurement). This can be given as in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%); or a percentage quantity after a fixed limit (i.e. 0.5%&gt;=50).</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_reported_flow_rate</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1d63dc28-4906-4b5f-9594-d6906b156c30' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1d63dc28-4906-4b5f-9594-d6906b156c30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5edf73e5-607a-4682-bdab-c298f61e51f1' class='xr-var-data-in' type='checkbox'><label for='data-5edf73e5-607a-4682-bdab-c298f61e51f1' 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>standard_name :</span></dt><dd>measuring instrument reported flow rate</dd><dt><span>long_name :</span></dt><dd>measuring instrument reported flow rate</dd><dt><span>units :</span></dt><dd>l min-1</dd><dt><span>description :</span></dt><dd>Volume (litres) of fluid which passes to the measuring instrument, per unit time (minutes), as given in metadata. Can be a range: e.g. 1.0-3.0.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_reported_lower_limit_of_detection</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e40ed552-8e48-4e9a-a47d-ef9ff9b0a8a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e40ed552-8e48-4e9a-a47d-ef9ff9b0a8a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b0a603a-a84c-417e-a939-9c0b1ec1d53c' class='xr-var-data-in' type='checkbox'><label for='data-5b0a603a-a84c-417e-a939-9c0b1ec1d53c' 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>standard_name :</span></dt><dd>measuring instrument reported lower limit of detection</dd><dt><span>long_name :</span></dt><dd>measuring instrument reported lower limit of detection</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Lower limit of detection of measurement methodology, as given in metadata.</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_reported_measurement_resolution</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1ffe440e-a8d7-4105-9c12-f1498ee3f3a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ffe440e-a8d7-4105-9c12-f1498ee3f3a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b57fb8a-334a-4f28-b4ca-81ddfac62799' class='xr-var-data-in' type='checkbox'><label for='data-9b57fb8a-334a-4f28-b4ca-81ddfac62799' 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>standard_name :</span></dt><dd>measuring instrument reported measurement resolution</dd><dt><span>long_name :</span></dt><dd>measuring instrument reported measurement resolution</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Measurement resolution, as given in metadata. The measurement resolution is defined as the smallest change or increment in the measured quantity that the instrument can detect. However it is often reported inconsistently, often being simply the number of digits an instrument can display, which does not relate to the actual physical resolution of the instrument.</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_reported_precision</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8e70ed20-9009-4f17-80a3-4d35105eed9a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e70ed20-9009-4f17-80a3-4d35105eed9a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65e695c1-47a2-4662-8287-5818fc89816a' class='xr-var-data-in' type='checkbox'><label for='data-65e695c1-47a2-4662-8287-5818fc89816a' 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>standard_name :</span></dt><dd>measuring instrument reported measurement precision</dd><dt><span>long_name :</span></dt><dd>measuring instrument reported measurement precision</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Measurement precision (±), as given in metadata. Precision describes the variation you see when you measure the same part repeatedly with the same device. It includes the following two types of variation: Repeatability (variation due to the measuring device -- it is the variation observed when the same operator measures the same part repeatedly with the same device) and Reproducibility (variation due to the operators and the interaction between operator and part -- It is the variation of the bias observed when different operators measure the same parts using the same device). This can be given as in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%); or a percentage quantity after a fixed limit (i.e. 0.5%&gt;=50).</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_reported_span_drift</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cbbdb85b-64d8-4aa1-ac9e-1597ee6b4225' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cbbdb85b-64d8-4aa1-ac9e-1597ee6b4225' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f91689f1-0fa0-4e6a-a6c9-51578486d6ed' class='xr-var-data-in' type='checkbox'><label for='data-f91689f1-0fa0-4e6a-a6c9-51578486d6ed' 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>standard_name :</span></dt><dd>measuring instrument reported span drift</dd><dt><span>long_name :</span></dt><dd>measuring instrument reported span drift</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Span drift of measuring instrument per unit of time, as given in metadata. Span drift (or sensitivity drift) refers to when there is proportional change in the indication of an instrument all along the upward scale, hence higher calibrations end up being shifted more than lower calibrations. It is reported as the maximum possible drift per unit of time in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%/day); or a percentage quantity after a fixed limit (i.e. 0.5%&gt;=50/day).</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_reported_uncertainty</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-943e6850-739b-48d7-9dcb-1cbebd172e32' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-943e6850-739b-48d7-9dcb-1cbebd172e32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8f96e25-d6e8-496d-a172-34ab7065d5a7' class='xr-var-data-in' type='checkbox'><label for='data-b8f96e25-d6e8-496d-a172-34ab7065d5a7' 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>standard_name :</span></dt><dd>measuring instrument reported measurement uncertainty</dd><dt><span>long_name :</span></dt><dd>measuring instrument reported measurement uncertainty</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Measurement uncertainty (±), as given in metadata. In principal this refers to the inherent uncertainty on every measurement as a function of the quadratic addition of the accuracy and precision metrics (at the same confidence interval), but is often reported incosistently e.g. being solely determined from random errors (i.e. just the measuremental precision). It can be given in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%); or a percentage quantity after a fixed limit (i.e. 0.5%&gt;=50).</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_reported_units</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-247d1040-198f-4713-b761-cba15fd74a41' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-247d1040-198f-4713-b761-cba15fd74a41' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8fab5a7d-4389-42cd-99a9-300ffaa62375' class='xr-var-data-in' type='checkbox'><label for='data-8fab5a7d-4389-42cd-99a9-300ffaa62375' 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>standard_name :</span></dt><dd>measuring instrument reported units</dd><dt><span>long_name :</span></dt><dd>measuring instrument reported measurement units</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Units that the measured parameter are natively reported in.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_reported_upper_limit_of_detection</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b228f91c-4065-41c7-abfd-090cd008ccd8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b228f91c-4065-41c7-abfd-090cd008ccd8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e7da8e2-8f6e-426c-a6d3-9e95f0603870' class='xr-var-data-in' type='checkbox'><label for='data-1e7da8e2-8f6e-426c-a6d3-9e95f0603870' 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>standard_name :</span></dt><dd>measuring instrument reported upper limit of detection</dd><dt><span>long_name :</span></dt><dd>measuring instrument reported upper limit of detection</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Upper limit of detection of measurement methodology, as given in metadata.</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_reported_zero_drift</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bea1f5cb-01bd-4787-b6f5-57bbad2c8616' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bea1f5cb-01bd-4787-b6f5-57bbad2c8616' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2c127ed-aca4-4fe4-a403-a3cd212a8764' class='xr-var-data-in' type='checkbox'><label for='data-a2c127ed-aca4-4fe4-a403-a3cd212a8764' 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>standard_name :</span></dt><dd>measuring instrument reported zero drift</dd><dt><span>long_name :</span></dt><dd>measuring instrument reported zero drift</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Zero drift of measuring instrument per unit of time, as given in metadata. Zero drift (or baseline drift) refers to the shifting of the whole calibration by the same amount caused by slippage or due to undue warming up of the electronic circuits. It is reported as the maximum possible drift per unit of time in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%/day); or a percentage quantity after a fixed limit (i.e. 0.5%&gt;=50/day).</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_reported_zonal_drift</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-31677176-dd92-4048-a131-a2cf97acf509' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31677176-dd92-4048-a131-a2cf97acf509' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-74898d9e-c603-4205-a9a9-720e6c8f73f0' class='xr-var-data-in' type='checkbox'><label for='data-74898d9e-c603-4205-a9a9-720e6c8f73f0' 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>standard_name :</span></dt><dd>measuring instrument reported zonal drift</dd><dt><span>long_name :</span></dt><dd>measuring instrument reported zonal drift</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Zonal drift of measuring instrument per unit of time, as given in metadata. Zonal drift refers to when drift occurs only over a portion of the full scale or span of an instrument, while the remaining portion of the scale remains unaffected. It is reported as the maximum possible drift per unit of time in absolute terms; as a percentage; the greater of either an absolute value or percentage (i.e. 25.0/0.5%/day); or a percentage quantity after a fixed limit (i.e. 0.5%&gt;=50/day).</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>measuring_instrument_sampling_type</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-37b46a70-04c1-4535-89f7-b3d8f58a64ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-37b46a70-04c1-4535-89f7-b3d8f58a64ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-76bf5455-2560-4e71-b4d2-308362cd7947' class='xr-var-data-in' type='checkbox'><label for='data-76bf5455-2560-4e71-b4d2-308362cd7947' 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>standard_name :</span></dt><dd>measuring instrument sampling type</dd><dt><span>long_name :</span></dt><dd>standardised sampling type of the measuring instrument</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Standardised name of the measuring instrument sampling type.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;remote&#x27;, &#x27;remote&#x27;, &#x27;remote&#x27;, ..., &#x27;remote&#x27;, &#x27;remote&#x27;, &#x27;remote&#x27;],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>monthly_native_max_gap_percent</span></div><div class='xr-var-dims'>(station, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3b30addd-d7e7-40d5-8ad9-246dbc2e60f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b30addd-d7e7-40d5-8ad9-246dbc2e60f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c59e4b0b-4d72-4f74-b545-11b82c49dd94' class='xr-var-data-in' type='checkbox'><label for='data-c59e4b0b-4d72-4f74-b545-11b82c49dd94' 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>standard_name :</span></dt><dd>monthly native max gap percent</dd><dt><span>long_name :</span></dt><dd>monthly native max gap percent</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>description :</span></dt><dd>Percentage of the maximum data gap in the monthly averaged measurement UTC window filled by native resolution data, relative to the total window length.</dd></dl></div><div class='xr-var-data'><pre>[263520 values with dtype=uint8]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>monthly_native_representativity_percent</span></div><div class='xr-var-dims'>(station, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-82e388ab-e233-4363-bfdd-4edb51822e87' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-82e388ab-e233-4363-bfdd-4edb51822e87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5d166a0-f00b-42ed-a6e1-a2109729c5ba' class='xr-var-data-in' type='checkbox'><label for='data-b5d166a0-f00b-42ed-a6e1-a2109729c5ba' 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>standard_name :</span></dt><dd>monthly native representativity percent</dd><dt><span>long_name :</span></dt><dd>monthly native representativity percent</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>description :</span></dt><dd>Percentage of the monthly averaged measurement UTC window represented by native resolution data.</dd></dl></div><div class='xr-var-data'><pre>[263520 values with dtype=uint8]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>network</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6d84f634-68ef-4f61-8aba-941abe520bb7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d84f634-68ef-4f61-8aba-941abe520bb7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3855e3d-2240-4b49-85bf-b61150b8e8a0' class='xr-var-data-in' type='checkbox'><label for='data-f3855e3d-2240-4b49-85bf-b61150b8e8a0' 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>standard_name :</span></dt><dd>network</dd><dt><span>long_name :</span></dt><dd>data network</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>The name of the network which reports data for the specific station in question.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;AERONET_v3_lev1.5&#x27;, &#x27;AERONET_v3_lev1.5&#x27;, &#x27;AERONET_v3_lev1.5&#x27;, ...,\n",
       "       &#x27;AERONET_v3_lev1.5&#x27;, &#x27;AERONET_v3_lev1.5&#x27;, &#x27;AERONET_v3_lev1.5&#x27;],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>network_maintenance_details</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-403fa7a0-ba92-43d6-a794-99aa33526b4f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-403fa7a0-ba92-43d6-a794-99aa33526b4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2729c6e1-2fc3-4650-8e83-6793288eb095' class='xr-var-data-in' type='checkbox'><label for='data-2729c6e1-2fc3-4650-8e83-6793288eb095' 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>standard_name :</span></dt><dd>network maintenance details</dd><dt><span>long_name :</span></dt><dd>network maintenance details</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Extra details provided by the reporting network about the operational maintenance done at the station.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>network_miscellaneous_details</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b8652522-cde3-47fe-8030-356ea5037d27' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b8652522-cde3-47fe-8030-356ea5037d27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b31ee11d-58d4-4c18-b7b4-336b3e391834' class='xr-var-data-in' type='checkbox'><label for='data-b31ee11d-58d4-4c18-b7b4-336b3e391834' 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>standard_name :</span></dt><dd>network miscellaneous details</dd><dt><span>long_name :</span></dt><dd>network miscellaneous details</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Extra miscellanous details provided by the reporting network.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>network_provided_volume_standard_pressure</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-df30e0f8-7ae2-4d46-aa4e-0dec4a450cfb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-df30e0f8-7ae2-4d46-aa4e-0dec4a450cfb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7bec1f7-0913-4486-9de4-62f498bfcbe4' class='xr-var-data-in' type='checkbox'><label for='data-e7bec1f7-0913-4486-9de4-62f498bfcbe4' 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>standard_name :</span></dt><dd>network provided volume standard pressure</dd><dt><span>long_name :</span></dt><dd>network provided volume standard pressure</dd><dt><span>units :</span></dt><dd>hPa</dd><dt><span>description :</span></dt><dd>The pressure (in hPa) associated with the volume of the sampled gas (which varies with temperature and pressure). This volume is typically normalised in-instrument to a standard temperature and pressure. These standard values typically follow network/continental/global standards (e.g. European Union) for the measured component. If no in-instrument normalisation is done then the reported pressure should be reported as the internal pressure of the instrument (i.e. the measurement conditions). If no numbers are reported explicitly per measurement, then the sample gas pressure is assumed to be the known network standard pressure for the measured component.</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>network_provided_volume_standard_temperature</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-242bdee7-5ce1-4eb3-a3ee-6615f5190dc4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-242bdee7-5ce1-4eb3-a3ee-6615f5190dc4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-889081c1-aeed-4990-ae6c-210a66e41c0a' class='xr-var-data-in' type='checkbox'><label for='data-889081c1-aeed-4990-ae6c-210a66e41c0a' 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>standard_name :</span></dt><dd>network provided volume standard temperature</dd><dt><span>long_name :</span></dt><dd>network provided volume standard temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>description :</span></dt><dd>The temperature (in Kelvin) associated with the volume of the sampled gas (which varies with temperature and pressure). This volume is typically normalised in-instrument to a standard temperature and pressure. These standard values typically follow network/continental/global standards (e.g. European Union) for the measured component. If no in-instrument normalisation is done then the reported temperature should be reported as the internal temperature of the instrument (i.e. the measurement conditions). If no numbers are reported explicitly per measurement, then the sample gas temperature is assumed to be the known network standard temperature for the measured component.</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>network_qa_details</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ca2d0ede-ed1b-459a-94c1-517e0033ac6c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca2d0ede-ed1b-459a-94c1-517e0033ac6c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dfb00ba2-4b8e-4c7b-a385-91670fd9bdc3' class='xr-var-data-in' type='checkbox'><label for='data-dfb00ba2-4b8e-4c7b-a385-91670fd9bdc3' 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>standard_name :</span></dt><dd>network qa details</dd><dt><span>long_name :</span></dt><dd>network qa details</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Extra details provided by the reporting network about the in-network quality assurance of measurements.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>network_sampling_details</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1fa198a8-8bd1-4ef0-9318-467ced2f80d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1fa198a8-8bd1-4ef0-9318-467ced2f80d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa806a79-924f-4e30-90a7-00818d0324c8' class='xr-var-data-in' type='checkbox'><label for='data-fa806a79-924f-4e30-90a7-00818d0324c8' 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>standard_name :</span></dt><dd>network sampling details</dd><dt><span>long_name :</span></dt><dd>network sampling details</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Extra details provided by the reporting network about the sampling methods employed.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>network_uncertainty_details</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-98a578f9-7e0e-4a71-9761-56906bf3d070' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98a578f9-7e0e-4a71-9761-56906bf3d070' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29109757-e7ae-4770-9185-705ecda369fc' class='xr-var-data-in' type='checkbox'><label for='data-29109757-e7ae-4770-9185-705ecda369fc' 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>standard_name :</span></dt><dd>network uncertainty details</dd><dt><span>long_name :</span></dt><dd>network uncertainty details</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Extra details provided by the reporting network about the uncertainties involved with the measurement methods employed.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>od550aero</span></div><div class='xr-var-dims'>(station, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ac3ef266-684c-4a91-87b5-7f1de5fdaab0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac3ef266-684c-4a91-87b5-7f1de5fdaab0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38b20dfd-0b07-454a-9d2c-af64c1b7a033' class='xr-var-data-in' type='checkbox'><label for='data-38b20dfd-0b07-454a-9d2c-af64c1b7a033' 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>standard_name :</span></dt><dd>aerosol optical depth at 550nm</dd><dt><span>long_name :</span></dt><dd>aerosol optical depth at 550nm</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Measured value of surface aerosol optical depth at 550nm for the stated temporal resolution.</dd></dl></div><div class='xr-var-data'><pre>[263520 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>population</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b596be4d-4e12-43d4-806f-de717b4f5833' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b596be4d-4e12-43d4-806f-de717b4f5833' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e62abd13-6f5f-4195-9409-cfe0b89ec1b4' class='xr-var-data-in' type='checkbox'><label for='data-e62abd13-6f5f-4195-9409-cfe0b89ec1b4' 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>standard_name :</span></dt><dd>population</dd><dt><span>long_name :</span></dt><dd>population</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Population size of the nearest urban settlement.</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>primary_sampling_further_details</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-007b5eda-f3ae-440d-b99a-4eb826e06617' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-007b5eda-f3ae-440d-b99a-4eb826e06617' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24dbea61-182b-496f-8b31-42f10c8e1ad4' class='xr-var-data-in' type='checkbox'><label for='data-24dbea61-182b-496f-8b31-42f10c8e1ad4' 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>standard_name :</span></dt><dd>primary sampling further details</dd><dt><span>long_name :</span></dt><dd>primary sampling further details</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Further associated details regarding the specifics of the primary sampling instrument/type.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>primary_sampling_instrument_documented_flow_rate</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-eaad3c45-4f23-496e-878d-2892c7433cf2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eaad3c45-4f23-496e-878d-2892c7433cf2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0c77051-db61-41fd-9e20-022bcf3e17ba' class='xr-var-data-in' type='checkbox'><label for='data-e0c77051-db61-41fd-9e20-022bcf3e17ba' 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>standard_name :</span></dt><dd>primary sampling instrument documented flow rate</dd><dt><span>long_name :</span></dt><dd>primary sampling instrument documented sampling flow rate</dd><dt><span>units :</span></dt><dd>l min-1</dd><dt><span>description :</span></dt><dd>Volume (litres) of fluid which passes to the primary sampling instrument, per unit time (minutes), as given in instrumental manual/documentation. Can be a range: e.g. 1.0-3.0.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>primary_sampling_instrument_manual_name</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fa5e36ae-4795-4007-89ad-f92ab3f24fbf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa5e36ae-4795-4007-89ad-f92ab3f24fbf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c6c6ae5-e3a2-41d4-bd6b-93d7cd55ff6a' class='xr-var-data-in' type='checkbox'><label for='data-7c6c6ae5-e3a2-41d4-bd6b-93d7cd55ff6a' 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>standard_name :</span></dt><dd>primary sampling instrument manual name</dd><dt><span>long_name :</span></dt><dd>primary sampling instrument manual name</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Path to the location in the esarchive of the manual for the specific primary sampling instrument.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>primary_sampling_instrument_name</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5c4821f1-029c-4e18-a6be-1c2619f87a83' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c4821f1-029c-4e18-a6be-1c2619f87a83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c7fb4eb-0643-4b54-8c71-90c34885fb4d' class='xr-var-data-in' type='checkbox'><label for='data-9c7fb4eb-0643-4b54-8c71-90c34885fb4d' 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>standard_name :</span></dt><dd>primary sampling instrument name</dd><dt><span>long_name :</span></dt><dd>standardised primary sampling instrument name</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Standardised name of the primary sampling instrument (if no specific instrument is used, or known, this is the standardised primary sampling type).</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>primary_sampling_instrument_reported_flow_rate</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-830ecbda-cba9-48aa-8a8f-2fb067ccff2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-830ecbda-cba9-48aa-8a8f-2fb067ccff2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96a43ce3-c00d-4ffe-ae39-7f0c972165dd' class='xr-var-data-in' type='checkbox'><label for='data-96a43ce3-c00d-4ffe-ae39-7f0c972165dd' 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>standard_name :</span></dt><dd>primary sampling instrument reported flow rate</dd><dt><span>long_name :</span></dt><dd>primary sampling instrument reported sampling flow rate</dd><dt><span>units :</span></dt><dd>l min-1</dd><dt><span>description :</span></dt><dd>Volume (litres) of fluid which passes to the primary sampling instrument, per unit time (minutes), as given in metadata. Can be a range: e.g. 1.0-3.0.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>primary_sampling_process_details</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3daf445f-5bd9-4546-a715-4ad052bd9bb8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3daf445f-5bd9-4546-a715-4ad052bd9bb8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3663e5c-6934-42df-9592-b4feea8edf02' class='xr-var-data-in' type='checkbox'><label for='data-f3663e5c-6934-42df-9592-b4feea8edf02' 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>standard_name :</span></dt><dd>primary sampling process details</dd><dt><span>long_name :</span></dt><dd>primary sampling process details</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Miscellaneous details regarding assumptions made in the standardisation of the primary sampling type/instrument.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>primary_sampling_type</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ae70e6a9-407d-43d6-bb10-7fd5c0c6887b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae70e6a9-407d-43d6-bb10-7fd5c0c6887b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7eca0263-2fa9-49c0-9709-882b3f1c64f6' class='xr-var-data-in' type='checkbox'><label for='data-7eca0263-2fa9-49c0-9709-882b3f1c64f6' 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>standard_name :</span></dt><dd>primary sampling type</dd><dt><span>long_name :</span></dt><dd>standardised primary sampling type</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Standardised primary sampling type.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>principal_investigator_email_address</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4f6d8816-95c3-4a96-b650-c1da13b479bc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f6d8816-95c3-4a96-b650-c1da13b479bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d62ea0e-37ad-45d9-8a2f-f4fdb89781cb' class='xr-var-data-in' type='checkbox'><label for='data-3d62ea0e-37ad-45d9-8a2f-f4fdb89781cb' 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>standard_name :</span></dt><dd>principal investigator email address</dd><dt><span>long_name :</span></dt><dd>principal investigator email address</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Email address of the principal scientific investigator for the specific reported data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Brent.N.Holben@nasa.gov&#x27;, &#x27;Brent.N.Holben@nasa.gov&#x27;,\n",
       "       &#x27;Brent.N.Holben@nasa.gov&#x27;, ..., &#x27;Brent.N.Holben@nasa.gov&#x27;,\n",
       "       &#x27;Brent.N.Holben@nasa.gov&#x27;, &#x27;Brent.N.Holben@nasa.gov&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>principal_investigator_institution</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b1794fb9-5e28-4e95-a3e2-92ad8c8e42df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b1794fb9-5e28-4e95-a3e2-92ad8c8e42df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb4543f9-ce13-416f-bab9-959d7d510a46' class='xr-var-data-in' type='checkbox'><label for='data-bb4543f9-ce13-416f-bab9-959d7d510a46' 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>standard_name :</span></dt><dd>principal investigator institution</dd><dt><span>long_name :</span></dt><dd>principal investigator institution</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Institution of the principal scientific investigator for the specific reported data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;NASA&#x27;, &#x27;NASA&#x27;, &#x27;NASA&#x27;, ..., &#x27;NASA&#x27;, &#x27;NASA&#x27;, &#x27;NASA&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>principal_investigator_name</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-93fd8011-3257-485e-b9ca-35b309e8928c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93fd8011-3257-485e-b9ca-35b309e8928c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e952cb71-a97b-4475-8577-912c95be36e9' class='xr-var-data-in' type='checkbox'><label for='data-e952cb71-a97b-4475-8577-912c95be36e9' 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>standard_name :</span></dt><dd>principal investigator name</dd><dt><span>long_name :</span></dt><dd>principal investigator name</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Full name of the principal scientific investigator for the specific reported data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Brent Holben&#x27;, &#x27;Brent Holben&#x27;, &#x27;Brent Holben&#x27;, ..., &#x27;Brent Holben&#x27;,\n",
       "       &#x27;Brent Holben&#x27;, &#x27;Brent Holben&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>process_warnings</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2221547f-d533-4f50-8efa-ba1babfb65c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2221547f-d533-4f50-8efa-ba1babfb65c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4b2ef37-6ba8-4d3a-a2f0-5fd50f359521' class='xr-var-data-in' type='checkbox'><label for='data-f4b2ef37-6ba8-4d3a-a2f0-5fd50f359521' 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>standard_name :</span></dt><dd>process warnings</dd><dt><span>long_name :</span></dt><dd>process warnings</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Warnings accumulated through GHOST processing regarding the data that should be considered.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, ..., &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>projection</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e5710933-00ac-489f-b31e-b09fc014c63d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5710933-00ac-489f-b31e-b09fc014c63d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a43ddfc6-e1bd-4c80-8c44-20311a4259d4' class='xr-var-data-in' type='checkbox'><label for='data-a43ddfc6-e1bd-4c80-8c44-20311a4259d4' 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>standard_name :</span></dt><dd>projection</dd><dt><span>long_name :</span></dt><dd>projection</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Name of the projected coordinate system of the original provided station position x, y coordinates. If the original coordinates are not projected, then this is set as &#x27;geographic&#x27;.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;GEOGRAPHIC&#x27;, &#x27;GEOGRAPHIC&#x27;, &#x27;GEOGRAPHIC&#x27;, ..., &#x27;GEOGRAPHIC&#x27;,\n",
       "       &#x27;GEOGRAPHIC&#x27;, &#x27;GEOGRAPHIC&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qa</span></div><div class='xr-var-dims'>(station, time, N_qa_codes)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-df64f2df-a695-4081-9aca-803121ef66b3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-df64f2df-a695-4081-9aca-803121ef66b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42e3fe95-63d9-4415-87a1-8dfe80439080' class='xr-var-data-in' type='checkbox'><label for='data-42e3fe95-63d9-4415-87a1-8dfe80439080' 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>standard_name :</span></dt><dd>qa</dd><dt><span>long_name :</span></dt><dd>qa standardised data flags</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>List of derived quality assurance flag codes per measurement, informing on the quality associated with each observation, determined by multiple scientific quality control/assurance checks. Fill value code of 255.</dd></dl></div><div class='xr-var-data'><pre>[20291040 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>reported_uncertainty_per_measurement</span></div><div class='xr-var-dims'>(station, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e4613ef2-4f0b-4f88-a853-14cf7547d588' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e4613ef2-4f0b-4f88-a853-14cf7547d588' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3710950a-8028-40df-b45c-e112632cb4dc' class='xr-var-data-in' type='checkbox'><label for='data-3710950a-8028-40df-b45c-e112632cb4dc' 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>standard_name :</span></dt><dd>reported measurement uncertainty per measurement</dd><dt><span>long_name :</span></dt><dd>reported measurement uncertainty per measurement</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Reported measurement uncertainty (±) of methodology, for a specific measurement. In principal this refers to the inherent uncertainty on every measurement as a function of the quadratic addition of the accuracy and precision metrics (at the same confidence interval), but is often reported incosistently e.g. being solely determined from random errors (i.e. just the measuremental precision). This is given in absolute terms in unitless.</dd></dl></div><div class='xr-var-data'><pre>[263520 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>representative_radius</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9823e079-5973-4187-8333-a3c1d758197b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9823e079-5973-4187-8333-a3c1d758197b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb307955-cc42-43e5-9d8c-162aab4e213d' class='xr-var-data-in' type='checkbox'><label for='data-bb307955-cc42-43e5-9d8c-162aab4e213d' 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>standard_name :</span></dt><dd>representative_radius</dd><dt><span>long_name :</span></dt><dd>representative_radius</dd><dt><span>units :</span></dt><dd>km</dd><dt><span>description :</span></dt><dd>Radius of representativity of the measurements made (i.e. for what distance scale around the sampling point would the measurements be very similar?), given in kilometres.  A quantitative version of the &quot;measurement_scale&quot; classification.</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>retrieval_algorithm</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6b1426c7-a156-48cc-a5d0-c97f9225170b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6b1426c7-a156-48cc-a5d0-c97f9225170b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e69c3a6e-9779-40d0-94c3-884db5b66291' class='xr-var-data-in' type='checkbox'><label for='data-e69c3a6e-9779-40d0-94c3-884db5b66291' 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>standard_name :</span></dt><dd>retrieval algorithm</dd><dt><span>long_name :</span></dt><dd>retrieval algorithm</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>The name of the retrieval algorithm. Remote sensing algorithms are used to retrieve the aerosol optical properties (as aerosol optical depths or single scattering albedo among others) using remote-sensing radiances for multiple wavelengths from ground stations or on satellite platforms. Each algorithm is particularly designed considering the characteristics of the sensor and other ancillary information.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;directsun algorithm&#x27;, &#x27;directsun algorithm&#x27;, &#x27;directsun algorithm&#x27;,\n",
       "       ..., &#x27;directsun algorithm&#x27;, &#x27;directsun algorithm&#x27;,\n",
       "       &#x27;directsun algorithm&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sample_preparation_further_details</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-70b4c5fa-3288-4a28-8d96-7599c1e94fee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-70b4c5fa-3288-4a28-8d96-7599c1e94fee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ece9ac06-c8c1-4883-8074-a808690dfc9a' class='xr-var-data-in' type='checkbox'><label for='data-ece9ac06-c8c1-4883-8074-a808690dfc9a' 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>standard_name :</span></dt><dd>sample preparation further details</dd><dt><span>long_name :</span></dt><dd>sample preparation further details</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Further associated details regarding the specifics of the sample preparation types/instruments. Multiple details specific to different types are separated by &quot;;&quot;.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sample_preparation_process_details</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c7b42a87-e432-41c4-833d-b5fafb9a799c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c7b42a87-e432-41c4-833d-b5fafb9a799c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2e61f0c-a80a-4218-b85c-cac60822d23a' class='xr-var-data-in' type='checkbox'><label for='data-e2e61f0c-a80a-4218-b85c-cac60822d23a' 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>standard_name :</span></dt><dd>sample preparation process details</dd><dt><span>long_name :</span></dt><dd>sample preparation process details</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Miscellaneous details regarding assumptions made in the standardisation of the sample preparation types/techniques. Multiple details specific to different types are separated by &quot;;&quot;.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sample_preparation_techniques</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-da7b04ec-e432-4563-a84a-30abd5268ffe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da7b04ec-e432-4563-a84a-30abd5268ffe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e1cbf9a-ea27-413b-9d92-b7929ce75128' class='xr-var-data-in' type='checkbox'><label for='data-8e1cbf9a-ea27-413b-9d92-b7929ce75128' 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>standard_name :</span></dt><dd>sample preparation techniques</dd><dt><span>long_name :</span></dt><dd>standardised specific preparation techniques</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Standardised sample preparation techniques utilised in the measurement process. Mutiple names are separated by &quot;;&quot;.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sample_preparation_types</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ed728401-d697-4044-98e6-d61e1bbba72c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ed728401-d697-4044-98e6-d61e1bbba72c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e69a8c1a-a875-45fe-a5f7-fe7135d7e71e' class='xr-var-data-in' type='checkbox'><label for='data-e69a8c1a-a875-45fe-a5f7-fe7135d7e71e' 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>standard_name :</span></dt><dd>sample preparation types</dd><dt><span>long_name :</span></dt><dd>standardised sample preparation types</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Standardised sample preparation types utilised in the measurement process. Mutiple types are separated by &quot;;&quot;.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sampling_height</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a7a2cbd3-1673-4199-8cc5-ba9114d6ebcb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a7a2cbd3-1673-4199-8cc5-ba9114d6ebcb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8be04a38-bc2b-42fc-86c2-7f97363175ab' class='xr-var-data-in' type='checkbox'><label for='data-8be04a38-bc2b-42fc-86c2-7f97363175ab' 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>standard_name :</span></dt><dd>sampling height</dd><dt><span>long_name :</span></dt><dd>sampling height relative to ground</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>description :</span></dt><dd>Height above the ground of the inlet/instrument/sampler, in metres.</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>season_code</span></div><div class='xr-var-dims'>(station, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-18d19c9c-7f68-415c-806e-05a8f6a073ca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18d19c9c-7f68-415c-806e-05a8f6a073ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cfaa21d-be5a-4204-8c2d-c37c8d2b8498' class='xr-var-data-in' type='checkbox'><label for='data-9cfaa21d-be5a-4204-8c2d-c37c8d2b8498' 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>standard_name :</span></dt><dd>season code</dd><dt><span>long_name :</span></dt><dd>season code per measurement</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Code decreeing if measurement was made during the Spring, Summer, Autumn or Winter Seasons. Spring=0, Summer=1, Autumn=2, Winter=3. The classification is made by evaluating which season the local-time of a mid-measurement window timestamp falls in.</dd></dl></div><div class='xr-var-data'><pre>[263520 values with dtype=uint8]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>station_classification</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-86e2c222-8d55-479e-88fa-6bc5635831ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-86e2c222-8d55-479e-88fa-6bc5635831ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a370854-5a1c-40ce-bb79-f17c80d16d4d' class='xr-var-data-in' type='checkbox'><label for='data-3a370854-5a1c-40ce-bb79-f17c80d16d4d' 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>standard_name :</span></dt><dd>station classification</dd><dt><span>long_name :</span></dt><dd>standardised network provided station classification</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Standardised network provided classification, categorising the type of air measured by a station.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>station_name</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9fe0009d-99ba-4ea0-b7bc-d930648b0eaf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9fe0009d-99ba-4ea0-b7bc-d930648b0eaf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7f41129-f024-4086-9454-681947796675' class='xr-var-data-in' type='checkbox'><label for='data-b7f41129-f024-4086-9454-681947796675' 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>standard_name :</span></dt><dd>station name</dd><dt><span>long_name :</span></dt><dd>station name</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Name of station where the measurement was conducted.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Aoe_Baotou&#x27;, &#x27;Arm_Graciosa&#x27;, &#x27;Arm_Oliktok_Ak&#x27;, ..., &#x27;Zaragoza&#x27;,\n",
       "       &#x27;Zinder_Airport&#x27;, &#x27;Zvenigorod&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>station_reference</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2eb330ab-eb5a-40d3-b5fa-d6ae8a461c49' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2eb330ab-eb5a-40d3-b5fa-d6ae8a461c49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f3d1eb6-23a1-4076-9f7a-bb4b10abce7b' class='xr-var-data-in' type='checkbox'><label for='data-9f3d1eb6-23a1-4076-9f7a-bb4b10abce7b' 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>standard_name :</span></dt><dd>station reference</dd><dt><span>long_name :</span></dt><dd>station reference identifier</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>reference ID for station.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;AOEBaotou_P-D&#x27;, &#x27;ARMGraciosa_P-D&#x27;, &#x27;ARMOliktokAK_P-D&#x27;, ...,\n",
       "       &#x27;Zaragoza_P-D&#x27;, &#x27;ZinderAirport_P-D&#x27;, &#x27;Zvenigorod_P-D&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>station_timezone</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bfb7ab8b-9106-44da-8307-6ff6a092bad8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfb7ab8b-9106-44da-8307-6ff6a092bad8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adc7c77e-af49-498b-86f7-0d3aaed5c3bd' class='xr-var-data-in' type='checkbox'><label for='data-adc7c77e-af49-498b-86f7-0d3aaed5c3bd' 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>standard_name :</span></dt><dd>station timezone</dd><dt><span>long_name :</span></dt><dd>station timezone</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Name of the local timezone that the measuring station is located in. This is automatically generated using Timezone Finder Python package (taking longitude and latitude as inputs).</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Asia/Shanghai&#x27;, &#x27;Atlantic/Azores&#x27;, &#x27;America/Anchorage&#x27;, ...,\n",
       "       &#x27;Europe/Madrid&#x27;, &#x27;Africa/Niamey&#x27;, &#x27;Europe/Moscow&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>street_type</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-94fd4e04-cff4-405e-8ece-43e773b4fbdc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94fd4e04-cff4-405e-8ece-43e773b4fbdc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b9377b5-5708-40fb-b29e-9b4897a51c40' class='xr-var-data-in' type='checkbox'><label for='data-0b9377b5-5708-40fb-b29e-9b4897a51c40' 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>standard_name :</span></dt><dd>street type</dd><dt><span>long_name :</span></dt><dd>type of street</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Type of street where measurements are being made (if applicable).</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>street_width</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4a53e779-290b-4f7e-988c-6feaf624a9cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a53e779-290b-4f7e-988c-6feaf624a9cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ea47606-2211-44ca-b9e9-13f3fb8172a8' class='xr-var-data-in' type='checkbox'><label for='data-5ea47606-2211-44ca-b9e9-13f3fb8172a8' 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>standard_name :</span></dt><dd>street width</dd><dt><span>long_name :</span></dt><dd>width of the street</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>description :</span></dt><dd>Width of the street where measurements are being made (if applicable), in metres.</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>terrain</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-938a3c14-12a6-4786-b15b-1c109d1ccef2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-938a3c14-12a6-4786-b15b-1c109d1ccef2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46ca05c3-4bc6-4fad-9cc6-a77188618dea' class='xr-var-data-in' type='checkbox'><label for='data-46ca05c3-4bc6-4fad-9cc6-a77188618dea' 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>standard_name :</span></dt><dd>terrain</dd><dt><span>long_name :</span></dt><dd>standardised network provided terrain type</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Standardised network provided classification, describing the dominant terrain in the area of the reporting station.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;, ..., &#x27;nan&#x27;, &#x27;nan&#x27;, &#x27;nan&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vertical_datum</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-80c57f85-002f-46c2-bec7-008cd1580454' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-80c57f85-002f-46c2-bec7-008cd1580454' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6182f08a-8543-4c56-9a64-94f916008aa8' class='xr-var-data-in' type='checkbox'><label for='data-6182f08a-8543-4c56-9a64-94f916008aa8' 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>standard_name :</span></dt><dd>vertical datum</dd><dt><span>long_name :</span></dt><dd>vertical datum</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Name of the vertical datum used to define vertical elevation on the Earth. The datum is a surface of zero elevation to which other heights can be reference against. If not explicitely stated then this is assumed to be &#x27;tidal - mean sea level&#x27;.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;TIDAL - MEAN SEA LEVEL&#x27;, &#x27;TIDAL - MEAN SEA LEVEL&#x27;,\n",
       "       &#x27;TIDAL - MEAN SEA LEVEL&#x27;, ..., &#x27;TIDAL - MEAN SEA LEVEL&#x27;,\n",
       "       &#x27;TIDAL - MEAN SEA LEVEL&#x27;, &#x27;TIDAL - MEAN SEA LEVEL&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>weekday_weekend_code</span></div><div class='xr-var-dims'>(station, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5561cfef-288a-4e95-b070-3bf98d2f89fb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5561cfef-288a-4e95-b070-3bf98d2f89fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79e0bd96-c2b4-4aea-b840-d26cd6873181' class='xr-var-data-in' type='checkbox'><label for='data-79e0bd96-c2b4-4aea-b840-d26cd6873181' 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>standard_name :</span></dt><dd>weekday/weekend code</dd><dt><span>long_name :</span></dt><dd>weekday/weekend code per measurement</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>Binary indication if measurement was made during the weekday or weekend. Weekday=0, Weekend=1. The classification is made by evaluating if the local-time of a mid-measurement window timestamp falls on a weekday or on the weekend. Classification is 255 if cannot be made.</dd></dl></div><div class='xr-var-data'><pre>[263520 values with dtype=uint8]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3520856c-30ae-42b0-9c09-bc5471e56650' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3520856c-30ae-42b0-9c09-bc5471e56650' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>Surface aerosol optical depth at 550nm data in the AERONET_v3_lev1.5 network in 2020-06.</dd><dt><span>institution :</span></dt><dd>Barcelona Supercomputing Center</dd><dt><span>source :</span></dt><dd>Surface observations</dd><dt><span>creator_name :</span></dt><dd>Dene R. Bowdalo</dd><dt><span>creator_email :</span></dt><dd>dene.bowdalo@bsc.es</dd><dt><span>version :</span></dt><dd>1.4</dd></dl></div></li></ul></div></div>"
      ],
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       "<xarray.Dataset>\n",
       "Dimensions:                                                           (station: 366, time: 720, N_flag_codes: 190, N_qa_codes: 77)\n",
       "Coordinates:\n",
       "  * time                                                              (time) datetime64[ns] ...\n",
       "Dimensions without coordinates: station, N_flag_codes, N_qa_codes\n",
       "Data variables: (12/180)\n",
       "    ASTER_v3_altitude                                                 (station) float32 ...\n",
       "    EDGAR_v4.3.2_annual_average_BC_emissions                          (station) float32 ...\n",
       "    EDGAR_v4.3.2_annual_average_CO_emissions                          (station) float32 ...\n",
       "    EDGAR_v4.3.2_annual_average_NH3_emissions                         (station) float32 ...\n",
       "    EDGAR_v4.3.2_annual_average_NMVOC_emissions                       (station) float32 ...\n",
       "    EDGAR_v4.3.2_annual_average_NOx_emissions                         (station) float32 ...\n",
       "    ...                                                                ...\n",
       "    station_timezone                                                  (station) object ...\n",
       "    street_type                                                       (station) object ...\n",
       "    street_width                                                      (station) float32 ...\n",
       "    terrain                                                           (station) object ...\n",
       "    vertical_datum                                                    (station) object ...\n",
       "    weekday_weekend_code                                              (station, time) uint8 ...\n",
       "Attributes:\n",
       "    title:          Surface aerosol optical depth at 550nm data in the AERONE...\n",
       "    institution:    Barcelona Supercomputing Center\n",
       "    source:         Surface observations\n",
       "    creator_name:   Dene R. Bowdalo\n",
       "    creator_email:  dene.bowdalo@bsc.es\n",
       "    version:        1.4"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xr.open_dataset(path_obs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/esarchive/scratch/avilanova/software/NES/nes/load_nes.py:69: UserWarning: Parallel method cannot be 'Y' to create points NES. Setting it to 'X'\n",
      "  warnings.warn(\"Parallel method cannot be 'Y' to create points NES. Setting it to 'X'\")\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<nes.nc_projections.points_nes_ghost.PointsNesGHOST at 0x7f510014eb90>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_obs = open_netcdf(path=path_obs, info=True)\n",
    "data_obs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rank 000: Loading od550aero var (1/1)\n",
      "Rank 000: Loaded od550aero var ((366, 720))\n"
     ]
    }
   ],
   "source": [
    "data_obs.keep_vars(['od550aero'])\n",
    "data_obs.load()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2. Create shapefile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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       "                        geometry  od550aero\n",
       "FID                                        \n",
       "0     POINT (109.62880 40.85170)        NaN\n",
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       "365    POINT (36.77500 55.69500)        NaN\n",
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       "[366 rows x 2 columns]"
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     "execution_count": 13,
     "metadata": {},
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   "source": [
    "data_obs.create_shapefile()\n",
    "data_obs.shapefile['od550aero'] = data_obs.variables['od550aero']['data'][:, 0].ravel()\n",
    "data_obs.shapefile"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Providentia Interpolation (before error)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1. Read data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "path_prv_before = '/gpfs/projects/bsc32/AC_cache/recon/exp_interp/bug_1.4/a4s2-global-000/hourly/od550aero/AERONET_v3_lev1.5/od550aero_202006.nc'"
   ]
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  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
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       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
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       "\n",
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       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
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       "\n",
       ".xr-var-data > table {\n",
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       "\n",
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       ".xr-attrs {\n",
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       "\n",
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       "\n",
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       ".xr-attrs dd {\n",
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       "  float: left;\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",
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       "\n",
       ".xr-attrs dd {\n",
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       "  white-space: pre-wrap;\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                 (grid_edge: 877, station: 366, model_latitude: 181, model_longitude: 257, time: 720)\n",
       "Coordinates:\n",
       "  * time                    (time) datetime64[ns] 2020-06-01 ... 2020-06-30T2...\n",
       "Dimensions without coordinates: grid_edge, station, model_latitude, model_longitude\n",
       "Data variables:\n",
       "    grid_edge_latitude      (grid_edge) float64 -90.5 -89.5 ... -90.5 -90.5\n",
       "    grid_edge_longitude     (grid_edge) float64 -180.7 -180.7 ... -179.3 -180.7\n",
       "    latitude                (station) float64 40.85 39.09 70.5 ... 13.78 55.7\n",
       "    longitude               (station) float64 109.6 -28.03 -149.9 ... 8.99 36.77\n",
       "    model_centre_latitude   (model_latitude, model_longitude) float64 -90.0 ....\n",
       "    model_centre_longitude  (model_latitude, model_longitude) float64 -180.0 ...\n",
       "    od550aero               (station, time) float32 ...\n",
       "    station_reference       (station) object &#x27;AOEBaotou_P-D&#x27; ... &#x27;Zvenigorod_...\n",
       "Attributes:\n",
       "    title:          Inverse distance weighting (4 neighbours) interpolated a4...\n",
       "    institution:    Barcelona Supercomputing Center\n",
       "    source:         Experiment a4s2\n",
       "    creator_name:   Dene R. Bowdalo\n",
       "    creator_email:  dene.bowdalo@bsc.es\n",
       "    conventions:    CF-1.7\n",
       "    data_version:   1.0\n",
       "    history:        Wed Nov 30 18:53:34 2022: ncks -O --dfl_lvl 1 /gpfs/proje...\n",
       "    NCO:            netCDF Operators version 4.9.2 (Homepage = http://nco.sf....</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-d000f329-acde-460d-9123-61399b307980' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d000f329-acde-460d-9123-61399b307980' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>grid_edge</span>: 877</li><li><span>station</span>: 366</li><li><span>model_latitude</span>: 181</li><li><span>model_longitude</span>: 257</li><li><span class='xr-has-index'>time</span>: 720</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1109c9a3-73b6-4002-86d6-cb1ee5af3411' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1109c9a3-73b6-4002-86d6-cb1ee5af3411' class='xr-section-summary' >Coordinates: <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 class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-06-01 ... 2020-06-30T23:00:00</div><input id='attrs-b0d4eb30-d651-46e7-9b16-81bad677341d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0d4eb30-d651-46e7-9b16-81bad677341d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8b7dddd-48c5-4667-9674-7032aa19656d' class='xr-var-data-in' type='checkbox'><label for='data-a8b7dddd-48c5-4667-9674-7032aa19656d' 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>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>description :</span></dt><dd>Time in hours since 2020-06-01 00:00 UTC. Time given refers to the start of the time window the measurement is representative of (temporal resolution).</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>tz :</span></dt><dd>UTC</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-06-01T00:00:00.000000000&#x27;, &#x27;2020-06-01T01:00:00.000000000&#x27;,\n",
       "       &#x27;2020-06-01T02:00:00.000000000&#x27;, ..., &#x27;2020-06-30T21:00:00.000000000&#x27;,\n",
       "       &#x27;2020-06-30T22:00:00.000000000&#x27;, &#x27;2020-06-30T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c291967c-a481-4b1c-81cb-67bc30f2e833' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c291967c-a481-4b1c-81cb-67bc30f2e833' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>grid_edge_latitude</span></div><div class='xr-var-dims'>(grid_edge)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-65ddc6f4-3e2d-4f87-970c-0bbf850f402a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65ddc6f4-3e2d-4f87-970c-0bbf850f402a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff2a0ee3-b4cd-46b1-bccd-df5e83160b19' class='xr-var-data-in' type='checkbox'><label for='data-ff2a0ee3-b4cd-46b1-bccd-df5e83160b19' 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>standard_name :</span></dt><dd>grid edge latitude</dd><dt><span>long_name :</span></dt><dd>grid edge latitude</dd><dt><span>units :</span></dt><dd>decimal degrees North</dd><dt><span>description :</span></dt><dd>Latitude coordinate along edge of grid domain (going clockwise around grid boundary from bottom-left corner).</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-90.5, -89.5, -88.5, ..., -90.5, -90.5, -90.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>grid_edge_longitude</span></div><div class='xr-var-dims'>(grid_edge)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cab5897a-12dd-420d-bcd0-02550218ea26' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cab5897a-12dd-420d-bcd0-02550218ea26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-815be4ef-e510-4060-84fe-27f1ff4a7e97' class='xr-var-data-in' type='checkbox'><label for='data-815be4ef-e510-4060-84fe-27f1ff4a7e97' 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>standard_name :</span></dt><dd>grid edge longitude</dd><dt><span>long_name :</span></dt><dd>grid edge longitude</dd><dt><span>units :</span></dt><dd>decimal degrees East</dd><dt><span>description :</span></dt><dd>Longitude coordinate along edge of grid domain (going clockwise around grid boundary from bottom-left corner).</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-180.703125, -180.703125, -180.703125, ..., -177.890625, -179.296875,\n",
       "       -180.703125])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b684848a-dd94-4f54-9bc3-db5ea877a229' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b684848a-dd94-4f54-9bc3-db5ea877a229' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-402d0600-f6ec-443a-a64d-2aeadf325d1a' class='xr-var-data-in' type='checkbox'><label for='data-402d0600-f6ec-443a-a64d-2aeadf325d1a' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>decimal degrees North</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>description :</span></dt><dd>Geodetic latitude of measuring instrument, in decimal degrees North, following the stated horizontal datum.</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([40.8517  , 39.09109 , 70.4995  , ..., 41.6334  , 13.776683, 55.695   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-49c77913-4285-402d-aa5f-7681bb14d91d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-49c77913-4285-402d-aa5f-7681bb14d91d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a9bf767e-f81d-4aa0-9fc6-160b58e050e4' class='xr-var-data-in' type='checkbox'><label for='data-a9bf767e-f81d-4aa0-9fc6-160b58e050e4' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>decimal degrees East</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>description :</span></dt><dd>Geodetic longitude of measuring instrument, in decimal degrees East, following the stated horizontal datum.</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 109.6288  ,  -28.02917 , -149.88    , ...,   -0.88235 ,    8.990233,\n",
       "         36.775   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>model_centre_latitude</span></div><div class='xr-var-dims'>(model_latitude, model_longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d9bcb966-a9d3-4690-90a1-61018a74f00c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d9bcb966-a9d3-4690-90a1-61018a74f00c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40c0b875-5b74-4ac7-906b-e56c49542184' class='xr-var-data-in' type='checkbox'><label for='data-40c0b875-5b74-4ac7-906b-e56c49542184' 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>standard_name :</span></dt><dd>model centre latitude</dd><dt><span>long_name :</span></dt><dd>model centre latitude</dd><dt><span>units :</span></dt><dd>decimal degrees North</dd><dt><span>description :</span></dt><dd>2D meshed grid centre latitudes with 181 latitudes in 257 bands of longitude</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([[-90., -90., -90., ..., -90., -90., -90.],\n",
       "       [-89., -89., -89., ..., -89., -89., -89.],\n",
       "       [-88., -88., -88., ..., -88., -88., -88.],\n",
       "       ...,\n",
       "       [ 88.,  88.,  88., ...,  88.,  88.,  88.],\n",
       "       [ 89.,  89.,  89., ...,  89.,  89.,  89.],\n",
       "       [ 90.,  90.,  90., ...,  90.,  90.,  90.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>model_centre_longitude</span></div><div class='xr-var-dims'>(model_latitude, model_longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e3898e38-826a-4110-95d1-7ac19607f67a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e3898e38-826a-4110-95d1-7ac19607f67a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed7efcf6-24a2-493d-ad3e-4de1aab148eb' class='xr-var-data-in' type='checkbox'><label for='data-ed7efcf6-24a2-493d-ad3e-4de1aab148eb' 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>standard_name :</span></dt><dd>model centre longitude</dd><dt><span>long_name :</span></dt><dd>model centre longitude</dd><dt><span>units :</span></dt><dd>decimal degrees East</dd><dt><span>description :</span></dt><dd>2D meshed grid centre longitudes with 257 longitudes in 181 bands of latitude</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([[-180.     , -178.59375, -177.1875 , ...,  177.1875 ,  178.59375,\n",
       "         180.     ],\n",
       "       [-180.     , -178.59375, -177.1875 , ...,  177.1875 ,  178.59375,\n",
       "         180.     ],\n",
       "       [-180.     , -178.59375, -177.1875 , ...,  177.1875 ,  178.59375,\n",
       "         180.     ],\n",
       "       ...,\n",
       "       [-180.     , -178.59375, -177.1875 , ...,  177.1875 ,  178.59375,\n",
       "         180.     ],\n",
       "       [-180.     , -178.59375, -177.1875 , ...,  177.1875 ,  178.59375,\n",
       "         180.     ],\n",
       "       [-180.     , -178.59375, -177.1875 , ...,  177.1875 ,  178.59375,\n",
       "         180.     ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>od550aero</span></div><div class='xr-var-dims'>(station, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5ee5a8de-241d-4e08-a37d-c969d2c2409b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ee5a8de-241d-4e08-a37d-c969d2c2409b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-816711ac-f02b-49b6-9ec4-7b3552058ed6' class='xr-var-data-in' type='checkbox'><label for='data-816711ac-f02b-49b6-9ec4-7b3552058ed6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>aerosol optical depth at 550nm</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>standard_name :</span></dt><dd>aerosol optical depth at 550nm</dd><dt><span>descrption :</span></dt><dd>Interpolated value of aerosol optical depth at 550nm from the experiment a4s2 with reference to the measurement stations in the AERONET_v3_lev1.5 network</dd></dl></div><div class='xr-var-data'><pre>[263520 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>station_reference</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-037615f6-453f-447b-a030-3fcbb887d35d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-037615f6-453f-447b-a030-3fcbb887d35d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9337a83-af1c-4a11-bb3f-a5f7ab64e22b' class='xr-var-data-in' type='checkbox'><label for='data-c9337a83-af1c-4a11-bb3f-a5f7ab64e22b' 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>standard_name :</span></dt><dd>station reference</dd><dt><span>long_name :</span></dt><dd>station reference identifier</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>reference ID for station.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;AOEBaotou_P-D&#x27;, &#x27;ARMGraciosa_P-D&#x27;, &#x27;ARMOliktokAK_P-D&#x27;, ...,\n",
       "       &#x27;Zaragoza_P-D&#x27;, &#x27;ZinderAirport_P-D&#x27;, &#x27;Zvenigorod_P-D&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0686ec6a-bb48-4b6a-8ed6-75dbb9e7ae62' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0686ec6a-bb48-4b6a-8ed6-75dbb9e7ae62' class='xr-section-summary' >Attributes: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>Inverse distance weighting (4 neighbours) interpolated a4s2 experiment data for the component od550aero with reference to the measurement stations in the AERONET_v3_lev1.5 network in 2020-06.</dd><dt><span>institution :</span></dt><dd>Barcelona Supercomputing Center</dd><dt><span>source :</span></dt><dd>Experiment a4s2</dd><dt><span>creator_name :</span></dt><dd>Dene R. Bowdalo</dd><dt><span>creator_email :</span></dt><dd>dene.bowdalo@bsc.es</dd><dt><span>conventions :</span></dt><dd>CF-1.7</dd><dt><span>data_version :</span></dt><dd>1.0</dd><dt><span>history :</span></dt><dd>Wed Nov 30 18:53:34 2022: ncks -O --dfl_lvl 1 /gpfs/projects/bsc32/AC_cache/recon/exp_interp/1.4/a4s2-global-000/hourly/od550aero/AERONET_v3_lev1.5/od550aero_202006.nc /gpfs/projects/bsc32/AC_cache/recon/exp_interp/1.4/a4s2-global-000/hourly/od550aero/AERONET_v3_lev1.5/od550aero_202006.nc</dd><dt><span>NCO :</span></dt><dd>netCDF Operators version 4.9.2 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                 (grid_edge: 877, station: 366, model_latitude: 181, model_longitude: 257, time: 720)\n",
       "Coordinates:\n",
       "  * time                    (time) datetime64[ns] 2020-06-01 ... 2020-06-30T2...\n",
       "Dimensions without coordinates: grid_edge, station, model_latitude, model_longitude\n",
       "Data variables:\n",
       "    grid_edge_latitude      (grid_edge) float64 ...\n",
       "    grid_edge_longitude     (grid_edge) float64 ...\n",
       "    latitude                (station) float64 ...\n",
       "    longitude               (station) float64 ...\n",
       "    model_centre_latitude   (model_latitude, model_longitude) float64 ...\n",
       "    model_centre_longitude  (model_latitude, model_longitude) float64 ...\n",
       "    od550aero               (station, time) float32 ...\n",
       "    station_reference       (station) object ...\n",
       "Attributes:\n",
       "    title:          Inverse distance weighting (4 neighbours) interpolated a4...\n",
       "    institution:    Barcelona Supercomputing Center\n",
       "    source:         Experiment a4s2\n",
       "    creator_name:   Dene R. Bowdalo\n",
       "    creator_email:  dene.bowdalo@bsc.es\n",
       "    conventions:    CF-1.7\n",
       "    data_version:   1.0\n",
       "    history:        Wed Nov 30 18:53:34 2022: ncks -O --dfl_lvl 1 /gpfs/proje...\n",
       "    NCO:            netCDF Operators version 4.9.2 (Homepage = http://nco.sf...."
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xr.open_dataset(path_prv_before)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/esarchive/scratch/avilanova/software/NES/nes/load_nes.py:69: UserWarning: Parallel method cannot be 'Y' to create points NES. Setting it to 'X'\n",
      "  warnings.warn(\"Parallel method cannot be 'Y' to create points NES. Setting it to 'X'\")\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<nes.nc_projections.points_nes_providentia.PointsNesProvidentia at 0x7f5100fcc7d0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_prv_before = open_netcdf(path=path_prv_before, info=True)\n",
    "data_prv_before"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rank 000: Loading od550aero var (1/1)\n",
      "Rank 000: Loaded od550aero var ((366, 720))\n"
     ]
    }
   ],
   "source": [
    "data_prv_before.keep_vars(['od550aero'])\n",
    "data_prv_before.load()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2. Create shapefile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "      <th>od550aero</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FID</th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>POINT (109.62880 40.85170)</td>\n",
       "      <td>0.227307</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>POINT (-28.02917 39.09109)</td>\n",
       "      <td>0.004195</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>POINT (-149.88000 70.49950)</td>\n",
       "      <td>0.006696</td>\n",
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       "      <td>POINT (-97.48562 36.60518)</td>\n",
       "      <td>0.005329</td>\n",
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       "      <th>361</th>\n",
       "      <td>POINT (-114.37625 62.45130)</td>\n",
       "      <td>0.007441</td>\n",
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       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>POINT (126.93479 37.56443)</td>\n",
       "      <td>0.082251</td>\n",
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       "      <th>363</th>\n",
       "      <td>POINT (-0.88235 41.63340)</td>\n",
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       "      <td>POINT (8.99023 13.77668)</td>\n",
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       "      <td>POINT (36.77500 55.69500)</td>\n",
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       "<p>366 rows × 2 columns</p>\n",
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       "                        geometry  od550aero\n",
       "FID                                        \n",
       "0     POINT (109.62880 40.85170)   0.227307\n",
       "1     POINT (-28.02917 39.09109)   0.004195\n",
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       "4      POINT (40.19450 -2.99600)   0.059810\n",
       "..                           ...        ...\n",
       "361  POINT (-114.37625 62.45130)   0.007441\n",
       "362   POINT (126.93479 37.56443)   0.082251\n",
       "363    POINT (-0.88235 41.63340)   0.008346\n",
       "364     POINT (8.99023 13.77668)   0.446823\n",
       "365    POINT (36.77500 55.69500)   0.006547\n",
       "\n",
       "[366 rows x 2 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_prv_before.create_shapefile()\n",
    "data_prv_before.shapefile['od550aero'] = data_prv_before.variables['od550aero']['data'][:, 0].ravel()\n",
    "data_prv_before.shapefile"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3. Plot data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "[encoded data, 222836 characters]",
      "text/plain": [
       "<Figure size 1440x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_1, ax_1 = plt.subplots(1, figsize=(20, 7))\n",
    "\n",
    "gdf_model.plot(ax=ax_1, column='od550du', cmap='viridis', legend=True, vmin=0, vmax=3)\n",
    "\n",
    "gdf_earth.plot(ax=ax_1, facecolor=\"none\", edgecolor='white', lw=0.5)\n",
    "\n",
    "gdf_prv_before = data_prv_before.shapefile\n",
    "gdf_prv_before.plot(ax=ax_1, column='od550aero', cmap='viridis', edgecolor='black', lw=0.5, vmin=0, vmax=3)\n",
    "\n",
    "ax_1.margins(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Providentia Interpolation (after error)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.1. Read data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "path_prv_after = '/gpfs/projects/bsc32/AC_cache/recon/exp_interp/1.4/a4s2-global-000/hourly/od550aero/AERONET_v3_lev1.5/od550aero_202006.nc'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                 (grid_edge: 877, station: 366, model_latitude: 181, model_longitude: 257, time: 720)\n",
       "Coordinates:\n",
       "  * time                    (time) datetime64[ns] 2020-06-01 ... 2020-06-30T2...\n",
       "Dimensions without coordinates: grid_edge, station, model_latitude, model_longitude\n",
       "Data variables:\n",
       "    grid_edge_latitude      (grid_edge) float64 -90.5 -89.5 ... -90.5 -90.5\n",
       "    grid_edge_longitude     (grid_edge) float64 -180.7 -180.7 ... -179.3 -180.7\n",
       "    latitude                (station) float64 40.85 39.09 70.5 ... 13.78 55.7\n",
       "    longitude               (station) float64 109.6 -28.03 -149.9 ... 8.99 36.77\n",
       "    model_centre_latitude   (model_latitude, model_longitude) float64 -90.0 ....\n",
       "    model_centre_longitude  (model_latitude, model_longitude) float64 -180.0 ...\n",
       "    od550aero               (station, time) float32 ...\n",
       "    station_reference       (station) object &#x27;AOEBaotou_P-D&#x27; ... &#x27;Zvenigorod_...\n",
       "Attributes:\n",
       "    title:          Inverse distance weighting (4 neighbours) interpolated a4...\n",
       "    institution:    Barcelona Supercomputing Center\n",
       "    source:         Experiment a4s2\n",
       "    creator_name:   Dene R. Bowdalo\n",
       "    creator_email:  dene.bowdalo@bsc.es\n",
       "    conventions:    CF-1.7\n",
       "    data_version:   1.0\n",
       "    history:        Wed Nov 30 18:53:34 2022: ncks -O --dfl_lvl 1 /gpfs/proje...\n",
       "    NCO:            netCDF Operators version 4.9.2 (Homepage = http://nco.sf....</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-f90e71b3-e8c9-45ff-add8-3d4d490a4ba1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f90e71b3-e8c9-45ff-add8-3d4d490a4ba1' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>grid_edge</span>: 877</li><li><span>station</span>: 366</li><li><span>model_latitude</span>: 181</li><li><span>model_longitude</span>: 257</li><li><span class='xr-has-index'>time</span>: 720</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b7053572-0ef5-4bec-acc6-9f5fa7b12ad0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b7053572-0ef5-4bec-acc6-9f5fa7b12ad0' class='xr-section-summary' >Coordinates: <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 class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-06-01 ... 2020-06-30T23:00:00</div><input id='attrs-8234056d-5d2c-49d8-98d2-728ae0ccebbd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8234056d-5d2c-49d8-98d2-728ae0ccebbd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7313da53-14ca-4d29-a739-9c36f3761b0c' class='xr-var-data-in' type='checkbox'><label for='data-7313da53-14ca-4d29-a739-9c36f3761b0c' 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>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>description :</span></dt><dd>Time in hours since 2020-06-01 00:00 UTC. Time given refers to the start of the time window the measurement is representative of (temporal resolution).</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>tz :</span></dt><dd>UTC</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-06-01T00:00:00.000000000&#x27;, &#x27;2020-06-01T01:00:00.000000000&#x27;,\n",
       "       &#x27;2020-06-01T02:00:00.000000000&#x27;, ..., &#x27;2020-06-30T21:00:00.000000000&#x27;,\n",
       "       &#x27;2020-06-30T22:00:00.000000000&#x27;, &#x27;2020-06-30T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f90b6eb1-d146-48a6-8dd0-f8ec62fc029a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f90b6eb1-d146-48a6-8dd0-f8ec62fc029a' class='xr-section-summary' >Data variables: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>grid_edge_latitude</span></div><div class='xr-var-dims'>(grid_edge)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d3c8fd4b-9e5d-46d4-8e2d-b1df5cb26bec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3c8fd4b-9e5d-46d4-8e2d-b1df5cb26bec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bbe1cdba-633c-4339-b74e-9e65b205926f' class='xr-var-data-in' type='checkbox'><label for='data-bbe1cdba-633c-4339-b74e-9e65b205926f' 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>standard_name :</span></dt><dd>grid edge latitude</dd><dt><span>long_name :</span></dt><dd>grid edge latitude</dd><dt><span>units :</span></dt><dd>decimal degrees North</dd><dt><span>description :</span></dt><dd>Latitude coordinate along edge of grid domain (going clockwise around grid boundary from bottom-left corner).</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-90.5, -89.5, -88.5, ..., -90.5, -90.5, -90.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>grid_edge_longitude</span></div><div class='xr-var-dims'>(grid_edge)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1f64b8f5-1c4b-4eaa-9af9-d8860fa95654' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f64b8f5-1c4b-4eaa-9af9-d8860fa95654' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a6ed0f6-0e97-4236-a677-186b294129af' class='xr-var-data-in' type='checkbox'><label for='data-7a6ed0f6-0e97-4236-a677-186b294129af' 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>standard_name :</span></dt><dd>grid edge longitude</dd><dt><span>long_name :</span></dt><dd>grid edge longitude</dd><dt><span>units :</span></dt><dd>decimal degrees East</dd><dt><span>description :</span></dt><dd>Longitude coordinate along edge of grid domain (going clockwise around grid boundary from bottom-left corner).</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-180.703125, -180.703125, -180.703125, ..., -177.890625, -179.296875,\n",
       "       -180.703125])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-161a5aca-8d9b-4d26-9b8d-d13d0999a366' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-161a5aca-8d9b-4d26-9b8d-d13d0999a366' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-653b70cf-be2b-4cb3-bc64-2bafd0333a38' class='xr-var-data-in' type='checkbox'><label for='data-653b70cf-be2b-4cb3-bc64-2bafd0333a38' 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>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>decimal degrees North</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>description :</span></dt><dd>Geodetic latitude of measuring instrument, in decimal degrees North, following the stated horizontal datum.</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([40.8517  , 39.09109 , 70.4995  , ..., 41.6334  , 13.776683, 55.695   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3c070fc2-3a38-4d47-b200-365072cefc1f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c070fc2-3a38-4d47-b200-365072cefc1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e747ffdf-167b-46b6-b64b-707cb1d23725' class='xr-var-data-in' type='checkbox'><label for='data-e747ffdf-167b-46b6-b64b-707cb1d23725' 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>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>decimal degrees East</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>description :</span></dt><dd>Geodetic longitude of measuring instrument, in decimal degrees East, following the stated horizontal datum.</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([ 109.6288  ,  -28.02917 , -149.88    , ...,   -0.88235 ,    8.990233,\n",
       "         36.775   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>model_centre_latitude</span></div><div class='xr-var-dims'>(model_latitude, model_longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9b24127b-045b-40ed-8c1e-22792a9d4d5b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b24127b-045b-40ed-8c1e-22792a9d4d5b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fac7e2a4-835b-4d5e-bd35-8965e83b6d7a' class='xr-var-data-in' type='checkbox'><label for='data-fac7e2a4-835b-4d5e-bd35-8965e83b6d7a' 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>standard_name :</span></dt><dd>model centre latitude</dd><dt><span>long_name :</span></dt><dd>model centre latitude</dd><dt><span>units :</span></dt><dd>decimal degrees North</dd><dt><span>description :</span></dt><dd>2D meshed grid centre latitudes with 181 latitudes in 257 bands of longitude</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([[-90., -90., -90., ..., -90., -90., -90.],\n",
       "       [-89., -89., -89., ..., -89., -89., -89.],\n",
       "       [-88., -88., -88., ..., -88., -88., -88.],\n",
       "       ...,\n",
       "       [ 88.,  88.,  88., ...,  88.,  88.,  88.],\n",
       "       [ 89.,  89.,  89., ...,  89.,  89.,  89.],\n",
       "       [ 90.,  90.,  90., ...,  90.,  90.,  90.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>model_centre_longitude</span></div><div class='xr-var-dims'>(model_latitude, model_longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f8bcb540-6633-4531-b9b8-f842a5408dac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f8bcb540-6633-4531-b9b8-f842a5408dac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7cf0dbd1-d26f-4f7f-89fb-d5f4de4c2b48' class='xr-var-data-in' type='checkbox'><label for='data-7cf0dbd1-d26f-4f7f-89fb-d5f4de4c2b48' 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>standard_name :</span></dt><dd>model centre longitude</dd><dt><span>long_name :</span></dt><dd>model centre longitude</dd><dt><span>units :</span></dt><dd>decimal degrees East</dd><dt><span>description :</span></dt><dd>2D meshed grid centre longitudes with 257 longitudes in 181 bands of latitude</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([[-180.     , -178.59375, -177.1875 , ...,  177.1875 ,  178.59375,\n",
       "         180.     ],\n",
       "       [-180.     , -178.59375, -177.1875 , ...,  177.1875 ,  178.59375,\n",
       "         180.     ],\n",
       "       [-180.     , -178.59375, -177.1875 , ...,  177.1875 ,  178.59375,\n",
       "         180.     ],\n",
       "       ...,\n",
       "       [-180.     , -178.59375, -177.1875 , ...,  177.1875 ,  178.59375,\n",
       "         180.     ],\n",
       "       [-180.     , -178.59375, -177.1875 , ...,  177.1875 ,  178.59375,\n",
       "         180.     ],\n",
       "       [-180.     , -178.59375, -177.1875 , ...,  177.1875 ,  178.59375,\n",
       "         180.     ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>od550aero</span></div><div class='xr-var-dims'>(station, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-33478ae1-b8bc-4183-bdac-70c5826367cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-33478ae1-b8bc-4183-bdac-70c5826367cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98550edc-7124-4351-a7e9-3b405c8f6002' class='xr-var-data-in' type='checkbox'><label for='data-98550edc-7124-4351-a7e9-3b405c8f6002' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>aerosol optical depth at 550nm</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>standard_name :</span></dt><dd>aerosol optical depth at 550nm</dd><dt><span>descrption :</span></dt><dd>Interpolated value of aerosol optical depth at 550nm from the experiment a4s2 with reference to the measurement stations in the AERONET_v3_lev1.5 network</dd></dl></div><div class='xr-var-data'><pre>[263520 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>station_reference</span></div><div class='xr-var-dims'>(station)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ed0c55bc-d623-4a2f-9caa-917861f8b6e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ed0c55bc-d623-4a2f-9caa-917861f8b6e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-022b9ae8-15d0-4bc7-88d6-bfc0d40df99f' class='xr-var-data-in' type='checkbox'><label for='data-022b9ae8-15d0-4bc7-88d6-bfc0d40df99f' 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>standard_name :</span></dt><dd>station reference</dd><dt><span>long_name :</span></dt><dd>station reference identifier</dd><dt><span>units :</span></dt><dd>unitless</dd><dt><span>description :</span></dt><dd>reference ID for station.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;AOEBaotou_P-D&#x27;, &#x27;ARMGraciosa_P-D&#x27;, &#x27;ARMOliktokAK_P-D&#x27;, ...,\n",
       "       &#x27;Zaragoza_P-D&#x27;, &#x27;ZinderAirport_P-D&#x27;, &#x27;Zvenigorod_P-D&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-11fd5a4d-8dc9-402b-b542-ef447c3c6433' class='xr-section-summary-in' type='checkbox'  checked><label for='section-11fd5a4d-8dc9-402b-b542-ef447c3c6433' class='xr-section-summary' >Attributes: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>Inverse distance weighting (4 neighbours) interpolated a4s2 experiment data for the component od550aero with reference to the measurement stations in the AERONET_v3_lev1.5 network in 2020-06.</dd><dt><span>institution :</span></dt><dd>Barcelona Supercomputing Center</dd><dt><span>source :</span></dt><dd>Experiment a4s2</dd><dt><span>creator_name :</span></dt><dd>Dene R. Bowdalo</dd><dt><span>creator_email :</span></dt><dd>dene.bowdalo@bsc.es</dd><dt><span>conventions :</span></dt><dd>CF-1.7</dd><dt><span>data_version :</span></dt><dd>1.0</dd><dt><span>history :</span></dt><dd>Wed Nov 30 18:53:34 2022: ncks -O --dfl_lvl 1 /gpfs/projects/bsc32/AC_cache/recon/exp_interp/1.4/a4s2-global-000/hourly/od550aero/AERONET_v3_lev1.5/od550aero_202006.nc /gpfs/projects/bsc32/AC_cache/recon/exp_interp/1.4/a4s2-global-000/hourly/od550aero/AERONET_v3_lev1.5/od550aero_202006.nc</dd><dt><span>NCO :</span></dt><dd>netCDF Operators version 4.9.2 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                 (grid_edge: 877, station: 366, model_latitude: 181, model_longitude: 257, time: 720)\n",
       "Coordinates:\n",
       "  * time                    (time) datetime64[ns] 2020-06-01 ... 2020-06-30T2...\n",
       "Dimensions without coordinates: grid_edge, station, model_latitude, model_longitude\n",
       "Data variables:\n",
       "    grid_edge_latitude      (grid_edge) float64 ...\n",
       "    grid_edge_longitude     (grid_edge) float64 ...\n",
       "    latitude                (station) float64 ...\n",
       "    longitude               (station) float64 ...\n",
       "    model_centre_latitude   (model_latitude, model_longitude) float64 ...\n",
       "    model_centre_longitude  (model_latitude, model_longitude) float64 ...\n",
       "    od550aero               (station, time) float32 ...\n",
       "    station_reference       (station) object ...\n",
       "Attributes:\n",
       "    title:          Inverse distance weighting (4 neighbours) interpolated a4...\n",
       "    institution:    Barcelona Supercomputing Center\n",
       "    source:         Experiment a4s2\n",
       "    creator_name:   Dene R. Bowdalo\n",
       "    creator_email:  dene.bowdalo@bsc.es\n",
       "    conventions:    CF-1.7\n",
       "    data_version:   1.0\n",
       "    history:        Wed Nov 30 18:53:34 2022: ncks -O --dfl_lvl 1 /gpfs/proje...\n",
       "    NCO:            netCDF Operators version 4.9.2 (Homepage = http://nco.sf...."
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xr.open_dataset(path_prv_before)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/esarchive/scratch/avilanova/software/NES/nes/load_nes.py:69: UserWarning: Parallel method cannot be 'Y' to create points NES. Setting it to 'X'\n",
      "  warnings.warn(\"Parallel method cannot be 'Y' to create points NES. Setting it to 'X'\")\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<nes.nc_projections.points_nes_providentia.PointsNesProvidentia at 0x7f510000f610>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_prv_after = open_netcdf(path=path_prv_after, info=True)\n",
    "data_prv_after"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rank 000: Loading od550aero var (1/1)\n",
      "Rank 000: Loaded od550aero var ((366, 720))\n"
     ]
    }
   ],
   "source": [
    "data_prv_after.keep_vars(['od550aero'])\n",
    "data_prv_after.load()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.2. Create shapefile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "      <th>od550aero</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POINT (109.62880 40.85170)</td>\n",
       "      <td>0.504757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>POINT (-28.02917 39.09109)</td>\n",
       "      <td>0.007563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>POINT (-149.88000 70.49950)</td>\n",
       "      <td>0.013467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POINT (-97.48562 36.60518)</td>\n",
       "      <td>0.011034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>POINT (40.19450 -2.99600)</td>\n",
       "      <td>0.002979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>POINT (-114.37625 62.45130)</td>\n",
       "      <td>0.014462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>POINT (126.93479 37.56443)</td>\n",
       "      <td>0.184404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>POINT (-0.88235 41.63340)</td>\n",
       "      <td>0.018486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>POINT (8.99023 13.77668)</td>\n",
       "      <td>0.900909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>POINT (36.77500 55.69500)</td>\n",
       "      <td>0.013143</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>366 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        geometry  od550aero\n",
       "FID                                        \n",
       "0     POINT (109.62880 40.85170)   0.504757\n",
       "1     POINT (-28.02917 39.09109)   0.007563\n",
       "2    POINT (-149.88000 70.49950)   0.013467\n",
       "3     POINT (-97.48562 36.60518)   0.011034\n",
       "4      POINT (40.19450 -2.99600)   0.002979\n",
       "..                           ...        ...\n",
       "361  POINT (-114.37625 62.45130)   0.014462\n",
       "362   POINT (126.93479 37.56443)   0.184404\n",
       "363    POINT (-0.88235 41.63340)   0.018486\n",
       "364     POINT (8.99023 13.77668)   0.900909\n",
       "365    POINT (36.77500 55.69500)   0.013143\n",
       "\n",
       "[366 rows x 2 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_prv_after.create_shapefile()\n",
    "data_prv_after.shapefile['od550aero'] = data_prv_after.variables['od550aero']['data'][:, 0].ravel()\n",
    "data_prv_after.shapefile"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.3. Plot data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "[encoded data, 222768 characters]",
      "text/plain": [
       "<Figure size 1440x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_2, ax_2 = plt.subplots(1, figsize=(20, 7))\n",
    "\n",
    "gdf_model.plot(ax=ax_2, column='od550du', cmap='viridis', legend=True, vmin=0, vmax=3)\n",
    "\n",
    "gdf_earth.plot(ax=ax_2, facecolor=\"none\", edgecolor='white', lw=0.5)\n",
    "\n",
    "gdf_prv_after = data_prv_after.shapefile\n",
    "gdf_prv_after.plot(ax=ax_2, column='od550aero', cmap='viridis', edgecolor='black', lw=0.5, vmin=0, vmax=3)\n",
    "\n",
    "ax_2.margins(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "masked_array(\n",
       "  data=[[-0.27745032, -0.33557633, -0.39707237, ..., -0.02371369,\n",
       "         -0.02375146, -0.02365999],\n",
       "        [-0.00336807, -0.00303048, -0.00253099, ..., -0.00627814,\n",
       "         -0.00588607, -0.00548861],\n",
       "        [-0.00677101, -0.00678938, -0.00670995, ..., -0.00168319,\n",
       "         -0.0017733 , -0.00185721],\n",
       "        ...,\n",
       "        [-0.01014002, -0.01006637, -0.01026233, ..., -0.04439881,\n",
       "         -0.04458728, -0.04401928],\n",
       "        [-0.4540865 , -0.4427302 , -0.4316749 , ..., -0.5309974 ,\n",
       "         -0.52981824, -0.526042  ],\n",
       "        [-0.00659596, -0.0059174 , -0.0054107 , ..., -0.00239577,\n",
       "         -0.00239077, -0.00250021]],\n",
       "  mask=False,\n",
       "  fill_value=1e+20,\n",
       "  dtype=float32)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diff = data_prv_before.variables['od550aero']['data'] - data_prv_after.variables['od550aero']['data']\n",
    "diff"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. NES Interpolation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.1. Interpolate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\tod550du horizontal interpolation\n"
     ]
    }
   ],
   "source": [
    "data_nes = data_model.interpolate_horizontal(data_obs, weight_matrix_path=None, \n",
    "                                             kind='NearestNeighbour', n_neighbours=4,\n",
    "                                             info=True, to_providentia=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'od550du': {'data': array([[0.5048964 , 0.63574161, 0.79751828, ..., 0.5958503 , 0.55814504,\n",
       "          0.54268227],\n",
       "         [0.00756333, 0.00732328, 0.00696368, ..., 0.01266789, 0.01230407,\n",
       "          0.01215834],\n",
       "         [0.01346751, 0.01355801, 0.01349525, ..., 0.01335663, 0.01338057,\n",
       "          0.01345622],\n",
       "         ...,\n",
       "         [0.01848428, 0.01945806, 0.02101376, ..., 0.02690235, 0.02741421,\n",
       "          0.02839378],\n",
       "         [0.90109581, 0.88706459, 0.87328311, ..., 0.84196177, 0.86970553,\n",
       "          0.89764859],\n",
       "         [0.01314365, 0.01134606, 0.01024394, ..., 0.00430861, 0.00383769,\n",
       "          0.00348033]]), 'dimensions': ('station', 'time')}}"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_nes.variables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2. Create shapefile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "      <th>od550du</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POINT (109.62880 40.85170)</td>\n",
       "      <td>0.504896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>POINT (-28.02917 39.09109)</td>\n",
       "      <td>0.007563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>POINT (-149.88000 70.49950)</td>\n",
       "      <td>0.013468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POINT (-97.48562 36.60518)</td>\n",
       "      <td>0.011034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>POINT (40.19450 -2.99600)</td>\n",
       "      <td>0.002980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>POINT (-114.37625 62.45130)</td>\n",
       "      <td>0.014462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>POINT (126.93479 37.56443)</td>\n",
       "      <td>0.184427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>POINT (-0.88235 41.63340)</td>\n",
       "      <td>0.018484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>POINT (8.99023 13.77668)</td>\n",
       "      <td>0.901096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>POINT (36.77500 55.69500)</td>\n",
       "      <td>0.013144</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>366 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        geometry   od550du\n",
       "FID                                       \n",
       "0     POINT (109.62880 40.85170)  0.504896\n",
       "1     POINT (-28.02917 39.09109)  0.007563\n",
       "2    POINT (-149.88000 70.49950)  0.013468\n",
       "3     POINT (-97.48562 36.60518)  0.011034\n",
       "4      POINT (40.19450 -2.99600)  0.002980\n",
       "..                           ...       ...\n",
       "361  POINT (-114.37625 62.45130)  0.014462\n",
       "362   POINT (126.93479 37.56443)  0.184427\n",
       "363    POINT (-0.88235 41.63340)  0.018484\n",
       "364     POINT (8.99023 13.77668)  0.901096\n",
       "365    POINT (36.77500 55.69500)  0.013144\n",
       "\n",
       "[366 rows x 2 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_nes.create_shapefile()\n",
    "data_nes.shapefile['od550du'] = data_nes.variables['od550du']['data'][:, 0].ravel()\n",
    "data_nes.shapefile"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.3. Plot data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "[encoded data, 222768 characters]",
      "text/plain": [
       "<Figure size 1440x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_3, ax_3 = plt.subplots(1, figsize=(20, 7))\n",
    "\n",
    "gdf_model.plot(ax=ax_3, column='od550du', cmap='viridis', legend=True, vmin=0, vmax=3)\n",
    "\n",
    "gdf_earth.plot(ax=ax_3, facecolor=\"none\", edgecolor='white', lw=0.5)\n",
    "\n",
    "gdf_nes = data_nes.shapefile\n",
    "gdf_nes.plot(ax=ax_3, column='od550du', cmap='viridis', edgecolor='black', lw=0.5, vmin=0, vmax=3)\n",
    "\n",
    "ax_3.margins(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Difference between Providentia Interpolation and NES"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.1. Visual comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "gdf_diff = gdf_prv_after.copy().rename(columns={'od550aero': 'providentia'})[['geometry', 'providentia']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "gdf_diff['nes'] = gdf_nes['od550du']\n",
    "gdf_diff['obs'] = data_obs.shapefile['od550aero']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 6.1.1. Absolute difference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "      <th>providentia</th>\n",
       "      <th>nes</th>\n",
       "      <th>obs</th>\n",
       "      <th>absolute_difference</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <td>0.504757</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>1.391183e-04</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>POINT (-28.02917 39.09109)</td>\n",
       "      <td>0.007563</td>\n",
       "      <td>0.007563</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.650604e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>POINT (-149.88000 70.49950)</td>\n",
       "      <td>0.013467</td>\n",
       "      <td>0.013468</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.439117e-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POINT (-97.48562 36.60518)</td>\n",
       "      <td>0.011034</td>\n",
       "      <td>0.011034</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.619126e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>POINT (40.19450 -2.99600)</td>\n",
       "      <td>0.002979</td>\n",
       "      <td>0.002980</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.042769e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>POINT (-114.37625 62.45130)</td>\n",
       "      <td>0.014462</td>\n",
       "      <td>0.014462</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-7.643789e-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>POINT (126.93479 37.56443)</td>\n",
       "      <td>0.184404</td>\n",
       "      <td>0.184427</td>\n",
       "      <td>0.152831</td>\n",
       "      <td>2.291842e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>POINT (-0.88235 41.63340)</td>\n",
       "      <td>0.018486</td>\n",
       "      <td>0.018484</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-1.265558e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>POINT (8.99023 13.77668)</td>\n",
       "      <td>0.900909</td>\n",
       "      <td>0.901096</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.867402e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>POINT (36.77500 55.69500)</td>\n",
       "      <td>0.013143</td>\n",
       "      <td>0.013144</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.505649e-07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>366 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        geometry  providentia       nes       obs  \\\n",
       "FID                                                                 \n",
       "0     POINT (109.62880 40.85170)     0.504757  0.504896       NaN   \n",
       "1     POINT (-28.02917 39.09109)     0.007563  0.007563       NaN   \n",
       "2    POINT (-149.88000 70.49950)     0.013467  0.013468       NaN   \n",
       "3     POINT (-97.48562 36.60518)     0.011034  0.011034       NaN   \n",
       "4      POINT (40.19450 -2.99600)     0.002979  0.002980       NaN   \n",
       "..                           ...          ...       ...       ...   \n",
       "361  POINT (-114.37625 62.45130)     0.014462  0.014462       NaN   \n",
       "362   POINT (126.93479 37.56443)     0.184404  0.184427  0.152831   \n",
       "363    POINT (-0.88235 41.63340)     0.018486  0.018484       NaN   \n",
       "364     POINT (8.99023 13.77668)     0.900909  0.901096       NaN   \n",
       "365    POINT (36.77500 55.69500)     0.013143  0.013144       NaN   \n",
       "\n",
       "     absolute_difference  \n",
       "FID                       \n",
       "0           1.391183e-04  \n",
       "1           3.650604e-07  \n",
       "2           3.439117e-08  \n",
       "3           4.619126e-07  \n",
       "4           2.042769e-07  \n",
       "..                   ...  \n",
       "361        -7.643789e-08  \n",
       "362         2.291842e-05  \n",
       "363        -1.265558e-06  \n",
       "364         1.867402e-04  \n",
       "365         5.505649e-07  \n",
       "\n",
       "[366 rows x 5 columns]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdf_diff['absolute_difference'] = gdf_diff['nes'] - gdf_diff['providentia']\n",
    "gdf_diff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "[encoded data, 231916 characters]",
      "text/plain": [
       "<Figure size 1440x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_4, ax_4 = plt.subplots(1, figsize=(20, 7))\n",
    "\n",
    "gdf_model.plot(ax=ax_4, column='od550du', cmap='viridis', vmin=0, vmax=3)\n",
    "\n",
    "gdf_earth.plot(ax=ax_4, facecolor=\"none\", edgecolor='white', lw=0.5)\n",
    "\n",
    "gdf_diff.plot(ax=ax_4, column='absolute_difference', cmap='bwr', edgecolor='black', legend=True, lw=0.5)\n",
    "\n",
    "ax_4.margins(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.0004256221585662301"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdf_diff['absolute_difference'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0012512493387983464"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdf_diff['absolute_difference'].max()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 6.1.2. Relative difference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "      <th>providentia</th>\n",
       "      <th>nes</th>\n",
       "      <th>absolute_difference</th>\n",
       "      <th>relative_difference</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POINT (109.62880 40.85170)</td>\n",
       "      <td>0.504757</td>\n",
       "      <td>0.504896</td>\n",
       "      <td>1.391183e-04</td>\n",
       "      <td>0.027554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>POINT (-28.02917 39.09109)</td>\n",
       "      <td>0.007563</td>\n",
       "      <td>0.007563</td>\n",
       "      <td>3.650604e-07</td>\n",
       "      <td>0.004827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>POINT (-149.88000 70.49950)</td>\n",
       "      <td>0.013467</td>\n",
       "      <td>0.013468</td>\n",
       "      <td>3.439117e-08</td>\n",
       "      <td>0.000255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POINT (-97.48562 36.60518)</td>\n",
       "      <td>0.011034</td>\n",
       "      <td>0.011034</td>\n",
       "      <td>4.619126e-07</td>\n",
       "      <td>0.004186</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>POINT (40.19450 -2.99600)</td>\n",
       "      <td>0.002979</td>\n",
       "      <td>0.002980</td>\n",
       "      <td>2.042769e-07</td>\n",
       "      <td>0.006856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>POINT (-114.37625 62.45130)</td>\n",
       "      <td>0.014462</td>\n",
       "      <td>0.014462</td>\n",
       "      <td>-7.643789e-08</td>\n",
       "      <td>-0.000529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>POINT (126.93479 37.56443)</td>\n",
       "      <td>0.184404</td>\n",
       "      <td>0.184427</td>\n",
       "      <td>2.291842e-05</td>\n",
       "      <td>0.012427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>POINT (-0.88235 41.63340)</td>\n",
       "      <td>0.018486</td>\n",
       "      <td>0.018484</td>\n",
       "      <td>-1.265558e-06</td>\n",
       "      <td>-0.006847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>POINT (8.99023 13.77668)</td>\n",
       "      <td>0.900909</td>\n",
       "      <td>0.901096</td>\n",
       "      <td>1.867402e-04</td>\n",
       "      <td>0.020724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>POINT (36.77500 55.69500)</td>\n",
       "      <td>0.013143</td>\n",
       "      <td>0.013144</td>\n",
       "      <td>5.505649e-07</td>\n",
       "      <td>0.004189</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>366 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        geometry  providentia       nes  absolute_difference  \\\n",
       "FID                                                                            \n",
       "0     POINT (109.62880 40.85170)     0.504757  0.504896         1.391183e-04   \n",
       "1     POINT (-28.02917 39.09109)     0.007563  0.007563         3.650604e-07   \n",
       "2    POINT (-149.88000 70.49950)     0.013467  0.013468         3.439117e-08   \n",
       "3     POINT (-97.48562 36.60518)     0.011034  0.011034         4.619126e-07   \n",
       "4      POINT (40.19450 -2.99600)     0.002979  0.002980         2.042769e-07   \n",
       "..                           ...          ...       ...                  ...   \n",
       "361  POINT (-114.37625 62.45130)     0.014462  0.014462        -7.643789e-08   \n",
       "362   POINT (126.93479 37.56443)     0.184404  0.184427         2.291842e-05   \n",
       "363    POINT (-0.88235 41.63340)     0.018486  0.018484        -1.265558e-06   \n",
       "364     POINT (8.99023 13.77668)     0.900909  0.901096         1.867402e-04   \n",
       "365    POINT (36.77500 55.69500)     0.013143  0.013144         5.505649e-07   \n",
       "\n",
       "     relative_difference  \n",
       "FID                       \n",
       "0               0.027554  \n",
       "1               0.004827  \n",
       "2               0.000255  \n",
       "3               0.004186  \n",
       "4               0.006856  \n",
       "..                   ...  \n",
       "361            -0.000529  \n",
       "362             0.012427  \n",
       "363            -0.006847  \n",
       "364             0.020724  \n",
       "365             0.004189  \n",
       "\n",
       "[366 rows x 5 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdf_diff['relative_difference'] = (gdf_diff['nes'] - gdf_diff['providentia'])*100/gdf_diff['nes']\n",
    "gdf_diff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "[encoded data, 224116 characters]",
      "text/plain": [
       "<Figure size 1440x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_4, ax_4 = plt.subplots(1, figsize=(20, 7))\n",
    "\n",
    "gdf_model.plot(ax=ax_4, column='od550du', cmap='viridis', vmin=0, vmax=3)\n",
    "\n",
    "gdf_earth.plot(ax=ax_4, facecolor=\"none\", edgecolor='white', lw=0.5)\n",
    "\n",
    "gdf_diff.plot(ax=ax_4, column='relative_difference', cmap='bwr', edgecolor='black', legend=True, lw=0.5, vmax = 7)\n",
    "\n",
    "ax_4.axhline(y=0, color='black')\n",
    "\n",
    "ax_4.margins(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.19982211142673692"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdf_diff['relative_difference'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.944350654874811"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdf_diff['relative_difference'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "      <th>providentia</th>\n",
       "      <th>nes</th>\n",
       "      <th>absolute_difference</th>\n",
       "      <th>relative_difference</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>306</th>\n",
       "      <td>POINT (103.78038 1.29767)</td>\n",
       "      <td>0.001023</td>\n",
       "      <td>0.001099</td>\n",
       "      <td>0.000076</td>\n",
       "      <td>6.944351</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      geometry  providentia       nes  absolute_difference  \\\n",
       "FID                                                                          \n",
       "306  POINT (103.78038 1.29767)     0.001023  0.001099             0.000076   \n",
       "\n",
       "     relative_difference  \n",
       "FID                       \n",
       "306             6.944351  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdf_diff.loc[gdf_diff['relative_difference'] == gdf_diff['relative_difference'].max()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 6.1.3. Scatter plots between interpolated values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f50feb530d0>"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "[encoded data, 7016 characters]",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(gdf_diff['providentia'], gdf_diff['nes'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 6.1.4. Scatter plots between interpolated values and observations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f50fe478510>"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "[encoded data, 6088 characters]",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(gdf_diff['nes'], gdf_diff['obs'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f50fe478790>"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "[encoded data, 6088 characters]",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(gdf_diff['providentia'], gdf_diff['obs'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.2. Numeric comparison"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 6.2.1. Add model data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "      <th>model</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>POLYGON ((-180.70312 -90.50000, -179.29688 -90...</td>\n",
       "      <td>0.000144</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>POLYGON ((-179.29688 -90.50000, -177.89062 -90...</td>\n",
       "      <td>0.000144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>POLYGON ((-177.89062 -90.50000, -176.48438 -90...</td>\n",
       "      <td>0.000144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POLYGON ((-176.48438 -90.50000, -175.07812 -90...</td>\n",
       "      <td>0.000144</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>POLYGON ((-175.07812 -90.50000, -173.67188 -90...</td>\n",
       "      <td>0.000144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>46512</th>\n",
       "      <td>POLYGON ((173.67188 89.50000, 175.07812 89.500...</td>\n",
       "      <td>0.023041</td>\n",
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       "    <tr>\n",
       "      <th>46513</th>\n",
       "      <td>POLYGON ((175.07812 89.50000, 176.48438 89.500...</td>\n",
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       "      <th>46514</th>\n",
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       "    <tr>\n",
       "      <th>46515</th>\n",
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       "      <td>0.023041</td>\n",
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       "    <tr>\n",
       "      <th>46516</th>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>46517 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                geometry     model\n",
       "FID                                                               \n",
       "0      POLYGON ((-180.70312 -90.50000, -179.29688 -90...  0.000144\n",
       "1      POLYGON ((-179.29688 -90.50000, -177.89062 -90...  0.000144\n",
       "2      POLYGON ((-177.89062 -90.50000, -176.48438 -90...  0.000144\n",
       "3      POLYGON ((-176.48438 -90.50000, -175.07812 -90...  0.000144\n",
       "4      POLYGON ((-175.07812 -90.50000, -173.67188 -90...  0.000144\n",
       "...                                                  ...       ...\n",
       "46512  POLYGON ((173.67188 89.50000, 175.07812 89.500...  0.023041\n",
       "46513  POLYGON ((175.07812 89.50000, 176.48438 89.500...  0.023041\n",
       "46514  POLYGON ((176.48438 89.50000, 177.89062 89.500...  0.023041\n",
       "46515  POLYGON ((177.89062 89.50000, 179.29688 89.500...  0.023041\n",
       "46516  POLYGON ((179.29688 89.50000, 180.70312 89.500...  0.023041\n",
       "\n",
       "[46517 rows x 2 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdf_eval = copy.deepcopy(gdf_model)\n",
    "gdf_eval.rename(columns={'od550du': 'model'}, inplace=True)\n",
    "gdf_eval"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 6.2.2. Add observations data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<p>366 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                geometry     model  obs\n",
       "FID                                                                    \n",
       "9587   POLYGON ((-71.01562 -53.50000, -69.60938 -53.5...  0.000458  NaN\n",
       "9845   POLYGON ((-69.60938 -52.50000, -68.20312 -52.5...  0.000429  NaN\n",
       "11388  POLYGON ((-68.20312 -46.50000, -66.79688 -46.5...  0.000508  NaN\n",
       "12161  POLYGON ((-65.39062 -43.50000, -63.98438 -43.5...  0.001136  NaN\n",
       "13187  POLYGON ((-68.20312 -39.50000, -66.79688 -39.5...  0.002681  NaN\n",
       "...                                                  ...       ...  ...\n",
       "41394  POLYGON ((-156.79688 70.50000, -155.39062 70.5...  0.013695  NaN\n",
       "42998  POLYGON ((-69.60938 76.50000, -68.20312 76.500...  0.013201  NaN\n",
       "43058  POLYGON ((14.76562 76.50000, 16.17188 76.50000...  0.017579  NaN\n",
       "43569  POLYGON ((10.54688 78.50000, 11.95312 78.50000...  0.013934  NaN\n",
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       "\n",
       "[366 rows x 3 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdf_eval = gdf_eval.sjoin(data_obs.shapefile.rename(columns={'od550aero': 'obs'}))\n",
    "gdf_eval = gdf_eval.drop(columns=['index_right'])\n",
    "gdf_eval"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 6.2.3. Add NES data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>0.011703</td>\n",
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       "<p>512 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                geometry     model  obs  \\\n",
       "FID                                                                       \n",
       "9587   POLYGON ((-71.01562 -53.50000, -69.60938 -53.5...  0.000458  NaN   \n",
       "9845   POLYGON ((-69.60938 -52.50000, -68.20312 -52.5...  0.000429  NaN   \n",
       "11388  POLYGON ((-68.20312 -46.50000, -66.79688 -46.5...  0.000508  NaN   \n",
       "12161  POLYGON ((-65.39062 -43.50000, -63.98438 -43.5...  0.001136  NaN   \n",
       "13187  POLYGON ((-68.20312 -39.50000, -66.79688 -39.5...  0.002681  NaN   \n",
       "...                                                  ...       ...  ...   \n",
       "41394  POLYGON ((-156.79688 70.50000, -155.39062 70.5...  0.013695  NaN   \n",
       "42998  POLYGON ((-69.60938 76.50000, -68.20312 76.500...  0.013201  NaN   \n",
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       "43757  POLYGON ((-86.48438 79.50000, -85.07812 79.500...  0.011777  NaN   \n",
       "\n",
       "            nes  \n",
       "FID              \n",
       "9587   0.000420  \n",
       "9845   0.000441  \n",
       "11388  0.000532  \n",
       "12161  0.001565  \n",
       "13187  0.001954  \n",
       "...         ...  \n",
       "41394  0.013110  \n",
       "42998  0.013245  \n",
       "43058  0.017365  \n",
       "43569  0.014070  \n",
       "43757  0.011703  \n",
       "\n",
       "[512 rows x 4 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "gdf_eval = gdf_eval.sjoin(gdf_nes.rename(columns={'od550du': 'nes'}))\n",
    "gdf_eval = gdf_eval.drop(columns=['index_right'])\n",
    "gdf_eval"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 6.2.4. Add Providentia Interpolation data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
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       "                                                geometry     model  obs  \\\n",
       "FID                                                                       \n",
       "9587   POLYGON ((-71.01562 -53.50000, -69.60938 -53.5...  0.000458  NaN   \n",
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       "13187  POLYGON ((-68.20312 -39.50000, -66.79688 -39.5...  0.002681  NaN   \n",
       "...                                                  ...       ...  ...   \n",
       "41394  POLYGON ((-156.79688 70.50000, -155.39062 70.5...  0.013695  NaN   \n",
       "42998  POLYGON ((-69.60938 76.50000, -68.20312 76.500...  0.013201  NaN   \n",
       "43058  POLYGON ((14.76562 76.50000, 16.17188 76.50000...  0.017579  NaN   \n",
       "43569  POLYGON ((10.54688 78.50000, 11.95312 78.50000...  0.013934  NaN   \n",
       "43757  POLYGON ((-86.48438 79.50000, -85.07812 79.500...  0.011777  NaN   \n",
       "\n",
       "            nes  providentia  \n",
       "FID                           \n",
       "9587   0.000420     0.000420  \n",
       "9845   0.000441     0.000441  \n",
       "11388  0.000532     0.000532  \n",
       "12161  0.001565     0.001565  \n",
       "13187  0.001954     0.001954  \n",
       "...         ...          ...  \n",
       "41394  0.013110     0.013110  \n",
       "42998  0.013245     0.013245  \n",
       "43058  0.017365     0.017365  \n",
       "43569  0.014070     0.014070  \n",
       "43757  0.011703     0.011703  \n",
       "\n",
       "[954 rows x 5 columns]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdf_eval = gdf_eval.sjoin(gdf_prv_after.rename(columns={'od550aero': 'providentia'}))\n",
    "gdf_eval = gdf_eval.drop(columns=['index_right'])\n",
    "gdf_eval"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 6.2.5. Calculate relative difference between NES and Providentia"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>geometry</th>\n",
       "      <th>model</th>\n",
       "      <th>obs</th>\n",
       "      <th>nes</th>\n",
       "      <th>providentia</th>\n",
       "      <th>nes-prov</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9587</th>\n",
       "      <td>POLYGON ((-71.01562 -53.50000, -69.60938 -53.5...</td>\n",
       "      <td>0.000458</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000420</td>\n",
       "      <td>0.000420</td>\n",
       "      <td>0.000568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9845</th>\n",
       "      <td>POLYGON ((-69.60938 -52.50000, -68.20312 -52.5...</td>\n",
       "      <td>0.000429</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000441</td>\n",
       "      <td>0.000441</td>\n",
       "      <td>0.001709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11388</th>\n",
       "      <td>POLYGON ((-68.20312 -46.50000, -66.79688 -46.5...</td>\n",
       "      <td>0.000508</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000532</td>\n",
       "      <td>0.000532</td>\n",
       "      <td>0.014902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12161</th>\n",
       "      <td>POLYGON ((-65.39062 -43.50000, -63.98438 -43.5...</td>\n",
       "      <td>0.001136</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.001565</td>\n",
       "      <td>0.001565</td>\n",
       "      <td>-0.011830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13187</th>\n",
       "      <td>POLYGON ((-68.20312 -39.50000, -66.79688 -39.5...</td>\n",
       "      <td>0.002681</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.001954</td>\n",
       "      <td>0.001954</td>\n",
       "      <td>0.001149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>41394</th>\n",
       "      <td>POLYGON ((-156.79688 70.50000, -155.39062 70.5...</td>\n",
       "      <td>0.013695</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.013110</td>\n",
       "      <td>0.013110</td>\n",
       "      <td>0.000853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42998</th>\n",
       "      <td>POLYGON ((-69.60938 76.50000, -68.20312 76.500...</td>\n",
       "      <td>0.013201</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.013245</td>\n",
       "      <td>0.013245</td>\n",
       "      <td>0.000210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43058</th>\n",
       "      <td>POLYGON ((14.76562 76.50000, 16.17188 76.50000...</td>\n",
       "      <td>0.017579</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.017365</td>\n",
       "      <td>0.017365</td>\n",
       "      <td>0.000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43569</th>\n",
       "      <td>POLYGON ((10.54688 78.50000, 11.95312 78.50000...</td>\n",
       "      <td>0.013934</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.014070</td>\n",
       "      <td>0.014070</td>\n",
       "      <td>-0.000013</td>\n",
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       "    <tr>\n",
       "      <th>43757</th>\n",
       "      <td>POLYGON ((-86.48438 79.50000, -85.07812 79.500...</td>\n",
       "      <td>0.011777</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.011703</td>\n",
       "      <td>0.011703</td>\n",
       "      <td>-0.000004</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>954 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                geometry     model  obs  \\\n",
       "FID                                                                       \n",
       "9587   POLYGON ((-71.01562 -53.50000, -69.60938 -53.5...  0.000458  NaN   \n",
       "9845   POLYGON ((-69.60938 -52.50000, -68.20312 -52.5...  0.000429  NaN   \n",
       "11388  POLYGON ((-68.20312 -46.50000, -66.79688 -46.5...  0.000508  NaN   \n",
       "12161  POLYGON ((-65.39062 -43.50000, -63.98438 -43.5...  0.001136  NaN   \n",
       "13187  POLYGON ((-68.20312 -39.50000, -66.79688 -39.5...  0.002681  NaN   \n",
       "...                                                  ...       ...  ...   \n",
       "41394  POLYGON ((-156.79688 70.50000, -155.39062 70.5...  0.013695  NaN   \n",
       "42998  POLYGON ((-69.60938 76.50000, -68.20312 76.500...  0.013201  NaN   \n",
       "43058  POLYGON ((14.76562 76.50000, 16.17188 76.50000...  0.017579  NaN   \n",
       "43569  POLYGON ((10.54688 78.50000, 11.95312 78.50000...  0.013934  NaN   \n",
       "43757  POLYGON ((-86.48438 79.50000, -85.07812 79.500...  0.011777  NaN   \n",
       "\n",
       "            nes  providentia  nes-prov  \n",
       "FID                                     \n",
       "9587   0.000420     0.000420  0.000568  \n",
       "9845   0.000441     0.000441  0.001709  \n",
       "11388  0.000532     0.000532  0.014902  \n",
       "12161  0.001565     0.001565 -0.011830  \n",
       "13187  0.001954     0.001954  0.001149  \n",
       "...         ...          ...       ...  \n",
       "41394  0.013110     0.013110  0.000853  \n",
       "42998  0.013245     0.013245  0.000210  \n",
       "43058  0.017365     0.017365  0.000002  \n",
       "43569  0.014070     0.014070 -0.000013  \n",
       "43757  0.011703     0.011703 -0.000004  \n",
       "\n",
       "[954 rows x 6 columns]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdf_eval['nes-prov'] = (gdf_eval['nes'] - gdf_eval['providentia'])*100 / gdf_eval['nes']\n",
    "gdf_eval"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "31.73012028502732"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Difference is higher now because we have used spatial joins (nearest 1 neighbour vs nearest 4)\n",
    "gdf_eval['nes-prov'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-46.491689814524314"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Difference is higher now because we have used spatial joins (nearest 1 neighbour vs nearest 4)\n",
    "gdf_eval['nes-prov'].min()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 6.2.6. Scatter plot between model and interpolated values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f50fefa5cd0>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "[encoded data, 7456 characters]",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(gdf_eval['providentia'], gdf_eval['model'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f50fea7c9d0>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "[encoded data, 7460 characters]",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(gdf_eval['nes'], gdf_eval['model'])"
   ]
  }
 ],
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