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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Using masks and computing weighted average"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This example is based from xarray example http://xarray.pydata.org/en/stable/examples/area_weighted_temperature.html"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import python packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "xr.set_options(display_style='html')\n",
    "import intake\n",
    "import matplotlib.pyplot as plt\n",
    "import cartopy.crs as ccrs\n",
    "import numpy as np\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<p><strong>pangeo-cmip6 catalog with 7674 dataset(s) from 514818 asset(s)</strong>:</p> <div>\n",
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>unique</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>activity_id</th>\n",
       "      <td>18</td>\n",
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       "    <tr>\n",
       "      <th>institution_id</th>\n",
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       "    <tr>\n",
       "      <th>grid_label</th>\n",
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       "    <tr>\n",
       "      <th>zstore</th>\n",
       "      <td>514818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dcpp_init_year</th>\n",
       "      <td>60</td>\n",
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       "    <tr>\n",
       "      <th>version</th>\n",
       "      <td>736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>derived_variable_id</th>\n",
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       "</table>\n",
       "</div>"
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   ],
   "source": [
    "cat_url = \"https://storage.googleapis.com/cmip6/pangeo-cmip6.json\"\n",
    "col = intake.open_esm_datastore(cat_url)\n",
    "col"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Search data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "      <th>activity_id</th>\n",
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       "      <th>experiment_id</th>\n",
       "      <th>member_id</th>\n",
       "      <th>table_id</th>\n",
       "      <th>variable_id</th>\n",
       "      <th>grid_label</th>\n",
       "      <th>zstore</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CMIP</td>\n",
       "      <td>NCC</td>\n",
       "      <td>NorESM2-LM</td>\n",
       "      <td>historical</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>Amon</td>\n",
       "      <td>tas</td>\n",
       "      <td>gn</td>\n",
       "      <td>gs://cmip6/CMIP6/CMIP/NCC/NorESM2-LM/historica...</td>\n",
       "      <td>NaN</td>\n",
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       "  activity_id institution_id   source_id experiment_id member_id table_id  \\\n",
       "0        CMIP            NCC  NorESM2-LM    historical  r1i1p1f1     Amon   \n",
       "\n",
       "  variable_id grid_label                                             zstore  \\\n",
       "0         tas         gn  gs://cmip6/CMIP6/CMIP/NCC/NorESM2-LM/historica...   \n",
       "\n",
       "   dcpp_init_year   version  \n",
       "0             NaN  20190815  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cat = col.search(source_id=['NorESM2-LM'], experiment_id=['historical'], table_id=['Amon'], variable_id=['tas'], member_id=['r1i1p1f1'])\n",
    "cat.df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create dictionary from the list of datasets we found\n",
    "- This step may take several minutes so be patient!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--> The keys in the returned dictionary of datasets are constructed as follows:\n",
      "\t'activity_id.institution_id.source_id.experiment_id.table_id.grid_label'\n"
     ]
    },
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       "['CMIP.NCC.NorESM2-LM.historical.Amon.gn']"
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   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-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",
       ".xr-no-icon {\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; Size: 110MB\n",
       "Dimensions:         (lat: 96, bnds: 2, lon: 144, member_id: 1,\n",
       "                     dcpp_init_year: 1, time: 1980)\n",
       "Coordinates:\n",
       "    height          float64 8B ...\n",
       "  * lat             (lat) float64 768B -90.0 -88.11 -86.21 ... 86.21 88.11 90.0\n",
       "    lat_bnds        (lat, bnds) float64 2kB dask.array&lt;chunksize=(96, 2), meta=np.ndarray&gt;\n",
       "  * lon             (lon) float64 1kB 0.0 2.5 5.0 7.5 ... 352.5 355.0 357.5\n",
       "    lon_bnds        (lon, bnds) float64 2kB dask.array&lt;chunksize=(144, 2), meta=np.ndarray&gt;\n",
       "  * time            (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:...\n",
       "    time_bnds       (time, bnds) object 32kB dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;\n",
       "  * member_id       (member_id) object 8B &#x27;r1i1p1f1&#x27;\n",
       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 109MB dask.array&lt;chunksize=(1, 1, 990, 96, 144), meta=np.ndarray&gt;\n",
       "Attributes: (12/65)\n",
       "    Conventions:                      CF-1.7 CMIP-6.2\n",
       "    activity_id:                      CMIP\n",
       "    branch_method:                    Hybrid-restart from year 1600-01-01 of ...\n",
       "    branch_time:                      0.0\n",
       "    branch_time_in_child:             0.0\n",
       "    branch_time_in_parent:            430335.0\n",
       "    ...                               ...\n",
       "    intake_esm_attrs:variable_id:     tas\n",
       "    intake_esm_attrs:grid_label:      gn\n",
       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCC/NorESM2-LM/hi...\n",
       "    intake_esm_attrs:version:         20190815\n",
       "    intake_esm_attrs:_data_format_:   zarr\n",
       "    intake_esm_dataset_key:           CMIP.NCC.NorESM2-LM.historical.Amon.gn</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6924334a-a063-4ff0-bc1c-e3bf01f9ebb2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6924334a-a063-4ff0-bc1c-e3bf01f9ebb2' 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'>lat</span>: 96</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 144</li><li><span class='xr-has-index'>member_id</span>: 1</li><li><span class='xr-has-index'>dcpp_init_year</span>: 1</li><li><span class='xr-has-index'>time</span>: 1980</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8ae84ad6-cfc6-4049-b783-d13907e8e7ff' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8ae84ad6-cfc6-4049-b783-d13907e8e7ff' class='xr-section-summary' >Coordinates: <span>(9)</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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5bc17ab4-f22a-4631-a123-3e473a3aff96' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5bc17ab4-f22a-4631-a123-3e473a3aff96' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e34a04ac-af0f-4b78-9714-8c0cc39f1c3a' class='xr-var-data-in' type='checkbox'><label for='data-e34a04ac-af0f-4b78-9714-8c0cc39f1c3a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Z</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</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 -88.11 -86.21 ... 88.11 90.0</div><input id='attrs-7f9f060d-b44e-4d4e-b1b0-4b4daea7506d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f9f060d-b44e-4d4e-b1b0-4b4daea7506d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-550fd257-880d-42c7-905d-ea0fe508c66c' class='xr-var-data-in' type='checkbox'><label for='data-550fd257-880d-42c7-905d-ea0fe508c66c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -88.105263, -86.210526, -84.315789, -82.421053, -80.526316,\n",
       "       -78.631579, -76.736842, -74.842105, -72.947368, -71.052632, -69.157895,\n",
       "       -67.263158, -65.368421, -63.473684, -61.578947, -59.684211, -57.789474,\n",
       "       -55.894737, -54.      , -52.105263, -50.210526, -48.315789, -46.421053,\n",
       "       -44.526316, -42.631579, -40.736842, -38.842105, -36.947368, -35.052632,\n",
       "       -33.157895, -31.263158, -29.368421, -27.473684, -25.578947, -23.684211,\n",
       "       -21.789474, -19.894737, -18.      , -16.105263, -14.210526, -12.315789,\n",
       "       -10.421053,  -8.526316,  -6.631579,  -4.736842,  -2.842105,  -0.947368,\n",
       "         0.947368,   2.842105,   4.736842,   6.631579,   8.526316,  10.421053,\n",
       "        12.315789,  14.210526,  16.105263,  18.      ,  19.894737,  21.789474,\n",
       "        23.684211,  25.578947,  27.473684,  29.368421,  31.263158,  33.157895,\n",
       "        35.052632,  36.947368,  38.842105,  40.736842,  42.631579,  44.526316,\n",
       "        46.421053,  48.315789,  50.210526,  52.105263,  54.      ,  55.894737,\n",
       "        57.789474,  59.684211,  61.578947,  63.473684,  65.368421,  67.263158,\n",
       "        69.157895,  71.052632,  72.947368,  74.842105,  76.736842,  78.631579,\n",
       "        80.526316,  82.421053,  84.315789,  86.210526,  88.105263,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(96, 2), meta=np.ndarray&gt;</div><input id='attrs-3f1215ef-af08-4501-8a9c-2ab03ebd09fa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3f1215ef-af08-4501-8a9c-2ab03ebd09fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb031fce-74c9-45c2-b6eb-1a8d037b47bb' class='xr-var-data-in' type='checkbox'><label for='data-fb031fce-74c9-45c2-b6eb-1a8d037b47bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 1.50 kiB </td>\n",
       "                        <td> 1.50 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (96, 2) </td>\n",
       "                        <td> (96, 2) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"79\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"29\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"29\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"29\" y1=\"0\" x2=\"29\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 29.2612335534925,0.0 29.2612335534925,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"14.630617\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
       "  <text x=\"49.261234\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,49.261234,60.000000)\">96</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></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'>0.0 2.5 5.0 ... 352.5 355.0 357.5</div><input id='attrs-97becfc2-44b7-4a36-b7e9-63b473fb14b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-97becfc2-44b7-4a36-b7e9-63b473fb14b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65905ed5-4890-453d-829c-1c652edebebd' class='xr-var-data-in' type='checkbox'><label for='data-65905ed5-4890-453d-829c-1c652edebebd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([  0. ,   2.5,   5. ,   7.5,  10. ,  12.5,  15. ,  17.5,  20. ,  22.5,\n",
       "        25. ,  27.5,  30. ,  32.5,  35. ,  37.5,  40. ,  42.5,  45. ,  47.5,\n",
       "        50. ,  52.5,  55. ,  57.5,  60. ,  62.5,  65. ,  67.5,  70. ,  72.5,\n",
       "        75. ,  77.5,  80. ,  82.5,  85. ,  87.5,  90. ,  92.5,  95. ,  97.5,\n",
       "       100. , 102.5, 105. , 107.5, 110. , 112.5, 115. , 117.5, 120. , 122.5,\n",
       "       125. , 127.5, 130. , 132.5, 135. , 137.5, 140. , 142.5, 145. , 147.5,\n",
       "       150. , 152.5, 155. , 157.5, 160. , 162.5, 165. , 167.5, 170. , 172.5,\n",
       "       175. , 177.5, 180. , 182.5, 185. , 187.5, 190. , 192.5, 195. , 197.5,\n",
       "       200. , 202.5, 205. , 207.5, 210. , 212.5, 215. , 217.5, 220. , 222.5,\n",
       "       225. , 227.5, 230. , 232.5, 235. , 237.5, 240. , 242.5, 245. , 247.5,\n",
       "       250. , 252.5, 255. , 257.5, 260. , 262.5, 265. , 267.5, 270. , 272.5,\n",
       "       275. , 277.5, 280. , 282.5, 285. , 287.5, 290. , 292.5, 295. , 297.5,\n",
       "       300. , 302.5, 305. , 307.5, 310. , 312.5, 315. , 317.5, 320. , 322.5,\n",
       "       325. , 327.5, 330. , 332.5, 335. , 337.5, 340. , 342.5, 345. , 347.5,\n",
       "       350. , 352.5, 355. , 357.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(144, 2), meta=np.ndarray&gt;</div><input id='attrs-a25eb002-fd3d-40ce-99cd-57704562a8dd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a25eb002-fd3d-40ce-99cd-57704562a8dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fcf1ded4-be3a-44e5-94c2-fa04e1951ac4' class='xr-var-data-in' type='checkbox'><label for='data-fcf1ded4-be3a-44e5-94c2-fa04e1951ac4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 2.25 kiB </td>\n",
       "                        <td> 2.25 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (144, 2) </td>\n",
       "                        <td> (144, 2) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"77\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"27\" y2=\"0\" style=\"stroke-width:2\" />\n",
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       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"27\" y1=\"0\" x2=\"27\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
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       "  <polygon points=\"0.0,0.0 27.054035963169408,0.0 27.054035963169408,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"13.527018\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
       "  <text x=\"47.054036\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,47.054036,60.000000)\">144</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-16 12:00:00 ... 2014-12-...</div><input id='attrs-bfa2d874-e6fb-471b-b432-fe4a7d04a492' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfa2d874-e6fb-471b-b432-fe4a7d04a492' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8cfde929-11a9-4154-b4df-919abc3c7442' class='xr-var-data-in' type='checkbox'><label for='data-8cfde929-11a9-4154-b4df-919abc3c7442' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(1850, 2, 15, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(1850, 3, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       ...,\n",
       "       cftime.DatetimeNoLeap(2014, 10, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2014, 11, 16, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2014, 12, 16, 12, 0, 0, 0, has_year_zero=True)],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;</div><input id='attrs-bc3d8d24-43d0-4d84-9cc5-e7667c22d6e9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bc3d8d24-43d0-4d84-9cc5-e7667c22d6e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a780c960-819a-428f-ba70-9438d3be167f' class='xr-var-data-in' type='checkbox'><label for='data-a780c960-819a-428f-ba70-9438d3be167f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 30.94 kiB </td>\n",
       "                        <td> 30.94 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1980, 2) </td>\n",
       "                        <td> (1980, 2) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
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       "\n",
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       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
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       "\n",
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       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">1980</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>member_id</span></div><div class='xr-var-dims'>(member_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-e45898e8-b3b2-42ee-84aa-9ed4f97d90fb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e45898e8-b3b2-42ee-84aa-9ed4f97d90fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e327270-468e-4f8d-b16a-2d2b5f9ca070' class='xr-var-data-in' type='checkbox'><label for='data-0e327270-468e-4f8d-b16a-2d2b5f9ca070' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;r1i1p1f1&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dcpp_init_year</span></div><div class='xr-var-dims'>(dcpp_init_year)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-07673a72-0370-4f8d-a4ea-6d91bd5a9be4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-07673a72-0370-4f8d-a4ea-6d91bd5a9be4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d22c7e63-1ced-4d5e-97dd-a1cc6efc206a' class='xr-var-data-in' type='checkbox'><label for='data-d22c7e63-1ced-4d5e-97dd-a1cc6efc206a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7c8614c9-507f-4811-800b-d213696d7e04' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7c8614c9-507f-4811-800b-d213696d7e04' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tas</span></div><div class='xr-var-dims'>(member_id, dcpp_init_year, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 1, 990, 96, 144), meta=np.ndarray&gt;</div><input id='attrs-84464e14-7271-4bbe-9985-41c74f0781cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-84464e14-7271-4bbe-9985-41c74f0781cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7e48d3e-0834-4cc1-8be0-1259cd0e81f1' class='xr-var-data-in' type='checkbox'><label for='data-b7e48d3e-0834-4cc1-8be0-1259cd0e81f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>cell_methods :</span></dt><dd>area: time: mean</dd><dt><span>comment :</span></dt><dd>near-surface (usually, 2 meter) air temperature</dd><dt><span>history :</span></dt><dd>2019-08-15T12:42:20Z altered by CMOR: Treated scalar dimension: &#x27;height&#x27;. 2019-08-15T12:42:21Z altered by CMOR: Converted type from &#x27;d&#x27; to &#x27;f&#x27;.</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>original_name :</span></dt><dd>TREFHT</dd><dt><span>standard_name :</span></dt><dd>air_temperature</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 104.41 MiB </td>\n",
       "                        <td> 52.21 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1, 1, 1980, 96, 144) </td>\n",
       "                        <td> (1, 1, 990, 96, 144) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"347\" height=\"154\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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       "  <text x=\"120.294118\" y=\"89.606646\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,120.294118,89.606646)\">1980</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-5491c40a-b7e8-46f4-ae03-be864cbe7dd5' class='xr-section-summary-in' type='checkbox'  ><label for='section-5491c40a-b7e8-46f4-ae03-be864cbe7dd5' class='xr-section-summary' >Indexes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f548cb6a-5dbc-460f-b4a9-8ae3901cc5b5' class='xr-index-data-in' type='checkbox'/><label for='index-f548cb6a-5dbc-460f-b4a9-8ae3901cc5b5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([              -90.0,  -88.10526315789474,  -86.21052631578948,\n",
       "         -84.3157894736842,  -82.42105263157895,  -80.52631578947368,\n",
       "        -78.63157894736842,  -76.73684210526316,  -74.84210526315789,\n",
       "        -72.94736842105263,  -71.05263157894737,  -69.15789473684211,\n",
       "        -67.26315789473685,  -65.36842105263158, -63.473684210526315,\n",
       "       -61.578947368421055, -59.684210526315795,  -57.78947368421053,\n",
       "        -55.89473684210527,               -54.0,  -52.10526315789474,\n",
       "        -50.21052631578947,  -48.31578947368421,  -46.42105263157895,\n",
       "       -44.526315789473685, -42.631578947368425,  -40.73684210526316,\n",
       "         -38.8421052631579,  -36.94736842105264,  -35.05263157894737,\n",
       "        -33.15789473684211, -31.263157894736842, -29.368421052631582,\n",
       "       -27.473684210526322, -25.578947368421055, -23.684210526315795,\n",
       "       -21.789473684210535,  -19.89473684210526,               -18.0,\n",
       "        -16.10526315789474,  -14.21052631578948,  -12.31578947368422,\n",
       "       -10.421052631578945,  -8.526315789473685,  -6.631578947368425,\n",
       "        -4.736842105263165, -2.8421052631579045, -0.9473684210526301,\n",
       "        0.9473684210526301,  2.8421052631578902,    4.73684210526315,\n",
       "         6.631578947368411,   8.526315789473685,  10.421052631578945,\n",
       "        12.315789473684205,  14.210526315789465,  16.105263157894726,\n",
       "                      18.0,   19.89473684210526,   21.78947368421052,\n",
       "         23.68421052631578,   25.57894736842104,  27.473684210526315,\n",
       "        29.368421052631575,  31.263157894736835,  33.157894736842096,\n",
       "        35.052631578947356,   36.94736842105263,   38.84210526315789,\n",
       "         40.73684210526315,   42.63157894736841,   44.52631578947367,\n",
       "         46.42105263157893,   48.31578947368419,   50.21052631578948,\n",
       "         52.10526315789474,                54.0,   55.89473684210526,\n",
       "         57.78947368421052,   59.68421052631578,   61.57894736842104,\n",
       "          63.4736842105263,   65.36842105263156,   67.26315789473682,\n",
       "         69.15789473684211,   71.05263157894737,   72.94736842105263,\n",
       "         74.84210526315789,   76.73684210526315,   78.63157894736841,\n",
       "         80.52631578947367,   82.42105263157893,   84.31578947368419,\n",
       "         86.21052631578945,   88.10526315789474,                90.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-19d716d8-0628-44c1-a4be-7a1372a2847b' class='xr-index-data-in' type='checkbox'/><label for='index-19d716d8-0628-44c1-a4be-7a1372a2847b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0.0,   2.5,   5.0,   7.5,  10.0,  12.5,  15.0,  17.5,  20.0,  22.5,\n",
       "       ...\n",
       "       335.0, 337.5, 340.0, 342.5, 345.0, 347.5, 350.0, 352.5, 355.0, 357.5],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=144))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cda53e4a-3edf-4d03-b7be-5dfb7b78cf0e' class='xr-index-data-in' type='checkbox'/><label for='index-cda53e4a-3edf-4d03-b7be-5dfb7b78cf0e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-16 12:00:00, 1850-02-15 00:00:00, 1850-03-16 12:00:00,\n",
       "             1850-04-16 00:00:00, 1850-05-16 12:00:00, 1850-06-16 00:00:00,\n",
       "             1850-07-16 12:00:00, 1850-08-16 12:00:00, 1850-09-16 00:00:00,\n",
       "             1850-10-16 12:00:00,\n",
       "             ...\n",
       "             2014-03-16 12:00:00, 2014-04-16 00:00:00, 2014-05-16 12:00:00,\n",
       "             2014-06-16 00:00:00, 2014-07-16 12:00:00, 2014-08-16 12:00:00,\n",
       "             2014-09-16 00:00:00, 2014-10-16 12:00:00, 2014-11-16 00:00:00,\n",
       "             2014-12-16 12:00:00],\n",
       "            dtype=&#x27;object&#x27;, length=1980, calendar=&#x27;noleap&#x27;, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>member_id</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9404ab5d-3120-4f19-82d0-302c62c130f6' class='xr-index-data-in' type='checkbox'/><label for='index-9404ab5d-3120-4f19-82d0-302c62c130f6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;r1i1p1f1&#x27;], dtype=&#x27;object&#x27;, name=&#x27;member_id&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dcpp_init_year</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e8394413-e6b1-4a2a-8ca8-786a591f365a' class='xr-index-data-in' type='checkbox'/><label for='index-e8394413-e6b1-4a2a-8ca8-786a591f365a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([nan], dtype=&#x27;float64&#x27;, name=&#x27;dcpp_init_year&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c3efa81d-f8eb-42d7-9afb-2e8d0761a4d5' class='xr-section-summary-in' type='checkbox'  ><label for='section-c3efa81d-f8eb-42d7-9afb-2e8d0761a4d5' class='xr-section-summary' >Attributes: <span>(65)</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 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>Hybrid-restart from year 1600-01-01 of piControl</dd><dt><span>branch_time :</span></dt><dd>0.0</dd><dt><span>branch_time_in_child :</span></dt><dd>0.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>430335.0</dd><dt><span>cmor_version :</span></dt><dd>3.5.0</dd><dt><span>contact :</span></dt><dd>Please send any requests or bug reports to noresm-ncc@met.no.</dd><dt><span>creation_date :</span></dt><dd>2019-08-15T12:42:21Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.31</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.NCC.NorESM2-LM.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>finite-volume grid with 1.9x2.5 degree lat/lon resolution</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>history :</span></dt><dd>2019-08-15T12:42:21Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 CMIP-6.2 and CF standards.</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>NorESM Climate modeling Consortium consisting of CICERO (Center for International Climate and Environmental Research, Oslo 0349), MET-Norway (Norwegian Meteorological Institute, Oslo 0313), NERSC (Nansen Environmental and Remote Sensing Center, Bergen 5006), NILU (Norwegian Institute for Air Research, Kjeller 2027), UiB (University of Bergen, Bergen 5007), UiO (University of Oslo, Oslo 0313) and UNI (Uni Research, Bergen 5008), Norway. Mailing address: NCC, c/o MET-Norway, Henrik Mohns plass 1, Oslo 0313, Norway</dd><dt><span>institution_id :</span></dt><dd>NCC</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by NCC is licensed under a Creative Commons Attribution ShareAlike 4.0 International License (https://creativecommons.org/licenses). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file) and at https:///pcmdi.llnl.gov/. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>model_id :</span></dt><dd>NorESM2-LM</dd><dt><span>nominal_resolution :</span></dt><dd>250 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>NorESM2-LM</dd><dt><span>parent_sub_experiment_id :</span></dt><dd>none</dd><dt><span>parent_time_units :</span></dt><dd>days since 0421-01-01</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>run_variant :</span></dt><dd>N/A</dd><dt><span>source :</span></dt><dd>NorESM2-LM (2017): \n",
       "aerosol: OsloAero\n",
       "atmos: CAM-OSLO (2 degree resolution; 144 x 96; 32 levels; top level 3 mb)\n",
       "atmosChem: OsloChemSimp\n",
       "land: CLM\n",
       "landIce: CISM\n",
       "ocean: MICOM (1 degree resolution; 360 x 384; 70 levels; top grid cell minimum 0-2.5 m [native model uses hybrid density and generic upper-layer coordinate interpolated to z-level for contributed data])\n",
       "ocnBgchem: HAMOCC\n",
       "seaIce: CICE</dd><dt><span>source_id :</span></dt><dd>NorESM2-LM</dd><dt><span>source_type :</span></dt><dd>AOGCM</dd><dt><span>status :</span></dt><dd>2020-04-30;created; by gcs.cmip6.ldeo@gmail.com</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>Amon</dd><dt><span>table_info :</span></dt><dd>Creation Date:(24 July 2019) MD5:08e314340b9dd440c36c1b8e484514f4</dd><dt><span>title :</span></dt><dd>NorESM2-LM output prepared for CMIP6</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/2486cf87-033c-4848-ab3e-e828c3b7c759\n",
       "hdl:21.14100/8d2ec216-30d3-4f90-8664-7cf75e29780b\n",
       "hdl:21.14100/9f798305-d0cf-4eac-89b0-b13dc25574ca\n",
       "hdl:21.14100/e0da9277-4784-446b-b3b5-ba33bb18cc3a\n",
       "hdl:21.14100/ca48487c-955a-4b15-9582-5ce55ce39c73\n",
       "hdl:21.14100/fc7602aa-fd09-49d8-94c6-e619622c211b\n",
       "hdl:21.14100/cd51a9c2-0a94-45b2-8d9b-59bcb3467214\n",
       "hdl:21.14100/9b7ad334-1217-4229-98e8-b5a9287c0e5e\n",
       "hdl:21.14100/043ca527-40c7-451f-990b-ccc94720f612\n",
       "hdl:21.14100/a9613498-ea0d-4be4-97e8-77661872798d\n",
       "hdl:21.14100/52699832-d86c-491b-a0a4-2f27d9ee4d69\n",
       "hdl:21.14100/358c4a18-33b2-4c44-bd30-f6125a4df63c\n",
       "hdl:21.14100/77254eaf-90ca-44e7-9a3c-763a840e188f\n",
       "hdl:21.14100/62aed49c-6ca5-4027-80fe-4ddd99af575a\n",
       "hdl:21.14100/83ffe172-769b-42b1-b979-b92d768f60fd\n",
       "hdl:21.14100/91a8c4e2-d33b-4b87-a978-0247d8112ef3\n",
       "hdl:21.14100/e8fb384f-d5a7-41e1-bf12-b8de3e2ffb80</dd><dt><span>variable_id :</span></dt><dd>tas</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>netcdf_tracking_ids :</span></dt><dd>hdl:21.14100/2486cf87-033c-4848-ab3e-e828c3b7c759\n",
       "hdl:21.14100/8d2ec216-30d3-4f90-8664-7cf75e29780b\n",
       "hdl:21.14100/9f798305-d0cf-4eac-89b0-b13dc25574ca\n",
       "hdl:21.14100/e0da9277-4784-446b-b3b5-ba33bb18cc3a\n",
       "hdl:21.14100/ca48487c-955a-4b15-9582-5ce55ce39c73\n",
       "hdl:21.14100/fc7602aa-fd09-49d8-94c6-e619622c211b\n",
       "hdl:21.14100/cd51a9c2-0a94-45b2-8d9b-59bcb3467214\n",
       "hdl:21.14100/9b7ad334-1217-4229-98e8-b5a9287c0e5e\n",
       "hdl:21.14100/043ca527-40c7-451f-990b-ccc94720f612\n",
       "hdl:21.14100/a9613498-ea0d-4be4-97e8-77661872798d\n",
       "hdl:21.14100/52699832-d86c-491b-a0a4-2f27d9ee4d69\n",
       "hdl:21.14100/358c4a18-33b2-4c44-bd30-f6125a4df63c\n",
       "hdl:21.14100/77254eaf-90ca-44e7-9a3c-763a840e188f\n",
       "hdl:21.14100/62aed49c-6ca5-4027-80fe-4ddd99af575a\n",
       "hdl:21.14100/83ffe172-769b-42b1-b979-b92d768f60fd\n",
       "hdl:21.14100/91a8c4e2-d33b-4b87-a978-0247d8112ef3\n",
       "hdl:21.14100/e8fb384f-d5a7-41e1-bf12-b8de3e2ffb80</dd><dt><span>version_id :</span></dt><dd>v20190815</dd><dt><span>intake_esm_vars :</span></dt><dd>[&#x27;tas&#x27;]</dd><dt><span>intake_esm_attrs:activity_id :</span></dt><dd>CMIP</dd><dt><span>intake_esm_attrs:institution_id :</span></dt><dd>NCC</dd><dt><span>intake_esm_attrs:source_id :</span></dt><dd>NorESM2-LM</dd><dt><span>intake_esm_attrs:experiment_id :</span></dt><dd>historical</dd><dt><span>intake_esm_attrs:member_id :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_attrs:table_id :</span></dt><dd>Amon</dd><dt><span>intake_esm_attrs:variable_id :</span></dt><dd>tas</dd><dt><span>intake_esm_attrs:grid_label :</span></dt><dd>gn</dd><dt><span>intake_esm_attrs:zstore :</span></dt><dd>gs://cmip6/CMIP6/CMIP/NCC/NorESM2-LM/historical/r1i1p1f1/Amon/tas/gn/v20190815/</dd><dt><span>intake_esm_attrs:version :</span></dt><dd>20190815</dd><dt><span>intake_esm_attrs:_data_format_ :</span></dt><dd>zarr</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCC.NorESM2-LM.historical.Amon.gn</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 110MB\n",
       "Dimensions:         (lat: 96, bnds: 2, lon: 144, member_id: 1,\n",
       "                     dcpp_init_year: 1, time: 1980)\n",
       "Coordinates:\n",
       "    height          float64 8B ...\n",
       "  * lat             (lat) float64 768B -90.0 -88.11 -86.21 ... 86.21 88.11 90.0\n",
       "    lat_bnds        (lat, bnds) float64 2kB dask.array<chunksize=(96, 2), meta=np.ndarray>\n",
       "  * lon             (lon) float64 1kB 0.0 2.5 5.0 7.5 ... 352.5 355.0 357.5\n",
       "    lon_bnds        (lon, bnds) float64 2kB dask.array<chunksize=(144, 2), meta=np.ndarray>\n",
       "  * time            (time) object 16kB 1850-01-16 12:00:00 ... 2014-12-16 12:...\n",
       "    time_bnds       (time, bnds) object 32kB dask.array<chunksize=(1980, 2), meta=np.ndarray>\n",
       "  * member_id       (member_id) object 8B 'r1i1p1f1'\n",
       "  * dcpp_init_year  (dcpp_init_year) float64 8B nan\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    tas             (member_id, dcpp_init_year, time, lat, lon) float32 109MB dask.array<chunksize=(1, 1, 990, 96, 144), meta=np.ndarray>\n",
       "Attributes: (12/65)\n",
       "    Conventions:                      CF-1.7 CMIP-6.2\n",
       "    activity_id:                      CMIP\n",
       "    branch_method:                    Hybrid-restart from year 1600-01-01 of ...\n",
       "    branch_time:                      0.0\n",
       "    branch_time_in_child:             0.0\n",
       "    branch_time_in_parent:            430335.0\n",
       "    ...                               ...\n",
       "    intake_esm_attrs:variable_id:     tas\n",
       "    intake_esm_attrs:grid_label:      gn\n",
       "    intake_esm_attrs:zstore:          gs://cmip6/CMIP6/CMIP/NCC/NorESM2-LM/hi...\n",
       "    intake_esm_attrs:version:         20190815\n",
       "    intake_esm_attrs:_data_format_:   zarr\n",
       "    intake_esm_dataset_key:           CMIP.NCC.NorESM2-LM.historical.Amon.gn"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dset = dset_dict[list(dset_dict.keys())[0]]\n",
    "dset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the first timestep"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<cartopy.mpl.feature_artist.FeatureArtist at 0x7f1e479d0c90>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "projection = ccrs.Mercator(central_longitude=-10)\n",
    "\n",
    "f, ax = plt.subplots(subplot_kw=dict(projection=projection))\n",
    "\n",
    "dset['tas'].isel(time=0).plot(transform=ccrs.PlateCarree(), cbar_kwargs=dict(shrink=0.7), cmap='coolwarm')\n",
    "ax.coastlines()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compute weighted mean\n",
    "\n",
    "1. Creating weights: for a rectangular grid the cosine of the latitude is proportional to the grid cell area.\n",
    "2. Compute weighted mean values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def computeWeightedMean(ds):\n",
    "    # Compute weights based on the xarray you pass\n",
    "    weights = np.cos(np.deg2rad(ds.lat))\n",
    "    weights.name = \"weights\"\n",
    "    # Compute weighted mean\n",
    "    air_weighted = ds.weighted(weights)\n",
    "    weighted_mean = air_weighted.mean((\"lon\", \"lat\"))\n",
    "    return weighted_mean"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compute weighted average over the entire globe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "weighted_mean = computeWeightedMean(dset)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparison with unweighted mean\n",
    "- We select a time range\n",
    "- Note how the weighted mean temperature is higher than the unweighted."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f1e47a58410>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weighted_mean['tas'].sel(time=slice('2000-01-01', '2010-01-01')).plot(label=\"weighted\")\n",
    "dset['tas'].sel(time=slice('2000-01-01', '2010-01-01')).mean((\"lon\", \"lat\")).plot(label=\"unweighted\")\n",
    "\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compute Weigted arctic average\n",
    "Let's try to also take only the data above 60$^\\circ$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "weighted_mean = computeWeightedMean(dset.where(dset['lat']>60.))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f1e46139ed0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weighted_mean['tas'].sel(time=slice('2000-01-01', '2010-01-01')).plot(label=\"weighted\")\n",
    "dset['tas'].where(dset['lat']>60.).sel(time=slice('2000-01-01', '2010-01-01')).mean((\"lon\", \"lat\")).plot(label=\"unweighted\")\n",
    "\n",
    "plt.legend()"
   ]
  }
 ],
 "metadata": {
  "jupytext": {
   "formats": "ipynb,md"
  },
  "kernelspec": {
   "display_name": "Python [conda env:pangeo-notebook]",
   "language": "python",
   "name": "conda-env-pangeo-notebook-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}