{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "dominant-indicator",
   "metadata": {},
   "source": [
    "# Regridding model data with xESMF"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "reflected-chambers",
   "metadata": {},
   "source": [
    "## Import python packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "novel-indicator",
   "metadata": {},
   "outputs": [],
   "source": [
    "# supress warnings\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore') # don't output warnings\n",
    "\n",
    "import os\n",
    "# import packages\n",
    "import xarray as xr\n",
    "xr.set_options(display_style='html')\n",
    "import intake\n",
    "import cftime\n",
    "import cartopy.crs as ccrs\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.path as mpath\n",
    "import numpy as np\n",
    "import xesmf as xe\n",
    "from cmcrameri import cm\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "conditional-configuration",
   "metadata": {},
   "source": [
    "## Open CMIP6 online catalog"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "formed-symbol",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<p><strong>pangeo-cmip6 catalog with 7619 dataset(s) from 517624 asset(s)</strong>:</p> <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>unique</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>activity_id</th>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>institution_id</th>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>source_id</th>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>experiment_id</th>\n",
       "      <td>170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>member_id</th>\n",
       "      <td>657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>table_id</th>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>variable_id</th>\n",
       "      <td>709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>grid_label</th>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zstore</th>\n",
       "      <td>517624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dcpp_init_year</th>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>version</th>\n",
       "      <td>710</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cat_url = \"https://storage.googleapis.com/cmip6/pangeo-cmip6.json\"\n",
    "col = intake.open_esm_datastore(cat_url)\n",
    "col"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "polyphonic-national",
   "metadata": {},
   "source": [
    "## Get data in xarray\n",
    "### Search od550aer variable dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "local-wrist",
   "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>activity_id</th>\n",
       "      <th>institution_id</th>\n",
       "      <th>source_id</th>\n",
       "      <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",
       "      <th>dcpp_init_year</th>\n",
       "      <th>version</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CMIP</td>\n",
       "      <td>NCAR</td>\n",
       "      <td>CESM2-WACCM</td>\n",
       "      <td>historical</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>AERmon</td>\n",
       "      <td>od550aer</td>\n",
       "      <td>gn</td>\n",
       "      <td>gs://cmip6/CMIP6/CMIP/NCAR/CESM2-WACCM/histori...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20190227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CMIP</td>\n",
       "      <td>NCAR</td>\n",
       "      <td>CESM2</td>\n",
       "      <td>historical</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>AERmon</td>\n",
       "      <td>od550aer</td>\n",
       "      <td>gn</td>\n",
       "      <td>gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20190308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CMIP</td>\n",
       "      <td>CCCma</td>\n",
       "      <td>CanESM5</td>\n",
       "      <td>historical</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>AERmon</td>\n",
       "      <td>od550aer</td>\n",
       "      <td>gn</td>\n",
       "      <td>gs://cmip6/CMIP6/CMIP/CCCma/CanESM5/historical...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20190429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CMIP</td>\n",
       "      <td>HAMMOZ-Consortium</td>\n",
       "      <td>MPI-ESM-1-2-HAM</td>\n",
       "      <td>historical</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>AERmon</td>\n",
       "      <td>od550aer</td>\n",
       "      <td>gn</td>\n",
       "      <td>gs://cmip6/CMIP6/CMIP/HAMMOZ-Consortium/MPI-ES...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20190627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CMIP</td>\n",
       "      <td>MPI-M</td>\n",
       "      <td>MPI-ESM1-2-HR</td>\n",
       "      <td>historical</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>AERmon</td>\n",
       "      <td>od550aer</td>\n",
       "      <td>gn</td>\n",
       "      <td>gs://cmip6/CMIP6/CMIP/MPI-M/MPI-ESM1-2-HR/hist...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20190710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>CMIP</td>\n",
       "      <td>MPI-M</td>\n",
       "      <td>MPI-ESM1-2-LR</td>\n",
       "      <td>historical</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>AERmon</td>\n",
       "      <td>od550aer</td>\n",
       "      <td>gn</td>\n",
       "      <td>gs://cmip6/CMIP6/CMIP/MPI-M/MPI-ESM1-2-LR/hist...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20190710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>CMIP</td>\n",
       "      <td>NCC</td>\n",
       "      <td>NorESM2-LM</td>\n",
       "      <td>historical</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>AERmon</td>\n",
       "      <td>od550aer</td>\n",
       "      <td>gn</td>\n",
       "      <td>gs://cmip6/CMIP6/CMIP/NCC/NorESM2-LM/historica...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20190815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>CMIP</td>\n",
       "      <td>BCC</td>\n",
       "      <td>BCC-ESM1</td>\n",
       "      <td>historical</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>AERmon</td>\n",
       "      <td>od550aer</td>\n",
       "      <td>gn</td>\n",
       "      <td>gs://cmip6/CMIP6/CMIP/BCC/BCC-ESM1/historical/...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20190918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>CMIP</td>\n",
       "      <td>NCAR</td>\n",
       "      <td>CESM2-WACCM-FV2</td>\n",
       "      <td>historical</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>AERmon</td>\n",
       "      <td>od550aer</td>\n",
       "      <td>gn</td>\n",
       "      <td>gs://cmip6/CMIP6/CMIP/NCAR/CESM2-WACCM-FV2/his...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20191120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>CMIP</td>\n",
       "      <td>NCAR</td>\n",
       "      <td>CESM2-FV2</td>\n",
       "      <td>historical</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>AERmon</td>\n",
       "      <td>od550aer</td>\n",
       "      <td>gn</td>\n",
       "      <td>gs://cmip6/CMIP6/CMIP/NCAR/CESM2-FV2/historica...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20191120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>CMIP</td>\n",
       "      <td>MRI</td>\n",
       "      <td>MRI-ESM2-0</td>\n",
       "      <td>historical</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>AERmon</td>\n",
       "      <td>od550aer</td>\n",
       "      <td>gn</td>\n",
       "      <td>gs://cmip6/CMIP6/CMIP/MRI/MRI-ESM2-0/historica...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20200207</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   activity_id     institution_id        source_id experiment_id member_id  \\\n",
       "0         CMIP               NCAR      CESM2-WACCM    historical  r1i1p1f1   \n",
       "1         CMIP               NCAR            CESM2    historical  r1i1p1f1   \n",
       "2         CMIP              CCCma          CanESM5    historical  r1i1p1f1   \n",
       "3         CMIP  HAMMOZ-Consortium  MPI-ESM-1-2-HAM    historical  r1i1p1f1   \n",
       "4         CMIP              MPI-M    MPI-ESM1-2-HR    historical  r1i1p1f1   \n",
       "5         CMIP              MPI-M    MPI-ESM1-2-LR    historical  r1i1p1f1   \n",
       "6         CMIP                NCC       NorESM2-LM    historical  r1i1p1f1   \n",
       "7         CMIP                BCC         BCC-ESM1    historical  r1i1p1f1   \n",
       "8         CMIP               NCAR  CESM2-WACCM-FV2    historical  r1i1p1f1   \n",
       "9         CMIP               NCAR        CESM2-FV2    historical  r1i1p1f1   \n",
       "10        CMIP                MRI       MRI-ESM2-0    historical  r1i1p1f1   \n",
       "\n",
       "   table_id variable_id grid_label  \\\n",
       "0    AERmon    od550aer         gn   \n",
       "1    AERmon    od550aer         gn   \n",
       "2    AERmon    od550aer         gn   \n",
       "3    AERmon    od550aer         gn   \n",
       "4    AERmon    od550aer         gn   \n",
       "5    AERmon    od550aer         gn   \n",
       "6    AERmon    od550aer         gn   \n",
       "7    AERmon    od550aer         gn   \n",
       "8    AERmon    od550aer         gn   \n",
       "9    AERmon    od550aer         gn   \n",
       "10   AERmon    od550aer         gn   \n",
       "\n",
       "                                               zstore  dcpp_init_year  \\\n",
       "0   gs://cmip6/CMIP6/CMIP/NCAR/CESM2-WACCM/histori...             NaN   \n",
       "1   gs://cmip6/CMIP6/CMIP/NCAR/CESM2/historical/r1...             NaN   \n",
       "2   gs://cmip6/CMIP6/CMIP/CCCma/CanESM5/historical...             NaN   \n",
       "3   gs://cmip6/CMIP6/CMIP/HAMMOZ-Consortium/MPI-ES...             NaN   \n",
       "4   gs://cmip6/CMIP6/CMIP/MPI-M/MPI-ESM1-2-HR/hist...             NaN   \n",
       "5   gs://cmip6/CMIP6/CMIP/MPI-M/MPI-ESM1-2-LR/hist...             NaN   \n",
       "6   gs://cmip6/CMIP6/CMIP/NCC/NorESM2-LM/historica...             NaN   \n",
       "7   gs://cmip6/CMIP6/CMIP/BCC/BCC-ESM1/historical/...             NaN   \n",
       "8   gs://cmip6/CMIP6/CMIP/NCAR/CESM2-WACCM-FV2/his...             NaN   \n",
       "9   gs://cmip6/CMIP6/CMIP/NCAR/CESM2-FV2/historica...             NaN   \n",
       "10  gs://cmip6/CMIP6/CMIP/MRI/MRI-ESM2-0/historica...             NaN   \n",
       "\n",
       "     version  \n",
       "0   20190227  \n",
       "1   20190308  \n",
       "2   20190429  \n",
       "3   20190627  \n",
       "4   20190710  \n",
       "5   20190710  \n",
       "6   20190815  \n",
       "7   20190918  \n",
       "8   20191120  \n",
       "9   20191120  \n",
       "10  20200207  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cat = col.search(experiment_id=['historical'], variable_id='od550aer', member_id=['r1i1p1f1'], grid_label='gn')\n",
    "cat.df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "acoustic-anaheim",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['CESM2-WACCM', 'CESM2', 'CanESM5', 'MPI-ESM-1-2-HAM',\n",
       "       'MPI-ESM1-2-HR', 'MPI-ESM1-2-LR', 'NorESM2-LM', 'BCC-ESM1',\n",
       "       'CESM2-WACCM-FV2', 'CESM2-FV2', 'MRI-ESM2-0'], dtype=object)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cat.df['source_id'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "introductory-blond",
   "metadata": {},
   "source": [
    "### Create dictionary from the list of datasets we found\n",
    "\n",
    "- This step may take several minutes so be patient!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "broad-carol",
   "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"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "    <div>\n",
       "        <style>\n",
       "            /* Turns off some styling */\n",
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       "      100.00% [11/11 01:42<00:00]\n",
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       "    "
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       "<IPython.core.display.HTML object>"
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   ],
   "source": [
    "dset_dict = cat.to_dataset_dict(zarr_kwargs={'use_cftime':True})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "incorporated-range",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['CMIP.MPI-M.MPI-ESM1-2-LR.historical.AERmon.gn',\n",
       " 'CMIP.BCC.BCC-ESM1.historical.AERmon.gn',\n",
       " 'CMIP.NCAR.CESM2-WACCM.historical.AERmon.gn',\n",
       " 'CMIP.MPI-M.MPI-ESM1-2-HR.historical.AERmon.gn',\n",
       " 'CMIP.MRI.MRI-ESM2-0.historical.AERmon.gn',\n",
       " 'CMIP.CCCma.CanESM5.historical.AERmon.gn',\n",
       " 'CMIP.NCAR.CESM2.historical.AERmon.gn',\n",
       " 'CMIP.NCC.NorESM2-LM.historical.AERmon.gn',\n",
       " 'CMIP.HAMMOZ-Consortium.MPI-ESM-1-2-HAM.historical.AERmon.gn',\n",
       " 'CMIP.NCAR.CESM2-WACCM-FV2.historical.AERmon.gn',\n",
       " 'CMIP.NCAR.CESM2-FV2.historical.AERmon.gn']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(dset_dict.keys())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "endless-dominican",
   "metadata": {},
   "source": [
    "## Select model and visualize a single date\n",
    "- Use data as xarray to make a simple plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "olive-heaven",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:     (bnds: 2, lat: 96, lon: 144, member_id: 1, time: 1980)\n",
       "Coordinates:\n",
       "  * lat         (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 86.21 88.11 90.0\n",
       "    lat_bnds    (lat, bnds) float64 dask.array&lt;chunksize=(96, 2), meta=np.ndarray&gt;\n",
       "  * lon         (lon) float64 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5\n",
       "    lon_bnds    (lon, bnds) float64 dask.array&lt;chunksize=(144, 2), meta=np.ndarray&gt;\n",
       "  * time        (time) object 1850-01-16 12:00:00 ... 2014-12-16 12:00:00\n",
       "    time_bnds   (time, bnds) object dask.array&lt;chunksize=(1980, 2), meta=np.ndarray&gt;\n",
       "    wavelength  float64 ...\n",
       "  * member_id   (member_id) &lt;U8 &#x27;r1i1p1f1&#x27;\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    od550aer    (member_id, time, lat, lon) float32 dask.array&lt;chunksize=(1, 990, 96, 144), meta=np.ndarray&gt;\n",
       "Attributes: (12/52)\n",
       "    Conventions:               CF-1.7 CMIP-6.2\n",
       "    activity_id:               CMIP\n",
       "    branch_method:             Hybrid-restart from year 1600-01-01 of piControl\n",
       "    branch_time:               0.0\n",
       "    branch_time_in_child:      0.0\n",
       "    branch_time_in_parent:     430335.0\n",
       "    ...                        ...\n",
       "    title:                     NorESM2-LM output prepared for CMIP6\n",
       "    tracking_id:               hdl:21.14100/efd7a56e-94a8-47f5-b3d8-06ae02268...\n",
       "    variable_id:               od550aer\n",
       "    variant_label:             r1i1p1f1\n",
       "    intake_esm_varname:        [&#x27;od550aer&#x27;]\n",
       "    intake_esm_dataset_key:    CMIP.NCC.NorESM2-LM.historical.AERmon.gn</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-e991e3f6-7203-45e5-b126-bfd474472247' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e991e3f6-7203-45e5-b126-bfd474472247' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 96</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'>time</span>: 1980</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-060c2b13-816e-43d9-87d7-57a11ad0fa3c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-060c2b13-816e-43d9-87d7-57a11ad0fa3c' class='xr-section-summary' >Coordinates: <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 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-3a6a7962-fb00-40d3-9e75-34fa66e5611d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a6a7962-fb00-40d3-9e75-34fa66e5611d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75a5b486-ceab-4c0b-9131-5ae1f50542f7' class='xr-var-data-in' type='checkbox'><label for='data-75a5b486-ceab-4c0b-9131-5ae1f50542f7' title='Show/Hide data 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-24e54432-5be5-4d66-a26b-c31f2d34b491' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-24e54432-5be5-4d66-a26b-c31f2d34b491' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41d6ae8a-b630-4675-9fba-135b700df15e' class='xr-var-data-in' type='checkbox'><label for='data-41d6ae8a-b630-4675-9fba-135b700df15e' title='Show/Hide data 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",
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       "</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-d66d427c-89ef-405f-abc8-7c06b2e8d005' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d66d427c-89ef-405f-abc8-7c06b2e8d005' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ee76ef8-a030-44cb-82ff-37b310c76d1f' class='xr-var-data-in' type='checkbox'><label for='data-1ee76ef8-a030-44cb-82ff-37b310c76d1f' title='Show/Hide data 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-46a983f5-79fb-4ca4-b9b9-9a609e5381d6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-46a983f5-79fb-4ca4-b9b9-9a609e5381d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7abb1d0-6088-478e-bb37-901fe14a53b3' class='xr-var-data-in' type='checkbox'><label for='data-a7abb1d0-6088-478e-bb37-901fe14a53b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
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       "  <tbody>\n",
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       "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
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       "</table>\n",
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       "</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-c303b163-c78c-46a7-8662-4ae586a6c814' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c303b163-c78c-46a7-8662-4ae586a6c814' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b95ee2e8-d841-42e5-8639-52fa0a48c3c3' class='xr-var-data-in' type='checkbox'><label for='data-b95ee2e8-d841-42e5-8639-52fa0a48c3c3' title='Show/Hide data 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),\n",
       "       cftime.DatetimeNoLeap(1850, 2, 15, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1850, 3, 16, 12, 0, 0, 0), ...,\n",
       "       cftime.DatetimeNoLeap(2014, 10, 16, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(2014, 11, 16, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(2014, 12, 16, 12, 0, 0, 0)], 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-c0467840-25e1-4318-b146-c24dcba9c480' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c0467840-25e1-4318-b146-c24dcba9c480' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c82cd964-733a-4f46-bc53-62e773058a6d' class='xr-var-data-in' type='checkbox'><label for='data-c82cd964-733a-4f46-bc53-62e773058a6d' title='Show/Hide data 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",
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       "    <tr><th> Bytes </th><td> 31.68 kB </td> <td> 31.68 kB </td></tr>\n",
       "    <tr><th> Shape </th><td> (1980, 2) </td> <td> (1980, 2) </td></tr>\n",
       "    <tr><th> Count </th><td> 2 Tasks </td><td> 1 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> object </td><td> numpy.ndarray </td></tr>\n",
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       "</tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wavelength</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-6b07882e-fdaa-4da6-810e-19b272c4a748' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6b07882e-fdaa-4da6-810e-19b272c4a748' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35e84ca6-095e-4b5e-bcfb-d3bf952d72a8' class='xr-var-data-in' type='checkbox'><label for='data-35e84ca6-095e-4b5e-bcfb-d3bf952d72a8' title='Show/Hide data 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>Radiation Wavelength 550 nanometers</dd><dt><span>standard_name :</span></dt><dd>radiation_wavelength</dd><dt><span>units :</span></dt><dd>nm</dd></dl></div><div class='xr-var-data'><pre>array(550.)</pre></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'>&lt;U8</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-7191189d-5e6e-4502-99ae-98a5dd6fbebb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7191189d-5e6e-4502-99ae-98a5dd6fbebb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf9830df-0635-4ea9-9829-621786e9b354' class='xr-var-data-in' type='checkbox'><label for='data-cf9830df-0635-4ea9-9829-621786e9b354' title='Show/Hide data 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=&#x27;&lt;U8&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9642e696-65a4-48bd-9971-6a404bbe0fb9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9642e696-65a4-48bd-9971-6a404bbe0fb9' 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>od550aer</span></div><div class='xr-var-dims'>(member_id, time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 990, 96, 144), meta=np.ndarray&gt;</div><input id='attrs-e1c89c1b-63e3-434d-be76-6d0a2ebe7000' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e1c89c1b-63e3-434d-be76-6d0a2ebe7000' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62adec62-c13d-4eb8-b69a-961ed2f518ea' class='xr-var-data-in' type='checkbox'><label for='data-62adec62-c13d-4eb8-b69a-961ed2f518ea' title='Show/Hide data 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>AOD from the ambient aerosols (i.e., includes aerosol water).  Does not include AOD from stratospheric aerosols if these are prescribed but includes other possible background aerosol types. Needs a comment attribute &#x27;wavelength: 550nm&#x27;</dd><dt><span>history :</span></dt><dd>2019-08-15T14:30:44Z altered by CMOR: Treated scalar dimension: &#x27;wavelength&#x27;. 2019-08-15T14:30:45Z altered by CMOR: Converted type from &#x27;d&#x27; to &#x27;f&#x27;.</dd><dt><span>long_name :</span></dt><dd>Ambient Aerosol Optical Thickness at 550nm</dd><dt><span>original_name :</span></dt><dd>DOD550</dd><dt><span>standard_name :</span></dt><dd>atmosphere_optical_thickness_due_to_ambient_aerosol_particles</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
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       "    <tr><th> Shape </th><td> (1, 1980, 96, 144) </td> <td> (1, 990, 96, 144) </td></tr>\n",
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       "    <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n",
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       "</tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-2fa06a4a-7f9c-43af-a427-ffc6e6b422f2' class='xr-section-summary-in' type='checkbox'  ><label for='section-2fa06a4a-7f9c-43af-a427-ffc6e6b422f2' class='xr-section-summary' >Attributes: <span>(52)</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>2019-08-15T14:30:45Z</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>2019-08-15T14:30:45Z ; 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>aerosol</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>2020-03-25;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>AERmon</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/efd7a56e-94a8-47f5-b3d8-06ae02268192\n",
       "hdl:21.14100/0c3683e7-1c3f-45d6-bbc7-414f68e7a801\n",
       "hdl:21.14100/a83a3a96-0d16-4f3e-aa88-a68f00e1ce2e\n",
       "hdl:21.14100/7a629db0-dda1-445d-a496-2e77c9c7c20a\n",
       "hdl:21.14100/388888f8-7ee4-467f-aca9-8a6e45361f55\n",
       "hdl:21.14100/7aa3797a-b0e7-427d-a209-efed00cd1724\n",
       "hdl:21.14100/33d3ae45-cb42-47e5-8c08-76df86d298a8\n",
       "hdl:21.14100/10f9c9e3-3d54-494a-b153-ea63c5b584c7\n",
       "hdl:21.14100/2a3a1f67-8890-4e89-b6de-84b2b13cf70e\n",
       "hdl:21.14100/447d4151-8161-461a-a66e-f21144baabf6\n",
       "hdl:21.14100/c1bd13af-f8b2-4b18-bd2c-34b13a4921dc\n",
       "hdl:21.14100/eee79e49-dd70-4d8f-b195-c885aca26e3a\n",
       "hdl:21.14100/7cd2e526-a94c-4004-bfe8-32832a9df6d7\n",
       "hdl:21.14100/b2421ba2-c8c9-44c0-84af-f9b09cb87759\n",
       "hdl:21.14100/f87b3cf5-e68d-40f2-a289-667b4cf7d15f\n",
       "hdl:21.14100/a6542f1a-0567-4e7a-b063-f5609f017d69\n",
       "hdl:21.14100/01e4e8d6-b84e-4d25-9f50-4a9ea5588f07</dd><dt><span>variable_id :</span></dt><dd>od550aer</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_varname :</span></dt><dd>[&#x27;od550aer&#x27;]</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCC.NorESM2-LM.historical.AERmon.gn</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:     (bnds: 2, lat: 96, lon: 144, member_id: 1, time: 1980)\n",
       "Coordinates:\n",
       "  * lat         (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 86.21 88.11 90.0\n",
       "    lat_bnds    (lat, bnds) float64 dask.array<chunksize=(96, 2), meta=np.ndarray>\n",
       "  * lon         (lon) float64 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5\n",
       "    lon_bnds    (lon, bnds) float64 dask.array<chunksize=(144, 2), meta=np.ndarray>\n",
       "  * time        (time) object 1850-01-16 12:00:00 ... 2014-12-16 12:00:00\n",
       "    time_bnds   (time, bnds) object dask.array<chunksize=(1980, 2), meta=np.ndarray>\n",
       "    wavelength  float64 ...\n",
       "  * member_id   (member_id) <U8 'r1i1p1f1'\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    od550aer    (member_id, time, lat, lon) float32 dask.array<chunksize=(1, 990, 96, 144), meta=np.ndarray>\n",
       "Attributes: (12/52)\n",
       "    Conventions:               CF-1.7 CMIP-6.2\n",
       "    activity_id:               CMIP\n",
       "    branch_method:             Hybrid-restart from year 1600-01-01 of piControl\n",
       "    branch_time:               0.0\n",
       "    branch_time_in_child:      0.0\n",
       "    branch_time_in_parent:     430335.0\n",
       "    ...                        ...\n",
       "    title:                     NorESM2-LM output prepared for CMIP6\n",
       "    tracking_id:               hdl:21.14100/efd7a56e-94a8-47f5-b3d8-06ae02268...\n",
       "    variable_id:               od550aer\n",
       "    variant_label:             r1i1p1f1\n",
       "    intake_esm_varname:        ['od550aer']\n",
       "    intake_esm_dataset_key:    CMIP.NCC.NorESM2-LM.historical.AERmon.gn"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = dset_dict['CMIP.NCC.NorESM2-LM.historical.AERmon.gn']\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "informative-backing",
   "metadata": {},
   "source": [
    "### Plot on NorthPolarStereo and set the latitude limit "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "steady-pantyhose",
   "metadata": {},
   "outputs": [],
   "source": [
    "def polarCentral_set_latlim(lat_lims, ax):\n",
    "    ax.set_extent([-180, 180, lat_lims[0], lat_lims[1]], ccrs.PlateCarree())\n",
    "    # Compute a circle in axes coordinates, which we can use as a boundary\n",
    "    # for the map. We can pan/zoom as much as we like - the boundary will be\n",
    "    # permanently circular.\n",
    "    theta = np.linspace(0, 2*np.pi, 100)\n",
    "    center, radius = [0.5, 0.5], 0.5\n",
    "    verts = np.vstack([np.sin(theta), np.cos(theta)]).T\n",
    "    circle = mpath.Path(verts * radius + center)\n",
    "\n",
    "    ax.set_boundary(circle, transform=ax.transAxes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "competent-fantasy",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fbfbc1aec70>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(1, figsize=[10,10])\n",
    "\n",
    "# Fix extent\n",
    "minval = 0\n",
    "maxval = 0.3\n",
    "\n",
    "ax = plt.subplot(1, 1, 1, projection=ccrs.NorthPolarStereo())\n",
    "ax.coastlines()\n",
    "ax.gridlines()\n",
    "polarCentral_set_latlim([50,90], ax)\n",
    "ds['od550aer'].sel(time=cftime.DatetimeNoLeap(1985, 1, 16, 12, 0, 0, 0)).plot(ax=ax, vmin=minval, vmax=maxval, transform=ccrs.PlateCarree(), cmap=cm.oslo_r)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "material-lender",
   "metadata": {},
   "source": [
    "### Get attributes (unique identifier)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "bizarre-province",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'hdl:21.14100/efd7a56e-94a8-47f5-b3d8-06ae02268192\\nhdl:21.14100/0c3683e7-1c3f-45d6-bbc7-414f68e7a801\\nhdl:21.14100/a83a3a96-0d16-4f3e-aa88-a68f00e1ce2e\\nhdl:21.14100/7a629db0-dda1-445d-a496-2e77c9c7c20a\\nhdl:21.14100/388888f8-7ee4-467f-aca9-8a6e45361f55\\nhdl:21.14100/7aa3797a-b0e7-427d-a209-efed00cd1724\\nhdl:21.14100/33d3ae45-cb42-47e5-8c08-76df86d298a8\\nhdl:21.14100/10f9c9e3-3d54-494a-b153-ea63c5b584c7\\nhdl:21.14100/2a3a1f67-8890-4e89-b6de-84b2b13cf70e\\nhdl:21.14100/447d4151-8161-461a-a66e-f21144baabf6\\nhdl:21.14100/c1bd13af-f8b2-4b18-bd2c-34b13a4921dc\\nhdl:21.14100/eee79e49-dd70-4d8f-b195-c885aca26e3a\\nhdl:21.14100/7cd2e526-a94c-4004-bfe8-32832a9df6d7\\nhdl:21.14100/b2421ba2-c8c9-44c0-84af-f9b09cb87759\\nhdl:21.14100/f87b3cf5-e68d-40f2-a289-667b4cf7d15f\\nhdl:21.14100/a6542f1a-0567-4e7a-b063-f5609f017d69\\nhdl:21.14100/01e4e8d6-b84e-4d25-9f50-4a9ea5588f07'"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.attrs['tracking_id']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "marine-samoa",
   "metadata": {},
   "source": [
    "## Regrid CMIP6 data to common NorESM2-LM grid\n",
    "- Select a time range\n",
    "- we use `squeeze` to remove dimension with one element only e.g. member_id='r1i1p1f1'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "designing-bridges",
   "metadata": {},
   "outputs": [],
   "source": [
    "starty = 1985; endy = 1986\n",
    "year_range = range(starty, endy+1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "unknown-physics",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:     (bnds: 2, lat: 96, lon: 144, time: 24)\n",
       "Coordinates:\n",
       "  * lat         (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 86.21 88.11 90.0\n",
       "    lat_bnds    (lat, bnds) float64 dask.array&lt;chunksize=(96, 2), meta=np.ndarray&gt;\n",
       "  * lon         (lon) float64 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5\n",
       "    lon_bnds    (lon, bnds) float64 dask.array&lt;chunksize=(144, 2), meta=np.ndarray&gt;\n",
       "  * time        (time) object 1985-01-16 12:00:00 ... 1986-12-16 12:00:00\n",
       "    time_bnds   (time, bnds) object dask.array&lt;chunksize=(24, 2), meta=np.ndarray&gt;\n",
       "    wavelength  float64 ...\n",
       "    member_id   &lt;U8 &#x27;r1i1p1f1&#x27;\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    od550aer    (time, lat, lon) float32 dask.array&lt;chunksize=(24, 96, 144), meta=np.ndarray&gt;\n",
       "Attributes: (12/52)\n",
       "    Conventions:               CF-1.7 CMIP-6.2\n",
       "    activity_id:               CMIP\n",
       "    branch_method:             Hybrid-restart from year 1600-01-01 of piControl\n",
       "    branch_time:               0.0\n",
       "    branch_time_in_child:      0.0\n",
       "    branch_time_in_parent:     430335.0\n",
       "    ...                        ...\n",
       "    title:                     NorESM2-LM output prepared for CMIP6\n",
       "    tracking_id:               hdl:21.14100/efd7a56e-94a8-47f5-b3d8-06ae02268...\n",
       "    variable_id:               od550aer\n",
       "    variant_label:             r1i1p1f1\n",
       "    intake_esm_varname:        [&#x27;od550aer&#x27;]\n",
       "    intake_esm_dataset_key:    CMIP.NCC.NorESM2-LM.historical.AERmon.gn</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-26d9fcfd-9736-42a1-97e5-d2a3c74c3ea1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-26d9fcfd-9736-42a1-97e5-d2a3c74c3ea1' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 96</li><li><span class='xr-has-index'>lon</span>: 144</li><li><span class='xr-has-index'>time</span>: 24</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-67eddefd-3ee8-4f66-ac0e-f99993c0b0cd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-67eddefd-3ee8-4f66-ac0e-f99993c0b0cd' class='xr-section-summary' >Coordinates: <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 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-4728c411-5e4e-4ccf-a1c1-46ac02e74b73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4728c411-5e4e-4ccf-a1c1-46ac02e74b73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-74be4e4f-a896-47e5-853d-dd989cfab684' class='xr-var-data-in' type='checkbox'><label for='data-74be4e4f-a896-47e5-853d-dd989cfab684' title='Show/Hide data 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-8c8882dc-cedf-4781-9d87-3222a0ca576a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8c8882dc-cedf-4781-9d87-3222a0ca576a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5be608f8-9edc-4573-abbd-dadce228a45d' class='xr-var-data-in' type='checkbox'><label for='data-5be608f8-9edc-4573-abbd-dadce228a45d' title='Show/Hide data 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",
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       "</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-fed06314-9c57-4c4a-bcd0-01258415d1de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fed06314-9c57-4c4a-bcd0-01258415d1de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0167ef33-a43c-4b99-bebf-269f7b2c155b' class='xr-var-data-in' type='checkbox'><label for='data-0167ef33-a43c-4b99-bebf-269f7b2c155b' title='Show/Hide data 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-805eeedd-5c75-4bb7-a94c-67ab5213496e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-805eeedd-5c75-4bb7-a94c-67ab5213496e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-198e4677-d0fe-444f-9616-5d2bd06c40b0' class='xr-var-data-in' type='checkbox'><label for='data-198e4677-d0fe-444f-9616-5d2bd06c40b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
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       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 2.30 kB </td> <td> 2.30 kB </td></tr>\n",
       "    <tr><th> Shape </th><td> (144, 2) </td> <td> (144, 2) </td></tr>\n",
       "    <tr><th> Count </th><td> 2 Tasks </td><td> 1 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
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       "</table>\n",
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       "</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'>1985-01-16 12:00:00 ... 1986-12-...</div><input id='attrs-b8289dce-eea6-423a-a621-8a6a1baf4468' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b8289dce-eea6-423a-a621-8a6a1baf4468' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07f378cc-ec88-4a9e-a645-b3c5a0b73890' class='xr-var-data-in' type='checkbox'><label for='data-07f378cc-ec88-4a9e-a645-b3c5a0b73890' title='Show/Hide data 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(1985, 1, 16, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 2, 15, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 3, 16, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 4, 16, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 5, 16, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 6, 16, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 7, 16, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 8, 16, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 9, 16, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 10, 16, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 11, 16, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 12, 16, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 1, 16, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 2, 15, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 3, 16, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 4, 16, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 5, 16, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 6, 16, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 7, 16, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 8, 16, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 9, 16, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 10, 16, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 11, 16, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 12, 16, 12, 0, 0, 0)], 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=(24, 2), meta=np.ndarray&gt;</div><input id='attrs-0d269fc7-28b4-4f6a-9693-c50820693b04' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0d269fc7-28b4-4f6a-9693-c50820693b04' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad2364ef-a5c3-4686-9b0a-1aaa0e9fe70b' class='xr-var-data-in' type='checkbox'><label for='data-ad2364ef-a5c3-4686-9b0a-1aaa0e9fe70b' title='Show/Hide data 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",
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       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 384 B </td> <td> 384 B </td></tr>\n",
       "    <tr><th> Shape </th><td> (24, 2) </td> <td> (24, 2) </td></tr>\n",
       "    <tr><th> Count </th><td> 3 Tasks </td><td> 1 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> object </td><td> numpy.ndarray </td></tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wavelength</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-d623c34f-98b6-4431-aace-13fff69d70fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d623c34f-98b6-4431-aace-13fff69d70fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e284eef2-a0d6-4798-a934-45fadff5a3d4' class='xr-var-data-in' type='checkbox'><label for='data-e284eef2-a0d6-4798-a934-45fadff5a3d4' title='Show/Hide data 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>Radiation Wavelength 550 nanometers</dd><dt><span>standard_name :</span></dt><dd>radiation_wavelength</dd><dt><span>units :</span></dt><dd>nm</dd></dl></div><div class='xr-var-data'><pre>array(550.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>member_id</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U8</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27;</div><input id='attrs-1f9855e3-6ade-44ad-bc34-dc782f88d02c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1f9855e3-6ade-44ad-bc34-dc782f88d02c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93f53456-39d9-4042-b76d-94e419f893e2' class='xr-var-data-in' type='checkbox'><label for='data-93f53456-39d9-4042-b76d-94e419f893e2' title='Show/Hide data 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=&#x27;&lt;U8&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1d1f1171-ccb6-4edb-a855-aaec2b4c8cdc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1d1f1171-ccb6-4edb-a855-aaec2b4c8cdc' 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>od550aer</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(24, 96, 144), meta=np.ndarray&gt;</div><input id='attrs-fc881a2b-2aa7-4533-9481-e40a473bb85f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fc881a2b-2aa7-4533-9481-e40a473bb85f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1cd85e49-47e8-4b5b-9faa-31071231c926' class='xr-var-data-in' type='checkbox'><label for='data-1cd85e49-47e8-4b5b-9faa-31071231c926' title='Show/Hide data 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>AOD from the ambient aerosols (i.e., includes aerosol water).  Does not include AOD from stratospheric aerosols if these are prescribed but includes other possible background aerosol types. Needs a comment attribute &#x27;wavelength: 550nm&#x27;</dd><dt><span>history :</span></dt><dd>2019-08-15T14:30:44Z altered by CMOR: Treated scalar dimension: &#x27;wavelength&#x27;. 2019-08-15T14:30:45Z altered by CMOR: Converted type from &#x27;d&#x27; to &#x27;f&#x27;.</dd><dt><span>long_name :</span></dt><dd>Ambient Aerosol Optical Thickness at 550nm</dd><dt><span>original_name :</span></dt><dd>DOD550</dd><dt><span>standard_name :</span></dt><dd>atmosphere_optical_thickness_due_to_ambient_aerosol_particles</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
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       "    <tr><th> Bytes </th><td> 1.33 MB </td> <td> 1.33 MB </td></tr>\n",
       "    <tr><th> Shape </th><td> (24, 96, 144) </td> <td> (24, 96, 144) </td></tr>\n",
       "    <tr><th> Count </th><td> 7 Tasks </td><td> 1 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n",
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       "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>2020-03-25;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>AERmon</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/efd7a56e-94a8-47f5-b3d8-06ae02268192\n",
       "hdl:21.14100/0c3683e7-1c3f-45d6-bbc7-414f68e7a801\n",
       "hdl:21.14100/a83a3a96-0d16-4f3e-aa88-a68f00e1ce2e\n",
       "hdl:21.14100/7a629db0-dda1-445d-a496-2e77c9c7c20a\n",
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       "hdl:21.14100/33d3ae45-cb42-47e5-8c08-76df86d298a8\n",
       "hdl:21.14100/10f9c9e3-3d54-494a-b153-ea63c5b584c7\n",
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       "hdl:21.14100/447d4151-8161-461a-a66e-f21144baabf6\n",
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       "hdl:21.14100/eee79e49-dd70-4d8f-b195-c885aca26e3a\n",
       "hdl:21.14100/7cd2e526-a94c-4004-bfe8-32832a9df6d7\n",
       "hdl:21.14100/b2421ba2-c8c9-44c0-84af-f9b09cb87759\n",
       "hdl:21.14100/f87b3cf5-e68d-40f2-a289-667b4cf7d15f\n",
       "hdl:21.14100/a6542f1a-0567-4e7a-b063-f5609f017d69\n",
       "hdl:21.14100/01e4e8d6-b84e-4d25-9f50-4a9ea5588f07</dd><dt><span>variable_id :</span></dt><dd>od550aer</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_varname :</span></dt><dd>[&#x27;od550aer&#x27;]</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCC.NorESM2-LM.historical.AERmon.gn</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:     (bnds: 2, lat: 96, lon: 144, time: 24)\n",
       "Coordinates:\n",
       "  * lat         (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 86.21 88.11 90.0\n",
       "    lat_bnds    (lat, bnds) float64 dask.array<chunksize=(96, 2), meta=np.ndarray>\n",
       "  * lon         (lon) float64 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5\n",
       "    lon_bnds    (lon, bnds) float64 dask.array<chunksize=(144, 2), meta=np.ndarray>\n",
       "  * time        (time) object 1985-01-16 12:00:00 ... 1986-12-16 12:00:00\n",
       "    time_bnds   (time, bnds) object dask.array<chunksize=(24, 2), meta=np.ndarray>\n",
       "    wavelength  float64 ...\n",
       "    member_id   <U8 'r1i1p1f1'\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    od550aer    (time, lat, lon) float32 dask.array<chunksize=(24, 96, 144), meta=np.ndarray>\n",
       "Attributes: (12/52)\n",
       "    Conventions:               CF-1.7 CMIP-6.2\n",
       "    activity_id:               CMIP\n",
       "    branch_method:             Hybrid-restart from year 1600-01-01 of piControl\n",
       "    branch_time:               0.0\n",
       "    branch_time_in_child:      0.0\n",
       "    branch_time_in_parent:     430335.0\n",
       "    ...                        ...\n",
       "    title:                     NorESM2-LM output prepared for CMIP6\n",
       "    tracking_id:               hdl:21.14100/efd7a56e-94a8-47f5-b3d8-06ae02268...\n",
       "    variable_id:               od550aer\n",
       "    variant_label:             r1i1p1f1\n",
       "    intake_esm_varname:        ['od550aer']\n",
       "    intake_esm_dataset_key:    CMIP.NCC.NorESM2-LM.historical.AERmon.gn"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read in the output grid from NorESM\n",
    "ds_out = ds.sel(time = ds.time.dt.year.isin(year_range)).squeeze()\n",
    "ds_out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "altered-rebecca",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CMIP.MPI-M.MPI-ESM1-2-LR.historical.AERmon.gn\n",
      "file written: CMIP6_hist/MPI-ESM1-2-LR/od550aer_AERmon.nc\n",
      "CMIP.BCC.BCC-ESM1.historical.AERmon.gn\n",
      "file written: CMIP6_hist/BCC-ESM1/od550aer_AERmon.nc\n",
      "CMIP.NCAR.CESM2-WACCM.historical.AERmon.gn\n",
      "file written: CMIP6_hist/CESM2-WACCM/od550aer_AERmon.nc\n",
      "CMIP.MPI-M.MPI-ESM1-2-HR.historical.AERmon.gn\n",
      "file written: CMIP6_hist/MPI-ESM1-2-HR/od550aer_AERmon.nc\n",
      "CMIP.MRI.MRI-ESM2-0.historical.AERmon.gn\n",
      "file written: CMIP6_hist/MRI-ESM2-0/od550aer_AERmon.nc\n",
      "CMIP.CCCma.CanESM5.historical.AERmon.gn\n",
      "file written: CMIP6_hist/CanESM5/od550aer_AERmon.nc\n",
      "CMIP.NCAR.CESM2.historical.AERmon.gn\n",
      "file written: CMIP6_hist/CESM2/od550aer_AERmon.nc\n",
      "CMIP.NCC.NorESM2-LM.historical.AERmon.gn\n",
      "file written: CMIP6_hist/NorESM2-LM/od550aer_AERmon.nc\n",
      "CMIP.HAMMOZ-Consortium.MPI-ESM-1-2-HAM.historical.AERmon.gn\n",
      "file written: CMIP6_hist/MPI-ESM-1-2-HAM/od550aer_AERmon.nc\n",
      "CMIP.NCAR.CESM2-WACCM-FV2.historical.AERmon.gn\n",
      "file written: CMIP6_hist/CESM2-WACCM-FV2/od550aer_AERmon.nc\n",
      "CMIP.NCAR.CESM2-FV2.historical.AERmon.gn\n",
      "file written: CMIP6_hist/CESM2-FV2/od550aer_AERmon.nc\n"
     ]
    }
   ],
   "source": [
    "# create dictionary for reggridded data\n",
    "ds_regrid_dict = dict()\n",
    "for key in dset_dict.keys():\n",
    "    print(key)\n",
    "    ds_in = dset_dict[keys]\n",
    "    ds_in = ds_in.sel(time = ds_in.time.dt.year.isin(year_range)).squeeze()\n",
    "    regridder = xe.Regridder(ds_in, ds_out, 'bilinear')\n",
    "    # Apply regridder to data\n",
    "    # the entire dataset can be processed at once\n",
    "    ds_in_regrid = regridder(ds_in, keep_attrs=True)\n",
    "    # Save to netcdf file\n",
    "    model = key.split('.')[2]\n",
    "    filename = 'od550aer_AERmon.nc'\n",
    "    savepath = 'CMIP6_hist/{}'.format(model)\n",
    "    nc_out = os.path.join(savepath, filename)\n",
    "    os.makedirs(savepath, exist_ok=True) \n",
    "    ds_in_regrid.to_netcdf(nc_out)\n",
    "    # create dataset with all models\n",
    "    ds_regrid_dict[model] = ds_in_regrid\n",
    "    print('file written: {}'.format(nc_out))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "practical-winter",
   "metadata": {},
   "source": [
    "## Concatenate all models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "yellow-organic",
   "metadata": {},
   "outputs": [
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       "  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:    (lat: 96, lon: 144, model: 11, nbnd: 2, time: 24)\n",
       "Coordinates:\n",
       "  * time       (time) object 1985-01-15 12:00:00 ... 1986-12-15 12:00:00\n",
       "    time_bnds  (model, time, nbnd) object dask.array&lt;chunksize=(1, 24, 2), meta=np.ndarray&gt;\n",
       "    member_id  (model) &lt;U8 &#x27;r1i1p1f1&#x27; &#x27;r1i1p1f1&#x27; ... &#x27;r1i1p1f1&#x27; &#x27;r1i1p1f1&#x27;\n",
       "  * lon        (lon) float64 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5\n",
       "  * lat        (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 86.21 88.11 90.0\n",
       "  * model      (model) &lt;U15 &#x27;MPI-ESM1-2-LR&#x27; &#x27;BCC-ESM1&#x27; ... &#x27;CESM2-FV2&#x27;\n",
       "Dimensions without coordinates: nbnd\n",
       "Data variables:\n",
       "    od550aer   (model, time, lat, lon) float64 dask.array&lt;chunksize=(1, 24, 96, 144), meta=np.ndarray&gt;\n",
       "Attributes: (12/49)\n",
       "    Conventions:             CF-1.7 CMIP-6.2\n",
       "    activity_id:             CMIP\n",
       "    branch_method:           standard\n",
       "    branch_time_in_child:    674885.0\n",
       "    branch_time_in_parent:   10950.0\n",
       "    case_id:                 1559\n",
       "    ...                      ...\n",
       "    variable_id:             od550aer\n",
       "    variant_info:            CMIP6 CESM2-FV2 historical experiment (1850-2014...\n",
       "    variant_label:           r1i1p1f1\n",
       "    intake_esm_varname:      [&#x27;od550aer&#x27;]\n",
       "    intake_esm_dataset_key:  CMIP.NCAR.CESM2-FV2.historical.AERmon.gn\n",
       "    regrid_method:           bilinear</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-c0e8df02-bbed-4e8c-905f-39252f457780' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c0e8df02-bbed-4e8c-905f-39252f457780' 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 class='xr-has-index'>lon</span>: 144</li><li><span class='xr-has-index'>model</span>: 11</li><li><span>nbnd</span>: 2</li><li><span class='xr-has-index'>time</span>: 24</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1c892025-46f1-441b-85d8-dd4e9fd69a7f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1c892025-46f1-441b-85d8-dd4e9fd69a7f' class='xr-section-summary' >Coordinates: <span>(6)</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'>object</div><div class='xr-var-preview xr-preview'>1985-01-15 12:00:00 ... 1986-12-...</div><input id='attrs-9c0af3a2-6150-47ec-86c4-ba0a9b9d1448' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c0af3a2-6150-47ec-86c4-ba0a9b9d1448' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02de7981-395e-43da-adbd-16c438edb537' class='xr-var-data-in' type='checkbox'><label for='data-02de7981-395e-43da-adbd-16c438edb537' title='Show/Hide data 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>standard_name :</span></dt><dd>time</dd><dt><span>title :</span></dt><dd>time</dd><dt><span>type :</span></dt><dd>double</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1985, 1, 15, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 2, 14, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 3, 15, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 4, 15, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 5, 15, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 6, 15, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 7, 15, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 8, 15, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 9, 15, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 10, 15, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 11, 15, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1985, 12, 15, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 1, 15, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 2, 14, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 3, 15, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 4, 15, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 5, 15, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 6, 15, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 7, 15, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 8, 15, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 9, 15, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 10, 15, 12, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 11, 15, 0, 0, 0, 0),\n",
       "       cftime.DatetimeNoLeap(1986, 12, 15, 12, 0, 0, 0)], 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'>(model, time, nbnd)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 24, 2), meta=np.ndarray&gt;</div><input id='attrs-2f4b27ba-2eab-4cf0-b4dd-6b9c59ce14bf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2f4b27ba-2eab-4cf0-b4dd-6b9c59ce14bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-61c4af31-d2fc-460f-bfb9-5714e26da6d9' class='xr-var-data-in' type='checkbox'><label for='data-61c4af31-d2fc-460f-bfb9-5714e26da6d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 4.22 kB </td> <td> 384 B </td></tr>\n",
       "    <tr><th> Shape </th><td> (11, 24, 2) </td> <td> (1, 24, 2) </td></tr>\n",
       "    <tr><th> Count </th><td> 15 Tasks </td><td> 11 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> object </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</td>\n",
       "<td>\n",
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       "  <text x=\"16.176471\" y=\"156.176471\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,16.176471,156.176471)\">11</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>member_id</span></div><div class='xr-var-dims'>(model)</div><div class='xr-var-dtype'>&lt;U8</div><div class='xr-var-preview xr-preview'>&#x27;r1i1p1f1&#x27; ... &#x27;r1i1p1f1&#x27;</div><input id='attrs-2c5efd80-3e8e-4ad4-8749-cf7a23341c6b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2c5efd80-3e8e-4ad4-8749-cf7a23341c6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25670f79-dbf4-47b0-96d2-8c007b0cfabd' class='xr-var-data-in' type='checkbox'><label for='data-25670f79-dbf4-47b0-96d2-8c007b0cfabd' title='Show/Hide data 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;, &#x27;r1i1p1f1&#x27;, &#x27;r1i1p1f1&#x27;, &#x27;r1i1p1f1&#x27;, &#x27;r1i1p1f1&#x27;,\n",
       "       &#x27;r1i1p1f1&#x27;, &#x27;r1i1p1f1&#x27;, &#x27;r1i1p1f1&#x27;, &#x27;r1i1p1f1&#x27;, &#x27;r1i1p1f1&#x27;,\n",
       "       &#x27;r1i1p1f1&#x27;], dtype=&#x27;&lt;U8&#x27;)</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'>0.0 2.5 5.0 ... 352.5 355.0 357.5</div><input id='attrs-3d1c2b2b-3292-434a-9bd2-2df101fc3827' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d1c2b2b-3292-434a-9bd2-2df101fc3827' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f263d146-e589-440b-a063-8bf0f62356e8' class='xr-var-data-in' type='checkbox'><label for='data-f263d146-e589-440b-a063-8bf0f62356e8' title='Show/Hide data 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 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-53d64e3e-738f-452a-9e12-e6bf81dc1d8b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-53d64e3e-738f-452a-9e12-e6bf81dc1d8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a343a59a-905e-45ad-941f-3454cfb243e4' class='xr-var-data-in' type='checkbox'><label for='data-a343a59a-905e-45ad-941f-3454cfb243e4' title='Show/Hide data 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 class='xr-has-index'>model</span></div><div class='xr-var-dims'>(model)</div><div class='xr-var-dtype'>&lt;U15</div><div class='xr-var-preview xr-preview'>&#x27;MPI-ESM1-2-LR&#x27; ... &#x27;CESM2-FV2&#x27;</div><input id='attrs-1afab199-caf3-48a8-88b3-a0f18fe54057' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1afab199-caf3-48a8-88b3-a0f18fe54057' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-757ed72d-ad24-49bc-ad08-6d16da742064' class='xr-var-data-in' type='checkbox'><label for='data-757ed72d-ad24-49bc-ad08-6d16da742064' title='Show/Hide data 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;MPI-ESM1-2-LR&#x27;, &#x27;BCC-ESM1&#x27;, &#x27;CESM2-WACCM&#x27;, &#x27;MPI-ESM1-2-HR&#x27;,\n",
       "       &#x27;MRI-ESM2-0&#x27;, &#x27;CanESM5&#x27;, &#x27;CESM2&#x27;, &#x27;NorESM2-LM&#x27;, &#x27;MPI-ESM-1-2-HAM&#x27;,\n",
       "       &#x27;CESM2-WACCM-FV2&#x27;, &#x27;CESM2-FV2&#x27;], dtype=&#x27;&lt;U15&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6e242ffe-a162-4f1f-ada7-96a9e886f701' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6e242ffe-a162-4f1f-ada7-96a9e886f701' 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>od550aer</span></div><div class='xr-var-dims'>(model, time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 24, 96, 144), meta=np.ndarray&gt;</div><input id='attrs-8ad44f23-a638-4f9d-bfa5-3ca5a496253b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ad44f23-a638-4f9d-bfa5-3ca5a496253b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9003d8e1-e4e9-4f54-9031-a103ca555f57' class='xr-var-data-in' type='checkbox'><label for='data-9003d8e1-e4e9-4f54-9031-a103ca555f57' title='Show/Hide data 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>AODVISdn</dd><dt><span>description :</span></dt><dd>AOD from ambient aerosols (i.e., includes aerosol water).  Does not include AOD from stratospheric aerosols if these are prescribed but includes other possible background aerosol types. Needs a comment attribute &quot;wavelength: 550 nm&quot;</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>od550aer</dd><dt><span>long_name :</span></dt><dd>Ambient Aerosol Optical Thickness at 550nm</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>od550aer</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>atmosphere_optical_thickness_due_to_ambient_aerosol_particles</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Ambient Aerosol Optical Thickness at 550nm</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>variable_id :</span></dt><dd>od550aer</dd></dl></div><div class='xr-var-data'><table>\n",
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Impose changing conditions (consistent with observations). Should be initialised from a point early enough in the pre-industrial control run to ensure that the end of all the perturbed runs branching from the end of this historical run end before the end of the control. Only one ensemble member is requested but modelling groups are strongly encouraged to submit at least three ensemble members of their CMIP historical simulation. </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.NCAR.CESM2-FV2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 1.9x2.5 finite volume grid (96x144 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; 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)[]. 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_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</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>CESM2-FV2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</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>aerosol</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (1.9x2.5 finite volume grid; 144 x 96 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 1.9x2.5 finite volume grid; 144 x 96 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (1.9x2.5 finite volume grid; 144 x 96 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (1.9x2.5 finite volume grid; 144 x 96 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2-FV2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC AER</dd><dt><span>status :</span></dt><dd>2020-03-25;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>AERmon</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/9b90d489-3171-4178-856b-837379636a2e\n",
       "hdl:21.14100/9b90d489-3171-4178-856b-837379636a2e\n",
       "hdl:21.14100/9b90d489-3171-4178-856b-837379636a2e\n",
       "hdl:21.14100/9b90d489-3171-4178-856b-837379636a2e</dd><dt><span>variable_id :</span></dt><dd>od550aer</dd><dt><span>variant_info :</span></dt><dd>CMIP6 CESM2-FV2 historical experiment (1850-2014) with CAM6-FV2 and interactive land CLM5 at 1.9 degree latitude x 2.5 degree longitude, coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1).</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_varname :</span></dt><dd>[&#x27;od550aer&#x27;]</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2-FV2.historical.AERmon.gn</dd><dt><span>regrid_method :</span></dt><dd>bilinear</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (lat: 96, lon: 144, model: 11, nbnd: 2, time: 24)\n",
       "Coordinates:\n",
       "  * time       (time) object 1985-01-15 12:00:00 ... 1986-12-15 12:00:00\n",
       "    time_bnds  (model, time, nbnd) object dask.array<chunksize=(1, 24, 2), meta=np.ndarray>\n",
       "    member_id  (model) <U8 'r1i1p1f1' 'r1i1p1f1' ... 'r1i1p1f1' 'r1i1p1f1'\n",
       "  * lon        (lon) float64 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5\n",
       "  * lat        (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 86.21 88.11 90.0\n",
       "  * model      (model) <U15 'MPI-ESM1-2-LR' 'BCC-ESM1' ... 'CESM2-FV2'\n",
       "Dimensions without coordinates: nbnd\n",
       "Data variables:\n",
       "    od550aer   (model, time, lat, lon) float64 dask.array<chunksize=(1, 24, 96, 144), meta=np.ndarray>\n",
       "Attributes: (12/49)\n",
       "    Conventions:             CF-1.7 CMIP-6.2\n",
       "    activity_id:             CMIP\n",
       "    branch_method:           standard\n",
       "    branch_time_in_child:    674885.0\n",
       "    branch_time_in_parent:   10950.0\n",
       "    case_id:                 1559\n",
       "    ...                      ...\n",
       "    variable_id:             od550aer\n",
       "    variant_info:            CMIP6 CESM2-FV2 historical experiment (1850-2014...\n",
       "    variant_label:           r1i1p1f1\n",
       "    intake_esm_varname:      ['od550aer']\n",
       "    intake_esm_dataset_key:  CMIP.NCAR.CESM2-FV2.historical.AERmon.gn\n",
       "    regrid_method:           bilinear"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_ds = list(ds_regrid_dict.values())\n",
    "_coord = list(ds_regrid_dict.keys())\n",
    "ds_out_regrid = xr.concat(objs=_ds, dim=_coord, coords=\"all\").rename({'concat_dim':'model'})\n",
    "ds_out_regrid"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "simplified-equivalent",
   "metadata": {},
   "source": [
    "## Compute seasonal mean of all regridded models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "given-stuart",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:   (lat: 96, lon: 144, season: 4)\n",
       "Coordinates:\n",
       "  * lon       (lon) float64 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5\n",
       "  * lat       (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 86.21 88.11 90.0\n",
       "  * season    (season) object &#x27;DJF&#x27; &#x27;JJA&#x27; &#x27;MAM&#x27; &#x27;SON&#x27;\n",
       "Data variables:\n",
       "    od550aer  (season, lat, lon) float64 dask.array&lt;chunksize=(1, 96, 144), meta=np.ndarray&gt;\n",
       "Attributes: (12/49)\n",
       "    Conventions:             CF-1.7 CMIP-6.2\n",
       "    activity_id:             CMIP\n",
       "    branch_method:           standard\n",
       "    branch_time_in_child:    674885.0\n",
       "    branch_time_in_parent:   10950.0\n",
       "    case_id:                 1559\n",
       "    ...                      ...\n",
       "    variable_id:             od550aer\n",
       "    variant_info:            CMIP6 CESM2-FV2 historical experiment (1850-2014...\n",
       "    variant_label:           r1i1p1f1\n",
       "    intake_esm_varname:      [&#x27;od550aer&#x27;]\n",
       "    intake_esm_dataset_key:  CMIP.NCAR.CESM2-FV2.historical.AERmon.gn\n",
       "    regrid_method:           bilinear</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-3d98e124-e536-4fee-bb4a-758c39cc9206' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3d98e124-e536-4fee-bb4a-758c39cc9206' 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 class='xr-has-index'>lon</span>: 144</li><li><span class='xr-has-index'>season</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a95182b7-243b-4d44-aa9c-b425720d7156' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a95182b7-243b-4d44-aa9c-b425720d7156' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-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-ff391c15-d90c-4a65-a755-c12d3b8a2e4a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff391c15-d90c-4a65-a755-c12d3b8a2e4a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94c42ddb-3da1-4c34-857d-fdb2429fd761' class='xr-var-data-in' type='checkbox'><label for='data-94c42ddb-3da1-4c34-857d-fdb2429fd761' title='Show/Hide data 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 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-4eed287a-222f-4bc3-859a-8d11dafd701d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4eed287a-222f-4bc3-859a-8d11dafd701d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b55f22f-2138-462f-aced-eb389011bdfd' class='xr-var-data-in' type='checkbox'><label for='data-3b55f22f-2138-462f-aced-eb389011bdfd' title='Show/Hide data 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 class='xr-has-index'>season</span></div><div class='xr-var-dims'>(season)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;DJF&#x27; &#x27;JJA&#x27; &#x27;MAM&#x27; &#x27;SON&#x27;</div><input id='attrs-213b612b-829d-4520-9db2-24c3831d9f2f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-213b612b-829d-4520-9db2-24c3831d9f2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd9e6eac-36f9-40e2-ab92-2ed2a1fe4a43' class='xr-var-data-in' type='checkbox'><label for='data-cd9e6eac-36f9-40e2-ab92-2ed2a1fe4a43' title='Show/Hide data 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;DJF&#x27;, &#x27;JJA&#x27;, &#x27;MAM&#x27;, &#x27;SON&#x27;], dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-be1f7ee0-fa16-4eac-915c-9190beb8a71d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-be1f7ee0-fa16-4eac-915c-9190beb8a71d' 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>od550aer</span></div><div class='xr-var-dims'>(season, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 96, 144), meta=np.ndarray&gt;</div><input id='attrs-4905c1ab-3f73-461c-8b03-9e821889f0fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4905c1ab-3f73-461c-8b03-9e821889f0fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09c75874-8c31-462d-84ac-60104c260b00' class='xr-var-data-in' type='checkbox'><label for='data-09c75874-8c31-462d-84ac-60104c260b00' title='Show/Hide data 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>AODVISdn</dd><dt><span>description :</span></dt><dd>AOD from ambient aerosols (i.e., includes aerosol water).  Does not include AOD from stratospheric aerosols if these are prescribed but includes other possible background aerosol types. Needs a comment attribute &quot;wavelength: 550 nm&quot;</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>id :</span></dt><dd>od550aer</dd><dt><span>long_name :</span></dt><dd>Ambient Aerosol Optical Thickness at 550nm</dd><dt><span>mipTable :</span></dt><dd>AERmon</dd><dt><span>out_name :</span></dt><dd>od550aer</dd><dt><span>prov :</span></dt><dd>AERmon ((isd.003))</dd><dt><span>realm :</span></dt><dd>aerosol</dd><dt><span>standard_name :</span></dt><dd>atmosphere_optical_thickness_due_to_ambient_aerosol_particles</dd><dt><span>time :</span></dt><dd>time</dd><dt><span>time_label :</span></dt><dd>time-mean</dd><dt><span>time_title :</span></dt><dd>Temporal mean</dd><dt><span>title :</span></dt><dd>Ambient Aerosol Optical Thickness at 550nm</dd><dt><span>type :</span></dt><dd>real</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>variable_id :</span></dt><dd>od550aer</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-69aa76dd-5c7e-4eb9-a222-712bb16d45a3' class='xr-section-summary-in' type='checkbox'  ><label for='section-69aa76dd-5c7e-4eb9-a222-712bb16d45a3' class='xr-section-summary' >Attributes: <span>(49)</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>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>674885.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>10950.0</dd><dt><span>case_id :</span></dt><dd>1559</dd><dt><span>cesm_casename :</span></dt><dd>b.e21.BHIST.f19_g17.CMIP6-historical-2deg.001</dd><dt><span>contact :</span></dt><dd>cesm_cmip6@ucar.edu</dd><dt><span>creation_date :</span></dt><dd>2019-07-31T15:48:41Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.31</dd><dt><span>experiment :</span></dt><dd>Simulation of recent past (1850 to 2014). Impose changing conditions (consistent with observations). Should be initialised from a point early enough in the pre-industrial control run to ensure that the end of all the perturbed runs branching from the end of this historical run end before the end of the control. Only one ensemble member is requested but modelling groups are strongly encouraged to submit at least three ensemble members of their CMIP historical simulation. </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.NCAR.CESM2-FV2.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native 1.9x2.5 finite volume grid (96x144 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA</dd><dt><span>institution_id :</span></dt><dd>NCAR</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by &lt;The National Center for Atmospheric Research&gt; 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)[]. 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_doi_url :</span></dt><dd>https://doi.org/10.5065/D67H1H0V</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>CESM2-FV2</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01 00:00:00</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>aerosol</dd><dt><span>source :</span></dt><dd>CESM2 (2017): atmosphere: CAM6 (1.9x2.5 finite volume grid; 144 x 96 longitude/latitude; 32 levels; top level 2.25 mb); ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m); sea_ice: CICE5.1 (same grid as ocean); land: CLM5 1.9x2.5 finite volume grid; 144 x 96 longitude/latitude; 32 levels; top level 2.25 mb); aerosol: MAM4 (1.9x2.5 finite volume grid; 144 x 96 longitude/latitude; 32 levels; top level 2.25 mb); atmoschem: MAM4 (1.9x2.5 finite volume grid; 144 x 96 longitude/latitude; 32 levels; top level 2.25 mb); landIce: CISM2.1; ocnBgchem: MARBL (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m)</dd><dt><span>source_id :</span></dt><dd>CESM2-FV2</dd><dt><span>source_type :</span></dt><dd>AOGCM BGC AER</dd><dt><span>status :</span></dt><dd>2020-03-25;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>AERmon</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/9b90d489-3171-4178-856b-837379636a2e\n",
       "hdl:21.14100/9b90d489-3171-4178-856b-837379636a2e\n",
       "hdl:21.14100/9b90d489-3171-4178-856b-837379636a2e\n",
       "hdl:21.14100/9b90d489-3171-4178-856b-837379636a2e</dd><dt><span>variable_id :</span></dt><dd>od550aer</dd><dt><span>variant_info :</span></dt><dd>CMIP6 CESM2-FV2 historical experiment (1850-2014) with CAM6-FV2 and interactive land CLM5 at 1.9 degree latitude x 2.5 degree longitude, coupled ocean (POP2) with biogeochemistry (MARBL), interactive sea ice (CICE5.1), and non-evolving land ice (CISM2.1).</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>intake_esm_varname :</span></dt><dd>[&#x27;od550aer&#x27;]</dd><dt><span>intake_esm_dataset_key :</span></dt><dd>CMIP.NCAR.CESM2-FV2.historical.AERmon.gn</dd><dt><span>regrid_method :</span></dt><dd>bilinear</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:   (lat: 96, lon: 144, season: 4)\n",
       "Coordinates:\n",
       "  * lon       (lon) float64 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5\n",
       "  * lat       (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 86.21 88.11 90.0\n",
       "  * season    (season) object 'DJF' 'JJA' 'MAM' 'SON'\n",
       "Data variables:\n",
       "    od550aer  (season, lat, lon) float64 dask.array<chunksize=(1, 96, 144), meta=np.ndarray>\n",
       "Attributes: (12/49)\n",
       "    Conventions:             CF-1.7 CMIP-6.2\n",
       "    activity_id:             CMIP\n",
       "    branch_method:           standard\n",
       "    branch_time_in_child:    674885.0\n",
       "    branch_time_in_parent:   10950.0\n",
       "    case_id:                 1559\n",
       "    ...                      ...\n",
       "    variable_id:             od550aer\n",
       "    variant_info:            CMIP6 CESM2-FV2 historical experiment (1850-2014...\n",
       "    variant_label:           r1i1p1f1\n",
       "    intake_esm_varname:      ['od550aer']\n",
       "    intake_esm_dataset_key:  CMIP.NCAR.CESM2-FV2.historical.AERmon.gn\n",
       "    regrid_method:           bilinear"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_seas = ds_out_regrid.mean('model', keep_attrs=True, skipna = True).groupby('time.season').mean('time', keep_attrs=True, skipna = True)\n",
    "ds_seas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "confidential-communications",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<xarray.DataArray 'od550aer' ()>\n",
       " array(0.0031875),\n",
       " <xarray.DataArray 'od550aer' ()>\n",
       " array(2.65120286))"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_seas['od550aer'].min().compute(), ds_seas['od550aer'].max().compute()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "marked-knight",
   "metadata": {},
   "source": [
    "## Save seasonal mean in a new netCDF file and in the current Galaxy history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "crazy-arbitration",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_seas.to_netcdf('CMIP6_hist/od550aer_seasonal.nc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "nervous-worship",
   "metadata": {},
   "outputs": [],
   "source": [
    "!put -p CMIP6_hist/od550aer_seasonal.nc -t netcdf"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "initial-volleyball",
   "metadata": {},
   "source": [
    "## Visualize final results (seasonal mean for all models)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "affecting-republic",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1332x756 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib\n",
    "proj_plot = ccrs.Mercator()\n",
    "\n",
    "p = ds_seas['od550aer'].plot(x='lon', y='lat', transform=ccrs.PlateCarree(),\n",
    "                             aspect=ds_seas.dims[\"lon\"] / ds_seas.dims[\"lat\"],  # for a sensible figsize\n",
    "                             subplot_kws={\"projection\": proj_plot},\n",
    "                             col='season', col_wrap=2, robust=True, cmap='PiYG')\n",
    "# We have to set the map's options on all four axes\n",
    "for ax,i in zip(p.axes.flat,  ds_seas.season.values):\n",
    "    ax.coastlines()\n",
    "    ax.set_title('Season '+i, fontsize=18)\n",
    "fig = matplotlib.pyplot.gcf()\n",
    "fig.set_size_inches(18.5, 10.5)\n",
    "fig.savefig('od550aer_seasonal_mean.png', dpi=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "european-seller",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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