tas_intake_CICLAD_test.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Near-Surface Air Temperature\n",
    "\n",
    "## Test analyse 'tas' en multimodèle avec Intake en local\n",
    "Environnement `scipyconf2020_xesmf`\n",
    "\n",
    "```bash\n",
    "conda create --name myenv --file scipyconf2020_xesmf.txt  \n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.8.3 | packaged by conda-forge | (default, Jun  1 2020, 17:43:00) \n",
      "[GCC 7.5.0]\n",
      "Virtual memory usage - total: 31 GB / available: 23 GB / percent used: 25.4 %\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table style=\"border: 2px solid white;\">\n",
       "<tr>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3 style=\"text-align: left;\">Client</h3>\n",
       "<ul style=\"text-align: left; list-style: none; margin: 0; padding: 0;\">\n",
       "  <li><b>Scheduler: </b>tcp://127.0.0.1:45711</li>\n",
       "  <li><b>Dashboard: </b><a href='http://127.0.0.1:8787/status' target='_blank'>http://127.0.0.1:8787/status</a></li>\n",
       "</ul>\n",
       "</td>\n",
       "<td style=\"vertical-align: top; border: 0px solid white\">\n",
       "<h3 style=\"text-align: left;\">Cluster</h3>\n",
       "<ul style=\"text-align: left; list-style:none; margin: 0; padding: 0;\">\n",
       "  <li><b>Workers: </b>4</li>\n",
       "  <li><b>Cores: </b>12</li>\n",
       "  <li><b>Memory: </b>33.33 GB</li>\n",
       "</ul>\n",
       "</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Client: 'tcp://127.0.0.1:45711' processes=4 threads=12, memory=33.33 GB>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# To reload external files automatically (ex: utils)\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "import xarray as xr\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import proplot as plot # New plot library (https://proplot.readthedocs.io/en/latest/)\n",
    "from scipy import stats\n",
    "import xesmf as xe # For regridding (https://xesmf.readthedocs.io/en/latest/)\n",
    "import intake\n",
    "from dask.distributed import Client\n",
    "\n",
    "import sys\n",
    "sys.path.insert(1, '/home/lalandmi/Dropbox/Thèse/notebooks/utils') # to include my util file in previous directory\n",
    "import utils as u # my personal functions\n",
    "u.check_python_version()\n",
    "u.check_virtual_memory()\n",
    "client = Client()\n",
    "client"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Near-Surface Air Temperature'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "period = slice('1979','2014')\n",
    "latlim, lonlim = u.get_domain_HMA()\n",
    "\n",
    "var = 'tas'\n",
    "table = u.get_table(var)\n",
    "label, units, cmap, levels = u.get_var_infos(var)\n",
    "label"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load topography"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = xr.open_dataset('GMTED2010_15n240_1000deg.nc').drop_dims('nbounds').swap_dims(\n",
    "    {'nlat': 'latitude', 'nlon': 'longitude'}).drop({'nlat', 'nlon'}).rename(\n",
    "    {'latitude': 'lat', 'longitude': 'lon'}).sel(lat=latlim, lon=lonlim)\n",
    "elevation = ds.elevation\n",
    "elevation_std = ds.elevation_stddev"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load obs\n",
    "cru_ts4.00: https://crudata.uea.ac.uk/cru/data/hrg/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "obs_longname = 'CRU TS v. 4.00'\n",
    "obs_name = 'CRU'\n",
    "\n",
    "obs = xr.open_dataset('~/data/cru_ts4.00.1901.2015.tmp.dat.nc').sel(\n",
    "    time=period, lat=latlim, lon=lonlim).tmp\n",
    "obs_clim = u.clim(obs, calendar=obs.time.encoding['calendar'])\n",
    "# obs_clim.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Regrid obs towards the elevation grid of 1°x1°\n",
    "Using xESMF (https://xesmf.readthedocs.io/en/latest/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reuse existing file: bilinear_50x100_25x50.nc\n"
     ]
    }
   ],
   "source": [
    "regridder = xe.Regridder(obs_clim, elevation, 'bilinear', periodic=False, reuse_weights=True)\n",
    "obs_clim_regrid = regridder(obs_clim)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Check models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "url = \"https://raw.githubusercontent.com/NCAR/intake-esm-datastore/master/catalogs/pangeo-cmip6.json\"\n",
    "col = intake.open_esm_datastore(url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<p><strong>pangeo-cmip6 catalog with 121 dataset(s) from 1677 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>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>institution_id</th>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>source_id</th>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>experiment_id</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>member_id</th>\n",
       "      <td>176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>table_id</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>variable_id</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>grid_label</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zstore</th>\n",
       "      <td>1677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dcpp_init_year</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>version</th>\n",
       "      <td>155</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cat = col.search(\n",
    "    experiment_id=\"historical\",\n",
    "#     table_id=\"Amon\",\n",
    "    variable_id=[\"tas\",\"snc\",\"pr\"],\n",
    "#     grid_label=\"gn\",\n",
    ")\n",
    "\n",
    "cat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>experiment_id</th>\n",
       "      <th>variable_id</th>\n",
       "      <th>table_id</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>source_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ACCESS-CM2</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ACCESS-ESM1-5</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AWI-CM-1-1-MR</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AWI-ESM-1-1-LR</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BCC-CSM2-MR</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BCC-ESM1</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAMS-CSM1-0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAS-ESM2-0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CESM2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CESM2-FV2</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CESM2-WACCM</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CESM2-WACCM-FV2</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CIESM</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CMCC-CM2-SR5</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CNRM-CM6-1</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CNRM-CM6-1-HR</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CNRM-ESM2-1</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CanESM5</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CanESM5-CanOE</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E3SM-1-0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E3SM-1-1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>E3SM-1-1-ECA</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EC-Earth3</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EC-Earth3-Veg</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EC-Earth3-Veg-LR</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FGOALS-f3-L</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FGOALS-g3</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIO-ESM-2-0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GFDL-CM4</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GFDL-ESM4</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GISS-E2-1-G</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GISS-E2-1-G-CC</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GISS-E2-1-H</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HadGEM3-GC31-LL</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HadGEM3-GC31-MM</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INM-CM4-8</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INM-CM5-0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IPSL-CM6A-LR</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KACE-1-0-G</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MCM-UA-1-0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIROC-ES2L</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIROC6</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MPI-ESM-1-2-HAM</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MPI-ESM1-2-HR</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MPI-ESM1-2-LR</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MRI-ESM2-0</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NESM3</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NorCPM1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NorESM2-LM</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NorESM2-MM</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SAM0-UNICON</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TaiESM1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UKESM1-0-LL</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  experiment_id  variable_id  table_id\n",
       "source_id                                             \n",
       "ACCESS-CM2                    1            2         2\n",
       "ACCESS-ESM1-5                 1            2         2\n",
       "AWI-CM-1-1-MR                 1            2         2\n",
       "AWI-ESM-1-1-LR                1            2         2\n",
       "BCC-CSM2-MR                   1            3         4\n",
       "BCC-ESM1                      1            3         3\n",
       "CAMS-CSM1-0                   1            2         1\n",
       "CAS-ESM2-0                    1            2         1\n",
       "CESM2                         1            3         3\n",
       "CESM2-FV2                     1            2         2\n",
       "CESM2-WACCM                   1            3         3\n",
       "CESM2-WACCM-FV2               1            2         1\n",
       "CIESM                         1            2         1\n",
       "CMCC-CM2-SR5                  1            2         2\n",
       "CNRM-CM6-1                    1            3         4\n",
       "CNRM-CM6-1-HR                 1            2         2\n",
       "CNRM-ESM2-1                   1            3         4\n",
       "CanESM5                       1            3         3\n",
       "CanESM5-CanOE                 1            2         1\n",
       "E3SM-1-0                      1            2         1\n",
       "E3SM-1-1                      1            2         1\n",
       "E3SM-1-1-ECA                  1            1         1\n",
       "EC-Earth3                     1            2         2\n",
       "EC-Earth3-Veg                 1            3         3\n",
       "EC-Earth3-Veg-LR              1            2         2\n",
       "FGOALS-f3-L                   1            2         2\n",
       "FGOALS-g3                     1            2         2\n",
       "FIO-ESM-2-0                   1            2         1\n",
       "GFDL-CM4                      1            3         4\n",
       "GFDL-ESM4                     1            2         2\n",
       "GISS-E2-1-G                   1            3         3\n",
       "GISS-E2-1-G-CC                1            2         1\n",
       "GISS-E2-1-H                   1            3         2\n",
       "HadGEM3-GC31-LL               1            3         3\n",
       "HadGEM3-GC31-MM               1            2         2\n",
       "INM-CM4-8                     1            2         2\n",
       "INM-CM5-0                     1            2         2\n",
       "IPSL-CM6A-LR                  1            3         4\n",
       "KACE-1-0-G                    1            2         2\n",
       "MCM-UA-1-0                    1            2         1\n",
       "MIROC-ES2L                    1            3         3\n",
       "MIROC6                        1            3         3\n",
       "MPI-ESM-1-2-HAM               1            2         2\n",
       "MPI-ESM1-2-HR                 1            2         2\n",
       "MPI-ESM1-2-LR                 1            2         2\n",
       "MRI-ESM2-0                    1            3         4\n",
       "NESM3                         1            2         2\n",
       "NorCPM1                       1            2         2\n",
       "NorESM2-LM                    1            2         2\n",
       "NorESM2-MM                    1            2         2\n",
       "SAM0-UNICON                   1            3         3\n",
       "TaiESM1                       1            2         2\n",
       "UKESM1-0-LL                   1            3         3"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cat.df.groupby(\"source_id\")[\n",
    "    [\"experiment_id\", \"variable_id\", \"table_id\"]\n",
    "].nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get only the models that have the 3 variables \n",
    "https://intake-esm.readthedocs.io/en/latest/notebooks/tutorial.html#Enhanced-search:-enforce-query-criteria-via-require_all_on-argument"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define our query\n",
    "query = dict(\n",
    "    experiment_id=\"historical\",\n",
    "    variable_id=[\"tas\",\"snc\",\"pr\"],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>experiment_id</th>\n",
       "      <th>variable_id</th>\n",
       "      <th>table_id</th>\n",
       "      <th>member_id</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>source_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BCC-CSM2-MR</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BCC-ESM1</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CESM2</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CESM2-WACCM</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CNRM-CM6-1</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CNRM-ESM2-1</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CanESM5</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EC-Earth3-Veg</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GFDL-CM4</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GISS-E2-1-G</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GISS-E2-1-H</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HadGEM3-GC31-LL</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IPSL-CM6A-LR</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIROC-ES2L</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIROC6</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MRI-ESM2-0</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SAM0-UNICON</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UKESM1-0-LL</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 experiment_id  variable_id  table_id  member_id\n",
       "source_id                                                       \n",
       "BCC-CSM2-MR                  1            3         4          3\n",
       "BCC-ESM1                     1            3         3          3\n",
       "CESM2                        1            3         3         11\n",
       "CESM2-WACCM                  1            3         3          3\n",
       "CNRM-CM6-1                   1            3         4         30\n",
       "CNRM-ESM2-1                  1            3         4         11\n",
       "CanESM5                      1            3         3         50\n",
       "EC-Earth3-Veg                1            3         3          6\n",
       "GFDL-CM4                     1            3         4          1\n",
       "GISS-E2-1-G                  1            3         3         40\n",
       "GISS-E2-1-H                  1            3         2         23\n",
       "HadGEM3-GC31-LL              1            3         3          4\n",
       "IPSL-CM6A-LR                 1            3         4         32\n",
       "MIROC-ES2L                   1            3         3         10\n",
       "MIROC6                       1            3         3         50\n",
       "MRI-ESM2-0                   1            3         4          6\n",
       "SAM0-UNICON                  1            3         3          1\n",
       "UKESM1-0-LL                  1            3         3         17"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col_subset = col.search(require_all_on=[\"source_id\"], **query)\n",
    "col_subset.df.groupby(\"source_id\")[\n",
    "    [\"experiment_id\", \"variable_id\", \"table_id\", \"member_id\"]\n",
    "].nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BCC-CSM2-MR\n",
      "Reuse existing file: bilinear_32x54_25x50.nc\n",
      "BCC-ESM1\n",
      "Reuse existing file: bilinear_13x21_25x50.nc\n"
     ]
    }
   ],
   "source": [
    "url = \"https://raw.githubusercontent.com/NCAR/intake-esm-datastore/master/catalogs/pangeo-cmip6.json\"\n",
    "col = intake.open_esm_datastore(url)\n",
    "\n",
    "list_models = u.get_model_names()\n",
    "\n",
    "bias = []\n",
    "\n",
    "for model in list_models[:2]:\n",
    "    print(model)\n",
    "    institute, grid, realization = u.get_model_infos(model, var)\n",
    "    \n",
    "    # Intake\n",
    "    cat = col.search(experiment_id=[\"historical\"], table_id=table, variable_id=var, source_id=model, member_id=realization, grid_label=grid)\n",
    "    data_source = cat[cat.keys()[0]]\n",
    "    ds = data_source(zarr_kwargs={'consolidated': True, 'decode_times': True}).to_dask()\n",
    "    \n",
    "    model_clim = ds.sel(time=period, \n",
    "          lat=slice(latlim.start-5, latlim.stop+5), # Add 5° for the regrid\n",
    "          lon=slice(lonlim.start-5, lonlim.stop+5))[var].mean('time').squeeze().load() - 273.15\n",
    "    \n",
    "    # Regrid towards elevation grid 1°x1°\n",
    "    regridder = xe.Regridder(model_clim, elevation, 'bilinear', periodic=False, reuse_weights=True)\n",
    "    model_clim_regrid = regridder(model_clim)\n",
    "    \n",
    "    bias.append(model_clim_regrid - obs_clim_regrid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/lalandmi/miniconda3/envs/scipyconf2020_xesmf/lib/python3.8/site-packages/proplot/config.py:554: ProPlotWarning: rc setting 'geogrid.linewidth' was renamed to grid.linewidth in version 0.6.\n",
      "/home/lalandmi/miniconda3/envs/scipyconf2020_xesmf/lib/python3.8/site-packages/proplot/config.py:554: ProPlotWarning: rc setting 'geogrid.color' was renamed to grid.color in version 0.6.\n",
      "/home/lalandmi/miniconda3/envs/scipyconf2020_xesmf/lib/python3.8/site-packages/proplot/config.py:554: ProPlotWarning: rc setting 'geogrid.alpha' was renamed to grid.alpha in version 0.6.\n",
      "/home/lalandmi/miniconda3/envs/scipyconf2020_xesmf/lib/python3.8/site-packages/proplot/config.py:554: ProPlotWarning: rc setting 'geogrid.linewidth' was renamed to grid.linewidth in version 0.6.\n",
      "/home/lalandmi/miniconda3/envs/scipyconf2020_xesmf/lib/python3.8/site-packages/proplot/config.py:554: ProPlotWarning: rc setting 'geogrid.color' was renamed to grid.color in version 0.6.\n",
      "/home/lalandmi/miniconda3/envs/scipyconf2020_xesmf/lib/python3.8/site-packages/proplot/config.py:554: ProPlotWarning: rc setting 'geogrid.alpha' was renamed to grid.alpha in version 0.6.\n",
      "/home/lalandmi/miniconda3/envs/scipyconf2020_xesmf/lib/python3.8/site-packages/proplot/config.py:554: ProPlotWarning: rc setting 'geogrid.linewidth' was renamed to grid.linewidth in version 0.6.\n",
      "/home/lalandmi/miniconda3/envs/scipyconf2020_xesmf/lib/python3.8/site-packages/proplot/config.py:554: ProPlotWarning: rc setting 'geogrid.color' was renamed to grid.color in version 0.6.\n",
      "/home/lalandmi/miniconda3/envs/scipyconf2020_xesmf/lib/python3.8/site-packages/proplot/config.py:554: ProPlotWarning: rc setting 'geogrid.alpha' was renamed to grid.alpha in version 0.6.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1029.86x191.528 with 7 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 160,
       "width": 920
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, axs = plot.subplots(proj='cyl', ncols=3, nrows=1)\n",
    "\n",
    "for i, ax in enumerate(axs):\n",
    "    if i == 0:\n",
    "        axs[i].contourf(obs_clim_regrid, cmap=cmap, levels=levels, colorbar='l')\n",
    "    else:\n",
    "        #Plot\n",
    "        m = axs[i].contourf(bias[i-1], cmap='RdBu_r', levels=plot.arange(-20,20,2))\n",
    "\n",
    "        # Compute RMSE\n",
    "    #     rmse = np.sqrt((bias[i].sel(lat=slice(latlim[0],latlim[1]), lon=slice(lonlim[0],lonlim[1]))**2).mean().values)\n",
    "\n",
    "    #     axs[i].format(\n",
    "    #         title=list_models[i],\n",
    "    #         lltitle='RMSE = '+str(round(rmse,1)) +' °C'\n",
    "    #     )\n",
    "    \n",
    "    \n",
    "f.colorbar(m, label='aze', loc='r')\n",
    "\n",
    "axs.format(\n",
    "    geogridlinewidth=0.5, geogridcolor='gray8', geogridalpha=0.5, labels=False, \n",
    "    coast=True, ocean=True, oceancolor='gray3', borders=True,\n",
    "    suptitle=\"Bias of Near-Surface Air Temperature annual climatology (1981-2014) versus \"+obs_longname,\n",
    "    lonlines=10, latlines=5, abc=False,\n",
    "    latlim=(elevation.lat.min().values, elevation.lat.max().values), \n",
    "    lonlim=(elevation.lon.min().values, elevation.lon.max().values)\n",
    ")\n",
    "\n",
    "# f.save('img/'+var+'_bias_multimodel.jpg')\n",
    "# f.save('img/'+var+'_bias_multimodel.png')\n",
    "# f.save('img/'+var+'_bias_multimodel.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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