InstantaneousRF.ipynb

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    "import numpy as np\n",
    "import xarray as xr\n",
    "import intake\n",
    "import xesmf as xe\n",
    "import pandas as pd\n",
    "import cfgrib\n",
    "\n",
    "import warnings\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.colors as mcolors\n",
    "from matplotlib.colors import from_levels_and_colors\n",
    "from matplotlib.colors import TwoSlopeNorm, Normalize\n",
    "import matplotlib.patches as mpatches\n",
    "from matplotlib.lines import Line2D\n",
    "from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
    "\n",
    "import cartopy.crs as ccrs\n",
    "from cartopy.util import add_cyclic_point\n",
    "import seaborn as sns\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "%matplotlib inline\n"
   ]
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     "text": [
      "forcing_density.pdf\t rfmip_models.csv.gz\r\n",
      "instantaneous_plots.pdf  rfmip_models.json\r\n",
      "InstantaneousRF.ipynb\t sfi0014_forcing_1851.nc\r\n",
      "PET0.ESMF_LogFile\t spaer_ensemble.pdf\r\n",
      "rfmip_erf_lw.pdf\t SpAer_ERF.ipynb\r\n",
      "rfmip_erf.pdf\t\t total_aerosol_radiative_forcing.ipynb\r\n",
      "rfmip_intake.ipynb\r\n"
     ]
    }
   ],
   "source": [
    "!ls"
   ]
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    "def compute_forcings_allsky(data_aerosols, data_control):\n",
    "    ''' Calculate the effective radiative forcing at TOA due shortwave and longwave radiation flux\n",
    "       Parameters:\n",
    "       -----------\n",
    "       data_aerosols: xarray.Dataset\n",
    "                 aerosol data; should include 'rsdt', 'rsut' and 'rlut' fluxes; usually: dim=(time, lat, lon) \n",
    "       data_control: xarray.Dataset\n",
    "                     control data; should include 'rsdt', 'rsut' and 'rlut' fluxes and has to be of the \n",
    "                     same dimension as data_aer\n",
    "\n",
    "       Returns:\n",
    "       --------\n",
    "       sw_forcing_toa: xarray.DataArray\n",
    "                       shortwave forcing at toa; same dimension as input data (usually (time, lat, lon))\n",
    "       lw_forcing_toa: xarray.DataArray\n",
    "                       longwave forcing at toa; same dimension as input data (usually (time, lat, lon))\n",
    "    '''\n",
    "    \n",
    "    sw_balance_aer = data_aerosols[\"rsdt\"] - data_aerosols[\"rsut\"]\n",
    "    sw_balance_control = data_control[\"rsdt\"] - data_control[\"rsut\"]\n",
    "    sw_forcing_toa = -sw_balance_control + sw_balance_aer\n",
    "    lw_balance_aer = data_aerosols[\"rsdt\"] - data_aerosols[\"rsut\"] - data_aerosols[\"rlut\"]\n",
    "    lw_balance_control = data_control[\"rsdt\"] - data_control[\"rsut\"] - data_control[\"rlut\"]\n",
    "    lw_forcing_toa = -lw_balance_control + lw_balance_aer\n",
    "\n",
    "    return sw_forcing_toa, lw_forcing_toa"
   ]
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   "source": [
    "# regridding to common resolution\n",
    "\n",
    "def regridding(ds_aerosols, ds_control, periodic=True):\n",
    "    regrid = xe.Regridder(ds_control, noresm_control, # which one to use?\n",
    "                          method='bilinear', \n",
    "                          periodic=periodic,\n",
    "                          ignore_degenerate=True)\n",
    "    regridded_control = regrid(ds_control, keep_attrs=True)\n",
    "    \n",
    "    regrid = xe.Regridder(ds_aerosols, noresm_control, \n",
    "                          method='bilinear', \n",
    "                          periodic=periodic,\n",
    "                          ignore_degenerate=True)\n",
    "    regridded_aer = regrid(ds_aerosols, keep_attrs=True)\n",
    "    \n",
    "    regridded_params = compute_forcing_allsky(data_aerosols=regridded_aer, data_control=regridded_control)\n",
    "    \n",
    "    return regridded_params"
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    "def preprocess(ds):\n",
    "    # rename variables\n",
    "    ds = ds.rename({'var21':'irfstcs','var22':'irfst','var23':'irfsscs','var24':'irfss',\n",
    "                    'var31':'irfltcs','var32': 'irflt','var33':'irflscs','var34': 'irfls',\n",
    "                    'var73':'d_aflx_sw','var74':'d_aflx_lw','var75':'d_aflx_swcs','var76':'d_aflx_lwcs',\n",
    "                    'var77':'netht_sw', 'var78':'netht_lw',\n",
    "                    'var129':'geopot_surface','var134':'surface_pres','var152':'log_surface_pres',\n",
    "                    'var1':'gboxarea'}\n",
    "                  )\n",
    "    # add variable attributes\n",
    "    ds.irfstcs.attrs = {'name':'Mean instantaneous shortwave forcing at top of the atmosphere for clear sky ','units': 'W/m^2'}\n",
    "    ds.irfst.attrs = {'name':'Mean instantaneous shortwave forcing at top of the atmosphere for all sky','units': 'W/m^2'}\n",
    "    ds.irfsscs.attrs = {'name':'Mean instantaneous shortwave forcing at surface for clear sky','units': 'W/m^2'}\n",
    "    ds.irfss.attrs = {'name':'Mean instantaneous shortwave forcing at surface for all sky','units': 'W/m^2'}\n",
    "    ds.irfltcs.attrs = {'name':'Mean instantaneous longwave forcing at top of the atmosphere for clear sky','units': 'W/m^2'}\n",
    "    ds.irflt.attrs = {'name':'Mean instantaneous longwave forcing at top of the atmosphere for all sky','units': 'W/m^2'}\n",
    "    ds.irflscs.attrs = {'name':'Mean instantaneous longwave forcing at surface for clear sky','units': 'W/m^2'}\n",
    "    ds.irfls.attrs = {'name':'Mean instantaneous longwave forcing at surface for all sky','units': 'W/m^2'}\n",
    "    ds.d_aflx_sw.attrs = {'name':'Accumulated SW flux anomalies for all sky', 'units': 'W/m^2'}\n",
    "    ds.d_aflx_lw.attrs = {'name':'Accumulated LW flux anomalies for all sky', 'units': 'W/m^2'}\n",
    "    ds.d_aflx_swcs.attrs = {'name':'Accumulated SW flux anomalies for clear sky', 'units': 'W/m^2'}\n",
    "    ds.d_aflx_lwcs.attrs = {'name':'Accumulated LW flux anomalies for clear sky', 'units': 'W/m^2'}\n",
    "    ds.netht_sw.attrs = {'name':'Net SW heating rate forcing', 'units': 'K/d'}\n",
    "    ds.netht_lw.attrs = {'name':'Net LW heating rate forcing', 'units': 'K/d'}\n",
    "    ds.geopot_surface.attrs = {'name':'surface geopotential', 'units': 'm^2/s^2'}\n",
    "    ds.surface_pres.attrs = {'name':'surface pressure','units':'Pa'}\n",
    "    ds.log_surface_pres.attrs = {'name':'log surface pressure','units':'log Pa'}\n",
    "    ds.gboxarea.attrs = {'name':'guassian grid','units':'m^2'}\n",
    "    \n",
    "    return ds"
   ]
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    "path = '/work/bb1198/b381265/RFMIP-IRF/'\n",
    "mpiesm_irf_r1 = xr.open_mfdataset(path+'r1/*.nc', preprocess=preprocess)\n",
    "mpiesm_irf_r2 = xr.open_mfdataset(path+'r2/*.nc', preprocess=preprocess)\n",
    "mpiesm_irf_r3 = xr.open_mfdataset(path+'r3/*.nc', preprocess=preprocess)"
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       "  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:           (time: 348, lon: 192, lat: 96, lev: 48, nhyi: 48, nhym: 47, lev_2: 47, nsp: 2080, nc2: 2)\n",
       "Coordinates:\n",
       "  * time              (time) float64 1.851e+07 1.851e+07 ... 1.879e+07 1.879e+07\n",
       "  * lon               (lon) float64 0.0 1.875 3.75 5.625 ... 354.4 356.2 358.1\n",
       "  * lat               (lat) float64 88.57 86.72 84.86 ... -84.86 -86.72 -88.57\n",
       "  * lev               (lev) float64 1.0 2.0 3.0 4.0 5.0 ... 45.0 46.0 47.0 48.0\n",
       "  * lev_2             (lev_2) float64 1.0 2.0 3.0 4.0 ... 44.0 45.0 46.0 47.0\n",
       "Dimensions without coordinates: nhyi, nhym, nsp, nc2\n",
       "Data variables: (12/22)\n",
       "    hyai              (time, nhyi) float64 dask.array&lt;chunksize=(12, 48), meta=np.ndarray&gt;\n",
       "    hybi              (time, nhyi) float64 dask.array&lt;chunksize=(12, 48), meta=np.ndarray&gt;\n",
       "    hyam              (time, nhym) float64 dask.array&lt;chunksize=(12, 47), meta=np.ndarray&gt;\n",
       "    hybm              (time, nhym) float64 dask.array&lt;chunksize=(12, 47), meta=np.ndarray&gt;\n",
       "    irfstcs           (time, lat, lon) float32 dask.array&lt;chunksize=(12, 96, 192), meta=np.ndarray&gt;\n",
       "    irfst             (time, lat, lon) float32 dask.array&lt;chunksize=(12, 96, 192), meta=np.ndarray&gt;\n",
       "    ...                ...\n",
       "    netht_sw          (time, lev_2, lat, lon) float32 dask.array&lt;chunksize=(12, 47, 96, 192), meta=np.ndarray&gt;\n",
       "    netht_lw          (time, lev_2, lat, lon) float32 dask.array&lt;chunksize=(12, 47, 96, 192), meta=np.ndarray&gt;\n",
       "    geopot_surface    (time, lat, lon) float32 dask.array&lt;chunksize=(12, 96, 192), meta=np.ndarray&gt;\n",
       "    surface_pres      (time, lat, lon) float32 dask.array&lt;chunksize=(12, 96, 192), meta=np.ndarray&gt;\n",
       "    log_surface_pres  (time, nsp, nc2) float32 dask.array&lt;chunksize=(12, 2080, 2), meta=np.ndarray&gt;\n",
       "    gboxarea          (time, lat, lon) float32 dask.array&lt;chunksize=(12, 96, 192), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 1.9.10 (https://mpimet.mpg.d...\n",
       "    Conventions:  CF-1.6\n",
       "    institution:  Max Planck Institute for Meteorology\n",
       "    history:      Thu Nov 04 13:41:47 2021: cdo -f nc copy /work/bb1198/m3003...\n",
       "    CDO:          Climate Data Operators version 1.9.10 (https://mpimet.mpg.d...</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-6c59f21d-c1e2-4b29-9847-d9b804735e65' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6c59f21d-c1e2-4b29-9847-d9b804735e65' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 348</li><li><span class='xr-has-index'>lon</span>: 192</li><li><span class='xr-has-index'>lat</span>: 96</li><li><span class='xr-has-index'>lev</span>: 48</li><li><span>nhyi</span>: 48</li><li><span>nhym</span>: 47</li><li><span class='xr-has-index'>lev_2</span>: 47</li><li><span>nsp</span>: 2080</li><li><span>nc2</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-2042e186-3ceb-458b-a5fd-5bfa1c418a88' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2042e186-3ceb-458b-a5fd-5bfa1c418a88' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.851e+07 1.851e+07 ... 1.879e+07</div><input id='attrs-3ee9f06a-f888-48ae-967b-3eda8c26ef32' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ee9f06a-f888-48ae-967b-3eda8c26ef32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8815d982-72df-4625-9193-c2240bb844d3' class='xr-var-data-in' type='checkbox'><label for='data-8815d982-72df-4625-9193-c2240bb844d3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>units :</span></dt><dd>day as %Y%m%d.%f</dd><dt><span>calendar :</span></dt><dd>proleptic_gregorian</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([18510131.994444, 18510228.994444, 18510331.994444, ..., 18791031.994444,\n",
       "       18791130.994444, 18791231.994444])</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 1.875 3.75 ... 356.2 358.1</div><input id='attrs-88743b0a-e3be-462d-adc4-ef7f9c9a5fa8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88743b0a-e3be-462d-adc4-ef7f9c9a5fa8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3319a6da-b8f8-4201-94ab-bc7a849065e8' class='xr-var-data-in' type='checkbox'><label for='data-3319a6da-b8f8-4201-94ab-bc7a849065e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.   ,   1.875,   3.75 ,   5.625,   7.5  ,   9.375,  11.25 ,  13.125,\n",
       "        15.   ,  16.875,  18.75 ,  20.625,  22.5  ,  24.375,  26.25 ,  28.125,\n",
       "        30.   ,  31.875,  33.75 ,  35.625,  37.5  ,  39.375,  41.25 ,  43.125,\n",
       "        45.   ,  46.875,  48.75 ,  50.625,  52.5  ,  54.375,  56.25 ,  58.125,\n",
       "        60.   ,  61.875,  63.75 ,  65.625,  67.5  ,  69.375,  71.25 ,  73.125,\n",
       "        75.   ,  76.875,  78.75 ,  80.625,  82.5  ,  84.375,  86.25 ,  88.125,\n",
       "        90.   ,  91.875,  93.75 ,  95.625,  97.5  ,  99.375, 101.25 , 103.125,\n",
       "       105.   , 106.875, 108.75 , 110.625, 112.5  , 114.375, 116.25 , 118.125,\n",
       "       120.   , 121.875, 123.75 , 125.625, 127.5  , 129.375, 131.25 , 133.125,\n",
       "       135.   , 136.875, 138.75 , 140.625, 142.5  , 144.375, 146.25 , 148.125,\n",
       "       150.   , 151.875, 153.75 , 155.625, 157.5  , 159.375, 161.25 , 163.125,\n",
       "       165.   , 166.875, 168.75 , 170.625, 172.5  , 174.375, 176.25 , 178.125,\n",
       "       180.   , 181.875, 183.75 , 185.625, 187.5  , 189.375, 191.25 , 193.125,\n",
       "       195.   , 196.875, 198.75 , 200.625, 202.5  , 204.375, 206.25 , 208.125,\n",
       "       210.   , 211.875, 213.75 , 215.625, 217.5  , 219.375, 221.25 , 223.125,\n",
       "       225.   , 226.875, 228.75 , 230.625, 232.5  , 234.375, 236.25 , 238.125,\n",
       "       240.   , 241.875, 243.75 , 245.625, 247.5  , 249.375, 251.25 , 253.125,\n",
       "       255.   , 256.875, 258.75 , 260.625, 262.5  , 264.375, 266.25 , 268.125,\n",
       "       270.   , 271.875, 273.75 , 275.625, 277.5  , 279.375, 281.25 , 283.125,\n",
       "       285.   , 286.875, 288.75 , 290.625, 292.5  , 294.375, 296.25 , 298.125,\n",
       "       300.   , 301.875, 303.75 , 305.625, 307.5  , 309.375, 311.25 , 313.125,\n",
       "       315.   , 316.875, 318.75 , 320.625, 322.5  , 324.375, 326.25 , 328.125,\n",
       "       330.   , 331.875, 333.75 , 335.625, 337.5  , 339.375, 341.25 , 343.125,\n",
       "       345.   , 346.875, 348.75 , 350.625, 352.5  , 354.375, 356.25 , 358.125])</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'>88.57 86.72 84.86 ... -86.72 -88.57</div><input id='attrs-fe398084-7215-4438-a379-9791014e471f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fe398084-7215-4438-a379-9791014e471f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc30a538-db51-4f77-b257-ca3510dc6844' class='xr-var-data-in' type='checkbox'><label for='data-bc30a538-db51-4f77-b257-ca3510dc6844' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([ 88.572169,  86.722531,  84.86197 ,  82.998942,  81.134977,  79.270559,\n",
       "        77.405888,  75.541061,  73.676132,  71.811132,  69.946081,  68.080991,\n",
       "        66.215872,  64.35073 ,  62.485571,  60.620396,  58.755209,  56.890013,\n",
       "        55.024808,  53.159595,  51.294377,  49.429154,  47.563926,  45.698694,\n",
       "        43.833459,  41.96822 ,  40.102979,  38.237736,  36.372491,  34.507243,\n",
       "        32.641994,  30.776744,  28.911492,  27.046239,  25.180986,  23.315731,\n",
       "        21.450475,  19.585219,  17.719962,  15.854704,  13.989446,  12.124187,\n",
       "        10.258928,   8.393669,   6.528409,   4.66315 ,   2.79789 ,   0.93263 ,\n",
       "        -0.93263 ,  -2.79789 ,  -4.66315 ,  -6.528409,  -8.393669, -10.258928,\n",
       "       -12.124187, -13.989446, -15.854704, -17.719962, -19.585219, -21.450475,\n",
       "       -23.315731, -25.180986, -27.046239, -28.911492, -30.776744, -32.641994,\n",
       "       -34.507243, -36.372491, -38.237736, -40.102979, -41.96822 , -43.833459,\n",
       "       -45.698694, -47.563926, -49.429154, -51.294377, -53.159595, -55.024808,\n",
       "       -56.890013, -58.755209, -60.620396, -62.485571, -64.35073 , -66.215872,\n",
       "       -68.080991, -69.946081, -71.811132, -73.676132, -75.541061, -77.405888,\n",
       "       -79.270559, -81.134977, -82.998942, -84.86197 , -86.722531, -88.572169])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0 3.0 4.0 ... 46.0 47.0 48.0</div><input id='attrs-98d208cc-cbf3-440e-8d1b-2ea0fc1f43aa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98d208cc-cbf3-440e-8d1b-2ea0fc1f43aa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14ef6bed-4925-4672-b0b4-5f490ea6cb74' class='xr-var-data-in' type='checkbox'><label for='data-14ef6bed-4925-4672-b0b4-5f490ea6cb74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>hybrid_sigma_pressure</dd><dt><span>long_name :</span></dt><dd>hybrid level at layer midpoints</dd><dt><span>formula :</span></dt><dd>hyam hybm (mlev=hyam+hybm*aps)</dd><dt><span>formula_terms :</span></dt><dd>ap: hyam b: hybm ps: aps</dd><dt><span>units :</span></dt><dd>level</dd><dt><span>positive :</span></dt><dd>down</dd></dl></div><div class='xr-var-data'><pre>array([ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 13., 14.,\n",
       "       15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28.,\n",
       "       29., 30., 31., 32., 33., 34., 35., 36., 37., 38., 39., 40., 41., 42.,\n",
       "       43., 44., 45., 46., 47., 48.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev_2</span></div><div class='xr-var-dims'>(lev_2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0 3.0 4.0 ... 45.0 46.0 47.0</div><input id='attrs-060b6838-3a8f-4ea0-a432-5e8a89a12b58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-060b6838-3a8f-4ea0-a432-5e8a89a12b58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a8864af-dd3c-4c15-a625-c98dd3968cfc' class='xr-var-data-in' type='checkbox'><label for='data-3a8864af-dd3c-4c15-a625-c98dd3968cfc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>hybrid_sigma_pressure</dd><dt><span>long_name :</span></dt><dd>hybrid level at layer midpoints</dd><dt><span>formula :</span></dt><dd>hyam hybm (mlev=hyam+hybm*aps)</dd><dt><span>formula_terms :</span></dt><dd>ap: hyam b: hybm ps: aps</dd><dt><span>units :</span></dt><dd>level</dd><dt><span>positive :</span></dt><dd>down</dd></dl></div><div class='xr-var-data'><pre>array([ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 13., 14.,\n",
       "       15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28.,\n",
       "       29., 30., 31., 32., 33., 34., 35., 36., 37., 38., 39., 40., 41., 42.,\n",
       "       43., 44., 45., 46., 47.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bb54e956-9607-4fe8-bd35-895a0417bb7a' class='xr-section-summary-in' type='checkbox'  ><label for='section-bb54e956-9607-4fe8-bd35-895a0417bb7a' class='xr-section-summary' >Data variables: <span>(22)</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>hyai</span></div><div class='xr-var-dims'>(time, nhyi)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(12, 48), meta=np.ndarray&gt;</div><input id='attrs-ea008302-7e3f-4b5e-a69a-6f58a3c1f0ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea008302-7e3f-4b5e-a69a-6f58a3c1f0ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8fbda28e-80d7-4ada-8008-d454173d228e' class='xr-var-data-in' type='checkbox'><label for='data-8fbda28e-80d7-4ada-8008-d454173d228e' title='Show/Hide data 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>hybrid A coefficient at layer interfaces</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><table>\n",
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       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 130.50 kiB </td> <td> 4.50 kiB </td></tr>\n",
       "    <tr><th> Shape </th><td> (348, 48) </td> <td> (12, 48) </td></tr>\n",
       "    <tr><th> Count </th><td> 116 Tasks </td><td> 29 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
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       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:           (time: 348, lon: 192, lat: 96, lev: 48, nhyi: 48, nhym: 47, lev_2: 47, nsp: 2080, nc2: 2)\n",
       "Coordinates:\n",
       "  * time              (time) float64 1.851e+07 1.851e+07 ... 1.879e+07 1.879e+07\n",
       "  * lon               (lon) float64 0.0 1.875 3.75 5.625 ... 354.4 356.2 358.1\n",
       "  * lat               (lat) float64 88.57 86.72 84.86 ... -84.86 -86.72 -88.57\n",
       "  * lev               (lev) float64 1.0 2.0 3.0 4.0 5.0 ... 45.0 46.0 47.0 48.0\n",
       "  * lev_2             (lev_2) float64 1.0 2.0 3.0 4.0 ... 44.0 45.0 46.0 47.0\n",
       "Dimensions without coordinates: nhyi, nhym, nsp, nc2\n",
       "Data variables: (12/22)\n",
       "    hyai              (time, nhyi) float64 dask.array&lt;chunksize=(12, 48), meta=np.ndarray&gt;\n",
       "    hybi              (time, nhyi) float64 dask.array&lt;chunksize=(12, 48), meta=np.ndarray&gt;\n",
       "    hyam              (time, nhym) float64 dask.array&lt;chunksize=(12, 47), meta=np.ndarray&gt;\n",
       "    hybm              (time, nhym) float64 dask.array&lt;chunksize=(12, 47), meta=np.ndarray&gt;\n",
       "    irfstcs           (time, lat, lon) float32 dask.array&lt;chunksize=(12, 96, 192), meta=np.ndarray&gt;\n",
       "    irfst             (time, lat, lon) float32 dask.array&lt;chunksize=(12, 96, 192), meta=np.ndarray&gt;\n",
       "    ...                ...\n",
       "    netht_sw          (time, lev_2, lat, lon) float32 dask.array&lt;chunksize=(12, 47, 96, 192), meta=np.ndarray&gt;\n",
       "    netht_lw          (time, lev_2, lat, lon) float32 dask.array&lt;chunksize=(12, 47, 96, 192), meta=np.ndarray&gt;\n",
       "    geopot_surface    (time, lat, lon) float32 dask.array&lt;chunksize=(12, 96, 192), meta=np.ndarray&gt;\n",
       "    surface_pres      (time, lat, lon) float32 dask.array&lt;chunksize=(12, 96, 192), meta=np.ndarray&gt;\n",
       "    log_surface_pres  (time, nsp, nc2) float32 dask.array&lt;chunksize=(12, 2080, 2), meta=np.ndarray&gt;\n",
       "    gboxarea          (time, lat, lon) float32 dask.array&lt;chunksize=(12, 96, 192), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 1.9.10 (https://mpimet.mpg.d...\n",
       "    Conventions:  CF-1.6\n",
       "    institution:  Max Planck Institute for Meteorology\n",
       "    history:      Thu Nov 04 13:25:27 2021: cdo -f nc copy /work/bb1198/m3003...\n",
       "    CDO:          Climate Data Operators version 1.9.10 (https://mpimet.mpg.d...</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-65437447-71f8-4b8d-8563-6d7049ce1dd2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-65437447-71f8-4b8d-8563-6d7049ce1dd2' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 348</li><li><span class='xr-has-index'>lon</span>: 192</li><li><span class='xr-has-index'>lat</span>: 96</li><li><span class='xr-has-index'>lev</span>: 48</li><li><span>nhyi</span>: 48</li><li><span>nhym</span>: 47</li><li><span class='xr-has-index'>lev_2</span>: 47</li><li><span>nsp</span>: 2080</li><li><span>nc2</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-59ea391c-cc24-4bed-acbb-a2d9eedd067c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-59ea391c-cc24-4bed-acbb-a2d9eedd067c' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.851e+07 1.851e+07 ... 1.879e+07</div><input id='attrs-d7e74be3-87fe-4866-bebc-ca07f4f518e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7e74be3-87fe-4866-bebc-ca07f4f518e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0613fda3-cfbe-481b-8056-bb869b70838b' class='xr-var-data-in' type='checkbox'><label for='data-0613fda3-cfbe-481b-8056-bb869b70838b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>units :</span></dt><dd>day as %Y%m%d.%f</dd><dt><span>calendar :</span></dt><dd>proleptic_gregorian</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([18510131.994444, 18510228.994444, 18510331.994444, ..., 18791031.994444,\n",
       "       18791130.994444, 18791231.994444])</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 1.875 3.75 ... 356.2 358.1</div><input id='attrs-4c844a05-2136-49bb-992c-a2fbcfde1db0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c844a05-2136-49bb-992c-a2fbcfde1db0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1e13c00-6d03-4bc6-9db2-4e7b3f00bd44' class='xr-var-data-in' type='checkbox'><label for='data-a1e13c00-6d03-4bc6-9db2-4e7b3f00bd44' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.   ,   1.875,   3.75 ,   5.625,   7.5  ,   9.375,  11.25 ,  13.125,\n",
       "        15.   ,  16.875,  18.75 ,  20.625,  22.5  ,  24.375,  26.25 ,  28.125,\n",
       "        30.   ,  31.875,  33.75 ,  35.625,  37.5  ,  39.375,  41.25 ,  43.125,\n",
       "        45.   ,  46.875,  48.75 ,  50.625,  52.5  ,  54.375,  56.25 ,  58.125,\n",
       "        60.   ,  61.875,  63.75 ,  65.625,  67.5  ,  69.375,  71.25 ,  73.125,\n",
       "        75.   ,  76.875,  78.75 ,  80.625,  82.5  ,  84.375,  86.25 ,  88.125,\n",
       "        90.   ,  91.875,  93.75 ,  95.625,  97.5  ,  99.375, 101.25 , 103.125,\n",
       "       105.   , 106.875, 108.75 , 110.625, 112.5  , 114.375, 116.25 , 118.125,\n",
       "       120.   , 121.875, 123.75 , 125.625, 127.5  , 129.375, 131.25 , 133.125,\n",
       "       135.   , 136.875, 138.75 , 140.625, 142.5  , 144.375, 146.25 , 148.125,\n",
       "       150.   , 151.875, 153.75 , 155.625, 157.5  , 159.375, 161.25 , 163.125,\n",
       "       165.   , 166.875, 168.75 , 170.625, 172.5  , 174.375, 176.25 , 178.125,\n",
       "       180.   , 181.875, 183.75 , 185.625, 187.5  , 189.375, 191.25 , 193.125,\n",
       "       195.   , 196.875, 198.75 , 200.625, 202.5  , 204.375, 206.25 , 208.125,\n",
       "       210.   , 211.875, 213.75 , 215.625, 217.5  , 219.375, 221.25 , 223.125,\n",
       "       225.   , 226.875, 228.75 , 230.625, 232.5  , 234.375, 236.25 , 238.125,\n",
       "       240.   , 241.875, 243.75 , 245.625, 247.5  , 249.375, 251.25 , 253.125,\n",
       "       255.   , 256.875, 258.75 , 260.625, 262.5  , 264.375, 266.25 , 268.125,\n",
       "       270.   , 271.875, 273.75 , 275.625, 277.5  , 279.375, 281.25 , 283.125,\n",
       "       285.   , 286.875, 288.75 , 290.625, 292.5  , 294.375, 296.25 , 298.125,\n",
       "       300.   , 301.875, 303.75 , 305.625, 307.5  , 309.375, 311.25 , 313.125,\n",
       "       315.   , 316.875, 318.75 , 320.625, 322.5  , 324.375, 326.25 , 328.125,\n",
       "       330.   , 331.875, 333.75 , 335.625, 337.5  , 339.375, 341.25 , 343.125,\n",
       "       345.   , 346.875, 348.75 , 350.625, 352.5  , 354.375, 356.25 , 358.125])</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'>88.57 86.72 84.86 ... -86.72 -88.57</div><input id='attrs-3dcf48da-ea88-4289-9c6f-7d10df99720b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3dcf48da-ea88-4289-9c6f-7d10df99720b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6dfdd8ba-44ee-4214-87ac-88e3086a3ee8' class='xr-var-data-in' type='checkbox'><label for='data-6dfdd8ba-44ee-4214-87ac-88e3086a3ee8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([ 88.572169,  86.722531,  84.86197 ,  82.998942,  81.134977,  79.270559,\n",
       "        77.405888,  75.541061,  73.676132,  71.811132,  69.946081,  68.080991,\n",
       "        66.215872,  64.35073 ,  62.485571,  60.620396,  58.755209,  56.890013,\n",
       "        55.024808,  53.159595,  51.294377,  49.429154,  47.563926,  45.698694,\n",
       "        43.833459,  41.96822 ,  40.102979,  38.237736,  36.372491,  34.507243,\n",
       "        32.641994,  30.776744,  28.911492,  27.046239,  25.180986,  23.315731,\n",
       "        21.450475,  19.585219,  17.719962,  15.854704,  13.989446,  12.124187,\n",
       "        10.258928,   8.393669,   6.528409,   4.66315 ,   2.79789 ,   0.93263 ,\n",
       "        -0.93263 ,  -2.79789 ,  -4.66315 ,  -6.528409,  -8.393669, -10.258928,\n",
       "       -12.124187, -13.989446, -15.854704, -17.719962, -19.585219, -21.450475,\n",
       "       -23.315731, -25.180986, -27.046239, -28.911492, -30.776744, -32.641994,\n",
       "       -34.507243, -36.372491, -38.237736, -40.102979, -41.96822 , -43.833459,\n",
       "       -45.698694, -47.563926, -49.429154, -51.294377, -53.159595, -55.024808,\n",
       "       -56.890013, -58.755209, -60.620396, -62.485571, -64.35073 , -66.215872,\n",
       "       -68.080991, -69.946081, -71.811132, -73.676132, -75.541061, -77.405888,\n",
       "       -79.270559, -81.134977, -82.998942, -84.86197 , -86.722531, -88.572169])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0 3.0 4.0 ... 46.0 47.0 48.0</div><input id='attrs-2f29d2f6-a729-44c5-ad66-018f95877843' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2f29d2f6-a729-44c5-ad66-018f95877843' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f296d23-65f0-47ab-936b-c891efeba06d' class='xr-var-data-in' type='checkbox'><label for='data-4f296d23-65f0-47ab-936b-c891efeba06d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>hybrid_sigma_pressure</dd><dt><span>long_name :</span></dt><dd>hybrid level at layer midpoints</dd><dt><span>formula :</span></dt><dd>hyam hybm (mlev=hyam+hybm*aps)</dd><dt><span>formula_terms :</span></dt><dd>ap: hyam b: hybm ps: aps</dd><dt><span>units :</span></dt><dd>level</dd><dt><span>positive :</span></dt><dd>down</dd></dl></div><div class='xr-var-data'><pre>array([ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 13., 14.,\n",
       "       15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28.,\n",
       "       29., 30., 31., 32., 33., 34., 35., 36., 37., 38., 39., 40., 41., 42.,\n",
       "       43., 44., 45., 46., 47., 48.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev_2</span></div><div class='xr-var-dims'>(lev_2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0 3.0 4.0 ... 45.0 46.0 47.0</div><input id='attrs-89472a11-a74e-40ff-9b4e-6fb3ce169780' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89472a11-a74e-40ff-9b4e-6fb3ce169780' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c8db855-4899-407c-b1e4-0655e0cadde4' class='xr-var-data-in' type='checkbox'><label for='data-5c8db855-4899-407c-b1e4-0655e0cadde4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>hybrid_sigma_pressure</dd><dt><span>long_name :</span></dt><dd>hybrid level at layer midpoints</dd><dt><span>formula :</span></dt><dd>hyam hybm (mlev=hyam+hybm*aps)</dd><dt><span>formula_terms :</span></dt><dd>ap: hyam b: hybm ps: aps</dd><dt><span>units :</span></dt><dd>level</dd><dt><span>positive :</span></dt><dd>down</dd></dl></div><div class='xr-var-data'><pre>array([ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 13., 14.,\n",
       "       15., 16., 17., 18., 19., 20., 21., 22., 23., 24., 25., 26., 27., 28.,\n",
       "       29., 30., 31., 32., 33., 34., 35., 36., 37., 38., 39., 40., 41., 42.,\n",
       "       43., 44., 45., 46., 47.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a33607bb-37bc-45bb-89ac-4387156b7bb7' class='xr-section-summary-in' type='checkbox'  ><label for='section-a33607bb-37bc-45bb-89ac-4387156b7bb7' class='xr-section-summary' >Data variables: <span>(22)</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>hyai</span></div><div class='xr-var-dims'>(time, nhyi)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(12, 48), meta=np.ndarray&gt;</div><input id='attrs-c3316f25-2afc-422f-8797-88cc866e73ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c3316f25-2afc-422f-8797-88cc866e73ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-608819cd-ed27-41fe-b4ab-09d8cdd238c5' class='xr-var-data-in' type='checkbox'><label for='data-608819cd-ed27-41fe-b4ab-09d8cdd238c5' title='Show/Hide data 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>hybrid A coefficient at layer interfaces</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><table>\n",
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       "    <tr><th> Type </th><td> float64 </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>hybi</span></div><div class='xr-var-dims'>(time, nhyi)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(12, 48), meta=np.ndarray&gt;</div><input id='attrs-b79201af-0b8b-4be8-bf1a-6440771e2bb7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b79201af-0b8b-4be8-bf1a-6440771e2bb7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b1d4d73-169f-48c1-bb98-2bb0e654027e' class='xr-var-data-in' type='checkbox'><label for='data-6b1d4d73-169f-48c1-bb98-2bb0e654027e' title='Show/Hide data 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>hybrid B coefficient at layer interfaces</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hyam</span></div><div class='xr-var-dims'>(time, nhym)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(12, 47), meta=np.ndarray&gt;</div><input id='attrs-c28e329f-34eb-450e-bcd9-50118b318f01' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c28e329f-34eb-450e-bcd9-50118b318f01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-224b4b1e-678f-4814-a9a9-8181116b3567' class='xr-var-data-in' type='checkbox'><label for='data-224b4b1e-678f-4814-a9a9-8181116b3567' title='Show/Hide data 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>hybrid A coefficient at layer midpoints</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hybm</span></div><div class='xr-var-dims'>(time, nhym)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(12, 47), meta=np.ndarray&gt;</div><input id='attrs-06283290-3539-4808-9f0b-2f8433d58f46' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06283290-3539-4808-9f0b-2f8433d58f46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8248fe36-27f9-47c4-b7f5-269a2b979300' class='xr-var-data-in' type='checkbox'><label for='data-8248fe36-27f9-47c4-b7f5-269a2b979300' title='Show/Hide data 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>hybrid B coefficient at layer midpoints</dd><dt><span>units :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>log_surface_pres</span></div><div class='xr-var-dims'>(time, nsp, nc2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(12, 2080, 2), meta=np.ndarray&gt;</div><input id='attrs-b21aa49b-0797-4a8c-b4b7-48ad25a7a25c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b21aa49b-0797-4a8c-b4b7-48ad25a7a25c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-573b4915-8192-4c5a-a834-6af5aa6503e6' class='xr-var-data-in' type='checkbox'><label for='data-573b4915-8192-4c5a-a834-6af5aa6503e6' title='Show/Hide data 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>name :</span></dt><dd>log surface pressure</dd><dt><span>units :</span></dt><dd>log Pa</dd></dl></div><div class='xr-var-data'><table>\n",
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       "    surface_pres      (time, lat, lon) float32 dask.array<chunksize=(12, 96, 192), meta=np.ndarray>\n",
       "    log_surface_pres  (time, nsp, nc2) float32 dask.array<chunksize=(12, 2080, 2), meta=np.ndarray>\n",
       "    gboxarea          (time, lat, lon) float32 dask.array<chunksize=(12, 96, 192), meta=np.ndarray>\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 1.9.10 (https://mpimet.mpg.d...\n",
       "    Conventions:  CF-1.6\n",
       "    institution:  Max Planck Institute for Meteorology\n",
       "    history:      Thu Nov 04 13:25:27 2021: cdo -f nc copy /work/bb1198/m3003...\n",
       "    CDO:          Climate Data Operators version 1.9.10 (https://mpimet.mpg.d..."
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_mpi = xr.concat([mpiesm_irf_r1, mpiesm_irf_r2,mpiesm_irf_r3], dim='member_id')\n",
    "ds = ds_mpi.mean(dim='member_id', keep_attrs=True)\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-11-22T14:19:43.835918Z",
     "start_time": "2021-11-22T14:19:43.643349Z"
    }
   },
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;irfst&#x27; (time: 348, lat: 96, lon: 192)&gt;\n",
       "dask.array&lt;mean_agg-aggregate, shape=(348, 96, 192), dtype=float32, chunksize=(12, 96, 192), chunktype=numpy.ndarray&gt;\n",
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       "Attributes:\n",
       "    name:     Mean instantaneous shortwave forcing at top of the atmosphere f...\n",
       "    units:    W/m^2</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'irfst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 348</li><li><span class='xr-has-index'>lat</span>: 96</li><li><span class='xr-has-index'>lon</span>: 192</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-78716537-b62f-4420-a121-1e7972347057' class='xr-array-in' type='checkbox' checked><label for='section-78716537-b62f-4420-a121-1e7972347057' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array&lt;chunksize=(12, 96, 192), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
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       "       18791130.994444, 18791231.994444])</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 1.875 3.75 ... 356.2 358.1</div><input id='attrs-3572b517-afac-4f88-ae7e-15dc53c5f158' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3572b517-afac-4f88-ae7e-15dc53c5f158' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6e66082-7d88-4259-a60e-db9e3c823e5c' class='xr-var-data-in' type='checkbox'><label for='data-b6e66082-7d88-4259-a60e-db9e3c823e5c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.   ,   1.875,   3.75 ,   5.625,   7.5  ,   9.375,  11.25 ,  13.125,\n",
       "        15.   ,  16.875,  18.75 ,  20.625,  22.5  ,  24.375,  26.25 ,  28.125,\n",
       "        30.   ,  31.875,  33.75 ,  35.625,  37.5  ,  39.375,  41.25 ,  43.125,\n",
       "        45.   ,  46.875,  48.75 ,  50.625,  52.5  ,  54.375,  56.25 ,  58.125,\n",
       "        60.   ,  61.875,  63.75 ,  65.625,  67.5  ,  69.375,  71.25 ,  73.125,\n",
       "        75.   ,  76.875,  78.75 ,  80.625,  82.5  ,  84.375,  86.25 ,  88.125,\n",
       "        90.   ,  91.875,  93.75 ,  95.625,  97.5  ,  99.375, 101.25 , 103.125,\n",
       "       105.   , 106.875, 108.75 , 110.625, 112.5  , 114.375, 116.25 , 118.125,\n",
       "       120.   , 121.875, 123.75 , 125.625, 127.5  , 129.375, 131.25 , 133.125,\n",
       "       135.   , 136.875, 138.75 , 140.625, 142.5  , 144.375, 146.25 , 148.125,\n",
       "       150.   , 151.875, 153.75 , 155.625, 157.5  , 159.375, 161.25 , 163.125,\n",
       "       165.   , 166.875, 168.75 , 170.625, 172.5  , 174.375, 176.25 , 178.125,\n",
       "       180.   , 181.875, 183.75 , 185.625, 187.5  , 189.375, 191.25 , 193.125,\n",
       "       195.   , 196.875, 198.75 , 200.625, 202.5  , 204.375, 206.25 , 208.125,\n",
       "       210.   , 211.875, 213.75 , 215.625, 217.5  , 219.375, 221.25 , 223.125,\n",
       "       225.   , 226.875, 228.75 , 230.625, 232.5  , 234.375, 236.25 , 238.125,\n",
       "       240.   , 241.875, 243.75 , 245.625, 247.5  , 249.375, 251.25 , 253.125,\n",
       "       255.   , 256.875, 258.75 , 260.625, 262.5  , 264.375, 266.25 , 268.125,\n",
       "       270.   , 271.875, 273.75 , 275.625, 277.5  , 279.375, 281.25 , 283.125,\n",
       "       285.   , 286.875, 288.75 , 290.625, 292.5  , 294.375, 296.25 , 298.125,\n",
       "       300.   , 301.875, 303.75 , 305.625, 307.5  , 309.375, 311.25 , 313.125,\n",
       "       315.   , 316.875, 318.75 , 320.625, 322.5  , 324.375, 326.25 , 328.125,\n",
       "       330.   , 331.875, 333.75 , 335.625, 337.5  , 339.375, 341.25 , 343.125,\n",
       "       345.   , 346.875, 348.75 , 350.625, 352.5  , 354.375, 356.25 , 358.125])</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'>88.57 86.72 84.86 ... -86.72 -88.57</div><input id='attrs-4d6b4c61-1cc9-4f5d-a806-2034ca6454d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4d6b4c61-1cc9-4f5d-a806-2034ca6454d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a9c9f359-9e6a-47a9-ac75-5117f1b00251' class='xr-var-data-in' type='checkbox'><label for='data-a9c9f359-9e6a-47a9-ac75-5117f1b00251' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([ 88.572169,  86.722531,  84.86197 ,  82.998942,  81.134977,  79.270559,\n",
       "        77.405888,  75.541061,  73.676132,  71.811132,  69.946081,  68.080991,\n",
       "        66.215872,  64.35073 ,  62.485571,  60.620396,  58.755209,  56.890013,\n",
       "        55.024808,  53.159595,  51.294377,  49.429154,  47.563926,  45.698694,\n",
       "        43.833459,  41.96822 ,  40.102979,  38.237736,  36.372491,  34.507243,\n",
       "        32.641994,  30.776744,  28.911492,  27.046239,  25.180986,  23.315731,\n",
       "        21.450475,  19.585219,  17.719962,  15.854704,  13.989446,  12.124187,\n",
       "        10.258928,   8.393669,   6.528409,   4.66315 ,   2.79789 ,   0.93263 ,\n",
       "        -0.93263 ,  -2.79789 ,  -4.66315 ,  -6.528409,  -8.393669, -10.258928,\n",
       "       -12.124187, -13.989446, -15.854704, -17.719962, -19.585219, -21.450475,\n",
       "       -23.315731, -25.180986, -27.046239, -28.911492, -30.776744, -32.641994,\n",
       "       -34.507243, -36.372491, -38.237736, -40.102979, -41.96822 , -43.833459,\n",
       "       -45.698694, -47.563926, -49.429154, -51.294377, -53.159595, -55.024808,\n",
       "       -56.890013, -58.755209, -60.620396, -62.485571, -64.35073 , -66.215872,\n",
       "       -68.080991, -69.946081, -71.811132, -73.676132, -75.541061, -77.405888,\n",
       "       -79.270559, -81.134977, -82.998942, -84.86197 , -86.722531, -88.572169])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9c75ee06-d965-43b3-9853-70686a0bf110' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9c75ee06-d965-43b3-9853-70686a0bf110' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>Mean instantaneous shortwave forcing at top of the atmosphere for all sky</dd><dt><span>units :</span></dt><dd>W/m^2</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'irfst' (time: 348, lat: 96, lon: 192)>\n",
       "dask.array<mean_agg-aggregate, shape=(348, 96, 192), dtype=float32, chunksize=(12, 96, 192), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * time     (time) float64 1.851e+07 1.851e+07 ... 1.879e+07 1.879e+07\n",
       "  * lon      (lon) float64 0.0 1.875 3.75 5.625 7.5 ... 352.5 354.4 356.2 358.1\n",
       "  * lat      (lat) float64 88.57 86.72 84.86 83.0 ... -83.0 -84.86 -86.72 -88.57\n",
       "Attributes:\n",
       "    name:     Mean instantaneous shortwave forcing at top of the atmosphere f...\n",
       "    units:    W/m^2"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.irfst"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-11-22T14:19:43.936254Z",
     "start_time": "2021-11-22T14:19:43.837245Z"
    }
   },
   "outputs": [],
   "source": [
    "# compute erf and adj\n",
    "# load clt from piclim spaer aer and plclim control"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-11-22T14:19:44.370093Z",
     "start_time": "2021-11-22T14:19:43.938991Z"
    }
   },
   "outputs": [],
   "source": [
    "path = '/work/bb1198/m300385/RFMIP/IRF/IPSL/piClim-spAer-anthroO3/CM616-LR-piClim-spAer-anthroO3-4-2RadCall_20140101_20431231_1M_irfstar.nc'\n",
    "ipsl_irf = xr.open_dataset(path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-11-22T14:19:44.444579Z",
     "start_time": "2021-11-22T14:19:44.371379Z"
    }
   },
   "outputs": [
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       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:               (lat: 143, lon: 144, presnivs: 79, time_counter: 360, axis_nbounds: 2)\n",
       "Coordinates:\n",
       "  * lat                   (lat) float32 90.0 88.73 87.46 ... -87.46 -88.73 -90.0\n",
       "  * lon                   (lon) float32 -180.0 -177.5 -175.0 ... 175.0 177.5\n",
       "  * presnivs              (presnivs) float32 1.012e+05 1.009e+05 ... 5.297 1.483\n",
       "  * time_counter          (time_counter) object 2014-01-16 12:00:00 ... 2043-...\n",
       "    time_centered         (time_counter) object 2014-01-16 12:00:00 ... 2043-...\n",
       "Dimensions without coordinates: axis_nbounds\n",
       "Data variables:\n",
       "    time_centered_bounds  (time_counter, axis_nbounds) object 2014-01-01 00:0...\n",
       "    aire                  (lat, lon) float32 1.084e+08 1.084e+08 ... 1.084e+08\n",
       "    irfstar               (time_counter, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    name:                      histmth\n",
       "    description:               Created by xios\n",
       "    title:                     Created by xios\n",
       "    Conventions:               CF-1.6\n",
       "    timeStamp:                 2019-May-03 23:59:29 GMT\n",
       "    uuid:                      12dcdf9e-a910-41c6-bf2f-bd364488cee1\n",
       "    LongName:                  IPSLCM6.1.6-LR\n",
       "    history:                   Sat May  4 16:32:20 2019: ncrcat -C --buffer_s...\n",
       "    NCO:                       &quot;4.6.0&quot;\n",
       "    nco_openmp_thread_number:  1</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-e6d1d3f3-64a7-4243-a323-2601e71c483a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e6d1d3f3-64a7-4243-a323-2601e71c483a' 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>: 143</li><li><span class='xr-has-index'>lon</span>: 144</li><li><span class='xr-has-index'>presnivs</span>: 79</li><li><span class='xr-has-index'>time_counter</span>: 360</li><li><span>axis_nbounds</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ff4b4223-2a1b-4118-b3b3-1474c7bb4946' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ff4b4223-2a1b-4118-b3b3-1474c7bb4946' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>90.0 88.73 87.46 ... -88.73 -90.0</div><input id='attrs-04d3a8ef-02b5-4609-8ce6-7e5febf45c4d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-04d3a8ef-02b5-4609-8ce6-7e5febf45c4d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-804dfa77-3ac4-44a4-a14d-7a1be5f60fba' class='xr-var-data-in' type='checkbox'><label for='data-804dfa77-3ac4-44a4-a14d-7a1be5f60fba' title='Show/Hide data 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_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.      ,  88.73239 ,  87.46479 ,  86.19718 ,  84.92958 ,  83.66197 ,\n",
       "        82.39436 ,  81.12676 ,  79.85915 ,  78.59155 ,  77.323944,  76.056335,\n",
       "        74.788734,  73.521126,  72.253525,  70.985916,  69.71831 ,  68.45071 ,\n",
       "        67.1831  ,  65.91549 ,  64.64789 ,  63.380283,  62.112675,  60.84507 ,\n",
       "        59.577465,  58.30986 ,  57.042255,  55.774647,  54.507042,  53.239437,\n",
       "        51.971832,  50.704224,  49.43662 ,  48.169014,  46.90141 ,  45.633804,\n",
       "        44.366196,  43.09859 ,  41.830986,  40.56338 ,  39.295776,  38.028168,\n",
       "        36.760563,  35.492958,  34.225353,  32.957745,  31.690142,  30.422535,\n",
       "        29.15493 ,  27.887323,  26.619719,  25.352112,  24.084507,  22.816902,\n",
       "        21.549295,  20.28169 ,  19.014084,  17.746479,  16.478872,  15.211267,\n",
       "        13.943662,  12.676056,  11.408451,  10.140845,   8.87324 ,   7.605634,\n",
       "         6.338028,   5.070423,   3.802817,   2.535211,   1.267606,   0.      ,\n",
       "        -1.267606,  -2.535211,  -3.802817,  -5.070423,  -6.338028,  -7.605634,\n",
       "        -8.87324 , -10.140845, -11.408451, -12.676056, -13.943662, -15.211267,\n",
       "       -16.478872, -17.746479, -19.014084, -20.28169 , -21.549295, -22.816902,\n",
       "       -24.084507, -25.352112, -26.619719, -27.887323, -29.15493 , -30.422535,\n",
       "       -31.690142, -32.957745, -34.225353, -35.492958, -36.760563, -38.028168,\n",
       "       -39.295776, -40.56338 , -41.830986, -43.09859 , -44.366196, -45.633804,\n",
       "       -46.90141 , -48.169014, -49.43662 , -50.704224, -51.971832, -53.239437,\n",
       "       -54.507042, -55.774647, -57.042255, -58.30986 , -59.577465, -60.84507 ,\n",
       "       -62.112675, -63.380283, -64.64789 , -65.91549 , -67.1831  , -68.45071 ,\n",
       "       -69.71831 , -70.985916, -72.253525, -73.521126, -74.788734, -76.056335,\n",
       "       -77.323944, -78.59155 , -79.85915 , -81.12676 , -82.39436 , -83.66197 ,\n",
       "       -84.92958 , -86.19718 , -87.46479 , -88.73239 , -90.      ],\n",
       "      dtype=float32)</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'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -177.5 ... 175.0 177.5</div><input id='attrs-fa69061c-2f55-4793-9e0a-7ac7ff4a6d85' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa69061c-2f55-4793-9e0a-7ac7ff4a6d85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85631592-c8f5-44c1-b17e-6b6e04e2d85c' class='xr-var-data-in' type='checkbox'><label for='data-85631592-c8f5-44c1-b17e-6b6e04e2d85c' title='Show/Hide data 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-180. , -177.5, -175. , -172.5, -170. , -167.5, -165. , -162.5, -160. ,\n",
       "       -157.5, -155. , -152.5, -150. , -147.5, -145. , -142.5, -140. , -137.5,\n",
       "       -135. , -132.5, -130. , -127.5, -125. , -122.5, -120. , -117.5, -115. ,\n",
       "       -112.5, -110. , -107.5, -105. , -102.5, -100. ,  -97.5,  -95. ,  -92.5,\n",
       "        -90. ,  -87.5,  -85. ,  -82.5,  -80. ,  -77.5,  -75. ,  -72.5,  -70. ,\n",
       "        -67.5,  -65. ,  -62.5,  -60. ,  -57.5,  -55. ,  -52.5,  -50. ,  -47.5,\n",
       "        -45. ,  -42.5,  -40. ,  -37.5,  -35. ,  -32.5,  -30. ,  -27.5,  -25. ,\n",
       "        -22.5,  -20. ,  -17.5,  -15. ,  -12.5,  -10. ,   -7.5,   -5. ,   -2.5,\n",
       "          0. ,    2.5,    5. ,    7.5,   10. ,   12.5,   15. ,   17.5,   20. ,\n",
       "         22.5,   25. ,   27.5,   30. ,   32.5,   35. ,   37.5,   40. ,   42.5,\n",
       "         45. ,   47.5,   50. ,   52.5,   55. ,   57.5,   60. ,   62.5,   65. ,\n",
       "         67.5,   70. ,   72.5,   75. ,   77.5,   80. ,   82.5,   85. ,   87.5,\n",
       "         90. ,   92.5,   95. ,   97.5,  100. ,  102.5,  105. ,  107.5,  110. ,\n",
       "        112.5,  115. ,  117.5,  120. ,  122.5,  125. ,  127.5,  130. ,  132.5,\n",
       "        135. ,  137.5,  140. ,  142.5,  145. ,  147.5,  150. ,  152.5,  155. ,\n",
       "        157.5,  160. ,  162.5,  165. ,  167.5,  170. ,  172.5,  175. ,  177.5],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>presnivs</span></div><div class='xr-var-dims'>(presnivs)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.012e+05 1.009e+05 ... 5.297 1.483</div><input id='attrs-3a978433-6005-4aba-870d-f2bb7ada6d5e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a978433-6005-4aba-870d-f2bb7ada6d5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-202a6f20-d736-49b3-b7cd-162f9511da69' class='xr-var-data-in' type='checkbox'><label for='data-202a6f20-d736-49b3-b7cd-162f9511da69' title='Show/Hide data 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>name :</span></dt><dd>presnivs</dd><dt><span>standard_name :</span></dt><dd>Vertical levels</dd><dt><span>units :</span></dt><dd>Pa</dd></dl></div><div class='xr-var-data'><pre>array([1.012021e+05, 1.009424e+05, 1.006534e+05, 1.003319e+05, 9.997420e+04,\n",
       "       9.957655e+04, 9.913467e+04, 9.864384e+04, 9.809898e+04, 9.749448e+04,\n",
       "       9.682430e+04, 9.608191e+04, 9.526024e+04, 9.435173e+04, 9.334834e+04,\n",
       "       9.224155e+04, 9.102246e+04, 8.968182e+04, 8.821020e+04, 8.659811e+04,\n",
       "       8.483623e+04, 8.291569e+04, 8.082840e+04, 7.856748e+04, 7.612779e+04,\n",
       "       7.350645e+04, 7.070354e+04, 6.772281e+04, 6.457239e+04, 6.126538e+04,\n",
       "       5.782047e+04, 5.426217e+04, 5.062074e+04, 4.693169e+04, 4.323469e+04,\n",
       "       3.957199e+04, 3.598637e+04, 3.251885e+04, 2.920636e+04, 2.607983e+04,\n",
       "       2.316271e+04, 2.047042e+04, 1.801036e+04, 1.578271e+04, 1.378158e+04,\n",
       "       1.199642e+04, 1.041344e+04, 9.016865e+03, 7.790020e+03, 6.716147e+03,\n",
       "       5.778999e+03, 4.963233e+03, 4.254644e+03, 3.640276e+03, 3.108450e+03,\n",
       "       2.648733e+03, 2.251867e+03, 1.909687e+03, 1.615018e+03, 1.361581e+03,\n",
       "       1.143891e+03, 9.571722e+02, 7.972696e+02, 6.605754e+02, 5.439607e+02,\n",
       "       4.447146e+02, 3.604912e+02, 2.892627e+02, 2.292787e+02, 1.790303e+02,\n",
       "       1.372198e+02, 1.027344e+02, 7.462312e+01, 5.207758e+01, 3.441441e+01,\n",
       "       2.105668e+01, 1.150741e+01, 5.296797e+00, 1.483435e+00], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_counter</span></div><div class='xr-var-dims'>(time_counter)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>2014-01-16 12:00:00 ... 2043-12-...</div><input id='attrs-cc8aade1-ad65-4f4d-81ca-a7e5e254311d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc8aade1-ad65-4f4d-81ca-a7e5e254311d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10d7a22c-a5aa-4029-9701-0fef08af4bbb' class='xr-var-data-in' type='checkbox'><label for='data-10d7a22c-a5aa-4029-9701-0fef08af4bbb' title='Show/Hide data 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>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time axis</dd><dt><span>time_origin :</span></dt><dd>2014-01-01 00:00:00</dd><dt><span>bounds :</span></dt><dd>time_counter_bounds</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(2014, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2014, 2, 15, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2014, 3, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       ...,\n",
       "       cftime.DatetimeNoLeap(2043, 10, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2043, 11, 16, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2043, 12, 16, 12, 0, 0, 0, has_year_zero=True)],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_centered</span></div><div class='xr-var-dims'>(time_counter)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a0045156-5bd6-441e-8a0f-c9bc52c3da73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0045156-5bd6-441e-8a0f-c9bc52c3da73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a33c528c-335e-45f7-a2c0-00b269cdb05b' class='xr-var-data-in' type='checkbox'><label for='data-a33c528c-335e-45f7-a2c0-00b269cdb05b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time axis</dd><dt><span>time_origin :</span></dt><dd>2014-01-01 00:00:00</dd><dt><span>bounds :</span></dt><dd>time_centered_bounds</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(2014, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2014, 2, 15, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2014, 3, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       ...,\n",
       "       cftime.DatetimeNoLeap(2043, 10, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2043, 11, 16, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2043, 12, 16, 12, 0, 0, 0, has_year_zero=True)],\n",
       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-66fd48e0-0479-485a-9c83-5f3b87df9ccd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-66fd48e0-0479-485a-9c83-5f3b87df9ccd' class='xr-section-summary' >Data variables: <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>time_centered_bounds</span></div><div class='xr-var-dims'>(time_counter, axis_nbounds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b574c22d-c84b-456d-a9ce-206d843591b6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b574c22d-c84b-456d-a9ce-206d843591b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5cec214-d50a-4534-8bc8-82708b68bbb4' class='xr-var-data-in' type='checkbox'><label for='data-c5cec214-d50a-4534-8bc8-82708b68bbb4' title='Show/Hide data 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([[cftime.DatetimeNoLeap(2014, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2014, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2014, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2014, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2014, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2014, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       ...,\n",
       "       [cftime.DatetimeNoLeap(2043, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2043, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2043, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2043, 12, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2043, 12, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2044, 1, 1, 0, 0, 0, 0, has_year_zero=True)]],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aire</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2b6831ec-c3c4-4bc7-ae12-664002384cdd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b6831ec-c3c4-4bc7-ae12-664002384cdd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02021d99-85d1-4edb-a406-b5ed123c298c' class='xr-var-data-in' type='checkbox'><label for='data-02021d99-85d1-4edb-a406-b5ed123c298c' title='Show/Hide data 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>Grid area</dd><dt><span>units :</span></dt><dd>-</dd><dt><span>online_operation :</span></dt><dd>once</dd></dl></div><div class='xr-var-data'><pre>array([[1.083664e+08, 1.083664e+08, 1.083664e+08, ..., 1.083664e+08,\n",
       "        1.083664e+08, 1.083664e+08],\n",
       "       [8.668516e+08, 8.668516e+08, 8.668516e+08, ..., 8.668516e+08,\n",
       "        8.668516e+08, 8.668516e+08],\n",
       "       [1.733279e+09, 1.733279e+09, 1.733279e+09, ..., 1.733279e+09,\n",
       "        1.733279e+09, 1.733279e+09],\n",
       "       ...,\n",
       "       [1.733279e+09, 1.733279e+09, 1.733279e+09, ..., 1.733279e+09,\n",
       "        1.733279e+09, 1.733279e+09],\n",
       "       [8.668516e+08, 8.668516e+08, 8.668516e+08, ..., 8.668516e+08,\n",
       "        8.668516e+08, 8.668516e+08],\n",
       "       [1.083664e+08, 1.083664e+08, 1.083664e+08, ..., 1.083664e+08,\n",
       "        1.083664e+08, 1.083664e+08]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>irfstar</span></div><div class='xr-var-dims'>(time_counter, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-99acccf0-f8b0-4531-bf8c-bfa52ed09f98' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-99acccf0-f8b0-4531-bf8c-bfa52ed09f98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f894ac7-81f2-4c97-adea-881297eecd20' class='xr-var-data-in' type='checkbox'><label for='data-5f894ac7-81f2-4c97-adea-881297eecd20' title='Show/Hide data 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>Instantaneous Net Shortwave Radiative Forcing at TOA due to Aerosol-Radiation interaction</dd><dt><span>units :</span></dt><dd>W/m2</dd><dt><span>online_operation :</span></dt><dd>average</dd><dt><span>interval_operation :</span></dt><dd>900 s</dd><dt><span>interval_write :</span></dt><dd>1 month</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 900 s)</dd></dl></div><div class='xr-var-data'><pre>[7413120 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bebfe825-0507-48d2-ab48-d705b488c36d' class='xr-section-summary-in' type='checkbox'  ><label for='section-bebfe825-0507-48d2-ab48-d705b488c36d' class='xr-section-summary' >Attributes: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>histmth</dd><dt><span>description :</span></dt><dd>Created by xios</dd><dt><span>title :</span></dt><dd>Created by xios</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>timeStamp :</span></dt><dd>2019-May-03 23:59:29 GMT</dd><dt><span>uuid :</span></dt><dd>12dcdf9e-a910-41c6-bf2f-bd364488cee1</dd><dt><span>LongName :</span></dt><dd>IPSLCM6.1.6-LR</dd><dt><span>history :</span></dt><dd>Sat May  4 16:32:20 2019: ncrcat -C --buffer_size 838860800 -p /ccc/scratch/cont003/gencmip6/p25sima/IGCM_OUT/LMDZOR/PROD/piClim-spAer-anthro/CM616-LR-piClim-spAer-anthroO3-4-2RadCall/ATM/Output/MO CM616-LR-piClim-spAer-anthroO3-4-2RadCall_20140101_20141231_1M_histmth.nc CM616-LR-piClim-spAer-anthroO3-4-2RadCall_20150101_20151231_1M_histmth.nc CM616-LR-piClim-spAer-anthroO3-4-2RadCall_20160101_20161231_1M_histmth.nc CM616-LR-piClim-spAer-anthroO3-4-2RadCall_20170101_20171231_1M_histmth.nc CM616-LR-piClim-spAer-anthroO3-4-2RadCall_20180101_20181231_1M_histmth.nc CM616-LR-piClim-spAer-anthroO3-4-2RadCall_20190101_20191231_1M_histmth.nc CM616-LR-piClim-spAer-anthroO3-4-2RadCall_20200101_20201231_1M_histmth.nc CM616-LR-piClim-spAer-anthroO3-4-2RadCall_20210101_20211231_1M_histmth.nc CM616-LR-piClim-spAer-anthroO3-4-2RadCall_20220101_20221231_1M_histmth.nc CM616-LR-piClim-spAer-anthroO3-4-2RadCall_20230101_20231231_1M_histmth.nc --output CM616-LR-piClim-spAer-anthroO3-4-2RadCall_20140101_20231231_1M_histmth.nc</dd><dt><span>NCO :</span></dt><dd>&quot;4.6.0&quot;</dd><dt><span>nco_openmp_thread_number :</span></dt><dd>1</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:               (lat: 143, lon: 144, presnivs: 79, time_counter: 360, axis_nbounds: 2)\n",
       "Coordinates:\n",
       "  * lat                   (lat) float32 90.0 88.73 87.46 ... -87.46 -88.73 -90.0\n",
       "  * lon                   (lon) float32 -180.0 -177.5 -175.0 ... 175.0 177.5\n",
       "  * presnivs              (presnivs) float32 1.012e+05 1.009e+05 ... 5.297 1.483\n",
       "  * time_counter          (time_counter) object 2014-01-16 12:00:00 ... 2043-...\n",
       "    time_centered         (time_counter) object ...\n",
       "Dimensions without coordinates: axis_nbounds\n",
       "Data variables:\n",
       "    time_centered_bounds  (time_counter, axis_nbounds) object ...\n",
       "    aire                  (lat, lon) float32 ...\n",
       "    irfstar               (time_counter, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    name:                      histmth\n",
       "    description:               Created by xios\n",
       "    title:                     Created by xios\n",
       "    Conventions:               CF-1.6\n",
       "    timeStamp:                 2019-May-03 23:59:29 GMT\n",
       "    uuid:                      12dcdf9e-a910-41c6-bf2f-bd364488cee1\n",
       "    LongName:                  IPSLCM6.1.6-LR\n",
       "    history:                   Sat May  4 16:32:20 2019: ncrcat -C --buffer_s...\n",
       "    NCO:                       \"4.6.0\"\n",
       "    nco_openmp_thread_number:  1"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipsl_irf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-11-22T14:19:47.641304Z",
     "start_time": "2021-11-22T14:19:44.446073Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>dcpp_init_year</th>\n",
       "      <th>version</th>\n",
       "      <th>time_range</th>\n",
       "      <th>path</th>\n",
       "      <th>opendap_url</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RFMIP</td>\n",
       "      <td>EC-Earth-Consortium</td>\n",
       "      <td>EC-Earth3</td>\n",
       "      <td>piClim-aer</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>Amon</td>\n",
       "      <td>clt</td>\n",
       "      <td>gr</td>\n",
       "      <td>NaN</td>\n",
       "      <td>v20200324</td>\n",
       "      <td>185001-185012</td>\n",
       "      <td>/mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...</td>\n",
       "      <td>http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RFMIP</td>\n",
       "      <td>EC-Earth-Consortium</td>\n",
       "      <td>EC-Earth3</td>\n",
       "      <td>piClim-aer</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>Amon</td>\n",
       "      <td>clt</td>\n",
       "      <td>gr</td>\n",
       "      <td>NaN</td>\n",
       "      <td>v20200324</td>\n",
       "      <td>185101-185112</td>\n",
       "      <td>/mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...</td>\n",
       "      <td>http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RFMIP</td>\n",
       "      <td>EC-Earth-Consortium</td>\n",
       "      <td>EC-Earth3</td>\n",
       "      <td>piClim-aer</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>Amon</td>\n",
       "      <td>clt</td>\n",
       "      <td>gr</td>\n",
       "      <td>NaN</td>\n",
       "      <td>v20200324</td>\n",
       "      <td>185201-185212</td>\n",
       "      <td>/mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...</td>\n",
       "      <td>http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>RFMIP</td>\n",
       "      <td>EC-Earth-Consortium</td>\n",
       "      <td>EC-Earth3</td>\n",
       "      <td>piClim-aer</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>Amon</td>\n",
       "      <td>clt</td>\n",
       "      <td>gr</td>\n",
       "      <td>NaN</td>\n",
       "      <td>v20200324</td>\n",
       "      <td>185301-185312</td>\n",
       "      <td>/mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...</td>\n",
       "      <td>http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RFMIP</td>\n",
       "      <td>EC-Earth-Consortium</td>\n",
       "      <td>EC-Earth3</td>\n",
       "      <td>piClim-aer</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>Amon</td>\n",
       "      <td>clt</td>\n",
       "      <td>gr</td>\n",
       "      <td>NaN</td>\n",
       "      <td>v20200324</td>\n",
       "      <td>185401-185412</td>\n",
       "      <td>/mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...</td>\n",
       "      <td>http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  activity_id       institution_id  source_id experiment_id member_id  \\\n",
       "0       RFMIP  EC-Earth-Consortium  EC-Earth3    piClim-aer  r1i1p1f1   \n",
       "1       RFMIP  EC-Earth-Consortium  EC-Earth3    piClim-aer  r1i1p1f1   \n",
       "2       RFMIP  EC-Earth-Consortium  EC-Earth3    piClim-aer  r1i1p1f1   \n",
       "3       RFMIP  EC-Earth-Consortium  EC-Earth3    piClim-aer  r1i1p1f1   \n",
       "4       RFMIP  EC-Earth-Consortium  EC-Earth3    piClim-aer  r1i1p1f1   \n",
       "\n",
       "  table_id variable_id grid_label  dcpp_init_year    version     time_range  \\\n",
       "0     Amon         clt         gr             NaN  v20200324  185001-185012   \n",
       "1     Amon         clt         gr             NaN  v20200324  185101-185112   \n",
       "2     Amon         clt         gr             NaN  v20200324  185201-185212   \n",
       "3     Amon         clt         gr             NaN  v20200324  185301-185312   \n",
       "4     Amon         clt         gr             NaN  v20200324  185401-185412   \n",
       "\n",
       "                                                path  \\\n",
       "0  /mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...   \n",
       "1  /mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...   \n",
       "2  /mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...   \n",
       "3  /mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...   \n",
       "4  /mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...   \n",
       "\n",
       "                                         opendap_url  \n",
       "0  http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...  \n",
       "1  http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...  \n",
       "2  http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...  \n",
       "3  http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...  \n",
       "4  http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read in the saved json file and load the models\n",
    "json_file = '/mnt/lustre01/pf/b/b381265/rfmip_analysis/rfmip_models.json'\n",
    "collection = intake.open_esm_datastore(json_file)\n",
    "collection.df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-11-22T14:19:47.680441Z",
     "start_time": "2021-11-22T14:19:47.643985Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "  <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>dcpp_init_year</th>\n",
       "      <th>version</th>\n",
       "      <th>time_range</th>\n",
       "      <th>path</th>\n",
       "      <th>opendap_url</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RFMIP</td>\n",
       "      <td>IPSL</td>\n",
       "      <td>IPSL-CM6A-LR</td>\n",
       "      <td>piClim-control</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>Amon</td>\n",
       "      <td>clt</td>\n",
       "      <td>gr</td>\n",
       "      <td>NaN</td>\n",
       "      <td>v20181204</td>\n",
       "      <td>201401-204312</td>\n",
       "      <td>/mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...</td>\n",
       "      <td>http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RFMIP</td>\n",
       "      <td>IPSL</td>\n",
       "      <td>IPSL-CM6A-LR</td>\n",
       "      <td>piClim-control</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>Amon</td>\n",
       "      <td>rlut</td>\n",
       "      <td>gr</td>\n",
       "      <td>NaN</td>\n",
       "      <td>v20181204</td>\n",
       "      <td>201401-204312</td>\n",
       "      <td>/mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...</td>\n",
       "      <td>http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RFMIP</td>\n",
       "      <td>IPSL</td>\n",
       "      <td>IPSL-CM6A-LR</td>\n",
       "      <td>piClim-control</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>Amon</td>\n",
       "      <td>rsdt</td>\n",
       "      <td>gr</td>\n",
       "      <td>NaN</td>\n",
       "      <td>v20181204</td>\n",
       "      <td>201401-204312</td>\n",
       "      <td>/mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...</td>\n",
       "      <td>http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>RFMIP</td>\n",
       "      <td>IPSL</td>\n",
       "      <td>IPSL-CM6A-LR</td>\n",
       "      <td>piClim-control</td>\n",
       "      <td>r1i1p1f1</td>\n",
       "      <td>Amon</td>\n",
       "      <td>rsut</td>\n",
       "      <td>gr</td>\n",
       "      <td>NaN</td>\n",
       "      <td>v20181204</td>\n",
       "      <td>201401-204312</td>\n",
       "      <td>/mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...</td>\n",
       "      <td>http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RFMIP</td>\n",
       "      <td>IPSL</td>\n",
       "      <td>IPSL-CM6A-LR</td>\n",
       "      <td>piClim-control</td>\n",
       "      <td>r2i1p1f1</td>\n",
       "      <td>Amon</td>\n",
       "      <td>clt</td>\n",
       "      <td>gr</td>\n",
       "      <td>NaN</td>\n",
       "      <td>v20181204</td>\n",
       "      <td>201401-204312</td>\n",
       "      <td>/mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...</td>\n",
       "      <td>http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  activity_id institution_id     source_id   experiment_id member_id table_id  \\\n",
       "0       RFMIP           IPSL  IPSL-CM6A-LR  piClim-control  r1i1p1f1     Amon   \n",
       "1       RFMIP           IPSL  IPSL-CM6A-LR  piClim-control  r1i1p1f1     Amon   \n",
       "2       RFMIP           IPSL  IPSL-CM6A-LR  piClim-control  r1i1p1f1     Amon   \n",
       "3       RFMIP           IPSL  IPSL-CM6A-LR  piClim-control  r1i1p1f1     Amon   \n",
       "4       RFMIP           IPSL  IPSL-CM6A-LR  piClim-control  r2i1p1f1     Amon   \n",
       "\n",
       "  variable_id grid_label  dcpp_init_year    version     time_range  \\\n",
       "0         clt         gr             NaN  v20181204  201401-204312   \n",
       "1        rlut         gr             NaN  v20181204  201401-204312   \n",
       "2        rsdt         gr             NaN  v20181204  201401-204312   \n",
       "3        rsut         gr             NaN  v20181204  201401-204312   \n",
       "4         clt         gr             NaN  v20181204  201401-204312   \n",
       "\n",
       "                                                path  \\\n",
       "0  /mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...   \n",
       "1  /mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...   \n",
       "2  /mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...   \n",
       "3  /mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...   \n",
       "4  /mnt/lustre02/work/ik1017/CMIP6/data/CMIP6/RFM...   \n",
       "\n",
       "                                         opendap_url  \n",
       "0  http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...  \n",
       "1  http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...  \n",
       "2  http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...  \n",
       "3  http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...  \n",
       "4  http://esgf3.dkrz.de/thredds/dodsC/cmip6/RFMIP...  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "subset = collection.search(source_id = ['IPSL-CM6A-LR','MPI-ESM1-2-LR'],\n",
    "                           experiment_id=['piClim-control','piClim-spAer-aer'],\n",
    "                           variable_id=['clt', 'rsdt', 'rlut', 'rsut']\n",
    "                          ) \n",
    "subset.df.head()"
   ]
  },
  {
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   "execution_count": 15,
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     "end_time": "2021-11-22T14:20:04.488843Z",
     "start_time": "2021-11-22T14:19:47.681662Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--> The keys in the returned dictionary of datasets are constructed as follows:\n",
      "\t'activity_id.institution_id.source_id.experiment_id.table_id.grid_label'\n"
     ]
    },
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    "kwargs = {\n",
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    "        'consolidated':True,\n",
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    "        'decode_times':True\n",
    "    }\n",
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    "dset_dict = subset.to_dataset_dict(**kwargs)"
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     "end_time": "2021-11-22T14:20:04.498233Z",
     "start_time": "2021-11-22T14:20:04.491910Z"
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    {
     "data": {
      "text/plain": [
       "['RFMIP.IPSL.IPSL-CM6A-LR.piClim-control.Amon.gr',\n",
       " 'RFMIP.IPSL.IPSL-CM6A-LR.piClim-spAer-aer.Amon.gr',\n",
       " 'RFMIP.MPI-M.MPI-ESM1-2-LR.piClim-control.Amon.gn',\n",
       " 'RFMIP.MPI-M.MPI-ESM1-2-LR.piClim-spAer-aer.Amon.gn']"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[key for key in dset_dict.keys()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-11-22T14:20:25.567664Z",
     "start_time": "2021-11-22T14:20:04.500946Z"
    }
   },
   "outputs": [],
   "source": [
    "ipsl_control = dset_dict['RFMIP.IPSL.IPSL-CM6A-LR.piClim-control.Amon.gr'].load().mean(dim='member_id', keep_attrs=True)\n",
    "ipsl_spaer = dset_dict['RFMIP.IPSL.IPSL-CM6A-LR.piClim-spAer-aer.Amon.gr'].load().mean(dim='member_id', keep_attrs=True)\n",
    "#noresm_control = dset_dict['RFMIP.NCC.NorESM2-LM.piClim-control.Amon.gn'].load().mean(dim='member_id', keep_attrs=True)\n",
    "#noresm_spaer = dset_dict['RFMIP.NCC.NorESM2-LM.piClim-spAer-aer.Amon.gn'].load().mean(dim='member_id', keep_attrs=True)\n",
    "mpiesm_control = dset_dict['RFMIP.MPI-M.MPI-ESM1-2-LR.piClim-control.Amon.gn'].load().mean(dim='member_id', keep_attrs=True)\n",
    "mpiesm_spaer = dset_dict['RFMIP.MPI-M.MPI-ESM1-2-LR.piClim-spAer-aer.Amon.gn'].load().mean(dim='member_id', keep_attrs=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-11-22T14:20:25.883461Z",
     "start_time": "2021-11-22T14:20:25.569052Z"
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   },
   "outputs": [],
   "source": [
    "# compute erf for both models\n",
    "\n",
    "erf_mpi = compute_forcings_allsky(data_aerosols=mpiesm_spaer, data_control=mpiesm_control)[0][24:]\n",
    "erf_ipsl = compute_forcings_allsky(data_aerosols=ipsl_spaer, data_control=ipsl_control)[0][12:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-11-22T14:20:25.914945Z",
     "start_time": "2021-11-22T14:20:25.886002Z"
    }
   },
   "outputs": [
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       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;irfstar&#x27; (time: 348, lat: 143, lon: 144)&gt;\n",
       "[7166016 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * lat            (lat) float32 90.0 88.73 87.46 86.2 ... -87.46 -88.73 -90.0\n",
       "  * lon            (lon) float32 -180.0 -177.5 -175.0 ... 172.5 175.0 177.5\n",
       "    time_counter   (time) object 2015-01-16 12:00:00 ... 2043-12-16 12:00:00\n",
       "    time_centered  (time) object 2015-01-16 12:00:00 ... 2043-12-16 12:00:00\n",
       "Dimensions without coordinates: time\n",
       "Attributes:\n",
       "    long_name:           Instantaneous Net Shortwave Radiative Forcing at TOA...\n",
       "    units:               W/m2\n",
       "    online_operation:    average\n",
       "    interval_operation:  900 s\n",
       "    interval_write:      1 month\n",
       "    cell_methods:        time: mean (interval: 900 s)</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'irfstar'</div><ul class='xr-dim-list'><li><span>time</span>: 348</li><li><span class='xr-has-index'>lat</span>: 143</li><li><span class='xr-has-index'>lon</span>: 144</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-bf704658-7b92-4efc-9ae9-84045c22f859' class='xr-array-in' type='checkbox' checked><label for='section-bf704658-7b92-4efc-9ae9-84045c22f859' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[7166016 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-3d0c556f-2f2a-4ab7-ad63-05e094907f34' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3d0c556f-2f2a-4ab7-ad63-05e094907f34' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>90.0 88.73 87.46 ... -88.73 -90.0</div><input id='attrs-17cf5695-b008-4e85-b895-af575d8863a2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17cf5695-b008-4e85-b895-af575d8863a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47f05e27-c770-4bb6-9b03-e37833482fcd' class='xr-var-data-in' type='checkbox'><label for='data-47f05e27-c770-4bb6-9b03-e37833482fcd' title='Show/Hide data 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>standard_name :</span></dt><dd>latitude</dd><dt><span>long_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.      ,  88.73239 ,  87.46479 ,  86.19718 ,  84.92958 ,  83.66197 ,\n",
       "        82.39436 ,  81.12676 ,  79.85915 ,  78.59155 ,  77.323944,  76.056335,\n",
       "        74.788734,  73.521126,  72.253525,  70.985916,  69.71831 ,  68.45071 ,\n",
       "        67.1831  ,  65.91549 ,  64.64789 ,  63.380283,  62.112675,  60.84507 ,\n",
       "        59.577465,  58.30986 ,  57.042255,  55.774647,  54.507042,  53.239437,\n",
       "        51.971832,  50.704224,  49.43662 ,  48.169014,  46.90141 ,  45.633804,\n",
       "        44.366196,  43.09859 ,  41.830986,  40.56338 ,  39.295776,  38.028168,\n",
       "        36.760563,  35.492958,  34.225353,  32.957745,  31.690142,  30.422535,\n",
       "        29.15493 ,  27.887323,  26.619719,  25.352112,  24.084507,  22.816902,\n",
       "        21.549295,  20.28169 ,  19.014084,  17.746479,  16.478872,  15.211267,\n",
       "        13.943662,  12.676056,  11.408451,  10.140845,   8.87324 ,   7.605634,\n",
       "         6.338028,   5.070423,   3.802817,   2.535211,   1.267606,   0.      ,\n",
       "        -1.267606,  -2.535211,  -3.802817,  -5.070423,  -6.338028,  -7.605634,\n",
       "        -8.87324 , -10.140845, -11.408451, -12.676056, -13.943662, -15.211267,\n",
       "       -16.478872, -17.746479, -19.014084, -20.28169 , -21.549295, -22.816902,\n",
       "       -24.084507, -25.352112, -26.619719, -27.887323, -29.15493 , -30.422535,\n",
       "       -31.690142, -32.957745, -34.225353, -35.492958, -36.760563, -38.028168,\n",
       "       -39.295776, -40.56338 , -41.830986, -43.09859 , -44.366196, -45.633804,\n",
       "       -46.90141 , -48.169014, -49.43662 , -50.704224, -51.971832, -53.239437,\n",
       "       -54.507042, -55.774647, -57.042255, -58.30986 , -59.577465, -60.84507 ,\n",
       "       -62.112675, -63.380283, -64.64789 , -65.91549 , -67.1831  , -68.45071 ,\n",
       "       -69.71831 , -70.985916, -72.253525, -73.521126, -74.788734, -76.056335,\n",
       "       -77.323944, -78.59155 , -79.85915 , -81.12676 , -82.39436 , -83.66197 ,\n",
       "       -84.92958 , -86.19718 , -87.46479 , -88.73239 , -90.      ],\n",
       "      dtype=float32)</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'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -177.5 ... 175.0 177.5</div><input id='attrs-bd9924ed-d76c-4776-a3d1-7182b3c0ebae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd9924ed-d76c-4776-a3d1-7182b3c0ebae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e49af68-c5d4-45eb-b66e-3637294a1e6a' class='xr-var-data-in' type='checkbox'><label for='data-2e49af68-c5d4-45eb-b66e-3637294a1e6a' title='Show/Hide data 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>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-180. , -177.5, -175. , -172.5, -170. , -167.5, -165. , -162.5, -160. ,\n",
       "       -157.5, -155. , -152.5, -150. , -147.5, -145. , -142.5, -140. , -137.5,\n",
       "       -135. , -132.5, -130. , -127.5, -125. , -122.5, -120. , -117.5, -115. ,\n",
       "       -112.5, -110. , -107.5, -105. , -102.5, -100. ,  -97.5,  -95. ,  -92.5,\n",
       "        -90. ,  -87.5,  -85. ,  -82.5,  -80. ,  -77.5,  -75. ,  -72.5,  -70. ,\n",
       "        -67.5,  -65. ,  -62.5,  -60. ,  -57.5,  -55. ,  -52.5,  -50. ,  -47.5,\n",
       "        -45. ,  -42.5,  -40. ,  -37.5,  -35. ,  -32.5,  -30. ,  -27.5,  -25. ,\n",
       "        -22.5,  -20. ,  -17.5,  -15. ,  -12.5,  -10. ,   -7.5,   -5. ,   -2.5,\n",
       "          0. ,    2.5,    5. ,    7.5,   10. ,   12.5,   15. ,   17.5,   20. ,\n",
       "         22.5,   25. ,   27.5,   30. ,   32.5,   35. ,   37.5,   40. ,   42.5,\n",
       "         45. ,   47.5,   50. ,   52.5,   55. ,   57.5,   60. ,   62.5,   65. ,\n",
       "         67.5,   70. ,   72.5,   75. ,   77.5,   80. ,   82.5,   85. ,   87.5,\n",
       "         90. ,   92.5,   95. ,   97.5,  100. ,  102.5,  105. ,  107.5,  110. ,\n",
       "        112.5,  115. ,  117.5,  120. ,  122.5,  125. ,  127.5,  130. ,  132.5,\n",
       "        135. ,  137.5,  140. ,  142.5,  145. ,  147.5,  150. ,  152.5,  155. ,\n",
       "        157.5,  160. ,  162.5,  165. ,  167.5,  170. ,  172.5,  175. ,  177.5],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_counter</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>2015-01-16 12:00:00 ... 2043-12-...</div><input id='attrs-d1fcb1cb-f14a-4eab-ac9a-dd42d8cd07c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d1fcb1cb-f14a-4eab-ac9a-dd42d8cd07c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1a3f642-4c9f-45ae-8ae4-5b74a6ebd53d' class='xr-var-data-in' type='checkbox'><label for='data-a1a3f642-4c9f-45ae-8ae4-5b74a6ebd53d' title='Show/Hide data 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>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time axis</dd><dt><span>time_origin :</span></dt><dd>2014-01-01 00:00:00</dd><dt><span>bounds :</span></dt><dd>time_counter_bounds</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(2015, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2015, 2, 15, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2015, 3, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       ...,\n",
       "       cftime.DatetimeNoLeap(2043, 10, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2043, 11, 16, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2043, 12, 16, 12, 0, 0, 0, has_year_zero=True)],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_centered</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>2015-01-16 12:00:00 ... 2043-12-...</div><input id='attrs-6d4b9d03-5d33-4de5-b2ef-b144085e8994' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d4b9d03-5d33-4de5-b2ef-b144085e8994' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba1dfd30-00ad-4a35-b956-38a19d6f6e73' class='xr-var-data-in' type='checkbox'><label for='data-ba1dfd30-00ad-4a35-b956-38a19d6f6e73' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time axis</dd><dt><span>time_origin :</span></dt><dd>2014-01-01 00:00:00</dd><dt><span>bounds :</span></dt><dd>time_centered_bounds</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(2015, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2015, 2, 15, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2015, 3, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       ...,\n",
       "       cftime.DatetimeNoLeap(2043, 10, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2043, 11, 16, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2043, 12, 16, 12, 0, 0, 0, has_year_zero=True)],\n",
       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6b2b056a-1109-4c42-9997-9f80c2254ad5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6b2b056a-1109-4c42-9997-9f80c2254ad5' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Instantaneous Net Shortwave Radiative Forcing at TOA due to Aerosol-Radiation interaction</dd><dt><span>units :</span></dt><dd>W/m2</dd><dt><span>online_operation :</span></dt><dd>average</dd><dt><span>interval_operation :</span></dt><dd>900 s</dd><dt><span>interval_write :</span></dt><dd>1 month</dd><dt><span>cell_methods :</span></dt><dd>time: mean (interval: 900 s)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'irfstar' (time: 348, lat: 143, lon: 144)>\n",
       "[7166016 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * lat            (lat) float32 90.0 88.73 87.46 86.2 ... -87.46 -88.73 -90.0\n",
       "  * lon            (lon) float32 -180.0 -177.5 -175.0 ... 172.5 175.0 177.5\n",
       "    time_counter   (time) object 2015-01-16 12:00:00 ... 2043-12-16 12:00:00\n",
       "    time_centered  (time) object 2015-01-16 12:00:00 ... 2043-12-16 12:00:00\n",
       "Dimensions without coordinates: time\n",
       "Attributes:\n",
       "    long_name:           Instantaneous Net Shortwave Radiative Forcing at TOA...\n",
       "    units:               W/m2\n",
       "    online_operation:    average\n",
       "    interval_operation:  900 s\n",
       "    interval_write:      1 month\n",
       "    cell_methods:        time: mean (interval: 900 s)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipsl_irf = ipsl_irf.rename_dims({'time_counter':'time'})\n",
    "irf_ipsl = ipsl_irf.irfstar[12:]\n",
    "irf_ipsl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-11-22T14:20:43.387704Z",
     "start_time": "2021-11-22T14:20:25.916198Z"
    }
   },
   "outputs": [],
   "source": [
    "adj_mpi = erf_mpi.values - ds.irfst.values\n",
    "adj_ipsl = erf_ipsl.values - irf_ipsl.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-11-22T14:20:43.426951Z",
     "start_time": "2021-11-22T14:20:43.389222Z"
    }
   },
   "outputs": [],
   "source": [
    "clt_mpi = mpiesm_spaer.clt[24:] - mpiesm_control.clt[24:]\n",
    "clt_ipsl = ipsl_spaer.clt[12:] - ipsl_control.clt[12:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-11-22T14:20:43.501170Z",
     "start_time": "2021-11-22T14:20:43.428214Z"
    }
   },
   "outputs": [],
   "source": [
    "# regrid for ensemble range\n",
    "# compute ensemble range\n",
    "\n",
    "# irf -10,3 ^ -10,12\n",
    "# adj -10, 15 ^ -12,10\n",
    "# clt diff 4, -2.4 ^ 7,-3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-11-22T14:20:43.635187Z",
     "start_time": "2021-11-22T14:20:43.504001Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((348, 96, 192), (348, 143, 144), (348, 96, 192), (348, 143, 144))"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adj_mpi.shape, adj_ipsl.shape, clt_mpi.shape, clt_ipsl.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-11-22T14:20:46.755495Z",
     "start_time": "2021-11-22T14:20:43.637661Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset = clt_mpi\n",
    "val= np.mean(clt_mpi, axis=0) \n",
    "\n",
    "fig = plt.figure(figsize=(9,7))\n",
    "ax = fig.add_subplot(1,1,1,projection=ccrs.Mollweide())\n",
    "ax.set_global()\n",
    "ax.coastlines()\n",
    "var, ll = add_cyclic_point(val, coord = dataset.lon) \n",
    "\n",
    "ticks = [-5,-4,-3,-2,-1,0,1,2,3,4,5]\n",
    "levels = [-5,-4,-3,-2,-1,-0.5,0.5,1,2,3,4,5]\n",
    "colors = [\"#874e0a\",\"#b67827\",\"#d6b166\",\"#eedaa9\",\"#f6efde\", 'white',\"#e0f0ee\",\"#aee0d8\",\"#6dbeb3\",\"#2d8e86\",\"#016259\"]\n",
    "normalize = mcolors.TwoSlopeNorm(vmin=-5, vmax=5, vcenter=0)\n",
    "\n",
    "cs = ax.contourf(ll, dataset.lat, var,transform=ccrs.PlateCarree(),colors=colors,levels=levels,norm=normalize,extend='both')\n",
    "plt.colorbar(cs, shrink=0.8, fraction=0.046, pad=0.04,  label=r\"${\\%}$\", orientation='horizontal',ticks=ticks)\n",
    "cs.cmap.set_under(\"#543005\")\n",
    "cs.cmap.set_over(\"#003c30\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-11-22T14:20:48.731190Z",
     "start_time": "2021-11-22T14:20:46.758021Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset = irf_ipsl\n",
    "val= np.mean(adj_ipsl, axis=0) \n",
    "\n",
    "fig = plt.figure(figsize=(9,7))\n",
    "ax = fig.add_subplot(1,1,1,projection=ccrs.Mollweide())\n",
    "ax.set_global()\n",
    "ax.coastlines()\n",
    "var, ll = add_cyclic_point(val, coord = dataset.lon) \n",
    "\n",
    "ticks = [-10, -8,-6,-4,-2,0,2,4,6,8,10] \n",
    "colors = ['#1e61a5','#3d8bbf','#7cb7d7','#bad9e9','#e6eff4','white','#faeae1','#fac7ae','#ec9274','#cf5347','#ab162a']\n",
    "levels = [-10,-8,-6,-4,-2,-.2,.2,2,4,6,8,10]\n",
    "normalize = mcolors.TwoSlopeNorm(vmin=-10, vmax=10, vcenter=0)\n",
    "\n",
    "cs = ax.contourf(ll, dataset.lat, var,transform=ccrs.PlateCarree(),colors=colors,levels=levels,norm=normalize,extend='both')\n",
    "plt.colorbar(cs, shrink=0.8, fraction=0.046, pad=0.04,  label=r\"$\\mathrm{Wm}^{-2}$\", orientation='horizontal',ticks=ticks)\n",
    "cs.cmap.set_under(\"#053061\")\n",
    "cs.cmap.set_over(\"#67001f\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-11-22T14:20:58.150001Z",
     "start_time": "2021-11-22T14:20:48.732944Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1224x432 with 8 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot irf, adj and clt \n",
    "\n",
    "fig, axes = plt.subplots(2, 3, figsize=(17,6), subplot_kw=dict(projection=ccrs.Mollweide()),constrained_layout=True)\n",
    "fig.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0.03, hspace=0.09)\n",
    "\n",
    "titles = ['Instantaneous RF', 'Rapid Adjustments', 'Cloud Cover Change'] + [None]*3\n",
    "labels = ['MPI-ESM1-2-LR'] + [None]*2 + ['IPSL-CM6A-LR'] + [None]*2\n",
    "\n",
    "var = [ds.irfst,adj_mpi, clt_mpi,irf_ipsl,adj_ipsl,clt_ipsl]\n",
    "dataset = [ds.irfst,ds, clt_mpi,irf_ipsl,irf_ipsl,clt_ipsl]\n",
    "\n",
    "normalize = [mcolors.TwoSlopeNorm(vmin=-10, vmax=10, vcenter=0)]*2 + [mcolors.TwoSlopeNorm(vmin=-5, vmax=5, vcenter=0)] + [mcolors.TwoSlopeNorm(vmin=-10, vmax=10, vcenter=0)]*2 + [mcolors.TwoSlopeNorm(vmin=-5, vmax=5, vcenter=0)]\n",
    "\n",
    "ticks_rf = [-10, -8,-6,-4,-2,0,2,4,6,8,10]\n",
    "ticks_clt = [-5,-4,-3,-2,-1,0,1,2,3,4,5]\n",
    "\n",
    "colors_rf = ['#1e61a5','#3d8bbf','#7cb7d7','#bad9e9','#e6eff4','white','#faeae1','#fac7ae','#ec9274','#cf5347','#ab162a']\n",
    "colors_clt = [\"#874e0a\",\"#b67827\",\"#d6b166\",\"#eedaa9\",\"#f6efde\", 'white',\"#e0f0ee\",\"#aee0d8\",\"#6dbeb3\",\"#2d8e86\",\"#016259\"]\n",
    "colors = [colors_rf]*2 + [colors_clt] + [colors_rf]*2 + [colors_clt]\n",
    "\n",
    "levels_rf1 = [-10,-8,-6,-4,-2,-.1,.1,2,4,6,8,10]\n",
    "levels_rf2 = [-10,-8,-6,-4,-2,-.5,.5,2,4,6,8,10]\n",
    "levels_clt = [-5,-4,-3,-2,-1,-0.5,0.5,1,2,3,4,5]\n",
    "levels = [levels_rf1] + [levels_rf2] +[levels_clt] + [levels_rf1] + [levels_rf2] +[levels_clt]\n",
    "\n",
    "for i, ax in enumerate(fig.axes):\n",
    "    ax.set_global()\n",
    "    ax.coastlines(resolution='110m')\n",
    "    ax.set_title(titles[i], fontsize=14)\n",
    "    ax.set_aspect('auto')\n",
    "    ax.text(-0.03, 0.55, labels[i], va='bottom', ha='center',rotation='vertical', rotation_mode='anchor',\n",
    "            transform=ax.transAxes, fontsize=12)\n",
    "    \n",
    "    val, ll = add_cyclic_point(var[i], coord = dataset[i].lon)\n",
    "    ax.contourf(ll, dataset[i].lat, np.mean(val, axis=0),norm =normalize[i], transform=ccrs.PlateCarree(),colors=colors[i],\n",
    "                levels = levels[i],extend='both') \n",
    "\n",
    "cmap = mcolors.ListedColormap(colors_rf)\n",
    "norm = mcolors.BoundaryNorm(levels_rf1, cmap.N)    \n",
    "sm = plt.cm.ScalarMappable(norm=norm, cmap=cmap)\n",
    "\n",
    "cbar = fig.colorbar(sm, ax=axes[1,:2], orientation='horizontal',label=r\"$\\mathrm{Wm}^{-2}$\",\n",
    "                    extendrect=False, extend='both', ticks=ticks_rf,\n",
    "                   fraction=0.075,shrink=0.9, pad=0.05)\n",
    "cbar.cmap.set_under(\"#053061\")\n",
    "cbar.cmap.set_over(\"#67001f\")\n",
    "\n",
    "cmap_clt = mcolors.ListedColormap(colors_clt)\n",
    "norm_clt = mcolors.BoundaryNorm(levels_clt, cmap_clt.N)    \n",
    "sm_clt = plt.cm.ScalarMappable(norm=norm_clt, cmap=cmap_clt)\n",
    "\n",
    "cbar_clt = fig.colorbar(sm_clt, ax=axes[1,2], orientation='horizontal',\n",
    "             label=r\"${\\%}$\",fraction=0.065, shrink=0.9, pad=0.05,extendrect=False,\n",
    "                           extend='max',ticks=ticks_clt)\n",
    "\n",
    "cbar_clt.cmap.set_over(\"#003c30\")\n",
    "plt.savefig('instantaneous_plots.pdf',bbox_inches='tight', transparent=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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