Seasonal Bias(gcm Noresm-chirps).ipynb

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    "#writing some conda package or module\n",
    "#!pip install netCDF4\n",
    "%matplotlib inline\n",
    "import warnings\n",
    "from netCDF4 import Dataset\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "#!pip install cartopy\n",
    "import cartopy.feature as cfeature\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.mpl.ticker as cticker\n",
    "from cartopy.util import add_cyclic_point"
   ]
  },
  {
   "cell_type": "code",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 496, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1981-01-01 1981-02-01 ... 2022-04-01\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Data variables:\n",
       "    precip   (time, lat, lon) float32 ...\n",
       "Attributes: (12/17)\n",
       "    CDI:               Climate Data Interface version 1.9.9rc1 (https://mpime...\n",
       "    Conventions:       CF-1.6\n",
       "    history:           Thu Aug 11 11:16:04 2022: cdo remapnn,grid.des chirps-...\n",
       "    institution:       Climate Hazards Group.  University of California at Sa...\n",
       "    title:             CHIRPS Version 2.0\n",
       "    version:           Version 2.0\n",
       "    ...                ...\n",
       "    comments:           time variable denotes the first day of the given month.\n",
       "    acknowledgements:  The Climate Hazards Group InfraRed Precipitation with ...\n",
       "    ftp_url:           ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CH...\n",
       "    website:           http://chg.geog.ucsb.edu/data/chirps/index.html\n",
       "    faq:               http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ\n",
       "    CDO:               Climate Data Operators version 1.9.9rc1 (https://mpime...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b1a6e5b4-1dab-4e01-aab5-b915030c0f74' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b1a6e5b4-1dab-4e01-aab5-b915030c0f74' 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>: 496</li><li><span class='xr-has-index'>lon</span>: 32</li><li><span class='xr-has-index'>lat</span>: 40</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-53751e49-34c6-44be-9072-61eec5790eb1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-53751e49-34c6-44be-9072-61eec5790eb1' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-01-01 ... 2022-04-01</div><input id='attrs-a661c8ba-5540-4710-85e2-39462145372b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a661c8ba-5540-4710-85e2-39462145372b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab8a1c60-0ce3-406c-bc5d-c84ed9266d10' class='xr-var-data-in' type='checkbox'><label for='data-ab8a1c60-0ce3-406c-bc5d-c84ed9266d10' title='Show/Hide data 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>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-01-01T00:00:00.000000000&#x27;, &#x27;1981-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-03-01T00:00:00.000000000&#x27;, ..., &#x27;2022-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-03-01T00:00:00.000000000&#x27;, &#x27;2022-04-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-1e6b1d9f-abf1-411c-9186-a36f5a2fdd7e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e6b1d9f-abf1-411c-9186-a36f5a2fdd7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d61b2bf5-fdd8-4107-9ef5-f8f19f759781' class='xr-var-data-in' type='checkbox'><label for='data-d61b2bf5-fdd8-4107-9ef5-f8f19f759781' title='Show/Hide data 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([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875], dtype=float32)</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'>float32</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-7fe75313-154b-4716-87e2-5b268565d062' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7fe75313-154b-4716-87e2-5b268565d062' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-014bf2f3-ec73-4ae6-9187-10ac5b1032d7' class='xr-var-data-in' type='checkbox'><label for='data-014bf2f3-ec73-4ae6-9187-10ac5b1032d7' title='Show/Hide data 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([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8d4fab00-8b6b-4b23-bc99-49ebfb3fa608' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8d4fab00-8b6b-4b23-bc99-49ebfb3fa608' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>precip</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-360ac861-910c-47e3-a071-1c2975b26f04' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-360ac861-910c-47e3-a071-1c2975b26f04' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4bfa3748-82d8-4496-8c52-6e1aaa5a72a3' class='xr-var-data-in' type='checkbox'><label for='data-4bfa3748-82d8-4496-8c52-6e1aaa5a72a3' title='Show/Hide data 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>convective precipitation rate</dd><dt><span>long_name :</span></dt><dd>Climate Hazards group InfraRed Precipitation with Stations</dd><dt><span>units :</span></dt><dd>mm/month</dd><dt><span>time_step :</span></dt><dd>month</dd><dt><span>geostatial_lat_min :</span></dt><dd>-50.0</dd><dt><span>geostatial_lat_max :</span></dt><dd>50.0</dd><dt><span>geostatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geostatial_lon_max :</span></dt><dd>180.0</dd></dl></div><div class='xr-var-data'><pre>[634880 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f5568311-9769-4dd0-a7d5-45bacffcab52' class='xr-section-summary-in' type='checkbox'  ><label for='section-f5568311-9769-4dd0-a7d5-45bacffcab52' class='xr-section-summary' >Attributes: <span>(17)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Thu Aug 11 11:16:04 2022: cdo remapnn,grid.des chirps-v2.0.monthly.nc chirps-v2.0.monthly_remap.nc\n",
       "created by Climate Hazards Group</dd><dt><span>institution :</span></dt><dd>Climate Hazards Group.  University of California at Santa Barbara</dd><dt><span>title :</span></dt><dd>CHIRPS Version 2.0</dd><dt><span>version :</span></dt><dd>Version 2.0</dd><dt><span>date_created :</span></dt><dd>2022-05-16</dd><dt><span>creator_name :</span></dt><dd>Pete Peterson</dd><dt><span>creator_email :</span></dt><dd>pete@geog.ucsb.edu</dd><dt><span>documentation :</span></dt><dd>http://pubs.usgs.gov/ds/832/</dd><dt><span>reference :</span></dt><dd>Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros, D.H., Verdin, J.P., Rowland, J.D., Romero, B.E., Husak, G.J., Michaelsen, J.C., and Verdin, A.P., 2014, A quasi-global precipitation time series for drought monitoring: U.S. Geological Survey Data Series 832, 4 p., http://dx.doi.org/110.3133/ds832. </dd><dt><span>comments :</span></dt><dd> time variable denotes the first day of the given month.</dd><dt><span>acknowledgements :</span></dt><dd>The Climate Hazards Group InfraRed Precipitation with Stations development process was carried out through U.S. Geological Survey (USGS) cooperative agreement #G09AC000001 &quot;Monitoring and Forecasting Climate, Water and Land Use for Food Production in the Developing World&quot; with funding from: U.S. Agency for International Development Office of Food for Peace, award #AID-FFP-P-10-00002 for &quot;Famine Early Warning Systems Network Support,&quot; the National Aeronautics and Space Administration Applied Sciences Program, Decisions award #NN10AN26I for &quot;A Land Data Assimilation System for Famine Early Warning,&quot; SERVIR award #NNH12AU22I for &quot;A Long Time-Series Indicator of Agricultural Drought for the Greater Horn of Africa,&quot; The National Oceanic and Atmospheric Administration award NA11OAR4310151 for &quot;A Global Standardized Precipitation Index supporting the US Drought Portal and the Famine Early Warning System Network,&quot; and the USGS Land Change Science Program.</dd><dt><span>ftp_url :</span></dt><dd>ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-latest/</dd><dt><span>website :</span></dt><dd>http://chg.geog.ucsb.edu/data/chirps/index.html</dd><dt><span>faq :</span></dt><dd>http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.9rc1 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 496, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1981-01-01 1981-02-01 ... 2022-04-01\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Data variables:\n",
       "    precip   (time, lat, lon) float32 ...\n",
       "Attributes: (12/17)\n",
       "    CDI:               Climate Data Interface version 1.9.9rc1 (https://mpime...\n",
       "    Conventions:       CF-1.6\n",
       "    history:           Thu Aug 11 11:16:04 2022: cdo remapnn,grid.des chirps-...\n",
       "    institution:       Climate Hazards Group.  University of California at Sa...\n",
       "    title:             CHIRPS Version 2.0\n",
       "    version:           Version 2.0\n",
       "    ...                ...\n",
       "    comments:           time variable denotes the first day of the given month.\n",
       "    acknowledgements:  The Climate Hazards Group InfraRed Precipitation with ...\n",
       "    ftp_url:           ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CH...\n",
       "    website:           http://chg.geog.ucsb.edu/data/chirps/index.html\n",
       "    faq:               http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ\n",
       "    CDO:               Climate Data Operators version 1.9.9rc1 (https://mpime..."
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = xr.open_dataset('/home/mkibria/Academic/pr_of_thesis/observation/chirps/chirps-v2.0.monthly_remap.nc')\n",
    " \n",
    "\n",
    "data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "800e4d90",
   "metadata": {},
   "outputs": [
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 299, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1981-02-01 1981-03-01 ... 2005-12-01\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Data variables:\n",
       "    precip   (time, lat, lon) float32 ...\n",
       "Attributes: (12/17)\n",
       "    CDI:               Climate Data Interface version 1.9.9rc1 (https://mpime...\n",
       "    Conventions:       CF-1.6\n",
       "    history:           Thu Aug 11 11:16:04 2022: cdo remapnn,grid.des chirps-...\n",
       "    institution:       Climate Hazards Group.  University of California at Sa...\n",
       "    title:             CHIRPS Version 2.0\n",
       "    version:           Version 2.0\n",
       "    ...                ...\n",
       "    comments:           time variable denotes the first day of the given month.\n",
       "    acknowledgements:  The Climate Hazards Group InfraRed Precipitation with ...\n",
       "    ftp_url:           ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CH...\n",
       "    website:           http://chg.geog.ucsb.edu/data/chirps/index.html\n",
       "    faq:               http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ\n",
       "    CDO:               Climate Data Operators version 1.9.9rc1 (https://mpime...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-251090ed-da08-4d00-a65f-ead93cc8373b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-251090ed-da08-4d00-a65f-ead93cc8373b' 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>: 299</li><li><span class='xr-has-index'>lon</span>: 32</li><li><span class='xr-has-index'>lat</span>: 40</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-70e31931-91fa-4b17-b2c1-dddba41f6a2f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-70e31931-91fa-4b17-b2c1-dddba41f6a2f' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-02-01 ... 2005-12-01</div><input id='attrs-8303cda3-5c55-4288-a778-2e679ac1d954' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8303cda3-5c55-4288-a778-2e679ac1d954' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c37c789b-455e-4230-a542-0606bbb0508c' class='xr-var-data-in' type='checkbox'><label for='data-c37c789b-455e-4230-a542-0606bbb0508c' title='Show/Hide data 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>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-02-01T00:00:00.000000000&#x27;, &#x27;1981-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-04-01T00:00:00.000000000&#x27;, ..., &#x27;2005-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-11-01T00:00:00.000000000&#x27;, &#x27;2005-12-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-342e9346-925b-43b3-8d02-fae8accfae8c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-342e9346-925b-43b3-8d02-fae8accfae8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29baff4d-1347-481f-bb31-09461555259e' class='xr-var-data-in' type='checkbox'><label for='data-29baff4d-1347-481f-bb31-09461555259e' title='Show/Hide data 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([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875], dtype=float32)</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'>float32</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-c76925ed-cfcf-472b-b253-c0519aaf881d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c76925ed-cfcf-472b-b253-c0519aaf881d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e107280a-c10d-46e6-b5c3-f7b5e8d0cf5b' class='xr-var-data-in' type='checkbox'><label for='data-e107280a-c10d-46e6-b5c3-f7b5e8d0cf5b' title='Show/Hide data 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([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a7cc94f2-12b1-4ad7-aa0d-7c7a0017aa5f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a7cc94f2-12b1-4ad7-aa0d-7c7a0017aa5f' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>precip</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-95e51ea9-1b8c-456a-b692-f552caa11aa9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95e51ea9-1b8c-456a-b692-f552caa11aa9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65c169ef-37f5-4df4-8b7c-1ac52551dc3b' class='xr-var-data-in' type='checkbox'><label for='data-65c169ef-37f5-4df4-8b7c-1ac52551dc3b' title='Show/Hide data 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>convective precipitation rate</dd><dt><span>long_name :</span></dt><dd>Climate Hazards group InfraRed Precipitation with Stations</dd><dt><span>units :</span></dt><dd>mm/month</dd><dt><span>time_step :</span></dt><dd>month</dd><dt><span>geostatial_lat_min :</span></dt><dd>-50.0</dd><dt><span>geostatial_lat_max :</span></dt><dd>50.0</dd><dt><span>geostatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geostatial_lon_max :</span></dt><dd>180.0</dd></dl></div><div class='xr-var-data'><pre>[382720 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4d949588-1010-4873-ad1e-2ec2ca988f94' class='xr-section-summary-in' type='checkbox'  ><label for='section-4d949588-1010-4873-ad1e-2ec2ca988f94' class='xr-section-summary' >Attributes: <span>(17)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Thu Aug 11 11:16:04 2022: cdo remapnn,grid.des chirps-v2.0.monthly.nc chirps-v2.0.monthly_remap.nc\n",
       "created by Climate Hazards Group</dd><dt><span>institution :</span></dt><dd>Climate Hazards Group.  University of California at Santa Barbara</dd><dt><span>title :</span></dt><dd>CHIRPS Version 2.0</dd><dt><span>version :</span></dt><dd>Version 2.0</dd><dt><span>date_created :</span></dt><dd>2022-05-16</dd><dt><span>creator_name :</span></dt><dd>Pete Peterson</dd><dt><span>creator_email :</span></dt><dd>pete@geog.ucsb.edu</dd><dt><span>documentation :</span></dt><dd>http://pubs.usgs.gov/ds/832/</dd><dt><span>reference :</span></dt><dd>Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros, D.H., Verdin, J.P., Rowland, J.D., Romero, B.E., Husak, G.J., Michaelsen, J.C., and Verdin, A.P., 2014, A quasi-global precipitation time series for drought monitoring: U.S. Geological Survey Data Series 832, 4 p., http://dx.doi.org/110.3133/ds832. </dd><dt><span>comments :</span></dt><dd> time variable denotes the first day of the given month.</dd><dt><span>acknowledgements :</span></dt><dd>The Climate Hazards Group InfraRed Precipitation with Stations development process was carried out through U.S. Geological Survey (USGS) cooperative agreement #G09AC000001 &quot;Monitoring and Forecasting Climate, Water and Land Use for Food Production in the Developing World&quot; with funding from: U.S. Agency for International Development Office of Food for Peace, award #AID-FFP-P-10-00002 for &quot;Famine Early Warning Systems Network Support,&quot; the National Aeronautics and Space Administration Applied Sciences Program, Decisions award #NN10AN26I for &quot;A Land Data Assimilation System for Famine Early Warning,&quot; SERVIR award #NNH12AU22I for &quot;A Long Time-Series Indicator of Agricultural Drought for the Greater Horn of Africa,&quot; The National Oceanic and Atmospheric Administration award NA11OAR4310151 for &quot;A Global Standardized Precipitation Index supporting the US Drought Portal and the Famine Early Warning System Network,&quot; and the USGS Land Change Science Program.</dd><dt><span>ftp_url :</span></dt><dd>ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-latest/</dd><dt><span>website :</span></dt><dd>http://chg.geog.ucsb.edu/data/chirps/index.html</dd><dt><span>faq :</span></dt><dd>http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.9rc1 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 299, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1981-02-01 1981-03-01 ... 2005-12-01\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Data variables:\n",
       "    precip   (time, lat, lon) float32 ...\n",
       "Attributes: (12/17)\n",
       "    CDI:               Climate Data Interface version 1.9.9rc1 (https://mpime...\n",
       "    Conventions:       CF-1.6\n",
       "    history:           Thu Aug 11 11:16:04 2022: cdo remapnn,grid.des chirps-...\n",
       "    institution:       Climate Hazards Group.  University of California at Sa...\n",
       "    title:             CHIRPS Version 2.0\n",
       "    version:           Version 2.0\n",
       "    ...                ...\n",
       "    comments:           time variable denotes the first day of the given month.\n",
       "    acknowledgements:  The Climate Hazards Group InfraRed Precipitation with ...\n",
       "    ftp_url:           ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CH...\n",
       "    website:           http://chg.geog.ucsb.edu/data/chirps/index.html\n",
       "    faq:               http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ\n",
       "    CDO:               Climate Data Operators version 1.9.9rc1 (https://mpime..."
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#to select the year from 1980 to 2015\n",
    "data = data.sel(time=slice('1981-01-16T12:00:00.000000000','2005-12-16T00:00:00.000000000'))\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "10070b93",
   "metadata": {},
   "outputs": [
    {
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       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 100, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1981-06-01 1981-07-01 ... 2005-09-01\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Data variables:\n",
       "    precip   (time, lat, lon) float32 ...\n",
       "Attributes: (12/17)\n",
       "    CDI:               Climate Data Interface version 1.9.9rc1 (https://mpime...\n",
       "    Conventions:       CF-1.6\n",
       "    history:           Thu Aug 11 11:16:04 2022: cdo remapnn,grid.des chirps-...\n",
       "    institution:       Climate Hazards Group.  University of California at Sa...\n",
       "    title:             CHIRPS Version 2.0\n",
       "    version:           Version 2.0\n",
       "    ...                ...\n",
       "    comments:           time variable denotes the first day of the given month.\n",
       "    acknowledgements:  The Climate Hazards Group InfraRed Precipitation with ...\n",
       "    ftp_url:           ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CH...\n",
       "    website:           http://chg.geog.ucsb.edu/data/chirps/index.html\n",
       "    faq:               http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ\n",
       "    CDO:               Climate Data Operators version 1.9.9rc1 (https://mpime...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-7141c94f-206d-4f66-b669-54fbd64f1c99' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7141c94f-206d-4f66-b669-54fbd64f1c99' 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>: 100</li><li><span class='xr-has-index'>lon</span>: 32</li><li><span class='xr-has-index'>lat</span>: 40</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-707a2d8a-538a-4c6c-accc-05575e4993e8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-707a2d8a-538a-4c6c-accc-05575e4993e8' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-06-01 ... 2005-09-01</div><input id='attrs-56da8ba3-c0ac-43de-9371-9ee15c054ce0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-56da8ba3-c0ac-43de-9371-9ee15c054ce0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef82b18b-177c-4466-854f-1a939d698f46' class='xr-var-data-in' type='checkbox'><label for='data-ef82b18b-177c-4466-854f-1a939d698f46' title='Show/Hide data 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>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-06-01T00:00:00.000000000&#x27;, &#x27;1981-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-08-01T00:00:00.000000000&#x27;, &#x27;1981-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-06-01T00:00:00.000000000&#x27;, &#x27;1982-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-08-01T00:00:00.000000000&#x27;, &#x27;1982-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-06-01T00:00:00.000000000&#x27;, &#x27;1983-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-08-01T00:00:00.000000000&#x27;, &#x27;1983-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-06-01T00:00:00.000000000&#x27;, &#x27;1984-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-08-01T00:00:00.000000000&#x27;, &#x27;1984-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-06-01T00:00:00.000000000&#x27;, &#x27;1985-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-08-01T00:00:00.000000000&#x27;, &#x27;1985-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-06-01T00:00:00.000000000&#x27;, &#x27;1986-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-08-01T00:00:00.000000000&#x27;, &#x27;1986-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-06-01T00:00:00.000000000&#x27;, &#x27;1987-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-08-01T00:00:00.000000000&#x27;, &#x27;1987-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-06-01T00:00:00.000000000&#x27;, &#x27;1988-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-08-01T00:00:00.000000000&#x27;, &#x27;1988-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-06-01T00:00:00.000000000&#x27;, &#x27;1989-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-08-01T00:00:00.000000000&#x27;, &#x27;1989-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-06-01T00:00:00.000000000&#x27;, &#x27;1990-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-08-01T00:00:00.000000000&#x27;, &#x27;1990-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-06-01T00:00:00.000000000&#x27;, &#x27;1991-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-08-01T00:00:00.000000000&#x27;, &#x27;1991-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-06-01T00:00:00.000000000&#x27;, &#x27;1992-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-08-01T00:00:00.000000000&#x27;, &#x27;1992-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-06-01T00:00:00.000000000&#x27;, &#x27;1993-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-08-01T00:00:00.000000000&#x27;, &#x27;1993-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-06-01T00:00:00.000000000&#x27;, &#x27;1994-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-08-01T00:00:00.000000000&#x27;, &#x27;1994-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-06-01T00:00:00.000000000&#x27;, &#x27;1995-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-08-01T00:00:00.000000000&#x27;, &#x27;1995-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-06-01T00:00:00.000000000&#x27;, &#x27;1996-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-08-01T00:00:00.000000000&#x27;, &#x27;1996-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-06-01T00:00:00.000000000&#x27;, &#x27;1997-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-08-01T00:00:00.000000000&#x27;, &#x27;1997-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-06-01T00:00:00.000000000&#x27;, &#x27;1998-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-08-01T00:00:00.000000000&#x27;, &#x27;1998-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-06-01T00:00:00.000000000&#x27;, &#x27;1999-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-08-01T00:00:00.000000000&#x27;, &#x27;1999-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-01T00:00:00.000000000&#x27;, &#x27;2000-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-08-01T00:00:00.000000000&#x27;, &#x27;2000-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-06-01T00:00:00.000000000&#x27;, &#x27;2001-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-08-01T00:00:00.000000000&#x27;, &#x27;2001-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-01T00:00:00.000000000&#x27;, &#x27;2002-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-01T00:00:00.000000000&#x27;, &#x27;2002-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-01T00:00:00.000000000&#x27;, &#x27;2003-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-01T00:00:00.000000000&#x27;, &#x27;2003-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-01T00:00:00.000000000&#x27;, &#x27;2004-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-01T00:00:00.000000000&#x27;, &#x27;2004-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-01T00:00:00.000000000&#x27;, &#x27;2005-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-08-01T00:00:00.000000000&#x27;, &#x27;2005-09-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-0b81db15-78ca-475e-bf5d-05434fdbbee6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b81db15-78ca-475e-bf5d-05434fdbbee6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ab749b4-6ff5-433d-aedc-d42f2c278450' class='xr-var-data-in' type='checkbox'><label for='data-4ab749b4-6ff5-433d-aedc-d42f2c278450' title='Show/Hide data 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([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875], dtype=float32)</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'>float32</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-39e348bf-1399-4fcf-8f0f-6ee65ac56616' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39e348bf-1399-4fcf-8f0f-6ee65ac56616' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7c25030-6db5-4a3c-838a-0374a09fc07c' class='xr-var-data-in' type='checkbox'><label for='data-b7c25030-6db5-4a3c-838a-0374a09fc07c' title='Show/Hide data 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([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-aa8ac842-a697-43a5-9ea3-a66fae865aa4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-aa8ac842-a697-43a5-9ea3-a66fae865aa4' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>precip</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-23d16ad7-3b86-4367-bbbc-df75209528ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-23d16ad7-3b86-4367-bbbc-df75209528ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f64a42f-f319-4d5a-a58f-8895b723713c' class='xr-var-data-in' type='checkbox'><label for='data-7f64a42f-f319-4d5a-a58f-8895b723713c' title='Show/Hide data 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>convective precipitation rate</dd><dt><span>long_name :</span></dt><dd>Climate Hazards group InfraRed Precipitation with Stations</dd><dt><span>units :</span></dt><dd>mm/month</dd><dt><span>time_step :</span></dt><dd>month</dd><dt><span>geostatial_lat_min :</span></dt><dd>-50.0</dd><dt><span>geostatial_lat_max :</span></dt><dd>50.0</dd><dt><span>geostatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geostatial_lon_max :</span></dt><dd>180.0</dd></dl></div><div class='xr-var-data'><pre>[128000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-161b6538-340c-43c9-8172-c8e5e097d630' class='xr-section-summary-in' type='checkbox'  ><label for='section-161b6538-340c-43c9-8172-c8e5e097d630' class='xr-section-summary' >Attributes: <span>(17)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Thu Aug 11 11:16:04 2022: cdo remapnn,grid.des chirps-v2.0.monthly.nc chirps-v2.0.monthly_remap.nc\n",
       "created by Climate Hazards Group</dd><dt><span>institution :</span></dt><dd>Climate Hazards Group.  University of California at Santa Barbara</dd><dt><span>title :</span></dt><dd>CHIRPS Version 2.0</dd><dt><span>version :</span></dt><dd>Version 2.0</dd><dt><span>date_created :</span></dt><dd>2022-05-16</dd><dt><span>creator_name :</span></dt><dd>Pete Peterson</dd><dt><span>creator_email :</span></dt><dd>pete@geog.ucsb.edu</dd><dt><span>documentation :</span></dt><dd>http://pubs.usgs.gov/ds/832/</dd><dt><span>reference :</span></dt><dd>Funk, C.C., Peterson, P.J., Landsfeld, M.F., Pedreros, D.H., Verdin, J.P., Rowland, J.D., Romero, B.E., Husak, G.J., Michaelsen, J.C., and Verdin, A.P., 2014, A quasi-global precipitation time series for drought monitoring: U.S. Geological Survey Data Series 832, 4 p., http://dx.doi.org/110.3133/ds832. </dd><dt><span>comments :</span></dt><dd> time variable denotes the first day of the given month.</dd><dt><span>acknowledgements :</span></dt><dd>The Climate Hazards Group InfraRed Precipitation with Stations development process was carried out through U.S. Geological Survey (USGS) cooperative agreement #G09AC000001 &quot;Monitoring and Forecasting Climate, Water and Land Use for Food Production in the Developing World&quot; with funding from: U.S. Agency for International Development Office of Food for Peace, award #AID-FFP-P-10-00002 for &quot;Famine Early Warning Systems Network Support,&quot; the National Aeronautics and Space Administration Applied Sciences Program, Decisions award #NN10AN26I for &quot;A Land Data Assimilation System for Famine Early Warning,&quot; SERVIR award #NNH12AU22I for &quot;A Long Time-Series Indicator of Agricultural Drought for the Greater Horn of Africa,&quot; The National Oceanic and Atmospheric Administration award NA11OAR4310151 for &quot;A Global Standardized Precipitation Index supporting the US Drought Portal and the Famine Early Warning System Network,&quot; and the USGS Land Change Science Program.</dd><dt><span>ftp_url :</span></dt><dd>ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CHIRPS-latest/</dd><dt><span>website :</span></dt><dd>http://chg.geog.ucsb.edu/data/chirps/index.html</dd><dt><span>faq :</span></dt><dd>http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.9rc1 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 100, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1981-06-01 1981-07-01 ... 2005-09-01\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Data variables:\n",
       "    precip   (time, lat, lon) float32 ...\n",
       "Attributes: (12/17)\n",
       "    CDI:               Climate Data Interface version 1.9.9rc1 (https://mpime...\n",
       "    Conventions:       CF-1.6\n",
       "    history:           Thu Aug 11 11:16:04 2022: cdo remapnn,grid.des chirps-...\n",
       "    institution:       Climate Hazards Group.  University of California at Sa...\n",
       "    title:             CHIRPS Version 2.0\n",
       "    version:           Version 2.0\n",
       "    ...                ...\n",
       "    comments:           time variable denotes the first day of the given month.\n",
       "    acknowledgements:  The Climate Hazards Group InfraRed Precipitation with ...\n",
       "    ftp_url:           ftp://chg-ftpout.geog.ucsb.edu/pub/org/chg/products/CH...\n",
       "    website:           http://chg.geog.ucsb.edu/data/chirps/index.html\n",
       "    faq:               http://chg-wiki.geog.ucsb.edu/wiki/CHIRPS_FAQ\n",
       "    CDO:               Climate Data Operators version 1.9.9rc1 (https://mpime..."
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#selecting only JJAS months\n",
    "\n",
    "def is_jjas(month):\n",
    "    return (month >= 6) & (month <= 9)\n",
    "\n",
    "jjas_data = data.sel(time=is_jjas(data['time.month']))\n",
    "\n",
    "jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "735515f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#for i in data.latitude.values:\n",
    " #   print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fd310367",
   "metadata": {},
   "outputs": [],
   "source": [
    "#for i in data.longitude.values:\n",
    " #   print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2a9644bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "#to select the x and y coordinates\n",
    "#jjas_data = jjas_data.sel(longitude=slice(86,94),latitude=slice(18,28))\n",
    "#jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "91600dec",
   "metadata": {},
   "outputs": [],
   "source": [
    "#interpolating to low resolution \n",
    "#new_lon=np.arange(86.125,94,0.25)\n",
    "#new_lat=np.arange(18.125,28,.25)\n",
    "#jjas_data = jjas_data.interp(longitude=new_lon,latitude=new_lat)\n",
    "#jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "82d6b5d0",
   "metadata": {},
   "outputs": [
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       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;precip&#x27; (lat: 40, lon: 32)&gt;\n",
       "array([[      nan,       nan,       nan, ...,       nan,       nan,\n",
       "              nan],\n",
       "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
       "              nan],\n",
       "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
       "              nan],\n",
       "       ...,\n",
       "       [248.97762, 275.25247, 338.84406, ..., 204.03615, 273.31155,\n",
       "        398.09113],\n",
       "       [313.03275, 304.99213, 340.83173, ..., 159.18379, 245.99791,\n",
       "        286.82858],\n",
       "       [300.33856, 273.78464, 231.78273, ..., 220.41202, 251.78061,\n",
       "        284.67566]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'precip'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 40</li><li><span class='xr-has-index'>lon</span>: 32</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-6d0b9ba1-7b74-4508-8cd0-86ae893a4ab8' class='xr-array-in' type='checkbox' checked><label for='section-6d0b9ba1-7b74-4508-8cd0-86ae893a4ab8' 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>nan nan nan nan nan nan nan ... 74.31 103.7 151.5 220.4 251.8 284.7</span></div><div class='xr-array-data'><pre>array([[      nan,       nan,       nan, ...,       nan,       nan,\n",
       "              nan],\n",
       "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
       "              nan],\n",
       "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
       "              nan],\n",
       "       ...,\n",
       "       [248.97762, 275.25247, 338.84406, ..., 204.03615, 273.31155,\n",
       "        398.09113],\n",
       "       [313.03275, 304.99213, 340.83173, ..., 159.18379, 245.99791,\n",
       "        286.82858],\n",
       "       [300.33856, 273.78464, 231.78273, ..., 220.41202, 251.78061,\n",
       "        284.67566]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-c2fba991-12cb-498a-8ce6-e6093370ed82' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c2fba991-12cb-498a-8ce6-e6093370ed82' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span 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'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-221e1764-7bff-45e4-b0e4-f9664a20478d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-221e1764-7bff-45e4-b0e4-f9664a20478d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d43f0bea-ba21-4021-86b2-c7ce6ba1c079' class='xr-var-data-in' type='checkbox'><label for='data-d43f0bea-ba21-4021-86b2-c7ce6ba1c079' title='Show/Hide data 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([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875], dtype=float32)</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'>float32</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-3a0e7780-45ec-4998-883f-02502dde0b83' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a0e7780-45ec-4998-883f-02502dde0b83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b90c76a-b17d-4b38-ba5c-51a194ad0555' class='xr-var-data-in' type='checkbox'><label for='data-0b90c76a-b17d-4b38-ba5c-51a194ad0555' title='Show/Hide data 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([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-33f71442-dc4e-48b7-bdf8-594c9d3bf7b2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-33f71442-dc4e-48b7-bdf8-594c9d3bf7b2' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'precip' (lat: 40, lon: 32)>\n",
       "array([[      nan,       nan,       nan, ...,       nan,       nan,\n",
       "              nan],\n",
       "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
       "              nan],\n",
       "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
       "              nan],\n",
       "       ...,\n",
       "       [248.97762, 275.25247, 338.84406, ..., 204.03615, 273.31155,\n",
       "        398.09113],\n",
       "       [313.03275, 304.99213, 340.83173, ..., 159.18379, 245.99791,\n",
       "        286.82858],\n",
       "       [300.33856, 273.78464, 231.78273, ..., 220.41202, 251.78061,\n",
       "        284.67566]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#getting the mean for JJAS data\n",
    "jjas_mean = jjas_data.precip.mean('time')\n",
    " \n",
    "jjas_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6d00cba7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#changing unit from mm/month to mm/day\n",
    "pr_mm = jjas_mean/30.4167\n",
    "\n",
    "\n",
    "\n",
    "chirps = pr_mm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b6d9b2b3",
   "metadata": {},
   "outputs": [
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       "  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: 1872, bnds: 2, lat: 96, lon: 144)\n",
       "Coordinates:\n",
       "  * time       (time) object 1850-01-16 12:00:00 ... 2005-12-16 12:00:00\n",
       "  * lat        (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 86.21 88.11 90.0\n",
       "  * lon        (lon) float64 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1850-01-01 00:00:00 ... 2006-01-01 00:00:00\n",
       "    lat_bnds   (lat, bnds) float64 -90.0 -89.05 -89.05 ... 89.05 89.05 90.0\n",
       "    lon_bnds   (lon, bnds) float64 -1.25 1.25 1.25 3.75 ... 356.2 356.2 358.8\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/26)\n",
       "    institution:            Norwegian Climate Centre\n",
       "    institute_id:           NCC\n",
       "    experiment_id:          historical\n",
       "    source:                 NorESM1-M 2011  atmosphere: CAM-Oslo (CAM4-Oslo-n...\n",
       "    model_id:               NorESM1-M\n",
       "    forcing:                GHG, SA, Oz, Sl, Vl, BC, OC\n",
       "    ...                     ...\n",
       "    table_id:               Table Amon (27 April 2011) a5a1c518f52ae340313ba0...\n",
       "    title:                  NorESM1-M model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.6.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-7f84be84-a3e7-4f63-abca-19a7bf88a111' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7f84be84-a3e7-4f63-abca-19a7bf88a111' 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>: 1872</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 96</li><li><span class='xr-has-index'>lon</span>: 144</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-fb138124-507e-4bcb-80b8-0491bf23224c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fb138124-507e-4bcb-80b8-0491bf23224c' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-16 12:00:00 ... 2005-12-...</div><input id='attrs-46d4e7a4-0ab3-4f8a-a5e5-5989b616f2d9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-46d4e7a4-0ab3-4f8a-a5e5-5989b616f2d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1cdec78-31f9-419b-9f6e-0e68f024f8ee' class='xr-var-data-in' type='checkbox'><label for='data-e1cdec78-31f9-419b-9f6e-0e68f024f8ee' title='Show/Hide data 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>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(1850, 2, 15, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(1850, 3, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       ...,\n",
       "       cftime.DatetimeNoLeap(2005, 10, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2005, 11, 16, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2005, 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 class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.11 -86.21 ... 88.11 90.0</div><input id='attrs-dbfad8b6-6d6c-4d03-90b2-b506bec77c60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dbfad8b6-6d6c-4d03-90b2-b506bec77c60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-184b815d-2960-4150-b5f5-9fcff3006fe3' class='xr-var-data-in' type='checkbox'><label for='data-184b815d-2960-4150-b5f5-9fcff3006fe3' title='Show/Hide data 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -88.105263, -86.210526, -84.315789, -82.421053, -80.526316,\n",
       "       -78.631579, -76.736842, -74.842105, -72.947368, -71.052632, -69.157895,\n",
       "       -67.263158, -65.368421, -63.473684, -61.578947, -59.684211, -57.789474,\n",
       "       -55.894737, -54.      , -52.105263, -50.210526, -48.315789, -46.421053,\n",
       "       -44.526316, -42.631579, -40.736842, -38.842105, -36.947368, -35.052632,\n",
       "       -33.157895, -31.263158, -29.368421, -27.473684, -25.578947, -23.684211,\n",
       "       -21.789474, -19.894737, -18.      , -16.105263, -14.210526, -12.315789,\n",
       "       -10.421053,  -8.526316,  -6.631579,  -4.736842,  -2.842105,  -0.947368,\n",
       "         0.947368,   2.842105,   4.736842,   6.631579,   8.526316,  10.421053,\n",
       "        12.315789,  14.210526,  16.105263,  18.      ,  19.894737,  21.789474,\n",
       "        23.684211,  25.578947,  27.473684,  29.368421,  31.263158,  33.157895,\n",
       "        35.052632,  36.947368,  38.842105,  40.736842,  42.631579,  44.526316,\n",
       "        46.421053,  48.315789,  50.210526,  52.105263,  54.      ,  55.894737,\n",
       "        57.789474,  59.684211,  61.578947,  63.473684,  65.368421,  67.263158,\n",
       "        69.157895,  71.052632,  72.947368,  74.842105,  76.736842,  78.631579,\n",
       "        80.526316,  82.421053,  84.315789,  86.210526,  88.105263,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.5 5.0 ... 352.5 355.0 357.5</div><input id='attrs-030a48e3-705b-4b80-8ee1-5273efd3ce12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-030a48e3-705b-4b80-8ee1-5273efd3ce12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42aacf13-51eb-4300-8d4a-796a1ba470cf' class='xr-var-data-in' type='checkbox'><label for='data-42aacf13-51eb-4300-8d4a-796a1ba470cf' title='Show/Hide data 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0. ,   2.5,   5. ,   7.5,  10. ,  12.5,  15. ,  17.5,  20. ,  22.5,\n",
       "        25. ,  27.5,  30. ,  32.5,  35. ,  37.5,  40. ,  42.5,  45. ,  47.5,\n",
       "        50. ,  52.5,  55. ,  57.5,  60. ,  62.5,  65. ,  67.5,  70. ,  72.5,\n",
       "        75. ,  77.5,  80. ,  82.5,  85. ,  87.5,  90. ,  92.5,  95. ,  97.5,\n",
       "       100. , 102.5, 105. , 107.5, 110. , 112.5, 115. , 117.5, 120. , 122.5,\n",
       "       125. , 127.5, 130. , 132.5, 135. , 137.5, 140. , 142.5, 145. , 147.5,\n",
       "       150. , 152.5, 155. , 157.5, 160. , 162.5, 165. , 167.5, 170. , 172.5,\n",
       "       175. , 177.5, 180. , 182.5, 185. , 187.5, 190. , 192.5, 195. , 197.5,\n",
       "       200. , 202.5, 205. , 207.5, 210. , 212.5, 215. , 217.5, 220. , 222.5,\n",
       "       225. , 227.5, 230. , 232.5, 235. , 237.5, 240. , 242.5, 245. , 247.5,\n",
       "       250. , 252.5, 255. , 257.5, 260. , 262.5, 265. , 267.5, 270. , 272.5,\n",
       "       275. , 277.5, 280. , 282.5, 285. , 287.5, 290. , 292.5, 295. , 297.5,\n",
       "       300. , 302.5, 305. , 307.5, 310. , 312.5, 315. , 317.5, 320. , 322.5,\n",
       "       325. , 327.5, 330. , 332.5, 335. , 337.5, 340. , 342.5, 345. , 347.5,\n",
       "       350. , 352.5, 355. , 357.5])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-76b4940b-2724-46fb-a7df-665a61a51ee4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-76b4940b-2724-46fb-a7df-665a61a51ee4' class='xr-section-summary' >Data variables: <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>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-154b9c4d-ed99-4408-ac4e-b52590a3fc39' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-154b9c4d-ed99-4408-ac4e-b52590a3fc39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b0ba116-3aed-424a-971b-0b57cddd5690' class='xr-var-data-in' type='checkbox'><label for='data-4b0ba116-3aed-424a-971b-0b57cddd5690' title='Show/Hide data 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(1850, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1850, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1850, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1850, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1850, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1850, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       ...,\n",
       "       [cftime.DatetimeNoLeap(2005, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 12, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 12, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2006, 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>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f093225d-de89-408c-92bd-a85d236bc07f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f093225d-de89-408c-92bd-a85d236bc07f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-827cf89a-c212-4f42-9fc2-18487af9c491' class='xr-var-data-in' type='checkbox'><label for='data-827cf89a-c212-4f42-9fc2-18487af9c491' title='Show/Hide data 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([[-90.      , -89.052632],\n",
       "       [-89.052632, -87.157895],\n",
       "       [-87.157895, -85.263158],\n",
       "       [-85.263158, -83.368421],\n",
       "       [-83.368421, -81.473684],\n",
       "       [-81.473684, -79.578947],\n",
       "       [-79.578947, -77.684211],\n",
       "       [-77.684211, -75.789474],\n",
       "       [-75.789474, -73.894737],\n",
       "       [-73.894737, -72.      ],\n",
       "       [-72.      , -70.105263],\n",
       "       [-70.105263, -68.210526],\n",
       "       [-68.210526, -66.315789],\n",
       "       [-66.315789, -64.421053],\n",
       "       [-64.421053, -62.526316],\n",
       "       [-62.526316, -60.631579],\n",
       "       [-60.631579, -58.736842],\n",
       "       [-58.736842, -56.842105],\n",
       "       [-56.842105, -54.947368],\n",
       "       [-54.947368, -53.052632],\n",
       "       [-53.052632, -51.157895],\n",
       "       [-51.157895, -49.263158],\n",
       "       [-49.263158, -47.368421],\n",
       "       [-47.368421, -45.473684],\n",
       "       [-45.473684, -43.578947],\n",
       "       [-43.578947, -41.684211],\n",
       "       [-41.684211, -39.789474],\n",
       "       [-39.789474, -37.894737],\n",
       "       [-37.894737, -36.      ],\n",
       "       [-36.      , -34.105263],\n",
       "       [-34.105263, -32.210526],\n",
       "       [-32.210526, -30.315789],\n",
       "       [-30.315789, -28.421053],\n",
       "       [-28.421053, -26.526316],\n",
       "       [-26.526316, -24.631579],\n",
       "       [-24.631579, -22.736842],\n",
       "       [-22.736842, -20.842105],\n",
       "       [-20.842105, -18.947368],\n",
       "       [-18.947368, -17.052632],\n",
       "       [-17.052632, -15.157895],\n",
       "       [-15.157895, -13.263158],\n",
       "       [-13.263158, -11.368421],\n",
       "       [-11.368421,  -9.473684],\n",
       "       [ -9.473684,  -7.578947],\n",
       "       [ -7.578947,  -5.684211],\n",
       "       [ -5.684211,  -3.789474],\n",
       "       [ -3.789474,  -1.894737],\n",
       "       [ -1.894737,   0.      ],\n",
       "       [  0.      ,   1.894737],\n",
       "       [  1.894737,   3.789474],\n",
       "       [  3.789474,   5.684211],\n",
       "       [  5.684211,   7.578947],\n",
       "       [  7.578947,   9.473684],\n",
       "       [  9.473684,  11.368421],\n",
       "       [ 11.368421,  13.263158],\n",
       "       [ 13.263158,  15.157895],\n",
       "       [ 15.157895,  17.052632],\n",
       "       [ 17.052632,  18.947368],\n",
       "       [ 18.947368,  20.842105],\n",
       "       [ 20.842105,  22.736842],\n",
       "       [ 22.736842,  24.631579],\n",
       "       [ 24.631579,  26.526316],\n",
       "       [ 26.526316,  28.421053],\n",
       "       [ 28.421053,  30.315789],\n",
       "       [ 30.315789,  32.210526],\n",
       "       [ 32.210526,  34.105263],\n",
       "       [ 34.105263,  36.      ],\n",
       "       [ 36.      ,  37.894737],\n",
       "       [ 37.894737,  39.789474],\n",
       "       [ 39.789474,  41.684211],\n",
       "       [ 41.684211,  43.578947],\n",
       "       [ 43.578947,  45.473684],\n",
       "       [ 45.473684,  47.368421],\n",
       "       [ 47.368421,  49.263158],\n",
       "       [ 49.263158,  51.157895],\n",
       "       [ 51.157895,  53.052632],\n",
       "       [ 53.052632,  54.947368],\n",
       "       [ 54.947368,  56.842105],\n",
       "       [ 56.842105,  58.736842],\n",
       "       [ 58.736842,  60.631579],\n",
       "       [ 60.631579,  62.526316],\n",
       "       [ 62.526316,  64.421053],\n",
       "       [ 64.421053,  66.315789],\n",
       "       [ 66.315789,  68.210526],\n",
       "       [ 68.210526,  70.105263],\n",
       "       [ 70.105263,  72.      ],\n",
       "       [ 72.      ,  73.894737],\n",
       "       [ 73.894737,  75.789474],\n",
       "       [ 75.789474,  77.684211],\n",
       "       [ 77.684211,  79.578947],\n",
       "       [ 79.578947,  81.473684],\n",
       "       [ 81.473684,  83.368421],\n",
       "       [ 83.368421,  85.263158],\n",
       "       [ 85.263158,  87.157895],\n",
       "       [ 87.157895,  89.052632],\n",
       "       [ 89.052632,  90.      ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9b7527bc-b0fa-47e5-8b00-82def7afeb15' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9b7527bc-b0fa-47e5-8b00-82def7afeb15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1998c806-83b6-4fb2-8823-336b888e24d7' class='xr-var-data-in' type='checkbox'><label for='data-1998c806-83b6-4fb2-8823-336b888e24d7' title='Show/Hide data 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([[ -1.25,   1.25],\n",
       "       [  1.25,   3.75],\n",
       "       [  3.75,   6.25],\n",
       "       ...,\n",
       "       [351.25, 353.75],\n",
       "       [353.75, 356.25],\n",
       "       [356.25, 358.75]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1a0ec17a-7b9e-48b7-a8aa-1773c27eb912' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a0ec17a-7b9e-48b7-a8aa-1773c27eb912' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1e66d32-0527-457e-826f-44a94b25ed55' class='xr-var-data-in' type='checkbox'><label for='data-e1e66d32-0527-457e-826f-44a94b25ed55' title='Show/Hide data 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>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>comment :</span></dt><dd>at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>original_name :</span></dt><dd>PRECT</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>history :</span></dt><dd>2011-06-01T05:45:35Z altered by CMOR: Converted type from &#x27;d&#x27; to &#x27;f&#x27;.</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_NorESM1-M_historical_r0i0p0.nc areacella: areacella_fx_NorESM1-M_historical_r0i0p0.nc</dd></dl></div><div class='xr-var-data'><pre>[25878528 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1d013bd6-2ada-430f-aa30-cc750d85347e' class='xr-section-summary-in' type='checkbox'  ><label for='section-1d013bd6-2ada-430f-aa30-cc750d85347e' class='xr-section-summary' >Attributes: <span>(26)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>institution :</span></dt><dd>Norwegian Climate Centre</dd><dt><span>institute_id :</span></dt><dd>NCC</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>source :</span></dt><dd>NorESM1-M 2011  atmosphere: CAM-Oslo (CAM4-Oslo-noresm-ver1_cmip5-r112, f19L26);  ocean: MICOM (MICOM-noresm-ver1_cmip5-r112, gx1v6L53);  sea ice: CICE (CICE4-noresm-ver1_cmip5-r112);  land: CLM (CLM4-noresm-ver1_cmip5-r112)</dd><dt><span>model_id :</span></dt><dd>NorESM1-M</dd><dt><span>forcing :</span></dt><dd>GHG, SA, Oz, Sl, Vl, BC, OC</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>255135.0</dd><dt><span>contact :</span></dt><dd>Please send any requests or bug reports to noresm-ncc@met.no.</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>5ccde64e-cfe8-47f6-9de8-9ea1621e7781</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>creation_date :</span></dt><dd>2011-06-01T05:45:35Z</dd><dt><span>history :</span></dt><dd>2011-06-01T05:45:35Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (27 April 2011) a5a1c518f52ae340313ba0aada03f862</dd><dt><span>title :</span></dt><dd>NorESM1-M model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>1</dd><dt><span>cmor_version :</span></dt><dd>2.6.0</dd></dl></div></li></ul></div></div>"
      ],
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       "<xarray.Dataset>\n",
       "Dimensions:    (time: 1872, bnds: 2, lat: 96, lon: 144)\n",
       "Coordinates:\n",
       "  * time       (time) object 1850-01-16 12:00:00 ... 2005-12-16 12:00:00\n",
       "  * lat        (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 86.21 88.11 90.0\n",
       "  * lon        (lon) float64 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object ...\n",
       "    lat_bnds   (lat, bnds) float64 ...\n",
       "    lon_bnds   (lon, bnds) float64 ...\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/26)\n",
       "    institution:            Norwegian Climate Centre\n",
       "    institute_id:           NCC\n",
       "    experiment_id:          historical\n",
       "    source:                 NorESM1-M 2011  atmosphere: CAM-Oslo (CAM4-Oslo-n...\n",
       "    model_id:               NorESM1-M\n",
       "    forcing:                GHG, SA, Oz, Sl, Vl, BC, OC\n",
       "    ...                     ...\n",
       "    table_id:               Table Amon (27 April 2011) a5a1c518f52ae340313ba0...\n",
       "    title:                  NorESM1-M model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.6.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#opening gcm noresm data\n",
    "\n",
    "data = xr.open_dataset('/home/mkibria/Academic/pr_of_thesis/GCM/Noresm1-M/pr_Amon_NorESM1-M_historical_r1i1p1_185001-200512.nc')\n",
    "\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5cbdbd2f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/mkibria/miniconda3/envs/esp-sp/lib/python3.9/site-packages/xarray/coding/times.py:351: FutureWarning: Index.ravel returning ndarray is deprecated; in a future version this will return a view on self.\n",
      "  sample = dates.ravel()[0]\n",
      "/tmp/ipykernel_28936/3137857967.py:3: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  datetimeindex = data.indexes['time'].to_datetimeindex()\n"
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       "  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: 1872, bnds: 2, lat: 96, lon: 144)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1850-01-16T12:00:00 ... 2005-12-16T12:00:00\n",
       "  * lat        (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 86.21 88.11 90.0\n",
       "  * lon        (lon) float64 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1850-01-01 00:00:00 ... 2006-01-01 00:00:00\n",
       "    lat_bnds   (lat, bnds) float64 -90.0 -89.05 -89.05 ... 89.05 89.05 90.0\n",
       "    lon_bnds   (lon, bnds) float64 -1.25 1.25 1.25 3.75 ... 356.2 356.2 358.8\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/26)\n",
       "    institution:            Norwegian Climate Centre\n",
       "    institute_id:           NCC\n",
       "    experiment_id:          historical\n",
       "    source:                 NorESM1-M 2011  atmosphere: CAM-Oslo (CAM4-Oslo-n...\n",
       "    model_id:               NorESM1-M\n",
       "    forcing:                GHG, SA, Oz, Sl, Vl, BC, OC\n",
       "    ...                     ...\n",
       "    table_id:               Table Amon (27 April 2011) a5a1c518f52ae340313ba0...\n",
       "    title:                  NorESM1-M model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.6.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-eee70301-eb2f-4282-9d03-1ed309141a7f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-eee70301-eb2f-4282-9d03-1ed309141a7f' 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>: 1872</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 96</li><li><span class='xr-has-index'>lon</span>: 144</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d39a82ce-946b-405b-b941-c3bb5cf3a5a1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d39a82ce-946b-405b-b941-c3bb5cf3a5a1' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1850-01-16T12:00:00 ... 2005-12-...</div><input id='attrs-901803d2-a58f-4a96-8399-7ded2283c457' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-901803d2-a58f-4a96-8399-7ded2283c457' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a04991fe-c9c1-4001-939c-97b10c4366cd' class='xr-var-data-in' type='checkbox'><label for='data-a04991fe-c9c1-4001-939c-97b10c4366cd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1850-01-16T12:00:00.000000000&#x27;, &#x27;1850-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;1850-03-16T12:00:00.000000000&#x27;, ..., &#x27;2005-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2005-11-16T00:00:00.000000000&#x27;, &#x27;2005-12-16T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.11 -86.21 ... 88.11 90.0</div><input id='attrs-d75acc09-c32a-4ba8-b113-44fa924dbedb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d75acc09-c32a-4ba8-b113-44fa924dbedb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8c21eb0-678e-4c11-84cf-435e96fb17b5' class='xr-var-data-in' type='checkbox'><label for='data-d8c21eb0-678e-4c11-84cf-435e96fb17b5' title='Show/Hide data 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -88.105263, -86.210526, -84.315789, -82.421053, -80.526316,\n",
       "       -78.631579, -76.736842, -74.842105, -72.947368, -71.052632, -69.157895,\n",
       "       -67.263158, -65.368421, -63.473684, -61.578947, -59.684211, -57.789474,\n",
       "       -55.894737, -54.      , -52.105263, -50.210526, -48.315789, -46.421053,\n",
       "       -44.526316, -42.631579, -40.736842, -38.842105, -36.947368, -35.052632,\n",
       "       -33.157895, -31.263158, -29.368421, -27.473684, -25.578947, -23.684211,\n",
       "       -21.789474, -19.894737, -18.      , -16.105263, -14.210526, -12.315789,\n",
       "       -10.421053,  -8.526316,  -6.631579,  -4.736842,  -2.842105,  -0.947368,\n",
       "         0.947368,   2.842105,   4.736842,   6.631579,   8.526316,  10.421053,\n",
       "        12.315789,  14.210526,  16.105263,  18.      ,  19.894737,  21.789474,\n",
       "        23.684211,  25.578947,  27.473684,  29.368421,  31.263158,  33.157895,\n",
       "        35.052632,  36.947368,  38.842105,  40.736842,  42.631579,  44.526316,\n",
       "        46.421053,  48.315789,  50.210526,  52.105263,  54.      ,  55.894737,\n",
       "        57.789474,  59.684211,  61.578947,  63.473684,  65.368421,  67.263158,\n",
       "        69.157895,  71.052632,  72.947368,  74.842105,  76.736842,  78.631579,\n",
       "        80.526316,  82.421053,  84.315789,  86.210526,  88.105263,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.5 5.0 ... 352.5 355.0 357.5</div><input id='attrs-be2243b7-742f-4277-a04c-d529865c115e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be2243b7-742f-4277-a04c-d529865c115e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3455515-5cb5-47c9-8d19-dbd81f748a6a' class='xr-var-data-in' type='checkbox'><label for='data-a3455515-5cb5-47c9-8d19-dbd81f748a6a' title='Show/Hide data 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0. ,   2.5,   5. ,   7.5,  10. ,  12.5,  15. ,  17.5,  20. ,  22.5,\n",
       "        25. ,  27.5,  30. ,  32.5,  35. ,  37.5,  40. ,  42.5,  45. ,  47.5,\n",
       "        50. ,  52.5,  55. ,  57.5,  60. ,  62.5,  65. ,  67.5,  70. ,  72.5,\n",
       "        75. ,  77.5,  80. ,  82.5,  85. ,  87.5,  90. ,  92.5,  95. ,  97.5,\n",
       "       100. , 102.5, 105. , 107.5, 110. , 112.5, 115. , 117.5, 120. , 122.5,\n",
       "       125. , 127.5, 130. , 132.5, 135. , 137.5, 140. , 142.5, 145. , 147.5,\n",
       "       150. , 152.5, 155. , 157.5, 160. , 162.5, 165. , 167.5, 170. , 172.5,\n",
       "       175. , 177.5, 180. , 182.5, 185. , 187.5, 190. , 192.5, 195. , 197.5,\n",
       "       200. , 202.5, 205. , 207.5, 210. , 212.5, 215. , 217.5, 220. , 222.5,\n",
       "       225. , 227.5, 230. , 232.5, 235. , 237.5, 240. , 242.5, 245. , 247.5,\n",
       "       250. , 252.5, 255. , 257.5, 260. , 262.5, 265. , 267.5, 270. , 272.5,\n",
       "       275. , 277.5, 280. , 282.5, 285. , 287.5, 290. , 292.5, 295. , 297.5,\n",
       "       300. , 302.5, 305. , 307.5, 310. , 312.5, 315. , 317.5, 320. , 322.5,\n",
       "       325. , 327.5, 330. , 332.5, 335. , 337.5, 340. , 342.5, 345. , 347.5,\n",
       "       350. , 352.5, 355. , 357.5])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c4ec7020-f286-4ed8-95bc-0cca7a5fdea7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c4ec7020-f286-4ed8-95bc-0cca7a5fdea7' class='xr-section-summary' >Data variables: <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>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-01 00:00:00 ... 2006-01-...</div><input id='attrs-6afa4565-d11c-4c0f-bbd0-85f7541280b1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6afa4565-d11c-4c0f-bbd0-85f7541280b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b800060-0932-4638-8019-11b77a369d99' class='xr-var-data-in' type='checkbox'><label for='data-2b800060-0932-4638-8019-11b77a369d99' title='Show/Hide data 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(1850, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1850, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1850, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1850, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1850, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1850, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       ...,\n",
       "       [cftime.DatetimeNoLeap(2005, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 12, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 12, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2006, 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>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.05 -89.05 ... 89.05 90.0</div><input id='attrs-b2bcf62c-cd00-44b8-a666-5f62917d7cea' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b2bcf62c-cd00-44b8-a666-5f62917d7cea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf55ac24-5b56-4fdc-9065-6d99f98dc656' class='xr-var-data-in' type='checkbox'><label for='data-bf55ac24-5b56-4fdc-9065-6d99f98dc656' title='Show/Hide data 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([[-90.      , -89.052632],\n",
       "       [-89.052632, -87.157895],\n",
       "       [-87.157895, -85.263158],\n",
       "       [-85.263158, -83.368421],\n",
       "       [-83.368421, -81.473684],\n",
       "       [-81.473684, -79.578947],\n",
       "       [-79.578947, -77.684211],\n",
       "       [-77.684211, -75.789474],\n",
       "       [-75.789474, -73.894737],\n",
       "       [-73.894737, -72.      ],\n",
       "       [-72.      , -70.105263],\n",
       "       [-70.105263, -68.210526],\n",
       "       [-68.210526, -66.315789],\n",
       "       [-66.315789, -64.421053],\n",
       "       [-64.421053, -62.526316],\n",
       "       [-62.526316, -60.631579],\n",
       "       [-60.631579, -58.736842],\n",
       "       [-58.736842, -56.842105],\n",
       "       [-56.842105, -54.947368],\n",
       "       [-54.947368, -53.052632],\n",
       "       [-53.052632, -51.157895],\n",
       "       [-51.157895, -49.263158],\n",
       "       [-49.263158, -47.368421],\n",
       "       [-47.368421, -45.473684],\n",
       "       [-45.473684, -43.578947],\n",
       "       [-43.578947, -41.684211],\n",
       "       [-41.684211, -39.789474],\n",
       "       [-39.789474, -37.894737],\n",
       "       [-37.894737, -36.      ],\n",
       "       [-36.      , -34.105263],\n",
       "       [-34.105263, -32.210526],\n",
       "       [-32.210526, -30.315789],\n",
       "       [-30.315789, -28.421053],\n",
       "       [-28.421053, -26.526316],\n",
       "       [-26.526316, -24.631579],\n",
       "       [-24.631579, -22.736842],\n",
       "       [-22.736842, -20.842105],\n",
       "       [-20.842105, -18.947368],\n",
       "       [-18.947368, -17.052632],\n",
       "       [-17.052632, -15.157895],\n",
       "       [-15.157895, -13.263158],\n",
       "       [-13.263158, -11.368421],\n",
       "       [-11.368421,  -9.473684],\n",
       "       [ -9.473684,  -7.578947],\n",
       "       [ -7.578947,  -5.684211],\n",
       "       [ -5.684211,  -3.789474],\n",
       "       [ -3.789474,  -1.894737],\n",
       "       [ -1.894737,   0.      ],\n",
       "       [  0.      ,   1.894737],\n",
       "       [  1.894737,   3.789474],\n",
       "       [  3.789474,   5.684211],\n",
       "       [  5.684211,   7.578947],\n",
       "       [  7.578947,   9.473684],\n",
       "       [  9.473684,  11.368421],\n",
       "       [ 11.368421,  13.263158],\n",
       "       [ 13.263158,  15.157895],\n",
       "       [ 15.157895,  17.052632],\n",
       "       [ 17.052632,  18.947368],\n",
       "       [ 18.947368,  20.842105],\n",
       "       [ 20.842105,  22.736842],\n",
       "       [ 22.736842,  24.631579],\n",
       "       [ 24.631579,  26.526316],\n",
       "       [ 26.526316,  28.421053],\n",
       "       [ 28.421053,  30.315789],\n",
       "       [ 30.315789,  32.210526],\n",
       "       [ 32.210526,  34.105263],\n",
       "       [ 34.105263,  36.      ],\n",
       "       [ 36.      ,  37.894737],\n",
       "       [ 37.894737,  39.789474],\n",
       "       [ 39.789474,  41.684211],\n",
       "       [ 41.684211,  43.578947],\n",
       "       [ 43.578947,  45.473684],\n",
       "       [ 45.473684,  47.368421],\n",
       "       [ 47.368421,  49.263158],\n",
       "       [ 49.263158,  51.157895],\n",
       "       [ 51.157895,  53.052632],\n",
       "       [ 53.052632,  54.947368],\n",
       "       [ 54.947368,  56.842105],\n",
       "       [ 56.842105,  58.736842],\n",
       "       [ 58.736842,  60.631579],\n",
       "       [ 60.631579,  62.526316],\n",
       "       [ 62.526316,  64.421053],\n",
       "       [ 64.421053,  66.315789],\n",
       "       [ 66.315789,  68.210526],\n",
       "       [ 68.210526,  70.105263],\n",
       "       [ 70.105263,  72.      ],\n",
       "       [ 72.      ,  73.894737],\n",
       "       [ 73.894737,  75.789474],\n",
       "       [ 75.789474,  77.684211],\n",
       "       [ 77.684211,  79.578947],\n",
       "       [ 79.578947,  81.473684],\n",
       "       [ 81.473684,  83.368421],\n",
       "       [ 83.368421,  85.263158],\n",
       "       [ 85.263158,  87.157895],\n",
       "       [ 87.157895,  89.052632],\n",
       "       [ 89.052632,  90.      ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.25 1.25 1.25 ... 356.2 358.8</div><input id='attrs-0caf9c33-7296-43df-b8b3-57f1c4275f61' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0caf9c33-7296-43df-b8b3-57f1c4275f61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6b84a8d-181b-4773-a830-10b7b0f76193' class='xr-var-data-in' type='checkbox'><label for='data-a6b84a8d-181b-4773-a830-10b7b0f76193' title='Show/Hide data 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([[ -1.25,   1.25],\n",
       "       [  1.25,   3.75],\n",
       "       [  3.75,   6.25],\n",
       "       ...,\n",
       "       [351.25, 353.75],\n",
       "       [353.75, 356.25],\n",
       "       [356.25, 358.75]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6f02b355-6238-4a4a-8fdc-d506848058d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f02b355-6238-4a4a-8fdc-d506848058d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c73493b-9d44-49fb-b029-30cabc7af8e7' class='xr-var-data-in' type='checkbox'><label for='data-5c73493b-9d44-49fb-b029-30cabc7af8e7' title='Show/Hide data 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>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>comment :</span></dt><dd>at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>original_name :</span></dt><dd>PRECT</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>history :</span></dt><dd>2011-06-01T05:45:35Z altered by CMOR: Converted type from &#x27;d&#x27; to &#x27;f&#x27;.</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_NorESM1-M_historical_r0i0p0.nc areacella: areacella_fx_NorESM1-M_historical_r0i0p0.nc</dd></dl></div><div class='xr-var-data'><pre>[25878528 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0a129df5-fdcf-4378-89d6-a8b0c047bc0a' class='xr-section-summary-in' type='checkbox'  ><label for='section-0a129df5-fdcf-4378-89d6-a8b0c047bc0a' class='xr-section-summary' >Attributes: <span>(26)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>institution :</span></dt><dd>Norwegian Climate Centre</dd><dt><span>institute_id :</span></dt><dd>NCC</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>source :</span></dt><dd>NorESM1-M 2011  atmosphere: CAM-Oslo (CAM4-Oslo-noresm-ver1_cmip5-r112, f19L26);  ocean: MICOM (MICOM-noresm-ver1_cmip5-r112, gx1v6L53);  sea ice: CICE (CICE4-noresm-ver1_cmip5-r112);  land: CLM (CLM4-noresm-ver1_cmip5-r112)</dd><dt><span>model_id :</span></dt><dd>NorESM1-M</dd><dt><span>forcing :</span></dt><dd>GHG, SA, Oz, Sl, Vl, BC, OC</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>255135.0</dd><dt><span>contact :</span></dt><dd>Please send any requests or bug reports to noresm-ncc@met.no.</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>5ccde64e-cfe8-47f6-9de8-9ea1621e7781</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>creation_date :</span></dt><dd>2011-06-01T05:45:35Z</dd><dt><span>history :</span></dt><dd>2011-06-01T05:45:35Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (27 April 2011) a5a1c518f52ae340313ba0aada03f862</dd><dt><span>title :</span></dt><dd>NorESM1-M model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>1</dd><dt><span>cmor_version :</span></dt><dd>2.6.0</dd></dl></div></li></ul></div></div>"
      ],
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       "<xarray.Dataset>\n",
       "Dimensions:    (time: 1872, bnds: 2, lat: 96, lon: 144)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1850-01-16T12:00:00 ... 2005-12-16T12:00:00\n",
       "  * lat        (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 86.21 88.11 90.0\n",
       "  * lon        (lon) float64 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1850-01-01 00:00:00 ... 2006-01-01 00:00:00\n",
       "    lat_bnds   (lat, bnds) float64 -90.0 -89.05 -89.05 ... 89.05 89.05 90.0\n",
       "    lon_bnds   (lon, bnds) float64 -1.25 1.25 1.25 3.75 ... 356.2 356.2 358.8\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/26)\n",
       "    institution:            Norwegian Climate Centre\n",
       "    institute_id:           NCC\n",
       "    experiment_id:          historical\n",
       "    source:                 NorESM1-M 2011  atmosphere: CAM-Oslo (CAM4-Oslo-n...\n",
       "    model_id:               NorESM1-M\n",
       "    forcing:                GHG, SA, Oz, Sl, Vl, BC, OC\n",
       "    ...                     ...\n",
       "    table_id:               Table Amon (27 April 2011) a5a1c518f52ae340313ba0...\n",
       "    title:                  NorESM1-M model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.6.0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#changing time dim to datetime64[ns] dtype\n",
    "\n",
    "datetimeindex = data.indexes['time'].to_datetimeindex()\n",
    "data['time']=datetimeindex\n",
    "data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "cafd5692",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 299, bnds: 2, lat: 96, lon: 144)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-01-16T12:00:00 ... 2005-11-16\n",
       "  * lat        (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 86.21 88.11 90.0\n",
       "  * lon        (lon) float64 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
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       "    lat_bnds   (lat, bnds) float64 -90.0 -89.05 -89.05 ... 89.05 89.05 90.0\n",
       "    lon_bnds   (lon, bnds) float64 -1.25 1.25 1.25 3.75 ... 356.2 356.2 358.8\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/26)\n",
       "    institution:            Norwegian Climate Centre\n",
       "    institute_id:           NCC\n",
       "    experiment_id:          historical\n",
       "    source:                 NorESM1-M 2011  atmosphere: CAM-Oslo (CAM4-Oslo-n...\n",
       "    model_id:               NorESM1-M\n",
       "    forcing:                GHG, SA, Oz, Sl, Vl, BC, OC\n",
       "    ...                     ...\n",
       "    table_id:               Table Amon (27 April 2011) a5a1c518f52ae340313ba0...\n",
       "    title:                  NorESM1-M model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.6.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-7ffe1e5f-faaa-4f23-863f-130743c355b8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7ffe1e5f-faaa-4f23-863f-130743c355b8' 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>: 299</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 96</li><li><span class='xr-has-index'>lon</span>: 144</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ede7265f-1abe-4721-90be-9206ff55ae82' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ede7265f-1abe-4721-90be-9206ff55ae82' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-01-16T12:00:00 ... 2005-11-16</div><input id='attrs-fbaab56a-a849-4352-be88-7177f3377260' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fbaab56a-a849-4352-be88-7177f3377260' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9f91538-70bc-4eff-be88-99c0bb93a9cc' class='xr-var-data-in' type='checkbox'><label for='data-b9f91538-70bc-4eff-be88-99c0bb93a9cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-01-16T12:00:00.000000000&#x27;, &#x27;1981-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-03-16T12:00:00.000000000&#x27;, ..., &#x27;2005-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-10-16T12:00:00.000000000&#x27;, &#x27;2005-11-16T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.11 -86.21 ... 88.11 90.0</div><input id='attrs-40c8127b-c5a3-4757-81c2-b3c531149546' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-40c8127b-c5a3-4757-81c2-b3c531149546' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-419e205b-5a4e-4a69-b0a7-f3d7c2c8f013' class='xr-var-data-in' type='checkbox'><label for='data-419e205b-5a4e-4a69-b0a7-f3d7c2c8f013' title='Show/Hide data 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -88.105263, -86.210526, -84.315789, -82.421053, -80.526316,\n",
       "       -78.631579, -76.736842, -74.842105, -72.947368, -71.052632, -69.157895,\n",
       "       -67.263158, -65.368421, -63.473684, -61.578947, -59.684211, -57.789474,\n",
       "       -55.894737, -54.      , -52.105263, -50.210526, -48.315789, -46.421053,\n",
       "       -44.526316, -42.631579, -40.736842, -38.842105, -36.947368, -35.052632,\n",
       "       -33.157895, -31.263158, -29.368421, -27.473684, -25.578947, -23.684211,\n",
       "       -21.789474, -19.894737, -18.      , -16.105263, -14.210526, -12.315789,\n",
       "       -10.421053,  -8.526316,  -6.631579,  -4.736842,  -2.842105,  -0.947368,\n",
       "         0.947368,   2.842105,   4.736842,   6.631579,   8.526316,  10.421053,\n",
       "        12.315789,  14.210526,  16.105263,  18.      ,  19.894737,  21.789474,\n",
       "        23.684211,  25.578947,  27.473684,  29.368421,  31.263158,  33.157895,\n",
       "        35.052632,  36.947368,  38.842105,  40.736842,  42.631579,  44.526316,\n",
       "        46.421053,  48.315789,  50.210526,  52.105263,  54.      ,  55.894737,\n",
       "        57.789474,  59.684211,  61.578947,  63.473684,  65.368421,  67.263158,\n",
       "        69.157895,  71.052632,  72.947368,  74.842105,  76.736842,  78.631579,\n",
       "        80.526316,  82.421053,  84.315789,  86.210526,  88.105263,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.5 5.0 ... 352.5 355.0 357.5</div><input id='attrs-b69a2ec7-b7fb-4ad2-bf40-5e2277e6f6f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b69a2ec7-b7fb-4ad2-bf40-5e2277e6f6f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4eb539f6-31de-47c8-b940-0aa2fe82d664' class='xr-var-data-in' type='checkbox'><label for='data-4eb539f6-31de-47c8-b940-0aa2fe82d664' title='Show/Hide data 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0. ,   2.5,   5. ,   7.5,  10. ,  12.5,  15. ,  17.5,  20. ,  22.5,\n",
       "        25. ,  27.5,  30. ,  32.5,  35. ,  37.5,  40. ,  42.5,  45. ,  47.5,\n",
       "        50. ,  52.5,  55. ,  57.5,  60. ,  62.5,  65. ,  67.5,  70. ,  72.5,\n",
       "        75. ,  77.5,  80. ,  82.5,  85. ,  87.5,  90. ,  92.5,  95. ,  97.5,\n",
       "       100. , 102.5, 105. , 107.5, 110. , 112.5, 115. , 117.5, 120. , 122.5,\n",
       "       125. , 127.5, 130. , 132.5, 135. , 137.5, 140. , 142.5, 145. , 147.5,\n",
       "       150. , 152.5, 155. , 157.5, 160. , 162.5, 165. , 167.5, 170. , 172.5,\n",
       "       175. , 177.5, 180. , 182.5, 185. , 187.5, 190. , 192.5, 195. , 197.5,\n",
       "       200. , 202.5, 205. , 207.5, 210. , 212.5, 215. , 217.5, 220. , 222.5,\n",
       "       225. , 227.5, 230. , 232.5, 235. , 237.5, 240. , 242.5, 245. , 247.5,\n",
       "       250. , 252.5, 255. , 257.5, 260. , 262.5, 265. , 267.5, 270. , 272.5,\n",
       "       275. , 277.5, 280. , 282.5, 285. , 287.5, 290. , 292.5, 295. , 297.5,\n",
       "       300. , 302.5, 305. , 307.5, 310. , 312.5, 315. , 317.5, 320. , 322.5,\n",
       "       325. , 327.5, 330. , 332.5, 335. , 337.5, 340. , 342.5, 345. , 347.5,\n",
       "       350. , 352.5, 355. , 357.5])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-aff4736b-b789-4ef4-9230-9749ced72c33' class='xr-section-summary-in' type='checkbox'  checked><label for='section-aff4736b-b789-4ef4-9230-9749ced72c33' class='xr-section-summary' >Data variables: <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>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1981-01-01 00:00:00 ... 2005-12-...</div><input id='attrs-552ee562-bce6-44fd-b042-47c282e1e269' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-552ee562-bce6-44fd-b042-47c282e1e269' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7bff9df4-82bf-42dc-99e3-92b5af8bb33f' class='xr-var-data-in' type='checkbox'><label for='data-7bff9df4-82bf-42dc-99e3-92b5af8bb33f' title='Show/Hide data 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(1981, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1981, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1981, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       ...,\n",
       "       [cftime.DatetimeNoLeap(2005, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 12, 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>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.05 -89.05 ... 89.05 90.0</div><input id='attrs-fbdc2d0a-685e-488d-838d-963879491c52' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fbdc2d0a-685e-488d-838d-963879491c52' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a30103de-89a9-4931-ae36-c1052c31f169' class='xr-var-data-in' type='checkbox'><label for='data-a30103de-89a9-4931-ae36-c1052c31f169' title='Show/Hide data 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([[-90.      , -89.052632],\n",
       "       [-89.052632, -87.157895],\n",
       "       [-87.157895, -85.263158],\n",
       "       [-85.263158, -83.368421],\n",
       "       [-83.368421, -81.473684],\n",
       "       [-81.473684, -79.578947],\n",
       "       [-79.578947, -77.684211],\n",
       "       [-77.684211, -75.789474],\n",
       "       [-75.789474, -73.894737],\n",
       "       [-73.894737, -72.      ],\n",
       "       [-72.      , -70.105263],\n",
       "       [-70.105263, -68.210526],\n",
       "       [-68.210526, -66.315789],\n",
       "       [-66.315789, -64.421053],\n",
       "       [-64.421053, -62.526316],\n",
       "       [-62.526316, -60.631579],\n",
       "       [-60.631579, -58.736842],\n",
       "       [-58.736842, -56.842105],\n",
       "       [-56.842105, -54.947368],\n",
       "       [-54.947368, -53.052632],\n",
       "       [-53.052632, -51.157895],\n",
       "       [-51.157895, -49.263158],\n",
       "       [-49.263158, -47.368421],\n",
       "       [-47.368421, -45.473684],\n",
       "       [-45.473684, -43.578947],\n",
       "       [-43.578947, -41.684211],\n",
       "       [-41.684211, -39.789474],\n",
       "       [-39.789474, -37.894737],\n",
       "       [-37.894737, -36.      ],\n",
       "       [-36.      , -34.105263],\n",
       "       [-34.105263, -32.210526],\n",
       "       [-32.210526, -30.315789],\n",
       "       [-30.315789, -28.421053],\n",
       "       [-28.421053, -26.526316],\n",
       "       [-26.526316, -24.631579],\n",
       "       [-24.631579, -22.736842],\n",
       "       [-22.736842, -20.842105],\n",
       "       [-20.842105, -18.947368],\n",
       "       [-18.947368, -17.052632],\n",
       "       [-17.052632, -15.157895],\n",
       "       [-15.157895, -13.263158],\n",
       "       [-13.263158, -11.368421],\n",
       "       [-11.368421,  -9.473684],\n",
       "       [ -9.473684,  -7.578947],\n",
       "       [ -7.578947,  -5.684211],\n",
       "       [ -5.684211,  -3.789474],\n",
       "       [ -3.789474,  -1.894737],\n",
       "       [ -1.894737,   0.      ],\n",
       "       [  0.      ,   1.894737],\n",
       "       [  1.894737,   3.789474],\n",
       "       [  3.789474,   5.684211],\n",
       "       [  5.684211,   7.578947],\n",
       "       [  7.578947,   9.473684],\n",
       "       [  9.473684,  11.368421],\n",
       "       [ 11.368421,  13.263158],\n",
       "       [ 13.263158,  15.157895],\n",
       "       [ 15.157895,  17.052632],\n",
       "       [ 17.052632,  18.947368],\n",
       "       [ 18.947368,  20.842105],\n",
       "       [ 20.842105,  22.736842],\n",
       "       [ 22.736842,  24.631579],\n",
       "       [ 24.631579,  26.526316],\n",
       "       [ 26.526316,  28.421053],\n",
       "       [ 28.421053,  30.315789],\n",
       "       [ 30.315789,  32.210526],\n",
       "       [ 32.210526,  34.105263],\n",
       "       [ 34.105263,  36.      ],\n",
       "       [ 36.      ,  37.894737],\n",
       "       [ 37.894737,  39.789474],\n",
       "       [ 39.789474,  41.684211],\n",
       "       [ 41.684211,  43.578947],\n",
       "       [ 43.578947,  45.473684],\n",
       "       [ 45.473684,  47.368421],\n",
       "       [ 47.368421,  49.263158],\n",
       "       [ 49.263158,  51.157895],\n",
       "       [ 51.157895,  53.052632],\n",
       "       [ 53.052632,  54.947368],\n",
       "       [ 54.947368,  56.842105],\n",
       "       [ 56.842105,  58.736842],\n",
       "       [ 58.736842,  60.631579],\n",
       "       [ 60.631579,  62.526316],\n",
       "       [ 62.526316,  64.421053],\n",
       "       [ 64.421053,  66.315789],\n",
       "       [ 66.315789,  68.210526],\n",
       "       [ 68.210526,  70.105263],\n",
       "       [ 70.105263,  72.      ],\n",
       "       [ 72.      ,  73.894737],\n",
       "       [ 73.894737,  75.789474],\n",
       "       [ 75.789474,  77.684211],\n",
       "       [ 77.684211,  79.578947],\n",
       "       [ 79.578947,  81.473684],\n",
       "       [ 81.473684,  83.368421],\n",
       "       [ 83.368421,  85.263158],\n",
       "       [ 85.263158,  87.157895],\n",
       "       [ 87.157895,  89.052632],\n",
       "       [ 89.052632,  90.      ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.25 1.25 1.25 ... 356.2 358.8</div><input id='attrs-ad07a3fc-a916-441b-8c03-e5d0cbdeb694' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ad07a3fc-a916-441b-8c03-e5d0cbdeb694' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7471ba6-35fd-47be-83a6-10a3acd0db0e' class='xr-var-data-in' type='checkbox'><label for='data-e7471ba6-35fd-47be-83a6-10a3acd0db0e' title='Show/Hide data 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([[ -1.25,   1.25],\n",
       "       [  1.25,   3.75],\n",
       "       [  3.75,   6.25],\n",
       "       ...,\n",
       "       [351.25, 353.75],\n",
       "       [353.75, 356.25],\n",
       "       [356.25, 358.75]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c2e78665-fc73-4d5d-b5a5-8d510b61ad58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c2e78665-fc73-4d5d-b5a5-8d510b61ad58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f880c9d-95c5-4c5b-808b-d7dcbd60ec69' class='xr-var-data-in' type='checkbox'><label for='data-5f880c9d-95c5-4c5b-808b-d7dcbd60ec69' title='Show/Hide data 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>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>comment :</span></dt><dd>at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>original_name :</span></dt><dd>PRECT</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>history :</span></dt><dd>2011-06-01T05:45:35Z altered by CMOR: Converted type from &#x27;d&#x27; to &#x27;f&#x27;.</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_NorESM1-M_historical_r0i0p0.nc areacella: areacella_fx_NorESM1-M_historical_r0i0p0.nc</dd></dl></div><div class='xr-var-data'><pre>[4133376 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ad9dd045-0e3d-4458-a5fb-a2f2377b608a' class='xr-section-summary-in' type='checkbox'  ><label for='section-ad9dd045-0e3d-4458-a5fb-a2f2377b608a' class='xr-section-summary' >Attributes: <span>(26)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>institution :</span></dt><dd>Norwegian Climate Centre</dd><dt><span>institute_id :</span></dt><dd>NCC</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>source :</span></dt><dd>NorESM1-M 2011  atmosphere: CAM-Oslo (CAM4-Oslo-noresm-ver1_cmip5-r112, f19L26);  ocean: MICOM (MICOM-noresm-ver1_cmip5-r112, gx1v6L53);  sea ice: CICE (CICE4-noresm-ver1_cmip5-r112);  land: CLM (CLM4-noresm-ver1_cmip5-r112)</dd><dt><span>model_id :</span></dt><dd>NorESM1-M</dd><dt><span>forcing :</span></dt><dd>GHG, SA, Oz, Sl, Vl, BC, OC</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>255135.0</dd><dt><span>contact :</span></dt><dd>Please send any requests or bug reports to noresm-ncc@met.no.</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>5ccde64e-cfe8-47f6-9de8-9ea1621e7781</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>creation_date :</span></dt><dd>2011-06-01T05:45:35Z</dd><dt><span>history :</span></dt><dd>2011-06-01T05:45:35Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (27 April 2011) a5a1c518f52ae340313ba0aada03f862</dd><dt><span>title :</span></dt><dd>NorESM1-M model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>1</dd><dt><span>cmor_version :</span></dt><dd>2.6.0</dd></dl></div></li></ul></div></div>"
      ],
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       "<xarray.Dataset>\n",
       "Dimensions:    (time: 299, bnds: 2, lat: 96, lon: 144)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-01-16T12:00:00 ... 2005-11-16\n",
       "  * lat        (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 86.21 88.11 90.0\n",
       "  * lon        (lon) float64 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1981-01-01 00:00:00 ... 2005-12-01 00:00:00\n",
       "    lat_bnds   (lat, bnds) float64 -90.0 -89.05 -89.05 ... 89.05 89.05 90.0\n",
       "    lon_bnds   (lon, bnds) float64 -1.25 1.25 1.25 3.75 ... 356.2 356.2 358.8\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/26)\n",
       "    institution:            Norwegian Climate Centre\n",
       "    institute_id:           NCC\n",
       "    experiment_id:          historical\n",
       "    source:                 NorESM1-M 2011  atmosphere: CAM-Oslo (CAM4-Oslo-n...\n",
       "    model_id:               NorESM1-M\n",
       "    forcing:                GHG, SA, Oz, Sl, Vl, BC, OC\n",
       "    ...                     ...\n",
       "    table_id:               Table Amon (27 April 2011) a5a1c518f52ae340313ba0...\n",
       "    title:                  NorESM1-M model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.6.0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#to select the year from 1980 to 2015\n",
    "data = data.sel(time=slice('1981-01-16T12:00:00.000000000','2005-12-16T00:00:00.000000000'))\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c811b0f2",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 100, bnds: 2, lat: 96, lon: 144)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-06-16 ... 2005-09-16\n",
       "  * lat        (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 86.21 88.11 90.0\n",
       "  * lon        (lon) float64 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5\n",
       "Dimensions without coordinates: bnds\n",
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       "    lat_bnds   (lat, bnds) float64 -90.0 -89.05 -89.05 ... 89.05 89.05 90.0\n",
       "    lon_bnds   (lon, bnds) float64 -1.25 1.25 1.25 3.75 ... 356.2 356.2 358.8\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/26)\n",
       "    institution:            Norwegian Climate Centre\n",
       "    institute_id:           NCC\n",
       "    experiment_id:          historical\n",
       "    source:                 NorESM1-M 2011  atmosphere: CAM-Oslo (CAM4-Oslo-n...\n",
       "    model_id:               NorESM1-M\n",
       "    forcing:                GHG, SA, Oz, Sl, Vl, BC, OC\n",
       "    ...                     ...\n",
       "    table_id:               Table Amon (27 April 2011) a5a1c518f52ae340313ba0...\n",
       "    title:                  NorESM1-M model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.6.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d628cfab-bde3-4f8c-b9af-3d09594afb25' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d628cfab-bde3-4f8c-b9af-3d09594afb25' 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>: 100</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 96</li><li><span class='xr-has-index'>lon</span>: 144</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-3a685216-2b5a-42e5-a45b-d3e553fb9a1a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3a685216-2b5a-42e5-a45b-d3e553fb9a1a' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-06-16 ... 2005-09-16</div><input id='attrs-6f84e6c2-3da7-4617-94d1-734f2881af53' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6f84e6c2-3da7-4617-94d1-734f2881af53' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad8b9844-e319-4699-b895-c9441912ef2f' class='xr-var-data-in' type='checkbox'><label for='data-ad8b9844-e319-4699-b895-c9441912ef2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-06-16T00:00:00.000000000&#x27;, &#x27;1981-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1981-08-16T12:00:00.000000000&#x27;, &#x27;1981-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-06-16T00:00:00.000000000&#x27;, &#x27;1982-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1982-08-16T12:00:00.000000000&#x27;, &#x27;1982-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-06-16T00:00:00.000000000&#x27;, &#x27;1983-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1983-08-16T12:00:00.000000000&#x27;, &#x27;1983-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-06-16T00:00:00.000000000&#x27;, &#x27;1984-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1984-08-16T12:00:00.000000000&#x27;, &#x27;1984-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-06-16T00:00:00.000000000&#x27;, &#x27;1985-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1985-08-16T12:00:00.000000000&#x27;, &#x27;1985-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-06-16T00:00:00.000000000&#x27;, &#x27;1986-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1986-08-16T12:00:00.000000000&#x27;, &#x27;1986-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-06-16T00:00:00.000000000&#x27;, &#x27;1987-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1987-08-16T12:00:00.000000000&#x27;, &#x27;1987-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-06-16T00:00:00.000000000&#x27;, &#x27;1988-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1988-08-16T12:00:00.000000000&#x27;, &#x27;1988-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-06-16T00:00:00.000000000&#x27;, &#x27;1989-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1989-08-16T12:00:00.000000000&#x27;, &#x27;1989-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-06-16T00:00:00.000000000&#x27;, &#x27;1990-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1990-08-16T12:00:00.000000000&#x27;, &#x27;1990-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-06-16T00:00:00.000000000&#x27;, &#x27;1991-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1991-08-16T12:00:00.000000000&#x27;, &#x27;1991-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-06-16T00:00:00.000000000&#x27;, &#x27;1992-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1992-08-16T12:00:00.000000000&#x27;, &#x27;1992-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-06-16T00:00:00.000000000&#x27;, &#x27;1993-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1993-08-16T12:00:00.000000000&#x27;, &#x27;1993-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-06-16T00:00:00.000000000&#x27;, &#x27;1994-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1994-08-16T12:00:00.000000000&#x27;, &#x27;1994-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-06-16T00:00:00.000000000&#x27;, &#x27;1995-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1995-08-16T12:00:00.000000000&#x27;, &#x27;1995-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-06-16T00:00:00.000000000&#x27;, &#x27;1996-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1996-08-16T12:00:00.000000000&#x27;, &#x27;1996-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-06-16T00:00:00.000000000&#x27;, &#x27;1997-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1997-08-16T12:00:00.000000000&#x27;, &#x27;1997-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-06-16T00:00:00.000000000&#x27;, &#x27;1998-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1998-08-16T12:00:00.000000000&#x27;, &#x27;1998-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-06-16T00:00:00.000000000&#x27;, &#x27;1999-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1999-08-16T12:00:00.000000000&#x27;, &#x27;1999-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-16T00:00:00.000000000&#x27;, &#x27;2000-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2000-08-16T12:00:00.000000000&#x27;, &#x27;2000-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-06-16T00:00:00.000000000&#x27;, &#x27;2001-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2001-08-16T12:00:00.000000000&#x27;, &#x27;2001-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-16T00:00:00.000000000&#x27;, &#x27;2002-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-16T12:00:00.000000000&#x27;, &#x27;2002-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-16T00:00:00.000000000&#x27;, &#x27;2003-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-16T12:00:00.000000000&#x27;, &#x27;2003-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-16T00:00:00.000000000&#x27;, &#x27;2004-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-16T12:00:00.000000000&#x27;, &#x27;2004-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-16T00:00:00.000000000&#x27;, &#x27;2005-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2005-08-16T12:00:00.000000000&#x27;, &#x27;2005-09-16T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.11 -86.21 ... 88.11 90.0</div><input id='attrs-9fbecec0-2d29-437b-bcf1-2a7f55094fa9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9fbecec0-2d29-437b-bcf1-2a7f55094fa9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-027fb35d-6191-49c9-9e1e-e8a41fe7fc0d' class='xr-var-data-in' type='checkbox'><label for='data-027fb35d-6191-49c9-9e1e-e8a41fe7fc0d' title='Show/Hide data 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-90.      , -88.105263, -86.210526, -84.315789, -82.421053, -80.526316,\n",
       "       -78.631579, -76.736842, -74.842105, -72.947368, -71.052632, -69.157895,\n",
       "       -67.263158, -65.368421, -63.473684, -61.578947, -59.684211, -57.789474,\n",
       "       -55.894737, -54.      , -52.105263, -50.210526, -48.315789, -46.421053,\n",
       "       -44.526316, -42.631579, -40.736842, -38.842105, -36.947368, -35.052632,\n",
       "       -33.157895, -31.263158, -29.368421, -27.473684, -25.578947, -23.684211,\n",
       "       -21.789474, -19.894737, -18.      , -16.105263, -14.210526, -12.315789,\n",
       "       -10.421053,  -8.526316,  -6.631579,  -4.736842,  -2.842105,  -0.947368,\n",
       "         0.947368,   2.842105,   4.736842,   6.631579,   8.526316,  10.421053,\n",
       "        12.315789,  14.210526,  16.105263,  18.      ,  19.894737,  21.789474,\n",
       "        23.684211,  25.578947,  27.473684,  29.368421,  31.263158,  33.157895,\n",
       "        35.052632,  36.947368,  38.842105,  40.736842,  42.631579,  44.526316,\n",
       "        46.421053,  48.315789,  50.210526,  52.105263,  54.      ,  55.894737,\n",
       "        57.789474,  59.684211,  61.578947,  63.473684,  65.368421,  67.263158,\n",
       "        69.157895,  71.052632,  72.947368,  74.842105,  76.736842,  78.631579,\n",
       "        80.526316,  82.421053,  84.315789,  86.210526,  88.105263,  90.      ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.5 5.0 ... 352.5 355.0 357.5</div><input id='attrs-d62c7d52-1d69-4da7-8f86-77a7f8aabb05' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d62c7d52-1d69-4da7-8f86-77a7f8aabb05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9219f47-e05e-4cc8-ba7c-07fb6c591992' class='xr-var-data-in' type='checkbox'><label for='data-d9219f47-e05e-4cc8-ba7c-07fb6c591992' title='Show/Hide data 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0. ,   2.5,   5. ,   7.5,  10. ,  12.5,  15. ,  17.5,  20. ,  22.5,\n",
       "        25. ,  27.5,  30. ,  32.5,  35. ,  37.5,  40. ,  42.5,  45. ,  47.5,\n",
       "        50. ,  52.5,  55. ,  57.5,  60. ,  62.5,  65. ,  67.5,  70. ,  72.5,\n",
       "        75. ,  77.5,  80. ,  82.5,  85. ,  87.5,  90. ,  92.5,  95. ,  97.5,\n",
       "       100. , 102.5, 105. , 107.5, 110. , 112.5, 115. , 117.5, 120. , 122.5,\n",
       "       125. , 127.5, 130. , 132.5, 135. , 137.5, 140. , 142.5, 145. , 147.5,\n",
       "       150. , 152.5, 155. , 157.5, 160. , 162.5, 165. , 167.5, 170. , 172.5,\n",
       "       175. , 177.5, 180. , 182.5, 185. , 187.5, 190. , 192.5, 195. , 197.5,\n",
       "       200. , 202.5, 205. , 207.5, 210. , 212.5, 215. , 217.5, 220. , 222.5,\n",
       "       225. , 227.5, 230. , 232.5, 235. , 237.5, 240. , 242.5, 245. , 247.5,\n",
       "       250. , 252.5, 255. , 257.5, 260. , 262.5, 265. , 267.5, 270. , 272.5,\n",
       "       275. , 277.5, 280. , 282.5, 285. , 287.5, 290. , 292.5, 295. , 297.5,\n",
       "       300. , 302.5, 305. , 307.5, 310. , 312.5, 315. , 317.5, 320. , 322.5,\n",
       "       325. , 327.5, 330. , 332.5, 335. , 337.5, 340. , 342.5, 345. , 347.5,\n",
       "       350. , 352.5, 355. , 357.5])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0b882ed2-4d7e-469a-81d6-f07039f3551d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0b882ed2-4d7e-469a-81d6-f07039f3551d' class='xr-section-summary' >Data variables: <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>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1981-06-01 00:00:00 ... 2005-10-...</div><input id='attrs-611fe22f-8722-45b5-b0f9-e059963ed243' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-611fe22f-8722-45b5-b0f9-e059963ed243' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5bca21da-093d-4252-ba3e-12dfb3a1bd23' class='xr-var-data-in' type='checkbox'><label for='data-5bca21da-093d-4252-ba3e-12dfb3a1bd23' title='Show/Hide data 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(1981, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1981, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1981, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1981, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1982, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1982, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1982, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1982, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1982, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1982, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1982, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1982, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1983, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1983, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1983, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1983, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1983, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1983, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1983, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1983, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1984, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1984, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1984, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1984, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1984, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1984, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1984, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1984, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1985, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1985, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1985, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1985, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1985, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1985, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1985, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1985, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1986, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1986, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1986, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1986, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1986, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1986, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1986, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1986, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1987, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1987, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1987, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1987, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1987, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1987, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1987, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1987, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1988, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1988, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1988, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1988, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1988, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1988, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1988, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1988, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1989, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1989, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1989, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1989, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1989, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1989, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1989, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1989, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1990, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1990, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1990, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1990, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1990, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1990, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1990, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1990, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1991, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1991, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1991, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1991, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1991, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1991, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1991, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1991, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1992, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1992, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1992, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1992, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1992, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1992, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1992, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1992, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1993, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1993, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1993, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1993, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1993, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1993, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1993, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1993, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1994, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1994, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1994, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1994, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1994, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1994, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1994, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1994, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1995, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1995, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1995, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1995, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1995, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1995, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1995, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1995, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1996, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1996, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1996, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1996, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1996, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1996, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1996, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1996, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1997, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1997, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1997, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1997, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1997, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1997, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1997, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1997, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 10, 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>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -89.05 -89.05 ... 89.05 90.0</div><input id='attrs-7f288e66-74ec-48a1-8acc-3ac11b9d1429' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7f288e66-74ec-48a1-8acc-3ac11b9d1429' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad403ad5-16f8-4a0a-a5a2-85359cd73475' class='xr-var-data-in' type='checkbox'><label for='data-ad403ad5-16f8-4a0a-a5a2-85359cd73475' title='Show/Hide data 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([[-90.      , -89.052632],\n",
       "       [-89.052632, -87.157895],\n",
       "       [-87.157895, -85.263158],\n",
       "       [-85.263158, -83.368421],\n",
       "       [-83.368421, -81.473684],\n",
       "       [-81.473684, -79.578947],\n",
       "       [-79.578947, -77.684211],\n",
       "       [-77.684211, -75.789474],\n",
       "       [-75.789474, -73.894737],\n",
       "       [-73.894737, -72.      ],\n",
       "       [-72.      , -70.105263],\n",
       "       [-70.105263, -68.210526],\n",
       "       [-68.210526, -66.315789],\n",
       "       [-66.315789, -64.421053],\n",
       "       [-64.421053, -62.526316],\n",
       "       [-62.526316, -60.631579],\n",
       "       [-60.631579, -58.736842],\n",
       "       [-58.736842, -56.842105],\n",
       "       [-56.842105, -54.947368],\n",
       "       [-54.947368, -53.052632],\n",
       "       [-53.052632, -51.157895],\n",
       "       [-51.157895, -49.263158],\n",
       "       [-49.263158, -47.368421],\n",
       "       [-47.368421, -45.473684],\n",
       "       [-45.473684, -43.578947],\n",
       "       [-43.578947, -41.684211],\n",
       "       [-41.684211, -39.789474],\n",
       "       [-39.789474, -37.894737],\n",
       "       [-37.894737, -36.      ],\n",
       "       [-36.      , -34.105263],\n",
       "       [-34.105263, -32.210526],\n",
       "       [-32.210526, -30.315789],\n",
       "       [-30.315789, -28.421053],\n",
       "       [-28.421053, -26.526316],\n",
       "       [-26.526316, -24.631579],\n",
       "       [-24.631579, -22.736842],\n",
       "       [-22.736842, -20.842105],\n",
       "       [-20.842105, -18.947368],\n",
       "       [-18.947368, -17.052632],\n",
       "       [-17.052632, -15.157895],\n",
       "       [-15.157895, -13.263158],\n",
       "       [-13.263158, -11.368421],\n",
       "       [-11.368421,  -9.473684],\n",
       "       [ -9.473684,  -7.578947],\n",
       "       [ -7.578947,  -5.684211],\n",
       "       [ -5.684211,  -3.789474],\n",
       "       [ -3.789474,  -1.894737],\n",
       "       [ -1.894737,   0.      ],\n",
       "       [  0.      ,   1.894737],\n",
       "       [  1.894737,   3.789474],\n",
       "       [  3.789474,   5.684211],\n",
       "       [  5.684211,   7.578947],\n",
       "       [  7.578947,   9.473684],\n",
       "       [  9.473684,  11.368421],\n",
       "       [ 11.368421,  13.263158],\n",
       "       [ 13.263158,  15.157895],\n",
       "       [ 15.157895,  17.052632],\n",
       "       [ 17.052632,  18.947368],\n",
       "       [ 18.947368,  20.842105],\n",
       "       [ 20.842105,  22.736842],\n",
       "       [ 22.736842,  24.631579],\n",
       "       [ 24.631579,  26.526316],\n",
       "       [ 26.526316,  28.421053],\n",
       "       [ 28.421053,  30.315789],\n",
       "       [ 30.315789,  32.210526],\n",
       "       [ 32.210526,  34.105263],\n",
       "       [ 34.105263,  36.      ],\n",
       "       [ 36.      ,  37.894737],\n",
       "       [ 37.894737,  39.789474],\n",
       "       [ 39.789474,  41.684211],\n",
       "       [ 41.684211,  43.578947],\n",
       "       [ 43.578947,  45.473684],\n",
       "       [ 45.473684,  47.368421],\n",
       "       [ 47.368421,  49.263158],\n",
       "       [ 49.263158,  51.157895],\n",
       "       [ 51.157895,  53.052632],\n",
       "       [ 53.052632,  54.947368],\n",
       "       [ 54.947368,  56.842105],\n",
       "       [ 56.842105,  58.736842],\n",
       "       [ 58.736842,  60.631579],\n",
       "       [ 60.631579,  62.526316],\n",
       "       [ 62.526316,  64.421053],\n",
       "       [ 64.421053,  66.315789],\n",
       "       [ 66.315789,  68.210526],\n",
       "       [ 68.210526,  70.105263],\n",
       "       [ 70.105263,  72.      ],\n",
       "       [ 72.      ,  73.894737],\n",
       "       [ 73.894737,  75.789474],\n",
       "       [ 75.789474,  77.684211],\n",
       "       [ 77.684211,  79.578947],\n",
       "       [ 79.578947,  81.473684],\n",
       "       [ 81.473684,  83.368421],\n",
       "       [ 83.368421,  85.263158],\n",
       "       [ 85.263158,  87.157895],\n",
       "       [ 87.157895,  89.052632],\n",
       "       [ 89.052632,  90.      ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.25 1.25 1.25 ... 356.2 358.8</div><input id='attrs-2a5d44eb-b51a-43de-b85d-a1f586a5920e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a5d44eb-b51a-43de-b85d-a1f586a5920e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6b1dc08-6de9-446b-9341-95f608ee3e30' class='xr-var-data-in' type='checkbox'><label for='data-d6b1dc08-6de9-446b-9341-95f608ee3e30' title='Show/Hide data 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([[ -1.25,   1.25],\n",
       "       [  1.25,   3.75],\n",
       "       [  3.75,   6.25],\n",
       "       ...,\n",
       "       [351.25, 353.75],\n",
       "       [353.75, 356.25],\n",
       "       [356.25, 358.75]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5c9cab2f-7cdc-4eb0-9a4c-48b786a4de75' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c9cab2f-7cdc-4eb0-9a4c-48b786a4de75' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa64625e-d5fd-4813-b6cf-06f898723d6b' class='xr-var-data-in' type='checkbox'><label for='data-aa64625e-d5fd-4813-b6cf-06f898723d6b' title='Show/Hide data 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>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>comment :</span></dt><dd>at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>original_name :</span></dt><dd>PRECT</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>history :</span></dt><dd>2011-06-01T05:45:35Z altered by CMOR: Converted type from &#x27;d&#x27; to &#x27;f&#x27;.</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_NorESM1-M_historical_r0i0p0.nc areacella: areacella_fx_NorESM1-M_historical_r0i0p0.nc</dd></dl></div><div class='xr-var-data'><pre>[1382400 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fd02dfca-94ad-42c2-b703-4ed45239a3a7' class='xr-section-summary-in' type='checkbox'  ><label for='section-fd02dfca-94ad-42c2-b703-4ed45239a3a7' class='xr-section-summary' >Attributes: <span>(26)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>institution :</span></dt><dd>Norwegian Climate Centre</dd><dt><span>institute_id :</span></dt><dd>NCC</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>source :</span></dt><dd>NorESM1-M 2011  atmosphere: CAM-Oslo (CAM4-Oslo-noresm-ver1_cmip5-r112, f19L26);  ocean: MICOM (MICOM-noresm-ver1_cmip5-r112, gx1v6L53);  sea ice: CICE (CICE4-noresm-ver1_cmip5-r112);  land: CLM (CLM4-noresm-ver1_cmip5-r112)</dd><dt><span>model_id :</span></dt><dd>NorESM1-M</dd><dt><span>forcing :</span></dt><dd>GHG, SA, Oz, Sl, Vl, BC, OC</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>255135.0</dd><dt><span>contact :</span></dt><dd>Please send any requests or bug reports to noresm-ncc@met.no.</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>5ccde64e-cfe8-47f6-9de8-9ea1621e7781</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>creation_date :</span></dt><dd>2011-06-01T05:45:35Z</dd><dt><span>history :</span></dt><dd>2011-06-01T05:45:35Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (27 April 2011) a5a1c518f52ae340313ba0aada03f862</dd><dt><span>title :</span></dt><dd>NorESM1-M model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>1</dd><dt><span>cmor_version :</span></dt><dd>2.6.0</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (time: 100, bnds: 2, lat: 96, lon: 144)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-06-16 ... 2005-09-16\n",
       "  * lat        (lat) float64 -90.0 -88.11 -86.21 -84.32 ... 86.21 88.11 90.0\n",
       "  * lon        (lon) float64 0.0 2.5 5.0 7.5 10.0 ... 350.0 352.5 355.0 357.5\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1981-06-01 00:00:00 ... 2005-10-01 00:00:00\n",
       "    lat_bnds   (lat, bnds) float64 -90.0 -89.05 -89.05 ... 89.05 89.05 90.0\n",
       "    lon_bnds   (lon, bnds) float64 -1.25 1.25 1.25 3.75 ... 356.2 356.2 358.8\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/26)\n",
       "    institution:            Norwegian Climate Centre\n",
       "    institute_id:           NCC\n",
       "    experiment_id:          historical\n",
       "    source:                 NorESM1-M 2011  atmosphere: CAM-Oslo (CAM4-Oslo-n...\n",
       "    model_id:               NorESM1-M\n",
       "    forcing:                GHG, SA, Oz, Sl, Vl, BC, OC\n",
       "    ...                     ...\n",
       "    table_id:               Table Amon (27 April 2011) a5a1c518f52ae340313ba0...\n",
       "    title:                  NorESM1-M model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.6.0"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#selecting only JJAS months\n",
    "\n",
    "def is_jjas(month):\n",
    "    return (month >= 6) & (month <= 9)\n",
    "\n",
    "jjas_data = data.sel(time=is_jjas(data['time.month']))\n",
    "\n",
    "jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "be94f5d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#jjas_data.x.values\n",
    "#jjas_data.y.values\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a41e4a60",
   "metadata": {},
   "outputs": [],
   "source": [
    "#to select the x and y coordinates\n",
    "#jjas_data = jjas_data.sel(x=slice(1000000.,5275000.),y=slice(2000000.,4175000.))\n",
    "#jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c29a2e8d",
   "metadata": {},
   "outputs": [
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       ".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: 100, bnds: 2, lat: 40, lon: 32)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-06-16 ... 2005-09-16\n",
       "  * lon        (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat        (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1981-06-01 00:00:00 ... 2005-10-01 00:00:00\n",
       "    lat_bnds   (lat, bnds) float64 17.18 19.07 17.43 19.32 ... 28.57 26.93 28.82\n",
       "    lon_bnds   (lon, bnds) float64 84.88 87.38 85.12 87.62 ... 94.88 92.62 95.12\n",
       "    pr         (time, lat, lon) float64 3.491e-05 3.505e-05 ... 0.0002537\n",
       "Attributes: (12/26)\n",
       "    institution:            Norwegian Climate Centre\n",
       "    institute_id:           NCC\n",
       "    experiment_id:          historical\n",
       "    source:                 NorESM1-M 2011  atmosphere: CAM-Oslo (CAM4-Oslo-n...\n",
       "    model_id:               NorESM1-M\n",
       "    forcing:                GHG, SA, Oz, Sl, Vl, BC, OC\n",
       "    ...                     ...\n",
       "    table_id:               Table Amon (27 April 2011) a5a1c518f52ae340313ba0...\n",
       "    title:                  NorESM1-M model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.6.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-49cf4e56-92b3-4a2c-93d0-4706c201dbca' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-49cf4e56-92b3-4a2c-93d0-4706c201dbca' 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>: 100</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 40</li><li><span class='xr-has-index'>lon</span>: 32</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-13bdb63c-7e73-41d0-8034-2997f4928b91' class='xr-section-summary-in' type='checkbox'  checked><label for='section-13bdb63c-7e73-41d0-8034-2997f4928b91' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-06-16 ... 2005-09-16</div><input id='attrs-9c9978ef-71fd-4f0c-8664-513af812cedf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9c9978ef-71fd-4f0c-8664-513af812cedf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c694053-d7d6-4ee4-a081-304445d8816e' class='xr-var-data-in' type='checkbox'><label for='data-4c694053-d7d6-4ee4-a081-304445d8816e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-06-16T00:00:00.000000000&#x27;, &#x27;1981-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1981-08-16T12:00:00.000000000&#x27;, &#x27;1981-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-06-16T00:00:00.000000000&#x27;, &#x27;1982-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1982-08-16T12:00:00.000000000&#x27;, &#x27;1982-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-06-16T00:00:00.000000000&#x27;, &#x27;1983-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1983-08-16T12:00:00.000000000&#x27;, &#x27;1983-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-06-16T00:00:00.000000000&#x27;, &#x27;1984-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1984-08-16T12:00:00.000000000&#x27;, &#x27;1984-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-06-16T00:00:00.000000000&#x27;, &#x27;1985-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1985-08-16T12:00:00.000000000&#x27;, &#x27;1985-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-06-16T00:00:00.000000000&#x27;, &#x27;1986-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1986-08-16T12:00:00.000000000&#x27;, &#x27;1986-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-06-16T00:00:00.000000000&#x27;, &#x27;1987-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1987-08-16T12:00:00.000000000&#x27;, &#x27;1987-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-06-16T00:00:00.000000000&#x27;, &#x27;1988-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1988-08-16T12:00:00.000000000&#x27;, &#x27;1988-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-06-16T00:00:00.000000000&#x27;, &#x27;1989-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1989-08-16T12:00:00.000000000&#x27;, &#x27;1989-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-06-16T00:00:00.000000000&#x27;, &#x27;1990-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1990-08-16T12:00:00.000000000&#x27;, &#x27;1990-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-06-16T00:00:00.000000000&#x27;, &#x27;1991-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1991-08-16T12:00:00.000000000&#x27;, &#x27;1991-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-06-16T00:00:00.000000000&#x27;, &#x27;1992-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1992-08-16T12:00:00.000000000&#x27;, &#x27;1992-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-06-16T00:00:00.000000000&#x27;, &#x27;1993-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1993-08-16T12:00:00.000000000&#x27;, &#x27;1993-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-06-16T00:00:00.000000000&#x27;, &#x27;1994-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1994-08-16T12:00:00.000000000&#x27;, &#x27;1994-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-06-16T00:00:00.000000000&#x27;, &#x27;1995-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1995-08-16T12:00:00.000000000&#x27;, &#x27;1995-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-06-16T00:00:00.000000000&#x27;, &#x27;1996-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1996-08-16T12:00:00.000000000&#x27;, &#x27;1996-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-06-16T00:00:00.000000000&#x27;, &#x27;1997-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1997-08-16T12:00:00.000000000&#x27;, &#x27;1997-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-06-16T00:00:00.000000000&#x27;, &#x27;1998-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1998-08-16T12:00:00.000000000&#x27;, &#x27;1998-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-06-16T00:00:00.000000000&#x27;, &#x27;1999-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1999-08-16T12:00:00.000000000&#x27;, &#x27;1999-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-16T00:00:00.000000000&#x27;, &#x27;2000-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2000-08-16T12:00:00.000000000&#x27;, &#x27;2000-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-06-16T00:00:00.000000000&#x27;, &#x27;2001-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2001-08-16T12:00:00.000000000&#x27;, &#x27;2001-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-16T00:00:00.000000000&#x27;, &#x27;2002-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-16T12:00:00.000000000&#x27;, &#x27;2002-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-16T00:00:00.000000000&#x27;, &#x27;2003-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-16T12:00:00.000000000&#x27;, &#x27;2003-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-16T00:00:00.000000000&#x27;, &#x27;2004-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-16T12:00:00.000000000&#x27;, &#x27;2004-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-16T00:00:00.000000000&#x27;, &#x27;2005-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2005-08-16T12:00:00.000000000&#x27;, &#x27;2005-09-16T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-144f11a7-faed-4c12-a4c6-665b0d4a4f30' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-144f11a7-faed-4c12-a4c6-665b0d4a4f30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-341de265-c43d-4732-b652-13efeff4b164' class='xr-var-data-in' type='checkbox'><label for='data-341de265-c43d-4732-b652-13efeff4b164' title='Show/Hide data 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875])</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'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-a504a55f-b679-48e2-a258-d4e16c767325' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a504a55f-b679-48e2-a258-d4e16c767325' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15282a61-b2f4-45ae-9806-9903cf23ba8b' class='xr-var-data-in' type='checkbox'><label for='data-15282a61-b2f4-45ae-9806-9903cf23ba8b' title='Show/Hide data 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f6972f8a-9540-4449-a004-e1744dd2bac8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f6972f8a-9540-4449-a004-e1744dd2bac8' class='xr-section-summary' >Data variables: <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>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1981-06-01 00:00:00 ... 2005-10-...</div><input id='attrs-58ba8e90-745c-457d-93bf-8e3f1ffe2175' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-58ba8e90-745c-457d-93bf-8e3f1ffe2175' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c0d1ff5-6de4-4851-8a8c-97316f1039e8' class='xr-var-data-in' type='checkbox'><label for='data-9c0d1ff5-6de4-4851-8a8c-97316f1039e8' title='Show/Hide data 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(1981, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1981, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1981, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1981, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1982, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1982, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1982, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1982, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1982, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1982, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1982, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1982, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1983, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1983, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1983, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1983, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1983, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1983, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1983, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1983, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1984, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1984, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1984, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1984, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1984, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1984, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1984, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1984, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1985, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1985, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1985, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1985, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1985, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1985, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1985, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1985, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1986, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1986, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1986, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1986, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1986, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1986, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1986, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1986, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1987, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1987, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1987, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1987, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1987, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1987, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1987, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1987, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1988, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1988, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1988, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1988, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1988, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1988, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1988, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1988, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1989, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1989, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1989, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1989, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1989, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1989, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1989, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1989, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1990, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1990, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1990, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1990, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1990, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1990, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1990, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1990, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1991, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1991, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1991, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1991, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1991, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1991, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1991, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1991, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1992, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1992, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1992, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1992, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1992, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1992, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1992, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1992, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1993, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1993, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1993, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1993, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1993, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1993, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1993, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1993, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1994, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1994, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1994, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1994, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1994, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1994, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1994, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1994, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1995, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1995, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1995, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1995, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1995, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1995, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1995, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1995, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1996, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1996, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1996, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1996, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1996, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1996, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1996, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1996, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1997, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1997, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1997, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1997, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1997, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1997, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1997, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1997, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 10, 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>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>17.18 19.07 17.43 ... 26.93 28.82</div><input id='attrs-5014e0a0-f354-4f86-8f13-afb7e8968709' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5014e0a0-f354-4f86-8f13-afb7e8968709' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93b00cf7-a843-4c68-9c94-673ef2e50cec' class='xr-var-data-in' type='checkbox'><label for='data-93b00cf7-a843-4c68-9c94-673ef2e50cec' title='Show/Hide data 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([[17.17763158, 19.07236842],\n",
       "       [17.42763158, 19.32236842],\n",
       "       [17.67763158, 19.57236842],\n",
       "       [17.92763158, 19.82236842],\n",
       "       [18.17763158, 20.07236842],\n",
       "       [18.42763158, 20.32236842],\n",
       "       [18.67763158, 20.57236842],\n",
       "       [18.92763158, 20.82236842],\n",
       "       [19.17763158, 21.07236842],\n",
       "       [19.42763158, 21.32236842],\n",
       "       [19.67763158, 21.57236842],\n",
       "       [19.92763158, 21.82236842],\n",
       "       [20.17763158, 22.07236842],\n",
       "       [20.42763158, 22.32236842],\n",
       "       [20.67763158, 22.57236842],\n",
       "       [20.92763158, 22.82236842],\n",
       "       [21.17763158, 23.07236842],\n",
       "       [21.42763158, 23.32236842],\n",
       "       [21.67763158, 23.57236842],\n",
       "       [21.92763158, 23.82236842],\n",
       "       [22.17763158, 24.07236842],\n",
       "       [22.42763158, 24.32236842],\n",
       "       [22.67763158, 24.57236842],\n",
       "       [22.92763158, 24.82236842],\n",
       "       [23.17763158, 25.07236842],\n",
       "       [23.42763158, 25.32236842],\n",
       "       [23.67763158, 25.57236842],\n",
       "       [23.92763158, 25.82236842],\n",
       "       [24.17763158, 26.07236842],\n",
       "       [24.42763158, 26.32236842],\n",
       "       [24.67763158, 26.57236842],\n",
       "       [24.92763158, 26.82236842],\n",
       "       [25.17763158, 27.07236842],\n",
       "       [25.42763158, 27.32236842],\n",
       "       [25.67763158, 27.57236842],\n",
       "       [25.92763158, 27.82236842],\n",
       "       [26.17763158, 28.07236842],\n",
       "       [26.42763158, 28.32236842],\n",
       "       [26.67763158, 28.57236842],\n",
       "       [26.92763158, 28.82236842]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>84.88 87.38 85.12 ... 92.62 95.12</div><input id='attrs-d1d79237-74ca-475a-9e2d-baf14c1ab8b7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d1d79237-74ca-475a-9e2d-baf14c1ab8b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e1bac2d-0d68-4071-917f-a80d5f5145d6' class='xr-var-data-in' type='checkbox'><label for='data-1e1bac2d-0d68-4071-917f-a80d5f5145d6' title='Show/Hide data 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([[84.875, 87.375],\n",
       "       [85.125, 87.625],\n",
       "       [85.375, 87.875],\n",
       "       [85.625, 88.125],\n",
       "       [85.875, 88.375],\n",
       "       [86.125, 88.625],\n",
       "       [86.375, 88.875],\n",
       "       [86.625, 89.125],\n",
       "       [86.875, 89.375],\n",
       "       [87.125, 89.625],\n",
       "       [87.375, 89.875],\n",
       "       [87.625, 90.125],\n",
       "       [87.875, 90.375],\n",
       "       [88.125, 90.625],\n",
       "       [88.375, 90.875],\n",
       "       [88.625, 91.125],\n",
       "       [88.875, 91.375],\n",
       "       [89.125, 91.625],\n",
       "       [89.375, 91.875],\n",
       "       [89.625, 92.125],\n",
       "       [89.875, 92.375],\n",
       "       [90.125, 92.625],\n",
       "       [90.375, 92.875],\n",
       "       [90.625, 93.125],\n",
       "       [90.875, 93.375],\n",
       "       [91.125, 93.625],\n",
       "       [91.375, 93.875],\n",
       "       [91.625, 94.125],\n",
       "       [91.875, 94.375],\n",
       "       [92.125, 94.625],\n",
       "       [92.375, 94.875],\n",
       "       [92.625, 95.125]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.491e-05 3.505e-05 ... 0.0002537</div><input id='attrs-1ce6c30c-97f7-4cad-9f98-27c7ba10941a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ce6c30c-97f7-4cad-9f98-27c7ba10941a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23a0e419-3d20-48ee-8bd3-decf0d53564e' class='xr-var-data-in' type='checkbox'><label for='data-23a0e419-3d20-48ee-8bd3-decf0d53564e' title='Show/Hide data 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>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>comment :</span></dt><dd>at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>original_name :</span></dt><dd>PRECT</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>history :</span></dt><dd>2011-06-01T05:45:35Z altered by CMOR: Converted type from &#x27;d&#x27; to &#x27;f&#x27;.</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_NorESM1-M_historical_r0i0p0.nc areacella: areacella_fx_NorESM1-M_historical_r0i0p0.nc</dd></dl></div><div class='xr-var-data'><pre>array([[[3.49083811e-05, 3.50546581e-05, 3.52009351e-05, ...,\n",
       "         7.13186514e-05, 7.32828077e-05, 7.52469641e-05],\n",
       "        [3.44021599e-05, 3.42062763e-05, 3.40103927e-05, ...,\n",
       "         6.99883540e-05, 7.18436721e-05, 7.36989902e-05],\n",
       "        [3.38959386e-05, 3.33578944e-05, 3.28198503e-05, ...,\n",
       "         6.86580566e-05, 7.04045365e-05, 7.21510163e-05],\n",
       "        ...,\n",
       "        [1.33521770e-04, 1.49854976e-04, 1.66188183e-04, ...,\n",
       "         4.06835444e-04, 3.95939930e-04, 3.85044415e-04],\n",
       "        [1.27053219e-04, 1.42613915e-04, 1.58174611e-04, ...,\n",
       "         4.09547270e-04, 4.00017267e-04, 3.90487264e-04],\n",
       "        [1.10019575e-04, 1.23390081e-04, 1.36760588e-04, ...,\n",
       "         3.83880952e-04, 3.77391794e-04, 3.70902636e-04]],\n",
       "\n",
       "       [[7.74577177e-05, 7.61072079e-05, 7.47566982e-05, ...,\n",
       "         7.85440948e-05, 8.10507727e-05, 8.35574505e-05],\n",
       "        [8.13647833e-05, 7.99300566e-05, 7.84953299e-05, ...,\n",
       "         7.71085891e-05, 7.93373657e-05, 8.15661424e-05],\n",
       "        [8.52718490e-05, 8.37529053e-05, 8.22339615e-05, ...,\n",
       "         7.56730833e-05, 7.76239588e-05, 7.95748343e-05],\n",
       "...\n",
       "        [2.69043223e-04, 2.72685242e-04, 2.76327261e-04, ...,\n",
       "         1.96206189e-04, 1.93690550e-04, 1.91174912e-04],\n",
       "        [2.67839606e-04, 2.70993474e-04, 2.74147343e-04, ...,\n",
       "         1.91606173e-04, 1.89351753e-04, 1.87097333e-04],\n",
       "        [2.46551213e-04, 2.48758132e-04, 2.50965051e-04, ...,\n",
       "         1.77588598e-04, 1.76165773e-04, 1.74742947e-04]],\n",
       "\n",
       "       [[9.95136971e-05, 9.58591888e-05, 9.22046806e-05, ...,\n",
       "         7.98599096e-05, 7.85213339e-05, 7.71827582e-05],\n",
       "        [1.03062438e-04, 9.95713000e-05, 9.60801619e-05, ...,\n",
       "         7.82825919e-05, 7.74345970e-05, 7.65866022e-05],\n",
       "        [1.06611179e-04, 1.03283411e-04, 9.99556433e-05, ...,\n",
       "         7.67052741e-05, 7.63478601e-05, 7.59904461e-05],\n",
       "        ...,\n",
       "        [2.54023582e-04, 2.67076671e-04, 2.80129760e-04, ...,\n",
       "         2.72289805e-04, 2.61498958e-04, 2.50708112e-04],\n",
       "        [2.48119164e-04, 2.60543673e-04, 2.72968181e-04, ...,\n",
       "         2.76913591e-04, 2.67486860e-04, 2.58060129e-04],\n",
       "        [2.22837218e-04, 2.33280702e-04, 2.43724187e-04, ...,\n",
       "         2.66372393e-04, 2.60049241e-04, 2.53726088e-04]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1d92558f-2f9a-4379-ad1a-9063f6e0b334' class='xr-section-summary-in' type='checkbox'  ><label for='section-1d92558f-2f9a-4379-ad1a-9063f6e0b334' class='xr-section-summary' >Attributes: <span>(26)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>institution :</span></dt><dd>Norwegian Climate Centre</dd><dt><span>institute_id :</span></dt><dd>NCC</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>source :</span></dt><dd>NorESM1-M 2011  atmosphere: CAM-Oslo (CAM4-Oslo-noresm-ver1_cmip5-r112, f19L26);  ocean: MICOM (MICOM-noresm-ver1_cmip5-r112, gx1v6L53);  sea ice: CICE (CICE4-noresm-ver1_cmip5-r112);  land: CLM (CLM4-noresm-ver1_cmip5-r112)</dd><dt><span>model_id :</span></dt><dd>NorESM1-M</dd><dt><span>forcing :</span></dt><dd>GHG, SA, Oz, Sl, Vl, BC, OC</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>255135.0</dd><dt><span>contact :</span></dt><dd>Please send any requests or bug reports to noresm-ncc@met.no.</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>5ccde64e-cfe8-47f6-9de8-9ea1621e7781</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>creation_date :</span></dt><dd>2011-06-01T05:45:35Z</dd><dt><span>history :</span></dt><dd>2011-06-01T05:45:35Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (27 April 2011) a5a1c518f52ae340313ba0aada03f862</dd><dt><span>title :</span></dt><dd>NorESM1-M model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>1</dd><dt><span>cmor_version :</span></dt><dd>2.6.0</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (time: 100, bnds: 2, lat: 40, lon: 32)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-06-16 ... 2005-09-16\n",
       "  * lon        (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat        (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1981-06-01 00:00:00 ... 2005-10-01 00:00:00\n",
       "    lat_bnds   (lat, bnds) float64 17.18 19.07 17.43 19.32 ... 28.57 26.93 28.82\n",
       "    lon_bnds   (lon, bnds) float64 84.88 87.38 85.12 87.62 ... 94.88 92.62 95.12\n",
       "    pr         (time, lat, lon) float64 3.491e-05 3.505e-05 ... 0.0002537\n",
       "Attributes: (12/26)\n",
       "    institution:            Norwegian Climate Centre\n",
       "    institute_id:           NCC\n",
       "    experiment_id:          historical\n",
       "    source:                 NorESM1-M 2011  atmosphere: CAM-Oslo (CAM4-Oslo-n...\n",
       "    model_id:               NorESM1-M\n",
       "    forcing:                GHG, SA, Oz, Sl, Vl, BC, OC\n",
       "    ...                     ...\n",
       "    table_id:               Table Amon (27 April 2011) a5a1c518f52ae340313ba0...\n",
       "    title:                  NorESM1-M model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.6.0"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#interpolating to low resolution \n",
    "new_lon=np.arange(86.125,94,0.25)\n",
    "new_lat=np.arange(18.125,28,.25)\n",
    "jjas_data = jjas_data.interp(lon=new_lon,lat=new_lat)\n",
    "jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "18269e45",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (lat: 40, lon: 32)&gt;\n",
       "array([[8.97452270e-05, 8.96268200e-05, 8.95084131e-05, ...,\n",
       "        1.07405456e-04, 1.08312868e-04, 1.09220280e-04],\n",
       "       [8.95236311e-05, 8.93062718e-05, 8.90889126e-05, ...,\n",
       "        1.05679837e-04, 1.06574834e-04, 1.07469831e-04],\n",
       "       [8.93020352e-05, 8.89857237e-05, 8.86694121e-05, ...,\n",
       "        1.03954218e-04, 1.04836800e-04, 1.05719382e-04],\n",
       "       ...,\n",
       "       [2.94812165e-04, 3.03439261e-04, 3.12066357e-04, ...,\n",
       "        2.58191676e-04, 2.51077785e-04, 2.43963895e-04],\n",
       "       [2.90319263e-04, 2.98435461e-04, 3.06551658e-04, ...,\n",
       "        2.58808011e-04, 2.52330325e-04, 2.45852639e-04],\n",
       "       [2.63478575e-04, 2.70211792e-04, 2.76945008e-04, ...,\n",
       "        2.44615097e-04, 2.39728170e-04, 2.34841243e-04]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'pr'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 40</li><li><span class='xr-has-index'>lon</span>: 32</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-d5d4a402-7b18-44f6-b5c5-50429fd6be37' class='xr-array-in' type='checkbox' checked><label for='section-d5d4a402-7b18-44f6-b5c5-50429fd6be37' 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>8.975e-05 8.963e-05 8.951e-05 ... 0.0002446 0.0002397 0.0002348</span></div><div class='xr-array-data'><pre>array([[8.97452270e-05, 8.96268200e-05, 8.95084131e-05, ...,\n",
       "        1.07405456e-04, 1.08312868e-04, 1.09220280e-04],\n",
       "       [8.95236311e-05, 8.93062718e-05, 8.90889126e-05, ...,\n",
       "        1.05679837e-04, 1.06574834e-04, 1.07469831e-04],\n",
       "       [8.93020352e-05, 8.89857237e-05, 8.86694121e-05, ...,\n",
       "        1.03954218e-04, 1.04836800e-04, 1.05719382e-04],\n",
       "       ...,\n",
       "       [2.94812165e-04, 3.03439261e-04, 3.12066357e-04, ...,\n",
       "        2.58191676e-04, 2.51077785e-04, 2.43963895e-04],\n",
       "       [2.90319263e-04, 2.98435461e-04, 3.06551658e-04, ...,\n",
       "        2.58808011e-04, 2.52330325e-04, 2.45852639e-04],\n",
       "       [2.63478575e-04, 2.70211792e-04, 2.76945008e-04, ...,\n",
       "        2.44615097e-04, 2.39728170e-04, 2.34841243e-04]])</pre></div></div></li><li class='xr-section-item'><input id='section-e0bd94a7-ae2d-43f7-8697-dd0942fdd7ce' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e0bd94a7-ae2d-43f7-8697-dd0942fdd7ce' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span 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'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-ccdc17ee-23e2-4cf0-8a40-94558b0dc705' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ccdc17ee-23e2-4cf0-8a40-94558b0dc705' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64ef9c72-dc92-495d-ba98-7f4f16113989' class='xr-var-data-in' type='checkbox'><label for='data-64ef9c72-dc92-495d-ba98-7f4f16113989' title='Show/Hide data 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875])</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'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-f298a418-5c49-43bb-8443-2bef937d54e0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f298a418-5c49-43bb-8443-2bef937d54e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9f63aef-3463-4192-964b-f52876c15be6' class='xr-var-data-in' type='checkbox'><label for='data-d9f63aef-3463-4192-964b-f52876c15be6' title='Show/Hide data 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e416af50-1887-4091-b37a-8c08ab334705' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e416af50-1887-4091-b37a-8c08ab334705' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'pr' (lat: 40, lon: 32)>\n",
       "array([[8.97452270e-05, 8.96268200e-05, 8.95084131e-05, ...,\n",
       "        1.07405456e-04, 1.08312868e-04, 1.09220280e-04],\n",
       "       [8.95236311e-05, 8.93062718e-05, 8.90889126e-05, ...,\n",
       "        1.05679837e-04, 1.06574834e-04, 1.07469831e-04],\n",
       "       [8.93020352e-05, 8.89857237e-05, 8.86694121e-05, ...,\n",
       "        1.03954218e-04, 1.04836800e-04, 1.05719382e-04],\n",
       "       ...,\n",
       "       [2.94812165e-04, 3.03439261e-04, 3.12066357e-04, ...,\n",
       "        2.58191676e-04, 2.51077785e-04, 2.43963895e-04],\n",
       "       [2.90319263e-04, 2.98435461e-04, 3.06551658e-04, ...,\n",
       "        2.58808011e-04, 2.52330325e-04, 2.45852639e-04],\n",
       "       [2.63478575e-04, 2.70211792e-04, 2.76945008e-04, ...,\n",
       "        2.44615097e-04, 2.39728170e-04, 2.34841243e-04]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#getting the mean for JJAS data\n",
    "jjas_mean = jjas_data.pr.mean('time')\n",
    " \n",
    "jjas_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "6f88bd72",
   "metadata": {},
   "outputs": [
    {
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       "  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",
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       "\n",
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       "  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",
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       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
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       "\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",
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       "\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",
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       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
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       "\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;pr&#x27; (lat: 40, lon: 32)&gt;\n",
       "array([[ 7.75398762,  7.74375725,  7.73352689, ...,  9.27983139,\n",
       "         9.3582318 ,  9.4366322 ],\n",
       "       [ 7.73484173,  7.71606189,  7.69728205, ...,  9.13073791,\n",
       "         9.20806565,  9.28539338],\n",
       "       [ 7.71569584,  7.68836652,  7.66103721, ...,  8.98164443,\n",
       "         9.05789949,  9.13415456],\n",
       "       ...,\n",
       "       [25.4717711 , 26.21715217, 26.96253324, ..., 22.30776077,\n",
       "        21.69312063, 21.07848049],\n",
       "       [25.08358434, 25.78482379, 26.48606324, ..., 22.36101219,\n",
       "        21.8013401 , 21.24166801],\n",
       "       [22.76454887, 23.34629879, 23.9280487 , ..., 21.13474442,\n",
       "        20.7125139 , 20.29028338]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'pr'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 40</li><li><span class='xr-has-index'>lon</span>: 32</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-481fdf21-a93f-40d0-a104-c911c95af96a' class='xr-array-in' type='checkbox' checked><label for='section-481fdf21-a93f-40d0-a104-c911c95af96a' 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>7.754 7.744 7.734 7.723 7.713 7.703 ... 21.98 21.56 21.13 20.71 20.29</span></div><div class='xr-array-data'><pre>array([[ 7.75398762,  7.74375725,  7.73352689, ...,  9.27983139,\n",
       "         9.3582318 ,  9.4366322 ],\n",
       "       [ 7.73484173,  7.71606189,  7.69728205, ...,  9.13073791,\n",
       "         9.20806565,  9.28539338],\n",
       "       [ 7.71569584,  7.68836652,  7.66103721, ...,  8.98164443,\n",
       "         9.05789949,  9.13415456],\n",
       "       ...,\n",
       "       [25.4717711 , 26.21715217, 26.96253324, ..., 22.30776077,\n",
       "        21.69312063, 21.07848049],\n",
       "       [25.08358434, 25.78482379, 26.48606324, ..., 22.36101219,\n",
       "        21.8013401 , 21.24166801],\n",
       "       [22.76454887, 23.34629879, 23.9280487 , ..., 21.13474442,\n",
       "        20.7125139 , 20.29028338]])</pre></div></div></li><li class='xr-section-item'><input id='section-a5718b5e-2b32-4eda-a2e9-64ee854b6e36' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a5718b5e-2b32-4eda-a2e9-64ee854b6e36' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span 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'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-aef257b8-bf0a-451e-a2d9-f9cbf0857bbe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aef257b8-bf0a-451e-a2d9-f9cbf0857bbe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db420972-a7d9-4447-94e7-3587d328badc' class='xr-var-data-in' type='checkbox'><label for='data-db420972-a7d9-4447-94e7-3587d328badc' title='Show/Hide data 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875])</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'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-af15d714-ae1d-47bb-a4da-7166b22927e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af15d714-ae1d-47bb-a4da-7166b22927e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d9bcddb-5539-41b8-b230-8b487a1da20d' class='xr-var-data-in' type='checkbox'><label for='data-1d9bcddb-5539-41b8-b230-8b487a1da20d' title='Show/Hide data 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a8c7ce08-8943-44da-b33c-bd96e93c6d1e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a8c7ce08-8943-44da-b33c-bd96e93c6d1e' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'pr' (lat: 40, lon: 32)>\n",
       "array([[ 7.75398762,  7.74375725,  7.73352689, ...,  9.27983139,\n",
       "         9.3582318 ,  9.4366322 ],\n",
       "       [ 7.73484173,  7.71606189,  7.69728205, ...,  9.13073791,\n",
       "         9.20806565,  9.28539338],\n",
       "       [ 7.71569584,  7.68836652,  7.66103721, ...,  8.98164443,\n",
       "         9.05789949,  9.13415456],\n",
       "       ...,\n",
       "       [25.4717711 , 26.21715217, 26.96253324, ..., 22.30776077,\n",
       "        21.69312063, 21.07848049],\n",
       "       [25.08358434, 25.78482379, 26.48606324, ..., 22.36101219,\n",
       "        21.8013401 , 21.24166801],\n",
       "       [22.76454887, 23.34629879, 23.9280487 , ..., 21.13474442,\n",
       "        20.7125139 , 20.29028338]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "noresm = jjas_mean*86400\n",
    "noresm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6c5c5811",
   "metadata": {},
   "outputs": [
    {
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       "  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",
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       "\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",
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       "\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",
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       "\n",
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       "\n",
       ".xr-var-dims {\n",
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       "}\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",
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       "\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 (lat: 40, lon: 32)&gt;\n",
       "array([[        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       ...,\n",
       "       [17.28621469, 17.16776615, 15.8224671 , ..., 15.59973055,\n",
       "        12.70754496,  7.99056793],\n",
       "       [14.79210809, 15.75769652, 15.28064943, ..., 17.12757846,\n",
       "        13.71374702, 11.81169727],\n",
       "       [12.89041576, 14.34516964, 16.30780277, ..., 13.88832975,\n",
       "        12.43480394, 10.93109435]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 40</li><li><span class='xr-has-index'>lon</span>: 32</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-54638fe5-571e-4123-a373-f271b631c134' class='xr-array-in' type='checkbox' checked><label for='section-54638fe5-571e-4123-a373-f271b631c134' 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>nan nan nan nan nan nan nan ... 19.96 18.57 16.58 13.89 12.43 10.93</span></div><div class='xr-array-data'><pre>array([[        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       ...,\n",
       "       [17.28621469, 17.16776615, 15.8224671 , ..., 15.59973055,\n",
       "        12.70754496,  7.99056793],\n",
       "       [14.79210809, 15.75769652, 15.28064943, ..., 17.12757846,\n",
       "        13.71374702, 11.81169727],\n",
       "       [12.89041576, 14.34516964, 16.30780277, ..., 13.88832975,\n",
       "        12.43480394, 10.93109435]])</pre></div></div></li><li class='xr-section-item'><input id='section-df787190-0bb7-48e7-8be4-898d72f389e3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-df787190-0bb7-48e7-8be4-898d72f389e3' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span 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'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-bf435eb3-dea6-4618-a0f2-25961fee16ee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf435eb3-dea6-4618-a0f2-25961fee16ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e68fdce-f277-4a46-a764-0b17eadc8d40' class='xr-var-data-in' type='checkbox'><label for='data-6e68fdce-f277-4a46-a764-0b17eadc8d40' title='Show/Hide data 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875])</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'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-390dc4ca-08bf-417e-8f66-70614a708501' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-390dc4ca-08bf-417e-8f66-70614a708501' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e577fbc1-a27b-4b03-9033-0e61a4ee0e1e' class='xr-var-data-in' type='checkbox'><label for='data-e577fbc1-a27b-4b03-9033-0e61a4ee0e1e' title='Show/Hide data 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fd1b141b-143a-4f33-a825-e488c2a3c748' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-fd1b141b-143a-4f33-a825-e488c2a3c748' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (lat: 40, lon: 32)>\n",
       "array([[        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       ...,\n",
       "       [17.28621469, 17.16776615, 15.8224671 , ..., 15.59973055,\n",
       "        12.70754496,  7.99056793],\n",
       "       [14.79210809, 15.75769652, 15.28064943, ..., 17.12757846,\n",
       "        13.71374702, 11.81169727],\n",
       "       [12.89041576, 14.34516964, 16.30780277, ..., 13.88832975,\n",
       "        12.43480394, 10.93109435]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bias = noresm - chirps\n",
    "bias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "445388ed",
   "metadata": {},
   "outputs": [
    {
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       ".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.DataArray (lat: 40, lon: 32)&gt;\n",
       "array([[         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       ...,\n",
       "       [211.17947047, 189.711944  , 142.03207494, ..., 232.55307489,\n",
       "        141.42160073,  61.05303571],\n",
       "       [143.73164478, 157.15065847, 136.36845255, ..., 327.27229134,\n",
       "        169.56524501, 125.25698745],\n",
       "       [130.54731608, 159.37077891, 214.00625273, ..., 191.65794954,\n",
       "        150.2203387 , 116.79531541]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 40</li><li><span class='xr-has-index'>lon</span>: 32</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-3d3f5f4e-a3c4-4bed-b237-a22dde6f4850' class='xr-array-in' type='checkbox' checked><label for='section-3d3f5f4e-a3c4-4bed-b237-a22dde6f4850' 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>nan nan nan nan nan nan nan ... 817.0 544.8 332.9 191.7 150.2 116.8</span></div><div class='xr-array-data'><pre>array([[         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       ...,\n",
       "       [211.17947047, 189.711944  , 142.03207494, ..., 232.55307489,\n",
       "        141.42160073,  61.05303571],\n",
       "       [143.73164478, 157.15065847, 136.36845255, ..., 327.27229134,\n",
       "        169.56524501, 125.25698745],\n",
       "       [130.54731608, 159.37077891, 214.00625273, ..., 191.65794954,\n",
       "        150.2203387 , 116.79531541]])</pre></div></div></li><li class='xr-section-item'><input id='section-231cd1e3-d664-49b7-970b-4dfb05d80ee6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-231cd1e3-d664-49b7-970b-4dfb05d80ee6' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span 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'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-8461522c-3d45-4c10-8309-da6e0892ee54' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8461522c-3d45-4c10-8309-da6e0892ee54' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0dc91e6-fa01-4ca3-8b90-59eaf96e2089' class='xr-var-data-in' type='checkbox'><label for='data-b0dc91e6-fa01-4ca3-8b90-59eaf96e2089' title='Show/Hide data 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875])</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'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-153005e6-397d-4fe3-a81c-21741cdb01f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-153005e6-397d-4fe3-a81c-21741cdb01f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a83081f-0abe-40d3-8eca-713c9009a985' class='xr-var-data-in' type='checkbox'><label for='data-1a83081f-0abe-40d3-8eca-713c9009a985' title='Show/Hide data 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-aef8d80a-1a43-4f9f-80e2-1fa90d390fa0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-aef8d80a-1a43-4f9f-80e2-1fa90d390fa0' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (lat: 40, lon: 32)>\n",
       "array([[         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       ...,\n",
       "       [211.17947047, 189.711944  , 142.03207494, ..., 232.55307489,\n",
       "        141.42160073,  61.05303571],\n",
       "       [143.73164478, 157.15065847, 136.36845255, ..., 327.27229134,\n",
       "        169.56524501, 125.25698745],\n",
       "       [130.54731608, 159.37077891, 214.00625273, ..., 191.65794954,\n",
       "        150.2203387 , 116.79531541]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bias_percentage = ((noresm - chirps)/chirps)*100\n",
    "bias_percentage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "08ba09cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x684 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting annual_pr_mean\n",
    "\n",
    "#plotting with cartopy\n",
    "import cartopy.feature as cfeature\n",
    "\n",
    "\n",
    "plt.rcParams['font.size'] = '16'\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize=(12,9.5))\n",
    "\n",
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "ax.set_extent([88,93,20,27])\n",
    "\n",
    "\n",
    "m1 = ax.contourf(bias['lon'], bias['lat'],bias[:,:],\n",
    "                levels=np.arange(-15,15+3,3),  transform = ccrs.PlateCarree(),cmap='BrBG',extend='both')\n",
    "\n",
    " \n",
    "# Define the xticks for longitude\n",
    "ax.set_xticks(np.arange(87,94,1), crs=ccrs.PlateCarree())\n",
    "lon_formatter = cticker.LongitudeFormatter()\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "\n",
    "# Define the yticks for latitude\n",
    "ax.set_yticks(np.arange(20,28,1), crs=ccrs.PlateCarree())\n",
    "lat_formatter = cticker.LatitudeFormatter()\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "\n",
    "\n",
    "plt.colorbar(m1,ticks=np.arange(-15,15+3,3),  orientation = 'horizontal',shrink=0.5, fraction = 0.04 , label = 'mm/day')\n",
    "ax.coastlines(linewidth=3)\n",
    "ax.add_feature(cfeature.BORDERS,linewidth=3)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "plt.title('Seasonal Bias(GCM NORESM-CHIRPS)',fontsize=19)\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/Seasonal Bias(gcm noresm-chirps).png\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "9003db92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x684 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting bias percentage \n",
    "\n",
    "#plotting with cartopy\n",
    "import cartopy.feature as cfeature\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize=(12,9.5))\n",
    "\n",
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "ax.set_extent([88,93,20,27])\n",
    "\n",
    "\n",
    "m1 = ax.contourf(bias_percentage['lon'], bias_percentage['lat'],bias_percentage[:,:],\n",
    "                levels=np.arange(-150,150+25,25),  transform = ccrs.PlateCarree(),cmap='BrBG',extend='both')\n",
    "\n",
    " \n",
    "# Define the xticks for longitude\n",
    "ax.set_xticks(np.arange(87,94,1), crs=ccrs.PlateCarree())\n",
    "lon_formatter = cticker.LongitudeFormatter()\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "\n",
    "# Define the yticks for latitude\n",
    "ax.set_yticks(np.arange(20,28,1), crs=ccrs.PlateCarree())\n",
    "lat_formatter = cticker.LatitudeFormatter()\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "\n",
    "\n",
    "plt.colorbar(m1,ticks=np.arange(-150,150+25,25),orientation = 'horizontal',shrink=0.5, fraction = 0.04 , label = 'percentage')\n",
    "ax.coastlines(linewidth=3)\n",
    "ax.add_feature(cfeature.BORDERS,linewidth=3)\n",
    "\n",
    "\n",
    "plt.title('Seasonal Bias-Percentage(GCM NORESM-CHIRPS)',fontsize=19)\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/Seasonal Bias_percentage(gcm noresm-chirps).png\")\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "220503a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Colormap CET_D1A is not recognized. Possible values are: Accent, Accent_r, Blues, Blues_r, \\nBrBG, BrBG_r, BuGn, BuGn_r, BuPu, BuPu_r, CMRmap, CMRmap_r, Dark2, Dark2_r, GnBu, GnBu_r, Greens,\\nGreens_r, Greys, Greys_r, OrRd, OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, \\nPastel2_r, PiYG, PiYG_r, PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Purples_r, RdBu, RdBu_r, RdGy,\\nRdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, \\nSpectral_r, Wistia, Wistia_r, YlGn, YlGnBu, YlGnBu_r, YlGn_r, YlOrBr, YlOrBr_r, YlOrRd, YlOrRd_r, afmhot, afmhot_r, autumn,\\nautumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, cividis, cividis_r, cool, cool_r, coolwarm, coolwarm_r, \\ncopper, copper_r, cubehelix, cubehelix_r, flag, flag_r, gist_earth, gist_earth_r, gist_gray, gist_gray_r, gist_heat,\\ngist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r,\\ngnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r, hsv, hsv_r, inferno, inferno_r, jet, jet_r, magma,\\nmagma_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, \\nseismic, seismic_r, spring, spring_r, summer, summer_r, tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, \\nter'"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#cma colors\n",
    "'''Colormap CET_D1A is not recognized. Possible values are: Accent, Accent_r, Blues, Blues_r, \n",
    "BrBG, BrBG_r, BuGn, BuGn_r, BuPu, BuPu_r, CMRmap, CMRmap_r, Dark2, Dark2_r, GnBu, GnBu_r, Greens,\n",
    "Greens_r, Greys, Greys_r, OrRd, OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, \n",
    "Pastel2_r, PiYG, PiYG_r, PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Purples_r, RdBu, RdBu_r, RdGy,\n",
    "RdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, \n",
    "Spectral_r, Wistia, Wistia_r, YlGn, YlGnBu, YlGnBu_r, YlGn_r, YlOrBr, YlOrBr_r, YlOrRd, YlOrRd_r, afmhot, afmhot_r, autumn,\n",
    "autumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, cividis, cividis_r, cool, cool_r, coolwarm, coolwarm_r, \n",
    "copper, copper_r, cubehelix, cubehelix_r, flag, flag_r, gist_earth, gist_earth_r, gist_gray, gist_gray_r, gist_heat,\n",
    "gist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r,\n",
    "gnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r, hsv, hsv_r, inferno, inferno_r, jet, jet_r, magma,\n",
    "magma_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, \n",
    "seismic, seismic_r, spring, spring_r, summer, summer_r, tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, \n",
    "ter'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "87f4ea28",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "20e38f40",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "21be7cc5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d334a9ec",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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