Seasonal Bias ensemble average(GCM-CRU).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:  (lon: 720, lat: 360, time: 1452)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 -179.8 -179.2 -178.8 -178.2 ... 178.8 179.2 179.8\n",
       "  * lat      (lat) float32 -89.75 -89.25 -88.75 -88.25 ... 88.75 89.25 89.75\n",
       "  * time     (time) datetime64[ns] 1901-01-16 1901-02-15 ... 2021-12-16\n",
       "Data variables:\n",
       "    pre      (time, lat, lon) float32 ...\n",
       "    stn      (time, lat, lon) float64 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk</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-15aebf36-5f5c-4fe0-b201-5878244ff1c7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-15aebf36-5f5c-4fe0-b201-5878244ff1c7' 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'>lon</span>: 720</li><li><span class='xr-has-index'>lat</span>: 360</li><li><span class='xr-has-index'>time</span>: 1452</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e5dce39b-4e44-44d8-be8f-afba6fa24e4d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e5dce39b-4e44-44d8-be8f-afba6fa24e4d' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-179.8 -179.2 ... 179.2 179.8</div><input id='attrs-086a2118-c9b3-445a-a09b-61d6d2f2aacd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-086a2118-c9b3-445a-a09b-61d6d2f2aacd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb21d84c-78f3-457c-9227-7fd57d288d9f' class='xr-var-data-in' type='checkbox'><label for='data-bb21d84c-78f3-457c-9227-7fd57d288d9f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-179.75, -179.25, -178.75, ...,  178.75,  179.25,  179.75],\n",
       "      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'>-89.75 -89.25 ... 89.25 89.75</div><input id='attrs-5fb37926-d0e3-4530-9574-1bd365c3346a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5fb37926-d0e3-4530-9574-1bd365c3346a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b17f615-e89f-4688-a44e-b7c5a8cdb164' class='xr-var-data-in' type='checkbox'><label for='data-0b17f615-e89f-4688-a44e-b7c5a8cdb164' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-89.75, -89.25, -88.75, ...,  88.75,  89.25,  89.75], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1901-01-16 ... 2021-12-16</div><input id='attrs-04b950a7-4375-447a-846c-b63b881d521b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-04b950a7-4375-447a-846c-b63b881d521b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc48450c-e5a5-4842-834e-689dfba3b482' class='xr-var-data-in' type='checkbox'><label for='data-cc48450c-e5a5-4842-834e-689dfba3b482' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1901-01-16T00:00:00.000000000&#x27;, &#x27;1901-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;1901-03-16T00:00:00.000000000&#x27;, ..., &#x27;2021-10-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-11-16T00:00:00.000000000&#x27;, &#x27;2021-12-16T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-888c2b2e-608a-4acf-bd59-5c11b570ff7e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-888c2b2e-608a-4acf-bd59-5c11b570ff7e' class='xr-section-summary' >Data variables: <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>pre</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-5b1b1194-5e3c-4a58-9660-401c94724d36' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5b1b1194-5e3c-4a58-9660-401c94724d36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98b97b84-8da5-4e18-922e-7e94a92cc2ff' class='xr-var-data-in' type='checkbox'><label for='data-98b97b84-8da5-4e18-922e-7e94a92cc2ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>precipitation</dd><dt><span>units :</span></dt><dd>mm/month</dd><dt><span>correlation_decay_distance :</span></dt><dd>450.0</dd></dl></div><div class='xr-var-data'><pre>[376358400 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stn</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'>...</div><input id='attrs-647060e3-1576-4c09-9114-91dea9924111' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-647060e3-1576-4c09-9114-91dea9924111' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5fd8cffe-48df-4d36-a93f-0192b60ce097' class='xr-var-data-in' type='checkbox'><label for='data-5fd8cffe-48df-4d36-a93f-0192b60ce097' 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>description :</span></dt><dd>number of stations contributing to each datum</dd></dl></div><div class='xr-var-data'><pre>[376358400 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2f4f8d39-467f-4cca-9648-5c06e8d084b4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2f4f8d39-467f-4cca-9648-5c06e8d084b4' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>title :</span></dt><dd>CRU TS4.06 Precipitation</dd><dt><span>institution :</span></dt><dd>Data held at British Atmospheric Data Centre, RAL, UK.</dd><dt><span>source :</span></dt><dd>Run ID = 2205201912. Data generated from:pre.2204291209.dtb</dd><dt><span>history :</span></dt><dd>Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegridsauto.for called by update.for</dd><dt><span>references :</span></dt><dd>Information on the data is available at http://badc.nerc.ac.uk/data/cru/</dd><dt><span>comment :</span></dt><dd>Access to these data is available to any registered CEDA user.</dd><dt><span>contact :</span></dt><dd>support@ceda.ac.uk</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lon: 720, lat: 360, time: 1452)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 -179.8 -179.2 -178.8 -178.2 ... 178.8 179.2 179.8\n",
       "  * lat      (lat) float32 -89.75 -89.25 -88.75 -88.25 ... 88.75 89.25 89.75\n",
       "  * time     (time) datetime64[ns] 1901-01-16 1901-02-15 ... 2021-12-16\n",
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       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
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     "execution_count": 2,
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   "source": [
    "data = xr.open_dataset('/home/mkibria/Academic/pr_of_thesis/observation/cru/cru_ts4.06.1901.2021.pre.dat.nc')\n",
    " \n",
    "\n",
    "data"
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       "Dimensions:  (lon: 720, lat: 360, time: 299)\n",
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       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
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       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk</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-96a245a4-d5d9-4bae-bac0-cc292516a28e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-96a245a4-d5d9-4bae-bac0-cc292516a28e' 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'>lon</span>: 720</li><li><span class='xr-has-index'>lat</span>: 360</li><li><span class='xr-has-index'>time</span>: 299</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-eda1ee77-bf75-480f-b71d-f90cbe09a385' class='xr-section-summary-in' type='checkbox'  checked><label for='section-eda1ee77-bf75-480f-b71d-f90cbe09a385' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-179.8 -179.2 ... 179.2 179.8</div><input id='attrs-a884ff36-d26f-4c23-95a0-9c75f9940906' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a884ff36-d26f-4c23-95a0-9c75f9940906' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-80f68e72-2c4d-4643-a17f-90ea3d2e349a' class='xr-var-data-in' type='checkbox'><label for='data-80f68e72-2c4d-4643-a17f-90ea3d2e349a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-179.75, -179.25, -178.75, ...,  178.75,  179.25,  179.75],\n",
       "      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'>-89.75 -89.25 ... 89.25 89.75</div><input id='attrs-d0d63e6c-6fe0-4a2c-8c2a-f3aa19f29b0e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0d63e6c-6fe0-4a2c-8c2a-f3aa19f29b0e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44c49f3d-3c2c-4650-b610-3e6800973f0c' class='xr-var-data-in' type='checkbox'><label for='data-44c49f3d-3c2c-4650-b610-3e6800973f0c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-89.75, -89.25, -88.75, ...,  88.75,  89.25,  89.75], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-02-15 ... 2005-12-16</div><input id='attrs-2098d838-fbcd-4773-8e26-7c33138a7770' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2098d838-fbcd-4773-8e26-7c33138a7770' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4d7bac8-e7a1-40e9-baf8-33878c11610a' class='xr-var-data-in' type='checkbox'><label for='data-d4d7bac8-e7a1-40e9-baf8-33878c11610a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-02-15T00:00:00.000000000&#x27;, &#x27;1981-03-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-04-16T00:00:00.000000000&#x27;, ..., &#x27;2005-10-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-11-16T00:00:00.000000000&#x27;, &#x27;2005-12-16T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-08f780ac-4f6d-481b-aeab-ffa1fdac84e4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-08f780ac-4f6d-481b-aeab-ffa1fdac84e4' class='xr-section-summary' >Data variables: <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>pre</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-e38c3de5-3428-483f-815b-726131c119d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e38c3de5-3428-483f-815b-726131c119d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1f2f360-7698-43d7-baf3-0873f9e5f258' class='xr-var-data-in' type='checkbox'><label for='data-e1f2f360-7698-43d7-baf3-0873f9e5f258' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>precipitation</dd><dt><span>units :</span></dt><dd>mm/month</dd><dt><span>correlation_decay_distance :</span></dt><dd>450.0</dd></dl></div><div class='xr-var-data'><pre>[77500800 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stn</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'>...</div><input id='attrs-53ecf5b7-4e01-4fd1-953f-3d09424b75d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-53ecf5b7-4e01-4fd1-953f-3d09424b75d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30cf0953-9802-46ef-8d05-7ddcbbfa83ed' class='xr-var-data-in' type='checkbox'><label for='data-30cf0953-9802-46ef-8d05-7ddcbbfa83ed' 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>description :</span></dt><dd>number of stations contributing to each datum</dd></dl></div><div class='xr-var-data'><pre>[77500800 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-290057a8-0202-488a-afc4-29dd4f3d540d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-290057a8-0202-488a-afc4-29dd4f3d540d' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>title :</span></dt><dd>CRU TS4.06 Precipitation</dd><dt><span>institution :</span></dt><dd>Data held at British Atmospheric Data Centre, RAL, UK.</dd><dt><span>source :</span></dt><dd>Run ID = 2205201912. Data generated from:pre.2204291209.dtb</dd><dt><span>history :</span></dt><dd>Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegridsauto.for called by update.for</dd><dt><span>references :</span></dt><dd>Information on the data is available at http://badc.nerc.ac.uk/data/cru/</dd><dt><span>comment :</span></dt><dd>Access to these data is available to any registered CEDA user.</dd><dt><span>contact :</span></dt><dd>support@ceda.ac.uk</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lon: 720, lat: 360, time: 299)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 -179.8 -179.2 -178.8 -178.2 ... 178.8 179.2 179.8\n",
       "  * lat      (lat) float32 -89.75 -89.25 -88.75 -88.25 ... 88.75 89.25 89.75\n",
       "  * time     (time) datetime64[ns] 1981-02-15 1981-03-16 ... 2005-12-16\n",
       "Data variables:\n",
       "    pre      (time, lat, lon) float32 ...\n",
       "    stn      (time, lat, lon) float64 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk"
      ]
     },
     "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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       "  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:  (lon: 720, lat: 360, time: 100)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 -179.8 -179.2 -178.8 -178.2 ... 178.8 179.2 179.8\n",
       "  * lat      (lat) float32 -89.75 -89.25 -88.75 -88.25 ... 88.75 89.25 89.75\n",
       "  * time     (time) datetime64[ns] 1981-06-16 1981-07-16 ... 2005-09-16\n",
       "Data variables:\n",
       "    pre      (time, lat, lon) float32 ...\n",
       "    stn      (time, lat, lon) float64 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk</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-03f3d403-bfb9-4680-adde-ac20729e0490' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-03f3d403-bfb9-4680-adde-ac20729e0490' 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'>lon</span>: 720</li><li><span class='xr-has-index'>lat</span>: 360</li><li><span class='xr-has-index'>time</span>: 100</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-10e6b032-f80b-4a30-b65f-c8cf4d006348' class='xr-section-summary-in' type='checkbox'  checked><label for='section-10e6b032-f80b-4a30-b65f-c8cf4d006348' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-179.8 -179.2 ... 179.2 179.8</div><input id='attrs-455b7a25-d468-4785-b0d9-fd1c451226d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-455b7a25-d468-4785-b0d9-fd1c451226d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-356d6516-14c0-423e-b4cc-8f7f56cbdba2' class='xr-var-data-in' type='checkbox'><label for='data-356d6516-14c0-423e-b4cc-8f7f56cbdba2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-179.75, -179.25, -178.75, ...,  178.75,  179.25,  179.75],\n",
       "      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'>-89.75 -89.25 ... 89.25 89.75</div><input id='attrs-dfb78270-222a-4d4e-9305-fb988decdda0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dfb78270-222a-4d4e-9305-fb988decdda0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd5d42f5-da50-4a40-9c17-6da345da7e2d' class='xr-var-data-in' type='checkbox'><label for='data-cd5d42f5-da50-4a40-9c17-6da345da7e2d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-89.75, -89.25, -88.75, ...,  88.75,  89.25,  89.75], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-06-16 ... 2005-09-16</div><input id='attrs-bd3fbea0-e62b-4f95-801b-a25917976ed1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd3fbea0-e62b-4f95-801b-a25917976ed1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d0795c7-d84a-4a9d-8eb6-78d6f5ff1c02' class='xr-var-data-in' type='checkbox'><label for='data-6d0795c7-d84a-4a9d-8eb6-78d6f5ff1c02' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-06-16T00:00:00.000000000&#x27;, &#x27;1981-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-08-16T00:00:00.000000000&#x27;, &#x27;1981-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-06-16T00:00:00.000000000&#x27;, &#x27;1982-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-08-16T00:00:00.000000000&#x27;, &#x27;1982-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-06-16T00:00:00.000000000&#x27;, &#x27;1983-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-08-16T00:00:00.000000000&#x27;, &#x27;1983-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-06-16T00:00:00.000000000&#x27;, &#x27;1984-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-08-16T00:00:00.000000000&#x27;, &#x27;1984-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-06-16T00:00:00.000000000&#x27;, &#x27;1985-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-08-16T00:00:00.000000000&#x27;, &#x27;1985-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-06-16T00:00:00.000000000&#x27;, &#x27;1986-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-08-16T00:00:00.000000000&#x27;, &#x27;1986-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-06-16T00:00:00.000000000&#x27;, &#x27;1987-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-08-16T00:00:00.000000000&#x27;, &#x27;1987-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-06-16T00:00:00.000000000&#x27;, &#x27;1988-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-08-16T00:00:00.000000000&#x27;, &#x27;1988-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-06-16T00:00:00.000000000&#x27;, &#x27;1989-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-08-16T00:00:00.000000000&#x27;, &#x27;1989-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-06-16T00:00:00.000000000&#x27;, &#x27;1990-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-08-16T00:00:00.000000000&#x27;, &#x27;1990-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-06-16T00:00:00.000000000&#x27;, &#x27;1991-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-08-16T00:00:00.000000000&#x27;, &#x27;1991-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-06-16T00:00:00.000000000&#x27;, &#x27;1992-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-08-16T00:00:00.000000000&#x27;, &#x27;1992-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-06-16T00:00:00.000000000&#x27;, &#x27;1993-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-08-16T00:00:00.000000000&#x27;, &#x27;1993-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-06-16T00:00:00.000000000&#x27;, &#x27;1994-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-08-16T00:00:00.000000000&#x27;, &#x27;1994-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-06-16T00:00:00.000000000&#x27;, &#x27;1995-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-08-16T00:00:00.000000000&#x27;, &#x27;1995-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-06-16T00:00:00.000000000&#x27;, &#x27;1996-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-08-16T00:00:00.000000000&#x27;, &#x27;1996-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-06-16T00:00:00.000000000&#x27;, &#x27;1997-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-08-16T00:00:00.000000000&#x27;, &#x27;1997-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-06-16T00:00:00.000000000&#x27;, &#x27;1998-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-08-16T00:00:00.000000000&#x27;, &#x27;1998-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-06-16T00:00:00.000000000&#x27;, &#x27;1999-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-08-16T00:00:00.000000000&#x27;, &#x27;1999-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-16T00:00:00.000000000&#x27;, &#x27;2000-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-08-16T00:00:00.000000000&#x27;, &#x27;2000-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-06-16T00:00:00.000000000&#x27;, &#x27;2001-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-08-16T00:00:00.000000000&#x27;, &#x27;2001-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-16T00:00:00.000000000&#x27;, &#x27;2002-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-16T00:00:00.000000000&#x27;, &#x27;2002-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-16T00:00:00.000000000&#x27;, &#x27;2003-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-16T00:00:00.000000000&#x27;, &#x27;2003-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-16T00:00:00.000000000&#x27;, &#x27;2004-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-16T00:00:00.000000000&#x27;, &#x27;2004-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-16T00:00:00.000000000&#x27;, &#x27;2005-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-08-16T00:00:00.000000000&#x27;, &#x27;2005-09-16T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bb383498-5047-44c4-a8fb-2b0861dbbd7b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bb383498-5047-44c4-a8fb-2b0861dbbd7b' class='xr-section-summary' >Data variables: <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>pre</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-e9e50b66-047a-41c8-b2ef-82067df5a6b3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e9e50b66-047a-41c8-b2ef-82067df5a6b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1028de90-4c25-4657-9890-1f17da787497' class='xr-var-data-in' type='checkbox'><label for='data-1028de90-4c25-4657-9890-1f17da787497' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>precipitation</dd><dt><span>units :</span></dt><dd>mm/month</dd><dt><span>correlation_decay_distance :</span></dt><dd>450.0</dd></dl></div><div class='xr-var-data'><pre>[25920000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stn</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'>...</div><input id='attrs-bec4596d-a521-44f0-b75e-26dbdd3ed3b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bec4596d-a521-44f0-b75e-26dbdd3ed3b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1315b16-f6fd-4922-b677-5573812ed866' class='xr-var-data-in' type='checkbox'><label for='data-e1315b16-f6fd-4922-b677-5573812ed866' 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>description :</span></dt><dd>number of stations contributing to each datum</dd></dl></div><div class='xr-var-data'><pre>[25920000 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-67e6641f-27d3-4503-88c8-05be16c3c197' class='xr-section-summary-in' type='checkbox'  checked><label for='section-67e6641f-27d3-4503-88c8-05be16c3c197' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>title :</span></dt><dd>CRU TS4.06 Precipitation</dd><dt><span>institution :</span></dt><dd>Data held at British Atmospheric Data Centre, RAL, UK.</dd><dt><span>source :</span></dt><dd>Run ID = 2205201912. Data generated from:pre.2204291209.dtb</dd><dt><span>history :</span></dt><dd>Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegridsauto.for called by update.for</dd><dt><span>references :</span></dt><dd>Information on the data is available at http://badc.nerc.ac.uk/data/cru/</dd><dt><span>comment :</span></dt><dd>Access to these data is available to any registered CEDA user.</dd><dt><span>contact :</span></dt><dd>support@ceda.ac.uk</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lon: 720, lat: 360, time: 100)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 -179.8 -179.2 -178.8 -178.2 ... 178.8 179.2 179.8\n",
       "  * lat      (lat) float32 -89.75 -89.25 -88.75 -88.25 ... 88.75 89.25 89.75\n",
       "  * time     (time) datetime64[ns] 1981-06-16 1981-07-16 ... 2005-09-16\n",
       "Data variables:\n",
       "    pre      (time, lat, lon) float32 ...\n",
       "    stn      (time, lat, lon) float64 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk"
      ]
     },
     "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": "db55dbfb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "\n",
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       "\n",
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       "  vertical-align: middle;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 100, lat: 40, lon: 32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1981-06-16 1981-07-16 ... 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",
       "Data variables:\n",
       "    pre      (time, lat, lon) float64 nan nan nan nan ... 106.5 119.5 132.0\n",
       "    stn      (time, lat, lon) float64 nan nan nan nan nan ... 8.0 8.0 8.0 8.0\n",
       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk</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-51245864-f943-4c43-a78d-2c4cc21ba7c6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-51245864-f943-4c43-a78d-2c4cc21ba7c6' 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'>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-2832f6ce-e0aa-46d0-b81b-0c501e3ec4f5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2832f6ce-e0aa-46d0-b81b-0c501e3ec4f5' 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-97a9d9e1-bc7b-4f4a-b715-b96e6942d3a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-97a9d9e1-bc7b-4f4a-b715-b96e6942d3a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd5fccab-543f-45f7-8baa-21c465a59714' class='xr-var-data-in' type='checkbox'><label for='data-dd5fccab-543f-45f7-8baa-21c465a59714' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-06-16T00:00:00.000000000&#x27;, &#x27;1981-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-08-16T00:00:00.000000000&#x27;, &#x27;1981-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-06-16T00:00:00.000000000&#x27;, &#x27;1982-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-08-16T00:00:00.000000000&#x27;, &#x27;1982-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-06-16T00:00:00.000000000&#x27;, &#x27;1983-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-08-16T00:00:00.000000000&#x27;, &#x27;1983-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-06-16T00:00:00.000000000&#x27;, &#x27;1984-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-08-16T00:00:00.000000000&#x27;, &#x27;1984-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-06-16T00:00:00.000000000&#x27;, &#x27;1985-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-08-16T00:00:00.000000000&#x27;, &#x27;1985-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-06-16T00:00:00.000000000&#x27;, &#x27;1986-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-08-16T00:00:00.000000000&#x27;, &#x27;1986-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-06-16T00:00:00.000000000&#x27;, &#x27;1987-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-08-16T00:00:00.000000000&#x27;, &#x27;1987-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-06-16T00:00:00.000000000&#x27;, &#x27;1988-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-08-16T00:00:00.000000000&#x27;, &#x27;1988-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-06-16T00:00:00.000000000&#x27;, &#x27;1989-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-08-16T00:00:00.000000000&#x27;, &#x27;1989-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-06-16T00:00:00.000000000&#x27;, &#x27;1990-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-08-16T00:00:00.000000000&#x27;, &#x27;1990-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-06-16T00:00:00.000000000&#x27;, &#x27;1991-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-08-16T00:00:00.000000000&#x27;, &#x27;1991-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-06-16T00:00:00.000000000&#x27;, &#x27;1992-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-08-16T00:00:00.000000000&#x27;, &#x27;1992-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-06-16T00:00:00.000000000&#x27;, &#x27;1993-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-08-16T00:00:00.000000000&#x27;, &#x27;1993-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-06-16T00:00:00.000000000&#x27;, &#x27;1994-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-08-16T00:00:00.000000000&#x27;, &#x27;1994-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-06-16T00:00:00.000000000&#x27;, &#x27;1995-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-08-16T00:00:00.000000000&#x27;, &#x27;1995-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-06-16T00:00:00.000000000&#x27;, &#x27;1996-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-08-16T00:00:00.000000000&#x27;, &#x27;1996-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-06-16T00:00:00.000000000&#x27;, &#x27;1997-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-08-16T00:00:00.000000000&#x27;, &#x27;1997-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-06-16T00:00:00.000000000&#x27;, &#x27;1998-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-08-16T00:00:00.000000000&#x27;, &#x27;1998-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-06-16T00:00:00.000000000&#x27;, &#x27;1999-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-08-16T00:00:00.000000000&#x27;, &#x27;1999-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-16T00:00:00.000000000&#x27;, &#x27;2000-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-08-16T00:00:00.000000000&#x27;, &#x27;2000-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-06-16T00:00:00.000000000&#x27;, &#x27;2001-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-08-16T00:00:00.000000000&#x27;, &#x27;2001-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-16T00:00:00.000000000&#x27;, &#x27;2002-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-16T00:00:00.000000000&#x27;, &#x27;2002-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-16T00:00:00.000000000&#x27;, &#x27;2003-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-16T00:00:00.000000000&#x27;, &#x27;2003-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-16T00:00:00.000000000&#x27;, &#x27;2004-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-16T00:00:00.000000000&#x27;, &#x27;2004-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-16T00:00:00.000000000&#x27;, &#x27;2005-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-08-16T00:00:00.000000000&#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-a2df82cc-8020-4bb2-9fbb-8b1adb70fc9b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2df82cc-8020-4bb2-9fbb-8b1adb70fc9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32e1ac3e-7a60-45cf-95dc-814d5e7df99a' class='xr-var-data-in' type='checkbox'><label for='data-32e1ac3e-7a60-45cf-95dc-814d5e7df99a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</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-1eca9ccc-a4e2-4206-bf90-37d606ec5afb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1eca9ccc-a4e2-4206-bf90-37d606ec5afb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15da3efe-8a35-4c9c-be0c-890cf361b582' class='xr-var-data-in' type='checkbox'><label for='data-15da3efe-8a35-4c9c-be0c-890cf361b582' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</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-bc25e984-d870-42e8-ae0d-fa4a5b4fbb9f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bc25e984-d870-42e8-ae0d-fa4a5b4fbb9f' class='xr-section-summary' >Data variables: <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>pre</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'>nan nan nan ... 106.5 119.5 132.0</div><input id='attrs-93eef2e4-3e39-413a-8c7f-4aa2310f7b77' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93eef2e4-3e39-413a-8c7f-4aa2310f7b77' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b12c36bb-7b77-43ec-b6d9-f981a3faaec3' class='xr-var-data-in' type='checkbox'><label for='data-b12c36bb-7b77-43ec-b6d9-f981a3faaec3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>precipitation</dd><dt><span>units :</span></dt><dd>mm/month</dd><dt><span>correlation_decay_distance :</span></dt><dd>450.0</dd></dl></div><div class='xr-var-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",
       "        [186.09999943, 192.2249999 , 211.72500277, ..., 216.03125286,\n",
       "         256.09375095, 299.78750229],\n",
       "        [166.50000286, 148.32500124, 138.92500067, ..., 192.64375401,\n",
       "         225.13125134, 262.81250381],\n",
       "        [122.48750365,  99.36875165,  81.30624998, ..., 164.90625381,\n",
       "         193.16875076, 225.40000343]],\n",
       "\n",
       "       [[         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",
       "        [294.41876221, 279.23751545, 281.96251583, ..., 210.16875267,\n",
       "         244.75625038, 282.01875019],\n",
       "        [295.0062561 , 249.11250973, 209.28751087, ..., 186.10624886,\n",
       "         213.46874809, 244.30625057],\n",
       "        [233.94375253, 188.16250539, 142.73750663, ..., 161.73749828,\n",
       "         184.7624979 , 210.28125095]],\n",
       "\n",
       "       [[         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",
       "        [215.03125572, 207.20000362, 214.70000172, ..., 128.88750315,\n",
       "         142.06250715, 155.93125725],\n",
       "        [195.74375343, 165.95000172, 139.5500021 , ..., 119.21250486,\n",
       "         131.83750772, 145.04375648],\n",
       "        [145.89375198, 114.26250076,  81.13750172, ..., 106.50625467,\n",
       "         119.51875639, 132.03125477]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stn</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'>nan nan nan nan ... 8.0 8.0 8.0 8.0</div><input id='attrs-af89136f-19f7-4563-a8c5-b9f924e7584a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af89136f-19f7-4563-a8c5-b9f924e7584a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3300e79c-b797-4693-871a-b536b1a0b471' class='xr-var-data-in' type='checkbox'><label for='data-3300e79c-b797-4693-871a-b536b1a0b471' 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>description :</span></dt><dd>number of stations contributing to each datum</dd></dl></div><div class='xr-var-data'><pre>array([[[   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        ...,\n",
       "        [8.    , 8.    , 8.    , ..., 8.    , 8.    , 8.    ],\n",
       "        [8.    , 8.    , 8.    , ..., 8.    , 8.    , 8.    ],\n",
       "        [8.    , 8.    , 8.    , ..., 8.    , 8.    , 8.    ]],\n",
       "\n",
       "       [[   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        ...,\n",
       "        [8.    , 8.    , 8.    , ..., 8.    , 8.    , 8.    ],\n",
       "        [8.    , 8.    , 8.    , ..., 8.    , 8.    , 8.    ],\n",
       "        [8.    , 8.    , 8.    , ..., 8.    , 8.    , 8.    ]],\n",
       "\n",
       "       [[   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [5.1875, 5.1875, 5.5625, ..., 7.25  , 7.25  , 7.25  ],\n",
       "        [5.0625, 5.0625, 5.1875, ..., 7.75  , 7.75  , 7.75  ],\n",
       "        [5.    , 5.    , 5.    , ..., 8.    , 8.    , 8.    ]],\n",
       "\n",
       "       [[   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        ...,\n",
       "        [5.1875, 5.1875, 5.5625, ..., 6.3125, 6.4375, 6.4375],\n",
       "        [5.0625, 5.0625, 5.1875, ..., 6.9375, 7.3125, 7.3125],\n",
       "        [5.    , 5.    , 5.    , ..., 7.4375, 7.8125, 7.8125]],\n",
       "\n",
       "       [[   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        ...,\n",
       "        [7.125 , 7.1875, 7.5625, ..., 8.    , 8.    , 8.    ],\n",
       "        [6.875 , 7.0625, 7.1875, ..., 8.    , 8.    , 8.    ],\n",
       "        [6.5625, 6.75  , 6.75  , ..., 8.    , 8.    , 8.    ]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-482e7b4e-5627-4c39-9091-f811b6328f47' class='xr-section-summary-in' type='checkbox'  checked><label for='section-482e7b4e-5627-4c39-9091-f811b6328f47' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>title :</span></dt><dd>CRU TS4.06 Precipitation</dd><dt><span>institution :</span></dt><dd>Data held at British Atmospheric Data Centre, RAL, UK.</dd><dt><span>source :</span></dt><dd>Run ID = 2205201912. Data generated from:pre.2204291209.dtb</dd><dt><span>history :</span></dt><dd>Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegridsauto.for called by update.for</dd><dt><span>references :</span></dt><dd>Information on the data is available at http://badc.nerc.ac.uk/data/cru/</dd><dt><span>comment :</span></dt><dd>Access to these data is available to any registered CEDA user.</dd><dt><span>contact :</span></dt><dd>support@ceda.ac.uk</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 100, lat: 40, lon: 32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1981-06-16 1981-07-16 ... 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",
       "Data variables:\n",
       "    pre      (time, lat, lon) float64 nan nan nan nan ... 106.5 119.5 132.0\n",
       "    stn      (time, lat, lon) float64 nan nan nan nan nan ... 8.0 8.0 8.0 8.0\n",
       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk"
      ]
     },
     "execution_count": 5,
     "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(18.125,28,0.25)\n",
    "jjas_data = jjas_data.interp(lon=new_lon,lat=new_lat)\n",
    "jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "735515f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#for i in data.latitude.values:\n",
    " #   print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "fd310367",
   "metadata": {},
   "outputs": [],
   "source": [
    "#for i in data.longitude.values:\n",
    " #   print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2a9644bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "#to select the x and y coordinates\n",
    "#jjas_data = jjas_data.sel(lon=slice(86,94),lat=slice(18,28))\n",
    "#jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "82d6b5d0",
   "metadata": {},
   "outputs": [
    {
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       "\n",
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       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
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       "  padding-right: 10px;\n",
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       "\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
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       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pre&#x27; (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",
       "       [322.41163091, 307.85400578, 313.06750626, ..., 257.97650403,\n",
       "        300.16450421, 345.07625492],\n",
       "       [310.9198804 , 261.39550442, 217.76700411, ..., 228.96350388,\n",
       "        263.6115048 , 302.68625538],\n",
       "       [238.8421915 , 187.87906546, 136.51418995, ..., 196.9485036 ,\n",
       "        227.13300466, 260.69975512]])\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'>'pre'</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-dd2bd6b2-d5f0-449d-bb69-abddc5c70894' class='xr-array-in' type='checkbox' checked><label for='section-dd2bd6b2-d5f0-449d-bb69-abddc5c70894' 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 ... 117.1 139.7 167.8 196.9 227.1 260.7</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",
       "       [322.41163091, 307.85400578, 313.06750626, ..., 257.97650403,\n",
       "        300.16450421, 345.07625492],\n",
       "       [310.9198804 , 261.39550442, 217.76700411, ..., 228.96350388,\n",
       "        263.6115048 , 302.68625538],\n",
       "       [238.8421915 , 187.87906546, 136.51418995, ..., 196.9485036 ,\n",
       "        227.13300466, 260.69975512]])</pre></div></div></li><li class='xr-section-item'><input id='section-55efa702-2c35-4d0d-8321-030f43ca7624' class='xr-section-summary-in' type='checkbox'  checked><label for='section-55efa702-2c35-4d0d-8321-030f43ca7624' 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-2cef5584-b51b-419a-84af-b0b4a96e9d9e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2cef5584-b51b-419a-84af-b0b4a96e9d9e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d0dfc11-b7e9-4562-92e6-daf1e3c18b25' class='xr-var-data-in' type='checkbox'><label for='data-5d0dfc11-b7e9-4562-92e6-daf1e3c18b25' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</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-e5d9a2f7-310c-48cd-9c1d-f17eeef89999' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5d9a2f7-310c-48cd-9c1d-f17eeef89999' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2091e01-2e5b-44e2-ab67-5ef4f9e76d24' class='xr-var-data-in' type='checkbox'><label for='data-a2091e01-2e5b-44e2-ab67-5ef4f9e76d24' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</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-99301fb9-2fa1-44d2-a676-84162ffc3a34' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-99301fb9-2fa1-44d2-a676-84162ffc3a34' 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 'pre' (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",
       "       [322.41163091, 307.85400578, 313.06750626, ..., 257.97650403,\n",
       "        300.16450421, 345.07625492],\n",
       "       [310.9198804 , 261.39550442, 217.76700411, ..., 228.96350388,\n",
       "        263.6115048 , 302.68625538],\n",
       "       [238.8421915 , 187.87906546, 136.51418995, ..., 196.9485036 ,\n",
       "        227.13300466, 260.69975512]])\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": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#getting the mean for JJAS data\n",
    "jjas_mean = jjas_data.pre.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",
    "\n",
    "pr_mm = jjas_mean/30.4167\n",
    " \n",
    "\n",
    "\n",
    "cru = pr_mm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b6d9b2b3",
   "metadata": {},
   "outputs": [
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       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".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: 1872, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) object 1850-01-16 12:00:00 ... 2005-12-16 12:00:00\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",
       "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",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/29)\n",
       "    CDI:                    Climate Data Interface version 1.9.9rc1 (https://...\n",
       "    Conventions:            CF-1.4\n",
       "    history:                Fri Jul 22 11:03:06 2022: cdo remapnn,grid1.des g...\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    ...                     ...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6\n",
       "    CDO:                    Climate Data Operators version 1.9.9rc1 (https://...</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-2792d0cc-24bc-4f1d-ae27-1fac1366d791' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2792d0cc-24bc-4f1d-ae27-1fac1366d791' 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'>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-cbe4f9cd-5d17-4aa2-91d3-903302cf59ba' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cbe4f9cd-5d17-4aa2-91d3-903302cf59ba' 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-1d5e701c-8f2b-478e-831c-cb61be2a3291' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1d5e701c-8f2b-478e-831c-cb61be2a3291' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0e719d7-7222-443e-a25e-e505a747d5e1' class='xr-var-data-in' type='checkbox'><label for='data-e0e719d7-7222-443e-a25e-e505a747d5e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</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'>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-87832b53-718f-4330-90a6-808b58d74202' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-87832b53-718f-4330-90a6-808b58d74202' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ebe34bfe-bb7a-48b3-961f-8d81cff8c90e' class='xr-var-data-in' type='checkbox'><label for='data-ebe34bfe-bb7a-48b3-961f-8d81cff8c90e' 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-5678443f-9239-4bb0-8fa1-874b7170299c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5678443f-9239-4bb0-8fa1-874b7170299c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-806eb91c-47be-4ba4-8ef5-5d93b43c947b' class='xr-var-data-in' type='checkbox'><label for='data-806eb91c-47be-4ba4-8ef5-5d93b43c947b' 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-b4768356-4ee6-40e0-a834-9c67ecff5678' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b4768356-4ee6-40e0-a834-9c67ecff5678' class='xr-section-summary' >Data variables: <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>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-218fd76c-63dc-4e8b-935b-134a7dd40347' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-218fd76c-63dc-4e8b-935b-134a7dd40347' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af1824d7-fd83-4e90-9998-6d1996523c22' class='xr-var-data-in' type='checkbox'><label for='data-af1824d7-fd83-4e90-9998-6d1996523c22' 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>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-09d09ff6-f30d-4d2f-961b-b16e59880ad5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-09d09ff6-f30d-4d2f-961b-b16e59880ad5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9df443f-e398-47a5-aa5f-bd58721edafc' class='xr-var-data-in' type='checkbox'><label for='data-f9df443f-e398-47a5-aa5f-bd58721edafc' 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>units :</span></dt><dd>kg m-2 s-1</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>original_name :</span></dt><dd>PRCP</dd><dt><span>original_units :</span></dt><dd>kg/m**2/s</dd><dt><span>history :</span></dt><dd>2011-04-23T09:11:46Z altered by CMOR: Converted units from &#x27;kg/m**2/s&#x27; to &#x27;kg m-2 s-1&#x27;. 2011-04-23T09:11:46Z altered by CMOR: replaced missing value flag (-999) with standard missing value (1e+20). 2011-04-23T09:11:46Z altered by CMOR: Inverted axis: lat.</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MIROC5_historical_r0i0p0.nc areacella: areacella_fx_MIROC5_historical_r0i0p0.nc</dd></dl></div><div class='xr-var-data'><pre>[2396160 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b0750fcb-0381-4132-ae8d-6c1025cbcc63' class='xr-section-summary-in' type='checkbox'  ><label for='section-b0750fcb-0381-4132-ae8d-6c1025cbcc63' class='xr-section-summary' >Attributes: <span>(29)</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-1.4</dd><dt><span>history :</span></dt><dd>Fri Jul 22 11:03:06 2022: cdo remapnn,grid1.des gcmensemble.nc gcmensemble_remap.nc\n",
       "Fri Jul 22 11:00:06 2022: cdo divc,3 final.nc gcmensemble.nc\n",
       "Fri Jul 22 10:53:46 2022: cdo -add gcm_miroc_remap1.nc -add gcm_mpi_remap.nc gcm_noresm_remap.nc final.nc\n",
       "Fri Jul 22 10:53:11 2022: cdo selyear,1850/2005 gcm_miroc_remap.nc gcm_miroc_remap1.nc\n",
       "Thu Jul 07 18:16:03 2022: cdo remapnn,grid1.des pr_Amon_MIROC5_historical_r1i1p1_185001-201212.nc gcm_miroc_remap.nc\n",
       "2011-04-23T09:11:46Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>source :</span></dt><dd>MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); ocean: COCO (COCO4.5, 256x224 L50); sea ice: COCO (COCO4.5); land: MATSIRO (MATSIRO, L6); aerosols: SPRINTARS (SPRINTARS 5.00, T85L40)</dd><dt><span>institution :</span></dt><dd>AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan), NIES (National Institute for Environmental Studies, Ibaraki, Japan), JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan)</dd><dt><span>institute_id :</span></dt><dd>MIROC</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>MIROC5</dd><dt><span>forcing :</span></dt><dd>GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG includes CO2, N2O, methane, and fluorocarbons; Oz includes OH and H2O2; LU excludes change in lake fraction)</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>150015.0</dd><dt><span>contact :</span></dt><dd>Masahiro Watanabe (hiro@aori.u-tokyo.ac.jp), Seita Emori (emori@nies.go.jp), Masayoshi Ishii (ism@jamstec.go.jp), Masahide Kimoto (kimoto@aori.u-tokyo.ac.jp)</dd><dt><span>references :</span></dt><dd>Watanabe et al., 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 6312-6335</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>a906be44-c850-4f0c-b8c4-2b165051669a</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>2011-04-23T09:11:46Z</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (31 January 2011) 53b766a395ac41696af40aab76a49ae5</dd><dt><span>title :</span></dt><dd>MIROC5 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>2.5.6</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>"
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       "<xarray.Dataset>\n",
       "Dimensions:    (time: 1872, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) object 1850-01-16 12:00:00 ... 2005-12-16 12:00:00\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",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object ...\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/29)\n",
       "    CDI:                    Climate Data Interface version 1.9.9rc1 (https://...\n",
       "    Conventions:            CF-1.4\n",
       "    history:                Fri Jul 22 11:03:06 2022: cdo remapnn,grid1.des g...\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    ...                     ...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6\n",
       "    CDO:                    Climate Data Operators version 1.9.9rc1 (https://..."
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#opening gcm miroc5 data\n",
    "\n",
    "data = xr.open_dataset('/home/mkibria/Academic/pr_of_thesis/GCM/ensemble-average/gcmensemble_remap.nc')\n",
    "\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f6e94198",
   "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_9742/1463838701.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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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 1872, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1850-01-16T12:00:00 ... 2005-12-16T12:00:00\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",
       "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",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/29)\n",
       "    CDI:                    Climate Data Interface version 1.9.9rc1 (https://...\n",
       "    Conventions:            CF-1.4\n",
       "    history:                Fri Jul 22 11:03:06 2022: cdo remapnn,grid1.des g...\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    ...                     ...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6\n",
       "    CDO:                    Climate Data Operators version 1.9.9rc1 (https://...</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-b81743cb-2730-490c-aed6-9336d63a9b62' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b81743cb-2730-490c-aed6-9336d63a9b62' 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'>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-6332d9da-7a26-4399-ae23-a2531d260a29' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6332d9da-7a26-4399-ae23-a2531d260a29' 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-c8c9ee9a-85c6-4cb0-80f1-130fd0affe83' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c8c9ee9a-85c6-4cb0-80f1-130fd0affe83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30498379-7b46-4e8f-8531-d6c65962aa2e' class='xr-var-data-in' type='checkbox'><label for='data-30498379-7b46-4e8f-8531-d6c65962aa2e' 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'>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-75c50c1c-f365-4796-a564-c5e94b111c7b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-75c50c1c-f365-4796-a564-c5e94b111c7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f281465-4bc6-48a6-ac6b-99622d9db7f7' class='xr-var-data-in' type='checkbox'><label for='data-1f281465-4bc6-48a6-ac6b-99622d9db7f7' 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-dc957097-2c04-42b8-a195-45e6c2826e8b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc957097-2c04-42b8-a195-45e6c2826e8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a285b70-84c7-4565-b5d7-bef8c93e01d4' class='xr-var-data-in' type='checkbox'><label for='data-6a285b70-84c7-4565-b5d7-bef8c93e01d4' 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-49fa3fd4-baa1-4571-9562-f3895814d86e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-49fa3fd4-baa1-4571-9562-f3895814d86e' class='xr-section-summary' >Data variables: <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>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-fdd66232-4680-440e-be3a-584a7c6a5bd5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fdd66232-4680-440e-be3a-584a7c6a5bd5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7bc4b005-ecd2-4f92-8e12-6b35b042ed1d' class='xr-var-data-in' type='checkbox'><label for='data-7bc4b005-ecd2-4f92-8e12-6b35b042ed1d' 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>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-6c9758f2-3a8c-4afb-868d-471b870e7129' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c9758f2-3a8c-4afb-868d-471b870e7129' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b092671-765f-4ee9-a1c5-a616ca5f40cf' class='xr-var-data-in' type='checkbox'><label for='data-4b092671-765f-4ee9-a1c5-a616ca5f40cf' 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>units :</span></dt><dd>kg m-2 s-1</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>original_name :</span></dt><dd>PRCP</dd><dt><span>original_units :</span></dt><dd>kg/m**2/s</dd><dt><span>history :</span></dt><dd>2011-04-23T09:11:46Z altered by CMOR: Converted units from &#x27;kg/m**2/s&#x27; to &#x27;kg m-2 s-1&#x27;. 2011-04-23T09:11:46Z altered by CMOR: replaced missing value flag (-999) with standard missing value (1e+20). 2011-04-23T09:11:46Z altered by CMOR: Inverted axis: lat.</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MIROC5_historical_r0i0p0.nc areacella: areacella_fx_MIROC5_historical_r0i0p0.nc</dd></dl></div><div class='xr-var-data'><pre>[2396160 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ddbed6f3-36ac-4208-9a7e-69c3948bd910' class='xr-section-summary-in' type='checkbox'  ><label for='section-ddbed6f3-36ac-4208-9a7e-69c3948bd910' class='xr-section-summary' >Attributes: <span>(29)</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-1.4</dd><dt><span>history :</span></dt><dd>Fri Jul 22 11:03:06 2022: cdo remapnn,grid1.des gcmensemble.nc gcmensemble_remap.nc\n",
       "Fri Jul 22 11:00:06 2022: cdo divc,3 final.nc gcmensemble.nc\n",
       "Fri Jul 22 10:53:46 2022: cdo -add gcm_miroc_remap1.nc -add gcm_mpi_remap.nc gcm_noresm_remap.nc final.nc\n",
       "Fri Jul 22 10:53:11 2022: cdo selyear,1850/2005 gcm_miroc_remap.nc gcm_miroc_remap1.nc\n",
       "Thu Jul 07 18:16:03 2022: cdo remapnn,grid1.des pr_Amon_MIROC5_historical_r1i1p1_185001-201212.nc gcm_miroc_remap.nc\n",
       "2011-04-23T09:11:46Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>source :</span></dt><dd>MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); ocean: COCO (COCO4.5, 256x224 L50); sea ice: COCO (COCO4.5); land: MATSIRO (MATSIRO, L6); aerosols: SPRINTARS (SPRINTARS 5.00, T85L40)</dd><dt><span>institution :</span></dt><dd>AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan), NIES (National Institute for Environmental Studies, Ibaraki, Japan), JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan)</dd><dt><span>institute_id :</span></dt><dd>MIROC</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>MIROC5</dd><dt><span>forcing :</span></dt><dd>GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG includes CO2, N2O, methane, and fluorocarbons; Oz includes OH and H2O2; LU excludes change in lake fraction)</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>150015.0</dd><dt><span>contact :</span></dt><dd>Masahiro Watanabe (hiro@aori.u-tokyo.ac.jp), Seita Emori (emori@nies.go.jp), Masayoshi Ishii (ism@jamstec.go.jp), Masahide Kimoto (kimoto@aori.u-tokyo.ac.jp)</dd><dt><span>references :</span></dt><dd>Watanabe et al., 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 6312-6335</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>a906be44-c850-4f0c-b8c4-2b165051669a</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>2011-04-23T09:11:46Z</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (31 January 2011) 53b766a395ac41696af40aab76a49ae5</dd><dt><span>title :</span></dt><dd>MIROC5 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>2.5.6</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: 1872, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1850-01-16T12:00:00 ... 2005-12-16T12:00:00\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",
       "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",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/29)\n",
       "    CDI:                    Climate Data Interface version 1.9.9rc1 (https://...\n",
       "    Conventions:            CF-1.4\n",
       "    history:                Fri Jul 22 11:03:06 2022: cdo remapnn,grid1.des g...\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    ...                     ...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6\n",
       "    CDO:                    Climate Data Operators version 1.9.9rc1 (https://..."
      ]
     },
     "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"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "cafd5692",
   "metadata": {},
   "outputs": [
    {
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       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".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: 299, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-01-16T12:00:00 ... 2005-11-16\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",
       "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",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/29)\n",
       "    CDI:                    Climate Data Interface version 1.9.9rc1 (https://...\n",
       "    Conventions:            CF-1.4\n",
       "    history:                Fri Jul 22 11:03:06 2022: cdo remapnn,grid1.des g...\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    ...                     ...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6\n",
       "    CDO:                    Climate Data Operators version 1.9.9rc1 (https://...</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-a3f4da5a-0483-4069-a70c-93143b8736be' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a3f4da5a-0483-4069-a70c-93143b8736be' 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'>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-a88c345b-abd4-46dd-bb82-5b2abce1795e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a88c345b-abd4-46dd-bb82-5b2abce1795e' 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-c1662d12-7ee9-4031-8070-3dc2579df3f7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c1662d12-7ee9-4031-8070-3dc2579df3f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b1764f9-57e7-444b-9bf1-ae31eb84821a' class='xr-var-data-in' type='checkbox'><label for='data-7b1764f9-57e7-444b-9bf1-ae31eb84821a' 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'>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-d263c776-0256-4f1d-9b5a-f39c73de5249' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d263c776-0256-4f1d-9b5a-f39c73de5249' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4770a577-9fcf-4c06-aeab-cdec69fb46b6' class='xr-var-data-in' type='checkbox'><label for='data-4770a577-9fcf-4c06-aeab-cdec69fb46b6' 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-aa750163-fded-4fdc-b208-204fe317b46f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa750163-fded-4fdc-b208-204fe317b46f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d958287f-b76b-4fdd-8ab6-51670c9a4e8a' class='xr-var-data-in' type='checkbox'><label for='data-d958287f-b76b-4fdd-8ab6-51670c9a4e8a' 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-98eb011f-0345-4a81-93ff-4da0db539785' class='xr-section-summary-in' type='checkbox'  checked><label for='section-98eb011f-0345-4a81-93ff-4da0db539785' class='xr-section-summary' >Data variables: <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>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-63b8db8c-2130-4a51-8bbc-68bea046d354' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-63b8db8c-2130-4a51-8bbc-68bea046d354' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf85037c-a42d-4f91-8c2d-335c604efe51' class='xr-var-data-in' type='checkbox'><label for='data-bf85037c-a42d-4f91-8c2d-335c604efe51' 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>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-27442262-e026-4a83-8fc6-7567cee0226e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-27442262-e026-4a83-8fc6-7567cee0226e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26bbc789-e689-4a62-89ec-5eae30946f00' class='xr-var-data-in' type='checkbox'><label for='data-26bbc789-e689-4a62-89ec-5eae30946f00' 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>units :</span></dt><dd>kg m-2 s-1</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>original_name :</span></dt><dd>PRCP</dd><dt><span>original_units :</span></dt><dd>kg/m**2/s</dd><dt><span>history :</span></dt><dd>2011-04-23T09:11:46Z altered by CMOR: Converted units from &#x27;kg/m**2/s&#x27; to &#x27;kg m-2 s-1&#x27;. 2011-04-23T09:11:46Z altered by CMOR: replaced missing value flag (-999) with standard missing value (1e+20). 2011-04-23T09:11:46Z altered by CMOR: Inverted axis: lat.</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MIROC5_historical_r0i0p0.nc areacella: areacella_fx_MIROC5_historical_r0i0p0.nc</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-8776a08a-b603-4180-9889-7a5cd8b1f900' class='xr-section-summary-in' type='checkbox'  ><label for='section-8776a08a-b603-4180-9889-7a5cd8b1f900' class='xr-section-summary' >Attributes: <span>(29)</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-1.4</dd><dt><span>history :</span></dt><dd>Fri Jul 22 11:03:06 2022: cdo remapnn,grid1.des gcmensemble.nc gcmensemble_remap.nc\n",
       "Fri Jul 22 11:00:06 2022: cdo divc,3 final.nc gcmensemble.nc\n",
       "Fri Jul 22 10:53:46 2022: cdo -add gcm_miroc_remap1.nc -add gcm_mpi_remap.nc gcm_noresm_remap.nc final.nc\n",
       "Fri Jul 22 10:53:11 2022: cdo selyear,1850/2005 gcm_miroc_remap.nc gcm_miroc_remap1.nc\n",
       "Thu Jul 07 18:16:03 2022: cdo remapnn,grid1.des pr_Amon_MIROC5_historical_r1i1p1_185001-201212.nc gcm_miroc_remap.nc\n",
       "2011-04-23T09:11:46Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>source :</span></dt><dd>MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); ocean: COCO (COCO4.5, 256x224 L50); sea ice: COCO (COCO4.5); land: MATSIRO (MATSIRO, L6); aerosols: SPRINTARS (SPRINTARS 5.00, T85L40)</dd><dt><span>institution :</span></dt><dd>AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan), NIES (National Institute for Environmental Studies, Ibaraki, Japan), JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan)</dd><dt><span>institute_id :</span></dt><dd>MIROC</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>MIROC5</dd><dt><span>forcing :</span></dt><dd>GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG includes CO2, N2O, methane, and fluorocarbons; Oz includes OH and H2O2; LU excludes change in lake fraction)</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>150015.0</dd><dt><span>contact :</span></dt><dd>Masahiro Watanabe (hiro@aori.u-tokyo.ac.jp), Seita Emori (emori@nies.go.jp), Masayoshi Ishii (ism@jamstec.go.jp), Masahide Kimoto (kimoto@aori.u-tokyo.ac.jp)</dd><dt><span>references :</span></dt><dd>Watanabe et al., 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 6312-6335</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>a906be44-c850-4f0c-b8c4-2b165051669a</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>2011-04-23T09:11:46Z</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (31 January 2011) 53b766a395ac41696af40aab76a49ae5</dd><dt><span>title :</span></dt><dd>MIROC5 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>2.5.6</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, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-01-16T12:00:00 ... 2005-11-16\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",
       "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",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/29)\n",
       "    CDI:                    Climate Data Interface version 1.9.9rc1 (https://...\n",
       "    Conventions:            CF-1.4\n",
       "    history:                Fri Jul 22 11:03:06 2022: cdo remapnn,grid1.des g...\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    ...                     ...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6\n",
       "    CDO:                    Climate Data Operators version 1.9.9rc1 (https://..."
      ]
     },
     "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, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-06-16 ... 2005-09-16\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",
       "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",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/29)\n",
       "    CDI:                    Climate Data Interface version 1.9.9rc1 (https://...\n",
       "    Conventions:            CF-1.4\n",
       "    history:                Fri Jul 22 11:03:06 2022: cdo remapnn,grid1.des g...\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    ...                     ...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6\n",
       "    CDO:                    Climate Data Operators version 1.9.9rc1 (https://...</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-3f8057a2-2302-46e3-aafe-7149186fc13f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3f8057a2-2302-46e3-aafe-7149186fc13f' 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'>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-e00312a8-ecaa-485e-a8d1-f0182abe6d08' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e00312a8-ecaa-485e-a8d1-f0182abe6d08' 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-fff6c2d4-8c86-4deb-8d4f-f11ec24c9ddc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fff6c2d4-8c86-4deb-8d4f-f11ec24c9ddc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7f227db-8bd1-4847-97ff-28e4cae94340' class='xr-var-data-in' type='checkbox'><label for='data-b7f227db-8bd1-4847-97ff-28e4cae94340' 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'>float32</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-64826850-a5a4-4b76-b837-52fd29419eff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64826850-a5a4-4b76-b837-52fd29419eff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a08e9ad8-09e4-4a04-b7bc-03b323358e7e' class='xr-var-data-in' type='checkbox'><label for='data-a08e9ad8-09e4-4a04-b7bc-03b323358e7e' 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-46f7eda0-1ead-412a-b18c-af27f4843564' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-46f7eda0-1ead-412a-b18c-af27f4843564' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7792942-cfe6-4769-a0af-88010e02ed5c' class='xr-var-data-in' type='checkbox'><label for='data-c7792942-cfe6-4769-a0af-88010e02ed5c' 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-a7ff3434-22b1-4602-be0d-61ffcee0a2b6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a7ff3434-22b1-4602-be0d-61ffcee0a2b6' class='xr-section-summary' >Data variables: <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>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-0a041124-47cf-4348-8a79-32e2e0970045' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0a041124-47cf-4348-8a79-32e2e0970045' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd72c8bd-2fc7-4c63-8027-6175b915550f' class='xr-var-data-in' type='checkbox'><label for='data-cd72c8bd-2fc7-4c63-8027-6175b915550f' 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>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-f2f607b9-e43a-4ca8-81b5-8d4ba83ea055' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f2f607b9-e43a-4ca8-81b5-8d4ba83ea055' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2750c54c-c155-4e39-8052-db19dad39fb4' class='xr-var-data-in' type='checkbox'><label for='data-2750c54c-c155-4e39-8052-db19dad39fb4' 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>units :</span></dt><dd>kg m-2 s-1</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>original_name :</span></dt><dd>PRCP</dd><dt><span>original_units :</span></dt><dd>kg/m**2/s</dd><dt><span>history :</span></dt><dd>2011-04-23T09:11:46Z altered by CMOR: Converted units from &#x27;kg/m**2/s&#x27; to &#x27;kg m-2 s-1&#x27;. 2011-04-23T09:11:46Z altered by CMOR: replaced missing value flag (-999) with standard missing value (1e+20). 2011-04-23T09:11:46Z altered by CMOR: Inverted axis: lat.</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MIROC5_historical_r0i0p0.nc areacella: areacella_fx_MIROC5_historical_r0i0p0.nc</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-d8b56a50-c0f9-488e-9f09-8735594ba9f8' class='xr-section-summary-in' type='checkbox'  ><label for='section-d8b56a50-c0f9-488e-9f09-8735594ba9f8' class='xr-section-summary' >Attributes: <span>(29)</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-1.4</dd><dt><span>history :</span></dt><dd>Fri Jul 22 11:03:06 2022: cdo remapnn,grid1.des gcmensemble.nc gcmensemble_remap.nc\n",
       "Fri Jul 22 11:00:06 2022: cdo divc,3 final.nc gcmensemble.nc\n",
       "Fri Jul 22 10:53:46 2022: cdo -add gcm_miroc_remap1.nc -add gcm_mpi_remap.nc gcm_noresm_remap.nc final.nc\n",
       "Fri Jul 22 10:53:11 2022: cdo selyear,1850/2005 gcm_miroc_remap.nc gcm_miroc_remap1.nc\n",
       "Thu Jul 07 18:16:03 2022: cdo remapnn,grid1.des pr_Amon_MIROC5_historical_r1i1p1_185001-201212.nc gcm_miroc_remap.nc\n",
       "2011-04-23T09:11:46Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>source :</span></dt><dd>MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); ocean: COCO (COCO4.5, 256x224 L50); sea ice: COCO (COCO4.5); land: MATSIRO (MATSIRO, L6); aerosols: SPRINTARS (SPRINTARS 5.00, T85L40)</dd><dt><span>institution :</span></dt><dd>AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan), NIES (National Institute for Environmental Studies, Ibaraki, Japan), JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan)</dd><dt><span>institute_id :</span></dt><dd>MIROC</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>MIROC5</dd><dt><span>forcing :</span></dt><dd>GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG includes CO2, N2O, methane, and fluorocarbons; Oz includes OH and H2O2; LU excludes change in lake fraction)</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>150015.0</dd><dt><span>contact :</span></dt><dd>Masahiro Watanabe (hiro@aori.u-tokyo.ac.jp), Seita Emori (emori@nies.go.jp), Masayoshi Ishii (ism@jamstec.go.jp), Masahide Kimoto (kimoto@aori.u-tokyo.ac.jp)</dd><dt><span>references :</span></dt><dd>Watanabe et al., 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 6312-6335</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>a906be44-c850-4f0c-b8c4-2b165051669a</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>2011-04-23T09:11:46Z</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (31 January 2011) 53b766a395ac41696af40aab76a49ae5</dd><dt><span>title :</span></dt><dd>MIROC5 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>2.5.6</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, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-06-16 ... 2005-09-16\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",
       "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",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/29)\n",
       "    CDI:                    Climate Data Interface version 1.9.9rc1 (https://...\n",
       "    Conventions:            CF-1.4\n",
       "    history:                Fri Jul 22 11:03:06 2022: cdo remapnn,grid1.des g...\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    ...                     ...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6\n",
       "    CDO:                    Climate Data Operators version 1.9.9rc1 (https://..."
      ]
     },
     "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": "18269e45",
   "metadata": {},
   "outputs": [
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (lat: 40, lon: 32)&gt;\n",
       "array([[0.00011733, 0.0001171 , 0.00011552, ..., 0.00014856, 0.00015397,\n",
       "        0.00015701],\n",
       "       [0.00012046, 0.00012023, 0.00012027, ..., 0.00016522, 0.00014499,\n",
       "        0.00014804],\n",
       "       [0.00012046, 0.00012023, 0.00012027, ..., 0.00016522, 0.00014499,\n",
       "        0.00014804],\n",
       "       ...,\n",
       "       [0.00024819, 0.00027803, 0.00028471, ..., 0.0002209 , 0.00022877,\n",
       "        0.00020397],\n",
       "       [0.00024819, 0.00027803, 0.00028471, ..., 0.0002209 , 0.00022877,\n",
       "        0.00020397],\n",
       "       [0.00024819, 0.00027803, 0.00028471, ..., 0.0002209 , 0.00022877,\n",
       "        0.00020397]], 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'>'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-a1ad49da-6728-409b-94e4-8fc8ce9ede4b' class='xr-array-in' type='checkbox' checked><label for='section-a1ad49da-6728-409b-94e4-8fc8ce9ede4b' 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>0.0001173 0.0001171 0.0001155 ... 0.0002209 0.0002288 0.000204</span></div><div class='xr-array-data'><pre>array([[0.00011733, 0.0001171 , 0.00011552, ..., 0.00014856, 0.00015397,\n",
       "        0.00015701],\n",
       "       [0.00012046, 0.00012023, 0.00012027, ..., 0.00016522, 0.00014499,\n",
       "        0.00014804],\n",
       "       [0.00012046, 0.00012023, 0.00012027, ..., 0.00016522, 0.00014499,\n",
       "        0.00014804],\n",
       "       ...,\n",
       "       [0.00024819, 0.00027803, 0.00028471, ..., 0.0002209 , 0.00022877,\n",
       "        0.00020397],\n",
       "       [0.00024819, 0.00027803, 0.00028471, ..., 0.0002209 , 0.00022877,\n",
       "        0.00020397],\n",
       "       [0.00024819, 0.00027803, 0.00028471, ..., 0.0002209 , 0.00022877,\n",
       "        0.00020397]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-1c4595e9-92bb-4c64-a5cd-8dec48bfc106' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1c4595e9-92bb-4c64-a5cd-8dec48bfc106' 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-c6404fcb-720e-49cd-9f55-914ae2742e98' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c6404fcb-720e-49cd-9f55-914ae2742e98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a495248-150d-4fb2-8566-bf1f6bc1130c' class='xr-var-data-in' type='checkbox'><label for='data-8a495248-150d-4fb2-8566-bf1f6bc1130c' 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-89285346-34eb-45e6-b648-64a4061acc5b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89285346-34eb-45e6-b648-64a4061acc5b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83c1e895-0368-4bfe-baf5-5b924b3f8a3d' class='xr-var-data-in' type='checkbox'><label for='data-83c1e895-0368-4bfe-baf5-5b924b3f8a3d' 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-b6978a83-a024-43ef-8ac4-e22b783a0ad8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b6978a83-a024-43ef-8ac4-e22b783a0ad8' 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([[0.00011733, 0.0001171 , 0.00011552, ..., 0.00014856, 0.00015397,\n",
       "        0.00015701],\n",
       "       [0.00012046, 0.00012023, 0.00012027, ..., 0.00016522, 0.00014499,\n",
       "        0.00014804],\n",
       "       [0.00012046, 0.00012023, 0.00012027, ..., 0.00016522, 0.00014499,\n",
       "        0.00014804],\n",
       "       ...,\n",
       "       [0.00024819, 0.00027803, 0.00028471, ..., 0.0002209 , 0.00022877,\n",
       "        0.00020397],\n",
       "       [0.00024819, 0.00027803, 0.00028471, ..., 0.0002209 , 0.00022877,\n",
       "        0.00020397],\n",
       "       [0.00024819, 0.00027803, 0.00028471, ..., 0.0002209 , 0.00022877,\n",
       "        0.00020397]], 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": 17,
     "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": 18,
   "id": "6f88bd72",
   "metadata": {},
   "outputs": [
    {
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       "\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-icon-database,\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (lat: 40, lon: 32)&gt;\n",
       "array([[10.13700748, 10.11715934,  9.98064454, ..., 12.83584619,\n",
       "        13.30275424, 13.56588146],\n",
       "       [10.40811595, 10.38825964, 10.39161345, ..., 14.27526204,\n",
       "        12.52745795, 12.79058391],\n",
       "       [10.40811595, 10.38825964, 10.39161345, ..., 14.27526204,\n",
       "        12.52745795, 12.79058391],\n",
       "       ...,\n",
       "       [21.44322759, 24.02177174, 24.5989915 , ..., 19.08538481,\n",
       "        19.76553979, 17.62266895],\n",
       "       [21.44322759, 24.02177174, 24.5989915 , ..., 19.08538481,\n",
       "        19.76553979, 17.62266895],\n",
       "       [21.44322759, 24.02177174, 24.5989915 , ..., 19.08538481,\n",
       "        19.76553979, 17.62266895]])\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'>'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-54633e4d-120c-498c-ab9c-ee71169a7bf9' class='xr-array-in' type='checkbox' checked><label for='section-54633e4d-120c-498c-ab9c-ee71169a7bf9' 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>10.14 10.12 9.981 9.981 9.981 10.68 ... 19.09 19.09 19.09 19.77 17.62</span></div><div class='xr-array-data'><pre>array([[10.13700748, 10.11715934,  9.98064454, ..., 12.83584619,\n",
       "        13.30275424, 13.56588146],\n",
       "       [10.40811595, 10.38825964, 10.39161345, ..., 14.27526204,\n",
       "        12.52745795, 12.79058391],\n",
       "       [10.40811595, 10.38825964, 10.39161345, ..., 14.27526204,\n",
       "        12.52745795, 12.79058391],\n",
       "       ...,\n",
       "       [21.44322759, 24.02177174, 24.5989915 , ..., 19.08538481,\n",
       "        19.76553979, 17.62266895],\n",
       "       [21.44322759, 24.02177174, 24.5989915 , ..., 19.08538481,\n",
       "        19.76553979, 17.62266895],\n",
       "       [21.44322759, 24.02177174, 24.5989915 , ..., 19.08538481,\n",
       "        19.76553979, 17.62266895]])</pre></div></div></li><li class='xr-section-item'><input id='section-b983aedb-c2b6-478f-9be7-0c83f20bf484' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b983aedb-c2b6-478f-9be7-0c83f20bf484' 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-d140f796-ab8f-4283-beca-8844d12afd59' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d140f796-ab8f-4283-beca-8844d12afd59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-696628d2-a1ef-4854-8eb4-f914b2a94018' class='xr-var-data-in' type='checkbox'><label for='data-696628d2-a1ef-4854-8eb4-f914b2a94018' 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-59673c62-4d7e-45cc-b40a-8efa1c7d6dde' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59673c62-4d7e-45cc-b40a-8efa1c7d6dde' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06f049f2-188d-435d-aa10-9f3751571ede' class='xr-var-data-in' type='checkbox'><label for='data-06f049f2-188d-435d-aa10-9f3751571ede' 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-a85aac1e-9a81-4272-b112-09818b9b5a06' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a85aac1e-9a81-4272-b112-09818b9b5a06' 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([[10.13700748, 10.11715934,  9.98064454, ..., 12.83584619,\n",
       "        13.30275424, 13.56588146],\n",
       "       [10.40811595, 10.38825964, 10.39161345, ..., 14.27526204,\n",
       "        12.52745795, 12.79058391],\n",
       "       [10.40811595, 10.38825964, 10.39161345, ..., 14.27526204,\n",
       "        12.52745795, 12.79058391],\n",
       "       ...,\n",
       "       [21.44322759, 24.02177174, 24.5989915 , ..., 19.08538481,\n",
       "        19.76553979, 17.62266895],\n",
       "       [21.44322759, 24.02177174, 24.5989915 , ..., 19.08538481,\n",
       "        19.76553979, 17.62266895],\n",
       "       [21.44322759, 24.02177174, 24.5989915 , ..., 19.08538481,\n",
       "        19.76553979, 17.62266895]])\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": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gcmmiroc = jjas_mean*86400\n",
    "gcmmiroc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "6c5c5811",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
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       "}\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",
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       "\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",
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       "  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",
       "       [10.84340476, 13.90055524, 14.30637244, ..., 10.6039748 ,\n",
       "         9.89712855,  6.27770862],\n",
       "       [11.22121532, 15.42795635, 17.4395362 , ..., 11.55782581,\n",
       "        11.09886968,  7.67135091],\n",
       "       [13.59089017, 17.84493252, 20.11085867, ..., 12.61037261,\n",
       "        12.29816152,  9.05172749]])\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'></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-55f26011-6b76-4123-be42-33795c32c0b2' class='xr-array-in' type='checkbox' checked><label for='section-55f26011-6b76-4123-be42-33795c32c0b2' 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 ... 17.69 14.49 13.57 12.61 12.3 9.052</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",
       "       [10.84340476, 13.90055524, 14.30637244, ..., 10.6039748 ,\n",
       "         9.89712855,  6.27770862],\n",
       "       [11.22121532, 15.42795635, 17.4395362 , ..., 11.55782581,\n",
       "        11.09886968,  7.67135091],\n",
       "       [13.59089017, 17.84493252, 20.11085867, ..., 12.61037261,\n",
       "        12.29816152,  9.05172749]])</pre></div></div></li><li class='xr-section-item'><input id='section-c3be9a95-d9b9-4531-86fb-376df2f287f6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c3be9a95-d9b9-4531-86fb-376df2f287f6' 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-0be2117e-5b2d-47e4-9aa9-740902ab3cca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0be2117e-5b2d-47e4-9aa9-740902ab3cca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b55623cc-d6da-4736-b6e0-b2170e84a7ea' class='xr-var-data-in' type='checkbox'><label for='data-b55623cc-d6da-4736-b6e0-b2170e84a7ea' 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-f0a30ae6-16f4-4f75-b3de-1fd8a738b543' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f0a30ae6-16f4-4f75-b3de-1fd8a738b543' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-deac32cb-149e-45fd-80ca-ab46c533d542' class='xr-var-data-in' type='checkbox'><label for='data-deac32cb-149e-45fd-80ca-ab46c533d542' 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-1340a09f-913b-40b0-8ad4-f1b028bc1f13' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1340a09f-913b-40b0-8ad4-f1b028bc1f13' 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",
       "       [10.84340476, 13.90055524, 14.30637244, ..., 10.6039748 ,\n",
       "         9.89712855,  6.27770862],\n",
       "       [11.22121532, 15.42795635, 17.4395362 , ..., 11.55782581,\n",
       "        11.09886968,  7.67135091],\n",
       "       [13.59089017, 17.84493252, 20.11085867, ..., 12.61037261,\n",
       "        12.29816152,  9.05172749]])\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": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bias = gcmmiroc - cru\n",
    "bias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "445388ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
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       "}\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",
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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 (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",
       "       [102.29798121, 137.3407559 , 138.99642401, ..., 125.02608382,\n",
       "        100.29100237,  55.33477802],\n",
       "       [109.77501331, 179.52394437, 243.5874722 , ..., 153.54015569,\n",
       "        128.06383003,  77.08879246],\n",
       "       [173.08082227, 288.90071258, 448.08964914, ..., 194.7544224 ,\n",
       "        164.69182457, 105.60948911]])\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'></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-9ed40fd4-49ab-473b-bc9c-5b1f8a67d13d' class='xr-array-in' type='checkbox' checked><label for='section-9ed40fd4-49ab-473b-bc9c-5b1f8a67d13d' 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 ... 459.6 315.5 245.9 194.8 164.7 105.6</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",
       "       [102.29798121, 137.3407559 , 138.99642401, ..., 125.02608382,\n",
       "        100.29100237,  55.33477802],\n",
       "       [109.77501331, 179.52394437, 243.5874722 , ..., 153.54015569,\n",
       "        128.06383003,  77.08879246],\n",
       "       [173.08082227, 288.90071258, 448.08964914, ..., 194.7544224 ,\n",
       "        164.69182457, 105.60948911]])</pre></div></div></li><li class='xr-section-item'><input id='section-e72bd634-4df6-4562-9536-c2489e3c3810' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e72bd634-4df6-4562-9536-c2489e3c3810' 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-c208278e-0997-4477-912c-67b20fac00dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c208278e-0997-4477-912c-67b20fac00dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2936d716-b5f3-45f6-b91c-638ed6aa64d0' class='xr-var-data-in' type='checkbox'><label for='data-2936d716-b5f3-45f6-b91c-638ed6aa64d0' 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-fde965ce-5c06-43a5-a5c7-503db8ba04e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fde965ce-5c06-43a5-a5c7-503db8ba04e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f634d489-cbed-4a4f-b3a5-9e3caa1c21fe' class='xr-var-data-in' type='checkbox'><label for='data-f634d489-cbed-4a4f-b3a5-9e3caa1c21fe' 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-7d909c65-caf0-4d97-8bf8-e6ddad6d0a85' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7d909c65-caf0-4d97-8bf8-e6ddad6d0a85' 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",
       "       [102.29798121, 137.3407559 , 138.99642401, ..., 125.02608382,\n",
       "        100.29100237,  55.33477802],\n",
       "       [109.77501331, 179.52394437, 243.5874722 , ..., 153.54015569,\n",
       "        128.06383003,  77.08879246],\n",
       "       [173.08082227, 288.90071258, 448.08964914, ..., 194.7544224 ,\n",
       "        164.69182457, 105.60948911]])\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": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bias_percentage = ((gcmmiroc - cru)/cru)*100\n",
    "bias_percentage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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",
    "plt.rcParams['font.size'] = '16'\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",
    "plt.title('Seasonal Bias(GCM ensemble avg-CRU)',fontsize=17)\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/Seasonal Bias(gcm ensemble avg-cru).png\")\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "9003db92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x972 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=(16,13.5))\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=0.7, 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 ensemble avg-CRU)')\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/Seasonal Bias_percentage(gcm ensemble avg-cru).png\")\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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": 23,
     "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": "0035ab2b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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