Seasonal Bias(Miroc5-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",
   "execution_count": 2,
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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-c5430fa3-974e-4d46-9d8f-ba02051537f1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c5430fa3-974e-4d46-9d8f-ba02051537f1' 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-6d069671-d2b6-4fe0-b86d-6f39bd4cf49f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6d069671-d2b6-4fe0-b86d-6f39bd4cf49f' 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-ec80df28-f95f-42bd-a28f-6efa9674779f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ec80df28-f95f-42bd-a28f-6efa9674779f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b1ae693-6d8d-48ba-a86b-0f79a3121cfa' class='xr-var-data-in' type='checkbox'><label for='data-8b1ae693-6d8d-48ba-a86b-0f79a3121cfa' 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-0bb93a91-bfe8-4309-a1df-3ee01feaefc5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0bb93a91-bfe8-4309-a1df-3ee01feaefc5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13e1c688-2096-4c80-8f84-8082165a4bad' class='xr-var-data-in' type='checkbox'><label for='data-13e1c688-2096-4c80-8f84-8082165a4bad' 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-708a4cc5-c2ea-42ef-a371-3d575e66b41a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-708a4cc5-c2ea-42ef-a371-3d575e66b41a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4619218a-e863-4508-835c-8c7978a8f461' class='xr-var-data-in' type='checkbox'><label for='data-4619218a-e863-4508-835c-8c7978a8f461' 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-c3019fed-aad9-4fe1-8ab7-9bac7e4fbcec' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c3019fed-aad9-4fe1-8ab7-9bac7e4fbcec' 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-12d2a217-337b-40db-8709-9f3b2f269b9f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-12d2a217-337b-40db-8709-9f3b2f269b9f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-026c5e96-3455-4211-9cb4-bc763a4b16c9' class='xr-var-data-in' type='checkbox'><label for='data-026c5e96-3455-4211-9cb4-bc763a4b16c9' 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-94292c3f-80a2-42f4-bf7b-84e5ce96c910' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94292c3f-80a2-42f4-bf7b-84e5ce96c910' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59242a08-73d5-4786-816c-996c843c9be0' class='xr-var-data-in' type='checkbox'><label for='data-59242a08-73d5-4786-816c-996c843c9be0' 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-5d865303-67fd-408c-bd2a-be5b07ef011c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5d865303-67fd-408c-bd2a-be5b07ef011c' 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>"
      ],
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       "<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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    "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-86eb076f-c032-4653-a782-cc52677bd5a6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-86eb076f-c032-4653-a782-cc52677bd5a6' 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-32877bda-f2a1-4f05-a2c5-971fece42ab7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-32877bda-f2a1-4f05-a2c5-971fece42ab7' 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-22ba2c3c-23e3-4f2a-b82c-f1e4735351b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-22ba2c3c-23e3-4f2a-b82c-f1e4735351b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7860c091-b94f-40a6-a9ed-7e524458341c' class='xr-var-data-in' type='checkbox'><label for='data-7860c091-b94f-40a6-a9ed-7e524458341c' 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-36acb2fa-0436-4614-bf1e-108d052e76c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36acb2fa-0436-4614-bf1e-108d052e76c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-375f8375-ccf3-4aba-95bb-1bb7bbd18fb3' class='xr-var-data-in' type='checkbox'><label for='data-375f8375-ccf3-4aba-95bb-1bb7bbd18fb3' 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-d36c541b-2771-4f95-9b2b-0862cdcba084' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d36c541b-2771-4f95-9b2b-0862cdcba084' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-271b0ae5-1b2f-49e2-aaac-122b50a1e05c' class='xr-var-data-in' type='checkbox'><label for='data-271b0ae5-1b2f-49e2-aaac-122b50a1e05c' 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-7660703e-6c36-44ed-ab71-8d88a7b7959a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7660703e-6c36-44ed-ab71-8d88a7b7959a' 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-5b5ec79f-d23a-42ff-86d3-5cfcf8a9e8b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5b5ec79f-d23a-42ff-86d3-5cfcf8a9e8b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02270be4-1278-401c-b67e-f43040b64b68' class='xr-var-data-in' type='checkbox'><label for='data-02270be4-1278-401c-b67e-f43040b64b68' 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-65e65cf4-a7cc-4da3-a6f5-ecc1138db42e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65e65cf4-a7cc-4da3-a6f5-ecc1138db42e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b293da09-cdff-41ff-8959-c827a4de3343' class='xr-var-data-in' type='checkbox'><label for='data-b293da09-cdff-41ff-8959-c827a4de3343' 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-fed06847-9dc7-4571-93f7-c202ba0060ef' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fed06847-9dc7-4571-93f7-c202ba0060ef' 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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       "\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-0a6af9d2-3eef-482a-9c5f-7587b04c6857' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0a6af9d2-3eef-482a-9c5f-7587b04c6857' 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-a37c9a16-9e25-4471-b61b-e85ac30c0dc3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a37c9a16-9e25-4471-b61b-e85ac30c0dc3' 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-013c32ac-3559-4af8-b19f-bea8b25284dc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-013c32ac-3559-4af8-b19f-bea8b25284dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ec0923c-10f1-4f25-bbf9-5bfce66aeb2d' class='xr-var-data-in' type='checkbox'><label for='data-0ec0923c-10f1-4f25-bbf9-5bfce66aeb2d' 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-44905b76-8e1b-40aa-980e-d9a3abaab831' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-44905b76-8e1b-40aa-980e-d9a3abaab831' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cbbb81d0-6580-439a-897b-03887eafc0cd' class='xr-var-data-in' type='checkbox'><label for='data-cbbb81d0-6580-439a-897b-03887eafc0cd' 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-b91682a6-81dc-4689-bc48-a8d79f193941' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b91682a6-81dc-4689-bc48-a8d79f193941' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e5735aec-cedb-4f5c-b2c6-73a0e6c3d83a' class='xr-var-data-in' type='checkbox'><label for='data-e5735aec-cedb-4f5c-b2c6-73a0e6c3d83a' 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-b55f16f0-6f7a-4159-9c9d-8dea5b757c94' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b55f16f0-6f7a-4159-9c9d-8dea5b757c94' 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-4abe23d3-5ece-41d3-a53f-f8c20f80599a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4abe23d3-5ece-41d3-a53f-f8c20f80599a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-794706b5-cfda-4177-93fa-e548f8aad76c' class='xr-var-data-in' type='checkbox'><label for='data-794706b5-cfda-4177-93fa-e548f8aad76c' 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-cd39c412-42cf-4a67-994f-07470ec7fea6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd39c412-42cf-4a67-994f-07470ec7fea6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6ff05ec-e33e-433d-82bf-19d9879043ee' class='xr-var-data-in' type='checkbox'><label for='data-c6ff05ec-e33e-433d-82bf-19d9879043ee' 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-d55ef245-72bc-4957-aeaf-1aa18799881b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d55ef245-72bc-4957-aeaf-1aa18799881b' 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": "735515f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#for i in data.latitude.values:\n",
    " #   print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fd310367",
   "metadata": {},
   "outputs": [],
   "source": [
    "#for i in data.longitude.values:\n",
    " #   print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2a9644bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       ".xr-attrs dt,\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
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       "\n",
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       "\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
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       "  height: 1.5em !important;\n",
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       "  fill: currentColor;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (lon: 16, lat: 20, time: 100)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 86.25 86.75 87.25 87.75 ... 92.25 92.75 93.25 93.75\n",
       "  * lat      (lat) float32 18.25 18.75 19.25 19.75 ... 26.25 26.75 27.25 27.75\n",
       "  * time     (time) datetime64[ns] 1981-06-16 1981-07-16 ... 2005-09-16\n",
       "Data variables:\n",
       "    pre      (time, lat, lon) float32 nan nan nan nan ... 48.9 76.6 108.2 132.9\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-cf72fea7-0613-4c97-9b82-3aafc854511b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cf72fea7-0613-4c97-9b82-3aafc854511b' 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>: 16</li><li><span class='xr-has-index'>lat</span>: 20</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-f34d7fd7-0f37-4abf-9aca-ab1dbc28274e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f34d7fd7-0f37-4abf-9aca-ab1dbc28274e' 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'>86.25 86.75 87.25 ... 93.25 93.75</div><input id='attrs-5321eb07-702f-478d-8369-2fb71560b920' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5321eb07-702f-478d-8369-2fb71560b920' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2068e83-245e-4e1c-91f6-ad63a775a261' class='xr-var-data-in' type='checkbox'><label for='data-a2068e83-245e-4e1c-91f6-ad63a775a261' 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([86.25, 86.75, 87.25, 87.75, 88.25, 88.75, 89.25, 89.75, 90.25, 90.75,\n",
       "       91.25, 91.75, 92.25, 92.75, 93.25, 93.75], 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'>18.25 18.75 19.25 ... 27.25 27.75</div><input id='attrs-1c754d35-f20b-419a-b1c8-1dee537456a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c754d35-f20b-419a-b1c8-1dee537456a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ef7718f-19b3-4bc4-a19e-c46bfc0cea32' class='xr-var-data-in' type='checkbox'><label for='data-1ef7718f-19b3-4bc4-a19e-c46bfc0cea32' 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([18.25, 18.75, 19.25, 19.75, 20.25, 20.75, 21.25, 21.75, 22.25, 22.75,\n",
       "       23.25, 23.75, 24.25, 24.75, 25.25, 25.75, 26.25, 26.75, 27.25, 27.75],\n",
       "      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-18788cf0-0e52-4411-9d98-24ff27ec615b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18788cf0-0e52-4411-9d98-24ff27ec615b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-416e2d30-d08e-4727-9d2f-558f6e773fbf' class='xr-var-data-in' type='checkbox'><label for='data-416e2d30-d08e-4727-9d2f-558f6e773fbf' 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",
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       "       &#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",
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       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-14005c23-eb39-4ce5-ad05-672a9ed3435d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-14005c23-eb39-4ce5-ad05-672a9ed3435d' 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-063f4b9d-cc49-4015-8c76-8d915bf0d5ce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-063f4b9d-cc49-4015-8c76-8d915bf0d5ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-478aa36b-e20e-4955-9524-c3015abf8bd5' class='xr-var-data-in' type='checkbox'><label for='data-478aa36b-e20e-4955-9524-c3015abf8bd5' 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, ...,         nan,  594.3     ],\n",
       "        ...,\n",
       "        [ 197.2     ,  265.1     , ...,  205.8     ,  293.5     ],\n",
       "        [ 138.3     ,   90.6     , ...,  166.6     ,  224.      ]],\n",
       "\n",
       "       [[        nan,         nan, ...,         nan,         nan],\n",
       "        [        nan,         nan, ...,         nan, 2512.1     ],\n",
       "        ...,\n",
       "        [ 428.6     ,  508.80002 , ...,  370.9     ,  497.1     ],\n",
       "        [ 362.9     ,  199.6     , ...,  269.1     ,  354.1     ]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[        nan,         nan, ...,         nan,         nan],\n",
       "        [        nan,         nan, ...,         nan, 1151.9     ],\n",
       "        ...,\n",
       "        [ 282.30002 ,  330.30002 , ...,  203.1     ,  279.5     ],\n",
       "        [ 264.6     ,  142.40001 , ...,  162.2     ,  209.7     ]],\n",
       "\n",
       "       [[        nan,         nan, ...,         nan,         nan],\n",
       "        [        nan,         nan, ...,         nan,  861.3     ],\n",
       "        ...,\n",
       "        [ 215.6     ,  264.5     , ...,  127.      ,  153.90001 ],\n",
       "        [ 167.      ,   80.3     , ...,  108.200005,  132.90001 ]]],\n",
       "      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-0038a4fc-7b2e-4e99-a222-18bd9dda6cee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0038a4fc-7b2e-4e99-a222-18bd9dda6cee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7796ce1e-dfe8-4ba5-9a4d-c115379e1d2d' class='xr-var-data-in' type='checkbox'><label for='data-7796ce1e-dfe8-4ba5-9a4d-c115379e1d2d' 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],\n",
       "        [nan, nan, ..., nan,  7.],\n",
       "        ...,\n",
       "        [ 8.,  8., ...,  8.,  8.],\n",
       "        [ 8.,  8., ...,  8.,  8.]],\n",
       "\n",
       "       [[nan, nan, ..., nan, nan],\n",
       "        [nan, nan, ..., nan,  5.],\n",
       "        ...,\n",
       "        [ 8.,  8., ...,  8.,  8.],\n",
       "        [ 8.,  8., ...,  8.,  8.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[nan, nan, ..., nan, nan],\n",
       "        [nan, nan, ..., nan,  3.],\n",
       "        ...,\n",
       "        [ 5.,  6., ...,  6.,  6.],\n",
       "        [ 5.,  5., ...,  7.,  8.]],\n",
       "\n",
       "       [[nan, nan, ..., nan, nan],\n",
       "        [nan, nan, ..., nan,  6.],\n",
       "        ...,\n",
       "        [ 7.,  8., ...,  8.,  8.],\n",
       "        [ 7.,  7., ...,  8.,  8.]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a3d33113-ddbf-4547-8c8e-4c7daa0f907f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a3d33113-ddbf-4547-8c8e-4c7daa0f907f' 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: 16, lat: 20, time: 100)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 86.25 86.75 87.25 87.75 ... 92.25 92.75 93.25 93.75\n",
       "  * lat      (lat) float32 18.25 18.75 19.25 19.75 ... 26.25 26.75 27.25 27.75\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": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "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": 8,
   "id": "91600dec",
   "metadata": {},
   "outputs": [
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       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 100, lat: 40, lon: 32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1981-06-16 1981-07-16 ... 2005-09-16\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "Data variables:\n",
       "    pre      (time, lat, lon) float64 nan nan nan nan nan ... nan nan nan nan\n",
       "    stn      (time, lat, lon) float64 nan nan nan nan nan ... nan nan nan nan\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-6a61f476-7843-4fc9-9f8d-7be799d38d52' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6a61f476-7843-4fc9-9f8d-7be799d38d52' 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-3f5ea73a-17f0-47a0-afef-90bc13fe4623' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3f5ea73a-17f0-47a0-afef-90bc13fe4623' 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-1d6a524f-bd32-4a56-9273-a8ace6852e06' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1d6a524f-bd32-4a56-9273-a8ace6852e06' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-352767b2-7912-42e7-9996-4fdf24d6be7c' class='xr-var-data-in' type='checkbox'><label for='data-352767b2-7912-42e7-9996-4fdf24d6be7c' 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'>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-95e32ae6-1af2-4aec-963e-e6292f1f7b8d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95e32ae6-1af2-4aec-963e-e6292f1f7b8d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67768945-3226-4704-82d1-d586e9cdffa6' class='xr-var-data-in' type='checkbox'><label for='data-67768945-3226-4704-82d1-d586e9cdffa6' 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><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-dea72425-971f-4e95-af4e-50b4286e3da1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dea72425-971f-4e95-af4e-50b4286e3da1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-431de564-3274-406f-a500-1018e98121df' class='xr-var-data-in' type='checkbox'><label for='data-431de564-3274-406f-a500-1018e98121df' 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></ul></div></li><li class='xr-section-item'><input id='section-08f533d9-12b6-46f8-a3ea-15431436c721' class='xr-section-summary-in' type='checkbox'  checked><label for='section-08f533d9-12b6-46f8-a3ea-15431436c721' 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 nan ... nan nan nan nan</div><input id='attrs-002b8291-bd1e-4be6-bd04-a4d29cff2af1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-002b8291-bd1e-4be6-bd04-a4d29cff2af1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-791334c6-227e-48b1-aa22-e5361ae946b3' class='xr-var-data-in' type='checkbox'><label for='data-791334c6-227e-48b1-aa22-e5361ae946b3' 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",
       "        [         nan, 192.22500038, 211.7250042 , ..., 216.03125286,\n",
       "         256.09375095,          nan],\n",
       "        [         nan, 148.32500267, 138.92500496, ..., 192.64375401,\n",
       "         225.13125134,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan]],\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",
       "        [         nan, 279.23751545, 281.96251583, ..., 210.16875267,\n",
       "         244.75625038,          nan],\n",
       "        [         nan, 249.11250973, 209.28751087, ..., 186.10624886,\n",
       "         213.46874809,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan]],\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",
       "        [         nan, 207.20000362, 214.70000172, ..., 128.88750315,\n",
       "         142.06250715,          nan],\n",
       "        [         nan, 165.95000172, 139.5500021 , ..., 119.21250486,\n",
       "         131.83750772,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan]]])</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 ... nan nan nan nan</div><input id='attrs-a0341352-cd2e-4a06-b4ca-27d9c283f168' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0341352-cd2e-4a06-b4ca-27d9c283f168' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1dcc0129-8f7e-4e41-a3ac-284a43adb243' class='xr-var-data-in' type='checkbox'><label for='data-1dcc0129-8f7e-4e41-a3ac-284a43adb243' 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",
       "        [   nan, 8.    , 8.    , ..., 8.    , 8.    ,    nan],\n",
       "        [   nan, 8.    , 8.    , ..., 8.    , 8.    ,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\n",
       "\n",
       "       [[   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        ...,\n",
       "        [   nan, 8.    , 8.    , ..., 8.    , 8.    ,    nan],\n",
       "        [   nan, 8.    , 8.    , ..., 8.    , 8.    ,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\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",
       "        [   nan, 5.1875, 5.5625, ..., 7.25  , 7.25  ,    nan],\n",
       "        [   nan, 5.0625, 5.1875, ..., 7.75  , 7.75  ,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\n",
       "\n",
       "       [[   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        ...,\n",
       "        [   nan, 5.1875, 5.5625, ..., 6.3125, 6.4375,    nan],\n",
       "        [   nan, 5.0625, 5.1875, ..., 6.9375, 7.3125,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\n",
       "\n",
       "       [[   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        ...,\n",
       "        [   nan, 7.1875, 7.5625, ..., 8.    , 8.    ,    nan],\n",
       "        [   nan, 7.0625, 7.1875, ..., 8.    , 8.    ,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-08dbb181-d0d6-4c6b-adff-caf03c8bea13' class='xr-section-summary-in' type='checkbox'  checked><label for='section-08dbb181-d0d6-4c6b-adff-caf03c8bea13' 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",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "Data variables:\n",
       "    pre      (time, lat, lon) float64 nan nan nan nan nan ... nan nan nan nan\n",
       "    stn      (time, lat, lon) float64 nan nan nan nan nan ... nan nan nan nan\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": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#interpolating to new lat and lon\n",
    "\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(lat=new_lat,lon=new_lon)\n",
    "jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "82d6b5d0",
   "metadata": {},
   "outputs": [
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       "</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",
       "       [         nan, 307.8540058 , 313.06750634, ..., 257.97650403,\n",
       "        300.16450421,          nan],\n",
       "       [         nan, 261.3955045 , 217.76700435, ..., 228.96350388,\n",
       "        263.6115048 ,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan]])\n",
       "Coordinates:\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88</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-f40b96c7-a51f-4611-82de-224d6f5858fd' class='xr-array-in' type='checkbox' checked><label for='section-f40b96c7-a51f-4611-82de-224d6f5858fd' 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 nan ... nan nan nan nan nan nan nan nan</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",
       "       [         nan, 307.8540058 , 313.06750634, ..., 257.97650403,\n",
       "        300.16450421,          nan],\n",
       "       [         nan, 261.3955045 , 217.76700435, ..., 228.96350388,\n",
       "        263.6115048 ,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan]])</pre></div></div></li><li class='xr-section-item'><input id='section-d164930a-9758-44e9-9f39-4e190e6be098' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d164930a-9758-44e9-9f39-4e190e6be098' 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'>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-811a1bab-aea1-4af1-996c-9517c23ba15c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-811a1bab-aea1-4af1-996c-9517c23ba15c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cab397a2-6e2e-4bc1-8c5e-f7ee513ac849' class='xr-var-data-in' type='checkbox'><label for='data-cab397a2-6e2e-4bc1-8c5e-f7ee513ac849' 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><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-67fd6839-838a-4219-8d04-41a974249548' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-67fd6839-838a-4219-8d04-41a974249548' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a12502b-42bb-41b0-b031-9f531c0cb0df' class='xr-var-data-in' type='checkbox'><label for='data-8a12502b-42bb-41b0-b031-9f531c0cb0df' 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></ul></div></li><li class='xr-section-item'><input id='section-0468af23-5a1b-45be-af8b-a94d0a36cea5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0468af23-5a1b-45be-af8b-a94d0a36cea5' 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",
       "       [         nan, 307.8540058 , 313.06750634, ..., 257.97650403,\n",
       "        300.16450421,          nan],\n",
       "       [         nan, 261.3955045 , 217.76700435, ..., 228.96350388,\n",
       "        263.6115048 ,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan]])\n",
       "Coordinates:\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88"
      ]
     },
     "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",
    "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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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 432, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) object 1970-01-16 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",
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       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1970-01-01 00:00:00 ... 2006-01-01 00:00:00\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:39:57 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment:                              MIROC-MIROC5, historical...\n",
       "    driving_model_id:                                MIROC-MIROC5\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    CDO:                                             Climate Data Operators v...</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-57a5aa00-c32f-49eb-8fda-6fa7cdadde1c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-57a5aa00-c32f-49eb-8fda-6fa7cdadde1c' 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>: 432</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-1596cc7e-21f7-475c-96fa-260828eea90d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1596cc7e-21f7-475c-96fa-260828eea90d' 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'>1970-01-16 12:00:00 ... 2005-12-...</div><input id='attrs-18cfce72-273e-4f3c-8d57-d6db4315714e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18cfce72-273e-4f3c-8d57-d6db4315714e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c273ae53-fb32-473c-be51-2f7bd2cd70d2' class='xr-var-data-in' type='checkbox'><label for='data-c273ae53-fb32-473c-be51-2f7bd2cd70d2' 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(1970, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(1970, 2, 15, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(1970, 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-ace6043d-2337-4916-b1e2-47ca90ef86b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ace6043d-2337-4916-b1e2-47ca90ef86b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84a7b034-1619-47fb-9630-87446906e8fe' class='xr-var-data-in' type='checkbox'><label for='data-84a7b034-1619-47fb-9630-87446906e8fe' 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-36a34a2c-d8ca-404b-8c71-f87b2339681d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36a34a2c-d8ca-404b-8c71-f87b2339681d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06ce64ed-2606-4ba8-93e3-962bebf753a9' class='xr-var-data-in' type='checkbox'><label for='data-06ce64ed-2606-4ba8-93e3-962bebf753a9' 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-705cd6a3-d933-481e-bc42-9a5e9108c470' class='xr-section-summary-in' type='checkbox'  checked><label for='section-705cd6a3-d933-481e-bc42-9a5e9108c470' 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-ad334afc-6b53-4f38-aa02-050c09f4515c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ad334afc-6b53-4f38-aa02-050c09f4515c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a73bc347-1b02-4948-9378-391bcaeb90ad' class='xr-var-data-in' type='checkbox'><label for='data-a73bc347-1b02-4948-9378-391bcaeb90ad' 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(1970, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1970, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1970, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1970, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1970, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1970, 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-4f24400b-8611-4ec9-b403-4f7c33d26ff2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f24400b-8611-4ec9-b403-4f7c33d26ff2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1e46b3a-482c-4d48-9347-9436bca519fa' class='xr-var-data-in' type='checkbox'><label for='data-b1e46b3a-482c-4d48-9347-9436bca519fa' 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>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><pre>[552960 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-270eaa8c-3e9c-433b-9b16-7e254b71e0c7' class='xr-section-summary-in' type='checkbox'  ><label for='section-270eaa8c-3e9c-433b-9b16-7e254b71e0c7' class='xr-section-summary' >Attributes: <span>(165)</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-1.7</dd><dt><span>history :</span></dt><dd>Thu Jul 07 17:39:57 2022: cdo remapnn,grid.des miroc5_pr_197001-200512.nc miroc_remap.nc\n",
       "Mon Jun 27 15:34:28 2022: cdo mergetime pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_197001-198012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_198101-199012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_199101-200012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_200101-200512.nc miroc5_pr_197001-200512.nc\n",
       "2018-05-11 16:23:33 : Created by RegCM RegCM Model program</dd><dt><span>source :</span></dt><dd>RegCM Model output file</dd><dt><span>institution :</span></dt><dd>Oak Ridge National Laboratory</dd><dt><span>project_id :</span></dt><dd>CORDEX</dd><dt><span>ipcc_scenario_code :</span></dt><dd>HISTORICAL</dd><dt><span>institute_id :</span></dt><dd>ORNL</dd><dt><span>note :</span></dt><dd>The domain is larger than WAS-22</dd><dt><span>comment :</span></dt><dd>RegCM CORDEX SAsia25 run</dd><dt><span>experiment :</span></dt><dd>WAS-22</dd><dt><span>driving_model_ensemble_member :</span></dt><dd>r1i1p1</dd><dt><span>creation_date :</span></dt><dd>2019-09-12T16:23:22Z</dd><dt><span>CORDEX_domain :</span></dt><dd>WAS-22</dd><dt><span>rcm_version_id :</span></dt><dd>v0</dd><dt><span>ICTP_version_note :</span></dt><dd>Model run at ORNL on Titan</dd><dt><span>contact :</span></dt><dd>mashfaq@ornl.gov</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>tracking_id :</span></dt><dd>635194b8-8309-11e9-827b-f04da273f023</dd><dt><span>title :</span></dt><dd>ICTP Regional Climatic model V4</dd><dt><span>references :</span></dt><dd>http://gforge.ictp.it/gf/project/regcm</dd><dt><span>model_revision :</span></dt><dd>tag-4.7.0</dd><dt><span>projection :</span></dt><dd>ROTMER</dd><dt><span>grid_size_in_meters :</span></dt><dd>25000.0</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>13.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>70.0</dd><dt><span>grid_north_pole_latitude :</span></dt><dd>13.0</dd><dt><span>grid_north_pole_longitude :</span></dt><dd>70.0</dd><dt><span>grid_factor :</span></dt><dd>0.0</dd><dt><span>landsurface_model :</span></dt><dd>clm4.5</dd><dt><span>model_icbc_data_source :</span></dt><dd>MI_85</dd><dt><span>model_sst_data_source :</span></dt><dd>MI_85</dd><dt><span>boundary_nspgx :</span></dt><dd>30</dd><dt><span>boundary_nspgd :</span></dt><dd>30</dd><dt><span>boundary_high_nudge :</span></dt><dd>8.0</dd><dt><span>boundary_medium_nudge :</span></dt><dd>6.0</dd><dt><span>boundary_low_nudge :</span></dt><dd>4.0</dd><dt><span>boundary_nm :</span></dt><dd>-1.0</dd><dt><span>boundary_dm :</span></dt><dd>-1.0</dd><dt><span>model_is_restarted :</span></dt><dd>No</dd><dt><span>model_simulation_initial_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_end :</span></dt><dd> 1975-01-01 00:00:00 UTC</dd><dt><span>atmosphere_time_step_in_seconds :</span></dt><dd>40.0</dd><dt><span>surface_interaction_time_step_in_seconds :</span></dt><dd>480.0</dd><dt><span>convection_time_step_in_seconds :</span></dt><dd>240.0</dd><dt><span>radiation_scheme_time_step_in_seconds :</span></dt><dd>1800.0</dd><dt><span>absorption_emission_time_step_in_seconds :</span></dt><dd>64800.0</dd><dt><span>dynamical_core :</span></dt><dd>1</dd><dt><span>asselin_filter_nu_1 :</span></dt><dd>0.0625</dd><dt><span>asselin_filter_nu_2 :</span></dt><dd>0.0625</dd><dt><span>diffusion_hgt_factor :</span></dt><dd>1</dd><dt><span>upstream_mode :</span></dt><dd>Yes</dd><dt><span>off_centering_max :</span></dt><dd>0.25</dd><dt><span>stability_enhance :</span></dt><dd>Yes</dd><dt><span>temperature_extreme_gradient :</span></dt><dd>5.0</dd><dt><span>cloud_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>vapor_extreme_gradient_fraction :</span></dt><dd>0.2</dd><dt><span>tracer_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>lateral_boundary_condition_scheme :</span></dt><dd>5</dd><dt><span>semi_lagrangian_advection_scheme :</span></dt><dd>0</dd><dt><span>boundary_layer_scheme :</span></dt><dd>2</dd><dt><span>cumulus_convection_scheme_lnd :</span></dt><dd>4</dd><dt><span>cumulus_convection_scheme_ocn :</span></dt><dd>5</dd><dt><span>moisture_scheme :</span></dt><dd>1</dd><dt><span>ocean_flux_scheme :</span></dt><dd>2</dd><dt><span>zeng_ocean_roughness_formula :</span></dt><dd>1</dd><dt><span>zeng_ocean_roughness_method :</span></dt><dd>1</dd><dt><span>pressure_gradient_scheme :</span></dt><dd>0</dd><dt><span>surface_emissivity_factor_computed :</span></dt><dd>0</dd><dt><span>lake_model_activated :</span></dt><dd>0</dd><dt><span>chemical_aerosol_scheme_activated :</span></dt><dd>0</dd><dt><span>diurnal_cycle_sst_scheme :</span></dt><dd>0</dd><dt><span>ocean_precipitaion_cooling_effect :</span></dt><dd>0</dd><dt><span>ocean_albedo_from_whitecapping :</span></dt><dd>0</dd><dt><span>simple_sea_ice_scheme :</span></dt><dd>0</dd><dt><span>seasonal_desert_albedo :</span></dt><dd>0</dd><dt><span>convective_lwp_as_large_scale :</span></dt><dd>0</dd><dt><span>large_scale_cloud_fraction_scheme :</span></dt><dd>0</dd><dt><span>ocean_stratiform_clouds_scheme :</span></dt><dd>1</dd><dt><span>rrtm_radiation_scheme_activated :</span></dt><dd>0</dd><dt><span>climatic_ozone_input_dataset :</span></dt><dd>0</dd><dt><span>climatic_aerosol_input_dataset :</span></dt><dd>0</dd><dt><span>static_solar_constant_used :</span></dt><dd>0</dd><dt><span>cumulus_cloud_model :</span></dt><dd>1</dd><dt><span>sun_year_offset :</span></dt><dd>0.0</dd><dt><span>fix_solar_parameters :</span></dt><dd>0</dd><dt><span>cloud_bottom_level_with_no_clouds :</span></dt><dd>1</dd><dt><span>cloud_rh_with_fcc_one :</span></dt><dd>1.01</dd><dt><span>cloud_rh_threshold_for_land :</span></dt><dd>0.8</dd><dt><span>cloud_rh_threshold_for_ocean :</span></dt><dd>0.9</dd><dt><span>cloud_rh1_limit_temperature :</span></dt><dd>238.0</dd><dt><span>cloud_cloud_fraction_maximum :</span></dt><dd>0.75</dd><dt><span>cloud_condensation_threshold :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_fraction_max_for_convection :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_liqwat_max_for_convection :</span></dt><dd>0.0003</dd><dt><span>cloud_shallow_convective_cf_param :</span></dt><dd>0.07</dd><dt><span>cloud_deep_convective_cf_param :</span></dt><dd>0.14</dd><dt><span>cloud_k2_convective_cf_param :</span></dt><dd>500.0</dd><dt><span>cloud_surface_radiation_hack :</span></dt><dd>No</dd><dt><span>cloud_arctic_cloud_correction :</span></dt><dd>Yes</dd><dt><span>subex_auto_conversion_rate_for_land :</span></dt><dd>0.00025</dd><dt><span>subex_auto_conversion_rate_for_ocean :</span></dt><dd>0.00025</dd><dt><span>subex_gultepe_factor_when_rain_for_land :</span></dt><dd>0.4</dd><dt><span>subex_gultepe_factor_when_rain_for_ocean :</span></dt><dd>0.4</dd><dt><span>subex_land_raindrop_evaporation_rate :</span></dt><dd>0.0002</dd><dt><span>subex_ocean_raindrop_evaporation_rate :</span></dt><dd>0.0001</dd><dt><span>subex_land_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>subex_ocean_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>mit_lowest_convection_sigma :</span></dt><dd>0.95</dd><dt><span>mit_autoconversion_threshold_mixing_over_ocean :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_mixing_over_land :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_temperature :</span></dt><dd>-55.0</dd><dt><span>mit_mixing_coefficient_in_entrainment :</span></dt><dd>1.5</dd><dt><span>mit_fractional_area_unsaturated_downdraft :</span></dt><dd>0.05</dd><dt><span>mit_fractional_precip_outside_cloud :</span></dt><dd>0.12</dd><dt><span>mit_pressure_velocity_of_rain :</span></dt><dd>50.0</dd><dt><span>mit_pressure_velocity_of_snow :</span></dt><dd>5.5</dd><dt><span>mit_rain_evaporation_coefficient :</span></dt><dd>1.0</dd><dt><span>mit_snow_evaporation_coefficient :</span></dt><dd>0.8</dd><dt><span>mit_momentum_transport_coefficient :</span></dt><dd>0.7</dd><dt><span>mit_downdraft_velocity_coefficient :</span></dt><dd>10.0</dd><dt><span>mit_max_parcel_neg_temp_perturbation :</span></dt><dd>0.9</dd><dt><span>mit_approach_rate_quasi_eq_coeff_a :</span></dt><dd>0.2</dd><dt><span>mit_approach_rate_quasi_eq_coeff_d :</span></dt><dd>0.1</dd><dt><span>mit_maximum_land_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>mit_maximum_ocean_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>tiedtke_actual_scheme :</span></dt><dd>4</dd><dt><span>tiedtke_entrainment_rate_downdraft :</span></dt><dd>0.0003</dd><dt><span>tiedtke_entrainment_rate_deep_land :</span></dt><dd>0.00075</dd><dt><span>tiedtke_entrainment_rate_deep_ocean :</span></dt><dd>0.00075</dd><dt><span>tiedtke_penetrative :</span></dt><dd>Yes</dd><dt><span>tiedtke_midlevel :</span></dt><dd>Yes</dd><dt><span>tiedtke_shallow :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_downdraft :</span></dt><dd>Yes</dd><dt><span>tiedtke_prognostic_cloud :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_friction :</span></dt><dd>Yes</dd><dt><span>tiedtke_ke_dissipation :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_transport :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_smooth_massflux :</span></dt><dd>No</dd><dt><span>tiedtke_shallow_wstar_closure :</span></dt><dd>No</dd><dt><span>tiedtke_detrainment_rate_deep_land :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_detrainment_rate_deep_ocean :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_shallow_entrainment :</span></dt><dd>2.0</dd><dt><span>tiedtke_cloud_cover_evap_over_land :</span></dt><dd>0.05</dd><dt><span>tiedtke_cloud_cover_evap_over_ocean :</span></dt><dd>0.05</dd><dt><span>tiedtke_coeff_evap_over_land :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_coeff_evap_over_ocean :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_critical_rh_over_land :</span></dt><dd>0.9</dd><dt><span>tiedtke_critical_rh_over_ocean :</span></dt><dd>0.9</dd><dt><span>tiedtke_cloud_water_conv_over_land :</span></dt><dd>0.03</dd><dt><span>tiedtke_cloud_water_conv_over_ocean :</span></dt><dd>0.0014</dd><dt><span>tiedtke_cape_adjustment_timescale :</span></dt><dd>2400.0</dd><dt><span>uwpbl_advection_scheme :</span></dt><dd>0</dd><dt><span>uwpbl_cloud_evap_entr_incr_efficiency :</span></dt><dd>15.0</dd><dt><span>uwpbl_eddy_LS_stable_PBL_scaling :</span></dt><dd>1.5</dd><dt><span>uwpbl_czero :</span></dt><dd>5.869</dd><dt><span>uwpbl_nuk :</span></dt><dd>5.0</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>driving_experiment :</span></dt><dd>MIROC-MIROC5, historical, r1i1p1</dd><dt><span>driving_model_id :</span></dt><dd>MIROC-MIROC5</dd><dt><span>driving_experiment_name :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>ICTP-RegCM4-7</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: 432, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) object 1970-01-16 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: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:39:57 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment:                              MIROC-MIROC5, historical...\n",
       "    driving_model_id:                                MIROC-MIROC5\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    CDO:                                             Climate Data Operators v..."
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#opening miroc5 data\n",
    "\n",
    "data = xr.open_dataset('/home/mkibria/Academic/pr_of_thesis/regcm driven by gcm/MIROC5/miroc_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_29135/1463838701.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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       "Dimensions:    (time: 432, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1970-01-16T12:00:00 ... 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 1970-01-01 00:00:00 ... 2006-01-01 00:00:00\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:39:57 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment:                              MIROC-MIROC5, historical...\n",
       "    driving_model_id:                                MIROC-MIROC5\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    CDO:                                             Climate Data Operators v...</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-3813b482-f314-4a5b-aca8-de75ae6ea23a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3813b482-f314-4a5b-aca8-de75ae6ea23a' 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>: 432</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-07066725-b346-4d97-9db7-a8d19efee674' class='xr-section-summary-in' type='checkbox'  checked><label for='section-07066725-b346-4d97-9db7-a8d19efee674' 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'>1970-01-16T12:00:00 ... 2005-12-...</div><input id='attrs-a81678c0-42ed-4835-b0a3-8e303cd80209' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a81678c0-42ed-4835-b0a3-8e303cd80209' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f464640b-c810-4d96-a192-94e4f8efce48' class='xr-var-data-in' type='checkbox'><label for='data-f464640b-c810-4d96-a192-94e4f8efce48' 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;1970-01-16T12:00:00.000000000&#x27;, &#x27;1970-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;1970-03-16T12:00:00.000000000&#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-eb1bb662-79dc-4710-8a6a-dcd62089703e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb1bb662-79dc-4710-8a6a-dcd62089703e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-830bba75-683a-41bb-bc67-8753d2fc7336' class='xr-var-data-in' type='checkbox'><label for='data-830bba75-683a-41bb-bc67-8753d2fc7336' 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-401be903-adaf-4401-9aa4-42d18e9a0681' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-401be903-adaf-4401-9aa4-42d18e9a0681' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0975c98-5ea1-4bce-926b-d40f6daf8e03' class='xr-var-data-in' type='checkbox'><label for='data-c0975c98-5ea1-4bce-926b-d40f6daf8e03' 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-3c5c32e8-fcf1-4233-ad69-1014e79fd543' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3c5c32e8-fcf1-4233-ad69-1014e79fd543' 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'>1970-01-01 00:00:00 ... 2006-01-...</div><input id='attrs-281a2fb4-bb82-4eaf-9a18-5410cea356e9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-281a2fb4-bb82-4eaf-9a18-5410cea356e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e81315a-3d70-4655-8cd0-cde3b0ff00cc' class='xr-var-data-in' type='checkbox'><label for='data-7e81315a-3d70-4655-8cd0-cde3b0ff00cc' 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(1970, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1970, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1970, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1970, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1970, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1970, 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-cc48ddb3-506c-434b-a7c2-12439f612937' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc48ddb3-506c-434b-a7c2-12439f612937' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c6d41c7-aa27-4e4a-98a4-9920f8e535a3' class='xr-var-data-in' type='checkbox'><label for='data-7c6d41c7-aa27-4e4a-98a4-9920f8e535a3' 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>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><pre>[552960 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-24fa8bc2-2f2c-4f74-b918-106b4d197b91' class='xr-section-summary-in' type='checkbox'  ><label for='section-24fa8bc2-2f2c-4f74-b918-106b4d197b91' class='xr-section-summary' >Attributes: <span>(165)</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-1.7</dd><dt><span>history :</span></dt><dd>Thu Jul 07 17:39:57 2022: cdo remapnn,grid.des miroc5_pr_197001-200512.nc miroc_remap.nc\n",
       "Mon Jun 27 15:34:28 2022: cdo mergetime pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_197001-198012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_198101-199012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_199101-200012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_200101-200512.nc miroc5_pr_197001-200512.nc\n",
       "2018-05-11 16:23:33 : Created by RegCM RegCM Model program</dd><dt><span>source :</span></dt><dd>RegCM Model output file</dd><dt><span>institution :</span></dt><dd>Oak Ridge National Laboratory</dd><dt><span>project_id :</span></dt><dd>CORDEX</dd><dt><span>ipcc_scenario_code :</span></dt><dd>HISTORICAL</dd><dt><span>institute_id :</span></dt><dd>ORNL</dd><dt><span>note :</span></dt><dd>The domain is larger than WAS-22</dd><dt><span>comment :</span></dt><dd>RegCM CORDEX SAsia25 run</dd><dt><span>experiment :</span></dt><dd>WAS-22</dd><dt><span>driving_model_ensemble_member :</span></dt><dd>r1i1p1</dd><dt><span>creation_date :</span></dt><dd>2019-09-12T16:23:22Z</dd><dt><span>CORDEX_domain :</span></dt><dd>WAS-22</dd><dt><span>rcm_version_id :</span></dt><dd>v0</dd><dt><span>ICTP_version_note :</span></dt><dd>Model run at ORNL on Titan</dd><dt><span>contact :</span></dt><dd>mashfaq@ornl.gov</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>tracking_id :</span></dt><dd>635194b8-8309-11e9-827b-f04da273f023</dd><dt><span>title :</span></dt><dd>ICTP Regional Climatic model V4</dd><dt><span>references :</span></dt><dd>http://gforge.ictp.it/gf/project/regcm</dd><dt><span>model_revision :</span></dt><dd>tag-4.7.0</dd><dt><span>projection :</span></dt><dd>ROTMER</dd><dt><span>grid_size_in_meters :</span></dt><dd>25000.0</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>13.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>70.0</dd><dt><span>grid_north_pole_latitude :</span></dt><dd>13.0</dd><dt><span>grid_north_pole_longitude :</span></dt><dd>70.0</dd><dt><span>grid_factor :</span></dt><dd>0.0</dd><dt><span>landsurface_model :</span></dt><dd>clm4.5</dd><dt><span>model_icbc_data_source :</span></dt><dd>MI_85</dd><dt><span>model_sst_data_source :</span></dt><dd>MI_85</dd><dt><span>boundary_nspgx :</span></dt><dd>30</dd><dt><span>boundary_nspgd :</span></dt><dd>30</dd><dt><span>boundary_high_nudge :</span></dt><dd>8.0</dd><dt><span>boundary_medium_nudge :</span></dt><dd>6.0</dd><dt><span>boundary_low_nudge :</span></dt><dd>4.0</dd><dt><span>boundary_nm :</span></dt><dd>-1.0</dd><dt><span>boundary_dm :</span></dt><dd>-1.0</dd><dt><span>model_is_restarted :</span></dt><dd>No</dd><dt><span>model_simulation_initial_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_end :</span></dt><dd> 1975-01-01 00:00:00 UTC</dd><dt><span>atmosphere_time_step_in_seconds :</span></dt><dd>40.0</dd><dt><span>surface_interaction_time_step_in_seconds :</span></dt><dd>480.0</dd><dt><span>convection_time_step_in_seconds :</span></dt><dd>240.0</dd><dt><span>radiation_scheme_time_step_in_seconds :</span></dt><dd>1800.0</dd><dt><span>absorption_emission_time_step_in_seconds :</span></dt><dd>64800.0</dd><dt><span>dynamical_core :</span></dt><dd>1</dd><dt><span>asselin_filter_nu_1 :</span></dt><dd>0.0625</dd><dt><span>asselin_filter_nu_2 :</span></dt><dd>0.0625</dd><dt><span>diffusion_hgt_factor :</span></dt><dd>1</dd><dt><span>upstream_mode :</span></dt><dd>Yes</dd><dt><span>off_centering_max :</span></dt><dd>0.25</dd><dt><span>stability_enhance :</span></dt><dd>Yes</dd><dt><span>temperature_extreme_gradient :</span></dt><dd>5.0</dd><dt><span>cloud_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>vapor_extreme_gradient_fraction :</span></dt><dd>0.2</dd><dt><span>tracer_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>lateral_boundary_condition_scheme :</span></dt><dd>5</dd><dt><span>semi_lagrangian_advection_scheme :</span></dt><dd>0</dd><dt><span>boundary_layer_scheme :</span></dt><dd>2</dd><dt><span>cumulus_convection_scheme_lnd :</span></dt><dd>4</dd><dt><span>cumulus_convection_scheme_ocn :</span></dt><dd>5</dd><dt><span>moisture_scheme :</span></dt><dd>1</dd><dt><span>ocean_flux_scheme :</span></dt><dd>2</dd><dt><span>zeng_ocean_roughness_formula :</span></dt><dd>1</dd><dt><span>zeng_ocean_roughness_method :</span></dt><dd>1</dd><dt><span>pressure_gradient_scheme :</span></dt><dd>0</dd><dt><span>surface_emissivity_factor_computed :</span></dt><dd>0</dd><dt><span>lake_model_activated :</span></dt><dd>0</dd><dt><span>chemical_aerosol_scheme_activated :</span></dt><dd>0</dd><dt><span>diurnal_cycle_sst_scheme :</span></dt><dd>0</dd><dt><span>ocean_precipitaion_cooling_effect :</span></dt><dd>0</dd><dt><span>ocean_albedo_from_whitecapping :</span></dt><dd>0</dd><dt><span>simple_sea_ice_scheme :</span></dt><dd>0</dd><dt><span>seasonal_desert_albedo :</span></dt><dd>0</dd><dt><span>convective_lwp_as_large_scale :</span></dt><dd>0</dd><dt><span>large_scale_cloud_fraction_scheme :</span></dt><dd>0</dd><dt><span>ocean_stratiform_clouds_scheme :</span></dt><dd>1</dd><dt><span>rrtm_radiation_scheme_activated :</span></dt><dd>0</dd><dt><span>climatic_ozone_input_dataset :</span></dt><dd>0</dd><dt><span>climatic_aerosol_input_dataset :</span></dt><dd>0</dd><dt><span>static_solar_constant_used :</span></dt><dd>0</dd><dt><span>cumulus_cloud_model :</span></dt><dd>1</dd><dt><span>sun_year_offset :</span></dt><dd>0.0</dd><dt><span>fix_solar_parameters :</span></dt><dd>0</dd><dt><span>cloud_bottom_level_with_no_clouds :</span></dt><dd>1</dd><dt><span>cloud_rh_with_fcc_one :</span></dt><dd>1.01</dd><dt><span>cloud_rh_threshold_for_land :</span></dt><dd>0.8</dd><dt><span>cloud_rh_threshold_for_ocean :</span></dt><dd>0.9</dd><dt><span>cloud_rh1_limit_temperature :</span></dt><dd>238.0</dd><dt><span>cloud_cloud_fraction_maximum :</span></dt><dd>0.75</dd><dt><span>cloud_condensation_threshold :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_fraction_max_for_convection :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_liqwat_max_for_convection :</span></dt><dd>0.0003</dd><dt><span>cloud_shallow_convective_cf_param :</span></dt><dd>0.07</dd><dt><span>cloud_deep_convective_cf_param :</span></dt><dd>0.14</dd><dt><span>cloud_k2_convective_cf_param :</span></dt><dd>500.0</dd><dt><span>cloud_surface_radiation_hack :</span></dt><dd>No</dd><dt><span>cloud_arctic_cloud_correction :</span></dt><dd>Yes</dd><dt><span>subex_auto_conversion_rate_for_land :</span></dt><dd>0.00025</dd><dt><span>subex_auto_conversion_rate_for_ocean :</span></dt><dd>0.00025</dd><dt><span>subex_gultepe_factor_when_rain_for_land :</span></dt><dd>0.4</dd><dt><span>subex_gultepe_factor_when_rain_for_ocean :</span></dt><dd>0.4</dd><dt><span>subex_land_raindrop_evaporation_rate :</span></dt><dd>0.0002</dd><dt><span>subex_ocean_raindrop_evaporation_rate :</span></dt><dd>0.0001</dd><dt><span>subex_land_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>subex_ocean_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>mit_lowest_convection_sigma :</span></dt><dd>0.95</dd><dt><span>mit_autoconversion_threshold_mixing_over_ocean :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_mixing_over_land :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_temperature :</span></dt><dd>-55.0</dd><dt><span>mit_mixing_coefficient_in_entrainment :</span></dt><dd>1.5</dd><dt><span>mit_fractional_area_unsaturated_downdraft :</span></dt><dd>0.05</dd><dt><span>mit_fractional_precip_outside_cloud :</span></dt><dd>0.12</dd><dt><span>mit_pressure_velocity_of_rain :</span></dt><dd>50.0</dd><dt><span>mit_pressure_velocity_of_snow :</span></dt><dd>5.5</dd><dt><span>mit_rain_evaporation_coefficient :</span></dt><dd>1.0</dd><dt><span>mit_snow_evaporation_coefficient :</span></dt><dd>0.8</dd><dt><span>mit_momentum_transport_coefficient :</span></dt><dd>0.7</dd><dt><span>mit_downdraft_velocity_coefficient :</span></dt><dd>10.0</dd><dt><span>mit_max_parcel_neg_temp_perturbation :</span></dt><dd>0.9</dd><dt><span>mit_approach_rate_quasi_eq_coeff_a :</span></dt><dd>0.2</dd><dt><span>mit_approach_rate_quasi_eq_coeff_d :</span></dt><dd>0.1</dd><dt><span>mit_maximum_land_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>mit_maximum_ocean_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>tiedtke_actual_scheme :</span></dt><dd>4</dd><dt><span>tiedtke_entrainment_rate_downdraft :</span></dt><dd>0.0003</dd><dt><span>tiedtke_entrainment_rate_deep_land :</span></dt><dd>0.00075</dd><dt><span>tiedtke_entrainment_rate_deep_ocean :</span></dt><dd>0.00075</dd><dt><span>tiedtke_penetrative :</span></dt><dd>Yes</dd><dt><span>tiedtke_midlevel :</span></dt><dd>Yes</dd><dt><span>tiedtke_shallow :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_downdraft :</span></dt><dd>Yes</dd><dt><span>tiedtke_prognostic_cloud :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_friction :</span></dt><dd>Yes</dd><dt><span>tiedtke_ke_dissipation :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_transport :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_smooth_massflux :</span></dt><dd>No</dd><dt><span>tiedtke_shallow_wstar_closure :</span></dt><dd>No</dd><dt><span>tiedtke_detrainment_rate_deep_land :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_detrainment_rate_deep_ocean :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_shallow_entrainment :</span></dt><dd>2.0</dd><dt><span>tiedtke_cloud_cover_evap_over_land :</span></dt><dd>0.05</dd><dt><span>tiedtke_cloud_cover_evap_over_ocean :</span></dt><dd>0.05</dd><dt><span>tiedtke_coeff_evap_over_land :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_coeff_evap_over_ocean :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_critical_rh_over_land :</span></dt><dd>0.9</dd><dt><span>tiedtke_critical_rh_over_ocean :</span></dt><dd>0.9</dd><dt><span>tiedtke_cloud_water_conv_over_land :</span></dt><dd>0.03</dd><dt><span>tiedtke_cloud_water_conv_over_ocean :</span></dt><dd>0.0014</dd><dt><span>tiedtke_cape_adjustment_timescale :</span></dt><dd>2400.0</dd><dt><span>uwpbl_advection_scheme :</span></dt><dd>0</dd><dt><span>uwpbl_cloud_evap_entr_incr_efficiency :</span></dt><dd>15.0</dd><dt><span>uwpbl_eddy_LS_stable_PBL_scaling :</span></dt><dd>1.5</dd><dt><span>uwpbl_czero :</span></dt><dd>5.869</dd><dt><span>uwpbl_nuk :</span></dt><dd>5.0</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>driving_experiment :</span></dt><dd>MIROC-MIROC5, historical, r1i1p1</dd><dt><span>driving_model_id :</span></dt><dd>MIROC-MIROC5</dd><dt><span>driving_experiment_name :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>ICTP-RegCM4-7</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: 432, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1970-01-16T12:00:00 ... 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 1970-01-01 00:00:00 ... 2006-01-01 00:00:00\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:39:57 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment:                              MIROC-MIROC5, historical...\n",
       "    driving_model_id:                                MIROC-MIROC5\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    CDO:                                             Climate Data Operators v..."
      ]
     },
     "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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       "</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",
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       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:39:57 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment:                              MIROC-MIROC5, historical...\n",
       "    driving_model_id:                                MIROC-MIROC5\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    CDO:                                             Climate Data Operators v...</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-e319ff93-13d1-48df-9994-82542177af4d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e319ff93-13d1-48df-9994-82542177af4d' 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-9f02a560-b314-4f45-ab17-a7abce198d93' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9f02a560-b314-4f45-ab17-a7abce198d93' 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-428d513d-6963-4e9b-8590-93d04c3e46cf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-428d513d-6963-4e9b-8590-93d04c3e46cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec6e3f14-a521-45ed-9326-3597b3e3eff3' class='xr-var-data-in' type='checkbox'><label for='data-ec6e3f14-a521-45ed-9326-3597b3e3eff3' 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-971bc442-e913-4cea-acb6-7da82d01ef8b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-971bc442-e913-4cea-acb6-7da82d01ef8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3e31991-1383-48c2-8566-7ae79a8ff372' class='xr-var-data-in' type='checkbox'><label for='data-a3e31991-1383-48c2-8566-7ae79a8ff372' 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-45350192-ecaa-4de0-b7b0-49f2b3601948' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45350192-ecaa-4de0-b7b0-49f2b3601948' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a43791d2-2b2a-419d-bb4a-8f138c32c470' class='xr-var-data-in' type='checkbox'><label for='data-a43791d2-2b2a-419d-bb4a-8f138c32c470' 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-36db03df-b4e0-427a-a8a9-d02a16d3445b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-36db03df-b4e0-427a-a8a9-d02a16d3445b' 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-8e7d2f2b-e3e5-4e21-962d-ff76879133c0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8e7d2f2b-e3e5-4e21-962d-ff76879133c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42e3c91f-5912-46fd-a56c-f44c1d039a5a' class='xr-var-data-in' type='checkbox'><label for='data-42e3c91f-5912-46fd-a56c-f44c1d039a5a' 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-9ff0ab29-d414-4271-bbbb-1bd572319fe7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ff0ab29-d414-4271-bbbb-1bd572319fe7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ebcee91b-37e1-49b2-8233-b8763a16e054' class='xr-var-data-in' type='checkbox'><label for='data-ebcee91b-37e1-49b2-8233-b8763a16e054' 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>cell_methods :</span></dt><dd>time: mean</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-51ed2f8f-453e-4c06-a5db-b53ab7f42991' class='xr-section-summary-in' type='checkbox'  ><label for='section-51ed2f8f-453e-4c06-a5db-b53ab7f42991' class='xr-section-summary' >Attributes: <span>(165)</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-1.7</dd><dt><span>history :</span></dt><dd>Thu Jul 07 17:39:57 2022: cdo remapnn,grid.des miroc5_pr_197001-200512.nc miroc_remap.nc\n",
       "Mon Jun 27 15:34:28 2022: cdo mergetime pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_197001-198012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_198101-199012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_199101-200012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_200101-200512.nc miroc5_pr_197001-200512.nc\n",
       "2018-05-11 16:23:33 : Created by RegCM RegCM Model program</dd><dt><span>source :</span></dt><dd>RegCM Model output file</dd><dt><span>institution :</span></dt><dd>Oak Ridge National Laboratory</dd><dt><span>project_id :</span></dt><dd>CORDEX</dd><dt><span>ipcc_scenario_code :</span></dt><dd>HISTORICAL</dd><dt><span>institute_id :</span></dt><dd>ORNL</dd><dt><span>note :</span></dt><dd>The domain is larger than WAS-22</dd><dt><span>comment :</span></dt><dd>RegCM CORDEX SAsia25 run</dd><dt><span>experiment :</span></dt><dd>WAS-22</dd><dt><span>driving_model_ensemble_member :</span></dt><dd>r1i1p1</dd><dt><span>creation_date :</span></dt><dd>2019-09-12T16:23:22Z</dd><dt><span>CORDEX_domain :</span></dt><dd>WAS-22</dd><dt><span>rcm_version_id :</span></dt><dd>v0</dd><dt><span>ICTP_version_note :</span></dt><dd>Model run at ORNL on Titan</dd><dt><span>contact :</span></dt><dd>mashfaq@ornl.gov</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>tracking_id :</span></dt><dd>635194b8-8309-11e9-827b-f04da273f023</dd><dt><span>title :</span></dt><dd>ICTP Regional Climatic model V4</dd><dt><span>references :</span></dt><dd>http://gforge.ictp.it/gf/project/regcm</dd><dt><span>model_revision :</span></dt><dd>tag-4.7.0</dd><dt><span>projection :</span></dt><dd>ROTMER</dd><dt><span>grid_size_in_meters :</span></dt><dd>25000.0</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>13.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>70.0</dd><dt><span>grid_north_pole_latitude :</span></dt><dd>13.0</dd><dt><span>grid_north_pole_longitude :</span></dt><dd>70.0</dd><dt><span>grid_factor :</span></dt><dd>0.0</dd><dt><span>landsurface_model :</span></dt><dd>clm4.5</dd><dt><span>model_icbc_data_source :</span></dt><dd>MI_85</dd><dt><span>model_sst_data_source :</span></dt><dd>MI_85</dd><dt><span>boundary_nspgx :</span></dt><dd>30</dd><dt><span>boundary_nspgd :</span></dt><dd>30</dd><dt><span>boundary_high_nudge :</span></dt><dd>8.0</dd><dt><span>boundary_medium_nudge :</span></dt><dd>6.0</dd><dt><span>boundary_low_nudge :</span></dt><dd>4.0</dd><dt><span>boundary_nm :</span></dt><dd>-1.0</dd><dt><span>boundary_dm :</span></dt><dd>-1.0</dd><dt><span>model_is_restarted :</span></dt><dd>No</dd><dt><span>model_simulation_initial_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_end :</span></dt><dd> 1975-01-01 00:00:00 UTC</dd><dt><span>atmosphere_time_step_in_seconds :</span></dt><dd>40.0</dd><dt><span>surface_interaction_time_step_in_seconds :</span></dt><dd>480.0</dd><dt><span>convection_time_step_in_seconds :</span></dt><dd>240.0</dd><dt><span>radiation_scheme_time_step_in_seconds :</span></dt><dd>1800.0</dd><dt><span>absorption_emission_time_step_in_seconds :</span></dt><dd>64800.0</dd><dt><span>dynamical_core :</span></dt><dd>1</dd><dt><span>asselin_filter_nu_1 :</span></dt><dd>0.0625</dd><dt><span>asselin_filter_nu_2 :</span></dt><dd>0.0625</dd><dt><span>diffusion_hgt_factor :</span></dt><dd>1</dd><dt><span>upstream_mode :</span></dt><dd>Yes</dd><dt><span>off_centering_max :</span></dt><dd>0.25</dd><dt><span>stability_enhance :</span></dt><dd>Yes</dd><dt><span>temperature_extreme_gradient :</span></dt><dd>5.0</dd><dt><span>cloud_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>vapor_extreme_gradient_fraction :</span></dt><dd>0.2</dd><dt><span>tracer_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>lateral_boundary_condition_scheme :</span></dt><dd>5</dd><dt><span>semi_lagrangian_advection_scheme :</span></dt><dd>0</dd><dt><span>boundary_layer_scheme :</span></dt><dd>2</dd><dt><span>cumulus_convection_scheme_lnd :</span></dt><dd>4</dd><dt><span>cumulus_convection_scheme_ocn :</span></dt><dd>5</dd><dt><span>moisture_scheme :</span></dt><dd>1</dd><dt><span>ocean_flux_scheme :</span></dt><dd>2</dd><dt><span>zeng_ocean_roughness_formula :</span></dt><dd>1</dd><dt><span>zeng_ocean_roughness_method :</span></dt><dd>1</dd><dt><span>pressure_gradient_scheme :</span></dt><dd>0</dd><dt><span>surface_emissivity_factor_computed :</span></dt><dd>0</dd><dt><span>lake_model_activated :</span></dt><dd>0</dd><dt><span>chemical_aerosol_scheme_activated :</span></dt><dd>0</dd><dt><span>diurnal_cycle_sst_scheme :</span></dt><dd>0</dd><dt><span>ocean_precipitaion_cooling_effect :</span></dt><dd>0</dd><dt><span>ocean_albedo_from_whitecapping :</span></dt><dd>0</dd><dt><span>simple_sea_ice_scheme :</span></dt><dd>0</dd><dt><span>seasonal_desert_albedo :</span></dt><dd>0</dd><dt><span>convective_lwp_as_large_scale :</span></dt><dd>0</dd><dt><span>large_scale_cloud_fraction_scheme :</span></dt><dd>0</dd><dt><span>ocean_stratiform_clouds_scheme :</span></dt><dd>1</dd><dt><span>rrtm_radiation_scheme_activated :</span></dt><dd>0</dd><dt><span>climatic_ozone_input_dataset :</span></dt><dd>0</dd><dt><span>climatic_aerosol_input_dataset :</span></dt><dd>0</dd><dt><span>static_solar_constant_used :</span></dt><dd>0</dd><dt><span>cumulus_cloud_model :</span></dt><dd>1</dd><dt><span>sun_year_offset :</span></dt><dd>0.0</dd><dt><span>fix_solar_parameters :</span></dt><dd>0</dd><dt><span>cloud_bottom_level_with_no_clouds :</span></dt><dd>1</dd><dt><span>cloud_rh_with_fcc_one :</span></dt><dd>1.01</dd><dt><span>cloud_rh_threshold_for_land :</span></dt><dd>0.8</dd><dt><span>cloud_rh_threshold_for_ocean :</span></dt><dd>0.9</dd><dt><span>cloud_rh1_limit_temperature :</span></dt><dd>238.0</dd><dt><span>cloud_cloud_fraction_maximum :</span></dt><dd>0.75</dd><dt><span>cloud_condensation_threshold :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_fraction_max_for_convection :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_liqwat_max_for_convection :</span></dt><dd>0.0003</dd><dt><span>cloud_shallow_convective_cf_param :</span></dt><dd>0.07</dd><dt><span>cloud_deep_convective_cf_param :</span></dt><dd>0.14</dd><dt><span>cloud_k2_convective_cf_param :</span></dt><dd>500.0</dd><dt><span>cloud_surface_radiation_hack :</span></dt><dd>No</dd><dt><span>cloud_arctic_cloud_correction :</span></dt><dd>Yes</dd><dt><span>subex_auto_conversion_rate_for_land :</span></dt><dd>0.00025</dd><dt><span>subex_auto_conversion_rate_for_ocean :</span></dt><dd>0.00025</dd><dt><span>subex_gultepe_factor_when_rain_for_land :</span></dt><dd>0.4</dd><dt><span>subex_gultepe_factor_when_rain_for_ocean :</span></dt><dd>0.4</dd><dt><span>subex_land_raindrop_evaporation_rate :</span></dt><dd>0.0002</dd><dt><span>subex_ocean_raindrop_evaporation_rate :</span></dt><dd>0.0001</dd><dt><span>subex_land_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>subex_ocean_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>mit_lowest_convection_sigma :</span></dt><dd>0.95</dd><dt><span>mit_autoconversion_threshold_mixing_over_ocean :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_mixing_over_land :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_temperature :</span></dt><dd>-55.0</dd><dt><span>mit_mixing_coefficient_in_entrainment :</span></dt><dd>1.5</dd><dt><span>mit_fractional_area_unsaturated_downdraft :</span></dt><dd>0.05</dd><dt><span>mit_fractional_precip_outside_cloud :</span></dt><dd>0.12</dd><dt><span>mit_pressure_velocity_of_rain :</span></dt><dd>50.0</dd><dt><span>mit_pressure_velocity_of_snow :</span></dt><dd>5.5</dd><dt><span>mit_rain_evaporation_coefficient :</span></dt><dd>1.0</dd><dt><span>mit_snow_evaporation_coefficient :</span></dt><dd>0.8</dd><dt><span>mit_momentum_transport_coefficient :</span></dt><dd>0.7</dd><dt><span>mit_downdraft_velocity_coefficient :</span></dt><dd>10.0</dd><dt><span>mit_max_parcel_neg_temp_perturbation :</span></dt><dd>0.9</dd><dt><span>mit_approach_rate_quasi_eq_coeff_a :</span></dt><dd>0.2</dd><dt><span>mit_approach_rate_quasi_eq_coeff_d :</span></dt><dd>0.1</dd><dt><span>mit_maximum_land_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>mit_maximum_ocean_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>tiedtke_actual_scheme :</span></dt><dd>4</dd><dt><span>tiedtke_entrainment_rate_downdraft :</span></dt><dd>0.0003</dd><dt><span>tiedtke_entrainment_rate_deep_land :</span></dt><dd>0.00075</dd><dt><span>tiedtke_entrainment_rate_deep_ocean :</span></dt><dd>0.00075</dd><dt><span>tiedtke_penetrative :</span></dt><dd>Yes</dd><dt><span>tiedtke_midlevel :</span></dt><dd>Yes</dd><dt><span>tiedtke_shallow :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_downdraft :</span></dt><dd>Yes</dd><dt><span>tiedtke_prognostic_cloud :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_friction :</span></dt><dd>Yes</dd><dt><span>tiedtke_ke_dissipation :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_transport :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_smooth_massflux :</span></dt><dd>No</dd><dt><span>tiedtke_shallow_wstar_closure :</span></dt><dd>No</dd><dt><span>tiedtke_detrainment_rate_deep_land :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_detrainment_rate_deep_ocean :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_shallow_entrainment :</span></dt><dd>2.0</dd><dt><span>tiedtke_cloud_cover_evap_over_land :</span></dt><dd>0.05</dd><dt><span>tiedtke_cloud_cover_evap_over_ocean :</span></dt><dd>0.05</dd><dt><span>tiedtke_coeff_evap_over_land :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_coeff_evap_over_ocean :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_critical_rh_over_land :</span></dt><dd>0.9</dd><dt><span>tiedtke_critical_rh_over_ocean :</span></dt><dd>0.9</dd><dt><span>tiedtke_cloud_water_conv_over_land :</span></dt><dd>0.03</dd><dt><span>tiedtke_cloud_water_conv_over_ocean :</span></dt><dd>0.0014</dd><dt><span>tiedtke_cape_adjustment_timescale :</span></dt><dd>2400.0</dd><dt><span>uwpbl_advection_scheme :</span></dt><dd>0</dd><dt><span>uwpbl_cloud_evap_entr_incr_efficiency :</span></dt><dd>15.0</dd><dt><span>uwpbl_eddy_LS_stable_PBL_scaling :</span></dt><dd>1.5</dd><dt><span>uwpbl_czero :</span></dt><dd>5.869</dd><dt><span>uwpbl_nuk :</span></dt><dd>5.0</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>driving_experiment :</span></dt><dd>MIROC-MIROC5, historical, r1i1p1</dd><dt><span>driving_model_id :</span></dt><dd>MIROC-MIROC5</dd><dt><span>driving_experiment_name :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>ICTP-RegCM4-7</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: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:39:57 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment:                              MIROC-MIROC5, historical...\n",
       "    driving_model_id:                                MIROC-MIROC5\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    CDO:                                             Climate Data Operators v..."
      ]
     },
     "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",
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       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:39:57 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment:                              MIROC-MIROC5, historical...\n",
       "    driving_model_id:                                MIROC-MIROC5\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    CDO:                                             Climate Data Operators v...</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-23f51a52-1393-45cf-9e71-fc2934e2c2be' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-23f51a52-1393-45cf-9e71-fc2934e2c2be' 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-d31c4bd2-dc18-4cad-9887-136dae108cf0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d31c4bd2-dc18-4cad-9887-136dae108cf0' 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-3e91baad-b326-4430-9a2a-e0c2ed7938f3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3e91baad-b326-4430-9a2a-e0c2ed7938f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7300b3d-7b29-45b7-9130-cd9fe97093f2' class='xr-var-data-in' type='checkbox'><label for='data-d7300b3d-7b29-45b7-9130-cd9fe97093f2' 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-e5f91547-e93b-4545-b5ae-afd4edd0ec9b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5f91547-e93b-4545-b5ae-afd4edd0ec9b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41b9ee1d-2f3f-4bff-8f0b-b7b99d85fca2' class='xr-var-data-in' type='checkbox'><label for='data-41b9ee1d-2f3f-4bff-8f0b-b7b99d85fca2' 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-910d2eb4-849d-4198-991f-eed4105d54b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-910d2eb4-849d-4198-991f-eed4105d54b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ebfc2a4a-bd28-42ff-86f7-9be6b553f0e3' class='xr-var-data-in' type='checkbox'><label for='data-ebfc2a4a-bd28-42ff-86f7-9be6b553f0e3' 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-5c07d7ef-6916-458b-8690-b77fa98fd670' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5c07d7ef-6916-458b-8690-b77fa98fd670' 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-b2239984-88a9-4f89-9c18-b06618a0fccc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b2239984-88a9-4f89-9c18-b06618a0fccc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2bd39b65-db06-47fb-8cfe-684f1d2fa202' class='xr-var-data-in' type='checkbox'><label for='data-2bd39b65-db06-47fb-8cfe-684f1d2fa202' 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-599b1cc3-40d3-4ba5-bc6e-4d122f46601a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-599b1cc3-40d3-4ba5-bc6e-4d122f46601a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0036f9d8-2ebe-4b83-b347-cf0fbd138285' class='xr-var-data-in' type='checkbox'><label for='data-0036f9d8-2ebe-4b83-b347-cf0fbd138285' 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>cell_methods :</span></dt><dd>time: mean</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-db1b528c-9fbc-47cc-be89-fe69b76fdeb0' class='xr-section-summary-in' type='checkbox'  ><label for='section-db1b528c-9fbc-47cc-be89-fe69b76fdeb0' class='xr-section-summary' >Attributes: <span>(165)</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-1.7</dd><dt><span>history :</span></dt><dd>Thu Jul 07 17:39:57 2022: cdo remapnn,grid.des miroc5_pr_197001-200512.nc miroc_remap.nc\n",
       "Mon Jun 27 15:34:28 2022: cdo mergetime pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_197001-198012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_198101-199012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_199101-200012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_200101-200512.nc miroc5_pr_197001-200512.nc\n",
       "2018-05-11 16:23:33 : Created by RegCM RegCM Model program</dd><dt><span>source :</span></dt><dd>RegCM Model output file</dd><dt><span>institution :</span></dt><dd>Oak Ridge National Laboratory</dd><dt><span>project_id :</span></dt><dd>CORDEX</dd><dt><span>ipcc_scenario_code :</span></dt><dd>HISTORICAL</dd><dt><span>institute_id :</span></dt><dd>ORNL</dd><dt><span>note :</span></dt><dd>The domain is larger than WAS-22</dd><dt><span>comment :</span></dt><dd>RegCM CORDEX SAsia25 run</dd><dt><span>experiment :</span></dt><dd>WAS-22</dd><dt><span>driving_model_ensemble_member :</span></dt><dd>r1i1p1</dd><dt><span>creation_date :</span></dt><dd>2019-09-12T16:23:22Z</dd><dt><span>CORDEX_domain :</span></dt><dd>WAS-22</dd><dt><span>rcm_version_id :</span></dt><dd>v0</dd><dt><span>ICTP_version_note :</span></dt><dd>Model run at ORNL on Titan</dd><dt><span>contact :</span></dt><dd>mashfaq@ornl.gov</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>tracking_id :</span></dt><dd>635194b8-8309-11e9-827b-f04da273f023</dd><dt><span>title :</span></dt><dd>ICTP Regional Climatic model V4</dd><dt><span>references :</span></dt><dd>http://gforge.ictp.it/gf/project/regcm</dd><dt><span>model_revision :</span></dt><dd>tag-4.7.0</dd><dt><span>projection :</span></dt><dd>ROTMER</dd><dt><span>grid_size_in_meters :</span></dt><dd>25000.0</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>13.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>70.0</dd><dt><span>grid_north_pole_latitude :</span></dt><dd>13.0</dd><dt><span>grid_north_pole_longitude :</span></dt><dd>70.0</dd><dt><span>grid_factor :</span></dt><dd>0.0</dd><dt><span>landsurface_model :</span></dt><dd>clm4.5</dd><dt><span>model_icbc_data_source :</span></dt><dd>MI_85</dd><dt><span>model_sst_data_source :</span></dt><dd>MI_85</dd><dt><span>boundary_nspgx :</span></dt><dd>30</dd><dt><span>boundary_nspgd :</span></dt><dd>30</dd><dt><span>boundary_high_nudge :</span></dt><dd>8.0</dd><dt><span>boundary_medium_nudge :</span></dt><dd>6.0</dd><dt><span>boundary_low_nudge :</span></dt><dd>4.0</dd><dt><span>boundary_nm :</span></dt><dd>-1.0</dd><dt><span>boundary_dm :</span></dt><dd>-1.0</dd><dt><span>model_is_restarted :</span></dt><dd>No</dd><dt><span>model_simulation_initial_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_end :</span></dt><dd> 1975-01-01 00:00:00 UTC</dd><dt><span>atmosphere_time_step_in_seconds :</span></dt><dd>40.0</dd><dt><span>surface_interaction_time_step_in_seconds :</span></dt><dd>480.0</dd><dt><span>convection_time_step_in_seconds :</span></dt><dd>240.0</dd><dt><span>radiation_scheme_time_step_in_seconds :</span></dt><dd>1800.0</dd><dt><span>absorption_emission_time_step_in_seconds :</span></dt><dd>64800.0</dd><dt><span>dynamical_core :</span></dt><dd>1</dd><dt><span>asselin_filter_nu_1 :</span></dt><dd>0.0625</dd><dt><span>asselin_filter_nu_2 :</span></dt><dd>0.0625</dd><dt><span>diffusion_hgt_factor :</span></dt><dd>1</dd><dt><span>upstream_mode :</span></dt><dd>Yes</dd><dt><span>off_centering_max :</span></dt><dd>0.25</dd><dt><span>stability_enhance :</span></dt><dd>Yes</dd><dt><span>temperature_extreme_gradient :</span></dt><dd>5.0</dd><dt><span>cloud_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>vapor_extreme_gradient_fraction :</span></dt><dd>0.2</dd><dt><span>tracer_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>lateral_boundary_condition_scheme :</span></dt><dd>5</dd><dt><span>semi_lagrangian_advection_scheme :</span></dt><dd>0</dd><dt><span>boundary_layer_scheme :</span></dt><dd>2</dd><dt><span>cumulus_convection_scheme_lnd :</span></dt><dd>4</dd><dt><span>cumulus_convection_scheme_ocn :</span></dt><dd>5</dd><dt><span>moisture_scheme :</span></dt><dd>1</dd><dt><span>ocean_flux_scheme :</span></dt><dd>2</dd><dt><span>zeng_ocean_roughness_formula :</span></dt><dd>1</dd><dt><span>zeng_ocean_roughness_method :</span></dt><dd>1</dd><dt><span>pressure_gradient_scheme :</span></dt><dd>0</dd><dt><span>surface_emissivity_factor_computed :</span></dt><dd>0</dd><dt><span>lake_model_activated :</span></dt><dd>0</dd><dt><span>chemical_aerosol_scheme_activated :</span></dt><dd>0</dd><dt><span>diurnal_cycle_sst_scheme :</span></dt><dd>0</dd><dt><span>ocean_precipitaion_cooling_effect :</span></dt><dd>0</dd><dt><span>ocean_albedo_from_whitecapping :</span></dt><dd>0</dd><dt><span>simple_sea_ice_scheme :</span></dt><dd>0</dd><dt><span>seasonal_desert_albedo :</span></dt><dd>0</dd><dt><span>convective_lwp_as_large_scale :</span></dt><dd>0</dd><dt><span>large_scale_cloud_fraction_scheme :</span></dt><dd>0</dd><dt><span>ocean_stratiform_clouds_scheme :</span></dt><dd>1</dd><dt><span>rrtm_radiation_scheme_activated :</span></dt><dd>0</dd><dt><span>climatic_ozone_input_dataset :</span></dt><dd>0</dd><dt><span>climatic_aerosol_input_dataset :</span></dt><dd>0</dd><dt><span>static_solar_constant_used :</span></dt><dd>0</dd><dt><span>cumulus_cloud_model :</span></dt><dd>1</dd><dt><span>sun_year_offset :</span></dt><dd>0.0</dd><dt><span>fix_solar_parameters :</span></dt><dd>0</dd><dt><span>cloud_bottom_level_with_no_clouds :</span></dt><dd>1</dd><dt><span>cloud_rh_with_fcc_one :</span></dt><dd>1.01</dd><dt><span>cloud_rh_threshold_for_land :</span></dt><dd>0.8</dd><dt><span>cloud_rh_threshold_for_ocean :</span></dt><dd>0.9</dd><dt><span>cloud_rh1_limit_temperature :</span></dt><dd>238.0</dd><dt><span>cloud_cloud_fraction_maximum :</span></dt><dd>0.75</dd><dt><span>cloud_condensation_threshold :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_fraction_max_for_convection :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_liqwat_max_for_convection :</span></dt><dd>0.0003</dd><dt><span>cloud_shallow_convective_cf_param :</span></dt><dd>0.07</dd><dt><span>cloud_deep_convective_cf_param :</span></dt><dd>0.14</dd><dt><span>cloud_k2_convective_cf_param :</span></dt><dd>500.0</dd><dt><span>cloud_surface_radiation_hack :</span></dt><dd>No</dd><dt><span>cloud_arctic_cloud_correction :</span></dt><dd>Yes</dd><dt><span>subex_auto_conversion_rate_for_land :</span></dt><dd>0.00025</dd><dt><span>subex_auto_conversion_rate_for_ocean :</span></dt><dd>0.00025</dd><dt><span>subex_gultepe_factor_when_rain_for_land :</span></dt><dd>0.4</dd><dt><span>subex_gultepe_factor_when_rain_for_ocean :</span></dt><dd>0.4</dd><dt><span>subex_land_raindrop_evaporation_rate :</span></dt><dd>0.0002</dd><dt><span>subex_ocean_raindrop_evaporation_rate :</span></dt><dd>0.0001</dd><dt><span>subex_land_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>subex_ocean_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>mit_lowest_convection_sigma :</span></dt><dd>0.95</dd><dt><span>mit_autoconversion_threshold_mixing_over_ocean :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_mixing_over_land :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_temperature :</span></dt><dd>-55.0</dd><dt><span>mit_mixing_coefficient_in_entrainment :</span></dt><dd>1.5</dd><dt><span>mit_fractional_area_unsaturated_downdraft :</span></dt><dd>0.05</dd><dt><span>mit_fractional_precip_outside_cloud :</span></dt><dd>0.12</dd><dt><span>mit_pressure_velocity_of_rain :</span></dt><dd>50.0</dd><dt><span>mit_pressure_velocity_of_snow :</span></dt><dd>5.5</dd><dt><span>mit_rain_evaporation_coefficient :</span></dt><dd>1.0</dd><dt><span>mit_snow_evaporation_coefficient :</span></dt><dd>0.8</dd><dt><span>mit_momentum_transport_coefficient :</span></dt><dd>0.7</dd><dt><span>mit_downdraft_velocity_coefficient :</span></dt><dd>10.0</dd><dt><span>mit_max_parcel_neg_temp_perturbation :</span></dt><dd>0.9</dd><dt><span>mit_approach_rate_quasi_eq_coeff_a :</span></dt><dd>0.2</dd><dt><span>mit_approach_rate_quasi_eq_coeff_d :</span></dt><dd>0.1</dd><dt><span>mit_maximum_land_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>mit_maximum_ocean_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>tiedtke_actual_scheme :</span></dt><dd>4</dd><dt><span>tiedtke_entrainment_rate_downdraft :</span></dt><dd>0.0003</dd><dt><span>tiedtke_entrainment_rate_deep_land :</span></dt><dd>0.00075</dd><dt><span>tiedtke_entrainment_rate_deep_ocean :</span></dt><dd>0.00075</dd><dt><span>tiedtke_penetrative :</span></dt><dd>Yes</dd><dt><span>tiedtke_midlevel :</span></dt><dd>Yes</dd><dt><span>tiedtke_shallow :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_downdraft :</span></dt><dd>Yes</dd><dt><span>tiedtke_prognostic_cloud :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_friction :</span></dt><dd>Yes</dd><dt><span>tiedtke_ke_dissipation :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_transport :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_smooth_massflux :</span></dt><dd>No</dd><dt><span>tiedtke_shallow_wstar_closure :</span></dt><dd>No</dd><dt><span>tiedtke_detrainment_rate_deep_land :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_detrainment_rate_deep_ocean :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_shallow_entrainment :</span></dt><dd>2.0</dd><dt><span>tiedtke_cloud_cover_evap_over_land :</span></dt><dd>0.05</dd><dt><span>tiedtke_cloud_cover_evap_over_ocean :</span></dt><dd>0.05</dd><dt><span>tiedtke_coeff_evap_over_land :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_coeff_evap_over_ocean :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_critical_rh_over_land :</span></dt><dd>0.9</dd><dt><span>tiedtke_critical_rh_over_ocean :</span></dt><dd>0.9</dd><dt><span>tiedtke_cloud_water_conv_over_land :</span></dt><dd>0.03</dd><dt><span>tiedtke_cloud_water_conv_over_ocean :</span></dt><dd>0.0014</dd><dt><span>tiedtke_cape_adjustment_timescale :</span></dt><dd>2400.0</dd><dt><span>uwpbl_advection_scheme :</span></dt><dd>0</dd><dt><span>uwpbl_cloud_evap_entr_incr_efficiency :</span></dt><dd>15.0</dd><dt><span>uwpbl_eddy_LS_stable_PBL_scaling :</span></dt><dd>1.5</dd><dt><span>uwpbl_czero :</span></dt><dd>5.869</dd><dt><span>uwpbl_nuk :</span></dt><dd>5.0</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>driving_experiment :</span></dt><dd>MIROC-MIROC5, historical, r1i1p1</dd><dt><span>driving_model_id :</span></dt><dd>MIROC-MIROC5</dd><dt><span>driving_experiment_name :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>ICTP-RegCM4-7</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: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:39:57 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment:                              MIROC-MIROC5, historical...\n",
       "    driving_model_id:                                MIROC-MIROC5\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    CDO:                                             Climate Data Operators v..."
      ]
     },
     "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": "17f8e12a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#data.x.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5d9405f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "#interpolating to low resolution \n",
    "#new_lon=np.arange(86,94,0.5)\n",
    "#new_lat=np.arange(17,28,.5)\n",
    "#jjas_data = jjas_data.interp(lon=new_lon,lat=new_lat)\n",
    "#jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "be94f5d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#jjas_data.x.values\n",
    "#jjas_data.y.values\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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": 19,
   "id": "18269e45",
   "metadata": {},
   "outputs": [
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       "\n",
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       "  background-color: var(--xr-background-color-row-odd);\n",
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       "\n",
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       "\n",
       ".xr-var-dims {\n",
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       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
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       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
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       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
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       "\n",
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       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
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       "\n",
       ".xr-attrs dt,\n",
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       ".xr-attrs dt {\n",
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       "  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",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (lat: 40, lon: 32)&gt;\n",
       "array([[2.17927827e-05, 2.13933308e-05, 2.12567156e-05, ...,\n",
       "        7.59974355e-05, 8.08874975e-05, 8.77504499e-05],\n",
       "       [2.11864317e-05, 2.08832516e-05, 2.05256001e-05, ...,\n",
       "        7.75653607e-05, 8.54473838e-05, 8.36988838e-05],\n",
       "       [2.05653923e-05, 2.03335239e-05, 1.94794156e-05, ...,\n",
       "        8.46634139e-05, 9.55786963e-05, 1.00208075e-04],\n",
       "       ...,\n",
       "       [2.16806046e-04, 2.42528797e-04, 2.79345782e-04, ...,\n",
       "        2.20444737e-04, 2.11302875e-04, 1.82475691e-04],\n",
       "       [2.20107308e-04, 2.60711648e-04, 3.16639838e-04, ...,\n",
       "        1.96795168e-04, 2.29429701e-04, 2.49268167e-04],\n",
       "       [2.11126186e-04, 3.36772064e-04, 5.30796999e-04, ...,\n",
       "        2.05720760e-04, 2.63516587e-04, 3.31312971e-04]], 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-5a566274-c087-49d5-be4a-8150b3e9f6d0' class='xr-array-in' type='checkbox' checked><label for='section-5a566274-c087-49d5-be4a-8150b3e9f6d0' 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>2.179e-05 2.139e-05 2.126e-05 ... 0.0002057 0.0002635 0.0003313</span></div><div class='xr-array-data'><pre>array([[2.17927827e-05, 2.13933308e-05, 2.12567156e-05, ...,\n",
       "        7.59974355e-05, 8.08874975e-05, 8.77504499e-05],\n",
       "       [2.11864317e-05, 2.08832516e-05, 2.05256001e-05, ...,\n",
       "        7.75653607e-05, 8.54473838e-05, 8.36988838e-05],\n",
       "       [2.05653923e-05, 2.03335239e-05, 1.94794156e-05, ...,\n",
       "        8.46634139e-05, 9.55786963e-05, 1.00208075e-04],\n",
       "       ...,\n",
       "       [2.16806046e-04, 2.42528797e-04, 2.79345782e-04, ...,\n",
       "        2.20444737e-04, 2.11302875e-04, 1.82475691e-04],\n",
       "       [2.20107308e-04, 2.60711648e-04, 3.16639838e-04, ...,\n",
       "        1.96795168e-04, 2.29429701e-04, 2.49268167e-04],\n",
       "       [2.11126186e-04, 3.36772064e-04, 5.30796999e-04, ...,\n",
       "        2.05720760e-04, 2.63516587e-04, 3.31312971e-04]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-c6cca47f-806a-4f1e-b1fb-85807d4276ec' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c6cca47f-806a-4f1e-b1fb-85807d4276ec' 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-470bbf3b-427c-40f5-bd62-393d9fd4202a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-470bbf3b-427c-40f5-bd62-393d9fd4202a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2d3bbcc-9b21-4c27-a036-be5faa4ef557' class='xr-var-data-in' type='checkbox'><label for='data-a2d3bbcc-9b21-4c27-a036-be5faa4ef557' 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-b04d792b-a4c5-44a2-be1a-0e2267984472' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b04d792b-a4c5-44a2-be1a-0e2267984472' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f00680e1-fc3d-4c78-9d1e-faf77cc032bf' class='xr-var-data-in' type='checkbox'><label for='data-f00680e1-fc3d-4c78-9d1e-faf77cc032bf' 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-c4765fa1-ba65-436f-8ba3-af1cbca0ec41' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c4765fa1-ba65-436f-8ba3-af1cbca0ec41' 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([[2.17927827e-05, 2.13933308e-05, 2.12567156e-05, ...,\n",
       "        7.59974355e-05, 8.08874975e-05, 8.77504499e-05],\n",
       "       [2.11864317e-05, 2.08832516e-05, 2.05256001e-05, ...,\n",
       "        7.75653607e-05, 8.54473838e-05, 8.36988838e-05],\n",
       "       [2.05653923e-05, 2.03335239e-05, 1.94794156e-05, ...,\n",
       "        8.46634139e-05, 9.55786963e-05, 1.00208075e-04],\n",
       "       ...,\n",
       "       [2.16806046e-04, 2.42528797e-04, 2.79345782e-04, ...,\n",
       "        2.20444737e-04, 2.11302875e-04, 1.82475691e-04],\n",
       "       [2.20107308e-04, 2.60711648e-04, 3.16639838e-04, ...,\n",
       "        1.96795168e-04, 2.29429701e-04, 2.49268167e-04],\n",
       "       [2.11126186e-04, 3.36772064e-04, 5.30796999e-04, ...,\n",
       "        2.05720760e-04, 2.63516587e-04, 3.31312971e-04]], 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": 19,
     "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": 20,
   "id": "6f88bd72",
   "metadata": {},
   "outputs": [
    {
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       ".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",
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       "\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",
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       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
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       "\n",
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       "\n",
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       "  background-color: var(--xr-background-color-row-even);\n",
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       ".xr-var-list > li:nth-child(odd) > div,\n",
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       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
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       ".xr-attrs dt:hover {\n",
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       "  width: auto;\n",
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       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
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       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
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       "\n",
       ".xr-var-data > table {\n",
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       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
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       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
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       "\n",
       "dl.xr-attrs {\n",
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       "  grid-template-columns: 125px auto;\n",
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       "\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",
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       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (lat: 40, lon: 32)&gt;\n",
       "array([[ 1.88289643,  1.84838378,  1.83658023, ...,  6.56617843,\n",
       "         6.98867978,  7.58163887],\n",
       "       [ 1.8305077 ,  1.80431294,  1.77341185, ...,  6.70164716,\n",
       "         7.38265396,  7.23158356],\n",
       "       [ 1.7768499 ,  1.75681647,  1.68302151, ...,  7.31491896,\n",
       "         8.25799936,  8.65797771],\n",
       "       ...,\n",
       "       [18.73204233, 20.95448803, 24.13547561, ..., 19.04642531,\n",
       "        18.2565684 , 15.7658997 ],\n",
       "       [19.01727137, 22.52548635, 27.35768203, ..., 17.00310255,\n",
       "        19.82272617, 21.53676962],\n",
       "       [18.24130244, 29.09710631, 45.86086068, ..., 17.77427369,\n",
       "        22.76783315, 28.62544069]])\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-f5a0126e-871b-41ec-85fd-6f1c912bb401' class='xr-array-in' type='checkbox' checked><label for='section-f5a0126e-871b-41ec-85fd-6f1c912bb401' 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>1.883 1.848 1.837 1.85 1.887 1.882 ... 26.86 20.8 17.77 22.77 28.63</span></div><div class='xr-array-data'><pre>array([[ 1.88289643,  1.84838378,  1.83658023, ...,  6.56617843,\n",
       "         6.98867978,  7.58163887],\n",
       "       [ 1.8305077 ,  1.80431294,  1.77341185, ...,  6.70164716,\n",
       "         7.38265396,  7.23158356],\n",
       "       [ 1.7768499 ,  1.75681647,  1.68302151, ...,  7.31491896,\n",
       "         8.25799936,  8.65797771],\n",
       "       ...,\n",
       "       [18.73204233, 20.95448803, 24.13547561, ..., 19.04642531,\n",
       "        18.2565684 , 15.7658997 ],\n",
       "       [19.01727137, 22.52548635, 27.35768203, ..., 17.00310255,\n",
       "        19.82272617, 21.53676962],\n",
       "       [18.24130244, 29.09710631, 45.86086068, ..., 17.77427369,\n",
       "        22.76783315, 28.62544069]])</pre></div></div></li><li class='xr-section-item'><input id='section-8b5fa901-cf37-4eac-8716-d0526c1f1cda' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8b5fa901-cf37-4eac-8716-d0526c1f1cda' 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-1faea925-09ac-46d0-8fc2-0dd554b34255' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1faea925-09ac-46d0-8fc2-0dd554b34255' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-00658e3e-e5dd-4bd0-9c3f-7c54294f8d7a' class='xr-var-data-in' type='checkbox'><label for='data-00658e3e-e5dd-4bd0-9c3f-7c54294f8d7a' 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-69460235-6f2a-45bb-92b7-09836ee5ff50' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69460235-6f2a-45bb-92b7-09836ee5ff50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6d60c1c-e162-44d0-bb40-a0694bbe0c76' class='xr-var-data-in' type='checkbox'><label for='data-d6d60c1c-e162-44d0-bb40-a0694bbe0c76' 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-139f3814-1eef-478d-a4de-e29a299db838' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-139f3814-1eef-478d-a4de-e29a299db838' 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([[ 1.88289643,  1.84838378,  1.83658023, ...,  6.56617843,\n",
       "         6.98867978,  7.58163887],\n",
       "       [ 1.8305077 ,  1.80431294,  1.77341185, ...,  6.70164716,\n",
       "         7.38265396,  7.23158356],\n",
       "       [ 1.7768499 ,  1.75681647,  1.68302151, ...,  7.31491896,\n",
       "         8.25799936,  8.65797771],\n",
       "       ...,\n",
       "       [18.73204233, 20.95448803, 24.13547561, ..., 19.04642531,\n",
       "        18.2565684 , 15.7658997 ],\n",
       "       [19.01727137, 22.52548635, 27.35768203, ..., 17.00310255,\n",
       "        19.82272617, 21.53676962],\n",
       "       [18.24130244, 29.09710631, 45.86086068, ..., 17.77427369,\n",
       "        22.76783315, 28.62544069]])\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": [
    "miroc = jjas_mean*86400\n",
    "miroc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6c5c5811",
   "metadata": {},
   "outputs": [
    {
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       ".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",
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       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
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       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
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       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (lat: 40, lon: 32)&gt;\n",
       "array([[        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       ...,\n",
       "       [        nan, 10.83327154, 13.84285654, ..., 10.56501529,\n",
       "         8.38815715,         nan],\n",
       "       [        nan, 13.93167096, 20.19822672, ...,  9.47554355,\n",
       "        11.15605605,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan]])\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-01f203ed-8fc9-4dba-b303-02b70bcde296' class='xr-array-in' type='checkbox' checked><label for='section-01f203ed-8fc9-4dba-b303-02b70bcde296' 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 nan ... nan nan nan nan nan nan nan nan</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",
       "       [        nan, 10.83327154, 13.84285654, ..., 10.56501529,\n",
       "         8.38815715,         nan],\n",
       "       [        nan, 13.93167096, 20.19822672, ...,  9.47554355,\n",
       "        11.15605605,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan]])</pre></div></div></li><li class='xr-section-item'><input id='section-52ebf63b-7466-45d1-afb9-bed58ce793fa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-52ebf63b-7466-45d1-afb9-bed58ce793fa' 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-ecf63e46-7d80-4500-8112-1322271336c5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ecf63e46-7d80-4500-8112-1322271336c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10a795a5-3b7e-418b-87ff-54bcaec748d1' class='xr-var-data-in' type='checkbox'><label for='data-10a795a5-3b7e-418b-87ff-54bcaec748d1' 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-5c7277d0-cd49-4a15-b600-dfcbfa6c8dc6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c7277d0-cd49-4a15-b600-dfcbfa6c8dc6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cae27db5-7208-4ae0-82b1-35ec8014b05b' class='xr-var-data-in' type='checkbox'><label for='data-cae27db5-7208-4ae0-82b1-35ec8014b05b' 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-d0e4c54f-69eb-4eaa-a103-637cc1fd0dd8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d0e4c54f-69eb-4eaa-a103-637cc1fd0dd8' 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",
       "       [        nan, 10.83327154, 13.84285654, ..., 10.56501529,\n",
       "         8.38815715,         nan],\n",
       "       [        nan, 13.93167096, 20.19822672, ...,  9.47554355,\n",
       "        11.15605605,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan]])\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": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bias = miroc - cru\n",
    "bias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "445388ed",
   "metadata": {},
   "outputs": [
    {
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       "\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.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",
       "       [         nan, 107.0352713 , 134.49304255, ..., 124.56673208,\n",
       "         85.00007701,          nan],\n",
       "       [         nan, 162.1127559 , 282.11960044, ..., 125.87803763,\n",
       "        128.72367252,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan]])\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-a07ae687-95b0-4133-b09e-cdd03acab0ca' class='xr-array-in' type='checkbox' checked><label for='section-a07ae687-95b0-4133-b09e-cdd03acab0ca' 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 nan ... nan nan nan nan nan nan nan nan</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",
       "       [         nan, 107.0352713 , 134.49304255, ..., 124.56673208,\n",
       "         85.00007701,          nan],\n",
       "       [         nan, 162.1127559 , 282.11960044, ..., 125.87803763,\n",
       "        128.72367252,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan]])</pre></div></div></li><li class='xr-section-item'><input id='section-b722e524-fec4-4741-b459-e216846abfd2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b722e524-fec4-4741-b459-e216846abfd2' 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-698d408f-e978-4fca-9619-f706b095494c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-698d408f-e978-4fca-9619-f706b095494c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-730c5bb4-2100-49b2-8edc-1710e2f040c7' class='xr-var-data-in' type='checkbox'><label for='data-730c5bb4-2100-49b2-8edc-1710e2f040c7' 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-f41f1e38-ae2a-4999-aac0-73468d590457' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f41f1e38-ae2a-4999-aac0-73468d590457' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25da7a3c-80c5-44e5-9a69-35a4b82397d3' class='xr-var-data-in' type='checkbox'><label for='data-25da7a3c-80c5-44e5-9a69-35a4b82397d3' 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-ad3ba7b2-b788-4bed-991a-984d257e56b3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ad3ba7b2-b788-4bed-991a-984d257e56b3' 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",
       "       [         nan, 107.0352713 , 134.49304255, ..., 124.56673208,\n",
       "         85.00007701,          nan],\n",
       "       [         nan, 162.1127559 , 282.11960044, ..., 125.87803763,\n",
       "        128.72367252,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan]])\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": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bias_percentage = ((miroc - cru)/cru)*100\n",
    "bias_percentage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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",
    "plt.rcParams['font.size'] = '16'\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize=(12,9.5))\n",
    "\n",
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "ax.set_extent([88,93,20,27])\n",
    "\n",
    "\n",
    "m1 = ax.contourf(bias['lon'], bias['lat'],bias[:,:],\n",
    "                levels=np.arange(-15,15+3,3),   transform = ccrs.PlateCarree(),cmap='BrBG',extend='both')\n",
    "\n",
    " \n",
    "# Define the xticks for longitude\n",
    "ax.set_xticks(np.arange(87,94,1), crs=ccrs.PlateCarree())\n",
    "lon_formatter = cticker.LongitudeFormatter()\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "\n",
    "# Define the yticks for latitude\n",
    "ax.set_yticks(np.arange(20,28,1), crs=ccrs.PlateCarree())\n",
    "lat_formatter = cticker.LatitudeFormatter()\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "\n",
    "\n",
    "plt.colorbar(m1,ticks=np.arange(-15,15+3,3),  orientation = 'horizontal',shrink=0.5, fraction = 0.04 , label = 'mm/day')\n",
    "ax.coastlines(linewidth=3)\n",
    "ax.add_feature(cfeature.BORDERS,linewidth=3)\n",
    "\n",
    "\n",
    "plt.title('Seasonal Bias(RegCM MIROC5-CRU)',fontsize=17)\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/Seasonal Bias(miroc5-cru).png\")\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "9003db92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x684 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting bias percentage \n",
    "\n",
    "#plotting with cartopy\n",
    "import cartopy.feature as cfeature\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize=(12,9.5))\n",
    "\n",
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "ax.set_extent([88,93,20,27])\n",
    "\n",
    "\n",
    "m1 = ax.contourf(bias_percentage['lon'][:], bias_percentage['lat'][:],bias_percentage[:,:],\n",
    "                levels=np.arange(-150,150+25,25), transform = ccrs.PlateCarree(),cmap='BrBG',extend='both')\n",
    "\n",
    " \n",
    "# Define the xticks for longitude\n",
    "ax.set_xticks(np.arange(87,94,1), crs=ccrs.PlateCarree())\n",
    "lon_formatter = cticker.LongitudeFormatter()\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "\n",
    "# Define the yticks for latitude\n",
    "ax.set_yticks(np.arange(20,28,1), crs=ccrs.PlateCarree())\n",
    "lat_formatter = cticker.LatitudeFormatter()\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "\n",
    "\n",
    "plt.colorbar(m1,ticks=np.arange(-150,150+25,25), orientation = 'horizontal',shrink=0.5, fraction = 0.04 , label = 'percentage')\n",
    "ax.coastlines(linewidth=3)\n",
    "ax.add_feature(cfeature.BORDERS,linewidth=3)\n",
    " \n",
    "    \n",
    "plt.title('Seasonal Bias-Percentage(RegCM MIROC5-CRU)',fontsize=17)\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/Seasonal Bias_percentage(miroc5-cru).png\")\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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": 25,
     "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'''"
   ]
  },
  {
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   "execution_count": null,
   "id": "87f4ea28",
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   "source": []
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   "execution_count": null,
   "id": "20e38f40",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "21be7cc5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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