Seasonal Bias ensemble average(RegCM-trmm).ipynb

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    "#writing some conda package or module\n",
    "#!pip install netCDF4\n",
    "%matplotlib inline\n",
    "import warnings\n",
    "from netCDF4 import Dataset\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "#!pip install cartopy\n",
    "import cartopy.feature as cfeature\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.mpl.ticker as cticker\n",
    "from cartopy.util import add_cyclic_point"
   ]
  },
  {
   "cell_type": "code",
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       "    nco_openmp_thread_number:  1</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-4b77c856-2362-415f-84c2-67de3a5dddbf' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4b77c856-2362-415f-84c2-67de3a5dddbf' 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>: 132</li><li><span class='xr-has-index'>lat</span>: 400</li><li><span class='xr-has-index'>lon</span>: 1440</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-74128980-9f0e-4d6f-8e0f-f7ffc89c792c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-74128980-9f0e-4d6f-8e0f-f7ffc89c792c' 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'>1998-01-01 ... 2008-12-01</div><input id='attrs-cfa4b931-950e-4289-b21f-8189e9f78b9a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cfa4b931-950e-4289-b21f-8189e9f78b9a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65a39308-09e9-4e7a-abe7-323db757fb5c' class='xr-var-data-in' type='checkbox'><label for='data-65a39308-09e9-4e7a-abe7-323db757fb5c' 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;1998-01-01T00:00:00.000000000&#x27;, &#x27;1998-02-01T00:00:00.000000000&#x27;,\n",
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       "       &#x27;2002-05-01T00:00:00.000000000&#x27;, &#x27;2002-06-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-07-01T00:00:00.000000000&#x27;, &#x27;2002-08-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-09-01T00:00:00.000000000&#x27;, &#x27;2002-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-11-01T00:00:00.000000000&#x27;, &#x27;2002-12-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-01-01T00:00:00.000000000&#x27;, &#x27;2003-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-03-01T00:00:00.000000000&#x27;, &#x27;2003-04-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-05-01T00:00:00.000000000&#x27;, &#x27;2003-06-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-07-01T00:00:00.000000000&#x27;, &#x27;2003-08-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-09-01T00:00:00.000000000&#x27;, &#x27;2003-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-11-01T00:00:00.000000000&#x27;, &#x27;2003-12-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-01-01T00:00:00.000000000&#x27;, &#x27;2004-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-03-01T00:00:00.000000000&#x27;, &#x27;2004-04-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-05-01T00:00:00.000000000&#x27;, &#x27;2004-06-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-07-01T00:00:00.000000000&#x27;, &#x27;2004-08-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-09-01T00:00:00.000000000&#x27;, &#x27;2004-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-11-01T00:00:00.000000000&#x27;, &#x27;2004-12-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-01-01T00:00:00.000000000&#x27;, &#x27;2005-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-03-01T00:00:00.000000000&#x27;, &#x27;2005-04-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-05-01T00:00:00.000000000&#x27;, &#x27;2005-06-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-07-01T00:00:00.000000000&#x27;, &#x27;2005-08-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-09-01T00:00:00.000000000&#x27;, &#x27;2005-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-11-01T00:00:00.000000000&#x27;, &#x27;2005-12-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2006-01-01T00:00:00.000000000&#x27;, &#x27;2006-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2006-03-01T00:00:00.000000000&#x27;, &#x27;2006-04-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2006-05-01T00:00:00.000000000&#x27;, &#x27;2006-06-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2006-07-01T00:00:00.000000000&#x27;, &#x27;2006-08-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2006-09-01T00:00:00.000000000&#x27;, &#x27;2006-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2006-11-01T00:00:00.000000000&#x27;, &#x27;2006-12-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2007-01-01T00:00:00.000000000&#x27;, &#x27;2007-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2007-03-01T00:00:00.000000000&#x27;, &#x27;2007-04-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2007-05-01T00:00:00.000000000&#x27;, &#x27;2007-06-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2007-07-01T00:00:00.000000000&#x27;, &#x27;2007-08-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2007-09-01T00:00:00.000000000&#x27;, &#x27;2007-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2007-11-01T00:00:00.000000000&#x27;, &#x27;2007-12-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2008-01-01T00:00:00.000000000&#x27;, &#x27;2008-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2008-03-01T00:00:00.000000000&#x27;, &#x27;2008-04-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2008-05-01T00:00:00.000000000&#x27;, &#x27;2008-06-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2008-07-01T00:00:00.000000000&#x27;, &#x27;2008-08-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2008-09-01T00:00:00.000000000&#x27;, &#x27;2008-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2008-11-01T00:00:00.000000000&#x27;, &#x27;2008-12-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-49.88 -49.62 ... 49.62 49.88</div><input id='attrs-0c3152ac-049e-4a81-b0ad-4d1134ef4c4c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c3152ac-049e-4a81-b0ad-4d1134ef4c4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9195f9c-8a98-48bf-ad49-2ea7f6bd6669' class='xr-var-data-in' type='checkbox'><label for='data-b9195f9c-8a98-48bf-ad49-2ea7f6bd6669' 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>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-49.875, -49.625, -49.375, ...,  49.375,  49.625,  49.875],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-179.9 -179.6 ... 179.6 179.9</div><input id='attrs-1a8c55fd-4f8c-4bd7-8966-41cd1c7e1939' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a8c55fd-4f8c-4bd7-8966-41cd1c7e1939' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93597002-0392-4dc6-8f27-83ec17e0176e' class='xr-var-data-in' type='checkbox'><label for='data-93597002-0392-4dc6-8f27-83ec17e0176e' 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>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-179.875, -179.625, -179.375, ...,  179.375,  179.625,  179.875],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9d4ecf6c-5853-4801-8767-8f3514ddd867' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9d4ecf6c-5853-4801-8767-8f3514ddd867' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>date</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a03332df-525a-4aaa-bccd-40ea709f6120' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a03332df-525a-4aaa-bccd-40ea709f6120' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2de2c5bc-70f7-48f6-b7f1-4480179c1229' class='xr-var-data-in' type='checkbox'><label for='data-2de2c5bc-70f7-48f6-b7f1-4480179c1229' 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>units :</span></dt><dd>yyyymmdd</dd><dt><span>long_name :</span></dt><dd>current date</dd></dl></div><div class='xr-var-data'><pre>array([19980101, 19980201, 19980301, 19980401, 19980501, 19980601, 19980701,\n",
       "       19980801, 19980901, 19981001, 19981101, 19981201, 19990101, 19990201,\n",
       "       19990301, 19990401, 19990501, 19990601, 19990701, 19990801, 19990901,\n",
       "       19991001, 19991101, 19991201, 20000101, 20000201, 20000301, 20000401,\n",
       "       20000501, 20000601, 20000701, 20000801, 20000901, 20001001, 20001101,\n",
       "       20001201, 20010101, 20010201, 20010301, 20010401, 20010501, 20010601,\n",
       "       20010701, 20010801, 20010901, 20011001, 20011101, 20011201, 20020101,\n",
       "       20020201, 20020301, 20020401, 20020501, 20020601, 20020701, 20020801,\n",
       "       20020901, 20021001, 20021101, 20021201, 20030101, 20030201, 20030301,\n",
       "       20030401, 20030501, 20030601, 20030701, 20030801, 20030901, 20031001,\n",
       "       20031101, 20031201, 20040101, 20040201, 20040301, 20040401, 20040501,\n",
       "       20040601, 20040701, 20040801, 20040901, 20041001, 20041101, 20041201,\n",
       "       20050101, 20050201, 20050301, 20050401, 20050501, 20050601, 20050701,\n",
       "       20050801, 20050901, 20051001, 20051101, 20051201, 20060101, 20060201,\n",
       "       20060301, 20060401, 20060501, 20060601, 20060701, 20060801, 20060901,\n",
       "       20061001, 20061101, 20061201, 20070101, 20070201, 20070301, 20070401,\n",
       "       20070501, 20070601, 20070701, 20070801, 20070901, 20071001, 20071101,\n",
       "       20071201, 20080101, 20080201, 20080301, 20080401, 20080501, 20080601,\n",
       "       20080701, 20080801, 20080901, 20081001, 20081101, 20081201], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>datesec</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9e42769b-db0f-438d-b73d-5c0407f67c9d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9e42769b-db0f-438d-b73d-5c0407f67c9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a101c8b1-19f4-4cf0-aa83-e850aef487e4' class='xr-var-data-in' type='checkbox'><label for='data-a101c8b1-19f4-4cf0-aa83-e850aef487e4' 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>current seconds of current date</dd></dl></div><div class='xr-var-data'><pre>array([86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000],\n",
       "      dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>precip</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f69926c2-eebf-46f3-8f3a-9b3e238312ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f69926c2-eebf-46f3-8f3a-9b3e238312ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d019f66e-5d93-4459-964f-e9956ac741da' class='xr-var-data-in' type='checkbox'><label for='data-d019f66e-5d93-4459-964f-e9956ac741da' 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>avg_period :</span></dt><dd>0000-00-00 01:00:00</dd><dt><span>delta_t :</span></dt><dd>0000-00-00 03:00:00</dd><dt><span>units :</span></dt><dd>mm/h</dd><dt><span>hdf_name :</span></dt><dd>precipitation</dd></dl></div><div class='xr-var-data'><pre>[76032000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6016c0f5-8cea-4723-a335-c0cc60653f58' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6016c0f5-8cea-4723-a335-c0cc60653f58' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>creation_date :</span></dt><dd>Thu Nov  5 16:19:03 CET 2009</dd><dt><span>Conventions :</span></dt><dd>None</dd><dt><span>source_html :</span></dt><dd>\n",
       "http://disc.sci.gsfc.nasa.gov/data/datapool/TRMM/01_Data_Products/02_Gridded/06_3-hour_Gpi_Cal_3B_42/index.html\n",
       "</dd><dt><span>title :</span></dt><dd>TRMM: 3B43</dd><dt><span>history :</span></dt><dd>Thu Nov  5 16:26:10 2009: ncrcat 3B43.1998.nc 3B43.1999.nc 3B43.2000.nc 3B43.2001.nc 3B43.2002.nc 3B43.2003.nc 3B43.2004.nc 3B43.2005.nc 3B43.2006.nc 3B43.2007.nc 3B43.2008.nc 3B43.1998_2008.nc\n",
       "Thu Nov  5 16:26:03 2009: ncrcat 3B43.19980101.nc 3B43.19980201.nc 3B43.19980301.nc 3B43.19980401.nc 3B43.19980501.nc 3B43.19980601.nc 3B43.19980701.nc 3B43.19980801.nc 3B43.19980901.nc 3B43.19981001.nc 3B43.19981101.nc 3B43.19981201.nc 3B43.1998.nc</dd><dt><span>nco_openmp_thread_number :</span></dt><dd>1</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 132, lat: 400, lon: 1440)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1998-01-01 1998-02-01 ... 2008-12-01\n",
       "  * lat      (lat) float32 -49.88 -49.62 -49.38 -49.12 ... 49.38 49.62 49.88\n",
       "  * lon      (lon) float32 -179.9 -179.6 -179.4 -179.1 ... 179.4 179.6 179.9\n",
       "Data variables:\n",
       "    date     (time) int32 ...\n",
       "    datesec  (time) timedelta64[ns] ...\n",
       "    precip   (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    creation_date:             Thu Nov  5 16:19:03 CET 2009\n",
       "    Conventions:               None\n",
       "    source_html:               \\nhttp://disc.sci.gsfc.nasa.gov/data/datapool/...\n",
       "    title:                     TRMM: 3B43\n",
       "    history:                   Thu Nov  5 16:26:10 2009: ncrcat 3B43.1998.nc ...\n",
       "    nco_openmp_thread_number:  1"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = xr.open_dataset('/home/mkibria/Academic/pr_of_thesis/observation/trm/MonthlyTRMM_3B43/3B43.1998_2008.nc')\n",
    " \n",
    "\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "800e4d90",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 95, lat: 400, lon: 1440)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1998-02-01 1998-03-01 ... 2005-12-01\n",
       "  * lat      (lat) float32 -49.88 -49.62 -49.38 -49.12 ... 49.38 49.62 49.88\n",
       "  * lon      (lon) float32 -179.9 -179.6 -179.4 -179.1 ... 179.4 179.6 179.9\n",
       "Data variables:\n",
       "    date     (time) int32 19980201 19980301 19980401 ... 20051101 20051201\n",
       "    datesec  (time) timedelta64[ns] 1 days 1 days 1 days ... 1 days 1 days\n",
       "    precip   (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    creation_date:             Thu Nov  5 16:19:03 CET 2009\n",
       "    Conventions:               None\n",
       "    source_html:               \\nhttp://disc.sci.gsfc.nasa.gov/data/datapool/...\n",
       "    title:                     TRMM: 3B43\n",
       "    history:                   Thu Nov  5 16:26:10 2009: ncrcat 3B43.1998.nc ...\n",
       "    nco_openmp_thread_number:  1</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-dfefdddc-fd75-4dfb-8623-e706ebcbb3f6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-dfefdddc-fd75-4dfb-8623-e706ebcbb3f6' 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>: 95</li><li><span class='xr-has-index'>lat</span>: 400</li><li><span class='xr-has-index'>lon</span>: 1440</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-17f93f41-ad28-4cc8-ad4e-a347c34e664d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-17f93f41-ad28-4cc8-ad4e-a347c34e664d' 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'>1998-02-01 ... 2005-12-01</div><input id='attrs-0eb8ac0e-0e5e-4dcb-bc00-40c9aa14c41e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0eb8ac0e-0e5e-4dcb-bc00-40c9aa14c41e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a83a267c-368f-4d91-89f1-30f3e247b2ec' class='xr-var-data-in' type='checkbox'><label for='data-a83a267c-368f-4d91-89f1-30f3e247b2ec' 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;1998-02-01T00:00:00.000000000&#x27;, &#x27;1998-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-04-01T00:00:00.000000000&#x27;, &#x27;1998-05-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-06-01T00:00:00.000000000&#x27;, &#x27;1998-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-08-01T00:00:00.000000000&#x27;, &#x27;1998-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-10-01T00:00:00.000000000&#x27;, &#x27;1998-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-12-01T00:00:00.000000000&#x27;, &#x27;1999-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-02-01T00:00:00.000000000&#x27;, &#x27;1999-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-04-01T00:00:00.000000000&#x27;, &#x27;1999-05-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-06-01T00:00:00.000000000&#x27;, &#x27;1999-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-08-01T00:00:00.000000000&#x27;, &#x27;1999-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-10-01T00:00:00.000000000&#x27;, &#x27;1999-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-12-01T00:00:00.000000000&#x27;, &#x27;2000-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-02-01T00:00:00.000000000&#x27;, &#x27;2000-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-04-01T00:00:00.000000000&#x27;, &#x27;2000-05-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-01T00:00:00.000000000&#x27;, &#x27;2000-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-08-01T00:00:00.000000000&#x27;, &#x27;2000-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-10-01T00:00:00.000000000&#x27;, &#x27;2000-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-12-01T00:00:00.000000000&#x27;, &#x27;2001-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-02-01T00:00:00.000000000&#x27;, &#x27;2001-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-04-01T00:00:00.000000000&#x27;, &#x27;2001-05-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-06-01T00:00:00.000000000&#x27;, &#x27;2001-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-08-01T00:00:00.000000000&#x27;, &#x27;2001-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-10-01T00:00:00.000000000&#x27;, &#x27;2001-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-12-01T00:00:00.000000000&#x27;, &#x27;2002-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-02-01T00:00:00.000000000&#x27;, &#x27;2002-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-04-01T00:00:00.000000000&#x27;, &#x27;2002-05-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-01T00:00:00.000000000&#x27;, &#x27;2002-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-01T00:00:00.000000000&#x27;, &#x27;2002-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-10-01T00:00:00.000000000&#x27;, &#x27;2002-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-12-01T00:00:00.000000000&#x27;, &#x27;2003-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-02-01T00:00:00.000000000&#x27;, &#x27;2003-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-04-01T00:00:00.000000000&#x27;, &#x27;2003-05-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-01T00:00:00.000000000&#x27;, &#x27;2003-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-01T00:00:00.000000000&#x27;, &#x27;2003-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-10-01T00:00:00.000000000&#x27;, &#x27;2003-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-12-01T00:00:00.000000000&#x27;, &#x27;2004-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-02-01T00:00:00.000000000&#x27;, &#x27;2004-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-04-01T00:00:00.000000000&#x27;, &#x27;2004-05-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-01T00:00:00.000000000&#x27;, &#x27;2004-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-01T00:00:00.000000000&#x27;, &#x27;2004-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-10-01T00:00:00.000000000&#x27;, &#x27;2004-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-12-01T00:00:00.000000000&#x27;, &#x27;2005-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-02-01T00:00:00.000000000&#x27;, &#x27;2005-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-04-01T00:00:00.000000000&#x27;, &#x27;2005-05-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-01T00:00:00.000000000&#x27;, &#x27;2005-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-08-01T00:00:00.000000000&#x27;, &#x27;2005-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-10-01T00:00:00.000000000&#x27;, &#x27;2005-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-12-01T00:00:00.000000000&#x27;], 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'>float32</div><div class='xr-var-preview xr-preview'>-49.88 -49.62 ... 49.62 49.88</div><input id='attrs-da7bff2f-679d-413e-89be-702262edc119' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da7bff2f-679d-413e-89be-702262edc119' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3d0cfc0-1b68-4c8f-a96b-e7065df15f07' class='xr-var-data-in' type='checkbox'><label for='data-c3d0cfc0-1b68-4c8f-a96b-e7065df15f07' 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>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-49.875, -49.625, -49.375, ...,  49.375,  49.625,  49.875],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-179.9 -179.6 ... 179.6 179.9</div><input id='attrs-66eb656e-e2aa-4c36-b3d6-7de45947fcc2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-66eb656e-e2aa-4c36-b3d6-7de45947fcc2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bddf2223-bc7e-490e-a428-b6477bf2389c' class='xr-var-data-in' type='checkbox'><label for='data-bddf2223-bc7e-490e-a428-b6477bf2389c' 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>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-179.875, -179.625, -179.375, ...,  179.375,  179.625,  179.875],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1a6b63e5-eb5d-4ae0-a786-a4bd870fbe48' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1a6b63e5-eb5d-4ae0-a786-a4bd870fbe48' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>date</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>19980201 19980301 ... 20051201</div><input id='attrs-ccde7f50-9e18-46f9-befa-c7e493ebce61' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ccde7f50-9e18-46f9-befa-c7e493ebce61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad25c5ea-2188-43d6-b058-91c96f5a0423' class='xr-var-data-in' type='checkbox'><label for='data-ad25c5ea-2188-43d6-b058-91c96f5a0423' 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>units :</span></dt><dd>yyyymmdd</dd><dt><span>long_name :</span></dt><dd>current date</dd></dl></div><div class='xr-var-data'><pre>array([19980201, 19980301, 19980401, 19980501, 19980601, 19980701, 19980801,\n",
       "       19980901, 19981001, 19981101, 19981201, 19990101, 19990201, 19990301,\n",
       "       19990401, 19990501, 19990601, 19990701, 19990801, 19990901, 19991001,\n",
       "       19991101, 19991201, 20000101, 20000201, 20000301, 20000401, 20000501,\n",
       "       20000601, 20000701, 20000801, 20000901, 20001001, 20001101, 20001201,\n",
       "       20010101, 20010201, 20010301, 20010401, 20010501, 20010601, 20010701,\n",
       "       20010801, 20010901, 20011001, 20011101, 20011201, 20020101, 20020201,\n",
       "       20020301, 20020401, 20020501, 20020601, 20020701, 20020801, 20020901,\n",
       "       20021001, 20021101, 20021201, 20030101, 20030201, 20030301, 20030401,\n",
       "       20030501, 20030601, 20030701, 20030801, 20030901, 20031001, 20031101,\n",
       "       20031201, 20040101, 20040201, 20040301, 20040401, 20040501, 20040601,\n",
       "       20040701, 20040801, 20040901, 20041001, 20041101, 20041201, 20050101,\n",
       "       20050201, 20050301, 20050401, 20050501, 20050601, 20050701, 20050801,\n",
       "       20050901, 20051001, 20051101, 20051201], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>datesec</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>1 days 1 days ... 1 days 1 days</div><input id='attrs-3d453e49-ace5-44bb-85b4-80fef503cccf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d453e49-ace5-44bb-85b4-80fef503cccf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1448b3ae-aa7a-40ab-8fd4-8aff1d784450' class='xr-var-data-in' type='checkbox'><label for='data-1448b3ae-aa7a-40ab-8fd4-8aff1d784450' 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>current seconds of current date</dd></dl></div><div class='xr-var-data'><pre>array([86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000], dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>precip</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bbe4fa7b-b505-4685-a3aa-72efebc06ab2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bbe4fa7b-b505-4685-a3aa-72efebc06ab2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd224749-5426-41e6-b2ff-797c3a1a2847' class='xr-var-data-in' type='checkbox'><label for='data-bd224749-5426-41e6-b2ff-797c3a1a2847' 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>avg_period :</span></dt><dd>0000-00-00 01:00:00</dd><dt><span>delta_t :</span></dt><dd>0000-00-00 03:00:00</dd><dt><span>units :</span></dt><dd>mm/h</dd><dt><span>hdf_name :</span></dt><dd>precipitation</dd></dl></div><div class='xr-var-data'><pre>[54720000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2dc8cfcf-f9b0-4230-b708-b2ee386c1d00' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2dc8cfcf-f9b0-4230-b708-b2ee386c1d00' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>creation_date :</span></dt><dd>Thu Nov  5 16:19:03 CET 2009</dd><dt><span>Conventions :</span></dt><dd>None</dd><dt><span>source_html :</span></dt><dd>\n",
       "http://disc.sci.gsfc.nasa.gov/data/datapool/TRMM/01_Data_Products/02_Gridded/06_3-hour_Gpi_Cal_3B_42/index.html\n",
       "</dd><dt><span>title :</span></dt><dd>TRMM: 3B43</dd><dt><span>history :</span></dt><dd>Thu Nov  5 16:26:10 2009: ncrcat 3B43.1998.nc 3B43.1999.nc 3B43.2000.nc 3B43.2001.nc 3B43.2002.nc 3B43.2003.nc 3B43.2004.nc 3B43.2005.nc 3B43.2006.nc 3B43.2007.nc 3B43.2008.nc 3B43.1998_2008.nc\n",
       "Thu Nov  5 16:26:03 2009: ncrcat 3B43.19980101.nc 3B43.19980201.nc 3B43.19980301.nc 3B43.19980401.nc 3B43.19980501.nc 3B43.19980601.nc 3B43.19980701.nc 3B43.19980801.nc 3B43.19980901.nc 3B43.19981001.nc 3B43.19981101.nc 3B43.19981201.nc 3B43.1998.nc</dd><dt><span>nco_openmp_thread_number :</span></dt><dd>1</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 95, lat: 400, lon: 1440)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1998-02-01 1998-03-01 ... 2005-12-01\n",
       "  * lat      (lat) float32 -49.88 -49.62 -49.38 -49.12 ... 49.38 49.62 49.88\n",
       "  * lon      (lon) float32 -179.9 -179.6 -179.4 -179.1 ... 179.4 179.6 179.9\n",
       "Data variables:\n",
       "    date     (time) int32 19980201 19980301 19980401 ... 20051101 20051201\n",
       "    datesec  (time) timedelta64[ns] 1 days 1 days 1 days ... 1 days 1 days\n",
       "    precip   (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    creation_date:             Thu Nov  5 16:19:03 CET 2009\n",
       "    Conventions:               None\n",
       "    source_html:               \\nhttp://disc.sci.gsfc.nasa.gov/data/datapool/...\n",
       "    title:                     TRMM: 3B43\n",
       "    history:                   Thu Nov  5 16:26:10 2009: ncrcat 3B43.1998.nc ...\n",
       "    nco_openmp_thread_number:  1"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#to select the year from 1980 to 2015\n",
    "data = data.sel(time=slice('1998-01-16T12:00:00.000000000','2005-12-16T00:00:00.000000000'))\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "10070b93",
   "metadata": {},
   "outputs": [
    {
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       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 32, lat: 400, lon: 1440)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1998-06-01 1998-07-01 ... 2005-09-01\n",
       "  * lat      (lat) float32 -49.88 -49.62 -49.38 -49.12 ... 49.38 49.62 49.88\n",
       "  * lon      (lon) float32 -179.9 -179.6 -179.4 -179.1 ... 179.4 179.6 179.9\n",
       "Data variables:\n",
       "    date     (time) int32 19980601 19980701 19980801 ... 20050801 20050901\n",
       "    datesec  (time) timedelta64[ns] 1 days 1 days 1 days ... 1 days 1 days\n",
       "    precip   (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    creation_date:             Thu Nov  5 16:19:03 CET 2009\n",
       "    Conventions:               None\n",
       "    source_html:               \\nhttp://disc.sci.gsfc.nasa.gov/data/datapool/...\n",
       "    title:                     TRMM: 3B43\n",
       "    history:                   Thu Nov  5 16:26:10 2009: ncrcat 3B43.1998.nc ...\n",
       "    nco_openmp_thread_number:  1</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-34778db2-5c2c-4550-9394-9368460e4534' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-34778db2-5c2c-4550-9394-9368460e4534' 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>: 32</li><li><span class='xr-has-index'>lat</span>: 400</li><li><span class='xr-has-index'>lon</span>: 1440</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-2e8173c5-db5f-46e8-bd0b-e649c7efb90e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2e8173c5-db5f-46e8-bd0b-e649c7efb90e' 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'>1998-06-01 ... 2005-09-01</div><input id='attrs-2f233557-4f95-4cc4-9499-1bb375906b08' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2f233557-4f95-4cc4-9499-1bb375906b08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35f847c0-f2c2-4bd3-88c3-91d38741949b' class='xr-var-data-in' type='checkbox'><label for='data-35f847c0-f2c2-4bd3-88c3-91d38741949b' 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;1998-06-01T00:00:00.000000000&#x27;, &#x27;1998-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-08-01T00:00:00.000000000&#x27;, &#x27;1998-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-06-01T00:00:00.000000000&#x27;, &#x27;1999-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-08-01T00:00:00.000000000&#x27;, &#x27;1999-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-01T00:00:00.000000000&#x27;, &#x27;2000-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-08-01T00:00:00.000000000&#x27;, &#x27;2000-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-06-01T00:00:00.000000000&#x27;, &#x27;2001-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-08-01T00:00:00.000000000&#x27;, &#x27;2001-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-01T00:00:00.000000000&#x27;, &#x27;2002-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-01T00:00:00.000000000&#x27;, &#x27;2002-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-01T00:00:00.000000000&#x27;, &#x27;2003-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-01T00:00:00.000000000&#x27;, &#x27;2003-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-01T00:00:00.000000000&#x27;, &#x27;2004-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-01T00:00:00.000000000&#x27;, &#x27;2004-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-01T00:00:00.000000000&#x27;, &#x27;2005-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-08-01T00:00:00.000000000&#x27;, &#x27;2005-09-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-49.88 -49.62 ... 49.62 49.88</div><input id='attrs-00765016-15b2-4299-9ce4-5f17929d9ae8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-00765016-15b2-4299-9ce4-5f17929d9ae8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1cdce820-f4cf-41ed-bda8-9f20e3e14086' class='xr-var-data-in' type='checkbox'><label for='data-1cdce820-f4cf-41ed-bda8-9f20e3e14086' 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>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-49.875, -49.625, -49.375, ...,  49.375,  49.625,  49.875],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-179.9 -179.6 ... 179.6 179.9</div><input id='attrs-314d3f60-787f-47b9-bf4a-a43219efa9a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-314d3f60-787f-47b9-bf4a-a43219efa9a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-472c06d9-bf65-4b8e-bd8a-927d3dd480cb' class='xr-var-data-in' type='checkbox'><label for='data-472c06d9-bf65-4b8e-bd8a-927d3dd480cb' 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>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-179.875, -179.625, -179.375, ...,  179.375,  179.625,  179.875],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d0305b0e-814b-48ab-9f74-afac037ee8d2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d0305b0e-814b-48ab-9f74-afac037ee8d2' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>date</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>19980601 19980701 ... 20050901</div><input id='attrs-20f1073f-e9ba-49c1-be42-3b5cdc93e037' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-20f1073f-e9ba-49c1-be42-3b5cdc93e037' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-999563ee-7e49-45ea-b486-9dd7ae3ab9fd' class='xr-var-data-in' type='checkbox'><label for='data-999563ee-7e49-45ea-b486-9dd7ae3ab9fd' 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>units :</span></dt><dd>yyyymmdd</dd><dt><span>long_name :</span></dt><dd>current date</dd></dl></div><div class='xr-var-data'><pre>array([19980601, 19980701, 19980801, 19980901, 19990601, 19990701, 19990801,\n",
       "       19990901, 20000601, 20000701, 20000801, 20000901, 20010601, 20010701,\n",
       "       20010801, 20010901, 20020601, 20020701, 20020801, 20020901, 20030601,\n",
       "       20030701, 20030801, 20030901, 20040601, 20040701, 20040801, 20040901,\n",
       "       20050601, 20050701, 20050801, 20050901], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>datesec</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>1 days 1 days ... 1 days 1 days</div><input id='attrs-cd45a9bc-b81f-45e8-9ec1-e654b5698bda' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd45a9bc-b81f-45e8-9ec1-e654b5698bda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-edfe1bbd-250c-4120-9d6f-a72084122e5b' class='xr-var-data-in' type='checkbox'><label for='data-edfe1bbd-250c-4120-9d6f-a72084122e5b' 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>current seconds of current date</dd></dl></div><div class='xr-var-data'><pre>array([86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000],\n",
       "      dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>precip</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e9950340-5ce3-4583-b944-ff82f460b2a8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e9950340-5ce3-4583-b944-ff82f460b2a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99c2d6b0-6346-4e42-a67b-524a325ad76a' class='xr-var-data-in' type='checkbox'><label for='data-99c2d6b0-6346-4e42-a67b-524a325ad76a' 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>avg_period :</span></dt><dd>0000-00-00 01:00:00</dd><dt><span>delta_t :</span></dt><dd>0000-00-00 03:00:00</dd><dt><span>units :</span></dt><dd>mm/h</dd><dt><span>hdf_name :</span></dt><dd>precipitation</dd></dl></div><div class='xr-var-data'><pre>[18432000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-67a27a9a-f464-4614-8aad-aae2d1b5666c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-67a27a9a-f464-4614-8aad-aae2d1b5666c' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>creation_date :</span></dt><dd>Thu Nov  5 16:19:03 CET 2009</dd><dt><span>Conventions :</span></dt><dd>None</dd><dt><span>source_html :</span></dt><dd>\n",
       "http://disc.sci.gsfc.nasa.gov/data/datapool/TRMM/01_Data_Products/02_Gridded/06_3-hour_Gpi_Cal_3B_42/index.html\n",
       "</dd><dt><span>title :</span></dt><dd>TRMM: 3B43</dd><dt><span>history :</span></dt><dd>Thu Nov  5 16:26:10 2009: ncrcat 3B43.1998.nc 3B43.1999.nc 3B43.2000.nc 3B43.2001.nc 3B43.2002.nc 3B43.2003.nc 3B43.2004.nc 3B43.2005.nc 3B43.2006.nc 3B43.2007.nc 3B43.2008.nc 3B43.1998_2008.nc\n",
       "Thu Nov  5 16:26:03 2009: ncrcat 3B43.19980101.nc 3B43.19980201.nc 3B43.19980301.nc 3B43.19980401.nc 3B43.19980501.nc 3B43.19980601.nc 3B43.19980701.nc 3B43.19980801.nc 3B43.19980901.nc 3B43.19981001.nc 3B43.19981101.nc 3B43.19981201.nc 3B43.1998.nc</dd><dt><span>nco_openmp_thread_number :</span></dt><dd>1</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 32, lat: 400, lon: 1440)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1998-06-01 1998-07-01 ... 2005-09-01\n",
       "  * lat      (lat) float32 -49.88 -49.62 -49.38 -49.12 ... 49.38 49.62 49.88\n",
       "  * lon      (lon) float32 -179.9 -179.6 -179.4 -179.1 ... 179.4 179.6 179.9\n",
       "Data variables:\n",
       "    date     (time) int32 19980601 19980701 19980801 ... 20050801 20050901\n",
       "    datesec  (time) timedelta64[ns] 1 days 1 days 1 days ... 1 days 1 days\n",
       "    precip   (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    creation_date:             Thu Nov  5 16:19:03 CET 2009\n",
       "    Conventions:               None\n",
       "    source_html:               \\nhttp://disc.sci.gsfc.nasa.gov/data/datapool/...\n",
       "    title:                     TRMM: 3B43\n",
       "    history:                   Thu Nov  5 16:26:10 2009: ncrcat 3B43.1998.nc ...\n",
       "    nco_openmp_thread_number:  1"
      ]
     },
     "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": {
      "text/html": [
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       "\n",
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       "\n",
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 32, lat: 40, lon: 32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1998-06-01 1998-07-01 ... 2005-09-01\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "Data variables:\n",
       "    date     (time) int32 19980601 19980701 19980801 ... 20050801 20050901\n",
       "    datesec  (time) timedelta64[ns] 1 days 1 days 1 days ... 1 days 1 days\n",
       "    precip   (time, lat, lon) float32 0.4308 0.3221 0.2765 ... 0.1774 0.1441\n",
       "Attributes:\n",
       "    creation_date:             Thu Nov  5 16:19:03 CET 2009\n",
       "    Conventions:               None\n",
       "    source_html:               \\nhttp://disc.sci.gsfc.nasa.gov/data/datapool/...\n",
       "    title:                     TRMM: 3B43\n",
       "    history:                   Thu Nov  5 16:26:10 2009: ncrcat 3B43.1998.nc ...\n",
       "    nco_openmp_thread_number:  1</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-905a287c-bdf8-4f2b-b36f-0bf7c41327ce' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-905a287c-bdf8-4f2b-b36f-0bf7c41327ce' 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>: 32</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-8b5ae1eb-ed25-4411-9cd6-ae9f8c454d6b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8b5ae1eb-ed25-4411-9cd6-ae9f8c454d6b' 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'>1998-06-01 ... 2005-09-01</div><input id='attrs-aa7a3544-642b-486d-961c-42efbc2500cc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-aa7a3544-642b-486d-961c-42efbc2500cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51ce498d-82d3-487e-ab80-a15dc88b4db0' class='xr-var-data-in' type='checkbox'><label for='data-51ce498d-82d3-487e-ab80-a15dc88b4db0' 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;1998-06-01T00:00:00.000000000&#x27;, &#x27;1998-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-08-01T00:00:00.000000000&#x27;, &#x27;1998-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-06-01T00:00:00.000000000&#x27;, &#x27;1999-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-08-01T00:00:00.000000000&#x27;, &#x27;1999-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-01T00:00:00.000000000&#x27;, &#x27;2000-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-08-01T00:00:00.000000000&#x27;, &#x27;2000-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-06-01T00:00:00.000000000&#x27;, &#x27;2001-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-08-01T00:00:00.000000000&#x27;, &#x27;2001-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-01T00:00:00.000000000&#x27;, &#x27;2002-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-01T00:00:00.000000000&#x27;, &#x27;2002-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-01T00:00:00.000000000&#x27;, &#x27;2003-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-01T00:00:00.000000000&#x27;, &#x27;2003-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-01T00:00:00.000000000&#x27;, &#x27;2004-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-01T00:00:00.000000000&#x27;, &#x27;2004-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-01T00:00:00.000000000&#x27;, &#x27;2005-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-08-01T00:00:00.000000000&#x27;, &#x27;2005-09-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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-cfe25a43-3d9d-4a65-acc9-5819af5ce6be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cfe25a43-3d9d-4a65-acc9-5819af5ce6be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b989676c-76c0-4eab-928b-003a40f6288f' class='xr-var-data-in' type='checkbox'><label for='data-b989676c-76c0-4eab-928b-003a40f6288f' 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>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-6e8ef0e4-5cd1-4813-912d-11867fef7577' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e8ef0e4-5cd1-4813-912d-11867fef7577' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3dd1a2a3-feff-4bb6-8d84-9793be0ea20c' class='xr-var-data-in' type='checkbox'><label for='data-3dd1a2a3-feff-4bb6-8d84-9793be0ea20c' 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>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5e13f3e2-f7bc-48c1-a464-1deffc57d9a9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5e13f3e2-f7bc-48c1-a464-1deffc57d9a9' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>date</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>19980601 19980701 ... 20050901</div><input id='attrs-8aba83c6-346a-4b10-9c62-eed87609bf41' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8aba83c6-346a-4b10-9c62-eed87609bf41' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6a77735-5ef4-495e-bd4d-d982d28c2c21' class='xr-var-data-in' type='checkbox'><label for='data-e6a77735-5ef4-495e-bd4d-d982d28c2c21' 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>units :</span></dt><dd>yyyymmdd</dd><dt><span>long_name :</span></dt><dd>current date</dd></dl></div><div class='xr-var-data'><pre>array([19980601, 19980701, 19980801, 19980901, 19990601, 19990701, 19990801,\n",
       "       19990901, 20000601, 20000701, 20000801, 20000901, 20010601, 20010701,\n",
       "       20010801, 20010901, 20020601, 20020701, 20020801, 20020901, 20030601,\n",
       "       20030701, 20030801, 20030901, 20040601, 20040701, 20040801, 20040901,\n",
       "       20050601, 20050701, 20050801, 20050901], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>datesec</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>1 days 1 days ... 1 days 1 days</div><input id='attrs-cb7dd111-f2a3-45b5-b94d-c90ebb1c78de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cb7dd111-f2a3-45b5-b94d-c90ebb1c78de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f469806-04b5-4a4d-99d6-3692bfcf7da1' class='xr-var-data-in' type='checkbox'><label for='data-0f469806-04b5-4a4d-99d6-3692bfcf7da1' 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>current seconds of current date</dd></dl></div><div class='xr-var-data'><pre>array([86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000],\n",
       "      dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>precip</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-47258fb6-ecde-4e81-b1e6-082ecfc1e92e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-47258fb6-ecde-4e81-b1e6-082ecfc1e92e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c61eabbf-8acf-46a7-91c0-400edaa3c0dc' class='xr-var-data-in' type='checkbox'><label for='data-c61eabbf-8acf-46a7-91c0-400edaa3c0dc' 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>avg_period :</span></dt><dd>0000-00-00 01:00:00</dd><dt><span>delta_t :</span></dt><dd>0000-00-00 03:00:00</dd><dt><span>units :</span></dt><dd>mm/h</dd><dt><span>hdf_name :</span></dt><dd>precipitation</dd></dl></div><div class='xr-var-data'><pre>array([[[0.430781, 0.322124, ..., 0.690971, 0.511044],\n",
       "        [0.346458, 0.285885, ..., 0.714057, 0.530204],\n",
       "        ...,\n",
       "        [0.210538, 0.242568, ..., 0.347411, 0.416681],\n",
       "        [0.231942, 0.248441, ..., 0.34638 , 0.382962]],\n",
       "\n",
       "       [[0.370449, 0.34102 , ..., 0.74982 , 1.003079],\n",
       "        [0.40649 , 0.328449, ..., 0.751424, 0.942093],\n",
       "        ...,\n",
       "        [0.206243, 0.196804, ..., 0.361962, 0.420819],\n",
       "        [0.202383, 0.187006, ..., 0.371911, 0.389453]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[0.248589, 0.281734, ..., 0.62056 , 0.201447],\n",
       "        [0.287298, 0.351694, ..., 0.594927, 0.229043],\n",
       "        ...,\n",
       "        [0.499972, 0.483239, ..., 0.337055, 0.352355],\n",
       "        [0.421131, 0.390675, ..., 0.31433 , 0.312789]],\n",
       "\n",
       "       [[0.905021, 0.772218, ..., 0.321426, 0.106503],\n",
       "        [0.790125, 0.811464, ..., 0.312985, 0.139072],\n",
       "        ...,\n",
       "        [0.144173, 0.128717, ..., 0.154787, 0.14331 ],\n",
       "        [0.084575, 0.081424, ..., 0.177377, 0.144111]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9e5a5b68-6135-4864-a041-61291a6906f6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9e5a5b68-6135-4864-a041-61291a6906f6' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>creation_date :</span></dt><dd>Thu Nov  5 16:19:03 CET 2009</dd><dt><span>Conventions :</span></dt><dd>None</dd><dt><span>source_html :</span></dt><dd>\n",
       "http://disc.sci.gsfc.nasa.gov/data/datapool/TRMM/01_Data_Products/02_Gridded/06_3-hour_Gpi_Cal_3B_42/index.html\n",
       "</dd><dt><span>title :</span></dt><dd>TRMM: 3B43</dd><dt><span>history :</span></dt><dd>Thu Nov  5 16:26:10 2009: ncrcat 3B43.1998.nc 3B43.1999.nc 3B43.2000.nc 3B43.2001.nc 3B43.2002.nc 3B43.2003.nc 3B43.2004.nc 3B43.2005.nc 3B43.2006.nc 3B43.2007.nc 3B43.2008.nc 3B43.1998_2008.nc\n",
       "Thu Nov  5 16:26:03 2009: ncrcat 3B43.19980101.nc 3B43.19980201.nc 3B43.19980301.nc 3B43.19980401.nc 3B43.19980501.nc 3B43.19980601.nc 3B43.19980701.nc 3B43.19980801.nc 3B43.19980901.nc 3B43.19981001.nc 3B43.19981101.nc 3B43.19981201.nc 3B43.1998.nc</dd><dt><span>nco_openmp_thread_number :</span></dt><dd>1</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 32, lat: 40, lon: 32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1998-06-01 1998-07-01 ... 2005-09-01\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "Data variables:\n",
       "    date     (time) int32 19980601 19980701 19980801 ... 20050801 20050901\n",
       "    datesec  (time) timedelta64[ns] 1 days 1 days 1 days ... 1 days 1 days\n",
       "    precip   (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    creation_date:             Thu Nov  5 16:19:03 CET 2009\n",
       "    Conventions:               None\n",
       "    source_html:               \\nhttp://disc.sci.gsfc.nasa.gov/data/datapool/...\n",
       "    title:                     TRMM: 3B43\n",
       "    history:                   Thu Nov  5 16:26:10 2009: ncrcat 3B43.1998.nc ...\n",
       "    nco_openmp_thread_number:  1"
      ]
     },
     "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-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: 32, lat: 40, lon: 32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1998-06-01 1998-07-01 ... 2005-09-01\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Data variables:\n",
       "    date     (time) int32 19980601 19980701 19980801 ... 20050801 20050901\n",
       "    datesec  (time) timedelta64[ns] 1 days 1 days 1 days ... 1 days 1 days\n",
       "    precip   (time, lat, lon) float64 0.4308 0.3221 0.2765 ... 0.1774 0.1441\n",
       "Attributes:\n",
       "    creation_date:             Thu Nov  5 16:19:03 CET 2009\n",
       "    Conventions:               None\n",
       "    source_html:               \\nhttp://disc.sci.gsfc.nasa.gov/data/datapool/...\n",
       "    title:                     TRMM: 3B43\n",
       "    history:                   Thu Nov  5 16:26:10 2009: ncrcat 3B43.1998.nc ...\n",
       "    nco_openmp_thread_number:  1</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-a243e259-eeec-4437-ad6b-f96836a769a2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a243e259-eeec-4437-ad6b-f96836a769a2' 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>: 32</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-293c6707-5b12-4382-b9b2-d667c1b5c742' class='xr-section-summary-in' type='checkbox'  checked><label for='section-293c6707-5b12-4382-b9b2-d667c1b5c742' 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'>1998-06-01 ... 2005-09-01</div><input id='attrs-88107b24-6b31-44cc-ad9c-e606d576f2aa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-88107b24-6b31-44cc-ad9c-e606d576f2aa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed31e5b1-c183-4c21-84d9-c0feecd4fdc8' class='xr-var-data-in' type='checkbox'><label for='data-ed31e5b1-c183-4c21-84d9-c0feecd4fdc8' 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;1998-06-01T00:00:00.000000000&#x27;, &#x27;1998-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-08-01T00:00:00.000000000&#x27;, &#x27;1998-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-06-01T00:00:00.000000000&#x27;, &#x27;1999-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-08-01T00:00:00.000000000&#x27;, &#x27;1999-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-01T00:00:00.000000000&#x27;, &#x27;2000-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-08-01T00:00:00.000000000&#x27;, &#x27;2000-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-06-01T00:00:00.000000000&#x27;, &#x27;2001-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-08-01T00:00:00.000000000&#x27;, &#x27;2001-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-01T00:00:00.000000000&#x27;, &#x27;2002-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-01T00:00:00.000000000&#x27;, &#x27;2002-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-01T00:00:00.000000000&#x27;, &#x27;2003-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-01T00:00:00.000000000&#x27;, &#x27;2003-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-01T00:00:00.000000000&#x27;, &#x27;2004-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-01T00:00:00.000000000&#x27;, &#x27;2004-09-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-01T00:00:00.000000000&#x27;, &#x27;2005-07-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-08-01T00:00:00.000000000&#x27;, &#x27;2005-09-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-8218ea97-2523-4c10-8108-135dd7af3d90' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8218ea97-2523-4c10-8108-135dd7af3d90' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81cbf3d5-66d4-4b1d-aa37-b3821c34281a' class='xr-var-data-in' type='checkbox'><label for='data-81cbf3d5-66d4-4b1d-aa37-b3821c34281a' 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>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-a64b9cf2-79f7-4aa6-9e90-978b7dbe1b65' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a64b9cf2-79f7-4aa6-9e90-978b7dbe1b65' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f99344e2-7427-4d37-bc35-3459ecc0aacd' class='xr-var-data-in' type='checkbox'><label for='data-f99344e2-7427-4d37-bc35-3459ecc0aacd' 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>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5519298d-e9fb-4fc3-9fb9-36354c87a99d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5519298d-e9fb-4fc3-9fb9-36354c87a99d' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>date</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>19980601 19980701 ... 20050901</div><input id='attrs-621c9f85-c1ee-4e9d-bc4a-41ac98a16cc2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-621c9f85-c1ee-4e9d-bc4a-41ac98a16cc2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fad136db-2a66-4a10-8b3b-d631060aa499' class='xr-var-data-in' type='checkbox'><label for='data-fad136db-2a66-4a10-8b3b-d631060aa499' 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>units :</span></dt><dd>yyyymmdd</dd><dt><span>long_name :</span></dt><dd>current date</dd></dl></div><div class='xr-var-data'><pre>array([19980601, 19980701, 19980801, 19980901, 19990601, 19990701, 19990801,\n",
       "       19990901, 20000601, 20000701, 20000801, 20000901, 20010601, 20010701,\n",
       "       20010801, 20010901, 20020601, 20020701, 20020801, 20020901, 20030601,\n",
       "       20030701, 20030801, 20030901, 20040601, 20040701, 20040801, 20040901,\n",
       "       20050601, 20050701, 20050801, 20050901], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>datesec</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>1 days 1 days ... 1 days 1 days</div><input id='attrs-cd1235ae-af06-4c17-89e3-9829cb537cc8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd1235ae-af06-4c17-89e3-9829cb537cc8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0e070c3-e5c0-4db4-b3fb-4c9ba3e121e3' class='xr-var-data-in' type='checkbox'><label for='data-d0e070c3-e5c0-4db4-b3fb-4c9ba3e121e3' 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>current seconds of current date</dd></dl></div><div class='xr-var-data'><pre>array([86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000,\n",
       "       86400000000000, 86400000000000, 86400000000000, 86400000000000],\n",
       "      dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>precip</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.4308 0.3221 ... 0.1774 0.1441</div><input id='attrs-9dcdf222-5744-4186-8890-a6f53c3221a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9dcdf222-5744-4186-8890-a6f53c3221a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06ec83a6-a4f9-4468-970c-6e1c7b677946' class='xr-var-data-in' type='checkbox'><label for='data-06ec83a6-a4f9-4468-970c-6e1c7b677946' 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>avg_period :</span></dt><dd>0000-00-00 01:00:00</dd><dt><span>delta_t :</span></dt><dd>0000-00-00 03:00:00</dd><dt><span>units :</span></dt><dd>mm/h</dd><dt><span>hdf_name :</span></dt><dd>precipitation</dd></dl></div><div class='xr-var-data'><pre>array([[[0.43078125, 0.32212433, 0.27652851, ..., 0.71414649,\n",
       "         0.69097066, 0.51104361],\n",
       "        [0.34645832, 0.28588545, 0.27891186, ..., 0.67252439,\n",
       "         0.71405703, 0.53020412],\n",
       "        [0.30466321, 0.28692707, 0.34890625, ..., 0.52755976,\n",
       "         0.44530717, 0.50524467],\n",
       "        ...,\n",
       "        [0.25164425, 0.22906637, 0.22276108, ..., 0.33158243,\n",
       "         0.39273235, 0.46620294],\n",
       "        [0.21053816, 0.24256794, 0.22192635, ..., 0.33510813,\n",
       "         0.34741056, 0.41668078],\n",
       "        [0.23194218, 0.24844146, 0.20519544, ..., 0.33965585,\n",
       "         0.34638026, 0.3829622 ]],\n",
       "\n",
       "       [[0.37044898, 0.34102049, 0.26514283, ..., 0.80254507,\n",
       "         0.74981993, 1.0030787 ],\n",
       "        [0.40648982, 0.32844895, 0.33179593, ..., 0.71308237,\n",
       "         0.75142395, 0.94209349],\n",
       "        [0.37599996, 0.33314285, 0.31755105, ..., 0.62495816,\n",
       "         0.7886126 , 0.82755727],\n",
       "...\n",
       "        [0.47652695, 0.46822199, 0.42713207, ..., 0.37804446,\n",
       "         0.38281152, 0.45988405],\n",
       "        [0.49997219, 0.48323852, 0.45986396, ..., 0.34103122,\n",
       "         0.33705536, 0.35235509],\n",
       "        [0.42113104, 0.39067474, 0.29115453, ..., 0.32737136,\n",
       "         0.31432962, 0.31278938]],\n",
       "\n",
       "       [[0.90502101, 0.77221751, 0.62841004, ..., 0.30199876,\n",
       "         0.32142636, 0.10650334],\n",
       "        [0.79012549, 0.81146431, 0.71573222, ..., 0.3164157 ,\n",
       "         0.31298488, 0.1390717 ],\n",
       "        [0.78330541, 0.81744772, 0.69393301, ..., 0.26952028,\n",
       "         0.08852844, 0.13059638],\n",
       "        ...,\n",
       "        [0.13947497, 0.12282646, 0.10006622, ..., 0.19674815,\n",
       "         0.17514312, 0.16353646],\n",
       "        [0.14417261, 0.12871726, 0.0876339 , ..., 0.17797181,\n",
       "         0.15478659, 0.14331004],\n",
       "        [0.08457547, 0.08142399, 0.06058535, ..., 0.17881694,\n",
       "         0.1773766 , 0.14411069]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f92ce196-f926-44c0-b72b-dc8814e17b08' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f92ce196-f926-44c0-b72b-dc8814e17b08' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>creation_date :</span></dt><dd>Thu Nov  5 16:19:03 CET 2009</dd><dt><span>Conventions :</span></dt><dd>None</dd><dt><span>source_html :</span></dt><dd>\n",
       "http://disc.sci.gsfc.nasa.gov/data/datapool/TRMM/01_Data_Products/02_Gridded/06_3-hour_Gpi_Cal_3B_42/index.html\n",
       "</dd><dt><span>title :</span></dt><dd>TRMM: 3B43</dd><dt><span>history :</span></dt><dd>Thu Nov  5 16:26:10 2009: ncrcat 3B43.1998.nc 3B43.1999.nc 3B43.2000.nc 3B43.2001.nc 3B43.2002.nc 3B43.2003.nc 3B43.2004.nc 3B43.2005.nc 3B43.2006.nc 3B43.2007.nc 3B43.2008.nc 3B43.1998_2008.nc\n",
       "Thu Nov  5 16:26:03 2009: ncrcat 3B43.19980101.nc 3B43.19980201.nc 3B43.19980301.nc 3B43.19980401.nc 3B43.19980501.nc 3B43.19980601.nc 3B43.19980701.nc 3B43.19980801.nc 3B43.19980901.nc 3B43.19981001.nc 3B43.19981101.nc 3B43.19981201.nc 3B43.1998.nc</dd><dt><span>nco_openmp_thread_number :</span></dt><dd>1</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 32, lat: 40, lon: 32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1998-06-01 1998-07-01 ... 2005-09-01\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Data variables:\n",
       "    date     (time) int32 19980601 19980701 19980801 ... 20050801 20050901\n",
       "    datesec  (time) timedelta64[ns] 1 days 1 days 1 days ... 1 days 1 days\n",
       "    precip   (time, lat, lon) float64 0.4308 0.3221 0.2765 ... 0.1774 0.1441\n",
       "Attributes:\n",
       "    creation_date:             Thu Nov  5 16:19:03 CET 2009\n",
       "    Conventions:               None\n",
       "    source_html:               \\nhttp://disc.sci.gsfc.nasa.gov/data/datapool/...\n",
       "    title:                     TRMM: 3B43\n",
       "    history:                   Thu Nov  5 16:26:10 2009: ncrcat 3B43.1998.nc ...\n",
       "    nco_openmp_thread_number:  1"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#interpolating to low resolution \n",
    "new_lon=np.arange(86.125,94,0.25)\n",
    "new_lat=np.arange(18.125,28,.25)\n",
    "jjas_data = jjas_data.interp(lon=new_lon,lat=new_lat)\n",
    "jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "82d6b5d0",
   "metadata": {},
   "outputs": [
    {
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       "\n",
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       "}\n",
       "\n",
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       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;precip&#x27; (lat: 40, lon: 32)&gt;\n",
       "array([[0.36424099, 0.37230343, 0.37556934, ..., 0.92753743, 0.87774413,\n",
       "        0.7401172 ],\n",
       "       [0.34889041, 0.35808088, 0.37171274, ..., 0.83811737, 0.85462887,\n",
       "        0.76615154],\n",
       "       [0.35725656, 0.3810575 , 0.38026427, ..., 0.77830642, 0.72501694,\n",
       "        0.73013412],\n",
       "       ...,\n",
       "       [0.30676399, 0.28645704, 0.2692595 , ..., 0.31475378, 0.32605261,\n",
       "        0.37545073],\n",
       "       [0.31019293, 0.28211734, 0.25408416, ..., 0.29370044, 0.29596804,\n",
       "        0.31669719],\n",
       "       [0.27611407, 0.25033029, 0.21442228, ..., 0.30539278, 0.32262473,\n",
       "        0.30854961]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'precip'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 40</li><li><span class='xr-has-index'>lon</span>: 32</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7757e4e5-8d8c-4fdb-914d-49566d339199' class='xr-array-in' type='checkbox' checked><label for='section-7757e4e5-8d8c-4fdb-914d-49566d339199' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.3642 0.3723 0.3756 0.392 0.4062 ... 0.2879 0.3054 0.3226 0.3085</span></div><div class='xr-array-data'><pre>array([[0.36424099, 0.37230343, 0.37556934, ..., 0.92753743, 0.87774413,\n",
       "        0.7401172 ],\n",
       "       [0.34889041, 0.35808088, 0.37171274, ..., 0.83811737, 0.85462887,\n",
       "        0.76615154],\n",
       "       [0.35725656, 0.3810575 , 0.38026427, ..., 0.77830642, 0.72501694,\n",
       "        0.73013412],\n",
       "       ...,\n",
       "       [0.30676399, 0.28645704, 0.2692595 , ..., 0.31475378, 0.32605261,\n",
       "        0.37545073],\n",
       "       [0.31019293, 0.28211734, 0.25408416, ..., 0.29370044, 0.29596804,\n",
       "        0.31669719],\n",
       "       [0.27611407, 0.25033029, 0.21442228, ..., 0.30539278, 0.32262473,\n",
       "        0.30854961]])</pre></div></div></li><li class='xr-section-item'><input id='section-d0fc3975-d1e5-40b5-9498-3f784d722f29' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d0fc3975-d1e5-40b5-9498-3f784d722f29' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-9f5b8a69-ec43-4daa-84cd-568a962bd623' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f5b8a69-ec43-4daa-84cd-568a962bd623' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c111198-da81-4b84-8284-499312fed661' class='xr-var-data-in' type='checkbox'><label for='data-7c111198-da81-4b84-8284-499312fed661' 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>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-6c0f92df-c48f-466c-b3e5-693dcd631a35' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c0f92df-c48f-466c-b3e5-693dcd631a35' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ecfbdda-f58d-48ae-a004-146c1f3a256d' class='xr-var-data-in' type='checkbox'><label for='data-9ecfbdda-f58d-48ae-a004-146c1f3a256d' 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>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-604f1e49-6075-4538-9a53-7c3da894bea6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-604f1e49-6075-4538-9a53-7c3da894bea6' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'precip' (lat: 40, lon: 32)>\n",
       "array([[0.36424099, 0.37230343, 0.37556934, ..., 0.92753743, 0.87774413,\n",
       "        0.7401172 ],\n",
       "       [0.34889041, 0.35808088, 0.37171274, ..., 0.83811737, 0.85462887,\n",
       "        0.76615154],\n",
       "       [0.35725656, 0.3810575 , 0.38026427, ..., 0.77830642, 0.72501694,\n",
       "        0.73013412],\n",
       "       ...,\n",
       "       [0.30676399, 0.28645704, 0.2692595 , ..., 0.31475378, 0.32605261,\n",
       "        0.37545073],\n",
       "       [0.31019293, 0.28211734, 0.25408416, ..., 0.29370044, 0.29596804,\n",
       "        0.31669719],\n",
       "       [0.27611407, 0.25033029, 0.21442228, ..., 0.30539278, 0.32262473,\n",
       "        0.30854961]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#getting the mean for JJAS data\n",
    "jjas_mean = jjas_data.precip.mean('time')\n",
    " \n",
    "jjas_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6d00cba7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#changing unit from mm/month to mm/day\n",
    "pr_mm = jjas_mean*24\n",
    "pr_mm\n",
    "\n",
    "\n",
    "trmm = 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",
       "  * 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 21 14:17:08 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-0a5b519e-569f-47f7-a4a4-a91ae402fb22' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0a5b519e-569f-47f7-a4a4-a91ae402fb22' 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-8c124159-fc42-4799-9685-9f87fe2a540e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8c124159-fc42-4799-9685-9f87fe2a540e' 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-b31da480-c20f-4c85-8d4b-8ee875d26bbe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b31da480-c20f-4c85-8d4b-8ee875d26bbe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57294e5a-9fdf-4efc-9db8-95b951026c52' class='xr-var-data-in' type='checkbox'><label for='data-57294e5a-9fdf-4efc-9db8-95b951026c52' 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-c31f2b1d-e7a8-4421-9fdc-760b78ab556a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c31f2b1d-e7a8-4421-9fdc-760b78ab556a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed40392b-510b-4001-9120-0fbabfee12e4' class='xr-var-data-in' type='checkbox'><label for='data-ed40392b-510b-4001-9120-0fbabfee12e4' 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-31e36e64-1849-4334-9f6f-fe530a979ab5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31e36e64-1849-4334-9f6f-fe530a979ab5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c67d3bf-4749-4980-b6af-8dd5f3401610' class='xr-var-data-in' type='checkbox'><label for='data-1c67d3bf-4749-4980-b6af-8dd5f3401610' 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-1cc21696-d9ad-4245-bd84-34af9cce34d5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1cc21696-d9ad-4245-bd84-34af9cce34d5' 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-a89896d7-87bd-4414-a5b4-1d62fcdb8408' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a89896d7-87bd-4414-a5b4-1d62fcdb8408' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6b5520d-ada6-4123-87d2-93f1f4206988' class='xr-var-data-in' type='checkbox'><label for='data-f6b5520d-ada6-4123-87d2-93f1f4206988' 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-26d356cc-8f00-4761-b038-925b5f88515b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26d356cc-8f00-4761-b038-925b5f88515b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6eb5f15-7d65-4b30-bbb1-63859a25d9e5' class='xr-var-data-in' type='checkbox'><label for='data-b6eb5f15-7d65-4b30-bbb1-63859a25d9e5' 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-070bb309-8303-4905-9dd3-22a7d3ae2854' class='xr-section-summary-in' type='checkbox'  ><label for='section-070bb309-8303-4905-9dd3-22a7d3ae2854' 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 21 14:17:08 2022: cdo remapnn,grid.des regcmensble.nc regcmensble_remap.nc\n",
       "Thu Jul 21 14:08:02 2022: cdo divc,3 final.nc regcmensble.nc\n",
       "Thu Jul 21 14:06:30 2022: cdo -add miroc5_pr_197001-200512.nc -add mpiesm_pr_197001-200512.nc noresm_pr_197001-200512.nc final.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) 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 21 14:17:08 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/ensemble-average/regcmensble_remap.nc')\n",
    "\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "54b53ce7",
   "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_9998/1463838701.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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       "</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) 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 21 14:17:08 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-6d551b4e-7d8a-4cb9-966f-8ff29b11e455' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6d551b4e-7d8a-4cb9-966f-8ff29b11e455' 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-5638bceb-6c67-4336-baf6-f31cdc555cac' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5638bceb-6c67-4336-baf6-f31cdc555cac' 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-e7334d27-95fe-4078-953e-d36a5e3cf189' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e7334d27-95fe-4078-953e-d36a5e3cf189' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c4fcbef-aa5a-47e0-9baa-87a8535770bc' class='xr-var-data-in' type='checkbox'><label for='data-5c4fcbef-aa5a-47e0-9baa-87a8535770bc' 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-992e7dd2-5226-45f4-be74-a05a32e0327e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-992e7dd2-5226-45f4-be74-a05a32e0327e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c98394c-7efb-4505-8806-b58263a79433' class='xr-var-data-in' type='checkbox'><label for='data-7c98394c-7efb-4505-8806-b58263a79433' 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-5681a5fa-04fa-4866-b10c-855159cb80c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5681a5fa-04fa-4866-b10c-855159cb80c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4fceb58-cfd1-4df2-8bbc-7520a6c9019d' class='xr-var-data-in' type='checkbox'><label for='data-b4fceb58-cfd1-4df2-8bbc-7520a6c9019d' 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-6ac48cff-f229-4b31-899f-ab44109484af' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6ac48cff-f229-4b31-899f-ab44109484af' 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-00d775ba-3c9c-4686-9be2-86b4a4b09348' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-00d775ba-3c9c-4686-9be2-86b4a4b09348' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d6d0703-d686-44ad-b251-079e678f17ad' class='xr-var-data-in' type='checkbox'><label for='data-1d6d0703-d686-44ad-b251-079e678f17ad' 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-540a98db-fa32-4b02-b58c-22d487e19c31' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-540a98db-fa32-4b02-b58c-22d487e19c31' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e9d3f0d-0b3e-41f6-ba7d-24335b1d93e1' class='xr-var-data-in' type='checkbox'><label for='data-3e9d3f0d-0b3e-41f6-ba7d-24335b1d93e1' 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-d959cbef-32b9-4dac-a7f4-984335095fe2' class='xr-section-summary-in' type='checkbox'  ><label for='section-d959cbef-32b9-4dac-a7f4-984335095fe2' 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 21 14:17:08 2022: cdo remapnn,grid.des regcmensble.nc regcmensble_remap.nc\n",
       "Thu Jul 21 14:08:02 2022: cdo divc,3 final.nc regcmensble.nc\n",
       "Thu Jul 21 14:06:30 2022: cdo -add miroc5_pr_197001-200512.nc -add mpiesm_pr_197001-200512.nc noresm_pr_197001-200512.nc final.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 21 14:17:08 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": [
    {
     "data": {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 95, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1998-01-16T12:00:00 ... 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 1998-01-01 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 21 14:17:08 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-a73e53a4-7f30-4c62-8290-324a4cbf73cb' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a73e53a4-7f30-4c62-8290-324a4cbf73cb' 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>: 95</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-5db188fa-93b9-46af-a212-30a6b999182e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5db188fa-93b9-46af-a212-30a6b999182e' 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'>1998-01-16T12:00:00 ... 2005-11-16</div><input id='attrs-1307bae6-810e-440e-8869-9c41ef4f65f3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1307bae6-810e-440e-8869-9c41ef4f65f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3f38250-3956-4f7b-a026-ee18d5f92894' class='xr-var-data-in' type='checkbox'><label for='data-e3f38250-3956-4f7b-a026-ee18d5f92894' 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;1998-01-16T12:00:00.000000000&#x27;, &#x27;1998-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-03-16T12:00:00.000000000&#x27;, &#x27;1998-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-05-16T12:00:00.000000000&#x27;, &#x27;1998-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-07-16T12:00:00.000000000&#x27;, &#x27;1998-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1998-09-16T00:00:00.000000000&#x27;, &#x27;1998-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1998-11-16T00:00:00.000000000&#x27;, &#x27;1998-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1999-01-16T12:00:00.000000000&#x27;, &#x27;1999-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-03-16T12:00:00.000000000&#x27;, &#x27;1999-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-05-16T12:00:00.000000000&#x27;, &#x27;1999-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-07-16T12:00:00.000000000&#x27;, &#x27;1999-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1999-09-16T00:00:00.000000000&#x27;, &#x27;1999-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1999-11-16T00:00:00.000000000&#x27;, &#x27;1999-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2000-01-16T12:00:00.000000000&#x27;, &#x27;2000-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-03-16T12:00:00.000000000&#x27;, &#x27;2000-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-05-16T12:00:00.000000000&#x27;, &#x27;2000-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-07-16T12:00:00.000000000&#x27;, &#x27;2000-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2000-09-16T00:00:00.000000000&#x27;, &#x27;2000-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2000-11-16T00:00:00.000000000&#x27;, &#x27;2000-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2001-01-16T12:00:00.000000000&#x27;, &#x27;2001-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-03-16T12:00:00.000000000&#x27;, &#x27;2001-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-05-16T12:00:00.000000000&#x27;, &#x27;2001-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-07-16T12:00:00.000000000&#x27;, &#x27;2001-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2001-09-16T00:00:00.000000000&#x27;, &#x27;2001-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2001-11-16T00:00:00.000000000&#x27;, &#x27;2001-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2002-01-16T12:00:00.000000000&#x27;, &#x27;2002-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-03-16T12:00:00.000000000&#x27;, &#x27;2002-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-05-16T12:00:00.000000000&#x27;, &#x27;2002-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-07-16T12:00:00.000000000&#x27;, &#x27;2002-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2002-09-16T00:00:00.000000000&#x27;, &#x27;2002-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2002-11-16T00:00:00.000000000&#x27;, &#x27;2002-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2003-01-16T12:00:00.000000000&#x27;, &#x27;2003-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-03-16T12:00:00.000000000&#x27;, &#x27;2003-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-05-16T12:00:00.000000000&#x27;, &#x27;2003-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-07-16T12:00:00.000000000&#x27;, &#x27;2003-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2003-09-16T00:00:00.000000000&#x27;, &#x27;2003-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2003-11-16T00:00:00.000000000&#x27;, &#x27;2003-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2004-01-16T12:00:00.000000000&#x27;, &#x27;2004-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-03-16T12:00:00.000000000&#x27;, &#x27;2004-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-05-16T12:00:00.000000000&#x27;, &#x27;2004-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-07-16T12:00:00.000000000&#x27;, &#x27;2004-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2004-09-16T00:00:00.000000000&#x27;, &#x27;2004-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2004-11-16T00:00:00.000000000&#x27;, &#x27;2004-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2005-01-16T12:00:00.000000000&#x27;, &#x27;2005-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-03-16T12:00:00.000000000&#x27;, &#x27;2005-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-05-16T12:00:00.000000000&#x27;, &#x27;2005-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-07-16T12:00:00.000000000&#x27;, &#x27;2005-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2005-09-16T00:00:00.000000000&#x27;, &#x27;2005-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2005-11-16T00:00:00.000000000&#x27;], 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-75e8c694-70a0-42fe-be16-8b7e157a73ec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-75e8c694-70a0-42fe-be16-8b7e157a73ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-696e8e49-27b9-404d-8102-ce1a872725e2' class='xr-var-data-in' type='checkbox'><label for='data-696e8e49-27b9-404d-8102-ce1a872725e2' 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-dce5f889-61ff-4340-9475-8c8418ab445b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dce5f889-61ff-4340-9475-8c8418ab445b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a962614b-e643-45b8-84e2-4628950b16f3' class='xr-var-data-in' type='checkbox'><label for='data-a962614b-e643-45b8-84e2-4628950b16f3' 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-7d14f37e-9f37-4d51-97a6-a11e54c2fb57' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7d14f37e-9f37-4d51-97a6-a11e54c2fb57' 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'>1998-01-01 00:00:00 ... 2005-12-...</div><input id='attrs-07399c87-d0a2-4647-a814-ec882edb313f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-07399c87-d0a2-4647-a814-ec882edb313f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-532bb107-f5a0-46ac-988f-1384bacd6861' class='xr-var-data-in' type='checkbox'><label for='data-532bb107-f5a0-46ac-988f-1384bacd6861' 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(1998, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 4, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 5, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 5, 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, 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(1998, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 12, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 12, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 1, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 4, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 5, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 5, 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, 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(1999, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 12, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 12, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 1, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 4, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 5, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 5, 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, 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(2000, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 12, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 12, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 1, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 4, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 5, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 5, 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, 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(2001, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 12, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 12, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 1, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 4, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 5, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 5, 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, 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(2002, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 12, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 12, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 1, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 4, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 5, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 5, 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, 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(2003, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 12, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 12, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 1, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 4, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 5, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 5, 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, 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(2004, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 12, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 12, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 1, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 4, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 5, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 5, 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, 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",
       "       [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-5cc53bd0-1d45-4a3c-9d9f-930fa5544d88' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5cc53bd0-1d45-4a3c-9d9f-930fa5544d88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ad2cf1e-f1e1-4650-8bb0-b971e50005e7' class='xr-var-data-in' type='checkbox'><label for='data-9ad2cf1e-f1e1-4650-8bb0-b971e50005e7' 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>[121600 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-27205139-76b6-477a-883b-0040a63149b5' class='xr-section-summary-in' type='checkbox'  ><label for='section-27205139-76b6-477a-883b-0040a63149b5' 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 21 14:17:08 2022: cdo remapnn,grid.des regcmensble.nc regcmensble_remap.nc\n",
       "Thu Jul 21 14:08:02 2022: cdo divc,3 final.nc regcmensble.nc\n",
       "Thu Jul 21 14:06:30 2022: cdo -add miroc5_pr_197001-200512.nc -add mpiesm_pr_197001-200512.nc noresm_pr_197001-200512.nc final.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: 95, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1998-01-16T12:00:00 ... 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 1998-01-01 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 21 14:17:08 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('1998-01-16T12:00:00.000000000','2005-12-16T00:00:00.000000000'))\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c811b0f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 32, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1998-06-16 ... 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 1998-06-01 00:00:00 ... 2005-10-01 00:00:00\n",
       "    pr         (time, lat, lon) float32 7.507e-06 8.527e-06 ... 0.0002444\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 21 14:17:08 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-7b52ba88-1cb6-4569-b96e-06d2b4f0f681' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7b52ba88-1cb6-4569-b96e-06d2b4f0f681' 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>: 32</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-d6ba0116-2cb2-4190-97e0-e80e5ff9de84' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d6ba0116-2cb2-4190-97e0-e80e5ff9de84' 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'>1998-06-16 ... 2005-09-16</div><input id='attrs-9190cf52-7645-4ab5-9670-02504b938d77' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9190cf52-7645-4ab5-9670-02504b938d77' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ccbabe1c-2394-4c68-9373-97b66001680e' class='xr-var-data-in' type='checkbox'><label for='data-ccbabe1c-2394-4c68-9373-97b66001680e' 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;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-9fd4a77a-f04c-45f8-9dfd-3611d1c16c36' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9fd4a77a-f04c-45f8-9dfd-3611d1c16c36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb137d9e-bbd4-40c1-a49b-d9e95a049c48' class='xr-var-data-in' type='checkbox'><label for='data-bb137d9e-bbd4-40c1-a49b-d9e95a049c48' 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-4f7e3fea-f29c-4554-8274-47becdd23136' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f7e3fea-f29c-4554-8274-47becdd23136' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e33fdc28-37d6-44b6-af56-ed257cae937a' class='xr-var-data-in' type='checkbox'><label for='data-e33fdc28-37d6-44b6-af56-ed257cae937a' 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-18c62d59-1cf5-4079-858a-0d650c77a291' class='xr-section-summary-in' type='checkbox'  checked><label for='section-18c62d59-1cf5-4079-858a-0d650c77a291' 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'>1998-06-01 00:00:00 ... 2005-10-...</div><input id='attrs-7df245b3-bfff-4edf-b067-4e9582f274a6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7df245b3-bfff-4edf-b067-4e9582f274a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41812146-f5b2-42b7-9653-af3796faebf5' class='xr-var-data-in' type='checkbox'><label for='data-41812146-f5b2-42b7-9653-af3796faebf5' 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(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-76cb1434-4f10-4a4a-b3b7-f7c2d04c1152' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-76cb1434-4f10-4a4a-b3b7-f7c2d04c1152' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65d817d0-8e57-4f1a-beed-a7803dd65a5e' class='xr-var-data-in' type='checkbox'><label for='data-65d817d0-8e57-4f1a-beed-a7803dd65a5e' 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>array([[[7.507070e-06, 8.527039e-06, ..., 1.173956e-04, 1.209060e-04],\n",
       "        [6.350594e-06, 8.668526e-06, ..., 1.290032e-04, 1.311683e-04],\n",
       "        ...,\n",
       "        [1.218992e-04, 1.155194e-04, ..., 2.822957e-04, 3.478297e-04],\n",
       "        [1.440291e-04, 2.189470e-04, ..., 2.759465e-04, 3.487610e-04]],\n",
       "\n",
       "       [[4.664989e-05, 4.723724e-05, ..., 6.879943e-05, 6.991918e-05],\n",
       "        [4.477118e-05, 4.660643e-05, ..., 7.667144e-05, 5.845620e-05],\n",
       "        ...,\n",
       "        [3.029910e-04, 3.474306e-04, ..., 2.362179e-04, 3.376169e-04],\n",
       "        [3.019010e-04, 5.372904e-04, ..., 2.932694e-04, 3.483378e-04]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[2.152589e-05, 2.244608e-05, ..., 6.013132e-05, 7.477219e-05],\n",
       "        [1.992765e-05, 1.970231e-05, ..., 7.203541e-05, 7.564334e-05],\n",
       "        ...,\n",
       "        [2.243816e-04, 2.350336e-04, ..., 2.693529e-04, 2.421035e-04],\n",
       "        [2.405207e-04, 3.557021e-04, ..., 2.999533e-04, 4.175887e-04]],\n",
       "\n",
       "       [[2.582793e-05, 2.429320e-05, ..., 1.123574e-05, 1.146252e-05],\n",
       "        [2.619803e-05, 2.499986e-05, ..., 1.090661e-05, 1.317567e-05],\n",
       "        ...,\n",
       "        [9.021912e-05, 7.532920e-05, ..., 1.555717e-04, 1.578470e-04],\n",
       "        [9.621084e-05, 1.648383e-04, ..., 2.149370e-04, 2.443651e-04]]],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-eb4eae94-051c-47a1-a0c0-fa5e93492ebc' class='xr-section-summary-in' type='checkbox'  ><label for='section-eb4eae94-051c-47a1-a0c0-fa5e93492ebc' 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 21 14:17:08 2022: cdo remapnn,grid.des regcmensble.nc regcmensble_remap.nc\n",
       "Thu Jul 21 14:08:02 2022: cdo divc,3 final.nc regcmensble.nc\n",
       "Thu Jul 21 14:06:30 2022: cdo -add miroc5_pr_197001-200512.nc -add mpiesm_pr_197001-200512.nc noresm_pr_197001-200512.nc final.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: 32, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1998-06-16 ... 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 1998-06-01 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 21 14:17:08 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": "be94f5d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#jjas_data.x.values\n",
    "#jjas_data.y.values\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "18269e45",
   "metadata": {},
   "outputs": [
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       "\n",
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       "\n",
       ".xr-attrs dt,\n",
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       "\n",
       ".xr-attrs dt {\n",
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       "  grid-column: 1;\n",
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       "\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",
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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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       "  stroke: currentColor;\n",
       "  fill: currentColor;\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([[3.6722486e-05, 3.6118607e-05, 3.7040805e-05, ..., 6.8845220e-05,\n",
       "        6.4427433e-05, 6.8805515e-05],\n",
       "       [3.5614867e-05, 3.5503821e-05, 3.5568639e-05, ..., 7.2409639e-05,\n",
       "        7.0451104e-05, 7.1024857e-05],\n",
       "       [3.3507698e-05, 3.3972330e-05, 3.3465589e-05, ..., 8.1044149e-05,\n",
       "        8.0409678e-05, 8.4466905e-05],\n",
       "       ...,\n",
       "       [1.8973458e-04, 2.1087436e-04, 2.3498239e-04, ..., 2.0993798e-04,\n",
       "        2.1861988e-04, 1.8470669e-04],\n",
       "       [1.9485061e-04, 2.2080420e-04, 2.6857739e-04, ..., 1.9099307e-04,\n",
       "        2.3935267e-04, 2.6059139e-04],\n",
       "       [2.0103669e-04, 3.2553580e-04, 5.1856344e-04, ..., 1.9354082e-04,\n",
       "        2.6153380e-04, 3.1822655e-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-bf045b87-a82e-4e8e-8491-05ce5359bd76' class='xr-array-in' type='checkbox' checked><label for='section-bf045b87-a82e-4e8e-8491-05ce5359bd76' 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>3.672e-05 3.612e-05 3.704e-05 ... 0.0001935 0.0002615 0.0003182</span></div><div class='xr-array-data'><pre>array([[3.6722486e-05, 3.6118607e-05, 3.7040805e-05, ..., 6.8845220e-05,\n",
       "        6.4427433e-05, 6.8805515e-05],\n",
       "       [3.5614867e-05, 3.5503821e-05, 3.5568639e-05, ..., 7.2409639e-05,\n",
       "        7.0451104e-05, 7.1024857e-05],\n",
       "       [3.3507698e-05, 3.3972330e-05, 3.3465589e-05, ..., 8.1044149e-05,\n",
       "        8.0409678e-05, 8.4466905e-05],\n",
       "       ...,\n",
       "       [1.8973458e-04, 2.1087436e-04, 2.3498239e-04, ..., 2.0993798e-04,\n",
       "        2.1861988e-04, 1.8470669e-04],\n",
       "       [1.9485061e-04, 2.2080420e-04, 2.6857739e-04, ..., 1.9099307e-04,\n",
       "        2.3935267e-04, 2.6059139e-04],\n",
       "       [2.0103669e-04, 3.2553580e-04, 5.1856344e-04, ..., 1.9354082e-04,\n",
       "        2.6153380e-04, 3.1822655e-04]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-b248882a-aad6-4459-8f30-81f3dc8dbffa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b248882a-aad6-4459-8f30-81f3dc8dbffa' 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-fecb123e-8d38-47fb-bbaa-d9c67263bd33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fecb123e-8d38-47fb-bbaa-d9c67263bd33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2446eac9-48b9-4f4c-b1de-c7b3966506a4' class='xr-var-data-in' type='checkbox'><label for='data-2446eac9-48b9-4f4c-b1de-c7b3966506a4' 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-fafb4061-b6e9-45be-af2b-41cc4cf2f12e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fafb4061-b6e9-45be-af2b-41cc4cf2f12e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee7d0dae-935a-4334-9d9c-4f6d1a5e0e85' class='xr-var-data-in' type='checkbox'><label for='data-ee7d0dae-935a-4334-9d9c-4f6d1a5e0e85' 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-96319ea0-13c8-47de-b0b7-689a6d6800dd' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-96319ea0-13c8-47de-b0b7-689a6d6800dd' 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([[3.6722486e-05, 3.6118607e-05, 3.7040805e-05, ..., 6.8845220e-05,\n",
       "        6.4427433e-05, 6.8805515e-05],\n",
       "       [3.5614867e-05, 3.5503821e-05, 3.5568639e-05, ..., 7.2409639e-05,\n",
       "        7.0451104e-05, 7.1024857e-05],\n",
       "       [3.3507698e-05, 3.3972330e-05, 3.3465589e-05, ..., 8.1044149e-05,\n",
       "        8.0409678e-05, 8.4466905e-05],\n",
       "       ...,\n",
       "       [1.8973458e-04, 2.1087436e-04, 2.3498239e-04, ..., 2.0993798e-04,\n",
       "        2.1861988e-04, 1.8470669e-04],\n",
       "       [1.9485061e-04, 2.2080420e-04, 2.6857739e-04, ..., 1.9099307e-04,\n",
       "        2.3935267e-04, 2.6059139e-04],\n",
       "       [2.0103669e-04, 3.2553580e-04, 5.1856344e-04, ..., 1.9354082e-04,\n",
       "        2.6153380e-04, 3.1822655e-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": 16,
     "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": 17,
   "id": "6f88bd72",
   "metadata": {},
   "outputs": [
    {
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       "}\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",
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       "\n",
       ".xr-var-name,\n",
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       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (lat: 40, lon: 32)&gt;\n",
       "array([[ 3.17282276,  3.12064762,  3.20032557, ...,  5.94822702,\n",
       "         5.56653023,  5.94479651],\n",
       "       [ 3.07712448,  3.06753013,  3.0731304 , ...,  6.25619281,\n",
       "         6.08697538,  6.13654763],\n",
       "       [ 2.89506514,  2.93520932,  2.89142687, ...,  7.00221446,\n",
       "         6.94739618,  7.29794058],\n",
       "       ...,\n",
       "       [16.39306764, 18.21954511, 20.30247864, ..., 18.13864131,\n",
       "        18.88875794, 15.95865791],\n",
       "       [16.83509275, 19.07748277, 23.20508687, ..., 16.50180146,\n",
       "        20.68007039, 22.51509614],\n",
       "       [17.36956984, 28.12629333, 44.8038809 , ..., 16.721927  ,\n",
       "        22.59652046, 27.49477392]])\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-1684cc29-7a4c-43bf-bbcd-c75d523c08e8' class='xr-array-in' type='checkbox' checked><label for='section-1684cc29-7a4c-43bf-bbcd-c75d523c08e8' 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>3.173 3.121 3.2 3.172 3.228 3.242 ... 24.19 19.32 16.72 22.6 27.49</span></div><div class='xr-array-data'><pre>array([[ 3.17282276,  3.12064762,  3.20032557, ...,  5.94822702,\n",
       "         5.56653023,  5.94479651],\n",
       "       [ 3.07712448,  3.06753013,  3.0731304 , ...,  6.25619281,\n",
       "         6.08697538,  6.13654763],\n",
       "       [ 2.89506514,  2.93520932,  2.89142687, ...,  7.00221446,\n",
       "         6.94739618,  7.29794058],\n",
       "       ...,\n",
       "       [16.39306764, 18.21954511, 20.30247864, ..., 18.13864131,\n",
       "        18.88875794, 15.95865791],\n",
       "       [16.83509275, 19.07748277, 23.20508687, ..., 16.50180146,\n",
       "        20.68007039, 22.51509614],\n",
       "       [17.36956984, 28.12629333, 44.8038809 , ..., 16.721927  ,\n",
       "        22.59652046, 27.49477392]])</pre></div></div></li><li class='xr-section-item'><input id='section-9cccc686-b551-4a52-80c2-5342536ba28c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9cccc686-b551-4a52-80c2-5342536ba28c' 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-e439c3b5-a9b2-46ad-8396-a8c7a288a3cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e439c3b5-a9b2-46ad-8396-a8c7a288a3cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93c37de6-f1d6-4214-983b-9c360a665270' class='xr-var-data-in' type='checkbox'><label for='data-93c37de6-f1d6-4214-983b-9c360a665270' 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-71167cf7-6f84-4a27-a74f-3f6e35daaea6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-71167cf7-6f84-4a27-a74f-3f6e35daaea6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-167cc346-e954-43b0-823f-a51d8136ff5a' class='xr-var-data-in' type='checkbox'><label for='data-167cc346-e954-43b0-823f-a51d8136ff5a' 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-6e5b3f6e-ec2f-4d71-ad40-c426320ea82a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6e5b3f6e-ec2f-4d71-ad40-c426320ea82a' 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([[ 3.17282276,  3.12064762,  3.20032557, ...,  5.94822702,\n",
       "         5.56653023,  5.94479651],\n",
       "       [ 3.07712448,  3.06753013,  3.0731304 , ...,  6.25619281,\n",
       "         6.08697538,  6.13654763],\n",
       "       [ 2.89506514,  2.93520932,  2.89142687, ...,  7.00221446,\n",
       "         6.94739618,  7.29794058],\n",
       "       ...,\n",
       "       [16.39306764, 18.21954511, 20.30247864, ..., 18.13864131,\n",
       "        18.88875794, 15.95865791],\n",
       "       [16.83509275, 19.07748277, 23.20508687, ..., 16.50180146,\n",
       "        20.68007039, 22.51509614],\n",
       "       [17.36956984, 28.12629333, 44.8038809 , ..., 16.721927  ,\n",
       "        22.59652046, 27.49477392]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eraint = jjas_mean*86400\n",
    "eraint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "6c5c5811",
   "metadata": {},
   "outputs": [
    {
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       "\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([[ -5.56896111,  -5.81463478,  -5.81333852, ..., -16.31267122,\n",
       "        -15.49932891, -11.81801635],\n",
       "       [ -5.29624546,  -5.52641095,  -5.84797538, ..., -13.85862417,\n",
       "        -14.42411759, -12.25108926],\n",
       "       [ -5.67909235,  -6.21017059,  -6.23491554, ..., -11.67713971,\n",
       "        -10.45301026, -10.22527841],\n",
       "       ...,\n",
       "       [  9.030732  ,  11.34457615,  13.84025074, ...,  10.58455063,\n",
       "         11.06349531,   6.94784031],\n",
       "       [  9.39046249,  12.30666663,  17.10706696, ...,   9.45299087,\n",
       "         13.57683745,  14.91436365],\n",
       "       [ 10.74283206,  22.11836638,  39.65774627, ...,   9.39250035,\n",
       "         14.85352693,  20.08958329]])\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-127077cd-e445-473a-b9f9-8bf398b275d1' class='xr-array-in' type='checkbox' checked><label for='section-127077cd-e445-473a-b9f9-8bf398b275d1' 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>-5.569 -5.815 -5.813 -6.235 -6.522 ... 18.13 12.41 9.393 14.85 20.09</span></div><div class='xr-array-data'><pre>array([[ -5.56896111,  -5.81463478,  -5.81333852, ..., -16.31267122,\n",
       "        -15.49932891, -11.81801635],\n",
       "       [ -5.29624546,  -5.52641095,  -5.84797538, ..., -13.85862417,\n",
       "        -14.42411759, -12.25108926],\n",
       "       [ -5.67909235,  -6.21017059,  -6.23491554, ..., -11.67713971,\n",
       "        -10.45301026, -10.22527841],\n",
       "       ...,\n",
       "       [  9.030732  ,  11.34457615,  13.84025074, ...,  10.58455063,\n",
       "         11.06349531,   6.94784031],\n",
       "       [  9.39046249,  12.30666663,  17.10706696, ...,   9.45299087,\n",
       "         13.57683745,  14.91436365],\n",
       "       [ 10.74283206,  22.11836638,  39.65774627, ...,   9.39250035,\n",
       "         14.85352693,  20.08958329]])</pre></div></div></li><li class='xr-section-item'><input id='section-c02c11de-5fb2-4261-8a3b-aa36332c2de2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c02c11de-5fb2-4261-8a3b-aa36332c2de2' 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-46243418-af3a-4337-bdad-916451fcfa40' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-46243418-af3a-4337-bdad-916451fcfa40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7b5d5d8-abc4-4659-8f70-201553a841ac' class='xr-var-data-in' type='checkbox'><label for='data-d7b5d5d8-abc4-4659-8f70-201553a841ac' 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-d2eabab6-0993-4838-b9fa-f0341d2d80ec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2eabab6-0993-4838-b9fa-f0341d2d80ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cea74f7b-4f7c-4bb7-925e-28b946816010' class='xr-var-data-in' type='checkbox'><label for='data-cea74f7b-4f7c-4bb7-925e-28b946816010' 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-83ee83c0-c798-4055-9bee-5d9c293efe2b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-83ee83c0-c798-4055-9bee-5d9c293efe2b' 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([[ -5.56896111,  -5.81463478,  -5.81333852, ..., -16.31267122,\n",
       "        -15.49932891, -11.81801635],\n",
       "       [ -5.29624546,  -5.52641095,  -5.84797538, ..., -13.85862417,\n",
       "        -14.42411759, -12.25108926],\n",
       "       [ -5.67909235,  -6.21017059,  -6.23491554, ..., -11.67713971,\n",
       "        -10.45301026, -10.22527841],\n",
       "       ...,\n",
       "       [  9.030732  ,  11.34457615,  13.84025074, ...,  10.58455063,\n",
       "         11.06349531,   6.94784031],\n",
       "       [  9.39046249,  12.30666663,  17.10706696, ...,   9.45299087,\n",
       "         13.57683745,  14.91436365],\n",
       "       [ 10.74283206,  22.11836638,  39.65774627, ...,   9.39250035,\n",
       "         14.85352693,  20.08958329]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bias = eraint - trmm\n",
    "bias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "445388ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  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([[-63.70508802, -65.07499734, -64.49473226, ..., -73.27948336,\n",
       "        -73.5755841 , -66.53234733],\n",
       "       [-63.2510626 , -64.30589759, -65.55213588, ..., -68.89759021,\n",
       "        -70.32349573, -66.6267739 ],\n",
       "       [-66.23498993, -67.90500394, -68.31779108, ..., -62.51361586,\n",
       "        -60.07336837, -58.35273998],\n",
       "       ...,\n",
       "       [122.66123731, 165.01276187, 214.17150482, ..., 140.11680678,\n",
       "        141.38177646,  77.1055483 ],\n",
       "       [126.13739254, 181.7604609 , 280.534784  , ..., 134.10760208,\n",
       "        191.13603006, 196.22271485],\n",
       "       [162.11343209, 368.15305157, 770.63172844, ..., 128.14781821,\n",
       "        191.83183968, 271.290562  ]])\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-999e5971-a7ef-49bd-8e96-bf7059f305a9' class='xr-array-in' type='checkbox' checked><label for='section-999e5971-a7ef-49bd-8e96-bf7059f305a9' 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>-63.71 -65.07 -64.49 -66.28 -66.89 ... 299.3 179.6 128.1 191.8 271.3</span></div><div class='xr-array-data'><pre>array([[-63.70508802, -65.07499734, -64.49473226, ..., -73.27948336,\n",
       "        -73.5755841 , -66.53234733],\n",
       "       [-63.2510626 , -64.30589759, -65.55213588, ..., -68.89759021,\n",
       "        -70.32349573, -66.6267739 ],\n",
       "       [-66.23498993, -67.90500394, -68.31779108, ..., -62.51361586,\n",
       "        -60.07336837, -58.35273998],\n",
       "       ...,\n",
       "       [122.66123731, 165.01276187, 214.17150482, ..., 140.11680678,\n",
       "        141.38177646,  77.1055483 ],\n",
       "       [126.13739254, 181.7604609 , 280.534784  , ..., 134.10760208,\n",
       "        191.13603006, 196.22271485],\n",
       "       [162.11343209, 368.15305157, 770.63172844, ..., 128.14781821,\n",
       "        191.83183968, 271.290562  ]])</pre></div></div></li><li class='xr-section-item'><input id='section-beeb6598-2fd2-4fe7-a329-bea86be08433' class='xr-section-summary-in' type='checkbox'  checked><label for='section-beeb6598-2fd2-4fe7-a329-bea86be08433' 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-0946b420-deb7-4e27-a880-c0af13c801a8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0946b420-deb7-4e27-a880-c0af13c801a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2c33d7ed-b56e-4046-a76c-5723bf054eb2' class='xr-var-data-in' type='checkbox'><label for='data-2c33d7ed-b56e-4046-a76c-5723bf054eb2' 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-85227416-11b1-43ce-a25a-c939402dd7ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-85227416-11b1-43ce-a25a-c939402dd7ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4aed9c29-3fa1-47b8-a2ea-a4acb9c2bc24' class='xr-var-data-in' type='checkbox'><label for='data-4aed9c29-3fa1-47b8-a2ea-a4acb9c2bc24' 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-3ddf8660-8454-47ec-b277-aaa2ce9e92d5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3ddf8660-8454-47ec-b277-aaa2ce9e92d5' 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([[-63.70508802, -65.07499734, -64.49473226, ..., -73.27948336,\n",
       "        -73.5755841 , -66.53234733],\n",
       "       [-63.2510626 , -64.30589759, -65.55213588, ..., -68.89759021,\n",
       "        -70.32349573, -66.6267739 ],\n",
       "       [-66.23498993, -67.90500394, -68.31779108, ..., -62.51361586,\n",
       "        -60.07336837, -58.35273998],\n",
       "       ...,\n",
       "       [122.66123731, 165.01276187, 214.17150482, ..., 140.11680678,\n",
       "        141.38177646,  77.1055483 ],\n",
       "       [126.13739254, 181.7604609 , 280.534784  , ..., 134.10760208,\n",
       "        191.13603006, 196.22271485],\n",
       "       [162.11343209, 368.15305157, 770.63172844, ..., 128.14781821,\n",
       "        191.83183968, 271.290562  ]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bias_percentage = ((eraint - trmm)/trmm)*100\n",
    "bias_percentage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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",
    "\n",
    "plt.title('Seasonal Bias(RegCM ensemble avg-TRMM)',fontsize=17)\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/Seasonal Bias(regcm ensemble avg-trmm).png\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "9003db92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x972 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting bias percentage \n",
    "\n",
    "#plotting with cartopy\n",
    "import cartopy.feature as cfeature\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize=(16,13.5))\n",
    "\n",
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "ax.set_extent([88,93,20,27])\n",
    "\n",
    "\n",
    "m1 = ax.contourf(bias_percentage['lon'], bias_percentage['lat'],bias_percentage[:,:],\n",
    "                levels=np.arange(-150,150+25,25),transform = ccrs.PlateCarree(),cmap='BrBG',extend='both')\n",
    "\n",
    "\n",
    "#levels=(-150,-100,-75,-50,-25,-10,-5,0,5,10,25,50,75,100,150)\n",
    "# Define the xticks for longitude\n",
    "ax.set_xticks(np.arange(87,94,1), crs=ccrs.PlateCarree())\n",
    "lon_formatter = cticker.LongitudeFormatter()\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "\n",
    "# Define the yticks for latitude\n",
    "ax.set_yticks(np.arange(20,28,1), crs=ccrs.PlateCarree())\n",
    "lat_formatter = cticker.LatitudeFormatter()\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "\n",
    "\n",
    "plt.colorbar(m1,ticks=np.arange(-150,150+25,25),orientation = 'horizontal',shrink=0.7, fraction = 0.04 , label = 'percentage')\n",
    "ax.coastlines(linewidth=3)\n",
    "ax.add_feature(cfeature.BORDERS,linewidth=3)\n",
    "\n",
    "\n",
    "plt.title('Seasonal Bias-Percentage(RegCM ensemble avg-TRMM)' )\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/Seasonal Bias_percentage(regcm ensemble avg-trmm).png\")\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#cma colors\n",
    "'''Colormap CET_D1A is not recognized. Possible values are: Accent, Accent_r, Blues, Blues_r, \n",
    "BrBG, BrBG_r, BuGn, BuGn_r, BuPu, BuPu_r, CMRmap, CMRmap_r, Dark2, Dark2_r, GnBu, GnBu_r, Greens,\n",
    "Greens_r, Greys, Greys_r, OrRd, OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, \n",
    "Pastel2_r, PiYG, PiYG_r, PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Purples_r, RdBu, RdBu_r, RdGy,\n",
    "RdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, \n",
    "Spectral_r, Wistia, Wistia_r, YlGn, YlGnBu, YlGnBu_r, YlGn_r, YlOrBr, YlOrBr_r, YlOrRd, YlOrRd_r, afmhot, afmhot_r, autumn,\n",
    "autumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, cividis, cividis_r, cool, cool_r, coolwarm, coolwarm_r, \n",
    "copper, copper_r, cubehelix, cubehelix_r, flag, flag_r, gist_earth, gist_earth_r, gist_gray, gist_gray_r, gist_heat,\n",
    "gist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r,\n",
    "gnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r, hsv, hsv_r, inferno, inferno_r, jet, jet_r, magma,\n",
    "magma_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, \n",
    "seismic, seismic_r, spring, spring_r, summer, summer_r, tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, \n",
    "ter'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "87f4ea28",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "20e38f40",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "21be7cc5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2b1ed707",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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