Seasonal Bias(Noresm-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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       "Dimensions:  (time: 132, lat: 400, lon: 1440)\n",
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       "    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-a59824ed-e3c3-4ea9-9882-2c08c2989812' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a59824ed-e3c3-4ea9-9882-2c08c2989812' 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-a9a41c19-e5b1-4d4f-bdf1-f7f8b9bd14d6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a9a41c19-e5b1-4d4f-bdf1-f7f8b9bd14d6' 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-4fc9e0df-808d-4586-ba7a-8c1d4612449d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4fc9e0df-808d-4586-ba7a-8c1d4612449d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf482fb9-6ef1-458c-99c9-caef25671fda' class='xr-var-data-in' type='checkbox'><label for='data-bf482fb9-6ef1-458c-99c9-caef25671fda' 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-b0dc9078-2586-42c2-88be-2d9d4ab484e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0dc9078-2586-42c2-88be-2d9d4ab484e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc73f7bc-0b37-4e6e-86b7-60510720c4f0' class='xr-var-data-in' type='checkbox'><label for='data-dc73f7bc-0b37-4e6e-86b7-60510720c4f0' 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-5ba752d9-089b-4934-9404-13dcb624a3f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ba752d9-089b-4934-9404-13dcb624a3f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae122f33-fff2-4051-9d85-daffa9f2084b' class='xr-var-data-in' type='checkbox'><label for='data-ae122f33-fff2-4051-9d85-daffa9f2084b' 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-868dfc65-8c26-4d1c-85ee-24ddee1a6fcb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-868dfc65-8c26-4d1c-85ee-24ddee1a6fcb' 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-7960d283-0745-4311-96a8-b8f26a895ac3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7960d283-0745-4311-96a8-b8f26a895ac3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0dc0f946-2bd1-47e6-810a-bc8a3414bb6d' class='xr-var-data-in' type='checkbox'><label for='data-0dc0f946-2bd1-47e6-810a-bc8a3414bb6d' 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-848df5db-71a0-4b00-803b-0c314421dc91' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-848df5db-71a0-4b00-803b-0c314421dc91' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-881574b9-1463-48ca-8cba-c19fc34ae21a' class='xr-var-data-in' type='checkbox'><label for='data-881574b9-1463-48ca-8cba-c19fc34ae21a' 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-d9414a5c-de00-453c-a789-7e9f4b052d7b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d9414a5c-de00-453c-a789-7e9f4b052d7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6734752-addf-4a39-8c1a-f707ac7127b3' class='xr-var-data-in' type='checkbox'><label for='data-e6734752-addf-4a39-8c1a-f707ac7127b3' 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-abbba395-71f9-4305-8db0-3deae7c01878' class='xr-section-summary-in' type='checkbox'  checked><label for='section-abbba395-71f9-4305-8db0-3deae7c01878' 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": [
    {
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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-ef9505c0-96dc-4e89-8778-80b0301726a5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ef9505c0-96dc-4e89-8778-80b0301726a5' 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-e9143eb4-82d8-46d1-a03a-3b5508706f35' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e9143eb4-82d8-46d1-a03a-3b5508706f35' 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-bd72f9d5-5edb-4692-bd46-e1cca9834a01' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bd72f9d5-5edb-4692-bd46-e1cca9834a01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45882182-a326-41d8-96f8-db523cd14962' class='xr-var-data-in' type='checkbox'><label for='data-45882182-a326-41d8-96f8-db523cd14962' 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-c1becbb5-45d7-43da-8473-1a2a1672d627' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1becbb5-45d7-43da-8473-1a2a1672d627' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2eef250-62b3-47e0-b757-6518e8e3abc4' class='xr-var-data-in' type='checkbox'><label for='data-a2eef250-62b3-47e0-b757-6518e8e3abc4' 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-7d2873b0-56e1-406a-bfbf-86e3151eb6ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d2873b0-56e1-406a-bfbf-86e3151eb6ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c876d00-56bc-46c7-b617-cf5ff550461a' class='xr-var-data-in' type='checkbox'><label for='data-7c876d00-56bc-46c7-b617-cf5ff550461a' 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-0eb689fb-1dd1-4a5c-9712-ffdf36eca3d8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0eb689fb-1dd1-4a5c-9712-ffdf36eca3d8' 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-a07eef9a-aaa7-4ebc-b9eb-4488b6d3242d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a07eef9a-aaa7-4ebc-b9eb-4488b6d3242d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47e6cbfd-06ae-4c76-b8ed-1cb17d2451b7' class='xr-var-data-in' type='checkbox'><label for='data-47e6cbfd-06ae-4c76-b8ed-1cb17d2451b7' 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-b0d28ca0-0ab3-4d5e-82ed-a7ab34d3cebf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0d28ca0-0ab3-4d5e-82ed-a7ab34d3cebf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-570b201d-377d-4885-bbe5-99b0850c4855' class='xr-var-data-in' type='checkbox'><label for='data-570b201d-377d-4885-bbe5-99b0850c4855' 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-6be5422a-4c0c-4a2a-8bf0-8e0a7bac071a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6be5422a-4c0c-4a2a-8bf0-8e0a7bac071a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28447dbd-ed41-46ef-9288-2abaf2b3bc20' class='xr-var-data-in' type='checkbox'><label for='data-28447dbd-ed41-46ef-9288-2abaf2b3bc20' 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-ab2ac3b6-b850-4cda-816b-7d4da1e30d61' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ab2ac3b6-b850-4cda-816b-7d4da1e30d61' 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-0081c32e-16f2-4759-bb60-688dcbe48318' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0081c32e-16f2-4759-bb60-688dcbe48318' 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-9580b953-41e6-4fa6-bf00-2ad782b22346' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9580b953-41e6-4fa6-bf00-2ad782b22346' 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-0797492c-cd52-4e0c-9b1c-a3e7acaf9b78' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0797492c-cd52-4e0c-9b1c-a3e7acaf9b78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9597edd4-5d0e-4709-a9a2-60498b482b08' class='xr-var-data-in' type='checkbox'><label for='data-9597edd4-5d0e-4709-a9a2-60498b482b08' 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-0982ab2f-ed0d-47f9-88ce-23d31dbb9811' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0982ab2f-ed0d-47f9-88ce-23d31dbb9811' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2633907c-d2ce-4da2-8f90-9406587c08c5' class='xr-var-data-in' type='checkbox'><label for='data-2633907c-d2ce-4da2-8f90-9406587c08c5' 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-841e096d-5e0f-4b0f-83d7-65cef2585472' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-841e096d-5e0f-4b0f-83d7-65cef2585472' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-740432ef-f89b-44ab-84db-ee1b0ba0e31d' class='xr-var-data-in' type='checkbox'><label for='data-740432ef-f89b-44ab-84db-ee1b0ba0e31d' 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-a9c9ddaa-3d69-42f7-ae11-d3216d7cc203' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a9c9ddaa-3d69-42f7-ae11-d3216d7cc203' 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-3e912afd-cb40-4548-bd6d-a2dcd3982919' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e912afd-cb40-4548-bd6d-a2dcd3982919' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53a49ce3-ff51-471c-b130-142cdadc04c2' class='xr-var-data-in' type='checkbox'><label for='data-53a49ce3-ff51-471c-b130-142cdadc04c2' 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-28cde83c-44c9-49b4-9de5-f82e16915c98' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-28cde83c-44c9-49b4-9de5-f82e16915c98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-538aec48-1937-4d8b-9e25-25149f767535' class='xr-var-data-in' type='checkbox'><label for='data-538aec48-1937-4d8b-9e25-25149f767535' 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-93a365a2-83fe-4a83-8494-cf8ac01dbe60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93a365a2-83fe-4a83-8494-cf8ac01dbe60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5c2d826-a5d9-43b6-a072-7c4ebd0153a4' class='xr-var-data-in' type='checkbox'><label for='data-f5c2d826-a5d9-43b6-a072-7c4ebd0153a4' 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-1a92f5bd-7a59-4724-b132-0c1580c6c9f3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1a92f5bd-7a59-4724-b132-0c1580c6c9f3' 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": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\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-c2221015-f3a9-40ad-9c5e-1e8348ac812b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c2221015-f3a9-40ad-9c5e-1e8348ac812b' 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-36fc920d-0efa-4880-b3ee-cb29a3fe0b33' class='xr-section-summary-in' type='checkbox'  checked><label for='section-36fc920d-0efa-4880-b3ee-cb29a3fe0b33' 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-dcc2ee57-91dd-4f0d-a707-7d3de82c6e4a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dcc2ee57-91dd-4f0d-a707-7d3de82c6e4a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a09ff003-415c-4a34-9df7-2ab9568b3485' class='xr-var-data-in' type='checkbox'><label for='data-a09ff003-415c-4a34-9df7-2ab9568b3485' 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-d8457535-1212-4717-8348-dbd967a649d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d8457535-1212-4717-8348-dbd967a649d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02be6ba3-e048-458f-8cdc-ca09d3033b19' class='xr-var-data-in' type='checkbox'><label for='data-02be6ba3-e048-458f-8cdc-ca09d3033b19' 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-efc20181-1a9f-4a74-989c-ef828e491cf4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-efc20181-1a9f-4a74-989c-ef828e491cf4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1ae27c4-abb6-4531-8279-86b456ea3691' class='xr-var-data-in' type='checkbox'><label for='data-f1ae27c4-abb6-4531-8279-86b456ea3691' 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-1003da7a-a950-4c79-a127-b46ada7784e7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1003da7a-a950-4c79-a127-b46ada7784e7' 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-19de55c2-8d04-41eb-ac93-3bd56cbfaf5e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-19de55c2-8d04-41eb-ac93-3bd56cbfaf5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77295e9f-c22c-4c11-a0e5-4e14c8880cdb' class='xr-var-data-in' type='checkbox'><label for='data-77295e9f-c22c-4c11-a0e5-4e14c8880cdb' 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-adc18232-f1a6-4bb3-ab89-2aebf6d8c0b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-adc18232-f1a6-4bb3-ab89-2aebf6d8c0b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3932fbc4-3800-491c-ab6b-bcc90f3cda7e' class='xr-var-data-in' type='checkbox'><label for='data-3932fbc4-3800-491c-ab6b-bcc90f3cda7e' 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-c2d7d4e1-5c72-4ff2-9cb0-bec56b93f8e5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c2d7d4e1-5c72-4ff2-9cb0-bec56b93f8e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b63aaaa7-8f70-426b-a1df-6adbe15f6d70' class='xr-var-data-in' type='checkbox'><label for='data-b63aaaa7-8f70-426b-a1df-6adbe15f6d70' 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-3426ed86-79c7-4966-b83b-c2c70578fa6c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3426ed86-79c7-4966-b83b-c2c70578fa6c' 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": "b6f4c992",
   "metadata": {},
   "outputs": [],
   "source": [
    "#interpolating to new lat and lon\n",
    "\n",
    "#new_lon = np.arange(86,94,0.2007)\n",
    "#new_lat = np.arange(18,28,0.034)\n",
    "#jjas_data = jjas_data.interp(lat=new_lat,lon=new_lon)\n",
    "#jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "82d6b5d0",
   "metadata": {},
   "outputs": [
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       "\n",
       ".xr-attrs dd {\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([[0.36424097, 0.37230343, 0.37556937, ..., 0.9275374 , 0.8777441 ,\n",
       "        0.7401172 ],\n",
       "       [0.3488904 , 0.3580809 , 0.37171277, ..., 0.8381174 , 0.8546289 ,\n",
       "        0.7661515 ],\n",
       "       [0.35725656, 0.38105756, 0.38026428, ..., 0.7783064 , 0.7250169 ,\n",
       "        0.7301341 ],\n",
       "       ...,\n",
       "       [0.30676398, 0.28645703, 0.2692595 , ..., 0.3147538 , 0.3260526 ,\n",
       "        0.37545067],\n",
       "       [0.31019294, 0.28211737, 0.25408417, ..., 0.2937004 , 0.295968  ,\n",
       "        0.31669715],\n",
       "       [0.27611408, 0.25033024, 0.2144223 , ..., 0.30539277, 0.3226247 ,\n",
       "        0.3085496 ]], dtype=float32)\n",
       "Coordinates:\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</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-70ef52ed-4738-47ca-87a1-da6f762eb1ba' class='xr-array-in' type='checkbox' checked><label for='section-70ef52ed-4738-47ca-87a1-da6f762eb1ba' 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([[0.36424097, 0.37230343, 0.37556937, ..., 0.9275374 , 0.8777441 ,\n",
       "        0.7401172 ],\n",
       "       [0.3488904 , 0.3580809 , 0.37171277, ..., 0.8381174 , 0.8546289 ,\n",
       "        0.7661515 ],\n",
       "       [0.35725656, 0.38105756, 0.38026428, ..., 0.7783064 , 0.7250169 ,\n",
       "        0.7301341 ],\n",
       "       ...,\n",
       "       [0.30676398, 0.28645703, 0.2692595 , ..., 0.3147538 , 0.3260526 ,\n",
       "        0.37545067],\n",
       "       [0.31019294, 0.28211737, 0.25408417, ..., 0.2937004 , 0.295968  ,\n",
       "        0.31669715],\n",
       "       [0.27611408, 0.25033024, 0.2144223 , ..., 0.30539277, 0.3226247 ,\n",
       "        0.3085496 ]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-4c7a7fe2-3480-423d-b1f4-a4daff18c490' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4c7a7fe2-3480-423d-b1f4-a4daff18c490' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-e79925b3-acd0-40f7-92f8-fd66dee5bd75' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e79925b3-acd0-40f7-92f8-fd66dee5bd75' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea9b7751-f18f-47f1-b3d5-e263e17267e7' class='xr-var-data-in' type='checkbox'><label for='data-ea9b7751-f18f-47f1-b3d5-e263e17267e7' 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-7107d6ef-6cfb-483c-992a-eccfcd4afcb5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7107d6ef-6cfb-483c-992a-eccfcd4afcb5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47f5bcb2-98ff-4412-a57b-f2f608dce1f8' class='xr-var-data-in' type='checkbox'><label for='data-47f5bcb2-98ff-4412-a57b-f2f608dce1f8' 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-2abe2c24-d6e9-41ac-93a1-d46df8a83261' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2abe2c24-d6e9-41ac-93a1-d46df8a83261' 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([[0.36424097, 0.37230343, 0.37556937, ..., 0.9275374 , 0.8777441 ,\n",
       "        0.7401172 ],\n",
       "       [0.3488904 , 0.3580809 , 0.37171277, ..., 0.8381174 , 0.8546289 ,\n",
       "        0.7661515 ],\n",
       "       [0.35725656, 0.38105756, 0.38026428, ..., 0.7783064 , 0.7250169 ,\n",
       "        0.7301341 ],\n",
       "       ...,\n",
       "       [0.30676398, 0.28645703, 0.2692595 , ..., 0.3147538 , 0.3260526 ,\n",
       "        0.37545067],\n",
       "       [0.31019294, 0.28211737, 0.25408417, ..., 0.2937004 , 0.295968  ,\n",
       "        0.31669715],\n",
       "       [0.27611408, 0.25033024, 0.2144223 , ..., 0.30539277, 0.3226247 ,\n",
       "        0.3085496 ]], dtype=float32)\n",
       "Coordinates:\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"
      ]
     },
     "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",
    " \n",
    "\n",
    "\n",
    "trmm = pr_mm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b6d9b2b3",
   "metadata": {},
   "outputs": [
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       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\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: 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 07 17:05:10 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_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    driving_experiment:                              NCC-NorESM1-M, historica...\n",
       "    driving_model_id:                                NCC-NorESM1-M\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-e3fb9049-5575-4110-8266-5f427e68724e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e3fb9049-5575-4110-8266-5f427e68724e' 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-49f40a36-565f-426a-8c75-50a48d99a0b1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-49f40a36-565f-426a-8c75-50a48d99a0b1' 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-c4cc9bec-5825-4a25-a14f-6e21ebae75df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c4cc9bec-5825-4a25-a14f-6e21ebae75df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27c9b050-7e53-4fa0-8c05-8699b617d0e8' class='xr-var-data-in' type='checkbox'><label for='data-27c9b050-7e53-4fa0-8c05-8699b617d0e8' 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-e7d7a719-53be-4b92-8f13-33e8df09208b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7d7a719-53be-4b92-8f13-33e8df09208b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8370cb09-d7ae-433b-a0c2-400fd5e424b3' class='xr-var-data-in' type='checkbox'><label for='data-8370cb09-d7ae-433b-a0c2-400fd5e424b3' 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-d855e077-124a-463b-ac95-8d9382327b18' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d855e077-124a-463b-ac95-8d9382327b18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67948fff-c307-4bb5-b41c-114ed97fbd45' class='xr-var-data-in' type='checkbox'><label for='data-67948fff-c307-4bb5-b41c-114ed97fbd45' 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-c198584a-e742-445b-9307-c2050882cd2f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c198584a-e742-445b-9307-c2050882cd2f' 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-3e9ddecb-3c59-4a5b-a0cc-4c53de86cc0b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3e9ddecb-3c59-4a5b-a0cc-4c53de86cc0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d9eb97d-1257-4af8-a986-7560641e5084' class='xr-var-data-in' type='checkbox'><label for='data-9d9eb97d-1257-4af8-a986-7560641e5084' 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-4df3edef-b8ee-454e-b030-8b3d6a427259' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4df3edef-b8ee-454e-b030-8b3d6a427259' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f812283f-acc8-48ca-ae32-939747b7e08e' class='xr-var-data-in' type='checkbox'><label for='data-f812283f-acc8-48ca-ae32-939747b7e08e' 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-5b378101-be03-4a4f-b633-2e305ea9f944' class='xr-section-summary-in' type='checkbox'  ><label for='section-5b378101-be03-4a4f-b633-2e305ea9f944' class='xr-section-summary' >Attributes: <span>(165)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>history :</span></dt><dd>Thu Jul 07 17:05:10 2022: cdo remapnn,grid1.des noresm_pr_197001-200512.nc noresm1_remap.nc\n",
       "Mon Jun 27 15:36:42 2022: cdo mergetime pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_197001-198012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_198101-199012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_199101-200012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_200101-200512.nc noresm_pr_197001-200512.nc\n",
       "2018-03-21 03:01:05 : 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>2019-09-19T16:13:52Z</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>e18baf90-8c3e-11e9-a8fd-f04da273d2fb</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>NO_85</dd><dt><span>model_sst_data_source :</span></dt><dd>NO_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> 2005-12-31 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 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:</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 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      ],
      "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 07 17:05:10 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_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    driving_experiment:                              NCC-NorESM1-M, historica...\n",
       "    driving_model_id:                                NCC-NorESM1-M\n",
       "    CDO:                                             Climate Data Operators v..."
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#opening the noresm data\n",
    "\n",
    "data = xr.open_dataset('/home/mkibria/Academic/pr_of_thesis/regcm driven by gcm/NorESM1-M/noresm1_remap.nc')\n",
    " \n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e0f877d3",
   "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_29207/1463838701.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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       ".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: 432, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1970-01-16T12:00:00 ... 2005-12-16T12:00:00\n",
       "  * lon        (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat        (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1970-01-01 00:00:00 ... 2006-01-01 00:00:00\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:05:10 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_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    driving_experiment:                              NCC-NorESM1-M, historica...\n",
       "    driving_model_id:                                NCC-NorESM1-M\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-f23f683b-7484-4567-aeca-97990cc71b8a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f23f683b-7484-4567-aeca-97990cc71b8a' 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-d7d93b14-06a1-460e-b738-62c1eaabae31' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d7d93b14-06a1-460e-b738-62c1eaabae31' 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-cd366f8e-c88d-42be-93eb-2bed0be4952e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cd366f8e-c88d-42be-93eb-2bed0be4952e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0ba169c-11ef-49a2-96db-0f870b4b8203' class='xr-var-data-in' type='checkbox'><label for='data-a0ba169c-11ef-49a2-96db-0f870b4b8203' 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-81df1abc-b00e-472f-94fb-39a0fb06011c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81df1abc-b00e-472f-94fb-39a0fb06011c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb0706eb-1e42-4431-9dcc-3db9509d1db2' class='xr-var-data-in' type='checkbox'><label for='data-bb0706eb-1e42-4431-9dcc-3db9509d1db2' 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-1f53a9c2-24c2-4b72-8c08-2359a2dafc0a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f53a9c2-24c2-4b72-8c08-2359a2dafc0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9eedf6bd-503f-49dc-9bba-f7d5c2112261' class='xr-var-data-in' type='checkbox'><label for='data-9eedf6bd-503f-49dc-9bba-f7d5c2112261' 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-01feff0e-8439-4870-b6b6-d754aba8ff62' class='xr-section-summary-in' type='checkbox'  checked><label for='section-01feff0e-8439-4870-b6b6-d754aba8ff62' 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-1c167a17-a8af-4560-b4cc-4de7c6c2a131' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1c167a17-a8af-4560-b4cc-4de7c6c2a131' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e63f2584-7ca6-4234-ad01-c8685e12fcf7' class='xr-var-data-in' type='checkbox'><label for='data-e63f2584-7ca6-4234-ad01-c8685e12fcf7' 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-26626af4-5561-4626-a8ea-ee9a576ee219' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26626af4-5561-4626-a8ea-ee9a576ee219' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ca8241f-824d-4ee4-a134-ec45e7e51477' class='xr-var-data-in' type='checkbox'><label for='data-4ca8241f-824d-4ee4-a134-ec45e7e51477' 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-8d2e6541-8dc1-44e7-9e50-ad651345551e' class='xr-section-summary-in' type='checkbox'  ><label for='section-8d2e6541-8dc1-44e7-9e50-ad651345551e' class='xr-section-summary' >Attributes: <span>(165)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>history :</span></dt><dd>Thu Jul 07 17:05:10 2022: cdo remapnn,grid1.des noresm_pr_197001-200512.nc noresm1_remap.nc\n",
       "Mon Jun 27 15:36:42 2022: cdo mergetime pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_197001-198012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_198101-199012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_199101-200012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_200101-200512.nc noresm_pr_197001-200512.nc\n",
       "2018-03-21 03:01:05 : 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>2019-09-19T16:13:52Z</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>e18baf90-8c3e-11e9-a8fd-f04da273d2fb</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>NO_85</dd><dt><span>model_sst_data_source :</span></dt><dd>NO_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> 2005-12-31 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_name :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>ICTP-RegCM4-7</dd><dt><span>driving_experiment :</span></dt><dd>NCC-NorESM1-M, historical, r1i1p1</dd><dt><span>driving_model_id :</span></dt><dd>NCC-NorESM1-M</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.9rc1 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (time: 432, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1970-01-16T12:00:00 ... 2005-12-16T12:00:00\n",
       "  * lon        (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat        (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1970-01-01 00:00:00 ... 2006-01-01 00:00:00\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:05:10 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_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    driving_experiment:                              NCC-NorESM1-M, historica...\n",
       "    driving_model_id:                                NCC-NorESM1-M\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": "fa087746",
   "metadata": {},
   "outputs": [],
   "source": [
    "#data.lat.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "cafd5692",
   "metadata": {},
   "outputs": [
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       "  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, 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 07 17:05:10 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_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    driving_experiment:                              NCC-NorESM1-M, historica...\n",
       "    driving_model_id:                                NCC-NorESM1-M\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-b8c1c67e-bcdf-415a-a3c7-ae9af8d2b173' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b8c1c67e-bcdf-415a-a3c7-ae9af8d2b173' 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-da059e21-b42c-45b1-b378-8d6df5b800ab' class='xr-section-summary-in' type='checkbox'  checked><label for='section-da059e21-b42c-45b1-b378-8d6df5b800ab' 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-d92859fe-f47e-4b22-a510-865e1eec6171' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d92859fe-f47e-4b22-a510-865e1eec6171' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-267e7fbe-45f1-4725-b350-322a9edfb118' class='xr-var-data-in' type='checkbox'><label for='data-267e7fbe-45f1-4725-b350-322a9edfb118' 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-ccf17e20-308b-449b-9785-257122954db0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ccf17e20-308b-449b-9785-257122954db0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a38d85e-2f9c-4fb6-91fb-2383be54dc7d' class='xr-var-data-in' type='checkbox'><label for='data-6a38d85e-2f9c-4fb6-91fb-2383be54dc7d' 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-8c6f145e-db9e-42f7-a577-d8972da72ad9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c6f145e-db9e-42f7-a577-d8972da72ad9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b873dcc7-8ca4-477a-8ea8-6f543e3f15d3' class='xr-var-data-in' type='checkbox'><label for='data-b873dcc7-8ca4-477a-8ea8-6f543e3f15d3' 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-07252fb4-c7e5-464b-87a1-5852fab09491' class='xr-section-summary-in' type='checkbox'  checked><label for='section-07252fb4-c7e5-464b-87a1-5852fab09491' 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-d427cfbc-5133-4db6-9e37-fad0cb8d2e4c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d427cfbc-5133-4db6-9e37-fad0cb8d2e4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ffccffa-a1c4-4e62-ba5e-51fd52a516fe' class='xr-var-data-in' type='checkbox'><label for='data-1ffccffa-a1c4-4e62-ba5e-51fd52a516fe' 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-1fa09e3e-43b0-47ab-95c4-2b224247164f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1fa09e3e-43b0-47ab-95c4-2b224247164f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-367081da-8ccc-4843-ba64-6342dfd514a1' class='xr-var-data-in' type='checkbox'><label for='data-367081da-8ccc-4843-ba64-6342dfd514a1' 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-e876d0af-b8cd-42e6-9e21-766c6086fac6' class='xr-section-summary-in' type='checkbox'  ><label for='section-e876d0af-b8cd-42e6-9e21-766c6086fac6' class='xr-section-summary' >Attributes: <span>(165)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>history :</span></dt><dd>Thu Jul 07 17:05:10 2022: cdo remapnn,grid1.des noresm_pr_197001-200512.nc noresm1_remap.nc\n",
       "Mon Jun 27 15:36:42 2022: cdo mergetime pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_197001-198012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_198101-199012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_199101-200012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_200101-200512.nc noresm_pr_197001-200512.nc\n",
       "2018-03-21 03:01:05 : 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>2019-09-19T16:13:52Z</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>e18baf90-8c3e-11e9-a8fd-f04da273d2fb</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>NO_85</dd><dt><span>model_sst_data_source :</span></dt><dd>NO_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> 2005-12-31 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_name :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>ICTP-RegCM4-7</dd><dt><span>driving_experiment :</span></dt><dd>NCC-NorESM1-M, historical, r1i1p1</dd><dt><span>driving_model_id :</span></dt><dd>NCC-NorESM1-M</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 07 17:05:10 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_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    driving_experiment:                              NCC-NorESM1-M, historica...\n",
       "    driving_model_id:                                NCC-NorESM1-M\n",
       "    CDO:                                             Climate Data Operators v..."
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#to select the year from 1980 to 2015\n",
    "#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": 15,
   "id": "c811b0f2",
   "metadata": {},
   "outputs": [
    {
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       "  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: 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 7.234e-06 7.954e-06 ... 0.0002561\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:05:10 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_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    driving_experiment:                              NCC-NorESM1-M, historica...\n",
       "    driving_model_id:                                NCC-NorESM1-M\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-06ae600e-5491-48d8-bb98-6cfb7800f473' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-06ae600e-5491-48d8-bb98-6cfb7800f473' 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-19911310-5c9f-4b02-a401-7da148d488e5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-19911310-5c9f-4b02-a401-7da148d488e5' 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-f659409f-2530-4afb-b78c-820fabe5e724' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f659409f-2530-4afb-b78c-820fabe5e724' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51970912-c5f3-4035-9376-78cae2eec5df' class='xr-var-data-in' type='checkbox'><label for='data-51970912-c5f3-4035-9376-78cae2eec5df' 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-5c3eb414-e58a-42d2-9550-64fec49999bb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c3eb414-e58a-42d2-9550-64fec49999bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-276571f8-f8e3-4e55-ace8-22eb19337340' class='xr-var-data-in' type='checkbox'><label for='data-276571f8-f8e3-4e55-ace8-22eb19337340' 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-c7423944-fc15-4012-b3dd-b10e84e49f95' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c7423944-fc15-4012-b3dd-b10e84e49f95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7afe8a35-394d-4a93-8140-1fc08670013e' class='xr-var-data-in' type='checkbox'><label for='data-7afe8a35-394d-4a93-8140-1fc08670013e' 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-44337d81-c198-4a78-bb64-b7751a381261' class='xr-section-summary-in' type='checkbox'  checked><label for='section-44337d81-c198-4a78-bb64-b7751a381261' 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-6ed69875-d0ff-4359-9cb5-f1a68a7c4902' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6ed69875-d0ff-4359-9cb5-f1a68a7c4902' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-798b7bb5-82c4-4567-8195-ef4b0d4d07e0' class='xr-var-data-in' type='checkbox'><label for='data-798b7bb5-82c4-4567-8195-ef4b0d4d07e0' 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-702db69a-db17-4f4d-99c6-c729079a86b9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-702db69a-db17-4f4d-99c6-c729079a86b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f359333-5f24-4462-a308-4c3f743ed0ec' class='xr-var-data-in' type='checkbox'><label for='data-2f359333-5f24-4462-a308-4c3f743ed0ec' 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([[[7.233793e-06, 7.954301e-06, ..., 1.065546e-04, 1.067560e-04],\n",
       "        [4.364233e-06, 1.209913e-05, ..., 8.871874e-05, 1.030033e-04],\n",
       "        ...,\n",
       "        [1.293476e-04, 1.199212e-04, ..., 2.385501e-04, 3.122941e-04],\n",
       "        [1.334700e-04, 2.467843e-04, ..., 2.877783e-04, 4.814459e-04]],\n",
       "\n",
       "       [[7.425116e-06, 6.810305e-06, ..., 1.477342e-05, 2.333068e-05],\n",
       "        [6.734258e-06, 5.776774e-06, ..., 1.696542e-05, 9.761841e-06],\n",
       "        ...,\n",
       "        [4.979145e-04, 6.358288e-04, ..., 2.834622e-04, 4.178414e-04],\n",
       "        [4.626163e-04, 7.919233e-04, ..., 3.625498e-04, 3.010014e-04]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[9.024598e-06, 1.042395e-05, ..., 5.980217e-05, 6.309975e-05],\n",
       "        [7.724128e-06, 8.755768e-06, ..., 6.141282e-05, 6.666772e-05],\n",
       "        ...,\n",
       "        [1.588596e-04, 1.502207e-04, ..., 1.388902e-04, 1.219929e-04],\n",
       "        [1.873819e-04, 2.610004e-04, ..., 1.696168e-04, 2.024294e-04]],\n",
       "\n",
       "       [[2.319058e-05, 2.176652e-05, ..., 1.523391e-05, 1.720650e-05],\n",
       "        [2.257082e-05, 2.172304e-05, ..., 1.540464e-05, 1.791543e-05],\n",
       "        ...,\n",
       "        [8.386163e-05, 5.593102e-05, ..., 6.990261e-05, 7.762669e-05],\n",
       "        [8.924141e-05, 1.515892e-04, ..., 1.661752e-04, 2.560732e-04]]],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-da26e92c-67ef-4dc2-ba76-9a0deb1961f9' class='xr-section-summary-in' type='checkbox'  ><label for='section-da26e92c-67ef-4dc2-ba76-9a0deb1961f9' class='xr-section-summary' >Attributes: <span>(165)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>history :</span></dt><dd>Thu Jul 07 17:05:10 2022: cdo remapnn,grid1.des noresm_pr_197001-200512.nc noresm1_remap.nc\n",
       "Mon Jun 27 15:36:42 2022: cdo mergetime pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_197001-198012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_198101-199012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_199101-200012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_200101-200512.nc noresm_pr_197001-200512.nc\n",
       "2018-03-21 03:01:05 : 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>2019-09-19T16:13:52Z</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>e18baf90-8c3e-11e9-a8fd-f04da273d2fb</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>NO_85</dd><dt><span>model_sst_data_source :</span></dt><dd>NO_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> 2005-12-31 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_name :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>ICTP-RegCM4-7</dd><dt><span>driving_experiment :</span></dt><dd>NCC-NorESM1-M, historical, r1i1p1</dd><dt><span>driving_model_id :</span></dt><dd>NCC-NorESM1-M</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 07 17:05:10 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_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    driving_experiment:                              NCC-NorESM1-M, historica...\n",
       "    driving_model_id:                                NCC-NorESM1-M\n",
       "    CDO:                                             Climate Data Operators v..."
      ]
     },
     "execution_count": 15,
     "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": 16,
   "id": "be94f5d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#jjas_data.x.values\n",
    "#jjas_data.lon.values\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "18269e45",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  --xr-background-color-row-even: #111111;\n",
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       "\n",
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       "  display: block !important;\n",
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       "  max-width: 700px;\n",
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       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
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       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
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       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
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       "\n",
       ".xr-obj-type {\n",
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       "\n",
       ".xr-sections {\n",
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       "  display: grid;\n",
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       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
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       "  font-size: 11px;\n",
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       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
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       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
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       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
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       "\n",
       ".xr-section-summary,\n",
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       "  padding-top: 4px;\n",
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       "\n",
       ".xr-section-details {\n",
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       "  display: contents;\n",
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       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
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       "\n",
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       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
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       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
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       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
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       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
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       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
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       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
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       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\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",
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       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
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       "\n",
       ".xr-var-name {\n",
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       "\n",
       ".xr-var-dims {\n",
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       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
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       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  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",
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       "\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([[2.8762943e-05, 2.8464339e-05, 3.0794246e-05, ..., 6.9784284e-05,\n",
       "        7.6980410e-05, 9.4289404e-05],\n",
       "       [2.7636936e-05, 2.8457882e-05, 2.9088866e-05, ..., 7.3735784e-05,\n",
       "        8.7867535e-05, 9.8345205e-05],\n",
       "       [2.6627135e-05, 2.7850470e-05, 2.8412051e-05, ..., 7.7518453e-05,\n",
       "        9.9341531e-05, 1.1133800e-04],\n",
       "       ...,\n",
       "       [1.7365685e-04, 1.9437198e-04, 2.1445446e-04, ..., 2.1362111e-04,\n",
       "        2.4107521e-04, 1.9385196e-04],\n",
       "       [1.9834371e-04, 2.1861590e-04, 2.7803390e-04, ..., 1.8474228e-04,\n",
       "        2.4710110e-04, 2.6863860e-04],\n",
       "       [2.0032108e-04, 3.1719045e-04, 5.3115201e-04, ..., 1.7659400e-04,\n",
       "        2.5860599e-04, 3.1809535e-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-311b1d0b-9498-4f51-b69c-b308060c6414' class='xr-array-in' type='checkbox' checked><label for='section-311b1d0b-9498-4f51-b69c-b308060c6414' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2.876e-05 2.846e-05 3.079e-05 ... 0.0001766 0.0002586 0.0003181</span></div><div class='xr-array-data'><pre>array([[2.8762943e-05, 2.8464339e-05, 3.0794246e-05, ..., 6.9784284e-05,\n",
       "        7.6980410e-05, 9.4289404e-05],\n",
       "       [2.7636936e-05, 2.8457882e-05, 2.9088866e-05, ..., 7.3735784e-05,\n",
       "        8.7867535e-05, 9.8345205e-05],\n",
       "       [2.6627135e-05, 2.7850470e-05, 2.8412051e-05, ..., 7.7518453e-05,\n",
       "        9.9341531e-05, 1.1133800e-04],\n",
       "       ...,\n",
       "       [1.7365685e-04, 1.9437198e-04, 2.1445446e-04, ..., 2.1362111e-04,\n",
       "        2.4107521e-04, 1.9385196e-04],\n",
       "       [1.9834371e-04, 2.1861590e-04, 2.7803390e-04, ..., 1.8474228e-04,\n",
       "        2.4710110e-04, 2.6863860e-04],\n",
       "       [2.0032108e-04, 3.1719045e-04, 5.3115201e-04, ..., 1.7659400e-04,\n",
       "        2.5860599e-04, 3.1809535e-04]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-5653c9ba-5c2c-461e-81ff-59ea9f98d669' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5653c9ba-5c2c-461e-81ff-59ea9f98d669' 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-44a975ba-b402-4664-be22-f38a4b48cb18' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-44a975ba-b402-4664-be22-f38a4b48cb18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d7ecd1c-8678-4634-8b99-e1534ee81437' class='xr-var-data-in' type='checkbox'><label for='data-6d7ecd1c-8678-4634-8b99-e1534ee81437' 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-708b7f87-a770-41ae-aad8-3eca4aa992d9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-708b7f87-a770-41ae-aad8-3eca4aa992d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e17bbed7-0c7b-42ab-b125-6f18e6480df4' class='xr-var-data-in' type='checkbox'><label for='data-e17bbed7-0c7b-42ab-b125-6f18e6480df4' 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-1021b899-c402-473a-8d78-07a238056658' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1021b899-c402-473a-8d78-07a238056658' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'pr' (lat: 40, lon: 32)>\n",
       "array([[2.8762943e-05, 2.8464339e-05, 3.0794246e-05, ..., 6.9784284e-05,\n",
       "        7.6980410e-05, 9.4289404e-05],\n",
       "       [2.7636936e-05, 2.8457882e-05, 2.9088866e-05, ..., 7.3735784e-05,\n",
       "        8.7867535e-05, 9.8345205e-05],\n",
       "       [2.6627135e-05, 2.7850470e-05, 2.8412051e-05, ..., 7.7518453e-05,\n",
       "        9.9341531e-05, 1.1133800e-04],\n",
       "       ...,\n",
       "       [1.7365685e-04, 1.9437198e-04, 2.1445446e-04, ..., 2.1362111e-04,\n",
       "        2.4107521e-04, 1.9385196e-04],\n",
       "       [1.9834371e-04, 2.1861590e-04, 2.7803390e-04, ..., 1.8474228e-04,\n",
       "        2.4710110e-04, 2.6863860e-04],\n",
       "       [2.0032108e-04, 3.1719045e-04, 5.3115201e-04, ..., 1.7659400e-04,\n",
       "        2.5860599e-04, 3.1809535e-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": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#getting the mean for JJAS data\n",
    "jjas_mean = jjas_data.pr.mean('time')\n",
    " \n",
    "jjas_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "6f88bd72",
   "metadata": {},
   "outputs": [
    {
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       "\n",
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       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
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       "  display: inline-block;\n",
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       "  padding-right: 10px;\n",
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       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\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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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (lat: 40, lon: 32)&gt;\n",
       "array([[ 2.48511825,  2.45931891,  2.66062289, ...,  6.02936216,\n",
       "         6.65110743,  8.1466045 ],\n",
       "       [ 2.38783123,  2.45876099,  2.51327799, ...,  6.37077175,\n",
       "         7.59175499,  8.49702568],\n",
       "       [ 2.30058442,  2.40628064,  2.45480117, ...,  6.6975943 ,\n",
       "         8.58310824,  9.61960307],\n",
       "       ...,\n",
       "       [15.00395201, 16.79373938, 18.528865  , ..., 18.45686403,\n",
       "        20.82889779, 16.74880902],\n",
       "       [17.13689659, 18.88841344, 24.02212881, ..., 15.96173323,\n",
       "        21.34953467, 23.21037501],\n",
       "       [17.30774157, 27.40525519, 45.89153342, ..., 15.25772125,\n",
       "        22.34355714, 27.48343823]])\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-47a95df8-d49a-46a7-aea2-3a30c013a017' class='xr-array-in' type='checkbox' checked><label for='section-47a95df8-d49a-46a7-aea2-3a30c013a017' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2.485 2.459 2.661 2.606 2.577 2.572 ... 20.98 17.26 15.26 22.34 27.48</span></div><div class='xr-array-data'><pre>array([[ 2.48511825,  2.45931891,  2.66062289, ...,  6.02936216,\n",
       "         6.65110743,  8.1466045 ],\n",
       "       [ 2.38783123,  2.45876099,  2.51327799, ...,  6.37077175,\n",
       "         7.59175499,  8.49702568],\n",
       "       [ 2.30058442,  2.40628064,  2.45480117, ...,  6.6975943 ,\n",
       "         8.58310824,  9.61960307],\n",
       "       ...,\n",
       "       [15.00395201, 16.79373938, 18.528865  , ..., 18.45686403,\n",
       "        20.82889779, 16.74880902],\n",
       "       [17.13689659, 18.88841344, 24.02212881, ..., 15.96173323,\n",
       "        21.34953467, 23.21037501],\n",
       "       [17.30774157, 27.40525519, 45.89153342, ..., 15.25772125,\n",
       "        22.34355714, 27.48343823]])</pre></div></div></li><li class='xr-section-item'><input id='section-d2c92a4e-3fb3-46bc-ac52-09475c00600d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d2c92a4e-3fb3-46bc-ac52-09475c00600d' 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-6c0986d6-7a82-4c11-9981-47973b307793' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c0986d6-7a82-4c11-9981-47973b307793' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30f2f7fe-0dcd-4581-8be1-2fdd45f5af06' class='xr-var-data-in' type='checkbox'><label for='data-30f2f7fe-0dcd-4581-8be1-2fdd45f5af06' 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-314fa4d6-d015-4d64-b4fd-04f76c17028a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-314fa4d6-d015-4d64-b4fd-04f76c17028a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f5cb533-83d5-4a5c-972e-4200ec92f4a5' class='xr-var-data-in' type='checkbox'><label for='data-9f5cb533-83d5-4a5c-972e-4200ec92f4a5' 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-38f868bf-f16c-4f4c-ad8c-7940e112f6bf' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-38f868bf-f16c-4f4c-ad8c-7940e112f6bf' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'pr' (lat: 40, lon: 32)>\n",
       "array([[ 2.48511825,  2.45931891,  2.66062289, ...,  6.02936216,\n",
       "         6.65110743,  8.1466045 ],\n",
       "       [ 2.38783123,  2.45876099,  2.51327799, ...,  6.37077175,\n",
       "         7.59175499,  8.49702568],\n",
       "       [ 2.30058442,  2.40628064,  2.45480117, ...,  6.6975943 ,\n",
       "         8.58310824,  9.61960307],\n",
       "       ...,\n",
       "       [15.00395201, 16.79373938, 18.528865  , ..., 18.45686403,\n",
       "        20.82889779, 16.74880902],\n",
       "       [17.13689659, 18.88841344, 24.02212881, ..., 15.96173323,\n",
       "        21.34953467, 23.21037501],\n",
       "       [17.30774157, 27.40525519, 45.89153342, ..., 15.25772125,\n",
       "        22.34355714, 27.48343823]])\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": [
    "noresm = jjas_mean*86400\n",
    "noresm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "6c5c5811",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
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       "\n",
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       "  display: block;\n",
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       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
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       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
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       "\n",
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       "  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([[ -6.25666489,  -6.47596284,  -6.35304231, ..., -16.23153452,\n",
       "        -14.4147495 ,  -9.61620907],\n",
       "       [ -5.98553798,  -6.1351807 ,  -6.40782835, ..., -13.74404683,\n",
       "        -12.91933815,  -9.89061051],\n",
       "       [ -6.27357329,  -6.73910129,  -6.6715416 , ..., -11.98175941,\n",
       "         -8.81729764,  -7.90361699],\n",
       "       ...,\n",
       "       [  7.64161681,   9.91877085,  12.0666367 , ...,  10.90277258,\n",
       "         13.00363524,   7.73799245],\n",
       "       [  9.69226597,  12.11759664,  17.92410873, ...,   8.9129237 ,\n",
       "         14.24630276,  15.60964316],\n",
       "       [ 10.68100397,  21.39732921,  40.74539809, ...,   7.92829449,\n",
       "         14.60056379,  20.07824777]])\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-6bf129c2-4e9a-44cd-bb77-b0ca30f7aea5' class='xr-array-in' type='checkbox' checked><label for='section-6bf129c2-4e9a-44cd-bb77-b0ca30f7aea5' 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>-6.257 -6.476 -6.353 -6.802 -7.173 ... 14.92 10.35 7.928 14.6 20.08</span></div><div class='xr-array-data'><pre>array([[ -6.25666489,  -6.47596284,  -6.35304231, ..., -16.23153452,\n",
       "        -14.4147495 ,  -9.61620907],\n",
       "       [ -5.98553798,  -6.1351807 ,  -6.40782835, ..., -13.74404683,\n",
       "        -12.91933815,  -9.89061051],\n",
       "       [ -6.27357329,  -6.73910129,  -6.6715416 , ..., -11.98175941,\n",
       "         -8.81729764,  -7.90361699],\n",
       "       ...,\n",
       "       [  7.64161681,   9.91877085,  12.0666367 , ...,  10.90277258,\n",
       "         13.00363524,   7.73799245],\n",
       "       [  9.69226597,  12.11759664,  17.92410873, ...,   8.9129237 ,\n",
       "         14.24630276,  15.60964316],\n",
       "       [ 10.68100397,  21.39732921,  40.74539809, ...,   7.92829449,\n",
       "         14.60056379,  20.07824777]])</pre></div></div></li><li class='xr-section-item'><input id='section-e1289a92-9a00-434e-aa7f-716add9ff4aa' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e1289a92-9a00-434e-aa7f-716add9ff4aa' 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-1412d8c2-0e2e-490a-82d2-07d3d2d2b447' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1412d8c2-0e2e-490a-82d2-07d3d2d2b447' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2b3a60d-8264-4119-b58c-e3b7359a3a20' class='xr-var-data-in' type='checkbox'><label for='data-e2b3a60d-8264-4119-b58c-e3b7359a3a20' 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-5dfb3f6c-5e7a-4654-b312-9ec33d482ba9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5dfb3f6c-5e7a-4654-b312-9ec33d482ba9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e592412-97f8-4363-ba34-a6462d98840a' class='xr-var-data-in' type='checkbox'><label for='data-2e592412-97f8-4363-ba34-a6462d98840a' 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-a1462229-abb4-4076-9608-6278c15c87cd' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a1462229-abb4-4076-9608-6278c15c87cd' 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([[ -6.25666489,  -6.47596284,  -6.35304231, ..., -16.23153452,\n",
       "        -14.4147495 ,  -9.61620907],\n",
       "       [ -5.98553798,  -6.1351807 ,  -6.40782835, ..., -13.74404683,\n",
       "        -12.91933815,  -9.89061051],\n",
       "       [ -6.27357329,  -6.73910129,  -6.6715416 , ..., -11.98175941,\n",
       "         -8.81729764,  -7.90361699],\n",
       "       ...,\n",
       "       [  7.64161681,   9.91877085,  12.0666367 , ...,  10.90277258,\n",
       "         13.00363524,   7.73799245],\n",
       "       [  9.69226597,  12.11759664,  17.92410873, ...,   8.9129237 ,\n",
       "         14.24630276,  15.60964316],\n",
       "       [ 10.68100397,  21.39732921,  40.74539809, ...,   7.92829449,\n",
       "         14.60056379,  20.07824777]])\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 = noresm - trmm\n",
    "bias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "445388ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       ".xr-attrs dt,\n",
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       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
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       "  padding-right: 10px;\n",
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       "\n",
       ".xr-attrs dd {\n",
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       "  white-space: pre-wrap;\n",
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       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
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       "  fill: currentColor;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (lat: 40, lon: 32)&gt;\n",
       "array([[-71.57195262, -72.47631378, -70.48234174, ..., -72.91500766,\n",
       "        -68.42707395, -54.1367449 ],\n",
       "       [-71.48302947, -71.38960117, -71.82773195, ..., -68.32796814,\n",
       "        -62.98707759, -53.78946161],\n",
       "       [-73.16839161, -73.68857137, -73.10202748, ..., -64.14440024,\n",
       "        -50.67294234, -45.10367935],\n",
       "       ...,\n",
       "       [103.7933834 , 144.27369095, 186.72563307, ..., 144.32936965,\n",
       "        166.17506648,  85.87448635],\n",
       "       [130.19136148, 178.96801804, 293.93325216, ..., 126.44580143,\n",
       "        200.56085669, 205.37026526],\n",
       "       [161.18042733, 356.15167785, 791.76693722, ..., 108.17073071,\n",
       "        188.56484977, 271.13749274]])\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-fd6b2d7a-ac02-4071-9e21-37f1230bfb76' class='xr-array-in' type='checkbox' checked><label for='section-fd6b2d7a-ac02-4071-9e21-37f1230bfb76' 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>-71.57 -72.48 -70.48 -72.3 -73.57 ... 246.3 149.7 108.2 188.6 271.1</span></div><div class='xr-array-data'><pre>array([[-71.57195262, -72.47631378, -70.48234174, ..., -72.91500766,\n",
       "        -68.42707395, -54.1367449 ],\n",
       "       [-71.48302947, -71.38960117, -71.82773195, ..., -68.32796814,\n",
       "        -62.98707759, -53.78946161],\n",
       "       [-73.16839161, -73.68857137, -73.10202748, ..., -64.14440024,\n",
       "        -50.67294234, -45.10367935],\n",
       "       ...,\n",
       "       [103.7933834 , 144.27369095, 186.72563307, ..., 144.32936965,\n",
       "        166.17506648,  85.87448635],\n",
       "       [130.19136148, 178.96801804, 293.93325216, ..., 126.44580143,\n",
       "        200.56085669, 205.37026526],\n",
       "       [161.18042733, 356.15167785, 791.76693722, ..., 108.17073071,\n",
       "        188.56484977, 271.13749274]])</pre></div></div></li><li class='xr-section-item'><input id='section-45fd5ef8-5733-474a-b951-c1e3c7bf7701' class='xr-section-summary-in' type='checkbox'  checked><label for='section-45fd5ef8-5733-474a-b951-c1e3c7bf7701' 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-07dce613-10bd-4702-8aff-e123db5f446f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07dce613-10bd-4702-8aff-e123db5f446f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83a945e5-6632-4c18-85b7-0e0f314de7a6' class='xr-var-data-in' type='checkbox'><label for='data-83a945e5-6632-4c18-85b7-0e0f314de7a6' 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-8b184cbe-91ed-4308-aad5-69cbbb522f15' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b184cbe-91ed-4308-aad5-69cbbb522f15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b928b5c8-f62f-4ec0-a075-21eaa72dc25c' class='xr-var-data-in' type='checkbox'><label for='data-b928b5c8-f62f-4ec0-a075-21eaa72dc25c' 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-bb06ca57-9530-4abb-b906-94d7ef489214' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bb06ca57-9530-4abb-b906-94d7ef489214' 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([[-71.57195262, -72.47631378, -70.48234174, ..., -72.91500766,\n",
       "        -68.42707395, -54.1367449 ],\n",
       "       [-71.48302947, -71.38960117, -71.82773195, ..., -68.32796814,\n",
       "        -62.98707759, -53.78946161],\n",
       "       [-73.16839161, -73.68857137, -73.10202748, ..., -64.14440024,\n",
       "        -50.67294234, -45.10367935],\n",
       "       ...,\n",
       "       [103.7933834 , 144.27369095, 186.72563307, ..., 144.32936965,\n",
       "        166.17506648,  85.87448635],\n",
       "       [130.19136148, 178.96801804, 293.93325216, ..., 126.44580143,\n",
       "        200.56085669, 205.37026526],\n",
       "       [161.18042733, 356.15167785, 791.76693722, ..., 108.17073071,\n",
       "        188.56484977, 271.13749274]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bias_percentage = ((noresm - trmm)/trmm)*100\n",
    "bias_percentage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "08ba09cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x684 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting annual_pr_mean\n",
    "\n",
    "#plotting with cartopy\n",
    "import cartopy.feature as cfeature\n",
    "\n",
    "plt.rcParams['font.size'] = '16'\n",
    "\n",
    "\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 NORESM-TRMM)' )\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/Seasonal Bias(noresm-trmm).png\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "9003db92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x684 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting bias percentage \n",
    "\n",
    "#plotting with cartopy\n",
    "import cartopy.feature as cfeature\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize=(12,9.5))\n",
    "\n",
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "ax.set_extent([88,93,20,27])\n",
    "\n",
    "\n",
    "m1 = ax.contourf(bias_percentage['lon'], bias_percentage['lat'],bias_percentage[:,:],\n",
    "                 levels=np.arange(-150,150+25,25), transform = ccrs.PlateCarree(),cmap='BrBG',extend='both')\n",
    "\n",
    " \n",
    "# Define the xticks for longitude\n",
    "ax.set_xticks(np.arange(87,94,1), crs=ccrs.PlateCarree())\n",
    "lon_formatter = cticker.LongitudeFormatter()\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "\n",
    "# Define the yticks for latitude\n",
    "ax.set_yticks(np.arange(20,28,1), crs=ccrs.PlateCarree())\n",
    "lat_formatter = cticker.LatitudeFormatter()\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "\n",
    "\n",
    "plt.colorbar(m1,ticks=np.arange(-150,150+25,25),orientation = 'horizontal',shrink=0.5, fraction = 0.04 , label = 'percentage')\n",
    "ax.coastlines(linewidth=3)\n",
    "ax.add_feature(cfeature.BORDERS,linewidth=3)\n",
    "\n",
    "\n",
    "plt.title('Seasonal Bias-Percentage(RegCM NORESM-TRMM)',fontsize=17)\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/Seasonal Bias_percentage(noresm-trmm).png\")\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "220503a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Colormap CET_D1A is not recognized. Possible values are: Accent, Accent_r, Blues, Blues_r, \\nBrBG, BrBG_r, BuGn, BuGn_r, BuPu, BuPu_r, CMRmap, CMRmap_r, Dark2, Dark2_r, GnBu, GnBu_r, Greens,\\nGreens_r, Greys, Greys_r, OrRd, OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, \\nPastel2_r, PiYG, PiYG_r, PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Purples_r, RdBu, RdBu_r, RdGy,\\nRdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, \\nSpectral_r, Wistia, Wistia_r, YlGn, YlGnBu, YlGnBu_r, YlGn_r, YlOrBr, YlOrBr_r, YlOrRd, YlOrRd_r, afmhot, afmhot_r, autumn,\\nautumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, cividis, cividis_r, cool, cool_r, coolwarm, coolwarm_r, \\ncopper, copper_r, cubehelix, cubehelix_r, flag, flag_r, gist_earth, gist_earth_r, gist_gray, gist_gray_r, gist_heat,\\ngist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r,\\ngnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r, hsv, hsv_r, inferno, inferno_r, jet, jet_r, magma,\\nmagma_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, \\nseismic, seismic_r, spring, spring_r, summer, summer_r, tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, \\nter'"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#cma colors\n",
    "'''Colormap CET_D1A is not recognized. Possible values are: Accent, Accent_r, Blues, Blues_r, \n",
    "BrBG, BrBG_r, BuGn, BuGn_r, BuPu, BuPu_r, CMRmap, CMRmap_r, Dark2, Dark2_r, GnBu, GnBu_r, Greens,\n",
    "Greens_r, Greys, Greys_r, OrRd, OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, \n",
    "Pastel2_r, PiYG, PiYG_r, PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Purples_r, RdBu, RdBu_r, RdGy,\n",
    "RdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, \n",
    "Spectral_r, Wistia, Wistia_r, YlGn, YlGnBu, YlGnBu_r, YlGn_r, YlOrBr, YlOrBr_r, YlOrRd, YlOrRd_r, afmhot, afmhot_r, autumn,\n",
    "autumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, cividis, cividis_r, cool, cool_r, coolwarm, coolwarm_r, \n",
    "copper, copper_r, cubehelix, cubehelix_r, flag, flag_r, gist_earth, gist_earth_r, gist_gray, gist_gray_r, gist_heat,\n",
    "gist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r,\n",
    "gnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r, hsv, hsv_r, inferno, inferno_r, jet, jet_r, magma,\n",
    "magma_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, \n",
    "seismic, seismic_r, spring, spring_r, summer, summer_r, tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, \n",
    "ter'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "87f4ea28",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "20e38f40",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "21be7cc5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f5489f24",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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