Seasonal Bias ensemble average(RegCM-CRU).ipynb

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    "#writing some conda package or module\n",
    "#!pip install netCDF4\n",
    "%matplotlib inline\n",
    "import warnings\n",
    "from netCDF4 import Dataset\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "#!pip install cartopy\n",
    "import cartopy.feature as cfeature\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.mpl.ticker as cticker\n",
    "from cartopy.util import add_cyclic_point"
   ]
  },
  {
   "cell_type": "code",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (lon: 720, lat: 360, time: 1452)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 -179.8 -179.2 -178.8 -178.2 ... 178.8 179.2 179.8\n",
       "  * lat      (lat) float32 -89.75 -89.25 -88.75 -88.25 ... 88.75 89.25 89.75\n",
       "  * time     (time) datetime64[ns] 1901-01-16 1901-02-15 ... 2021-12-16\n",
       "Data variables:\n",
       "    pre      (time, lat, lon) float32 ...\n",
       "    stn      (time, lat, lon) float64 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-bb25c84d-532e-407a-bc46-b23881db5b88' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bb25c84d-532e-407a-bc46-b23881db5b88' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 720</li><li><span class='xr-has-index'>lat</span>: 360</li><li><span class='xr-has-index'>time</span>: 1452</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e8741785-53da-49e2-b4ee-a88b1cc0df6f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e8741785-53da-49e2-b4ee-a88b1cc0df6f' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-179.8 -179.2 ... 179.2 179.8</div><input id='attrs-16c518f8-379f-4615-bb1f-35b3c06b96cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-16c518f8-379f-4615-bb1f-35b3c06b96cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e28039bd-08e7-48e4-9e4b-7288c588b853' class='xr-var-data-in' type='checkbox'><label for='data-e28039bd-08e7-48e4-9e4b-7288c588b853' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-179.75, -179.25, -178.75, ...,  178.75,  179.25,  179.75],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-89.75 -89.25 ... 89.25 89.75</div><input id='attrs-048ac724-ee09-4cf8-8202-1aa7c0c044f1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-048ac724-ee09-4cf8-8202-1aa7c0c044f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0fd2af35-7092-40ab-8643-3e26e832d672' class='xr-var-data-in' type='checkbox'><label for='data-0fd2af35-7092-40ab-8643-3e26e832d672' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-89.75, -89.25, -88.75, ...,  88.75,  89.25,  89.75], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1901-01-16 ... 2021-12-16</div><input id='attrs-bae1526b-d98c-4a9f-bdbe-c1e58bdeded7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bae1526b-d98c-4a9f-bdbe-c1e58bdeded7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-49cc22a1-7338-4c09-9ab2-c9d275c27e60' class='xr-var-data-in' type='checkbox'><label for='data-49cc22a1-7338-4c09-9ab2-c9d275c27e60' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1901-01-16T00:00:00.000000000&#x27;, &#x27;1901-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;1901-03-16T00:00:00.000000000&#x27;, ..., &#x27;2021-10-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-11-16T00:00:00.000000000&#x27;, &#x27;2021-12-16T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e1f5eb87-1079-4d3f-9900-7d86875c5960' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e1f5eb87-1079-4d3f-9900-7d86875c5960' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>pre</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e5f0aed7-1366-4a07-be7f-94849678e497' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5f0aed7-1366-4a07-be7f-94849678e497' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04c0722f-9f5c-4deb-8ea2-8fb2548e41a1' class='xr-var-data-in' type='checkbox'><label for='data-04c0722f-9f5c-4deb-8ea2-8fb2548e41a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>precipitation</dd><dt><span>units :</span></dt><dd>mm/month</dd><dt><span>correlation_decay_distance :</span></dt><dd>450.0</dd></dl></div><div class='xr-var-data'><pre>[376358400 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stn</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ef4ad1f3-701d-4cba-9635-9d26e2483df6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ef4ad1f3-701d-4cba-9635-9d26e2483df6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a87e431-ab0f-408f-8b7a-5d89556cd794' class='xr-var-data-in' type='checkbox'><label for='data-7a87e431-ab0f-408f-8b7a-5d89556cd794' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>number of stations contributing to each datum</dd></dl></div><div class='xr-var-data'><pre>[376358400 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-07768803-c852-4def-a47d-a50df4d8a451' class='xr-section-summary-in' type='checkbox'  checked><label for='section-07768803-c852-4def-a47d-a50df4d8a451' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>title :</span></dt><dd>CRU TS4.06 Precipitation</dd><dt><span>institution :</span></dt><dd>Data held at British Atmospheric Data Centre, RAL, UK.</dd><dt><span>source :</span></dt><dd>Run ID = 2205201912. Data generated from:pre.2204291209.dtb</dd><dt><span>history :</span></dt><dd>Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegridsauto.for called by update.for</dd><dt><span>references :</span></dt><dd>Information on the data is available at http://badc.nerc.ac.uk/data/cru/</dd><dt><span>comment :</span></dt><dd>Access to these data is available to any registered CEDA user.</dd><dt><span>contact :</span></dt><dd>support@ceda.ac.uk</dd></dl></div></li></ul></div></div>"
      ],
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       "<xarray.Dataset>\n",
       "Dimensions:  (lon: 720, lat: 360, time: 1452)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 -179.8 -179.2 -178.8 -178.2 ... 178.8 179.2 179.8\n",
       "  * lat      (lat) float32 -89.75 -89.25 -88.75 -88.25 ... 88.75 89.25 89.75\n",
       "  * time     (time) datetime64[ns] 1901-01-16 1901-02-15 ... 2021-12-16\n",
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       "Attributes:\n",
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       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
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     "execution_count": 2,
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   "source": [
    "data = xr.open_dataset('/home/mkibria/Academic/pr_of_thesis/observation/cru/cru_ts4.06.1901.2021.pre.dat.nc')\n",
    " \n",
    "\n",
    "data"
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       "Dimensions:  (lon: 720, lat: 360, time: 299)\n",
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       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
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       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5cdad283-d583-4afa-a241-a2949a933973' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5cdad283-d583-4afa-a241-a2949a933973' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 720</li><li><span class='xr-has-index'>lat</span>: 360</li><li><span class='xr-has-index'>time</span>: 299</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-04d6cecf-0c49-4313-8dee-fecabe78d20e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-04d6cecf-0c49-4313-8dee-fecabe78d20e' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-179.8 -179.2 ... 179.2 179.8</div><input id='attrs-3932e479-1c72-41d9-9383-8ced4818259a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3932e479-1c72-41d9-9383-8ced4818259a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c8b4e16-64ae-4229-9550-86cd6629571a' class='xr-var-data-in' type='checkbox'><label for='data-0c8b4e16-64ae-4229-9550-86cd6629571a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-179.75, -179.25, -178.75, ...,  178.75,  179.25,  179.75],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-89.75 -89.25 ... 89.25 89.75</div><input id='attrs-3a8558b6-f2ad-42de-a735-9849c31de8d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a8558b6-f2ad-42de-a735-9849c31de8d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c677d048-1ba8-41a7-b7eb-9d52af25f8b5' class='xr-var-data-in' type='checkbox'><label for='data-c677d048-1ba8-41a7-b7eb-9d52af25f8b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-89.75, -89.25, -88.75, ...,  88.75,  89.25,  89.75], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-02-15 ... 2005-12-16</div><input id='attrs-bb3e4f27-650b-4320-88b4-e0e57164c5f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb3e4f27-650b-4320-88b4-e0e57164c5f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3621fe18-75f5-4e50-8fe0-f9bc1f355ada' class='xr-var-data-in' type='checkbox'><label for='data-3621fe18-75f5-4e50-8fe0-f9bc1f355ada' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-02-15T00:00:00.000000000&#x27;, &#x27;1981-03-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-04-16T00:00:00.000000000&#x27;, ..., &#x27;2005-10-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-11-16T00:00:00.000000000&#x27;, &#x27;2005-12-16T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f345431e-a674-45e4-8176-15f34c3dd2f8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f345431e-a674-45e4-8176-15f34c3dd2f8' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>pre</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-25178403-886f-40ad-9fdf-b611326a1de7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25178403-886f-40ad-9fdf-b611326a1de7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19afb1e0-328c-4632-962f-b7a10947b882' class='xr-var-data-in' type='checkbox'><label for='data-19afb1e0-328c-4632-962f-b7a10947b882' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>precipitation</dd><dt><span>units :</span></dt><dd>mm/month</dd><dt><span>correlation_decay_distance :</span></dt><dd>450.0</dd></dl></div><div class='xr-var-data'><pre>[77500800 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stn</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b7a8008f-da1b-43e6-86b9-b022f9a2dcd9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b7a8008f-da1b-43e6-86b9-b022f9a2dcd9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c214d5b2-c2cb-45ff-88be-b489e47fa96d' class='xr-var-data-in' type='checkbox'><label for='data-c214d5b2-c2cb-45ff-88be-b489e47fa96d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>number of stations contributing to each datum</dd></dl></div><div class='xr-var-data'><pre>[77500800 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-eb39ae9f-423a-4058-b057-bb3efc0db747' class='xr-section-summary-in' type='checkbox'  checked><label for='section-eb39ae9f-423a-4058-b057-bb3efc0db747' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>title :</span></dt><dd>CRU TS4.06 Precipitation</dd><dt><span>institution :</span></dt><dd>Data held at British Atmospheric Data Centre, RAL, UK.</dd><dt><span>source :</span></dt><dd>Run ID = 2205201912. Data generated from:pre.2204291209.dtb</dd><dt><span>history :</span></dt><dd>Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegridsauto.for called by update.for</dd><dt><span>references :</span></dt><dd>Information on the data is available at http://badc.nerc.ac.uk/data/cru/</dd><dt><span>comment :</span></dt><dd>Access to these data is available to any registered CEDA user.</dd><dt><span>contact :</span></dt><dd>support@ceda.ac.uk</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lon: 720, lat: 360, time: 299)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 -179.8 -179.2 -178.8 -178.2 ... 178.8 179.2 179.8\n",
       "  * lat      (lat) float32 -89.75 -89.25 -88.75 -88.25 ... 88.75 89.25 89.75\n",
       "  * time     (time) datetime64[ns] 1981-02-15 1981-03-16 ... 2005-12-16\n",
       "Data variables:\n",
       "    pre      (time, lat, lon) float32 ...\n",
       "    stn      (time, lat, lon) float64 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#to select the year from 1980 to 2015\n",
    "data = data.sel(time=slice('1981-01-16T12:00:00.000000000','2005-12-16T00:00:00.000000000'))\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "10070b93",
   "metadata": {},
   "outputs": [
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (lon: 720, lat: 360, time: 100)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 -179.8 -179.2 -178.8 -178.2 ... 178.8 179.2 179.8\n",
       "  * lat      (lat) float32 -89.75 -89.25 -88.75 -88.25 ... 88.75 89.25 89.75\n",
       "  * time     (time) datetime64[ns] 1981-06-16 1981-07-16 ... 2005-09-16\n",
       "Data variables:\n",
       "    pre      (time, lat, lon) float32 ...\n",
       "    stn      (time, lat, lon) float64 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e8a1d92c-73ef-494d-b32b-0ba22f17ea36' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e8a1d92c-73ef-494d-b32b-0ba22f17ea36' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 720</li><li><span class='xr-has-index'>lat</span>: 360</li><li><span class='xr-has-index'>time</span>: 100</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f2204119-660c-43d3-bd96-b5dabffad26c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f2204119-660c-43d3-bd96-b5dabffad26c' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-179.8 -179.2 ... 179.2 179.8</div><input id='attrs-67979cf0-fe9d-445e-8b0e-2bd22a855af6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-67979cf0-fe9d-445e-8b0e-2bd22a855af6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd05fcba-bfea-4c6d-aa58-b565dab5d6af' class='xr-var-data-in' type='checkbox'><label for='data-dd05fcba-bfea-4c6d-aa58-b565dab5d6af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([-179.75, -179.25, -178.75, ...,  178.75,  179.25,  179.75],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-89.75 -89.25 ... 89.25 89.75</div><input id='attrs-00788622-5d4e-4b5b-bc6d-609497280b02' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-00788622-5d4e-4b5b-bc6d-609497280b02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd14048d-32a1-457e-8d42-a669a456921c' class='xr-var-data-in' type='checkbox'><label for='data-fd14048d-32a1-457e-8d42-a669a456921c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-89.75, -89.25, -88.75, ...,  88.75,  89.25,  89.75], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-06-16 ... 2005-09-16</div><input id='attrs-38287370-54ce-462c-9036-9a508688564e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-38287370-54ce-462c-9036-9a508688564e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d927ed5-9740-4d46-9974-979ac02290b0' class='xr-var-data-in' type='checkbox'><label for='data-3d927ed5-9740-4d46-9974-979ac02290b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-06-16T00:00:00.000000000&#x27;, &#x27;1981-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-08-16T00:00:00.000000000&#x27;, &#x27;1981-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-06-16T00:00:00.000000000&#x27;, &#x27;1982-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-08-16T00:00:00.000000000&#x27;, &#x27;1982-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-06-16T00:00:00.000000000&#x27;, &#x27;1983-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-08-16T00:00:00.000000000&#x27;, &#x27;1983-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-06-16T00:00:00.000000000&#x27;, &#x27;1984-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-08-16T00:00:00.000000000&#x27;, &#x27;1984-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-06-16T00:00:00.000000000&#x27;, &#x27;1985-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-08-16T00:00:00.000000000&#x27;, &#x27;1985-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-06-16T00:00:00.000000000&#x27;, &#x27;1986-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-08-16T00:00:00.000000000&#x27;, &#x27;1986-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-06-16T00:00:00.000000000&#x27;, &#x27;1987-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-08-16T00:00:00.000000000&#x27;, &#x27;1987-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-06-16T00:00:00.000000000&#x27;, &#x27;1988-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-08-16T00:00:00.000000000&#x27;, &#x27;1988-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-06-16T00:00:00.000000000&#x27;, &#x27;1989-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-08-16T00:00:00.000000000&#x27;, &#x27;1989-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-06-16T00:00:00.000000000&#x27;, &#x27;1990-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-08-16T00:00:00.000000000&#x27;, &#x27;1990-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-06-16T00:00:00.000000000&#x27;, &#x27;1991-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-08-16T00:00:00.000000000&#x27;, &#x27;1991-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-06-16T00:00:00.000000000&#x27;, &#x27;1992-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-08-16T00:00:00.000000000&#x27;, &#x27;1992-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-06-16T00:00:00.000000000&#x27;, &#x27;1993-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-08-16T00:00:00.000000000&#x27;, &#x27;1993-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-06-16T00:00:00.000000000&#x27;, &#x27;1994-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-08-16T00:00:00.000000000&#x27;, &#x27;1994-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-06-16T00:00:00.000000000&#x27;, &#x27;1995-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-08-16T00:00:00.000000000&#x27;, &#x27;1995-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-06-16T00:00:00.000000000&#x27;, &#x27;1996-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-08-16T00:00:00.000000000&#x27;, &#x27;1996-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-06-16T00:00:00.000000000&#x27;, &#x27;1997-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-08-16T00:00:00.000000000&#x27;, &#x27;1997-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-06-16T00:00:00.000000000&#x27;, &#x27;1998-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-08-16T00:00:00.000000000&#x27;, &#x27;1998-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-06-16T00:00:00.000000000&#x27;, &#x27;1999-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-08-16T00:00:00.000000000&#x27;, &#x27;1999-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-16T00:00:00.000000000&#x27;, &#x27;2000-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-08-16T00:00:00.000000000&#x27;, &#x27;2000-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-06-16T00:00:00.000000000&#x27;, &#x27;2001-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-08-16T00:00:00.000000000&#x27;, &#x27;2001-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-16T00:00:00.000000000&#x27;, &#x27;2002-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-16T00:00:00.000000000&#x27;, &#x27;2002-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-16T00:00:00.000000000&#x27;, &#x27;2003-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-16T00:00:00.000000000&#x27;, &#x27;2003-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-16T00:00:00.000000000&#x27;, &#x27;2004-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-16T00:00:00.000000000&#x27;, &#x27;2004-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-16T00:00:00.000000000&#x27;, &#x27;2005-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-08-16T00:00:00.000000000&#x27;, &#x27;2005-09-16T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4c448d57-9652-47bf-b14e-a55b3f81ea8c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4c448d57-9652-47bf-b14e-a55b3f81ea8c' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>pre</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-67ce3802-c68d-46bd-bb88-8011c9b964d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-67ce3802-c68d-46bd-bb88-8011c9b964d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cfd85534-3373-4c7e-b412-529d5a058ad3' class='xr-var-data-in' type='checkbox'><label for='data-cfd85534-3373-4c7e-b412-529d5a058ad3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>precipitation</dd><dt><span>units :</span></dt><dd>mm/month</dd><dt><span>correlation_decay_distance :</span></dt><dd>450.0</dd></dl></div><div class='xr-var-data'><pre>[25920000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stn</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3fb8b3b1-338b-4629-b034-338cccfb6684' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3fb8b3b1-338b-4629-b034-338cccfb6684' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50d5831a-35d2-4132-bef5-8682624adfcf' class='xr-var-data-in' type='checkbox'><label for='data-50d5831a-35d2-4132-bef5-8682624adfcf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>number of stations contributing to each datum</dd></dl></div><div class='xr-var-data'><pre>[25920000 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f9f2343a-d983-4909-8d26-81b1b8f75ca2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f9f2343a-d983-4909-8d26-81b1b8f75ca2' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>title :</span></dt><dd>CRU TS4.06 Precipitation</dd><dt><span>institution :</span></dt><dd>Data held at British Atmospheric Data Centre, RAL, UK.</dd><dt><span>source :</span></dt><dd>Run ID = 2205201912. Data generated from:pre.2204291209.dtb</dd><dt><span>history :</span></dt><dd>Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegridsauto.for called by update.for</dd><dt><span>references :</span></dt><dd>Information on the data is available at http://badc.nerc.ac.uk/data/cru/</dd><dt><span>comment :</span></dt><dd>Access to these data is available to any registered CEDA user.</dd><dt><span>contact :</span></dt><dd>support@ceda.ac.uk</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lon: 720, lat: 360, time: 100)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 -179.8 -179.2 -178.8 -178.2 ... 178.8 179.2 179.8\n",
       "  * lat      (lat) float32 -89.75 -89.25 -88.75 -88.25 ... 88.75 89.25 89.75\n",
       "  * time     (time) datetime64[ns] 1981-06-16 1981-07-16 ... 2005-09-16\n",
       "Data variables:\n",
       "    pre      (time, lat, lon) float32 ...\n",
       "    stn      (time, lat, lon) float64 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#selecting only JJAS months\n",
    "\n",
    "def is_jjas(month):\n",
    "    return (month >= 6) & (month <= 9)\n",
    "\n",
    "jjas_data = data.sel(time=is_jjas(data['time.month']))\n",
    "\n",
    "jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "735515f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#for i in data.latitude.values:\n",
    " #   print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fd310367",
   "metadata": {},
   "outputs": [],
   "source": [
    "#for i in data.longitude.values:\n",
    " #   print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2a9644bb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       ".xr-attrs dt,\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
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       "\n",
       ".xr-attrs dt:hover span {\n",
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       "\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
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       "  height: 1.5em !important;\n",
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       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (lon: 16, lat: 20, time: 100)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 86.25 86.75 87.25 87.75 ... 92.25 92.75 93.25 93.75\n",
       "  * lat      (lat) float32 18.25 18.75 19.25 19.75 ... 26.25 26.75 27.25 27.75\n",
       "  * time     (time) datetime64[ns] 1981-06-16 1981-07-16 ... 2005-09-16\n",
       "Data variables:\n",
       "    pre      (time, lat, lon) float32 nan nan nan nan ... 48.9 76.6 108.2 132.9\n",
       "    stn      (time, lat, lon) float64 nan nan nan nan nan ... 8.0 8.0 8.0 8.0\n",
       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-286f5037-3fd9-45a5-98ee-014851f2268e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-286f5037-3fd9-45a5-98ee-014851f2268e' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 16</li><li><span class='xr-has-index'>lat</span>: 20</li><li><span class='xr-has-index'>time</span>: 100</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b621223e-98e5-4c62-8d15-13527f61484f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b621223e-98e5-4c62-8d15-13527f61484f' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>86.25 86.75 87.25 ... 93.25 93.75</div><input id='attrs-bc153f60-3979-47a8-8077-9e55ddd7b9fd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc153f60-3979-47a8-8077-9e55ddd7b9fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-223e65d9-15e2-4298-8096-f786a26a051f' class='xr-var-data-in' type='checkbox'><label for='data-223e65d9-15e2-4298-8096-f786a26a051f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([86.25, 86.75, 87.25, 87.75, 88.25, 88.75, 89.25, 89.75, 90.25, 90.75,\n",
       "       91.25, 91.75, 92.25, 92.75, 93.25, 93.75], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>18.25 18.75 19.25 ... 27.25 27.75</div><input id='attrs-bfe0e26d-26a1-4a39-9cf6-4061af67feff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfe0e26d-26a1-4a39-9cf6-4061af67feff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d846c1d1-a4cb-4537-8d14-52a852399bd3' class='xr-var-data-in' type='checkbox'><label for='data-d846c1d1-a4cb-4537-8d14-52a852399bd3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([18.25, 18.75, 19.25, 19.75, 20.25, 20.75, 21.25, 21.75, 22.25, 22.75,\n",
       "       23.25, 23.75, 24.25, 24.75, 25.25, 25.75, 26.25, 26.75, 27.25, 27.75],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-06-16 ... 2005-09-16</div><input id='attrs-d9c6f140-31d0-4078-913e-83354c642dc4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d9c6f140-31d0-4078-913e-83354c642dc4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4dac3d6-ea15-49f2-bd98-cc140e708b9f' class='xr-var-data-in' type='checkbox'><label for='data-b4dac3d6-ea15-49f2-bd98-cc140e708b9f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-06-16T00:00:00.000000000&#x27;, &#x27;1981-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-08-16T00:00:00.000000000&#x27;, &#x27;1981-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-06-16T00:00:00.000000000&#x27;, &#x27;1982-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-08-16T00:00:00.000000000&#x27;, &#x27;1982-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-06-16T00:00:00.000000000&#x27;, &#x27;1983-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-08-16T00:00:00.000000000&#x27;, &#x27;1983-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-06-16T00:00:00.000000000&#x27;, &#x27;1984-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-08-16T00:00:00.000000000&#x27;, &#x27;1984-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-06-16T00:00:00.000000000&#x27;, &#x27;1985-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-08-16T00:00:00.000000000&#x27;, &#x27;1985-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-06-16T00:00:00.000000000&#x27;, &#x27;1986-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-08-16T00:00:00.000000000&#x27;, &#x27;1986-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-06-16T00:00:00.000000000&#x27;, &#x27;1987-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-08-16T00:00:00.000000000&#x27;, &#x27;1987-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-06-16T00:00:00.000000000&#x27;, &#x27;1988-07-16T00:00:00.000000000&#x27;,\n",
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       "       &#x27;2001-08-16T00:00:00.000000000&#x27;, &#x27;2001-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-16T00:00:00.000000000&#x27;, &#x27;2002-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-16T00:00:00.000000000&#x27;, &#x27;2002-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-16T00:00:00.000000000&#x27;, &#x27;2003-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-16T00:00:00.000000000&#x27;, &#x27;2003-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-16T00:00:00.000000000&#x27;, &#x27;2004-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-16T00:00:00.000000000&#x27;, &#x27;2004-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-16T00:00:00.000000000&#x27;, &#x27;2005-07-16T00:00:00.000000000&#x27;,\n",
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       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c42efe06-e3f4-437f-add8-4c8e14bbe12d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c42efe06-e3f4-437f-add8-4c8e14bbe12d' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>pre</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1a7bc3ea-30fc-4d3c-aa28-9971a68804cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a7bc3ea-30fc-4d3c-aa28-9971a68804cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6c84318-29a1-472d-a946-f3168ec1a34a' class='xr-var-data-in' type='checkbox'><label for='data-e6c84318-29a1-472d-a946-f3168ec1a34a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>precipitation</dd><dt><span>units :</span></dt><dd>mm/month</dd><dt><span>correlation_decay_distance :</span></dt><dd>450.0</dd></dl></div><div class='xr-var-data'><pre>array([[[        nan,         nan, ...,         nan,         nan],\n",
       "        [        nan,         nan, ...,         nan,  594.3     ],\n",
       "        ...,\n",
       "        [ 197.2     ,  265.1     , ...,  205.8     ,  293.5     ],\n",
       "        [ 138.3     ,   90.6     , ...,  166.6     ,  224.      ]],\n",
       "\n",
       "       [[        nan,         nan, ...,         nan,         nan],\n",
       "        [        nan,         nan, ...,         nan, 2512.1     ],\n",
       "        ...,\n",
       "        [ 428.6     ,  508.80002 , ...,  370.9     ,  497.1     ],\n",
       "        [ 362.9     ,  199.6     , ...,  269.1     ,  354.1     ]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[        nan,         nan, ...,         nan,         nan],\n",
       "        [        nan,         nan, ...,         nan, 1151.9     ],\n",
       "        ...,\n",
       "        [ 282.30002 ,  330.30002 , ...,  203.1     ,  279.5     ],\n",
       "        [ 264.6     ,  142.40001 , ...,  162.2     ,  209.7     ]],\n",
       "\n",
       "       [[        nan,         nan, ...,         nan,         nan],\n",
       "        [        nan,         nan, ...,         nan,  861.3     ],\n",
       "        ...,\n",
       "        [ 215.6     ,  264.5     , ...,  127.      ,  153.90001 ],\n",
       "        [ 167.      ,   80.3     , ...,  108.200005,  132.90001 ]]],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stn</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-59fe674f-5ce4-4964-8112-8ee14a4b837e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59fe674f-5ce4-4964-8112-8ee14a4b837e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-645e9ce1-56e6-464a-85f2-89d4631fdaf4' class='xr-var-data-in' type='checkbox'><label for='data-645e9ce1-56e6-464a-85f2-89d4631fdaf4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>number of stations contributing to each datum</dd></dl></div><div class='xr-var-data'><pre>array([[[nan, nan, ..., nan, nan],\n",
       "        [nan, nan, ..., nan,  7.],\n",
       "        ...,\n",
       "        [ 8.,  8., ...,  8.,  8.],\n",
       "        [ 8.,  8., ...,  8.,  8.]],\n",
       "\n",
       "       [[nan, nan, ..., nan, nan],\n",
       "        [nan, nan, ..., nan,  5.],\n",
       "        ...,\n",
       "        [ 8.,  8., ...,  8.,  8.],\n",
       "        [ 8.,  8., ...,  8.,  8.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[nan, nan, ..., nan, nan],\n",
       "        [nan, nan, ..., nan,  3.],\n",
       "        ...,\n",
       "        [ 5.,  6., ...,  6.,  6.],\n",
       "        [ 5.,  5., ...,  7.,  8.]],\n",
       "\n",
       "       [[nan, nan, ..., nan, nan],\n",
       "        [nan, nan, ..., nan,  6.],\n",
       "        ...,\n",
       "        [ 7.,  8., ...,  8.,  8.],\n",
       "        [ 7.,  7., ...,  8.,  8.]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-781b6077-0f64-4c1c-b3d5-71202d075e1b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-781b6077-0f64-4c1c-b3d5-71202d075e1b' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>title :</span></dt><dd>CRU TS4.06 Precipitation</dd><dt><span>institution :</span></dt><dd>Data held at British Atmospheric Data Centre, RAL, UK.</dd><dt><span>source :</span></dt><dd>Run ID = 2205201912. Data generated from:pre.2204291209.dtb</dd><dt><span>history :</span></dt><dd>Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegridsauto.for called by update.for</dd><dt><span>references :</span></dt><dd>Information on the data is available at http://badc.nerc.ac.uk/data/cru/</dd><dt><span>comment :</span></dt><dd>Access to these data is available to any registered CEDA user.</dd><dt><span>contact :</span></dt><dd>support@ceda.ac.uk</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lon: 16, lat: 20, time: 100)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 86.25 86.75 87.25 87.75 ... 92.25 92.75 93.25 93.75\n",
       "  * lat      (lat) float32 18.25 18.75 19.25 19.75 ... 26.25 26.75 27.25 27.75\n",
       "  * time     (time) datetime64[ns] 1981-06-16 1981-07-16 ... 2005-09-16\n",
       "Data variables:\n",
       "    pre      (time, lat, lon) float32 ...\n",
       "    stn      (time, lat, lon) float64 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#to select the x and y coordinates\n",
    "jjas_data = jjas_data.sel(lon=slice(86,94),lat=slice(18,28))\n",
    "jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "91600dec",
   "metadata": {},
   "outputs": [
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       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 100, lat: 40, lon: 32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1981-06-16 1981-07-16 ... 2005-09-16\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "Data variables:\n",
       "    pre      (time, lat, lon) float64 nan nan nan nan nan ... nan nan nan nan\n",
       "    stn      (time, lat, lon) float64 nan nan nan nan nan ... nan nan nan nan\n",
       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-744bcadc-34a0-43bd-94b3-1015681ab6b5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-744bcadc-34a0-43bd-94b3-1015681ab6b5' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 100</li><li><span class='xr-has-index'>lat</span>: 40</li><li><span class='xr-has-index'>lon</span>: 32</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-85c3cd46-e94e-41ca-bd80-17b74445ec34' class='xr-section-summary-in' type='checkbox'  checked><label for='section-85c3cd46-e94e-41ca-bd80-17b74445ec34' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-06-16 ... 2005-09-16</div><input id='attrs-3109041d-deaa-440c-b890-4549eb3d0bd6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3109041d-deaa-440c-b890-4549eb3d0bd6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d6564ab-b6c7-4847-8014-d4a1cbff2804' class='xr-var-data-in' type='checkbox'><label for='data-0d6564ab-b6c7-4847-8014-d4a1cbff2804' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-06-16T00:00:00.000000000&#x27;, &#x27;1981-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-08-16T00:00:00.000000000&#x27;, &#x27;1981-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-06-16T00:00:00.000000000&#x27;, &#x27;1982-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-08-16T00:00:00.000000000&#x27;, &#x27;1982-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-06-16T00:00:00.000000000&#x27;, &#x27;1983-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-08-16T00:00:00.000000000&#x27;, &#x27;1983-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-06-16T00:00:00.000000000&#x27;, &#x27;1984-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-08-16T00:00:00.000000000&#x27;, &#x27;1984-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-06-16T00:00:00.000000000&#x27;, &#x27;1985-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-08-16T00:00:00.000000000&#x27;, &#x27;1985-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-06-16T00:00:00.000000000&#x27;, &#x27;1986-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-08-16T00:00:00.000000000&#x27;, &#x27;1986-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-06-16T00:00:00.000000000&#x27;, &#x27;1987-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-08-16T00:00:00.000000000&#x27;, &#x27;1987-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-06-16T00:00:00.000000000&#x27;, &#x27;1988-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-08-16T00:00:00.000000000&#x27;, &#x27;1988-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-06-16T00:00:00.000000000&#x27;, &#x27;1989-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-08-16T00:00:00.000000000&#x27;, &#x27;1989-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-06-16T00:00:00.000000000&#x27;, &#x27;1990-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-08-16T00:00:00.000000000&#x27;, &#x27;1990-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-06-16T00:00:00.000000000&#x27;, &#x27;1991-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-08-16T00:00:00.000000000&#x27;, &#x27;1991-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-06-16T00:00:00.000000000&#x27;, &#x27;1992-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-08-16T00:00:00.000000000&#x27;, &#x27;1992-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-06-16T00:00:00.000000000&#x27;, &#x27;1993-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-08-16T00:00:00.000000000&#x27;, &#x27;1993-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-06-16T00:00:00.000000000&#x27;, &#x27;1994-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-08-16T00:00:00.000000000&#x27;, &#x27;1994-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-06-16T00:00:00.000000000&#x27;, &#x27;1995-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-08-16T00:00:00.000000000&#x27;, &#x27;1995-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-06-16T00:00:00.000000000&#x27;, &#x27;1996-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-08-16T00:00:00.000000000&#x27;, &#x27;1996-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-06-16T00:00:00.000000000&#x27;, &#x27;1997-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-08-16T00:00:00.000000000&#x27;, &#x27;1997-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-06-16T00:00:00.000000000&#x27;, &#x27;1998-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-08-16T00:00:00.000000000&#x27;, &#x27;1998-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-06-16T00:00:00.000000000&#x27;, &#x27;1999-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-08-16T00:00:00.000000000&#x27;, &#x27;1999-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-16T00:00:00.000000000&#x27;, &#x27;2000-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-08-16T00:00:00.000000000&#x27;, &#x27;2000-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-06-16T00:00:00.000000000&#x27;, &#x27;2001-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-08-16T00:00:00.000000000&#x27;, &#x27;2001-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-16T00:00:00.000000000&#x27;, &#x27;2002-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-16T00:00:00.000000000&#x27;, &#x27;2002-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-16T00:00:00.000000000&#x27;, &#x27;2003-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-16T00:00:00.000000000&#x27;, &#x27;2003-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-16T00:00:00.000000000&#x27;, &#x27;2004-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-16T00:00:00.000000000&#x27;, &#x27;2004-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-16T00:00:00.000000000&#x27;, &#x27;2005-07-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-08-16T00:00:00.000000000&#x27;, &#x27;2005-09-16T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-412b3fb1-f7bf-430d-a8dc-30fa37e344b9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-412b3fb1-f7bf-430d-a8dc-30fa37e344b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a0b8bbd-d8f6-4340-b238-8823d723f0c3' class='xr-var-data-in' type='checkbox'><label for='data-1a0b8bbd-d8f6-4340-b238-8823d723f0c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-63f261ff-2806-49bd-99f5-a66fe2797e5a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63f261ff-2806-49bd-99f5-a66fe2797e5a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4fc4845-fb74-4900-ac8f-bf34c083fa7a' class='xr-var-data-in' type='checkbox'><label for='data-b4fc4845-fb74-4900-ac8f-bf34c083fa7a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-63f6c48f-a383-4454-bb2a-ad024bb971f8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-63f6c48f-a383-4454-bb2a-ad024bb971f8' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>pre</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-76199d54-47e5-45ab-8aa3-180c881b13bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-76199d54-47e5-45ab-8aa3-180c881b13bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60d9c559-d632-4488-9120-64dfebce48cd' class='xr-var-data-in' type='checkbox'><label for='data-60d9c559-d632-4488-9120-64dfebce48cd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>precipitation</dd><dt><span>units :</span></dt><dd>mm/month</dd><dt><span>correlation_decay_distance :</span></dt><dd>450.0</dd></dl></div><div class='xr-var-data'><pre>array([[[         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        ...,\n",
       "        [         nan, 192.22500038, 211.7250042 , ..., 216.03125286,\n",
       "         256.09375095,          nan],\n",
       "        [         nan, 148.32500267, 138.92500496, ..., 192.64375401,\n",
       "         225.13125134,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan]],\n",
       "\n",
       "       [[         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "...\n",
       "        [         nan, 279.23751545, 281.96251583, ..., 210.16875267,\n",
       "         244.75625038,          nan],\n",
       "        [         nan, 249.11250973, 209.28751087, ..., 186.10624886,\n",
       "         213.46874809,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan]],\n",
       "\n",
       "       [[         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan],\n",
       "        ...,\n",
       "        [         nan, 207.20000362, 214.70000172, ..., 128.88750315,\n",
       "         142.06250715,          nan],\n",
       "        [         nan, 165.95000172, 139.5500021 , ..., 119.21250486,\n",
       "         131.83750772,          nan],\n",
       "        [         nan,          nan,          nan, ...,          nan,\n",
       "                  nan,          nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>stn</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0cd32314-644a-424f-96d9-e163c153365f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0cd32314-644a-424f-96d9-e163c153365f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f46ac4a4-fec2-4d6e-8f8f-13517d9e8a4a' class='xr-var-data-in' type='checkbox'><label for='data-f46ac4a4-fec2-4d6e-8f8f-13517d9e8a4a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>number of stations contributing to each datum</dd></dl></div><div class='xr-var-data'><pre>array([[[   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        ...,\n",
       "        [   nan, 8.    , 8.    , ..., 8.    , 8.    ,    nan],\n",
       "        [   nan, 8.    , 8.    , ..., 8.    , 8.    ,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\n",
       "\n",
       "       [[   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        ...,\n",
       "        [   nan, 8.    , 8.    , ..., 8.    , 8.    ,    nan],\n",
       "        [   nan, 8.    , 8.    , ..., 8.    , 8.    ,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\n",
       "\n",
       "       [[   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [   nan, 5.1875, 5.5625, ..., 7.25  , 7.25  ,    nan],\n",
       "        [   nan, 5.0625, 5.1875, ..., 7.75  , 7.75  ,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\n",
       "\n",
       "       [[   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        ...,\n",
       "        [   nan, 5.1875, 5.5625, ..., 6.3125, 6.4375,    nan],\n",
       "        [   nan, 5.0625, 5.1875, ..., 6.9375, 7.3125,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]],\n",
       "\n",
       "       [[   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan],\n",
       "        ...,\n",
       "        [   nan, 7.1875, 7.5625, ..., 8.    , 8.    ,    nan],\n",
       "        [   nan, 7.0625, 7.1875, ..., 8.    , 8.    ,    nan],\n",
       "        [   nan,    nan,    nan, ...,    nan,    nan,    nan]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dbfa5683-c357-43bc-8bd8-1e6de1bc48e2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-dbfa5683-c357-43bc-8bd8-1e6de1bc48e2' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>title :</span></dt><dd>CRU TS4.06 Precipitation</dd><dt><span>institution :</span></dt><dd>Data held at British Atmospheric Data Centre, RAL, UK.</dd><dt><span>source :</span></dt><dd>Run ID = 2205201912. Data generated from:pre.2204291209.dtb</dd><dt><span>history :</span></dt><dd>Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegridsauto.for called by update.for</dd><dt><span>references :</span></dt><dd>Information on the data is available at http://badc.nerc.ac.uk/data/cru/</dd><dt><span>comment :</span></dt><dd>Access to these data is available to any registered CEDA user.</dd><dt><span>contact :</span></dt><dd>support@ceda.ac.uk</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 100, lat: 40, lon: 32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1981-06-16 1981-07-16 ... 2005-09-16\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "Data variables:\n",
       "    pre      (time, lat, lon) float64 nan nan nan nan nan ... nan nan nan nan\n",
       "    stn      (time, lat, lon) float64 nan nan nan nan nan ... nan nan nan nan\n",
       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#interpolating to new lat and lon\n",
    "\n",
    "new_lon = np.arange(86.125,94,0.25)\n",
    "new_lat = np.arange(18.125,28,0.25)\n",
    "jjas_data = jjas_data.interp(lat=new_lat,lon=new_lon)\n",
    "jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "82d6b5d0",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pre&#x27; (lat: 40, lon: 32)&gt;\n",
       "array([[         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       ...,\n",
       "       [         nan, 307.8540058 , 313.06750634, ..., 257.97650403,\n",
       "        300.16450421,          nan],\n",
       "       [         nan, 261.3955045 , 217.76700435, ..., 228.96350388,\n",
       "        263.6115048 ,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan]])\n",
       "Coordinates:\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'pre'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 40</li><li><span class='xr-has-index'>lon</span>: 32</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-250ed322-8413-4698-af70-14803ceb31fa' class='xr-array-in' type='checkbox' checked><label for='section-250ed322-8413-4698-af70-14803ceb31fa' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>nan nan nan nan nan nan nan nan ... nan nan nan nan nan nan nan nan</span></div><div class='xr-array-data'><pre>array([[         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       ...,\n",
       "       [         nan, 307.8540058 , 313.06750634, ..., 257.97650403,\n",
       "        300.16450421,          nan],\n",
       "       [         nan, 261.3955045 , 217.76700435, ..., 228.96350388,\n",
       "        263.6115048 ,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan]])</pre></div></div></li><li class='xr-section-item'><input id='section-236b141d-16a7-4de1-bf2c-86b378fd6baf' class='xr-section-summary-in' type='checkbox'  checked><label for='section-236b141d-16a7-4de1-bf2c-86b378fd6baf' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>18.12 18.38 18.62 ... 27.62 27.88</div><input id='attrs-fd7b1dae-8ab3-4619-9ce8-fa3c93f1248b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd7b1dae-8ab3-4619-9ce8-fa3c93f1248b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1ffb59a-3a25-4e4b-be2f-9a02ea909c6e' class='xr-var-data-in' type='checkbox'><label for='data-f1ffb59a-3a25-4e4b-be2f-9a02ea909c6e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([18.125, 18.375, 18.625, 18.875, 19.125, 19.375, 19.625, 19.875, 20.125,\n",
       "       20.375, 20.625, 20.875, 21.125, 21.375, 21.625, 21.875, 22.125, 22.375,\n",
       "       22.625, 22.875, 23.125, 23.375, 23.625, 23.875, 24.125, 24.375, 24.625,\n",
       "       24.875, 25.125, 25.375, 25.625, 25.875, 26.125, 26.375, 26.625, 26.875,\n",
       "       27.125, 27.375, 27.625, 27.875])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-a1b4f53a-b56e-45f9-9a9f-c9c9bd897123' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a1b4f53a-b56e-45f9-9a9f-c9c9bd897123' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e56eb9d-b936-4a5d-952a-e7784c041f7e' class='xr-var-data-in' type='checkbox'><label for='data-4e56eb9d-b936-4a5d-952a-e7784c041f7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([86.125, 86.375, 86.625, 86.875, 87.125, 87.375, 87.625, 87.875, 88.125,\n",
       "       88.375, 88.625, 88.875, 89.125, 89.375, 89.625, 89.875, 90.125, 90.375,\n",
       "       90.625, 90.875, 91.125, 91.375, 91.625, 91.875, 92.125, 92.375, 92.625,\n",
       "       92.875, 93.125, 93.375, 93.625, 93.875])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-15fc88fa-e2cb-4d55-ae35-47f407bcc70d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-15fc88fa-e2cb-4d55-ae35-47f407bcc70d' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'pre' (lat: 40, lon: 32)>\n",
       "array([[         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       ...,\n",
       "       [         nan, 307.8540058 , 313.06750634, ..., 257.97650403,\n",
       "        300.16450421,          nan],\n",
       "       [         nan, 261.3955045 , 217.76700435, ..., 228.96350388,\n",
       "        263.6115048 ,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan]])\n",
       "Coordinates:\n",
       "  * lat      (lat) float64 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "  * lon      (lon) float64 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#getting the mean for JJAS data\n",
    "jjas_mean = jjas_data.pre.mean('time')\n",
    " \n",
    "jjas_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6d00cba7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#changing unit from mm/month to mm/day\n",
    "pr_mm = jjas_mean/30.4167\n",
    " \n",
    "\n",
    "\n",
    "cru = pr_mm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b6d9b2b3",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 432, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) object 1970-01-16 12:00:00 ... 2005-12-16 12:00:00\n",
       "  * lon        (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
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       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1970-01-01 00:00:00 ... 2006-01-01 00:00:00\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 21 14:17:08 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment:                              MIROC-MIROC5, historical...\n",
       "    driving_model_id:                                MIROC-MIROC5\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    CDO:                                             Climate Data Operators v...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-000d071a-5ac0-48a7-9a1a-7b41c047ed04' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-000d071a-5ac0-48a7-9a1a-7b41c047ed04' 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-aec4c262-cf72-4f42-a0ca-6103707eb69d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-aec4c262-cf72-4f42-a0ca-6103707eb69d' 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-15a7f0d1-dca9-4363-a7d9-09781772ec43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15a7f0d1-dca9-4363-a7d9-09781772ec43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22f78b7f-f233-40bc-b870-b6916aea84b5' class='xr-var-data-in' type='checkbox'><label for='data-22f78b7f-f233-40bc-b870-b6916aea84b5' title='Show/Hide data 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-3b3d1a70-d831-40e6-b3c3-9b28cf2d03f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b3d1a70-d831-40e6-b3c3-9b28cf2d03f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c4004624-777b-40b0-ae4c-aa0c45f790c1' class='xr-var-data-in' type='checkbox'><label for='data-c4004624-777b-40b0-ae4c-aa0c45f790c1' title='Show/Hide data 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-fbbb12dd-9ca4-4c9a-9963-fe7fcc576bf8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fbbb12dd-9ca4-4c9a-9963-fe7fcc576bf8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb5a554f-fee1-4156-8160-9b10e78a77b9' class='xr-var-data-in' type='checkbox'><label for='data-fb5a554f-fee1-4156-8160-9b10e78a77b9' title='Show/Hide data 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-ef96c336-9376-4c67-b847-8629363a62f7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ef96c336-9376-4c67-b847-8629363a62f7' 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-2a166237-fda9-4d51-bb78-076512ae1d86' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a166237-fda9-4d51-bb78-076512ae1d86' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-68e3127a-317f-4255-a648-3d2db51b6cec' class='xr-var-data-in' type='checkbox'><label for='data-68e3127a-317f-4255-a648-3d2db51b6cec' title='Show/Hide data 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-56cd7b68-b3e1-40f8-85c8-9b6e926a589a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-56cd7b68-b3e1-40f8-85c8-9b6e926a589a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0f374ae-a229-4043-a7c5-d7ec078e1aef' class='xr-var-data-in' type='checkbox'><label for='data-d0f374ae-a229-4043-a7c5-d7ec078e1aef' title='Show/Hide data 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-949f1165-1195-40e0-89f7-fb4d4dd2838e' class='xr-section-summary-in' type='checkbox'  ><label for='section-949f1165-1195-40e0-89f7-fb4d4dd2838e' class='xr-section-summary' >Attributes: <span>(165)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>history :</span></dt><dd>Thu Jul 21 14:17:08 2022: cdo remapnn,grid.des regcmensble.nc regcmensble_remap.nc\n",
       "Thu Jul 21 14:08:02 2022: cdo divc,3 final.nc regcmensble.nc\n",
       "Thu Jul 21 14:06:30 2022: cdo -add miroc5_pr_197001-200512.nc -add mpiesm_pr_197001-200512.nc noresm_pr_197001-200512.nc final.nc\n",
       "Mon Jun 27 15:34:28 2022: cdo mergetime pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_197001-198012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_198101-199012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_199101-200012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_200101-200512.nc miroc5_pr_197001-200512.nc\n",
       "2018-05-11 16:23:33 : Created by RegCM RegCM Model program</dd><dt><span>source :</span></dt><dd>RegCM Model output file</dd><dt><span>institution :</span></dt><dd>Oak Ridge National Laboratory</dd><dt><span>project_id :</span></dt><dd>CORDEX</dd><dt><span>ipcc_scenario_code :</span></dt><dd>HISTORICAL</dd><dt><span>institute_id :</span></dt><dd>ORNL</dd><dt><span>note :</span></dt><dd>The domain is larger than WAS-22</dd><dt><span>comment :</span></dt><dd>RegCM CORDEX SAsia25 run</dd><dt><span>experiment :</span></dt><dd>WAS-22</dd><dt><span>driving_model_ensemble_member :</span></dt><dd>r1i1p1</dd><dt><span>creation_date :</span></dt><dd>2019-09-12T16:23:22Z</dd><dt><span>CORDEX_domain :</span></dt><dd>WAS-22</dd><dt><span>rcm_version_id :</span></dt><dd>v0</dd><dt><span>ICTP_version_note :</span></dt><dd>Model run at ORNL on Titan</dd><dt><span>contact :</span></dt><dd>mashfaq@ornl.gov</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>tracking_id :</span></dt><dd>635194b8-8309-11e9-827b-f04da273f023</dd><dt><span>title :</span></dt><dd>ICTP Regional Climatic model V4</dd><dt><span>references :</span></dt><dd>http://gforge.ictp.it/gf/project/regcm</dd><dt><span>model_revision :</span></dt><dd>tag-4.7.0</dd><dt><span>projection :</span></dt><dd>ROTMER</dd><dt><span>grid_size_in_meters :</span></dt><dd>25000.0</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>13.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>70.0</dd><dt><span>grid_north_pole_latitude :</span></dt><dd>13.0</dd><dt><span>grid_north_pole_longitude :</span></dt><dd>70.0</dd><dt><span>grid_factor :</span></dt><dd>0.0</dd><dt><span>landsurface_model :</span></dt><dd>clm4.5</dd><dt><span>model_icbc_data_source :</span></dt><dd>MI_85</dd><dt><span>model_sst_data_source :</span></dt><dd>MI_85</dd><dt><span>boundary_nspgx :</span></dt><dd>30</dd><dt><span>boundary_nspgd :</span></dt><dd>30</dd><dt><span>boundary_high_nudge :</span></dt><dd>8.0</dd><dt><span>boundary_medium_nudge :</span></dt><dd>6.0</dd><dt><span>boundary_low_nudge :</span></dt><dd>4.0</dd><dt><span>boundary_nm :</span></dt><dd>-1.0</dd><dt><span>boundary_dm :</span></dt><dd>-1.0</dd><dt><span>model_is_restarted :</span></dt><dd>No</dd><dt><span>model_simulation_initial_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_end :</span></dt><dd> 1975-01-01 00:00:00 UTC</dd><dt><span>atmosphere_time_step_in_seconds :</span></dt><dd>40.0</dd><dt><span>surface_interaction_time_step_in_seconds :</span></dt><dd>480.0</dd><dt><span>convection_time_step_in_seconds :</span></dt><dd>240.0</dd><dt><span>radiation_scheme_time_step_in_seconds :</span></dt><dd>1800.0</dd><dt><span>absorption_emission_time_step_in_seconds :</span></dt><dd>64800.0</dd><dt><span>dynamical_core :</span></dt><dd>1</dd><dt><span>asselin_filter_nu_1 :</span></dt><dd>0.0625</dd><dt><span>asselin_filter_nu_2 :</span></dt><dd>0.0625</dd><dt><span>diffusion_hgt_factor :</span></dt><dd>1</dd><dt><span>upstream_mode :</span></dt><dd>Yes</dd><dt><span>off_centering_max :</span></dt><dd>0.25</dd><dt><span>stability_enhance :</span></dt><dd>Yes</dd><dt><span>temperature_extreme_gradient :</span></dt><dd>5.0</dd><dt><span>cloud_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>vapor_extreme_gradient_fraction :</span></dt><dd>0.2</dd><dt><span>tracer_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>lateral_boundary_condition_scheme :</span></dt><dd>5</dd><dt><span>semi_lagrangian_advection_scheme :</span></dt><dd>0</dd><dt><span>boundary_layer_scheme :</span></dt><dd>2</dd><dt><span>cumulus_convection_scheme_lnd :</span></dt><dd>4</dd><dt><span>cumulus_convection_scheme_ocn :</span></dt><dd>5</dd><dt><span>moisture_scheme :</span></dt><dd>1</dd><dt><span>ocean_flux_scheme :</span></dt><dd>2</dd><dt><span>zeng_ocean_roughness_formula :</span></dt><dd>1</dd><dt><span>zeng_ocean_roughness_method :</span></dt><dd>1</dd><dt><span>pressure_gradient_scheme :</span></dt><dd>0</dd><dt><span>surface_emissivity_factor_computed :</span></dt><dd>0</dd><dt><span>lake_model_activated :</span></dt><dd>0</dd><dt><span>chemical_aerosol_scheme_activated :</span></dt><dd>0</dd><dt><span>diurnal_cycle_sst_scheme :</span></dt><dd>0</dd><dt><span>ocean_precipitaion_cooling_effect :</span></dt><dd>0</dd><dt><span>ocean_albedo_from_whitecapping :</span></dt><dd>0</dd><dt><span>simple_sea_ice_scheme :</span></dt><dd>0</dd><dt><span>seasonal_desert_albedo :</span></dt><dd>0</dd><dt><span>convective_lwp_as_large_scale :</span></dt><dd>0</dd><dt><span>large_scale_cloud_fraction_scheme :</span></dt><dd>0</dd><dt><span>ocean_stratiform_clouds_scheme :</span></dt><dd>1</dd><dt><span>rrtm_radiation_scheme_activated :</span></dt><dd>0</dd><dt><span>climatic_ozone_input_dataset :</span></dt><dd>0</dd><dt><span>climatic_aerosol_input_dataset :</span></dt><dd>0</dd><dt><span>static_solar_constant_used :</span></dt><dd>0</dd><dt><span>cumulus_cloud_model :</span></dt><dd>1</dd><dt><span>sun_year_offset :</span></dt><dd>0.0</dd><dt><span>fix_solar_parameters :</span></dt><dd>0</dd><dt><span>cloud_bottom_level_with_no_clouds :</span></dt><dd>1</dd><dt><span>cloud_rh_with_fcc_one :</span></dt><dd>1.01</dd><dt><span>cloud_rh_threshold_for_land :</span></dt><dd>0.8</dd><dt><span>cloud_rh_threshold_for_ocean :</span></dt><dd>0.9</dd><dt><span>cloud_rh1_limit_temperature :</span></dt><dd>238.0</dd><dt><span>cloud_cloud_fraction_maximum :</span></dt><dd>0.75</dd><dt><span>cloud_condensation_threshold :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_fraction_max_for_convection :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_liqwat_max_for_convection :</span></dt><dd>0.0003</dd><dt><span>cloud_shallow_convective_cf_param :</span></dt><dd>0.07</dd><dt><span>cloud_deep_convective_cf_param :</span></dt><dd>0.14</dd><dt><span>cloud_k2_convective_cf_param :</span></dt><dd>500.0</dd><dt><span>cloud_surface_radiation_hack :</span></dt><dd>No</dd><dt><span>cloud_arctic_cloud_correction :</span></dt><dd>Yes</dd><dt><span>subex_auto_conversion_rate_for_land :</span></dt><dd>0.00025</dd><dt><span>subex_auto_conversion_rate_for_ocean :</span></dt><dd>0.00025</dd><dt><span>subex_gultepe_factor_when_rain_for_land :</span></dt><dd>0.4</dd><dt><span>subex_gultepe_factor_when_rain_for_ocean :</span></dt><dd>0.4</dd><dt><span>subex_land_raindrop_evaporation_rate :</span></dt><dd>0.0002</dd><dt><span>subex_ocean_raindrop_evaporation_rate :</span></dt><dd>0.0001</dd><dt><span>subex_land_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>subex_ocean_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>mit_lowest_convection_sigma :</span></dt><dd>0.95</dd><dt><span>mit_autoconversion_threshold_mixing_over_ocean :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_mixing_over_land :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_temperature :</span></dt><dd>-55.0</dd><dt><span>mit_mixing_coefficient_in_entrainment :</span></dt><dd>1.5</dd><dt><span>mit_fractional_area_unsaturated_downdraft :</span></dt><dd>0.05</dd><dt><span>mit_fractional_precip_outside_cloud :</span></dt><dd>0.12</dd><dt><span>mit_pressure_velocity_of_rain :</span></dt><dd>50.0</dd><dt><span>mit_pressure_velocity_of_snow :</span></dt><dd>5.5</dd><dt><span>mit_rain_evaporation_coefficient :</span></dt><dd>1.0</dd><dt><span>mit_snow_evaporation_coefficient :</span></dt><dd>0.8</dd><dt><span>mit_momentum_transport_coefficient :</span></dt><dd>0.7</dd><dt><span>mit_downdraft_velocity_coefficient :</span></dt><dd>10.0</dd><dt><span>mit_max_parcel_neg_temp_perturbation :</span></dt><dd>0.9</dd><dt><span>mit_approach_rate_quasi_eq_coeff_a :</span></dt><dd>0.2</dd><dt><span>mit_approach_rate_quasi_eq_coeff_d :</span></dt><dd>0.1</dd><dt><span>mit_maximum_land_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>mit_maximum_ocean_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>tiedtke_actual_scheme :</span></dt><dd>4</dd><dt><span>tiedtke_entrainment_rate_downdraft :</span></dt><dd>0.0003</dd><dt><span>tiedtke_entrainment_rate_deep_land :</span></dt><dd>0.00075</dd><dt><span>tiedtke_entrainment_rate_deep_ocean :</span></dt><dd>0.00075</dd><dt><span>tiedtke_penetrative :</span></dt><dd>Yes</dd><dt><span>tiedtke_midlevel :</span></dt><dd>Yes</dd><dt><span>tiedtke_shallow :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_downdraft :</span></dt><dd>Yes</dd><dt><span>tiedtke_prognostic_cloud :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_friction :</span></dt><dd>Yes</dd><dt><span>tiedtke_ke_dissipation :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_transport :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_smooth_massflux :</span></dt><dd>No</dd><dt><span>tiedtke_shallow_wstar_closure :</span></dt><dd>No</dd><dt><span>tiedtke_detrainment_rate_deep_land :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_detrainment_rate_deep_ocean :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_shallow_entrainment :</span></dt><dd>2.0</dd><dt><span>tiedtke_cloud_cover_evap_over_land :</span></dt><dd>0.05</dd><dt><span>tiedtke_cloud_cover_evap_over_ocean :</span></dt><dd>0.05</dd><dt><span>tiedtke_coeff_evap_over_land :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_coeff_evap_over_ocean :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_critical_rh_over_land :</span></dt><dd>0.9</dd><dt><span>tiedtke_critical_rh_over_ocean :</span></dt><dd>0.9</dd><dt><span>tiedtke_cloud_water_conv_over_land :</span></dt><dd>0.03</dd><dt><span>tiedtke_cloud_water_conv_over_ocean :</span></dt><dd>0.0014</dd><dt><span>tiedtke_cape_adjustment_timescale :</span></dt><dd>2400.0</dd><dt><span>uwpbl_advection_scheme :</span></dt><dd>0</dd><dt><span>uwpbl_cloud_evap_entr_incr_efficiency :</span></dt><dd>15.0</dd><dt><span>uwpbl_eddy_LS_stable_PBL_scaling :</span></dt><dd>1.5</dd><dt><span>uwpbl_czero :</span></dt><dd>5.869</dd><dt><span>uwpbl_nuk :</span></dt><dd>5.0</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>driving_experiment :</span></dt><dd>MIROC-MIROC5, historical, r1i1p1</dd><dt><span>driving_model_id :</span></dt><dd>MIROC-MIROC5</dd><dt><span>driving_experiment_name :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>ICTP-RegCM4-7</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.9rc1 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
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       "<xarray.Dataset>\n",
       "Dimensions:    (time: 432, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) object 1970-01-16 12:00:00 ... 2005-12-16 12:00:00\n",
       "  * lon        (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat        (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object ...\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 21 14:17:08 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment:                              MIROC-MIROC5, historical...\n",
       "    driving_model_id:                                MIROC-MIROC5\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    CDO:                                             Climate Data Operators v..."
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#opening miroc5 data\n",
    "\n",
    "data = xr.open_dataset('/home/mkibria/Academic/pr_of_thesis/regcm driven by gcm/ensemble-average/regcmensble_remap.nc')\n",
    "\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f6e94198",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/mkibria/miniconda3/envs/esp-sp/lib/python3.9/site-packages/xarray/coding/times.py:351: FutureWarning: Index.ravel returning ndarray is deprecated; in a future version this will return a view on self.\n",
      "  sample = dates.ravel()[0]\n",
      "/tmp/ipykernel_9984/1463838701.py:3: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  datetimeindex = data.indexes['time'].to_datetimeindex()\n"
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       "Dimensions:    (time: 432, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1970-01-16T12:00:00 ... 2005-12-16T12:00:00\n",
       "  * lon        (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat        (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1970-01-01 00:00:00 ... 2006-01-01 00:00:00\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 21 14:17:08 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment:                              MIROC-MIROC5, historical...\n",
       "    driving_model_id:                                MIROC-MIROC5\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    CDO:                                             Climate Data Operators v...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-a299b935-e427-4387-9813-4f42c915428f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a299b935-e427-4387-9813-4f42c915428f' 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-86a5495a-c9ff-4d63-aa59-0c2d83f9fb56' class='xr-section-summary-in' type='checkbox'  checked><label for='section-86a5495a-c9ff-4d63-aa59-0c2d83f9fb56' 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-6c76b694-7770-4c2d-a361-0ca4d184def8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6c76b694-7770-4c2d-a361-0ca4d184def8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94a0895b-5d15-42eb-b6b4-200e1eeee34b' class='xr-var-data-in' type='checkbox'><label for='data-94a0895b-5d15-42eb-b6b4-200e1eeee34b' title='Show/Hide data 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-f2f91fc5-dad0-473d-a39e-51fe67c8d757' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f2f91fc5-dad0-473d-a39e-51fe67c8d757' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f00e3c44-e91e-4cfd-be44-258b99c93c8e' class='xr-var-data-in' type='checkbox'><label for='data-f00e3c44-e91e-4cfd-be44-258b99c93c8e' title='Show/Hide data 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-bb43b156-8668-46a2-b9a4-852dd0b605c7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb43b156-8668-46a2-b9a4-852dd0b605c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dfb83dbf-ab06-4578-a7dc-821c85d2bb80' class='xr-var-data-in' type='checkbox'><label for='data-dfb83dbf-ab06-4578-a7dc-821c85d2bb80' title='Show/Hide data 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-2232baef-41ef-4034-a7c3-7b0c2a278b4b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2232baef-41ef-4034-a7c3-7b0c2a278b4b' 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-5bb3e43d-d12e-45b7-bc51-e8c63bda0506' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5bb3e43d-d12e-45b7-bc51-e8c63bda0506' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd32f426-132e-4617-b956-3c9222a7d5ed' class='xr-var-data-in' type='checkbox'><label for='data-bd32f426-132e-4617-b956-3c9222a7d5ed' title='Show/Hide data 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-c0845b74-9bf3-463b-9301-e4de8e560e34' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c0845b74-9bf3-463b-9301-e4de8e560e34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2d89107-cf0c-4e25-8114-120b58bc5cc0' class='xr-var-data-in' type='checkbox'><label for='data-a2d89107-cf0c-4e25-8114-120b58bc5cc0' title='Show/Hide data 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-411bd1f7-692e-47e6-bd82-7f066466b62e' class='xr-section-summary-in' type='checkbox'  ><label for='section-411bd1f7-692e-47e6-bd82-7f066466b62e' class='xr-section-summary' >Attributes: <span>(165)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>history :</span></dt><dd>Thu Jul 21 14:17:08 2022: cdo remapnn,grid.des regcmensble.nc regcmensble_remap.nc\n",
       "Thu Jul 21 14:08:02 2022: cdo divc,3 final.nc regcmensble.nc\n",
       "Thu Jul 21 14:06:30 2022: cdo -add miroc5_pr_197001-200512.nc -add mpiesm_pr_197001-200512.nc noresm_pr_197001-200512.nc final.nc\n",
       "Mon Jun 27 15:34:28 2022: cdo mergetime pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_197001-198012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_198101-199012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_199101-200012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_200101-200512.nc miroc5_pr_197001-200512.nc\n",
       "2018-05-11 16:23:33 : Created by RegCM RegCM Model program</dd><dt><span>source :</span></dt><dd>RegCM Model output file</dd><dt><span>institution :</span></dt><dd>Oak Ridge National Laboratory</dd><dt><span>project_id :</span></dt><dd>CORDEX</dd><dt><span>ipcc_scenario_code :</span></dt><dd>HISTORICAL</dd><dt><span>institute_id :</span></dt><dd>ORNL</dd><dt><span>note :</span></dt><dd>The domain is larger than WAS-22</dd><dt><span>comment :</span></dt><dd>RegCM CORDEX SAsia25 run</dd><dt><span>experiment :</span></dt><dd>WAS-22</dd><dt><span>driving_model_ensemble_member :</span></dt><dd>r1i1p1</dd><dt><span>creation_date :</span></dt><dd>2019-09-12T16:23:22Z</dd><dt><span>CORDEX_domain :</span></dt><dd>WAS-22</dd><dt><span>rcm_version_id :</span></dt><dd>v0</dd><dt><span>ICTP_version_note :</span></dt><dd>Model run at ORNL on Titan</dd><dt><span>contact :</span></dt><dd>mashfaq@ornl.gov</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>tracking_id :</span></dt><dd>635194b8-8309-11e9-827b-f04da273f023</dd><dt><span>title :</span></dt><dd>ICTP Regional Climatic model V4</dd><dt><span>references :</span></dt><dd>http://gforge.ictp.it/gf/project/regcm</dd><dt><span>model_revision :</span></dt><dd>tag-4.7.0</dd><dt><span>projection :</span></dt><dd>ROTMER</dd><dt><span>grid_size_in_meters :</span></dt><dd>25000.0</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>13.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>70.0</dd><dt><span>grid_north_pole_latitude :</span></dt><dd>13.0</dd><dt><span>grid_north_pole_longitude :</span></dt><dd>70.0</dd><dt><span>grid_factor :</span></dt><dd>0.0</dd><dt><span>landsurface_model :</span></dt><dd>clm4.5</dd><dt><span>model_icbc_data_source :</span></dt><dd>MI_85</dd><dt><span>model_sst_data_source :</span></dt><dd>MI_85</dd><dt><span>boundary_nspgx :</span></dt><dd>30</dd><dt><span>boundary_nspgd :</span></dt><dd>30</dd><dt><span>boundary_high_nudge :</span></dt><dd>8.0</dd><dt><span>boundary_medium_nudge :</span></dt><dd>6.0</dd><dt><span>boundary_low_nudge :</span></dt><dd>4.0</dd><dt><span>boundary_nm :</span></dt><dd>-1.0</dd><dt><span>boundary_dm :</span></dt><dd>-1.0</dd><dt><span>model_is_restarted :</span></dt><dd>No</dd><dt><span>model_simulation_initial_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_end :</span></dt><dd> 1975-01-01 00:00:00 UTC</dd><dt><span>atmosphere_time_step_in_seconds :</span></dt><dd>40.0</dd><dt><span>surface_interaction_time_step_in_seconds :</span></dt><dd>480.0</dd><dt><span>convection_time_step_in_seconds :</span></dt><dd>240.0</dd><dt><span>radiation_scheme_time_step_in_seconds :</span></dt><dd>1800.0</dd><dt><span>absorption_emission_time_step_in_seconds :</span></dt><dd>64800.0</dd><dt><span>dynamical_core :</span></dt><dd>1</dd><dt><span>asselin_filter_nu_1 :</span></dt><dd>0.0625</dd><dt><span>asselin_filter_nu_2 :</span></dt><dd>0.0625</dd><dt><span>diffusion_hgt_factor :</span></dt><dd>1</dd><dt><span>upstream_mode :</span></dt><dd>Yes</dd><dt><span>off_centering_max :</span></dt><dd>0.25</dd><dt><span>stability_enhance :</span></dt><dd>Yes</dd><dt><span>temperature_extreme_gradient :</span></dt><dd>5.0</dd><dt><span>cloud_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>vapor_extreme_gradient_fraction :</span></dt><dd>0.2</dd><dt><span>tracer_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>lateral_boundary_condition_scheme :</span></dt><dd>5</dd><dt><span>semi_lagrangian_advection_scheme :</span></dt><dd>0</dd><dt><span>boundary_layer_scheme :</span></dt><dd>2</dd><dt><span>cumulus_convection_scheme_lnd :</span></dt><dd>4</dd><dt><span>cumulus_convection_scheme_ocn :</span></dt><dd>5</dd><dt><span>moisture_scheme :</span></dt><dd>1</dd><dt><span>ocean_flux_scheme :</span></dt><dd>2</dd><dt><span>zeng_ocean_roughness_formula :</span></dt><dd>1</dd><dt><span>zeng_ocean_roughness_method :</span></dt><dd>1</dd><dt><span>pressure_gradient_scheme :</span></dt><dd>0</dd><dt><span>surface_emissivity_factor_computed :</span></dt><dd>0</dd><dt><span>lake_model_activated :</span></dt><dd>0</dd><dt><span>chemical_aerosol_scheme_activated :</span></dt><dd>0</dd><dt><span>diurnal_cycle_sst_scheme :</span></dt><dd>0</dd><dt><span>ocean_precipitaion_cooling_effect :</span></dt><dd>0</dd><dt><span>ocean_albedo_from_whitecapping :</span></dt><dd>0</dd><dt><span>simple_sea_ice_scheme :</span></dt><dd>0</dd><dt><span>seasonal_desert_albedo :</span></dt><dd>0</dd><dt><span>convective_lwp_as_large_scale :</span></dt><dd>0</dd><dt><span>large_scale_cloud_fraction_scheme :</span></dt><dd>0</dd><dt><span>ocean_stratiform_clouds_scheme :</span></dt><dd>1</dd><dt><span>rrtm_radiation_scheme_activated :</span></dt><dd>0</dd><dt><span>climatic_ozone_input_dataset :</span></dt><dd>0</dd><dt><span>climatic_aerosol_input_dataset :</span></dt><dd>0</dd><dt><span>static_solar_constant_used :</span></dt><dd>0</dd><dt><span>cumulus_cloud_model :</span></dt><dd>1</dd><dt><span>sun_year_offset :</span></dt><dd>0.0</dd><dt><span>fix_solar_parameters :</span></dt><dd>0</dd><dt><span>cloud_bottom_level_with_no_clouds :</span></dt><dd>1</dd><dt><span>cloud_rh_with_fcc_one :</span></dt><dd>1.01</dd><dt><span>cloud_rh_threshold_for_land :</span></dt><dd>0.8</dd><dt><span>cloud_rh_threshold_for_ocean :</span></dt><dd>0.9</dd><dt><span>cloud_rh1_limit_temperature :</span></dt><dd>238.0</dd><dt><span>cloud_cloud_fraction_maximum :</span></dt><dd>0.75</dd><dt><span>cloud_condensation_threshold :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_fraction_max_for_convection :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_liqwat_max_for_convection :</span></dt><dd>0.0003</dd><dt><span>cloud_shallow_convective_cf_param :</span></dt><dd>0.07</dd><dt><span>cloud_deep_convective_cf_param :</span></dt><dd>0.14</dd><dt><span>cloud_k2_convective_cf_param :</span></dt><dd>500.0</dd><dt><span>cloud_surface_radiation_hack :</span></dt><dd>No</dd><dt><span>cloud_arctic_cloud_correction :</span></dt><dd>Yes</dd><dt><span>subex_auto_conversion_rate_for_land :</span></dt><dd>0.00025</dd><dt><span>subex_auto_conversion_rate_for_ocean :</span></dt><dd>0.00025</dd><dt><span>subex_gultepe_factor_when_rain_for_land :</span></dt><dd>0.4</dd><dt><span>subex_gultepe_factor_when_rain_for_ocean :</span></dt><dd>0.4</dd><dt><span>subex_land_raindrop_evaporation_rate :</span></dt><dd>0.0002</dd><dt><span>subex_ocean_raindrop_evaporation_rate :</span></dt><dd>0.0001</dd><dt><span>subex_land_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>subex_ocean_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>mit_lowest_convection_sigma :</span></dt><dd>0.95</dd><dt><span>mit_autoconversion_threshold_mixing_over_ocean :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_mixing_over_land :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_temperature :</span></dt><dd>-55.0</dd><dt><span>mit_mixing_coefficient_in_entrainment :</span></dt><dd>1.5</dd><dt><span>mit_fractional_area_unsaturated_downdraft :</span></dt><dd>0.05</dd><dt><span>mit_fractional_precip_outside_cloud :</span></dt><dd>0.12</dd><dt><span>mit_pressure_velocity_of_rain :</span></dt><dd>50.0</dd><dt><span>mit_pressure_velocity_of_snow :</span></dt><dd>5.5</dd><dt><span>mit_rain_evaporation_coefficient :</span></dt><dd>1.0</dd><dt><span>mit_snow_evaporation_coefficient :</span></dt><dd>0.8</dd><dt><span>mit_momentum_transport_coefficient :</span></dt><dd>0.7</dd><dt><span>mit_downdraft_velocity_coefficient :</span></dt><dd>10.0</dd><dt><span>mit_max_parcel_neg_temp_perturbation :</span></dt><dd>0.9</dd><dt><span>mit_approach_rate_quasi_eq_coeff_a :</span></dt><dd>0.2</dd><dt><span>mit_approach_rate_quasi_eq_coeff_d :</span></dt><dd>0.1</dd><dt><span>mit_maximum_land_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>mit_maximum_ocean_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>tiedtke_actual_scheme :</span></dt><dd>4</dd><dt><span>tiedtke_entrainment_rate_downdraft :</span></dt><dd>0.0003</dd><dt><span>tiedtke_entrainment_rate_deep_land :</span></dt><dd>0.00075</dd><dt><span>tiedtke_entrainment_rate_deep_ocean :</span></dt><dd>0.00075</dd><dt><span>tiedtke_penetrative :</span></dt><dd>Yes</dd><dt><span>tiedtke_midlevel :</span></dt><dd>Yes</dd><dt><span>tiedtke_shallow :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_downdraft :</span></dt><dd>Yes</dd><dt><span>tiedtke_prognostic_cloud :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_friction :</span></dt><dd>Yes</dd><dt><span>tiedtke_ke_dissipation :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_transport :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_smooth_massflux :</span></dt><dd>No</dd><dt><span>tiedtke_shallow_wstar_closure :</span></dt><dd>No</dd><dt><span>tiedtke_detrainment_rate_deep_land :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_detrainment_rate_deep_ocean :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_shallow_entrainment :</span></dt><dd>2.0</dd><dt><span>tiedtke_cloud_cover_evap_over_land :</span></dt><dd>0.05</dd><dt><span>tiedtke_cloud_cover_evap_over_ocean :</span></dt><dd>0.05</dd><dt><span>tiedtke_coeff_evap_over_land :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_coeff_evap_over_ocean :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_critical_rh_over_land :</span></dt><dd>0.9</dd><dt><span>tiedtke_critical_rh_over_ocean :</span></dt><dd>0.9</dd><dt><span>tiedtke_cloud_water_conv_over_land :</span></dt><dd>0.03</dd><dt><span>tiedtke_cloud_water_conv_over_ocean :</span></dt><dd>0.0014</dd><dt><span>tiedtke_cape_adjustment_timescale :</span></dt><dd>2400.0</dd><dt><span>uwpbl_advection_scheme :</span></dt><dd>0</dd><dt><span>uwpbl_cloud_evap_entr_incr_efficiency :</span></dt><dd>15.0</dd><dt><span>uwpbl_eddy_LS_stable_PBL_scaling :</span></dt><dd>1.5</dd><dt><span>uwpbl_czero :</span></dt><dd>5.869</dd><dt><span>uwpbl_nuk :</span></dt><dd>5.0</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>driving_experiment :</span></dt><dd>MIROC-MIROC5, historical, r1i1p1</dd><dt><span>driving_model_id :</span></dt><dd>MIROC-MIROC5</dd><dt><span>driving_experiment_name :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>ICTP-RegCM4-7</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.9rc1 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (time: 432, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1970-01-16T12:00:00 ... 2005-12-16T12:00:00\n",
       "  * lon        (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat        (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1970-01-01 00:00:00 ... 2006-01-01 00:00:00\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 21 14:17:08 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment:                              MIROC-MIROC5, historical...\n",
       "    driving_model_id:                                MIROC-MIROC5\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    CDO:                                             Climate Data Operators v..."
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#changing time dim to datetime64[ns] dtype\n",
    "\n",
    "datetimeindex = data.indexes['time'].to_datetimeindex()\n",
    "data['time']=datetimeindex\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "cafd5692",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 299, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-01-16T12:00:00 ... 2005-11-16\n",
       "  * lon        (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat        (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
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       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 21 14:17:08 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment:                              MIROC-MIROC5, historical...\n",
       "    driving_model_id:                                MIROC-MIROC5\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    CDO:                                             Climate Data Operators v...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-da3f7bb3-14cf-4d88-b076-98a0e5c9a2b6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-da3f7bb3-14cf-4d88-b076-98a0e5c9a2b6' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 299</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 32</li><li><span class='xr-has-index'>lat</span>: 40</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-05e9d2c7-f9ec-412f-8ef7-d43621a7d1b6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-05e9d2c7-f9ec-412f-8ef7-d43621a7d1b6' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-01-16T12:00:00 ... 2005-11-16</div><input id='attrs-28e374c3-09ba-408a-a95a-9c75ca47fde7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-28e374c3-09ba-408a-a95a-9c75ca47fde7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3928a718-17c6-41cc-a683-3fc66bcae07a' class='xr-var-data-in' type='checkbox'><label for='data-3928a718-17c6-41cc-a683-3fc66bcae07a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-01-16T12:00:00.000000000&#x27;, &#x27;1981-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-03-16T12:00:00.000000000&#x27;, ..., &#x27;2005-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-10-16T12:00:00.000000000&#x27;, &#x27;2005-11-16T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-4c6f326e-32bf-4cbd-adb9-85f610d52d34' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c6f326e-32bf-4cbd-adb9-85f610d52d34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cba25d7-c906-44a9-a82a-88ba32fa2ddc' class='xr-var-data-in' type='checkbox'><label for='data-2cba25d7-c906-44a9-a82a-88ba32fa2ddc' title='Show/Hide data 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-62f6b574-00f5-496b-8e3c-8bf6c507c84f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62f6b574-00f5-496b-8e3c-8bf6c507c84f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d4fa5e4-5ac9-430a-825c-b0a0f2b067d1' class='xr-var-data-in' type='checkbox'><label for='data-3d4fa5e4-5ac9-430a-825c-b0a0f2b067d1' title='Show/Hide data 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-e10ffcd4-56f8-4f8c-adf3-15bb50a7fea6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e10ffcd4-56f8-4f8c-adf3-15bb50a7fea6' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1981-01-01 00:00:00 ... 2005-12-...</div><input id='attrs-a8c06e46-2a81-43c6-b8d3-88320308511c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a8c06e46-2a81-43c6-b8d3-88320308511c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9eb9bc50-8778-42e9-b629-6f9cc98abeec' class='xr-var-data-in' type='checkbox'><label for='data-9eb9bc50-8778-42e9-b629-6f9cc98abeec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[cftime.DatetimeNoLeap(1981, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1981, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1981, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       ...,\n",
       "       [cftime.DatetimeNoLeap(2005, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 12, 1, 0, 0, 0, 0, has_year_zero=True)]],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-48c06af0-c2d0-4485-8659-67b6a4130eeb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-48c06af0-c2d0-4485-8659-67b6a4130eeb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69092e8d-44aa-40d4-8b83-358bcb222cf3' class='xr-var-data-in' type='checkbox'><label for='data-69092e8d-44aa-40d4-8b83-358bcb222cf3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><pre>[382720 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-176c19ed-6d27-4476-8d0b-6317d8057b75' class='xr-section-summary-in' type='checkbox'  ><label for='section-176c19ed-6d27-4476-8d0b-6317d8057b75' class='xr-section-summary' >Attributes: <span>(165)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>history :</span></dt><dd>Thu Jul 21 14:17:08 2022: cdo remapnn,grid.des regcmensble.nc regcmensble_remap.nc\n",
       "Thu Jul 21 14:08:02 2022: cdo divc,3 final.nc regcmensble.nc\n",
       "Thu Jul 21 14:06:30 2022: cdo -add miroc5_pr_197001-200512.nc -add mpiesm_pr_197001-200512.nc noresm_pr_197001-200512.nc final.nc\n",
       "Mon Jun 27 15:34:28 2022: cdo mergetime pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_197001-198012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_198101-199012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_199101-200012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_200101-200512.nc miroc5_pr_197001-200512.nc\n",
       "2018-05-11 16:23:33 : Created by RegCM RegCM Model program</dd><dt><span>source :</span></dt><dd>RegCM Model output file</dd><dt><span>institution :</span></dt><dd>Oak Ridge National Laboratory</dd><dt><span>project_id :</span></dt><dd>CORDEX</dd><dt><span>ipcc_scenario_code :</span></dt><dd>HISTORICAL</dd><dt><span>institute_id :</span></dt><dd>ORNL</dd><dt><span>note :</span></dt><dd>The domain is larger than WAS-22</dd><dt><span>comment :</span></dt><dd>RegCM CORDEX SAsia25 run</dd><dt><span>experiment :</span></dt><dd>WAS-22</dd><dt><span>driving_model_ensemble_member :</span></dt><dd>r1i1p1</dd><dt><span>creation_date :</span></dt><dd>2019-09-12T16:23:22Z</dd><dt><span>CORDEX_domain :</span></dt><dd>WAS-22</dd><dt><span>rcm_version_id :</span></dt><dd>v0</dd><dt><span>ICTP_version_note :</span></dt><dd>Model run at ORNL on Titan</dd><dt><span>contact :</span></dt><dd>mashfaq@ornl.gov</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>tracking_id :</span></dt><dd>635194b8-8309-11e9-827b-f04da273f023</dd><dt><span>title :</span></dt><dd>ICTP Regional Climatic model V4</dd><dt><span>references :</span></dt><dd>http://gforge.ictp.it/gf/project/regcm</dd><dt><span>model_revision :</span></dt><dd>tag-4.7.0</dd><dt><span>projection :</span></dt><dd>ROTMER</dd><dt><span>grid_size_in_meters :</span></dt><dd>25000.0</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>13.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>70.0</dd><dt><span>grid_north_pole_latitude :</span></dt><dd>13.0</dd><dt><span>grid_north_pole_longitude :</span></dt><dd>70.0</dd><dt><span>grid_factor :</span></dt><dd>0.0</dd><dt><span>landsurface_model :</span></dt><dd>clm4.5</dd><dt><span>model_icbc_data_source :</span></dt><dd>MI_85</dd><dt><span>model_sst_data_source :</span></dt><dd>MI_85</dd><dt><span>boundary_nspgx :</span></dt><dd>30</dd><dt><span>boundary_nspgd :</span></dt><dd>30</dd><dt><span>boundary_high_nudge :</span></dt><dd>8.0</dd><dt><span>boundary_medium_nudge :</span></dt><dd>6.0</dd><dt><span>boundary_low_nudge :</span></dt><dd>4.0</dd><dt><span>boundary_nm :</span></dt><dd>-1.0</dd><dt><span>boundary_dm :</span></dt><dd>-1.0</dd><dt><span>model_is_restarted :</span></dt><dd>No</dd><dt><span>model_simulation_initial_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_end :</span></dt><dd> 1975-01-01 00:00:00 UTC</dd><dt><span>atmosphere_time_step_in_seconds :</span></dt><dd>40.0</dd><dt><span>surface_interaction_time_step_in_seconds :</span></dt><dd>480.0</dd><dt><span>convection_time_step_in_seconds :</span></dt><dd>240.0</dd><dt><span>radiation_scheme_time_step_in_seconds :</span></dt><dd>1800.0</dd><dt><span>absorption_emission_time_step_in_seconds :</span></dt><dd>64800.0</dd><dt><span>dynamical_core :</span></dt><dd>1</dd><dt><span>asselin_filter_nu_1 :</span></dt><dd>0.0625</dd><dt><span>asselin_filter_nu_2 :</span></dt><dd>0.0625</dd><dt><span>diffusion_hgt_factor :</span></dt><dd>1</dd><dt><span>upstream_mode :</span></dt><dd>Yes</dd><dt><span>off_centering_max :</span></dt><dd>0.25</dd><dt><span>stability_enhance :</span></dt><dd>Yes</dd><dt><span>temperature_extreme_gradient :</span></dt><dd>5.0</dd><dt><span>cloud_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>vapor_extreme_gradient_fraction :</span></dt><dd>0.2</dd><dt><span>tracer_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>lateral_boundary_condition_scheme :</span></dt><dd>5</dd><dt><span>semi_lagrangian_advection_scheme :</span></dt><dd>0</dd><dt><span>boundary_layer_scheme :</span></dt><dd>2</dd><dt><span>cumulus_convection_scheme_lnd :</span></dt><dd>4</dd><dt><span>cumulus_convection_scheme_ocn :</span></dt><dd>5</dd><dt><span>moisture_scheme :</span></dt><dd>1</dd><dt><span>ocean_flux_scheme :</span></dt><dd>2</dd><dt><span>zeng_ocean_roughness_formula :</span></dt><dd>1</dd><dt><span>zeng_ocean_roughness_method :</span></dt><dd>1</dd><dt><span>pressure_gradient_scheme :</span></dt><dd>0</dd><dt><span>surface_emissivity_factor_computed :</span></dt><dd>0</dd><dt><span>lake_model_activated :</span></dt><dd>0</dd><dt><span>chemical_aerosol_scheme_activated :</span></dt><dd>0</dd><dt><span>diurnal_cycle_sst_scheme :</span></dt><dd>0</dd><dt><span>ocean_precipitaion_cooling_effect :</span></dt><dd>0</dd><dt><span>ocean_albedo_from_whitecapping :</span></dt><dd>0</dd><dt><span>simple_sea_ice_scheme :</span></dt><dd>0</dd><dt><span>seasonal_desert_albedo :</span></dt><dd>0</dd><dt><span>convective_lwp_as_large_scale :</span></dt><dd>0</dd><dt><span>large_scale_cloud_fraction_scheme :</span></dt><dd>0</dd><dt><span>ocean_stratiform_clouds_scheme :</span></dt><dd>1</dd><dt><span>rrtm_radiation_scheme_activated :</span></dt><dd>0</dd><dt><span>climatic_ozone_input_dataset :</span></dt><dd>0</dd><dt><span>climatic_aerosol_input_dataset :</span></dt><dd>0</dd><dt><span>static_solar_constant_used :</span></dt><dd>0</dd><dt><span>cumulus_cloud_model :</span></dt><dd>1</dd><dt><span>sun_year_offset :</span></dt><dd>0.0</dd><dt><span>fix_solar_parameters :</span></dt><dd>0</dd><dt><span>cloud_bottom_level_with_no_clouds :</span></dt><dd>1</dd><dt><span>cloud_rh_with_fcc_one :</span></dt><dd>1.01</dd><dt><span>cloud_rh_threshold_for_land :</span></dt><dd>0.8</dd><dt><span>cloud_rh_threshold_for_ocean :</span></dt><dd>0.9</dd><dt><span>cloud_rh1_limit_temperature :</span></dt><dd>238.0</dd><dt><span>cloud_cloud_fraction_maximum :</span></dt><dd>0.75</dd><dt><span>cloud_condensation_threshold :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_fraction_max_for_convection :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_liqwat_max_for_convection :</span></dt><dd>0.0003</dd><dt><span>cloud_shallow_convective_cf_param :</span></dt><dd>0.07</dd><dt><span>cloud_deep_convective_cf_param :</span></dt><dd>0.14</dd><dt><span>cloud_k2_convective_cf_param :</span></dt><dd>500.0</dd><dt><span>cloud_surface_radiation_hack :</span></dt><dd>No</dd><dt><span>cloud_arctic_cloud_correction :</span></dt><dd>Yes</dd><dt><span>subex_auto_conversion_rate_for_land :</span></dt><dd>0.00025</dd><dt><span>subex_auto_conversion_rate_for_ocean :</span></dt><dd>0.00025</dd><dt><span>subex_gultepe_factor_when_rain_for_land :</span></dt><dd>0.4</dd><dt><span>subex_gultepe_factor_when_rain_for_ocean :</span></dt><dd>0.4</dd><dt><span>subex_land_raindrop_evaporation_rate :</span></dt><dd>0.0002</dd><dt><span>subex_ocean_raindrop_evaporation_rate :</span></dt><dd>0.0001</dd><dt><span>subex_land_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>subex_ocean_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>mit_lowest_convection_sigma :</span></dt><dd>0.95</dd><dt><span>mit_autoconversion_threshold_mixing_over_ocean :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_mixing_over_land :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_temperature :</span></dt><dd>-55.0</dd><dt><span>mit_mixing_coefficient_in_entrainment :</span></dt><dd>1.5</dd><dt><span>mit_fractional_area_unsaturated_downdraft :</span></dt><dd>0.05</dd><dt><span>mit_fractional_precip_outside_cloud :</span></dt><dd>0.12</dd><dt><span>mit_pressure_velocity_of_rain :</span></dt><dd>50.0</dd><dt><span>mit_pressure_velocity_of_snow :</span></dt><dd>5.5</dd><dt><span>mit_rain_evaporation_coefficient :</span></dt><dd>1.0</dd><dt><span>mit_snow_evaporation_coefficient :</span></dt><dd>0.8</dd><dt><span>mit_momentum_transport_coefficient :</span></dt><dd>0.7</dd><dt><span>mit_downdraft_velocity_coefficient :</span></dt><dd>10.0</dd><dt><span>mit_max_parcel_neg_temp_perturbation :</span></dt><dd>0.9</dd><dt><span>mit_approach_rate_quasi_eq_coeff_a :</span></dt><dd>0.2</dd><dt><span>mit_approach_rate_quasi_eq_coeff_d :</span></dt><dd>0.1</dd><dt><span>mit_maximum_land_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>mit_maximum_ocean_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>tiedtke_actual_scheme :</span></dt><dd>4</dd><dt><span>tiedtke_entrainment_rate_downdraft :</span></dt><dd>0.0003</dd><dt><span>tiedtke_entrainment_rate_deep_land :</span></dt><dd>0.00075</dd><dt><span>tiedtke_entrainment_rate_deep_ocean :</span></dt><dd>0.00075</dd><dt><span>tiedtke_penetrative :</span></dt><dd>Yes</dd><dt><span>tiedtke_midlevel :</span></dt><dd>Yes</dd><dt><span>tiedtke_shallow :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_downdraft :</span></dt><dd>Yes</dd><dt><span>tiedtke_prognostic_cloud :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_friction :</span></dt><dd>Yes</dd><dt><span>tiedtke_ke_dissipation :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_transport :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_smooth_massflux :</span></dt><dd>No</dd><dt><span>tiedtke_shallow_wstar_closure :</span></dt><dd>No</dd><dt><span>tiedtke_detrainment_rate_deep_land :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_detrainment_rate_deep_ocean :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_shallow_entrainment :</span></dt><dd>2.0</dd><dt><span>tiedtke_cloud_cover_evap_over_land :</span></dt><dd>0.05</dd><dt><span>tiedtke_cloud_cover_evap_over_ocean :</span></dt><dd>0.05</dd><dt><span>tiedtke_coeff_evap_over_land :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_coeff_evap_over_ocean :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_critical_rh_over_land :</span></dt><dd>0.9</dd><dt><span>tiedtke_critical_rh_over_ocean :</span></dt><dd>0.9</dd><dt><span>tiedtke_cloud_water_conv_over_land :</span></dt><dd>0.03</dd><dt><span>tiedtke_cloud_water_conv_over_ocean :</span></dt><dd>0.0014</dd><dt><span>tiedtke_cape_adjustment_timescale :</span></dt><dd>2400.0</dd><dt><span>uwpbl_advection_scheme :</span></dt><dd>0</dd><dt><span>uwpbl_cloud_evap_entr_incr_efficiency :</span></dt><dd>15.0</dd><dt><span>uwpbl_eddy_LS_stable_PBL_scaling :</span></dt><dd>1.5</dd><dt><span>uwpbl_czero :</span></dt><dd>5.869</dd><dt><span>uwpbl_nuk :</span></dt><dd>5.0</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>driving_experiment :</span></dt><dd>MIROC-MIROC5, historical, r1i1p1</dd><dt><span>driving_model_id :</span></dt><dd>MIROC-MIROC5</dd><dt><span>driving_experiment_name :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>ICTP-RegCM4-7</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.9rc1 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (time: 299, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-01-16T12:00:00 ... 2005-11-16\n",
       "  * lon        (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat        (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1981-01-01 00:00:00 ... 2005-12-01 00:00:00\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 21 14:17:08 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment:                              MIROC-MIROC5, historical...\n",
       "    driving_model_id:                                MIROC-MIROC5\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    CDO:                                             Climate Data Operators v..."
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#to select the year from 1980 to 2015\n",
    "data = data.sel(time=slice('1981-01-16T12:00:00.000000000','2005-12-16T00:00:00.000000000'))\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c811b0f2",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 100, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-06-16 ... 2005-09-16\n",
       "  * lon        (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat        (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
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       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 21 14:17:08 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment:                              MIROC-MIROC5, historical...\n",
       "    driving_model_id:                                MIROC-MIROC5\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    CDO:                                             Climate Data Operators v...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-2c45d7d3-1865-4912-821e-d9887c113985' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2c45d7d3-1865-4912-821e-d9887c113985' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 100</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 32</li><li><span class='xr-has-index'>lat</span>: 40</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d4513114-5826-4dc4-9387-eb9e1f0499cb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d4513114-5826-4dc4-9387-eb9e1f0499cb' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1981-06-16 ... 2005-09-16</div><input id='attrs-5cf09a28-8410-432e-a9a7-4984a97eeece' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5cf09a28-8410-432e-a9a7-4984a97eeece' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7341fbe4-945f-4813-999c-80069ae73110' class='xr-var-data-in' type='checkbox'><label for='data-7341fbe4-945f-4813-999c-80069ae73110' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-06-16T00:00:00.000000000&#x27;, &#x27;1981-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1981-08-16T12:00:00.000000000&#x27;, &#x27;1981-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-06-16T00:00:00.000000000&#x27;, &#x27;1982-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1982-08-16T12:00:00.000000000&#x27;, &#x27;1982-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-06-16T00:00:00.000000000&#x27;, &#x27;1983-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1983-08-16T12:00:00.000000000&#x27;, &#x27;1983-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-06-16T00:00:00.000000000&#x27;, &#x27;1984-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1984-08-16T12:00:00.000000000&#x27;, &#x27;1984-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-06-16T00:00:00.000000000&#x27;, &#x27;1985-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1985-08-16T12:00:00.000000000&#x27;, &#x27;1985-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-06-16T00:00:00.000000000&#x27;, &#x27;1986-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1986-08-16T12:00:00.000000000&#x27;, &#x27;1986-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-06-16T00:00:00.000000000&#x27;, &#x27;1987-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1987-08-16T12:00:00.000000000&#x27;, &#x27;1987-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-06-16T00:00:00.000000000&#x27;, &#x27;1988-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1988-08-16T12:00:00.000000000&#x27;, &#x27;1988-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-06-16T00:00:00.000000000&#x27;, &#x27;1989-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1989-08-16T12:00:00.000000000&#x27;, &#x27;1989-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-06-16T00:00:00.000000000&#x27;, &#x27;1990-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1990-08-16T12:00:00.000000000&#x27;, &#x27;1990-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-06-16T00:00:00.000000000&#x27;, &#x27;1991-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1991-08-16T12:00:00.000000000&#x27;, &#x27;1991-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-06-16T00:00:00.000000000&#x27;, &#x27;1992-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1992-08-16T12:00:00.000000000&#x27;, &#x27;1992-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-06-16T00:00:00.000000000&#x27;, &#x27;1993-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1993-08-16T12:00:00.000000000&#x27;, &#x27;1993-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-06-16T00:00:00.000000000&#x27;, &#x27;1994-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1994-08-16T12:00:00.000000000&#x27;, &#x27;1994-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-06-16T00:00:00.000000000&#x27;, &#x27;1995-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1995-08-16T12:00:00.000000000&#x27;, &#x27;1995-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-06-16T00:00:00.000000000&#x27;, &#x27;1996-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1996-08-16T12:00:00.000000000&#x27;, &#x27;1996-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-06-16T00:00:00.000000000&#x27;, &#x27;1997-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1997-08-16T12:00:00.000000000&#x27;, &#x27;1997-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-06-16T00:00:00.000000000&#x27;, &#x27;1998-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1998-08-16T12:00:00.000000000&#x27;, &#x27;1998-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-06-16T00:00:00.000000000&#x27;, &#x27;1999-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1999-08-16T12:00:00.000000000&#x27;, &#x27;1999-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-16T00:00:00.000000000&#x27;, &#x27;2000-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2000-08-16T12:00:00.000000000&#x27;, &#x27;2000-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-06-16T00:00:00.000000000&#x27;, &#x27;2001-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2001-08-16T12:00:00.000000000&#x27;, &#x27;2001-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-16T00:00:00.000000000&#x27;, &#x27;2002-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-16T12:00:00.000000000&#x27;, &#x27;2002-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-16T00:00:00.000000000&#x27;, &#x27;2003-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-16T12:00:00.000000000&#x27;, &#x27;2003-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-16T00:00:00.000000000&#x27;, &#x27;2004-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-16T12:00:00.000000000&#x27;, &#x27;2004-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-16T00:00:00.000000000&#x27;, &#x27;2005-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2005-08-16T12:00:00.000000000&#x27;, &#x27;2005-09-16T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>86.12 86.38 86.62 ... 93.62 93.88</div><input id='attrs-d1c3681e-6867-4e3c-8d2f-c6cf8184176c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d1c3681e-6867-4e3c-8d2f-c6cf8184176c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a409840a-2f60-4981-8674-4589e808a62a' class='xr-var-data-in' type='checkbox'><label for='data-a409840a-2f60-4981-8674-4589e808a62a' title='Show/Hide data 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-4b1b7678-e180-4b86-b8e9-118bd583cd9f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b1b7678-e180-4b86-b8e9-118bd583cd9f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16f90053-0bb6-4b2a-b356-dc467d4666d6' class='xr-var-data-in' type='checkbox'><label for='data-16f90053-0bb6-4b2a-b356-dc467d4666d6' title='Show/Hide data 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-be0dd85a-cc8e-4fbe-87b1-0121eb495e4d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-be0dd85a-cc8e-4fbe-87b1-0121eb495e4d' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1981-06-01 00:00:00 ... 2005-10-...</div><input id='attrs-ad27b9f2-3779-4367-bc14-779ddd8cc668' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ad27b9f2-3779-4367-bc14-779ddd8cc668' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26f55beb-4848-44c5-b00e-827b991bd74a' class='xr-var-data-in' type='checkbox'><label for='data-26f55beb-4848-44c5-b00e-827b991bd74a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[cftime.DatetimeNoLeap(1981, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1981, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1981, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1981, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1981, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1982, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1982, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1982, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1982, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1982, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1982, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1982, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1982, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1983, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1983, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1983, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1983, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1983, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1983, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1983, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1983, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1984, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1984, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1984, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1984, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1984, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1984, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1984, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1984, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1985, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1985, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1985, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1985, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1985, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1985, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1985, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1985, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1986, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1986, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1986, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1986, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1986, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1986, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1986, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1986, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1987, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1987, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1987, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1987, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1987, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1987, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1987, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1987, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1988, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1988, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1988, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1988, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1988, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1988, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1988, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1988, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1989, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1989, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1989, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1989, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1989, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1989, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1989, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1989, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1990, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1990, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1990, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1990, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1990, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1990, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1990, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1990, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1991, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1991, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1991, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1991, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1991, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1991, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1991, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1991, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1992, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1992, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1992, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1992, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1992, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1992, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1992, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1992, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1993, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1993, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1993, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1993, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1993, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1993, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1993, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1993, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1994, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1994, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1994, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1994, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1994, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1994, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1994, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1994, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1995, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1995, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1995, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1995, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1995, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1995, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1995, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1995, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1996, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1996, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1996, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1996, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1996, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1996, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1996, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1996, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1997, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1997, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1997, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1997, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1997, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1997, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1997, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1997, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1998, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1998, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1999, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1999, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2000, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2000, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2001, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2001, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2002, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2002, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2003, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2003, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2004, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2004, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 10, 1, 0, 0, 0, 0, has_year_zero=True)]],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d7e53c4f-977d-4212-b1e9-c17b00ece923' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7e53c4f-977d-4212-b1e9-c17b00ece923' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc8e7d88-5361-4b26-b59f-c0a4968b44e1' class='xr-var-data-in' type='checkbox'><label for='data-bc8e7d88-5361-4b26-b59f-c0a4968b44e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><pre>[128000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c58beac6-53cc-4ef2-9dde-030a06701093' class='xr-section-summary-in' type='checkbox'  ><label for='section-c58beac6-53cc-4ef2-9dde-030a06701093' class='xr-section-summary' >Attributes: <span>(165)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>history :</span></dt><dd>Thu Jul 21 14:17:08 2022: cdo remapnn,grid.des regcmensble.nc regcmensble_remap.nc\n",
       "Thu Jul 21 14:08:02 2022: cdo divc,3 final.nc regcmensble.nc\n",
       "Thu Jul 21 14:06:30 2022: cdo -add miroc5_pr_197001-200512.nc -add mpiesm_pr_197001-200512.nc noresm_pr_197001-200512.nc final.nc\n",
       "Mon Jun 27 15:34:28 2022: cdo mergetime pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_197001-198012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_198101-199012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_199101-200012.nc pr_WAS-22_MIROC-MIROC5_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_200101-200512.nc miroc5_pr_197001-200512.nc\n",
       "2018-05-11 16:23:33 : Created by RegCM RegCM Model program</dd><dt><span>source :</span></dt><dd>RegCM Model output file</dd><dt><span>institution :</span></dt><dd>Oak Ridge National Laboratory</dd><dt><span>project_id :</span></dt><dd>CORDEX</dd><dt><span>ipcc_scenario_code :</span></dt><dd>HISTORICAL</dd><dt><span>institute_id :</span></dt><dd>ORNL</dd><dt><span>note :</span></dt><dd>The domain is larger than WAS-22</dd><dt><span>comment :</span></dt><dd>RegCM CORDEX SAsia25 run</dd><dt><span>experiment :</span></dt><dd>WAS-22</dd><dt><span>driving_model_ensemble_member :</span></dt><dd>r1i1p1</dd><dt><span>creation_date :</span></dt><dd>2019-09-12T16:23:22Z</dd><dt><span>CORDEX_domain :</span></dt><dd>WAS-22</dd><dt><span>rcm_version_id :</span></dt><dd>v0</dd><dt><span>ICTP_version_note :</span></dt><dd>Model run at ORNL on Titan</dd><dt><span>contact :</span></dt><dd>mashfaq@ornl.gov</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>tracking_id :</span></dt><dd>635194b8-8309-11e9-827b-f04da273f023</dd><dt><span>title :</span></dt><dd>ICTP Regional Climatic model V4</dd><dt><span>references :</span></dt><dd>http://gforge.ictp.it/gf/project/regcm</dd><dt><span>model_revision :</span></dt><dd>tag-4.7.0</dd><dt><span>projection :</span></dt><dd>ROTMER</dd><dt><span>grid_size_in_meters :</span></dt><dd>25000.0</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>13.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>70.0</dd><dt><span>grid_north_pole_latitude :</span></dt><dd>13.0</dd><dt><span>grid_north_pole_longitude :</span></dt><dd>70.0</dd><dt><span>grid_factor :</span></dt><dd>0.0</dd><dt><span>landsurface_model :</span></dt><dd>clm4.5</dd><dt><span>model_icbc_data_source :</span></dt><dd>MI_85</dd><dt><span>model_sst_data_source :</span></dt><dd>MI_85</dd><dt><span>boundary_nspgx :</span></dt><dd>30</dd><dt><span>boundary_nspgd :</span></dt><dd>30</dd><dt><span>boundary_high_nudge :</span></dt><dd>8.0</dd><dt><span>boundary_medium_nudge :</span></dt><dd>6.0</dd><dt><span>boundary_low_nudge :</span></dt><dd>4.0</dd><dt><span>boundary_nm :</span></dt><dd>-1.0</dd><dt><span>boundary_dm :</span></dt><dd>-1.0</dd><dt><span>model_is_restarted :</span></dt><dd>No</dd><dt><span>model_simulation_initial_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_end :</span></dt><dd> 1975-01-01 00:00:00 UTC</dd><dt><span>atmosphere_time_step_in_seconds :</span></dt><dd>40.0</dd><dt><span>surface_interaction_time_step_in_seconds :</span></dt><dd>480.0</dd><dt><span>convection_time_step_in_seconds :</span></dt><dd>240.0</dd><dt><span>radiation_scheme_time_step_in_seconds :</span></dt><dd>1800.0</dd><dt><span>absorption_emission_time_step_in_seconds :</span></dt><dd>64800.0</dd><dt><span>dynamical_core :</span></dt><dd>1</dd><dt><span>asselin_filter_nu_1 :</span></dt><dd>0.0625</dd><dt><span>asselin_filter_nu_2 :</span></dt><dd>0.0625</dd><dt><span>diffusion_hgt_factor :</span></dt><dd>1</dd><dt><span>upstream_mode :</span></dt><dd>Yes</dd><dt><span>off_centering_max :</span></dt><dd>0.25</dd><dt><span>stability_enhance :</span></dt><dd>Yes</dd><dt><span>temperature_extreme_gradient :</span></dt><dd>5.0</dd><dt><span>cloud_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>vapor_extreme_gradient_fraction :</span></dt><dd>0.2</dd><dt><span>tracer_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>lateral_boundary_condition_scheme :</span></dt><dd>5</dd><dt><span>semi_lagrangian_advection_scheme :</span></dt><dd>0</dd><dt><span>boundary_layer_scheme :</span></dt><dd>2</dd><dt><span>cumulus_convection_scheme_lnd :</span></dt><dd>4</dd><dt><span>cumulus_convection_scheme_ocn :</span></dt><dd>5</dd><dt><span>moisture_scheme :</span></dt><dd>1</dd><dt><span>ocean_flux_scheme :</span></dt><dd>2</dd><dt><span>zeng_ocean_roughness_formula :</span></dt><dd>1</dd><dt><span>zeng_ocean_roughness_method :</span></dt><dd>1</dd><dt><span>pressure_gradient_scheme :</span></dt><dd>0</dd><dt><span>surface_emissivity_factor_computed :</span></dt><dd>0</dd><dt><span>lake_model_activated :</span></dt><dd>0</dd><dt><span>chemical_aerosol_scheme_activated :</span></dt><dd>0</dd><dt><span>diurnal_cycle_sst_scheme :</span></dt><dd>0</dd><dt><span>ocean_precipitaion_cooling_effect :</span></dt><dd>0</dd><dt><span>ocean_albedo_from_whitecapping :</span></dt><dd>0</dd><dt><span>simple_sea_ice_scheme :</span></dt><dd>0</dd><dt><span>seasonal_desert_albedo :</span></dt><dd>0</dd><dt><span>convective_lwp_as_large_scale :</span></dt><dd>0</dd><dt><span>large_scale_cloud_fraction_scheme :</span></dt><dd>0</dd><dt><span>ocean_stratiform_clouds_scheme :</span></dt><dd>1</dd><dt><span>rrtm_radiation_scheme_activated :</span></dt><dd>0</dd><dt><span>climatic_ozone_input_dataset :</span></dt><dd>0</dd><dt><span>climatic_aerosol_input_dataset :</span></dt><dd>0</dd><dt><span>static_solar_constant_used :</span></dt><dd>0</dd><dt><span>cumulus_cloud_model :</span></dt><dd>1</dd><dt><span>sun_year_offset :</span></dt><dd>0.0</dd><dt><span>fix_solar_parameters :</span></dt><dd>0</dd><dt><span>cloud_bottom_level_with_no_clouds :</span></dt><dd>1</dd><dt><span>cloud_rh_with_fcc_one :</span></dt><dd>1.01</dd><dt><span>cloud_rh_threshold_for_land :</span></dt><dd>0.8</dd><dt><span>cloud_rh_threshold_for_ocean :</span></dt><dd>0.9</dd><dt><span>cloud_rh1_limit_temperature :</span></dt><dd>238.0</dd><dt><span>cloud_cloud_fraction_maximum :</span></dt><dd>0.75</dd><dt><span>cloud_condensation_threshold :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_fraction_max_for_convection :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_liqwat_max_for_convection :</span></dt><dd>0.0003</dd><dt><span>cloud_shallow_convective_cf_param :</span></dt><dd>0.07</dd><dt><span>cloud_deep_convective_cf_param :</span></dt><dd>0.14</dd><dt><span>cloud_k2_convective_cf_param :</span></dt><dd>500.0</dd><dt><span>cloud_surface_radiation_hack :</span></dt><dd>No</dd><dt><span>cloud_arctic_cloud_correction :</span></dt><dd>Yes</dd><dt><span>subex_auto_conversion_rate_for_land :</span></dt><dd>0.00025</dd><dt><span>subex_auto_conversion_rate_for_ocean :</span></dt><dd>0.00025</dd><dt><span>subex_gultepe_factor_when_rain_for_land :</span></dt><dd>0.4</dd><dt><span>subex_gultepe_factor_when_rain_for_ocean :</span></dt><dd>0.4</dd><dt><span>subex_land_raindrop_evaporation_rate :</span></dt><dd>0.0002</dd><dt><span>subex_ocean_raindrop_evaporation_rate :</span></dt><dd>0.0001</dd><dt><span>subex_land_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>subex_ocean_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>mit_lowest_convection_sigma :</span></dt><dd>0.95</dd><dt><span>mit_autoconversion_threshold_mixing_over_ocean :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_mixing_over_land :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_temperature :</span></dt><dd>-55.0</dd><dt><span>mit_mixing_coefficient_in_entrainment :</span></dt><dd>1.5</dd><dt><span>mit_fractional_area_unsaturated_downdraft :</span></dt><dd>0.05</dd><dt><span>mit_fractional_precip_outside_cloud :</span></dt><dd>0.12</dd><dt><span>mit_pressure_velocity_of_rain :</span></dt><dd>50.0</dd><dt><span>mit_pressure_velocity_of_snow :</span></dt><dd>5.5</dd><dt><span>mit_rain_evaporation_coefficient :</span></dt><dd>1.0</dd><dt><span>mit_snow_evaporation_coefficient :</span></dt><dd>0.8</dd><dt><span>mit_momentum_transport_coefficient :</span></dt><dd>0.7</dd><dt><span>mit_downdraft_velocity_coefficient :</span></dt><dd>10.0</dd><dt><span>mit_max_parcel_neg_temp_perturbation :</span></dt><dd>0.9</dd><dt><span>mit_approach_rate_quasi_eq_coeff_a :</span></dt><dd>0.2</dd><dt><span>mit_approach_rate_quasi_eq_coeff_d :</span></dt><dd>0.1</dd><dt><span>mit_maximum_land_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>mit_maximum_ocean_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>tiedtke_actual_scheme :</span></dt><dd>4</dd><dt><span>tiedtke_entrainment_rate_downdraft :</span></dt><dd>0.0003</dd><dt><span>tiedtke_entrainment_rate_deep_land :</span></dt><dd>0.00075</dd><dt><span>tiedtke_entrainment_rate_deep_ocean :</span></dt><dd>0.00075</dd><dt><span>tiedtke_penetrative :</span></dt><dd>Yes</dd><dt><span>tiedtke_midlevel :</span></dt><dd>Yes</dd><dt><span>tiedtke_shallow :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_downdraft :</span></dt><dd>Yes</dd><dt><span>tiedtke_prognostic_cloud :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_friction :</span></dt><dd>Yes</dd><dt><span>tiedtke_ke_dissipation :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_transport :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_smooth_massflux :</span></dt><dd>No</dd><dt><span>tiedtke_shallow_wstar_closure :</span></dt><dd>No</dd><dt><span>tiedtke_detrainment_rate_deep_land :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_detrainment_rate_deep_ocean :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_shallow_entrainment :</span></dt><dd>2.0</dd><dt><span>tiedtke_cloud_cover_evap_over_land :</span></dt><dd>0.05</dd><dt><span>tiedtke_cloud_cover_evap_over_ocean :</span></dt><dd>0.05</dd><dt><span>tiedtke_coeff_evap_over_land :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_coeff_evap_over_ocean :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_critical_rh_over_land :</span></dt><dd>0.9</dd><dt><span>tiedtke_critical_rh_over_ocean :</span></dt><dd>0.9</dd><dt><span>tiedtke_cloud_water_conv_over_land :</span></dt><dd>0.03</dd><dt><span>tiedtke_cloud_water_conv_over_ocean :</span></dt><dd>0.0014</dd><dt><span>tiedtke_cape_adjustment_timescale :</span></dt><dd>2400.0</dd><dt><span>uwpbl_advection_scheme :</span></dt><dd>0</dd><dt><span>uwpbl_cloud_evap_entr_incr_efficiency :</span></dt><dd>15.0</dd><dt><span>uwpbl_eddy_LS_stable_PBL_scaling :</span></dt><dd>1.5</dd><dt><span>uwpbl_czero :</span></dt><dd>5.869</dd><dt><span>uwpbl_nuk :</span></dt><dd>5.0</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>driving_experiment :</span></dt><dd>MIROC-MIROC5, historical, r1i1p1</dd><dt><span>driving_model_id :</span></dt><dd>MIROC-MIROC5</dd><dt><span>driving_experiment_name :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>ICTP-RegCM4-7</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.9rc1 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (time: 100, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-06-16 ... 2005-09-16\n",
       "  * lon        (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat        (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1981-06-01 00:00:00 ... 2005-10-01 00:00:00\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 21 14:17:08 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment:                              MIROC-MIROC5, historical...\n",
       "    driving_model_id:                                MIROC-MIROC5\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    CDO:                                             Climate Data Operators v..."
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#selecting only JJAS months\n",
    "\n",
    "def is_jjas(month):\n",
    "    return (month >= 6) & (month <= 9)\n",
    "\n",
    "jjas_data = data.sel(time=is_jjas(data['time.month']))\n",
    "\n",
    "jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "17f8e12a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#data.x.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5d9405f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "#interpolating to low resolution \n",
    "#new_lon=np.arange(86,94,0.5)\n",
    "#new_lat=np.arange(17,28,.5)\n",
    "#jjas_data = jjas_data.interp(lon=new_lon,lat=new_lat)\n",
    "#jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "be94f5d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#jjas_data.x.values\n",
    "#jjas_data.y.values\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a41e4a60",
   "metadata": {},
   "outputs": [],
   "source": [
    "#to select the x and y coordinates\n",
    "#jjas_data = jjas_data.sel(x=slice(1000000.,5275000.),y=slice(2000000.,4175000.))\n",
    "#jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "18269e45",
   "metadata": {},
   "outputs": [
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       "  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",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
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       "\n",
       ".xr-var-dims {\n",
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       "\n",
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       "  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",
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       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
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       "\n",
       ".xr-attrs,\n",
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       "  grid-column: 1 / -1;\n",
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       "\n",
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       "\n",
       ".xr-attrs dt,\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (lat: 40, lon: 32)&gt;\n",
       "array([[3.9603128e-05, 4.0292754e-05, 4.1846084e-05, ..., 7.1517825e-05,\n",
       "        6.6991641e-05, 7.0500530e-05],\n",
       "       [3.8418944e-05, 3.9147384e-05, 3.9580678e-05, ..., 7.5560907e-05,\n",
       "        7.3236130e-05, 7.1829920e-05],\n",
       "       [3.6612117e-05, 3.7486705e-05, 3.7657341e-05, ..., 8.5610365e-05,\n",
       "        8.1372018e-05, 8.5974789e-05],\n",
       "       ...,\n",
       "       [1.8407845e-04, 2.0547943e-04, 2.2842888e-04, ..., 2.0595801e-04,\n",
       "        2.1437595e-04, 1.8386221e-04],\n",
       "       [1.8978299e-04, 2.1626672e-04, 2.6339813e-04, ..., 1.8772749e-04,\n",
       "        2.3271758e-04, 2.4781871e-04],\n",
       "       [1.9796759e-04, 3.2225845e-04, 5.0131447e-04, ..., 1.8953896e-04,\n",
       "        2.5643263e-04, 3.0891492e-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-2ec52e9c-868d-4954-9174-2eff9e8f38a3' class='xr-array-in' type='checkbox' checked><label for='section-2ec52e9c-868d-4954-9174-2eff9e8f38a3' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>3.96e-05 4.029e-05 4.185e-05 ... 0.0001895 0.0002564 0.0003089</span></div><div class='xr-array-data'><pre>array([[3.9603128e-05, 4.0292754e-05, 4.1846084e-05, ..., 7.1517825e-05,\n",
       "        6.6991641e-05, 7.0500530e-05],\n",
       "       [3.8418944e-05, 3.9147384e-05, 3.9580678e-05, ..., 7.5560907e-05,\n",
       "        7.3236130e-05, 7.1829920e-05],\n",
       "       [3.6612117e-05, 3.7486705e-05, 3.7657341e-05, ..., 8.5610365e-05,\n",
       "        8.1372018e-05, 8.5974789e-05],\n",
       "       ...,\n",
       "       [1.8407845e-04, 2.0547943e-04, 2.2842888e-04, ..., 2.0595801e-04,\n",
       "        2.1437595e-04, 1.8386221e-04],\n",
       "       [1.8978299e-04, 2.1626672e-04, 2.6339813e-04, ..., 1.8772749e-04,\n",
       "        2.3271758e-04, 2.4781871e-04],\n",
       "       [1.9796759e-04, 3.2225845e-04, 5.0131447e-04, ..., 1.8953896e-04,\n",
       "        2.5643263e-04, 3.0891492e-04]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-101126e7-b6f3-4f52-9319-f029010bf9e5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-101126e7-b6f3-4f52-9319-f029010bf9e5' 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-3198138b-09b6-4494-a2ca-db031183f574' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3198138b-09b6-4494-a2ca-db031183f574' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-264298e2-2cdc-4b77-b009-ae8c95803738' class='xr-var-data-in' type='checkbox'><label for='data-264298e2-2cdc-4b77-b009-ae8c95803738' title='Show/Hide data 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-29278cbd-a171-4bd4-990e-65f5e040be7b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29278cbd-a171-4bd4-990e-65f5e040be7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1bfaab9-3cda-4a5d-941b-e10775291292' class='xr-var-data-in' type='checkbox'><label for='data-a1bfaab9-3cda-4a5d-941b-e10775291292' title='Show/Hide data 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-d8ade81c-f90e-4865-aa43-0e51be36e13c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d8ade81c-f90e-4865-aa43-0e51be36e13c' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'pr' (lat: 40, lon: 32)>\n",
       "array([[3.9603128e-05, 4.0292754e-05, 4.1846084e-05, ..., 7.1517825e-05,\n",
       "        6.6991641e-05, 7.0500530e-05],\n",
       "       [3.8418944e-05, 3.9147384e-05, 3.9580678e-05, ..., 7.5560907e-05,\n",
       "        7.3236130e-05, 7.1829920e-05],\n",
       "       [3.6612117e-05, 3.7486705e-05, 3.7657341e-05, ..., 8.5610365e-05,\n",
       "        8.1372018e-05, 8.5974789e-05],\n",
       "       ...,\n",
       "       [1.8407845e-04, 2.0547943e-04, 2.2842888e-04, ..., 2.0595801e-04,\n",
       "        2.1437595e-04, 1.8386221e-04],\n",
       "       [1.8978299e-04, 2.1626672e-04, 2.6339813e-04, ..., 1.8772749e-04,\n",
       "        2.3271758e-04, 2.4781871e-04],\n",
       "       [1.9796759e-04, 3.2225845e-04, 5.0131447e-04, ..., 1.8953896e-04,\n",
       "        2.5643263e-04, 3.0891492e-04]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#getting the mean for JJAS data\n",
    "jjas_mean = jjas_data.pr.mean('time')\n",
    " \n",
    "jjas_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6f88bd72",
   "metadata": {},
   "outputs": [
    {
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       ".xr-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",
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       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
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       "\n",
       ".xr-dim-list:before {\n",
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       "\n",
       ".xr-dim-list:after {\n",
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       "\n",
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       "  content: ',';\n",
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       "\n",
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       "\n",
       ".xr-var-list,\n",
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       "  display: contents;\n",
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       "\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",
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       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
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       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
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       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
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       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
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       "\n",
       ".xr-var-data > table {\n",
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       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
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       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (lat: 40, lon: 32)&gt;\n",
       "array([[ 3.42171028,  3.48129398,  3.61550166, ...,  6.17914007,\n",
       "         5.78807776,  6.09124575],\n",
       "       [ 3.31939679,  3.38233399,  3.4197706 , ...,  6.52846238,\n",
       "         6.32760159,  6.20610507],\n",
       "       [ 3.16328688,  3.23885131,  3.25359424, ...,  7.39673555,\n",
       "         7.03054236,  7.42822175],\n",
       "       ...,\n",
       "       [15.90437838, 17.75342287, 19.7362551 , ..., 17.79477247,\n",
       "        18.52208194, 15.88569512],\n",
       "       [16.39725063, 18.68544482, 22.75759885, ..., 16.21965528,\n",
       "        20.1067985 , 21.41153645],\n",
       "       [17.10439953, 27.84313001, 43.31357013, ..., 16.37616595,\n",
       "        22.15577904, 26.69024952]])\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-0521721a-eca1-417a-8aa8-5e0e6fb39db6' class='xr-array-in' type='checkbox' checked><label for='section-0521721a-eca1-417a-8aa8-5e0e6fb39db6' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>3.422 3.481 3.616 3.684 3.765 3.853 ... 23.98 18.73 16.38 22.16 26.69</span></div><div class='xr-array-data'><pre>array([[ 3.42171028,  3.48129398,  3.61550166, ...,  6.17914007,\n",
       "         5.78807776,  6.09124575],\n",
       "       [ 3.31939679,  3.38233399,  3.4197706 , ...,  6.52846238,\n",
       "         6.32760159,  6.20610507],\n",
       "       [ 3.16328688,  3.23885131,  3.25359424, ...,  7.39673555,\n",
       "         7.03054236,  7.42822175],\n",
       "       ...,\n",
       "       [15.90437838, 17.75342287, 19.7362551 , ..., 17.79477247,\n",
       "        18.52208194, 15.88569512],\n",
       "       [16.39725063, 18.68544482, 22.75759885, ..., 16.21965528,\n",
       "        20.1067985 , 21.41153645],\n",
       "       [17.10439953, 27.84313001, 43.31357013, ..., 16.37616595,\n",
       "        22.15577904, 26.69024952]])</pre></div></div></li><li class='xr-section-item'><input id='section-860bf725-fe0b-4074-b33f-ee2c5fa738d7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-860bf725-fe0b-4074-b33f-ee2c5fa738d7' 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-f6d07584-9b24-41a5-80eb-b3dc3cdccf8b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f6d07584-9b24-41a5-80eb-b3dc3cdccf8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5d7bf41-024e-4b5c-a422-7412cf5eb579' class='xr-var-data-in' type='checkbox'><label for='data-c5d7bf41-024e-4b5c-a422-7412cf5eb579' title='Show/Hide data 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-9400bdc3-2734-4c79-bb97-b7d7d1f19f3d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9400bdc3-2734-4c79-bb97-b7d7d1f19f3d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dda30029-4494-4bbe-8096-77edc49d230c' class='xr-var-data-in' type='checkbox'><label for='data-dda30029-4494-4bbe-8096-77edc49d230c' title='Show/Hide data 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-9afb3dd1-9605-4bae-ae11-844d905ca10f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9afb3dd1-9605-4bae-ae11-844d905ca10f' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'pr' (lat: 40, lon: 32)>\n",
       "array([[ 3.42171028,  3.48129398,  3.61550166, ...,  6.17914007,\n",
       "         5.78807776,  6.09124575],\n",
       "       [ 3.31939679,  3.38233399,  3.4197706 , ...,  6.52846238,\n",
       "         6.32760159,  6.20610507],\n",
       "       [ 3.16328688,  3.23885131,  3.25359424, ...,  7.39673555,\n",
       "         7.03054236,  7.42822175],\n",
       "       ...,\n",
       "       [15.90437838, 17.75342287, 19.7362551 , ..., 17.79477247,\n",
       "        18.52208194, 15.88569512],\n",
       "       [16.39725063, 18.68544482, 22.75759885, ..., 16.21965528,\n",
       "        20.1067985 , 21.41153645],\n",
       "       [17.10439953, 27.84313001, 43.31357013, ..., 16.37616595,\n",
       "        22.15577904, 26.69024952]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "miroc = jjas_mean*86400\n",
    "miroc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6c5c5811",
   "metadata": {},
   "outputs": [
    {
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       "}\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",
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       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
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       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
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       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
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       "\n",
       ".xr-var-list,\n",
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       "\n",
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       "  background-color: var(--xr-background-color-row-even);\n",
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       "  padding-right: 5px;\n",
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       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
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       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
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       "\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",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (lat: 40, lon: 32)&gt;\n",
       "array([[        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       ...,\n",
       "       [        nan,  7.63220637,  9.44363603, ...,  9.31336245,\n",
       "         8.6536707 ,         nan],\n",
       "       [        nan, 10.09162943, 15.59814354, ...,  8.69209628,\n",
       "        11.44012839,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 40</li><li><span class='xr-has-index'>lon</span>: 32</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-60ba06b2-9679-49f2-8318-4ebf4b8bd2fb' class='xr-array-in' type='checkbox' checked><label for='section-60ba06b2-9679-49f2-8318-4ebf4b8bd2fb' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>nan nan nan nan nan nan nan nan ... nan nan nan nan nan nan nan nan</span></div><div class='xr-array-data'><pre>array([[        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       ...,\n",
       "       [        nan,  7.63220637,  9.44363603, ...,  9.31336245,\n",
       "         8.6536707 ,         nan],\n",
       "       [        nan, 10.09162943, 15.59814354, ...,  8.69209628,\n",
       "        11.44012839,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan]])</pre></div></div></li><li class='xr-section-item'><input id='section-5218559a-4f0c-479d-95cb-b62ba2c7a8ba' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5218559a-4f0c-479d-95cb-b62ba2c7a8ba' 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-48d6c83a-7cf7-4dbb-9cd9-b93a703597ee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-48d6c83a-7cf7-4dbb-9cd9-b93a703597ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d3a8b9e-203b-4968-9fb3-9190a85cbee3' class='xr-var-data-in' type='checkbox'><label for='data-0d3a8b9e-203b-4968-9fb3-9190a85cbee3' title='Show/Hide data 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-b57e0365-0c5e-4920-8cff-e374fe9e6fb0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b57e0365-0c5e-4920-8cff-e374fe9e6fb0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecc22e64-7ea1-4215-b72f-16f7d99d8e4f' class='xr-var-data-in' type='checkbox'><label for='data-ecc22e64-7ea1-4215-b72f-16f7d99d8e4f' title='Show/Hide data 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-72152e99-8077-4c5b-8e3a-2c6d6f8d0fbf' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-72152e99-8077-4c5b-8e3a-2c6d6f8d0fbf' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (lat: 40, lon: 32)>\n",
       "array([[        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       ...,\n",
       "       [        nan,  7.63220637,  9.44363603, ...,  9.31336245,\n",
       "         8.6536707 ,         nan],\n",
       "       [        nan, 10.09162943, 15.59814354, ...,  8.69209628,\n",
       "        11.44012839,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bias = miroc - cru\n",
    "bias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "445388ed",
   "metadata": {},
   "outputs": [
    {
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       "\n",
       ".xr-section-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.DataArray (lat: 40, lon: 32)&gt;\n",
       "array([[         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       ...,\n",
       "       [         nan,  75.40799441,  91.75153548, ..., 109.80912887,\n",
       "         87.69061696,          nan],\n",
       "       [         nan, 117.42897623, 217.86774082, ..., 115.47031756,\n",
       "        132.00142896,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 40</li><li><span class='xr-has-index'>lon</span>: 32</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-d3be82d6-e637-4f34-9db3-605ca183c501' class='xr-array-in' type='checkbox' checked><label for='section-d3be82d6-e637-4f34-9db3-605ca183c501' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>nan nan nan nan nan nan nan nan ... nan nan nan nan nan nan nan nan</span></div><div class='xr-array-data'><pre>array([[         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       ...,\n",
       "       [         nan,  75.40799441,  91.75153548, ..., 109.80912887,\n",
       "         87.69061696,          nan],\n",
       "       [         nan, 117.42897623, 217.86774082, ..., 115.47031756,\n",
       "        132.00142896,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan]])</pre></div></div></li><li class='xr-section-item'><input id='section-ce85edb1-13fb-4cbe-a5f1-c68bff1f041a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ce85edb1-13fb-4cbe-a5f1-c68bff1f041a' 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-94d6b626-1a8d-478e-bbc7-945ee9032173' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94d6b626-1a8d-478e-bbc7-945ee9032173' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c518ee9-ca16-431b-afa7-fe75be059e61' class='xr-var-data-in' type='checkbox'><label for='data-4c518ee9-ca16-431b-afa7-fe75be059e61' title='Show/Hide data 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-29db65ec-b2eb-4561-9e3b-a36b1b9f7dec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29db65ec-b2eb-4561-9e3b-a36b1b9f7dec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e204f05c-2d73-4f81-9161-732be0f394f0' class='xr-var-data-in' type='checkbox'><label for='data-e204f05c-2d73-4f81-9161-732be0f394f0' title='Show/Hide data 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-a6c81dc1-1647-46cb-be5f-c183f6cb7726' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a6c81dc1-1647-46cb-be5f-c183f6cb7726' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (lat: 40, lon: 32)>\n",
       "array([[         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan],\n",
       "       ...,\n",
       "       [         nan,  75.40799441,  91.75153548, ..., 109.80912887,\n",
       "         87.69061696,          nan],\n",
       "       [         nan, 117.42897623, 217.86774082, ..., 115.47031756,\n",
       "        132.00142896,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bias_percentage = ((miroc - cru)/cru)*100\n",
    "bias_percentage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "08ba09cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x684 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting annual_pr_mean\n",
    "\n",
    "#plotting with cartopy\n",
    "import cartopy.feature as cfeature\n",
    "plt.rcParams['font.size'] = '16'\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize=(12,9.5))\n",
    "\n",
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "ax.set_extent([88,93,20,27])\n",
    "\n",
    "\n",
    "m1 = ax.contourf(bias['lon'], bias['lat'],bias[:,:],\n",
    "                levels=np.arange(-15,15+3,3),   transform = ccrs.PlateCarree(),cmap='BrBG',extend='both')\n",
    "\n",
    " \n",
    "# Define the xticks for longitude\n",
    "ax.set_xticks(np.arange(87,94,1), crs=ccrs.PlateCarree())\n",
    "lon_formatter = cticker.LongitudeFormatter()\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "\n",
    "# Define the yticks for latitude\n",
    "ax.set_yticks(np.arange(20,28,1), crs=ccrs.PlateCarree())\n",
    "lat_formatter = cticker.LatitudeFormatter()\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "\n",
    "\n",
    "plt.colorbar(m1,ticks=np.arange(-15,15+3,3),  orientation = 'horizontal',shrink=0.5, fraction = 0.04 , label = 'mm/day')\n",
    "ax.coastlines(linewidth=3)\n",
    "ax.add_feature(cfeature.BORDERS,linewidth=3)\n",
    "\n",
    "\n",
    "\n",
    "plt.title('Seasonal Bias(RegCM Ensemble avg-CRU)',fontsize=17)\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/Seasonal Bias(RegCM Ensemble avg-cru).png\")\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "9003db92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x972 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting bias percentage \n",
    "\n",
    "#plotting with cartopy\n",
    "import cartopy.feature as cfeature\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize=(16,13.5))\n",
    "\n",
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "ax.set_extent([88,93,20,27])\n",
    "\n",
    "\n",
    "m1 = ax.contourf(bias_percentage['lon'][:], bias_percentage['lat'][:],bias_percentage[:,:],\n",
    "                levels=np.arange(-150,150+25,25), transform = ccrs.PlateCarree(),cmap='BrBG',extend='both')\n",
    "\n",
    " \n",
    "# Define the xticks for longitude\n",
    "ax.set_xticks(np.arange(87,94,1), crs=ccrs.PlateCarree())\n",
    "lon_formatter = cticker.LongitudeFormatter()\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "\n",
    "# Define the yticks for latitude\n",
    "ax.set_yticks(np.arange(20,28,1), crs=ccrs.PlateCarree())\n",
    "lat_formatter = cticker.LatitudeFormatter()\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "\n",
    "\n",
    "plt.colorbar(m1,ticks=np.arange(-150,150+25,25), orientation = 'horizontal',shrink=0.7, fraction = 0.04 , label = 'percentage')\n",
    "ax.coastlines(linewidth=3)\n",
    "ax.add_feature(cfeature.BORDERS,linewidth=3)\n",
    " \n",
    "    \n",
    "plt.title('Seasonal Bias-Percentage(RegCM Ensemble avg-CRU)')\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/Seasonal Bias_percentage(RegCM Ensemble avg-cru).png\")\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "220503a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Colormap CET_D1A is not recognized. Possible values are: Accent, Accent_r, Blues, Blues_r, \\nBrBG, BrBG_r, BuGn, BuGn_r, BuPu, BuPu_r, CMRmap, CMRmap_r, Dark2, Dark2_r, GnBu, GnBu_r, Greens,\\nGreens_r, Greys, Greys_r, OrRd, OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, \\nPastel2_r, PiYG, PiYG_r, PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Purples_r, RdBu, RdBu_r, RdGy,\\nRdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, \\nSpectral_r, Wistia, Wistia_r, YlGn, YlGnBu, YlGnBu_r, YlGn_r, YlOrBr, YlOrBr_r, YlOrRd, YlOrRd_r, afmhot, afmhot_r, autumn,\\nautumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, cividis, cividis_r, cool, cool_r, coolwarm, coolwarm_r, \\ncopper, copper_r, cubehelix, cubehelix_r, flag, flag_r, gist_earth, gist_earth_r, gist_gray, gist_gray_r, gist_heat,\\ngist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r,\\ngnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r, hsv, hsv_r, inferno, inferno_r, jet, jet_r, magma,\\nmagma_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, \\nseismic, seismic_r, spring, spring_r, summer, summer_r, tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, \\nter'"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#cma colors\n",
    "'''Colormap CET_D1A is not recognized. Possible values are: Accent, Accent_r, Blues, Blues_r, \n",
    "BrBG, BrBG_r, BuGn, BuGn_r, BuPu, BuPu_r, CMRmap, CMRmap_r, Dark2, Dark2_r, GnBu, GnBu_r, Greens,\n",
    "Greens_r, Greys, Greys_r, OrRd, OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, \n",
    "Pastel2_r, PiYG, PiYG_r, PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Purples_r, RdBu, RdBu_r, RdGy,\n",
    "RdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, \n",
    "Spectral_r, Wistia, Wistia_r, YlGn, YlGnBu, YlGnBu_r, YlGn_r, YlOrBr, YlOrBr_r, YlOrRd, YlOrRd_r, afmhot, afmhot_r, autumn,\n",
    "autumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, cividis, cividis_r, cool, cool_r, coolwarm, coolwarm_r, \n",
    "copper, copper_r, cubehelix, cubehelix_r, flag, flag_r, gist_earth, gist_earth_r, gist_gray, gist_gray_r, gist_heat,\n",
    "gist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r,\n",
    "gnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r, hsv, hsv_r, inferno, inferno_r, jet, jet_r, magma,\n",
    "magma_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, \n",
    "seismic, seismic_r, spring, spring_r, summer, summer_r, tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, \n",
    "ter'''"
   ]
  },
  {
   "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": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
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    "name": "ipython",
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