Seasonal Bias(Noresm-CRU).ipynb

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    "#writing some conda package or module\n",
    "#!pip install netCDF4\n",
    "%matplotlib inline\n",
    "import warnings\n",
    "from netCDF4 import Dataset\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "#!pip install cartopy\n",
    "import cartopy.feature as cfeature\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.mpl.ticker as cticker\n",
    "from cartopy.util import add_cyclic_point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (lon: 720, lat: 360, time: 1452)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 -179.8 -179.2 -178.8 -178.2 ... 178.8 179.2 179.8\n",
       "  * lat      (lat) float32 -89.75 -89.25 -88.75 -88.25 ... 88.75 89.25 89.75\n",
       "  * time     (time) datetime64[ns] 1901-01-16 1901-02-15 ... 2021-12-16\n",
       "Data variables:\n",
       "    pre      (time, lat, lon) float32 ...\n",
       "    stn      (time, lat, lon) float64 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-ab273f2a-b3a8-4517-a040-9f9c1076a577' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ab273f2a-b3a8-4517-a040-9f9c1076a577' 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-d9b62df6-9223-4c95-91b9-09724becfa28' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d9b62df6-9223-4c95-91b9-09724becfa28' 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-b63b9d9b-d9ad-4d25-b14e-801fe57c7da8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b63b9d9b-d9ad-4d25-b14e-801fe57c7da8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3d5177c-2d3e-462e-968b-08de9fabb4d8' class='xr-var-data-in' type='checkbox'><label for='data-c3d5177c-2d3e-462e-968b-08de9fabb4d8' title='Show/Hide data 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-9ddcef83-7028-49c6-bea3-0015f52af838' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ddcef83-7028-49c6-bea3-0015f52af838' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-70ad8fbb-fbde-44c3-85db-ecba9496b4f2' class='xr-var-data-in' type='checkbox'><label for='data-70ad8fbb-fbde-44c3-85db-ecba9496b4f2' title='Show/Hide data 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-e9577e43-b388-4dc1-bc8f-b4a13ef3215a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e9577e43-b388-4dc1-bc8f-b4a13ef3215a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-291a8189-5013-48c2-a4fd-b05084e76ed6' class='xr-var-data-in' type='checkbox'><label for='data-291a8189-5013-48c2-a4fd-b05084e76ed6' title='Show/Hide data 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-61bf2011-f020-4206-a0f0-074a38a163d3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-61bf2011-f020-4206-a0f0-074a38a163d3' 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-86a710a0-2422-4d94-8c0c-8a8e7639a9d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-86a710a0-2422-4d94-8c0c-8a8e7639a9d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97e02372-ab9b-4019-9373-b56924744f73' class='xr-var-data-in' type='checkbox'><label for='data-97e02372-ab9b-4019-9373-b56924744f73' title='Show/Hide data 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-21e83ed4-b18c-4a30-9905-ab2b4283e66d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21e83ed4-b18c-4a30-9905-ab2b4283e66d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b962de3-3a39-48fc-9748-cc21b99a5635' class='xr-var-data-in' type='checkbox'><label for='data-3b962de3-3a39-48fc-9748-cc21b99a5635' title='Show/Hide data 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-d235db75-0240-4048-b6e4-bb02821c2a65' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d235db75-0240-4048-b6e4-bb02821c2a65' 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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    "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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       "    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-0712c8bb-bc63-4010-8c86-1524038f4bf5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0712c8bb-bc63-4010-8c86-1524038f4bf5' 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-d55fe861-91de-4821-9834-de8318be3e33' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d55fe861-91de-4821-9834-de8318be3e33' 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-2b94492e-862b-4f9e-82b4-7aa8969bf084' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b94492e-862b-4f9e-82b4-7aa8969bf084' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db93f030-7b54-48d4-86ed-d3ea6e742f64' class='xr-var-data-in' type='checkbox'><label for='data-db93f030-7b54-48d4-86ed-d3ea6e742f64' title='Show/Hide data 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-3c5c8bfa-2d82-4d84-ad5a-8292c16154f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c5c8bfa-2d82-4d84-ad5a-8292c16154f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-060dbe0e-ebe9-4fe1-8adb-e197e3e0303a' class='xr-var-data-in' type='checkbox'><label for='data-060dbe0e-ebe9-4fe1-8adb-e197e3e0303a' title='Show/Hide data 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-65dffe63-9256-46cc-b955-5205711369ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65dffe63-9256-46cc-b955-5205711369ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2733377c-b1c4-45ab-97a8-970e97985cc9' class='xr-var-data-in' type='checkbox'><label for='data-2733377c-b1c4-45ab-97a8-970e97985cc9' title='Show/Hide data 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-201a8d3e-7ebd-46f3-80dd-e5c95cd0e462' class='xr-section-summary-in' type='checkbox'  checked><label for='section-201a8d3e-7ebd-46f3-80dd-e5c95cd0e462' 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-c32e5cde-ee47-4051-a4b0-3db05cb9e7ec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c32e5cde-ee47-4051-a4b0-3db05cb9e7ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0ca0177-d38f-45b8-91e2-1d8a72435fac' class='xr-var-data-in' type='checkbox'><label for='data-f0ca0177-d38f-45b8-91e2-1d8a72435fac' title='Show/Hide data 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-8fce0158-7d4f-44fb-a2ba-d4ece951ec9e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8fce0158-7d4f-44fb-a2ba-d4ece951ec9e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fbf5c717-cef4-4d40-a695-c4f47a2df54f' class='xr-var-data-in' type='checkbox'><label for='data-fbf5c717-cef4-4d40-a695-c4f47a2df54f' title='Show/Hide data 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-fe2716fb-812c-4fd5-a0e8-1030ce8151e5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fe2716fb-812c-4fd5-a0e8-1030ce8151e5' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>title :</span></dt><dd>CRU TS4.06 Precipitation</dd><dt><span>institution :</span></dt><dd>Data held at British Atmospheric Data Centre, RAL, UK.</dd><dt><span>source :</span></dt><dd>Run ID = 2205201912. Data generated from:pre.2204291209.dtb</dd><dt><span>history :</span></dt><dd>Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegridsauto.for called by update.for</dd><dt><span>references :</span></dt><dd>Information on the data is available at http://badc.nerc.ac.uk/data/cru/</dd><dt><span>comment :</span></dt><dd>Access to these data is available to any registered CEDA user.</dd><dt><span>contact :</span></dt><dd>support@ceda.ac.uk</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lon: 720, lat: 360, time: 299)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 -179.8 -179.2 -178.8 -178.2 ... 178.8 179.2 179.8\n",
       "  * lat      (lat) float32 -89.75 -89.25 -88.75 -88.25 ... 88.75 89.25 89.75\n",
       "  * time     (time) datetime64[ns] 1981-02-15 1981-03-16 ... 2005-12-16\n",
       "Data variables:\n",
       "    pre      (time, lat, lon) float32 ...\n",
       "    stn      (time, lat, lon) float64 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#to select the year from 1980 to 2015\n",
    "data = data.sel(time=slice('1981-01-16T12:00:00.000000000','2005-12-16T00:00:00.000000000'))\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "10070b93",
   "metadata": {},
   "outputs": [
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       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (lon: 720, lat: 360, time: 100)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 -179.8 -179.2 -178.8 -178.2 ... 178.8 179.2 179.8\n",
       "  * lat      (lat) float32 -89.75 -89.25 -88.75 -88.25 ... 88.75 89.25 89.75\n",
       "  * time     (time) datetime64[ns] 1981-06-16 1981-07-16 ... 2005-09-16\n",
       "Data variables:\n",
       "    pre      (time, lat, lon) float32 ...\n",
       "    stn      (time, lat, lon) float64 ...\n",
       "Attributes:\n",
       "    Conventions:  CF-1.4\n",
       "    title:        CRU TS4.06 Precipitation\n",
       "    institution:  Data held at British Atmospheric Data Centre, RAL, UK.\n",
       "    source:       Run ID = 2205201912. Data generated from:pre.2204291209.dtb\n",
       "    history:      Fri 20 May 21:52:05 BST 2022 : User f098 : Program makegrid...\n",
       "    references:   Information on the data is available at http://badc.nerc.ac...\n",
       "    comment:      Access to these data is available to any registered CEDA user.\n",
       "    contact:      support@ceda.ac.uk</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d2f1afa5-86fb-4263-8021-d8a7d84de1b2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d2f1afa5-86fb-4263-8021-d8a7d84de1b2' 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-569d9225-bdda-4066-b055-f2ef8ed1e1a2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-569d9225-bdda-4066-b055-f2ef8ed1e1a2' 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-7346adcb-72a6-4cf6-a6db-ab3d11ea20a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7346adcb-72a6-4cf6-a6db-ab3d11ea20a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee052ad3-f727-4385-ad6b-81ab38031838' class='xr-var-data-in' type='checkbox'><label for='data-ee052ad3-f727-4385-ad6b-81ab38031838' title='Show/Hide data 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-cc3c7279-be44-429e-9248-17765f6da910' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc3c7279-be44-429e-9248-17765f6da910' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-385cd057-5518-4b5a-b1bc-35021fce0a27' class='xr-var-data-in' type='checkbox'><label for='data-385cd057-5518-4b5a-b1bc-35021fce0a27' title='Show/Hide data 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-415e0b70-a48f-4f3a-aedd-1a5fbbac4178' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-415e0b70-a48f-4f3a-aedd-1a5fbbac4178' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ac98f33-6101-48e8-bdbc-a3ab90b57d92' class='xr-var-data-in' type='checkbox'><label for='data-5ac98f33-6101-48e8-bdbc-a3ab90b57d92' title='Show/Hide data 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-dedd4a01-7491-4b56-9817-c361fe779233' class='xr-section-summary-in' type='checkbox'  checked><label for='section-dedd4a01-7491-4b56-9817-c361fe779233' 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-68440303-1194-4a99-bc55-243d0c860e58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68440303-1194-4a99-bc55-243d0c860e58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ef76179-9609-477c-b95a-a154cf5c7f06' class='xr-var-data-in' type='checkbox'><label for='data-4ef76179-9609-477c-b95a-a154cf5c7f06' title='Show/Hide data 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-bec8a6d1-6d92-4e5f-a4ee-76d9910e3344' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bec8a6d1-6d92-4e5f-a4ee-76d9910e3344' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee0697c9-a505-4185-8d8c-f167aa9e143a' class='xr-var-data-in' type='checkbox'><label for='data-ee0697c9-a505-4185-8d8c-f167aa9e143a' title='Show/Hide data 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-86571813-1745-44f7-9536-53c391f49aec' class='xr-section-summary-in' type='checkbox'  checked><label for='section-86571813-1745-44f7-9536-53c391f49aec' 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-0d4c8bac-c954-40ec-b971-093f6587473b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0d4c8bac-c954-40ec-b971-093f6587473b' 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-28546548-c6d1-4f4f-9e40-aeb50ff6bd5e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-28546548-c6d1-4f4f-9e40-aeb50ff6bd5e' 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-27de5654-d3c1-4257-ac17-f2cdb97540d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-27de5654-d3c1-4257-ac17-f2cdb97540d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c777a42d-1db7-4da4-8ac8-f68d6b4c8771' class='xr-var-data-in' type='checkbox'><label for='data-c777a42d-1db7-4da4-8ac8-f68d6b4c8771' title='Show/Hide data 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-7d108255-e6aa-40e9-b9d9-ce06ea5a27db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d108255-e6aa-40e9-b9d9-ce06ea5a27db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23903b9e-ebe8-4224-bace-b2eb8853be2e' class='xr-var-data-in' type='checkbox'><label for='data-23903b9e-ebe8-4224-bace-b2eb8853be2e' title='Show/Hide data 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-bc0f979a-26ff-4539-abc2-bef11a8bc9c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc0f979a-26ff-4539-abc2-bef11a8bc9c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79cc0e71-0990-4dc7-9781-e977f3b9922e' class='xr-var-data-in' type='checkbox'><label for='data-79cc0e71-0990-4dc7-9781-e977f3b9922e' title='Show/Hide data 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-7bed0e24-53b6-45bb-b211-cf178f9ce0fd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7bed0e24-53b6-45bb-b211-cf178f9ce0fd' 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-2e480b3a-5292-4e2c-b6e2-180854357e88' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2e480b3a-5292-4e2c-b6e2-180854357e88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a77c525c-8fa9-47bf-8293-bd2155fd48e3' class='xr-var-data-in' type='checkbox'><label for='data-a77c525c-8fa9-47bf-8293-bd2155fd48e3' title='Show/Hide data 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-4f6a7726-462d-475b-9edd-be0da100ca2c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f6a7726-462d-475b-9edd-be0da100ca2c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6594ec0f-cce8-425c-bc4a-fa870d3e151d' class='xr-var-data-in' type='checkbox'><label for='data-6594ec0f-cce8-425c-bc4a-fa870d3e151d' title='Show/Hide data 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-6a1a086e-0ebd-4f4a-b3ef-578836c4ec5f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6a1a086e-0ebd-4f4a-b3ef-578836c4ec5f' 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": "18ff4cf1",
   "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-507aba9e-cc7a-431b-b9e3-f8d85a383c6c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-507aba9e-cc7a-431b-b9e3-f8d85a383c6c' 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-6bf00372-9862-4296-aa94-65153d80ca69' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6bf00372-9862-4296-aa94-65153d80ca69' 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-c821e42c-572a-4e34-a6f7-820d004b972a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c821e42c-572a-4e34-a6f7-820d004b972a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-612478fe-c972-432b-9fec-8273b217c910' class='xr-var-data-in' type='checkbox'><label for='data-612478fe-c972-432b-9fec-8273b217c910' title='Show/Hide data 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-0945b074-bba4-4ccb-94b7-78e3dc0c563b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0945b074-bba4-4ccb-94b7-78e3dc0c563b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3068ea65-876c-4c7a-8cf3-89880bd703a0' class='xr-var-data-in' type='checkbox'><label for='data-3068ea65-876c-4c7a-8cf3-89880bd703a0' title='Show/Hide data 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-64aa8566-12e9-4522-9627-40eaa0c65289' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64aa8566-12e9-4522-9627-40eaa0c65289' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c9de473-bfe0-42ca-befb-636741a6d0e3' class='xr-var-data-in' type='checkbox'><label for='data-5c9de473-bfe0-42ca-befb-636741a6d0e3' title='Show/Hide data 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-56914354-fd87-411a-970b-c822b5003777' class='xr-section-summary-in' type='checkbox'  checked><label for='section-56914354-fd87-411a-970b-c822b5003777' 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-7ab86b6d-e99a-49cf-b5f0-b46a58c38c1e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ab86b6d-e99a-49cf-b5f0-b46a58c38c1e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c504d7d-d16d-4bf7-9f5f-61c95f1c81b3' class='xr-var-data-in' type='checkbox'><label for='data-1c504d7d-d16d-4bf7-9f5f-61c95f1c81b3' title='Show/Hide data 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-dd6a9d31-2d4a-4140-88c1-a808264595d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd6a9d31-2d4a-4140-88c1-a808264595d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c47aba7c-53ff-41c5-99ff-c909903a27f1' class='xr-var-data-in' type='checkbox'><label for='data-c47aba7c-53ff-41c5-99ff-c909903a27f1' title='Show/Hide data 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-2e4d10fe-4efb-478d-9188-ae79eff4038d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2e4d10fe-4efb-478d-9188-ae79eff4038d' 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-3491b724-7cb6-45e4-8130-614f655758db' class='xr-array-in' type='checkbox' checked><label for='section-3491b724-7cb6-45e4-8130-614f655758db' 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-a2706dbf-057d-4218-b30d-232011e857b9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a2706dbf-057d-4218-b30d-232011e857b9' 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-b29e211d-de54-4b93-867e-305d3efeceae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b29e211d-de54-4b93-867e-305d3efeceae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c26dd1c-e9a5-41ce-b07b-6a8bff308f0a' class='xr-var-data-in' type='checkbox'><label for='data-0c26dd1c-e9a5-41ce-b07b-6a8bff308f0a' title='Show/Hide data 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-dc95cb69-6c55-4564-ac9e-60407eb7dda1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc95cb69-6c55-4564-ac9e-60407eb7dda1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e622723-5298-4031-8f71-6e0b32dbc9d4' class='xr-var-data-in' type='checkbox'><label for='data-5e622723-5298-4031-8f71-6e0b32dbc9d4' title='Show/Hide data 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-760fe6aa-9e0a-4d82-9af8-6c4de0fcdc07' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-760fe6aa-9e0a-4d82-9af8-6c4de0fcdc07' 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": [
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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",
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       "         8.66667011,         nan],\n",
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       "                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-eac47dce-8ee0-4046-a615-d4c5c5a943d4' class='xr-array-in' type='checkbox' checked><label for='section-eac47dce-8ee0-4046-a615-d4c5c5a943d4' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>nan nan nan nan nan nan nan nan ... nan nan nan nan nan nan nan nan</span></div><div class='xr-array-data'><pre>array([[        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan],\n",
       "       ...,\n",
       "       [        nan, 10.1212165 , 10.29261907, ...,  8.48141002,\n",
       "         9.86841124,         nan],\n",
       "       [        nan,  8.59381539,  7.15945531, ...,  7.527559  ,\n",
       "         8.66667011,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan]])</pre></div></div></li><li class='xr-section-item'><input id='section-b5d34fd5-df98-4425-8b0e-1ae5da1e298e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b5d34fd5-df98-4425-8b0e-1ae5da1e298e' 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-8b6df384-4572-4d66-a3ab-ce52caf0c2c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b6df384-4572-4d66-a3ab-ce52caf0c2c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5789ee4-7283-4e5f-8df5-bdba185635b9' class='xr-var-data-in' type='checkbox'><label for='data-a5789ee4-7283-4e5f-8df5-bdba185635b9' title='Show/Hide data 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-fd03eba1-bb37-4889-a241-610751e86a1d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd03eba1-bb37-4889-a241-610751e86a1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0bbda5ac-ada8-4a9c-90a6-30a062cb5aaa' class='xr-var-data-in' type='checkbox'><label for='data-0bbda5ac-ada8-4a9c-90a6-30a062cb5aaa' title='Show/Hide data 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-9766c23b-d558-4336-8d0f-5e5b5cc3cd03' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9766c23b-d558-4336-8d0f-5e5b5cc3cd03' 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, 10.1212165 , 10.29261907, ...,  8.48141002,\n",
       "         9.86841124,         nan],\n",
       "       [        nan,  8.59381539,  7.15945531, ...,  7.527559  ,\n",
       "         8.66667011,         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": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#changing unit from mm/month to mm/day\n",
    "pr_mm = jjas_mean/30.4167\n",
    " \n",
    "\n",
    "\n",
    "cru = pr_mm\n",
    "cru"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b6d9b2b3",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 432, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) object 1970-01-16 12:00:00 ... 2005-12-16 12:00:00\n",
       "  * lon        (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat        (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
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       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:05:10 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    driving_experiment:                              NCC-NorESM1-M, historica...\n",
       "    driving_model_id:                                NCC-NorESM1-M\n",
       "    CDO:                                             Climate Data Operators v...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e5b1c2b5-74cb-4182-af6c-9fd716cc1e32' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e5b1c2b5-74cb-4182-af6c-9fd716cc1e32' 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-4af66be8-b998-410c-b5d2-5adccef538a7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4af66be8-b998-410c-b5d2-5adccef538a7' 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-727d086a-e604-4734-ae1f-2c68f189a3b9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-727d086a-e604-4734-ae1f-2c68f189a3b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-073bd147-3986-4f2b-a056-cf38054addc0' class='xr-var-data-in' type='checkbox'><label for='data-073bd147-3986-4f2b-a056-cf38054addc0' title='Show/Hide data 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-c4b0a277-16bb-448f-9447-c121efa5c482' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c4b0a277-16bb-448f-9447-c121efa5c482' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a45e0cb-df5f-4910-b028-0b0f1c40918b' class='xr-var-data-in' type='checkbox'><label for='data-5a45e0cb-df5f-4910-b028-0b0f1c40918b' title='Show/Hide data 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-b029f7e9-f424-4ca9-b7e7-be1de3ee6988' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b029f7e9-f424-4ca9-b7e7-be1de3ee6988' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55056ea1-08e5-475e-a39f-f32c667c4890' class='xr-var-data-in' type='checkbox'><label for='data-55056ea1-08e5-475e-a39f-f32c667c4890' title='Show/Hide data 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-5dd2b9e8-8351-486e-ba9f-79629c5c89ae' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5dd2b9e8-8351-486e-ba9f-79629c5c89ae' 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-c19152db-a167-45fa-9ed5-df5eb954e3ba' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c19152db-a167-45fa-9ed5-df5eb954e3ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60ab870d-d859-4bad-99b2-13ccc5aa484f' class='xr-var-data-in' type='checkbox'><label for='data-60ab870d-d859-4bad-99b2-13ccc5aa484f' title='Show/Hide data 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-175e398d-7d60-4a5b-839d-45413dd11305' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-175e398d-7d60-4a5b-839d-45413dd11305' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b479677-773e-4542-9b94-8ddbcaf0a959' class='xr-var-data-in' type='checkbox'><label for='data-5b479677-773e-4542-9b94-8ddbcaf0a959' title='Show/Hide data 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-08640d41-9a78-4cae-9dac-6d6a8f8e1c21' class='xr-section-summary-in' type='checkbox'  ><label for='section-08640d41-9a78-4cae-9dac-6d6a8f8e1c21' class='xr-section-summary' >Attributes: <span>(165)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>history :</span></dt><dd>Thu Jul 07 17:05:10 2022: cdo remapnn,grid1.des noresm_pr_197001-200512.nc noresm1_remap.nc\n",
       "Mon Jun 27 15:36:42 2022: cdo mergetime pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_197001-198012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_198101-199012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_199101-200012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_200101-200512.nc noresm_pr_197001-200512.nc\n",
       "2018-03-21 03:01:05 : Created by RegCM RegCM Model program</dd><dt><span>source :</span></dt><dd>RegCM Model output file</dd><dt><span>institution :</span></dt><dd>Oak Ridge National Laboratory</dd><dt><span>project_id :</span></dt><dd>CORDEX</dd><dt><span>ipcc_scenario_code :</span></dt><dd>HISTORICAL</dd><dt><span>institute_id :</span></dt><dd>ORNL</dd><dt><span>note :</span></dt><dd>The domain is larger than WAS-22</dd><dt><span>comment :</span></dt><dd>RegCM CORDEX SAsia25 run</dd><dt><span>experiment :</span></dt><dd>WAS-22</dd><dt><span>driving_model_ensemble_member :</span></dt><dd>r1i1p1</dd><dt><span>creation_date :</span></dt><dd>2019-09-19T16:13:52Z</dd><dt><span>CORDEX_domain :</span></dt><dd>WAS-22</dd><dt><span>rcm_version_id :</span></dt><dd>v0</dd><dt><span>ICTP_version_note :</span></dt><dd>Model run at ORNL on Titan</dd><dt><span>contact :</span></dt><dd>mashfaq@ornl.gov</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>tracking_id :</span></dt><dd>e18baf90-8c3e-11e9-a8fd-f04da273d2fb</dd><dt><span>title :</span></dt><dd>ICTP Regional Climatic model V4</dd><dt><span>references :</span></dt><dd>http://gforge.ictp.it/gf/project/regcm</dd><dt><span>model_revision :</span></dt><dd>tag-4.7.0</dd><dt><span>projection :</span></dt><dd>ROTMER</dd><dt><span>grid_size_in_meters :</span></dt><dd>25000.0</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>13.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>70.0</dd><dt><span>grid_north_pole_latitude :</span></dt><dd>13.0</dd><dt><span>grid_north_pole_longitude :</span></dt><dd>70.0</dd><dt><span>grid_factor :</span></dt><dd>0.0</dd><dt><span>landsurface_model :</span></dt><dd>clm4.5</dd><dt><span>model_icbc_data_source :</span></dt><dd>NO_85</dd><dt><span>model_sst_data_source :</span></dt><dd>NO_85</dd><dt><span>boundary_nspgx :</span></dt><dd>30</dd><dt><span>boundary_nspgd :</span></dt><dd>30</dd><dt><span>boundary_high_nudge :</span></dt><dd>8.0</dd><dt><span>boundary_medium_nudge :</span></dt><dd>6.0</dd><dt><span>boundary_low_nudge :</span></dt><dd>4.0</dd><dt><span>boundary_nm :</span></dt><dd>-1.0</dd><dt><span>boundary_dm :</span></dt><dd>-1.0</dd><dt><span>model_is_restarted :</span></dt><dd>No</dd><dt><span>model_simulation_initial_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_end :</span></dt><dd> 2005-12-31 00:00:00 UTC</dd><dt><span>atmosphere_time_step_in_seconds :</span></dt><dd>40.0</dd><dt><span>surface_interaction_time_step_in_seconds :</span></dt><dd>480.0</dd><dt><span>convection_time_step_in_seconds :</span></dt><dd>240.0</dd><dt><span>radiation_scheme_time_step_in_seconds :</span></dt><dd>1800.0</dd><dt><span>absorption_emission_time_step_in_seconds :</span></dt><dd>64800.0</dd><dt><span>dynamical_core :</span></dt><dd>1</dd><dt><span>asselin_filter_nu_1 :</span></dt><dd>0.0625</dd><dt><span>asselin_filter_nu_2 :</span></dt><dd>0.0625</dd><dt><span>diffusion_hgt_factor :</span></dt><dd>1</dd><dt><span>upstream_mode :</span></dt><dd>Yes</dd><dt><span>off_centering_max :</span></dt><dd>0.25</dd><dt><span>stability_enhance :</span></dt><dd>Yes</dd><dt><span>temperature_extreme_gradient :</span></dt><dd>5.0</dd><dt><span>cloud_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>vapor_extreme_gradient_fraction :</span></dt><dd>0.2</dd><dt><span>tracer_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>lateral_boundary_condition_scheme :</span></dt><dd>5</dd><dt><span>semi_lagrangian_advection_scheme :</span></dt><dd>0</dd><dt><span>boundary_layer_scheme :</span></dt><dd>2</dd><dt><span>cumulus_convection_scheme_lnd :</span></dt><dd>4</dd><dt><span>cumulus_convection_scheme_ocn :</span></dt><dd>5</dd><dt><span>moisture_scheme :</span></dt><dd>1</dd><dt><span>ocean_flux_scheme :</span></dt><dd>2</dd><dt><span>zeng_ocean_roughness_formula :</span></dt><dd>1</dd><dt><span>zeng_ocean_roughness_method :</span></dt><dd>1</dd><dt><span>pressure_gradient_scheme :</span></dt><dd>0</dd><dt><span>surface_emissivity_factor_computed :</span></dt><dd>0</dd><dt><span>lake_model_activated :</span></dt><dd>0</dd><dt><span>chemical_aerosol_scheme_activated :</span></dt><dd>0</dd><dt><span>diurnal_cycle_sst_scheme :</span></dt><dd>0</dd><dt><span>ocean_precipitaion_cooling_effect :</span></dt><dd>0</dd><dt><span>ocean_albedo_from_whitecapping :</span></dt><dd>0</dd><dt><span>simple_sea_ice_scheme :</span></dt><dd>0</dd><dt><span>seasonal_desert_albedo :</span></dt><dd>0</dd><dt><span>convective_lwp_as_large_scale :</span></dt><dd>0</dd><dt><span>large_scale_cloud_fraction_scheme :</span></dt><dd>0</dd><dt><span>ocean_stratiform_clouds_scheme :</span></dt><dd>1</dd><dt><span>rrtm_radiation_scheme_activated :</span></dt><dd>0</dd><dt><span>climatic_ozone_input_dataset :</span></dt><dd>0</dd><dt><span>climatic_aerosol_input_dataset :</span></dt><dd>0</dd><dt><span>static_solar_constant_used :</span></dt><dd>0</dd><dt><span>cumulus_cloud_model :</span></dt><dd>1</dd><dt><span>sun_year_offset :</span></dt><dd>0.0</dd><dt><span>fix_solar_parameters :</span></dt><dd>0</dd><dt><span>cloud_bottom_level_with_no_clouds :</span></dt><dd>1</dd><dt><span>cloud_rh_with_fcc_one :</span></dt><dd>1.01</dd><dt><span>cloud_rh_threshold_for_land :</span></dt><dd>0.8</dd><dt><span>cloud_rh_threshold_for_ocean :</span></dt><dd>0.9</dd><dt><span>cloud_rh1_limit_temperature :</span></dt><dd>238.0</dd><dt><span>cloud_cloud_fraction_maximum :</span></dt><dd>0.75</dd><dt><span>cloud_condensation_threshold :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_fraction_max_for_convection :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_liqwat_max_for_convection :</span></dt><dd>0.0003</dd><dt><span>cloud_shallow_convective_cf_param :</span></dt><dd>0.07</dd><dt><span>cloud_deep_convective_cf_param :</span></dt><dd>0.14</dd><dt><span>cloud_k2_convective_cf_param :</span></dt><dd>500.0</dd><dt><span>cloud_surface_radiation_hack :</span></dt><dd>No</dd><dt><span>cloud_arctic_cloud_correction :</span></dt><dd>Yes</dd><dt><span>subex_auto_conversion_rate_for_land :</span></dt><dd>0.00025</dd><dt><span>subex_auto_conversion_rate_for_ocean :</span></dt><dd>0.00025</dd><dt><span>subex_gultepe_factor_when_rain_for_land :</span></dt><dd>0.4</dd><dt><span>subex_gultepe_factor_when_rain_for_ocean :</span></dt><dd>0.4</dd><dt><span>subex_land_raindrop_evaporation_rate :</span></dt><dd>0.0002</dd><dt><span>subex_ocean_raindrop_evaporation_rate :</span></dt><dd>0.0001</dd><dt><span>subex_land_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>subex_ocean_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>mit_lowest_convection_sigma :</span></dt><dd>0.95</dd><dt><span>mit_autoconversion_threshold_mixing_over_ocean :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_mixing_over_land :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_temperature :</span></dt><dd>-55.0</dd><dt><span>mit_mixing_coefficient_in_entrainment :</span></dt><dd>1.5</dd><dt><span>mit_fractional_area_unsaturated_downdraft :</span></dt><dd>0.05</dd><dt><span>mit_fractional_precip_outside_cloud :</span></dt><dd>0.12</dd><dt><span>mit_pressure_velocity_of_rain :</span></dt><dd>50.0</dd><dt><span>mit_pressure_velocity_of_snow :</span></dt><dd>5.5</dd><dt><span>mit_rain_evaporation_coefficient :</span></dt><dd>1.0</dd><dt><span>mit_snow_evaporation_coefficient :</span></dt><dd>0.8</dd><dt><span>mit_momentum_transport_coefficient :</span></dt><dd>0.7</dd><dt><span>mit_downdraft_velocity_coefficient :</span></dt><dd>10.0</dd><dt><span>mit_max_parcel_neg_temp_perturbation :</span></dt><dd>0.9</dd><dt><span>mit_approach_rate_quasi_eq_coeff_a :</span></dt><dd>0.2</dd><dt><span>mit_approach_rate_quasi_eq_coeff_d :</span></dt><dd>0.1</dd><dt><span>mit_maximum_land_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>mit_maximum_ocean_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>tiedtke_actual_scheme :</span></dt><dd>4</dd><dt><span>tiedtke_entrainment_rate_downdraft :</span></dt><dd>0.0003</dd><dt><span>tiedtke_entrainment_rate_deep_land :</span></dt><dd>0.00075</dd><dt><span>tiedtke_entrainment_rate_deep_ocean :</span></dt><dd>0.00075</dd><dt><span>tiedtke_penetrative :</span></dt><dd>Yes</dd><dt><span>tiedtke_midlevel :</span></dt><dd>Yes</dd><dt><span>tiedtke_shallow :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_downdraft :</span></dt><dd>Yes</dd><dt><span>tiedtke_prognostic_cloud :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_friction :</span></dt><dd>Yes</dd><dt><span>tiedtke_ke_dissipation :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_transport :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_smooth_massflux :</span></dt><dd>No</dd><dt><span>tiedtke_shallow_wstar_closure :</span></dt><dd>No</dd><dt><span>tiedtke_detrainment_rate_deep_land :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_detrainment_rate_deep_ocean :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_shallow_entrainment :</span></dt><dd>2.0</dd><dt><span>tiedtke_cloud_cover_evap_over_land :</span></dt><dd>0.05</dd><dt><span>tiedtke_cloud_cover_evap_over_ocean :</span></dt><dd>0.05</dd><dt><span>tiedtke_coeff_evap_over_land :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_coeff_evap_over_ocean :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_critical_rh_over_land :</span></dt><dd>0.9</dd><dt><span>tiedtke_critical_rh_over_ocean :</span></dt><dd>0.9</dd><dt><span>tiedtke_cloud_water_conv_over_land :</span></dt><dd>0.03</dd><dt><span>tiedtke_cloud_water_conv_over_ocean :</span></dt><dd>0.0014</dd><dt><span>tiedtke_cape_adjustment_timescale :</span></dt><dd>2400.0</dd><dt><span>uwpbl_advection_scheme :</span></dt><dd>0</dd><dt><span>uwpbl_cloud_evap_entr_incr_efficiency :</span></dt><dd>15.0</dd><dt><span>uwpbl_eddy_LS_stable_PBL_scaling :</span></dt><dd>1.5</dd><dt><span>uwpbl_czero :</span></dt><dd>5.869</dd><dt><span>uwpbl_nuk :</span></dt><dd>5.0</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>driving_experiment_name :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>ICTP-RegCM4-7</dd><dt><span>driving_experiment :</span></dt><dd>NCC-NorESM1-M, historical, r1i1p1</dd><dt><span>driving_model_id :</span></dt><dd>NCC-NorESM1-M</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.9rc1 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
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       "<xarray.Dataset>\n",
       "Dimensions:    (time: 432, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) object 1970-01-16 12:00:00 ... 2005-12-16 12:00:00\n",
       "  * lon        (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat        (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object ...\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:05:10 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    driving_experiment:                              NCC-NorESM1-M, historica...\n",
       "    driving_model_id:                                NCC-NorESM1-M\n",
       "    CDO:                                             Climate Data Operators v..."
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     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#opening the noresm data\n",
    "\n",
    "data = xr.open_dataset('/home/mkibria/Academic/pr_of_thesis/regcm driven by gcm/NorESM1-M/noresm1_remap.nc')\n",
    " \n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "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_27804/1463838701.py:3: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  datetimeindex = data.indexes['time'].to_datetimeindex()\n"
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       "Dimensions:    (time: 432, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1970-01-16T12:00:00 ... 2005-12-16T12:00:00\n",
       "  * lon        (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat        (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1970-01-01 00:00:00 ... 2006-01-01 00:00:00\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:05:10 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    driving_experiment:                              NCC-NorESM1-M, historica...\n",
       "    driving_model_id:                                NCC-NorESM1-M\n",
       "    CDO:                                             Climate Data Operators v...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-3594fa15-8f96-4978-847b-661425a7e08d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3594fa15-8f96-4978-847b-661425a7e08d' 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-d9f4d840-d401-4682-b281-091e7f0e9552' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d9f4d840-d401-4682-b281-091e7f0e9552' 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-1a870f5b-8e05-4524-aab2-3219bb2f7898' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a870f5b-8e05-4524-aab2-3219bb2f7898' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54a039a5-1a8a-4752-b2c5-738088d2b0e6' class='xr-var-data-in' type='checkbox'><label for='data-54a039a5-1a8a-4752-b2c5-738088d2b0e6' title='Show/Hide data 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-7024a985-fad1-4097-bf59-d4415a371a94' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7024a985-fad1-4097-bf59-d4415a371a94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e17df13-d827-43d3-9023-1dab00c85a35' class='xr-var-data-in' type='checkbox'><label for='data-1e17df13-d827-43d3-9023-1dab00c85a35' title='Show/Hide data 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-c3d0e97c-68fb-427c-8642-817b530d0934' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c3d0e97c-68fb-427c-8642-817b530d0934' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bea61912-bdcc-45fe-8ab8-d94fa6083778' class='xr-var-data-in' type='checkbox'><label for='data-bea61912-bdcc-45fe-8ab8-d94fa6083778' title='Show/Hide data 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-da0c1d36-1441-40b4-95c0-daba27276bd7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-da0c1d36-1441-40b4-95c0-daba27276bd7' 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-13669bf8-a858-4b7f-be41-39216b1687f1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-13669bf8-a858-4b7f-be41-39216b1687f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8012643b-a4f0-4a52-a963-2b14c5a020df' class='xr-var-data-in' type='checkbox'><label for='data-8012643b-a4f0-4a52-a963-2b14c5a020df' title='Show/Hide data 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-3bde5698-8cc1-4210-a1d2-a2ff6122f013' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3bde5698-8cc1-4210-a1d2-a2ff6122f013' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11262d28-79b4-4519-a9f1-06a2cbd1df51' class='xr-var-data-in' type='checkbox'><label for='data-11262d28-79b4-4519-a9f1-06a2cbd1df51' title='Show/Hide data 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-65d7eafc-b86f-41ff-bf7c-f2e778e89f50' class='xr-section-summary-in' type='checkbox'  ><label for='section-65d7eafc-b86f-41ff-bf7c-f2e778e89f50' class='xr-section-summary' >Attributes: <span>(165)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>history :</span></dt><dd>Thu Jul 07 17:05:10 2022: cdo remapnn,grid1.des noresm_pr_197001-200512.nc noresm1_remap.nc\n",
       "Mon Jun 27 15:36:42 2022: cdo mergetime pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_197001-198012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_198101-199012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_199101-200012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_200101-200512.nc noresm_pr_197001-200512.nc\n",
       "2018-03-21 03:01:05 : Created by RegCM RegCM Model program</dd><dt><span>source :</span></dt><dd>RegCM Model output file</dd><dt><span>institution :</span></dt><dd>Oak Ridge National Laboratory</dd><dt><span>project_id :</span></dt><dd>CORDEX</dd><dt><span>ipcc_scenario_code :</span></dt><dd>HISTORICAL</dd><dt><span>institute_id :</span></dt><dd>ORNL</dd><dt><span>note :</span></dt><dd>The domain is larger than WAS-22</dd><dt><span>comment :</span></dt><dd>RegCM CORDEX SAsia25 run</dd><dt><span>experiment :</span></dt><dd>WAS-22</dd><dt><span>driving_model_ensemble_member :</span></dt><dd>r1i1p1</dd><dt><span>creation_date :</span></dt><dd>2019-09-19T16:13:52Z</dd><dt><span>CORDEX_domain :</span></dt><dd>WAS-22</dd><dt><span>rcm_version_id :</span></dt><dd>v0</dd><dt><span>ICTP_version_note :</span></dt><dd>Model run at ORNL on Titan</dd><dt><span>contact :</span></dt><dd>mashfaq@ornl.gov</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>tracking_id :</span></dt><dd>e18baf90-8c3e-11e9-a8fd-f04da273d2fb</dd><dt><span>title :</span></dt><dd>ICTP Regional Climatic model V4</dd><dt><span>references :</span></dt><dd>http://gforge.ictp.it/gf/project/regcm</dd><dt><span>model_revision :</span></dt><dd>tag-4.7.0</dd><dt><span>projection :</span></dt><dd>ROTMER</dd><dt><span>grid_size_in_meters :</span></dt><dd>25000.0</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>13.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>70.0</dd><dt><span>grid_north_pole_latitude :</span></dt><dd>13.0</dd><dt><span>grid_north_pole_longitude :</span></dt><dd>70.0</dd><dt><span>grid_factor :</span></dt><dd>0.0</dd><dt><span>landsurface_model :</span></dt><dd>clm4.5</dd><dt><span>model_icbc_data_source :</span></dt><dd>NO_85</dd><dt><span>model_sst_data_source :</span></dt><dd>NO_85</dd><dt><span>boundary_nspgx :</span></dt><dd>30</dd><dt><span>boundary_nspgd :</span></dt><dd>30</dd><dt><span>boundary_high_nudge :</span></dt><dd>8.0</dd><dt><span>boundary_medium_nudge :</span></dt><dd>6.0</dd><dt><span>boundary_low_nudge :</span></dt><dd>4.0</dd><dt><span>boundary_nm :</span></dt><dd>-1.0</dd><dt><span>boundary_dm :</span></dt><dd>-1.0</dd><dt><span>model_is_restarted :</span></dt><dd>No</dd><dt><span>model_simulation_initial_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_end :</span></dt><dd> 2005-12-31 00:00:00 UTC</dd><dt><span>atmosphere_time_step_in_seconds :</span></dt><dd>40.0</dd><dt><span>surface_interaction_time_step_in_seconds :</span></dt><dd>480.0</dd><dt><span>convection_time_step_in_seconds :</span></dt><dd>240.0</dd><dt><span>radiation_scheme_time_step_in_seconds :</span></dt><dd>1800.0</dd><dt><span>absorption_emission_time_step_in_seconds :</span></dt><dd>64800.0</dd><dt><span>dynamical_core :</span></dt><dd>1</dd><dt><span>asselin_filter_nu_1 :</span></dt><dd>0.0625</dd><dt><span>asselin_filter_nu_2 :</span></dt><dd>0.0625</dd><dt><span>diffusion_hgt_factor :</span></dt><dd>1</dd><dt><span>upstream_mode :</span></dt><dd>Yes</dd><dt><span>off_centering_max :</span></dt><dd>0.25</dd><dt><span>stability_enhance :</span></dt><dd>Yes</dd><dt><span>temperature_extreme_gradient :</span></dt><dd>5.0</dd><dt><span>cloud_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>vapor_extreme_gradient_fraction :</span></dt><dd>0.2</dd><dt><span>tracer_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>lateral_boundary_condition_scheme :</span></dt><dd>5</dd><dt><span>semi_lagrangian_advection_scheme :</span></dt><dd>0</dd><dt><span>boundary_layer_scheme :</span></dt><dd>2</dd><dt><span>cumulus_convection_scheme_lnd :</span></dt><dd>4</dd><dt><span>cumulus_convection_scheme_ocn :</span></dt><dd>5</dd><dt><span>moisture_scheme :</span></dt><dd>1</dd><dt><span>ocean_flux_scheme :</span></dt><dd>2</dd><dt><span>zeng_ocean_roughness_formula :</span></dt><dd>1</dd><dt><span>zeng_ocean_roughness_method :</span></dt><dd>1</dd><dt><span>pressure_gradient_scheme :</span></dt><dd>0</dd><dt><span>surface_emissivity_factor_computed :</span></dt><dd>0</dd><dt><span>lake_model_activated :</span></dt><dd>0</dd><dt><span>chemical_aerosol_scheme_activated :</span></dt><dd>0</dd><dt><span>diurnal_cycle_sst_scheme :</span></dt><dd>0</dd><dt><span>ocean_precipitaion_cooling_effect :</span></dt><dd>0</dd><dt><span>ocean_albedo_from_whitecapping :</span></dt><dd>0</dd><dt><span>simple_sea_ice_scheme :</span></dt><dd>0</dd><dt><span>seasonal_desert_albedo :</span></dt><dd>0</dd><dt><span>convective_lwp_as_large_scale :</span></dt><dd>0</dd><dt><span>large_scale_cloud_fraction_scheme :</span></dt><dd>0</dd><dt><span>ocean_stratiform_clouds_scheme :</span></dt><dd>1</dd><dt><span>rrtm_radiation_scheme_activated :</span></dt><dd>0</dd><dt><span>climatic_ozone_input_dataset :</span></dt><dd>0</dd><dt><span>climatic_aerosol_input_dataset :</span></dt><dd>0</dd><dt><span>static_solar_constant_used :</span></dt><dd>0</dd><dt><span>cumulus_cloud_model :</span></dt><dd>1</dd><dt><span>sun_year_offset :</span></dt><dd>0.0</dd><dt><span>fix_solar_parameters :</span></dt><dd>0</dd><dt><span>cloud_bottom_level_with_no_clouds :</span></dt><dd>1</dd><dt><span>cloud_rh_with_fcc_one :</span></dt><dd>1.01</dd><dt><span>cloud_rh_threshold_for_land :</span></dt><dd>0.8</dd><dt><span>cloud_rh_threshold_for_ocean :</span></dt><dd>0.9</dd><dt><span>cloud_rh1_limit_temperature :</span></dt><dd>238.0</dd><dt><span>cloud_cloud_fraction_maximum :</span></dt><dd>0.75</dd><dt><span>cloud_condensation_threshold :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_fraction_max_for_convection :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_liqwat_max_for_convection :</span></dt><dd>0.0003</dd><dt><span>cloud_shallow_convective_cf_param :</span></dt><dd>0.07</dd><dt><span>cloud_deep_convective_cf_param :</span></dt><dd>0.14</dd><dt><span>cloud_k2_convective_cf_param :</span></dt><dd>500.0</dd><dt><span>cloud_surface_radiation_hack :</span></dt><dd>No</dd><dt><span>cloud_arctic_cloud_correction :</span></dt><dd>Yes</dd><dt><span>subex_auto_conversion_rate_for_land :</span></dt><dd>0.00025</dd><dt><span>subex_auto_conversion_rate_for_ocean :</span></dt><dd>0.00025</dd><dt><span>subex_gultepe_factor_when_rain_for_land :</span></dt><dd>0.4</dd><dt><span>subex_gultepe_factor_when_rain_for_ocean :</span></dt><dd>0.4</dd><dt><span>subex_land_raindrop_evaporation_rate :</span></dt><dd>0.0002</dd><dt><span>subex_ocean_raindrop_evaporation_rate :</span></dt><dd>0.0001</dd><dt><span>subex_land_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>subex_ocean_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>mit_lowest_convection_sigma :</span></dt><dd>0.95</dd><dt><span>mit_autoconversion_threshold_mixing_over_ocean :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_mixing_over_land :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_temperature :</span></dt><dd>-55.0</dd><dt><span>mit_mixing_coefficient_in_entrainment :</span></dt><dd>1.5</dd><dt><span>mit_fractional_area_unsaturated_downdraft :</span></dt><dd>0.05</dd><dt><span>mit_fractional_precip_outside_cloud :</span></dt><dd>0.12</dd><dt><span>mit_pressure_velocity_of_rain :</span></dt><dd>50.0</dd><dt><span>mit_pressure_velocity_of_snow :</span></dt><dd>5.5</dd><dt><span>mit_rain_evaporation_coefficient :</span></dt><dd>1.0</dd><dt><span>mit_snow_evaporation_coefficient :</span></dt><dd>0.8</dd><dt><span>mit_momentum_transport_coefficient :</span></dt><dd>0.7</dd><dt><span>mit_downdraft_velocity_coefficient :</span></dt><dd>10.0</dd><dt><span>mit_max_parcel_neg_temp_perturbation :</span></dt><dd>0.9</dd><dt><span>mit_approach_rate_quasi_eq_coeff_a :</span></dt><dd>0.2</dd><dt><span>mit_approach_rate_quasi_eq_coeff_d :</span></dt><dd>0.1</dd><dt><span>mit_maximum_land_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>mit_maximum_ocean_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>tiedtke_actual_scheme :</span></dt><dd>4</dd><dt><span>tiedtke_entrainment_rate_downdraft :</span></dt><dd>0.0003</dd><dt><span>tiedtke_entrainment_rate_deep_land :</span></dt><dd>0.00075</dd><dt><span>tiedtke_entrainment_rate_deep_ocean :</span></dt><dd>0.00075</dd><dt><span>tiedtke_penetrative :</span></dt><dd>Yes</dd><dt><span>tiedtke_midlevel :</span></dt><dd>Yes</dd><dt><span>tiedtke_shallow :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_downdraft :</span></dt><dd>Yes</dd><dt><span>tiedtke_prognostic_cloud :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_friction :</span></dt><dd>Yes</dd><dt><span>tiedtke_ke_dissipation :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_transport :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_smooth_massflux :</span></dt><dd>No</dd><dt><span>tiedtke_shallow_wstar_closure :</span></dt><dd>No</dd><dt><span>tiedtke_detrainment_rate_deep_land :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_detrainment_rate_deep_ocean :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_shallow_entrainment :</span></dt><dd>2.0</dd><dt><span>tiedtke_cloud_cover_evap_over_land :</span></dt><dd>0.05</dd><dt><span>tiedtke_cloud_cover_evap_over_ocean :</span></dt><dd>0.05</dd><dt><span>tiedtke_coeff_evap_over_land :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_coeff_evap_over_ocean :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_critical_rh_over_land :</span></dt><dd>0.9</dd><dt><span>tiedtke_critical_rh_over_ocean :</span></dt><dd>0.9</dd><dt><span>tiedtke_cloud_water_conv_over_land :</span></dt><dd>0.03</dd><dt><span>tiedtke_cloud_water_conv_over_ocean :</span></dt><dd>0.0014</dd><dt><span>tiedtke_cape_adjustment_timescale :</span></dt><dd>2400.0</dd><dt><span>uwpbl_advection_scheme :</span></dt><dd>0</dd><dt><span>uwpbl_cloud_evap_entr_incr_efficiency :</span></dt><dd>15.0</dd><dt><span>uwpbl_eddy_LS_stable_PBL_scaling :</span></dt><dd>1.5</dd><dt><span>uwpbl_czero :</span></dt><dd>5.869</dd><dt><span>uwpbl_nuk :</span></dt><dd>5.0</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>driving_experiment_name :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>ICTP-RegCM4-7</dd><dt><span>driving_experiment :</span></dt><dd>NCC-NorESM1-M, historical, r1i1p1</dd><dt><span>driving_model_id :</span></dt><dd>NCC-NorESM1-M</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.9rc1 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (time: 432, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1970-01-16T12:00:00 ... 2005-12-16T12:00:00\n",
       "  * lon        (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat        (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1970-01-01 00:00:00 ... 2006-01-01 00:00:00\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:05:10 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    driving_experiment:                              NCC-NorESM1-M, historica...\n",
       "    driving_model_id:                                NCC-NorESM1-M\n",
       "    CDO:                                             Climate Data Operators v..."
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#changing time dim to datetime64[ns] dtype\n",
    "\n",
    "datetimeindex = data.indexes['time'].to_datetimeindex()\n",
    "data['time']=datetimeindex\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "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",
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       "  * lat        (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
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       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:05:10 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    driving_experiment:                              NCC-NorESM1-M, historica...\n",
       "    driving_model_id:                                NCC-NorESM1-M\n",
       "    CDO:                                             Climate Data Operators v...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b979f963-7594-46a3-b361-cf026eebd74e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b979f963-7594-46a3-b361-cf026eebd74e' 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-deb6390e-bc13-47d3-91cd-93b8ed25da7f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-deb6390e-bc13-47d3-91cd-93b8ed25da7f' 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-9a91e2e5-23fb-4559-a5b1-3d57485e03d8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9a91e2e5-23fb-4559-a5b1-3d57485e03d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdabf473-bc8f-40d4-bda3-ed3af567071f' class='xr-var-data-in' type='checkbox'><label for='data-fdabf473-bc8f-40d4-bda3-ed3af567071f' title='Show/Hide data 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-a8387498-19d3-40a2-8597-f52160e7adfd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a8387498-19d3-40a2-8597-f52160e7adfd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6dc0114-f04f-481c-947f-6b04c1797db2' class='xr-var-data-in' type='checkbox'><label for='data-c6dc0114-f04f-481c-947f-6b04c1797db2' title='Show/Hide data 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-7b0e39e6-47bc-41ab-8e76-e223b9aba57b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b0e39e6-47bc-41ab-8e76-e223b9aba57b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8cfd63d3-296a-4c2f-acef-ccd413c19b5d' class='xr-var-data-in' type='checkbox'><label for='data-8cfd63d3-296a-4c2f-acef-ccd413c19b5d' title='Show/Hide data 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-81389c66-c991-476c-b5a8-2e6d5c03e921' class='xr-section-summary-in' type='checkbox'  checked><label for='section-81389c66-c991-476c-b5a8-2e6d5c03e921' 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-570d8f40-debb-4b82-bf12-caffd0a719b8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-570d8f40-debb-4b82-bf12-caffd0a719b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6276d91b-24b5-4be0-b35f-28bd28742844' class='xr-var-data-in' type='checkbox'><label for='data-6276d91b-24b5-4be0-b35f-28bd28742844' title='Show/Hide data 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-bbc910e2-398a-4315-bfa0-b07000ef4783' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bbc910e2-398a-4315-bfa0-b07000ef4783' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c7b57a1-09f0-4263-9452-b4502b2e09c7' class='xr-var-data-in' type='checkbox'><label for='data-9c7b57a1-09f0-4263-9452-b4502b2e09c7' title='Show/Hide data 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-88d1925a-d84d-499c-a0fd-062d51e06c80' class='xr-section-summary-in' type='checkbox'  ><label for='section-88d1925a-d84d-499c-a0fd-062d51e06c80' class='xr-section-summary' >Attributes: <span>(165)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>history :</span></dt><dd>Thu Jul 07 17:05:10 2022: cdo remapnn,grid1.des noresm_pr_197001-200512.nc noresm1_remap.nc\n",
       "Mon Jun 27 15:36:42 2022: cdo mergetime pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_197001-198012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_198101-199012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_199101-200012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_200101-200512.nc noresm_pr_197001-200512.nc\n",
       "2018-03-21 03:01:05 : Created by RegCM RegCM Model program</dd><dt><span>source :</span></dt><dd>RegCM Model output file</dd><dt><span>institution :</span></dt><dd>Oak Ridge National Laboratory</dd><dt><span>project_id :</span></dt><dd>CORDEX</dd><dt><span>ipcc_scenario_code :</span></dt><dd>HISTORICAL</dd><dt><span>institute_id :</span></dt><dd>ORNL</dd><dt><span>note :</span></dt><dd>The domain is larger than WAS-22</dd><dt><span>comment :</span></dt><dd>RegCM CORDEX SAsia25 run</dd><dt><span>experiment :</span></dt><dd>WAS-22</dd><dt><span>driving_model_ensemble_member :</span></dt><dd>r1i1p1</dd><dt><span>creation_date :</span></dt><dd>2019-09-19T16:13:52Z</dd><dt><span>CORDEX_domain :</span></dt><dd>WAS-22</dd><dt><span>rcm_version_id :</span></dt><dd>v0</dd><dt><span>ICTP_version_note :</span></dt><dd>Model run at ORNL on Titan</dd><dt><span>contact :</span></dt><dd>mashfaq@ornl.gov</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>tracking_id :</span></dt><dd>e18baf90-8c3e-11e9-a8fd-f04da273d2fb</dd><dt><span>title :</span></dt><dd>ICTP Regional Climatic model V4</dd><dt><span>references :</span></dt><dd>http://gforge.ictp.it/gf/project/regcm</dd><dt><span>model_revision :</span></dt><dd>tag-4.7.0</dd><dt><span>projection :</span></dt><dd>ROTMER</dd><dt><span>grid_size_in_meters :</span></dt><dd>25000.0</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>13.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>70.0</dd><dt><span>grid_north_pole_latitude :</span></dt><dd>13.0</dd><dt><span>grid_north_pole_longitude :</span></dt><dd>70.0</dd><dt><span>grid_factor :</span></dt><dd>0.0</dd><dt><span>landsurface_model :</span></dt><dd>clm4.5</dd><dt><span>model_icbc_data_source :</span></dt><dd>NO_85</dd><dt><span>model_sst_data_source :</span></dt><dd>NO_85</dd><dt><span>boundary_nspgx :</span></dt><dd>30</dd><dt><span>boundary_nspgd :</span></dt><dd>30</dd><dt><span>boundary_high_nudge :</span></dt><dd>8.0</dd><dt><span>boundary_medium_nudge :</span></dt><dd>6.0</dd><dt><span>boundary_low_nudge :</span></dt><dd>4.0</dd><dt><span>boundary_nm :</span></dt><dd>-1.0</dd><dt><span>boundary_dm :</span></dt><dd>-1.0</dd><dt><span>model_is_restarted :</span></dt><dd>No</dd><dt><span>model_simulation_initial_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_end :</span></dt><dd> 2005-12-31 00:00:00 UTC</dd><dt><span>atmosphere_time_step_in_seconds :</span></dt><dd>40.0</dd><dt><span>surface_interaction_time_step_in_seconds :</span></dt><dd>480.0</dd><dt><span>convection_time_step_in_seconds :</span></dt><dd>240.0</dd><dt><span>radiation_scheme_time_step_in_seconds :</span></dt><dd>1800.0</dd><dt><span>absorption_emission_time_step_in_seconds :</span></dt><dd>64800.0</dd><dt><span>dynamical_core :</span></dt><dd>1</dd><dt><span>asselin_filter_nu_1 :</span></dt><dd>0.0625</dd><dt><span>asselin_filter_nu_2 :</span></dt><dd>0.0625</dd><dt><span>diffusion_hgt_factor :</span></dt><dd>1</dd><dt><span>upstream_mode :</span></dt><dd>Yes</dd><dt><span>off_centering_max :</span></dt><dd>0.25</dd><dt><span>stability_enhance :</span></dt><dd>Yes</dd><dt><span>temperature_extreme_gradient :</span></dt><dd>5.0</dd><dt><span>cloud_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>vapor_extreme_gradient_fraction :</span></dt><dd>0.2</dd><dt><span>tracer_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>lateral_boundary_condition_scheme :</span></dt><dd>5</dd><dt><span>semi_lagrangian_advection_scheme :</span></dt><dd>0</dd><dt><span>boundary_layer_scheme :</span></dt><dd>2</dd><dt><span>cumulus_convection_scheme_lnd :</span></dt><dd>4</dd><dt><span>cumulus_convection_scheme_ocn :</span></dt><dd>5</dd><dt><span>moisture_scheme :</span></dt><dd>1</dd><dt><span>ocean_flux_scheme :</span></dt><dd>2</dd><dt><span>zeng_ocean_roughness_formula :</span></dt><dd>1</dd><dt><span>zeng_ocean_roughness_method :</span></dt><dd>1</dd><dt><span>pressure_gradient_scheme :</span></dt><dd>0</dd><dt><span>surface_emissivity_factor_computed :</span></dt><dd>0</dd><dt><span>lake_model_activated :</span></dt><dd>0</dd><dt><span>chemical_aerosol_scheme_activated :</span></dt><dd>0</dd><dt><span>diurnal_cycle_sst_scheme :</span></dt><dd>0</dd><dt><span>ocean_precipitaion_cooling_effect :</span></dt><dd>0</dd><dt><span>ocean_albedo_from_whitecapping :</span></dt><dd>0</dd><dt><span>simple_sea_ice_scheme :</span></dt><dd>0</dd><dt><span>seasonal_desert_albedo :</span></dt><dd>0</dd><dt><span>convective_lwp_as_large_scale :</span></dt><dd>0</dd><dt><span>large_scale_cloud_fraction_scheme :</span></dt><dd>0</dd><dt><span>ocean_stratiform_clouds_scheme :</span></dt><dd>1</dd><dt><span>rrtm_radiation_scheme_activated :</span></dt><dd>0</dd><dt><span>climatic_ozone_input_dataset :</span></dt><dd>0</dd><dt><span>climatic_aerosol_input_dataset :</span></dt><dd>0</dd><dt><span>static_solar_constant_used :</span></dt><dd>0</dd><dt><span>cumulus_cloud_model :</span></dt><dd>1</dd><dt><span>sun_year_offset :</span></dt><dd>0.0</dd><dt><span>fix_solar_parameters :</span></dt><dd>0</dd><dt><span>cloud_bottom_level_with_no_clouds :</span></dt><dd>1</dd><dt><span>cloud_rh_with_fcc_one :</span></dt><dd>1.01</dd><dt><span>cloud_rh_threshold_for_land :</span></dt><dd>0.8</dd><dt><span>cloud_rh_threshold_for_ocean :</span></dt><dd>0.9</dd><dt><span>cloud_rh1_limit_temperature :</span></dt><dd>238.0</dd><dt><span>cloud_cloud_fraction_maximum :</span></dt><dd>0.75</dd><dt><span>cloud_condensation_threshold :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_fraction_max_for_convection :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_liqwat_max_for_convection :</span></dt><dd>0.0003</dd><dt><span>cloud_shallow_convective_cf_param :</span></dt><dd>0.07</dd><dt><span>cloud_deep_convective_cf_param :</span></dt><dd>0.14</dd><dt><span>cloud_k2_convective_cf_param :</span></dt><dd>500.0</dd><dt><span>cloud_surface_radiation_hack :</span></dt><dd>No</dd><dt><span>cloud_arctic_cloud_correction :</span></dt><dd>Yes</dd><dt><span>subex_auto_conversion_rate_for_land :</span></dt><dd>0.00025</dd><dt><span>subex_auto_conversion_rate_for_ocean :</span></dt><dd>0.00025</dd><dt><span>subex_gultepe_factor_when_rain_for_land :</span></dt><dd>0.4</dd><dt><span>subex_gultepe_factor_when_rain_for_ocean :</span></dt><dd>0.4</dd><dt><span>subex_land_raindrop_evaporation_rate :</span></dt><dd>0.0002</dd><dt><span>subex_ocean_raindrop_evaporation_rate :</span></dt><dd>0.0001</dd><dt><span>subex_land_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>subex_ocean_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>mit_lowest_convection_sigma :</span></dt><dd>0.95</dd><dt><span>mit_autoconversion_threshold_mixing_over_ocean :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_mixing_over_land :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_temperature :</span></dt><dd>-55.0</dd><dt><span>mit_mixing_coefficient_in_entrainment :</span></dt><dd>1.5</dd><dt><span>mit_fractional_area_unsaturated_downdraft :</span></dt><dd>0.05</dd><dt><span>mit_fractional_precip_outside_cloud :</span></dt><dd>0.12</dd><dt><span>mit_pressure_velocity_of_rain :</span></dt><dd>50.0</dd><dt><span>mit_pressure_velocity_of_snow :</span></dt><dd>5.5</dd><dt><span>mit_rain_evaporation_coefficient :</span></dt><dd>1.0</dd><dt><span>mit_snow_evaporation_coefficient :</span></dt><dd>0.8</dd><dt><span>mit_momentum_transport_coefficient :</span></dt><dd>0.7</dd><dt><span>mit_downdraft_velocity_coefficient :</span></dt><dd>10.0</dd><dt><span>mit_max_parcel_neg_temp_perturbation :</span></dt><dd>0.9</dd><dt><span>mit_approach_rate_quasi_eq_coeff_a :</span></dt><dd>0.2</dd><dt><span>mit_approach_rate_quasi_eq_coeff_d :</span></dt><dd>0.1</dd><dt><span>mit_maximum_land_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>mit_maximum_ocean_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>tiedtke_actual_scheme :</span></dt><dd>4</dd><dt><span>tiedtke_entrainment_rate_downdraft :</span></dt><dd>0.0003</dd><dt><span>tiedtke_entrainment_rate_deep_land :</span></dt><dd>0.00075</dd><dt><span>tiedtke_entrainment_rate_deep_ocean :</span></dt><dd>0.00075</dd><dt><span>tiedtke_penetrative :</span></dt><dd>Yes</dd><dt><span>tiedtke_midlevel :</span></dt><dd>Yes</dd><dt><span>tiedtke_shallow :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_downdraft :</span></dt><dd>Yes</dd><dt><span>tiedtke_prognostic_cloud :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_friction :</span></dt><dd>Yes</dd><dt><span>tiedtke_ke_dissipation :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_transport :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_smooth_massflux :</span></dt><dd>No</dd><dt><span>tiedtke_shallow_wstar_closure :</span></dt><dd>No</dd><dt><span>tiedtke_detrainment_rate_deep_land :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_detrainment_rate_deep_ocean :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_shallow_entrainment :</span></dt><dd>2.0</dd><dt><span>tiedtke_cloud_cover_evap_over_land :</span></dt><dd>0.05</dd><dt><span>tiedtke_cloud_cover_evap_over_ocean :</span></dt><dd>0.05</dd><dt><span>tiedtke_coeff_evap_over_land :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_coeff_evap_over_ocean :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_critical_rh_over_land :</span></dt><dd>0.9</dd><dt><span>tiedtke_critical_rh_over_ocean :</span></dt><dd>0.9</dd><dt><span>tiedtke_cloud_water_conv_over_land :</span></dt><dd>0.03</dd><dt><span>tiedtke_cloud_water_conv_over_ocean :</span></dt><dd>0.0014</dd><dt><span>tiedtke_cape_adjustment_timescale :</span></dt><dd>2400.0</dd><dt><span>uwpbl_advection_scheme :</span></dt><dd>0</dd><dt><span>uwpbl_cloud_evap_entr_incr_efficiency :</span></dt><dd>15.0</dd><dt><span>uwpbl_eddy_LS_stable_PBL_scaling :</span></dt><dd>1.5</dd><dt><span>uwpbl_czero :</span></dt><dd>5.869</dd><dt><span>uwpbl_nuk :</span></dt><dd>5.0</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>driving_experiment_name :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>ICTP-RegCM4-7</dd><dt><span>driving_experiment :</span></dt><dd>NCC-NorESM1-M, historical, r1i1p1</dd><dt><span>driving_model_id :</span></dt><dd>NCC-NorESM1-M</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.9rc1 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (time: 299, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-01-16T12:00:00 ... 2005-11-16\n",
       "  * lon        (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat        (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1981-01-01 00:00:00 ... 2005-12-01 00:00:00\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:05:10 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    driving_experiment:                              NCC-NorESM1-M, historica...\n",
       "    driving_model_id:                                NCC-NorESM1-M\n",
       "    CDO:                                             Climate Data Operators v..."
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#to select the year from 1980 to 2015\n",
    "data = data.sel(time=slice('1981-01-16T12:00:00.000000000','2005-12-16T00:00:00.000000000'))\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c811b0f2",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 100, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-06-16 ... 2005-09-16\n",
       "  * lon        (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat        (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
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       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:05:10 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    driving_experiment:                              NCC-NorESM1-M, historica...\n",
       "    driving_model_id:                                NCC-NorESM1-M\n",
       "    CDO:                                             Climate Data Operators v...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f327c3fc-a40a-4627-a1b1-ad15d26e52ac' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f327c3fc-a40a-4627-a1b1-ad15d26e52ac' 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-c8622df3-3601-4e5e-a06e-ac243087fac7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c8622df3-3601-4e5e-a06e-ac243087fac7' 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-88c7db56-927c-4f65-bc32-1b8dffe9db56' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-88c7db56-927c-4f65-bc32-1b8dffe9db56' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d626d7bb-4363-400d-964b-63879a1aa324' class='xr-var-data-in' type='checkbox'><label for='data-d626d7bb-4363-400d-964b-63879a1aa324' title='Show/Hide data 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-aa84919e-e93e-46c1-977c-d94e0b8df2c5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa84919e-e93e-46c1-977c-d94e0b8df2c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22e3189b-cda3-4583-b2a9-5b2c0c88aac6' class='xr-var-data-in' type='checkbox'><label for='data-22e3189b-cda3-4583-b2a9-5b2c0c88aac6' title='Show/Hide data 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-b8a01cae-fc8c-4776-a4f8-95bf3ab6f724' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b8a01cae-fc8c-4776-a4f8-95bf3ab6f724' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66e06352-b900-4dd1-ab52-51b4693e98cf' class='xr-var-data-in' type='checkbox'><label for='data-66e06352-b900-4dd1-ab52-51b4693e98cf' title='Show/Hide data 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-9b4e88af-9de2-41da-b7c0-13b253fa691b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9b4e88af-9de2-41da-b7c0-13b253fa691b' 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-7bc092c7-0f43-4abf-978e-4d635b695edf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7bc092c7-0f43-4abf-978e-4d635b695edf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-185325ad-0e15-424e-be74-b1e64e50f328' class='xr-var-data-in' type='checkbox'><label for='data-185325ad-0e15-424e-be74-b1e64e50f328' title='Show/Hide data 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-3206224e-a966-4806-9b1e-9af334e5c488' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3206224e-a966-4806-9b1e-9af334e5c488' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7dc7b92-1229-4131-97ff-6368a6abf73f' class='xr-var-data-in' type='checkbox'><label for='data-b7dc7b92-1229-4131-97ff-6368a6abf73f' title='Show/Hide data 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-9000d589-2870-4cd1-a583-ba9fa3439a2f' class='xr-section-summary-in' type='checkbox'  ><label for='section-9000d589-2870-4cd1-a583-ba9fa3439a2f' class='xr-section-summary' >Attributes: <span>(165)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>history :</span></dt><dd>Thu Jul 07 17:05:10 2022: cdo remapnn,grid1.des noresm_pr_197001-200512.nc noresm1_remap.nc\n",
       "Mon Jun 27 15:36:42 2022: cdo mergetime pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_197001-198012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_198101-199012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_199101-200012.nc pr_WAS-22_NCC-NorESM1-M_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_200101-200512.nc noresm_pr_197001-200512.nc\n",
       "2018-03-21 03:01:05 : Created by RegCM RegCM Model program</dd><dt><span>source :</span></dt><dd>RegCM Model output file</dd><dt><span>institution :</span></dt><dd>Oak Ridge National Laboratory</dd><dt><span>project_id :</span></dt><dd>CORDEX</dd><dt><span>ipcc_scenario_code :</span></dt><dd>HISTORICAL</dd><dt><span>institute_id :</span></dt><dd>ORNL</dd><dt><span>note :</span></dt><dd>The domain is larger than WAS-22</dd><dt><span>comment :</span></dt><dd>RegCM CORDEX SAsia25 run</dd><dt><span>experiment :</span></dt><dd>WAS-22</dd><dt><span>driving_model_ensemble_member :</span></dt><dd>r1i1p1</dd><dt><span>creation_date :</span></dt><dd>2019-09-19T16:13:52Z</dd><dt><span>CORDEX_domain :</span></dt><dd>WAS-22</dd><dt><span>rcm_version_id :</span></dt><dd>v0</dd><dt><span>ICTP_version_note :</span></dt><dd>Model run at ORNL on Titan</dd><dt><span>contact :</span></dt><dd>mashfaq@ornl.gov</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>tracking_id :</span></dt><dd>e18baf90-8c3e-11e9-a8fd-f04da273d2fb</dd><dt><span>title :</span></dt><dd>ICTP Regional Climatic model V4</dd><dt><span>references :</span></dt><dd>http://gforge.ictp.it/gf/project/regcm</dd><dt><span>model_revision :</span></dt><dd>tag-4.7.0</dd><dt><span>projection :</span></dt><dd>ROTMER</dd><dt><span>grid_size_in_meters :</span></dt><dd>25000.0</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>13.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>70.0</dd><dt><span>grid_north_pole_latitude :</span></dt><dd>13.0</dd><dt><span>grid_north_pole_longitude :</span></dt><dd>70.0</dd><dt><span>grid_factor :</span></dt><dd>0.0</dd><dt><span>landsurface_model :</span></dt><dd>clm4.5</dd><dt><span>model_icbc_data_source :</span></dt><dd>NO_85</dd><dt><span>model_sst_data_source :</span></dt><dd>NO_85</dd><dt><span>boundary_nspgx :</span></dt><dd>30</dd><dt><span>boundary_nspgd :</span></dt><dd>30</dd><dt><span>boundary_high_nudge :</span></dt><dd>8.0</dd><dt><span>boundary_medium_nudge :</span></dt><dd>6.0</dd><dt><span>boundary_low_nudge :</span></dt><dd>4.0</dd><dt><span>boundary_nm :</span></dt><dd>-1.0</dd><dt><span>boundary_dm :</span></dt><dd>-1.0</dd><dt><span>model_is_restarted :</span></dt><dd>No</dd><dt><span>model_simulation_initial_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_end :</span></dt><dd> 2005-12-31 00:00:00 UTC</dd><dt><span>atmosphere_time_step_in_seconds :</span></dt><dd>40.0</dd><dt><span>surface_interaction_time_step_in_seconds :</span></dt><dd>480.0</dd><dt><span>convection_time_step_in_seconds :</span></dt><dd>240.0</dd><dt><span>radiation_scheme_time_step_in_seconds :</span></dt><dd>1800.0</dd><dt><span>absorption_emission_time_step_in_seconds :</span></dt><dd>64800.0</dd><dt><span>dynamical_core :</span></dt><dd>1</dd><dt><span>asselin_filter_nu_1 :</span></dt><dd>0.0625</dd><dt><span>asselin_filter_nu_2 :</span></dt><dd>0.0625</dd><dt><span>diffusion_hgt_factor :</span></dt><dd>1</dd><dt><span>upstream_mode :</span></dt><dd>Yes</dd><dt><span>off_centering_max :</span></dt><dd>0.25</dd><dt><span>stability_enhance :</span></dt><dd>Yes</dd><dt><span>temperature_extreme_gradient :</span></dt><dd>5.0</dd><dt><span>cloud_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>vapor_extreme_gradient_fraction :</span></dt><dd>0.2</dd><dt><span>tracer_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>lateral_boundary_condition_scheme :</span></dt><dd>5</dd><dt><span>semi_lagrangian_advection_scheme :</span></dt><dd>0</dd><dt><span>boundary_layer_scheme :</span></dt><dd>2</dd><dt><span>cumulus_convection_scheme_lnd :</span></dt><dd>4</dd><dt><span>cumulus_convection_scheme_ocn :</span></dt><dd>5</dd><dt><span>moisture_scheme :</span></dt><dd>1</dd><dt><span>ocean_flux_scheme :</span></dt><dd>2</dd><dt><span>zeng_ocean_roughness_formula :</span></dt><dd>1</dd><dt><span>zeng_ocean_roughness_method :</span></dt><dd>1</dd><dt><span>pressure_gradient_scheme :</span></dt><dd>0</dd><dt><span>surface_emissivity_factor_computed :</span></dt><dd>0</dd><dt><span>lake_model_activated :</span></dt><dd>0</dd><dt><span>chemical_aerosol_scheme_activated :</span></dt><dd>0</dd><dt><span>diurnal_cycle_sst_scheme :</span></dt><dd>0</dd><dt><span>ocean_precipitaion_cooling_effect :</span></dt><dd>0</dd><dt><span>ocean_albedo_from_whitecapping :</span></dt><dd>0</dd><dt><span>simple_sea_ice_scheme :</span></dt><dd>0</dd><dt><span>seasonal_desert_albedo :</span></dt><dd>0</dd><dt><span>convective_lwp_as_large_scale :</span></dt><dd>0</dd><dt><span>large_scale_cloud_fraction_scheme :</span></dt><dd>0</dd><dt><span>ocean_stratiform_clouds_scheme :</span></dt><dd>1</dd><dt><span>rrtm_radiation_scheme_activated :</span></dt><dd>0</dd><dt><span>climatic_ozone_input_dataset :</span></dt><dd>0</dd><dt><span>climatic_aerosol_input_dataset :</span></dt><dd>0</dd><dt><span>static_solar_constant_used :</span></dt><dd>0</dd><dt><span>cumulus_cloud_model :</span></dt><dd>1</dd><dt><span>sun_year_offset :</span></dt><dd>0.0</dd><dt><span>fix_solar_parameters :</span></dt><dd>0</dd><dt><span>cloud_bottom_level_with_no_clouds :</span></dt><dd>1</dd><dt><span>cloud_rh_with_fcc_one :</span></dt><dd>1.01</dd><dt><span>cloud_rh_threshold_for_land :</span></dt><dd>0.8</dd><dt><span>cloud_rh_threshold_for_ocean :</span></dt><dd>0.9</dd><dt><span>cloud_rh1_limit_temperature :</span></dt><dd>238.0</dd><dt><span>cloud_cloud_fraction_maximum :</span></dt><dd>0.75</dd><dt><span>cloud_condensation_threshold :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_fraction_max_for_convection :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_liqwat_max_for_convection :</span></dt><dd>0.0003</dd><dt><span>cloud_shallow_convective_cf_param :</span></dt><dd>0.07</dd><dt><span>cloud_deep_convective_cf_param :</span></dt><dd>0.14</dd><dt><span>cloud_k2_convective_cf_param :</span></dt><dd>500.0</dd><dt><span>cloud_surface_radiation_hack :</span></dt><dd>No</dd><dt><span>cloud_arctic_cloud_correction :</span></dt><dd>Yes</dd><dt><span>subex_auto_conversion_rate_for_land :</span></dt><dd>0.00025</dd><dt><span>subex_auto_conversion_rate_for_ocean :</span></dt><dd>0.00025</dd><dt><span>subex_gultepe_factor_when_rain_for_land :</span></dt><dd>0.4</dd><dt><span>subex_gultepe_factor_when_rain_for_ocean :</span></dt><dd>0.4</dd><dt><span>subex_land_raindrop_evaporation_rate :</span></dt><dd>0.0002</dd><dt><span>subex_ocean_raindrop_evaporation_rate :</span></dt><dd>0.0001</dd><dt><span>subex_land_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>subex_ocean_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>mit_lowest_convection_sigma :</span></dt><dd>0.95</dd><dt><span>mit_autoconversion_threshold_mixing_over_ocean :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_mixing_over_land :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_temperature :</span></dt><dd>-55.0</dd><dt><span>mit_mixing_coefficient_in_entrainment :</span></dt><dd>1.5</dd><dt><span>mit_fractional_area_unsaturated_downdraft :</span></dt><dd>0.05</dd><dt><span>mit_fractional_precip_outside_cloud :</span></dt><dd>0.12</dd><dt><span>mit_pressure_velocity_of_rain :</span></dt><dd>50.0</dd><dt><span>mit_pressure_velocity_of_snow :</span></dt><dd>5.5</dd><dt><span>mit_rain_evaporation_coefficient :</span></dt><dd>1.0</dd><dt><span>mit_snow_evaporation_coefficient :</span></dt><dd>0.8</dd><dt><span>mit_momentum_transport_coefficient :</span></dt><dd>0.7</dd><dt><span>mit_downdraft_velocity_coefficient :</span></dt><dd>10.0</dd><dt><span>mit_max_parcel_neg_temp_perturbation :</span></dt><dd>0.9</dd><dt><span>mit_approach_rate_quasi_eq_coeff_a :</span></dt><dd>0.2</dd><dt><span>mit_approach_rate_quasi_eq_coeff_d :</span></dt><dd>0.1</dd><dt><span>mit_maximum_land_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>mit_maximum_ocean_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>tiedtke_actual_scheme :</span></dt><dd>4</dd><dt><span>tiedtke_entrainment_rate_downdraft :</span></dt><dd>0.0003</dd><dt><span>tiedtke_entrainment_rate_deep_land :</span></dt><dd>0.00075</dd><dt><span>tiedtke_entrainment_rate_deep_ocean :</span></dt><dd>0.00075</dd><dt><span>tiedtke_penetrative :</span></dt><dd>Yes</dd><dt><span>tiedtke_midlevel :</span></dt><dd>Yes</dd><dt><span>tiedtke_shallow :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_downdraft :</span></dt><dd>Yes</dd><dt><span>tiedtke_prognostic_cloud :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_friction :</span></dt><dd>Yes</dd><dt><span>tiedtke_ke_dissipation :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_transport :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_smooth_massflux :</span></dt><dd>No</dd><dt><span>tiedtke_shallow_wstar_closure :</span></dt><dd>No</dd><dt><span>tiedtke_detrainment_rate_deep_land :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_detrainment_rate_deep_ocean :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_shallow_entrainment :</span></dt><dd>2.0</dd><dt><span>tiedtke_cloud_cover_evap_over_land :</span></dt><dd>0.05</dd><dt><span>tiedtke_cloud_cover_evap_over_ocean :</span></dt><dd>0.05</dd><dt><span>tiedtke_coeff_evap_over_land :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_coeff_evap_over_ocean :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_critical_rh_over_land :</span></dt><dd>0.9</dd><dt><span>tiedtke_critical_rh_over_ocean :</span></dt><dd>0.9</dd><dt><span>tiedtke_cloud_water_conv_over_land :</span></dt><dd>0.03</dd><dt><span>tiedtke_cloud_water_conv_over_ocean :</span></dt><dd>0.0014</dd><dt><span>tiedtke_cape_adjustment_timescale :</span></dt><dd>2400.0</dd><dt><span>uwpbl_advection_scheme :</span></dt><dd>0</dd><dt><span>uwpbl_cloud_evap_entr_incr_efficiency :</span></dt><dd>15.0</dd><dt><span>uwpbl_eddy_LS_stable_PBL_scaling :</span></dt><dd>1.5</dd><dt><span>uwpbl_czero :</span></dt><dd>5.869</dd><dt><span>uwpbl_nuk :</span></dt><dd>5.0</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>driving_experiment_name :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>ICTP-RegCM4-7</dd><dt><span>driving_experiment :</span></dt><dd>NCC-NorESM1-M, historical, r1i1p1</dd><dt><span>driving_model_id :</span></dt><dd>NCC-NorESM1-M</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.9rc1 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (time: 100, bnds: 2, lon: 32, lat: 40)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1981-06-16 ... 2005-09-16\n",
       "  * lon        (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat        (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1981-06-01 00:00:00 ... 2005-10-01 00:00:00\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Thu Jul 07 17:05:10 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    driving_experiment:                              NCC-NorESM1-M, historica...\n",
       "    driving_model_id:                                NCC-NorESM1-M\n",
       "    CDO:                                             Climate Data Operators v..."
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#selecting only JJAS months\n",
    "\n",
    "def is_jjas(month):\n",
    "    return (month >= 6) & (month <= 9)\n",
    "\n",
    "jjas_data = data.sel(time=is_jjas(data['time.month']))\n",
    "\n",
    "jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "be94f5d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#jjas_data.x.values\n",
    "#jjas_data.y.values\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a41e4a60",
   "metadata": {},
   "outputs": [],
   "source": [
    "#to select the x and y coordinates\n",
    "#jjas_data = jjas_data.sel(x=slice(1000000.,5275000.),y=slice(2000000.,4175000.))\n",
    "#jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "18269e45",
   "metadata": {},
   "outputs": [
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       "\n",
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (lat: 40, lon: 32)&gt;\n",
       "array([[2.7742273e-05, 2.8306044e-05, 3.0248149e-05, ..., 6.8471825e-05,\n",
       "        7.5464734e-05, 8.6877772e-05],\n",
       "       [2.6579350e-05, 2.7978740e-05, 2.8496665e-05, ..., 7.0115042e-05,\n",
       "        8.2230203e-05, 8.7119966e-05],\n",
       "       [2.5786814e-05, 2.6952594e-05, 2.7536636e-05, ..., 7.2977811e-05,\n",
       "        8.9453941e-05, 1.0093173e-04],\n",
       "       ...,\n",
       "       [1.6560616e-04, 1.9095752e-04, 2.0814226e-04, ..., 2.0336338e-04,\n",
       "        2.2328299e-04, 1.9262660e-04],\n",
       "       [1.7951433e-04, 2.0935173e-04, 2.6357861e-04, ..., 1.8205261e-04,\n",
       "        2.3664134e-04, 2.5447601e-04],\n",
       "       [1.9282992e-04, 3.1452853e-04, 5.0945889e-04, ..., 1.8248010e-04,\n",
       "        2.6029523e-04, 3.2178455e-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-ca1b23d5-6428-4e35-8eed-9140a795b79c' class='xr-array-in' type='checkbox' checked><label for='section-ca1b23d5-6428-4e35-8eed-9140a795b79c' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2.774e-05 2.831e-05 3.025e-05 ... 0.0001825 0.0002603 0.0003218</span></div><div class='xr-array-data'><pre>array([[2.7742273e-05, 2.8306044e-05, 3.0248149e-05, ..., 6.8471825e-05,\n",
       "        7.5464734e-05, 8.6877772e-05],\n",
       "       [2.6579350e-05, 2.7978740e-05, 2.8496665e-05, ..., 7.0115042e-05,\n",
       "        8.2230203e-05, 8.7119966e-05],\n",
       "       [2.5786814e-05, 2.6952594e-05, 2.7536636e-05, ..., 7.2977811e-05,\n",
       "        8.9453941e-05, 1.0093173e-04],\n",
       "       ...,\n",
       "       [1.6560616e-04, 1.9095752e-04, 2.0814226e-04, ..., 2.0336338e-04,\n",
       "        2.2328299e-04, 1.9262660e-04],\n",
       "       [1.7951433e-04, 2.0935173e-04, 2.6357861e-04, ..., 1.8205261e-04,\n",
       "        2.3664134e-04, 2.5447601e-04],\n",
       "       [1.9282992e-04, 3.1452853e-04, 5.0945889e-04, ..., 1.8248010e-04,\n",
       "        2.6029523e-04, 3.2178455e-04]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-cf5dab6d-0dec-452c-9691-a14931ef1043' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cf5dab6d-0dec-452c-9691-a14931ef1043' 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-2acc3482-046d-428f-bb04-e641e2963110' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2acc3482-046d-428f-bb04-e641e2963110' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b11e13bc-cac3-41e5-b8d1-d48daebdff77' class='xr-var-data-in' type='checkbox'><label for='data-b11e13bc-cac3-41e5-b8d1-d48daebdff77' title='Show/Hide data 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-1cc6da21-7120-4eca-a596-19ee09c5053a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1cc6da21-7120-4eca-a596-19ee09c5053a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e6697df-e574-4f9d-a2f7-27f8f95507ca' class='xr-var-data-in' type='checkbox'><label for='data-6e6697df-e574-4f9d-a2f7-27f8f95507ca' title='Show/Hide data 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-ea29fc3c-373b-40c2-ba33-929b47630fb5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ea29fc3c-373b-40c2-ba33-929b47630fb5' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'pr' (lat: 40, lon: 32)>\n",
       "array([[2.7742273e-05, 2.8306044e-05, 3.0248149e-05, ..., 6.8471825e-05,\n",
       "        7.5464734e-05, 8.6877772e-05],\n",
       "       [2.6579350e-05, 2.7978740e-05, 2.8496665e-05, ..., 7.0115042e-05,\n",
       "        8.2230203e-05, 8.7119966e-05],\n",
       "       [2.5786814e-05, 2.6952594e-05, 2.7536636e-05, ..., 7.2977811e-05,\n",
       "        8.9453941e-05, 1.0093173e-04],\n",
       "       ...,\n",
       "       [1.6560616e-04, 1.9095752e-04, 2.0814226e-04, ..., 2.0336338e-04,\n",
       "        2.2328299e-04, 1.9262660e-04],\n",
       "       [1.7951433e-04, 2.0935173e-04, 2.6357861e-04, ..., 1.8205261e-04,\n",
       "        2.3664134e-04, 2.5447601e-04],\n",
       "       [1.9282992e-04, 3.1452853e-04, 5.0945889e-04, ..., 1.8248010e-04,\n",
       "        2.6029523e-04, 3.2178455e-04]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#getting the mean for JJAS data\n",
    "jjas_mean = jjas_data.pr.mean('time')\n",
    " \n",
    "jjas_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "6f88bd72",
   "metadata": {},
   "outputs": [
    {
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       ".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",
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       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (lat: 40, lon: 32)&gt;\n",
       "array([[ 2.39693241,  2.44564216,  2.61344011, ...,  5.9159657 ,\n",
       "         6.52015298,  7.50623946],\n",
       "       [ 2.29645581,  2.41736314,  2.46211182, ...,  6.05793963,\n",
       "         7.10468951,  7.52716509],\n",
       "       [ 2.22798074,  2.32870408,  2.37916539, ...,  6.30528289,\n",
       "         7.72882048,  8.72050126],\n",
       "       ...,\n",
       "       [14.30837265, 16.49872991, 17.98349102, ..., 17.57059596,\n",
       "        19.29165004, 16.64293804],\n",
       "       [15.51003833, 18.08798905, 22.77319171, ..., 15.72934538,\n",
       "        20.4458117 , 21.98672695],\n",
       "       [16.66050483, 27.17526499, 44.01724767, ..., 15.76628066,\n",
       "        22.48950787, 27.80218525]])\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-27965af6-c22e-4904-a37c-fce6dd14bb64' class='xr-array-in' type='checkbox' checked><label for='section-27965af6-c22e-4904-a37c-fce6dd14bb64' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2.397 2.446 2.613 2.655 2.709 2.727 ... 22.21 17.96 15.77 22.49 27.8</span></div><div class='xr-array-data'><pre>array([[ 2.39693241,  2.44564216,  2.61344011, ...,  5.9159657 ,\n",
       "         6.52015298,  7.50623946],\n",
       "       [ 2.29645581,  2.41736314,  2.46211182, ...,  6.05793963,\n",
       "         7.10468951,  7.52716509],\n",
       "       [ 2.22798074,  2.32870408,  2.37916539, ...,  6.30528289,\n",
       "         7.72882048,  8.72050126],\n",
       "       ...,\n",
       "       [14.30837265, 16.49872991, 17.98349102, ..., 17.57059596,\n",
       "        19.29165004, 16.64293804],\n",
       "       [15.51003833, 18.08798905, 22.77319171, ..., 15.72934538,\n",
       "        20.4458117 , 21.98672695],\n",
       "       [16.66050483, 27.17526499, 44.01724767, ..., 15.76628066,\n",
       "        22.48950787, 27.80218525]])</pre></div></div></li><li class='xr-section-item'><input id='section-636163fb-c6a3-4b03-8252-3e70e81f7262' class='xr-section-summary-in' type='checkbox'  checked><label for='section-636163fb-c6a3-4b03-8252-3e70e81f7262' 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-937fa4b4-78ad-43da-81e8-dc1719a746dc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-937fa4b4-78ad-43da-81e8-dc1719a746dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88af298b-abdd-4a23-98cd-1797c55beac2' class='xr-var-data-in' type='checkbox'><label for='data-88af298b-abdd-4a23-98cd-1797c55beac2' title='Show/Hide data 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-a5045a5d-69b8-436c-bdf8-3e11aa042152' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a5045a5d-69b8-436c-bdf8-3e11aa042152' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6f627e1b-8cc8-48b6-bb87-3a5b0cee8b06' class='xr-var-data-in' type='checkbox'><label for='data-6f627e1b-8cc8-48b6-bb87-3a5b0cee8b06' title='Show/Hide data 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-27c7f5b6-f6b2-4378-88a1-e66c19bdd895' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-27c7f5b6-f6b2-4378-88a1-e66c19bdd895' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'pr' (lat: 40, lon: 32)>\n",
       "array([[ 2.39693241,  2.44564216,  2.61344011, ...,  5.9159657 ,\n",
       "         6.52015298,  7.50623946],\n",
       "       [ 2.29645581,  2.41736314,  2.46211182, ...,  6.05793963,\n",
       "         7.10468951,  7.52716509],\n",
       "       [ 2.22798074,  2.32870408,  2.37916539, ...,  6.30528289,\n",
       "         7.72882048,  8.72050126],\n",
       "       ...,\n",
       "       [14.30837265, 16.49872991, 17.98349102, ..., 17.57059596,\n",
       "        19.29165004, 16.64293804],\n",
       "       [15.51003833, 18.08798905, 22.77319171, ..., 15.72934538,\n",
       "        20.4458117 , 21.98672695],\n",
       "       [16.66050483, 27.17526499, 44.01724767, ..., 15.76628066,\n",
       "        22.48950787, 27.80218525]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float32 86.12 86.38 86.62 86.88 ... 93.12 93.38 93.62 93.88\n",
       "  * lat      (lat) float32 18.12 18.38 18.62 18.88 ... 27.12 27.38 27.62 27.88"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "noresm = jjas_mean*86400\n",
    "noresm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "6c5c5811",
   "metadata": {},
   "outputs": [
    {
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       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\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,  6.37751342,  7.69087195, ...,  9.08918594,\n",
       "         9.4232388 ,         nan],\n",
       "       [        nan,  9.49417366, 15.61373639, ...,  8.20178638,\n",
       "        11.77914159,         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-dd6c04bf-cd20-47c4-bd1c-e4b53c40ec74' class='xr-array-in' type='checkbox' checked><label for='section-dd6c04bf-cd20-47c4-bd1c-e4b53c40ec74' 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,  6.37751342,  7.69087195, ...,  9.08918594,\n",
       "         9.4232388 ,         nan],\n",
       "       [        nan,  9.49417366, 15.61373639, ...,  8.20178638,\n",
       "        11.77914159,         nan],\n",
       "       [        nan,         nan,         nan, ...,         nan,\n",
       "                nan,         nan]])</pre></div></div></li><li class='xr-section-item'><input id='section-6965ab59-3f49-42d6-a279-f88016f93573' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6965ab59-3f49-42d6-a279-f88016f93573' 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-ee5029a9-996f-4420-9962-545f942a1457' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee5029a9-996f-4420-9962-545f942a1457' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-075b0f0f-64c7-4589-8b39-dee80e86ea43' class='xr-var-data-in' type='checkbox'><label for='data-075b0f0f-64c7-4589-8b39-dee80e86ea43' title='Show/Hide data 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-c3e36c9f-f6b3-4a99-a56b-ba119157461f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c3e36c9f-f6b3-4a99-a56b-ba119157461f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d913636e-12d1-4940-96fc-c7a93c78cfe8' class='xr-var-data-in' type='checkbox'><label for='data-d913636e-12d1-4940-96fc-c7a93c78cfe8' title='Show/Hide data 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-67fb9bed-5a39-43a4-9940-09e5758ba4d8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-67fb9bed-5a39-43a4-9940-09e5758ba4d8' 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,  6.37751342,  7.69087195, ...,  9.08918594,\n",
       "         9.4232388 ,         nan],\n",
       "       [        nan,  9.49417366, 15.61373639, ...,  8.20178638,\n",
       "        11.77914159,         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": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bias = noresm - cru\n",
    "bias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "445388ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       ".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,  63.01133286,  74.72220535, ..., 107.16597738,\n",
       "         95.48891474,          nan],\n",
       "       [         nan, 110.47681652, 218.08553468, ..., 108.95678637,\n",
       "        135.91311816,          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-ecf46cf9-1c0a-4828-980f-5f49e22b2239' class='xr-array-in' type='checkbox' checked><label for='section-ecf46cf9-1c0a-4828-980f-5f49e22b2239' 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,  63.01133286,  74.72220535, ..., 107.16597738,\n",
       "         95.48891474,          nan],\n",
       "       [         nan, 110.47681652, 218.08553468, ..., 108.95678637,\n",
       "        135.91311816,          nan],\n",
       "       [         nan,          nan,          nan, ...,          nan,\n",
       "                 nan,          nan]])</pre></div></div></li><li class='xr-section-item'><input id='section-3ebdce1d-a2f9-476d-aee5-0717ae31f875' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3ebdce1d-a2f9-476d-aee5-0717ae31f875' 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-77edd69f-23be-47ec-8b76-d5c7f540e872' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-77edd69f-23be-47ec-8b76-d5c7f540e872' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3473a62c-1643-4c5d-b59a-d1446ea03e7a' class='xr-var-data-in' type='checkbox'><label for='data-3473a62c-1643-4c5d-b59a-d1446ea03e7a' title='Show/Hide data 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-c74a9689-f666-4ed9-a029-0fe020f96dd1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c74a9689-f666-4ed9-a029-0fe020f96dd1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f2a9570-f8da-4d5b-a2ae-d4f2e26dfb99' class='xr-var-data-in' type='checkbox'><label for='data-5f2a9570-f8da-4d5b-a2ae-d4f2e26dfb99' title='Show/Hide data 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-6ff24189-fb41-479f-bbc0-c5ae13e0ec07' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6ff24189-fb41-479f-bbc0-c5ae13e0ec07' 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,  63.01133286,  74.72220535, ..., 107.16597738,\n",
       "         95.48891474,          nan],\n",
       "       [         nan, 110.47681652, 218.08553468, ..., 108.95678637,\n",
       "        135.91311816,          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": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bias_percentage = ((noresm - cru)/cru)*100\n",
    "bias_percentage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "08ba09cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x684 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting annual_pr_mean\n",
    "\n",
    "#plotting with cartopy\n",
    "import cartopy.feature as cfeature\n",
    "\n",
    "plt.rcParams['font.size'] = '16'\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize=(12,9.5))\n",
    "\n",
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "ax.set_extent([88,93,20,27])\n",
    "\n",
    "\n",
    "m1 = ax.contourf(bias['lon'], bias['lat'],bias[:,:],\n",
    "                  levels=np.arange(-15,15+3,3), transform = ccrs.PlateCarree(),cmap='BrBG',extend='both')\n",
    "\n",
    " \n",
    "# Define the xticks for longitude\n",
    "ax.set_xticks(np.arange(87,94,1), crs=ccrs.PlateCarree())\n",
    "lon_formatter = cticker.LongitudeFormatter()\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "\n",
    "# Define the yticks for latitude\n",
    "ax.set_yticks(np.arange(20,28,1), crs=ccrs.PlateCarree())\n",
    "lat_formatter = cticker.LatitudeFormatter()\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "\n",
    "\n",
    "plt.colorbar(m1,ticks=np.arange(-15,15+3,3),  orientation = 'horizontal',shrink=0.5, fraction = 0.04 , label = 'mm/day')\n",
    "ax.coastlines(linewidth=3)\n",
    "ax.add_feature(cfeature.BORDERS,linewidth=3)\n",
    "\n",
    "\n",
    "\n",
    "plt.title('Seasonal Bias(RegCM NORESM-CRU)')\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/Seasonal Bias(noresm-cru).png\")\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "9003db92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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c5QOgL9bF73X9f2sf64ZzWbrPDkFKeV8IcQGokES0TSgDvZoCo5IQ339Q+nUtsRx4SwjRUEq53Uqc5GxN6j5cQSlvLVFW/99Sq0xxlNkESX5QuKXPTwjRXBgNKTcKr43Sj3AGQEoZhvIj9RdCFLYQP5fRrqHmZTxUPQSz6rwQIru+icCY0yhfEMH6/Q0oXx1DhJGXFKF4RihPMg+2FRLZp+ejFORlCx31/5MSIEv3zAvlIwCjsMzCbNqGVIamXyGhafSBlHKj2Z+1piFLHEIRrw+EhakfZr+1NQ6jfDANEULkMUsv9HbGo/QhdxIWhqPr++Ss9QUnhWHycbBZuLXf/QMLYWuAqvo+LIM9mVCcExhj872SUt5G+Si0Zei9gX9QCsZh+vtmz29j6zWA0r8mgdlW8s0nhPgyCTvXo7SivCelvJBEPHuYjvJcjzA/oO+qWQP0FkK8ZH5cCNENpf9spZRynw3nMr/PdiGEaGzpWdW36JTDcrcNoPaBD0b5DaYlEe+S+XttdPgHlObdP4XlaTtB+qbk5LB2H1ahPEsmI+H1fZlvo7RSbTI7JlD6Qa0Jtoq7an6/AIH6ZouTKC9ABZSZ/5HAt0Zx/4dSJT8qFFc3Z1EEsgrK15nBndAylKG6K/X55kYZ9HELMC4IXwPeEUIsQfmi9UGpNWZD6QtEShkhFLc5o4FNQoiFJEx1uIbSb2cvO1GaoP4RQvyK0uTZgcT9SymhntEzE4jSLPkiygOQ1NDttSgiv0oIMQWlMO5O4r6/UsB/+vtgaLZrhNJ2P9kB9iOl1AkhXtfbe0oIYSiE8qJMqShHMrUXfR5vohRQhuflKko/VA8S+gQ/QxmduV0I8SeKR5ZsKB823VBqa1fsvATDB9T/hBCRKGK4Vx9+DhgnhCiE0hzfGGXAV4RZHj+gFJ6rhRC/6I/3JkFYpdF12nOvlgKvCWXKj/EAIYvoa0C/oDznnaSUy+w4n03XoD/PXiHEGyjNz2eFEMYeXmqgPIvWmuMMHzLfJHc99iCljBVCfIv1JvHXUD6O5+m7WjahXFMzlGfnCAm1v+TOZXKfUcowA3mF4v3GEnP1A/E+Qpkus1R/3miUGnZflHuY1IcDUsolKAMNU4SU8or+I2AhynNh7OGlEkpNLgLT6V6W8rF2H0ajeIjZpH+Xj6P0s3dFGYz3kUzsSac2Sr968tclbRym6sg/lDloU1GE7xHKSMJrKE0XFSzEL4TyMN7Qx72N8tC9bRZvKIqgRaEUOEMwmzaAMiJwFsrXcKT+x9kGvGDhvP1QCsZoFOGahX74v1GcGVj2WmByXn1YDZR+vyf6885CET+TIbuW0lq5j01IPBQ6BuUrfTSJp4fMIPFUh1Yo000Mw40nonyISJSmOlA+Niag9Os8RhG/Yyj9fj5J2WhmZ7LeT1AEaC7KfKQYlGH0KzHyqGF0fxpYyaMmSu38of43Pgv8ZBYnBKWv95L+PPdQCtqPSRjiX0R/ni8snOMKib1/vIRSeMea3b+SKF+xD1Ge9+UoYmEpj4oo/bCR+t/jB5QPGQnUtvdeGcWTQHtbnl39sUC9vftScD6br8Eo3z/19yMa5f3YB3wKBBrF24J+akIyz5DVIfJm8Szmh/JBfEGfzwwLxzPpn5NDKKL+DKXV4RMgk4X49t7nK1if6iDRe2cB6qJUJI6gDCCLRSkbl2D2bpDMO2OLrUmkKYRSPpzT/+bPUVqcvsV0ipBd90EfngelTLqsf+Yeo5ShXa3kMx5FS5L19mSYm2MVfVW+J0rBnVuf8WLgOymlYRTjDBL8tZlzVkqpttsKZRLy7yj9ev8C70j9iD+hrGJgaPtvLs187QllZGaclLJJkkZraKQjhBBDUQZxhUopb6Ywj5UAUkpL03ScjiOuQUMjKYQQWVD06Wsp5YRk49sgfnv0GS5DqXlVRWkPPwPUk0oTTHGUIeTGFEERt7FSyo+NjLuMUr09glI7WSClHKs/XoQE8dsjpaxrZosmfhrpGiFEJqn3+GLYR+8MQEpZOhX5VkKpnVSTRis7OANnXYOGRlIIZTrWOyhOKpKds2hLn19HqQw8MbBVKCMy/0ZpztospbyI2ZwrkeD78G+j4LLAdSnlOH2cb1D65caanXM9yigwa/NtNDTSKzuEELtQmphDUPrLSqL0WaYYqayakWgZICfhlGvQ0EgKva6MszV+suJnJnwGDHN9CiSRtA9wUEppPN/lGoq3lSYonZe9UNqJzVmI4pniWyHESplc9VRDI/2wGqXvsB/KwIETKK7JFrnVKvtID9egkc5J6WjPxvr/py0d1A9zLoEyOlJFSnlPCPEFymgpH5SBFv+zkIVE8cCyGgfPgdHQ8GSklF+SzCg9Tyc9XING+ifZPr9ECYQogNJ3cFRKaT6p2RBnCspw3/wy8VBUg8/OEOCSNPKMYtTnN0BK+YcQYjvKaJ9yUso4W/r89EPd3wQQObJXFz6J9T1TpkSLLVskWyZrzgU8l5hnz7l/PcHTWpaQHGTLlTJ3nFl9/Rxllk3cvX6DJw8fqvtCCKSUZAsOIndoKCmYCqVhgaex9rhwtMyTSEuONdIGkZGOciGZPLro5M/l5a+URzIyEvlEv2CDlxdeOUMcaos7yz3j5+XZ1evrpJRtHH4SO7Gr5icUP2/LUFzHWJzLop902R1lomci4QN1grQtE6A/R5mG0Bfr827M856K3omud57cMvOr3SzGq1yunC3ZAdCoYtnkI3kQ++YuYtPPyvS7yEePefW3cYQULpiivOrnT+RbwGlMH/U9i6ck/MyGD7MnDx/RuHMnBo0c7jJbXE2lwBCOPTaf9uccdt6y5BTDPrYdt9jokyY4esrcaZNnIOPieTbtb4iKBp0O/5ZN8M6dGj/yCdhS3jm7nDM8MzsHvOOYi0olNnt4EUIEoMxPKga0llKaO3I28AKKl4u/rRy3Gam4zFmL4nczJV43rHL01CmbX4K09qLX7N6F/BWUB1kXF8f2P/5xs0W2kTvUehfyqr9n8TDcNeLgaioFhqj/DdsaGQ/h441PkULqfvzl1H+kgGcInydik/jp3cksAmqhrHeVlNf811AmhK9OIo49DENZMsV8gdFksaXJwR4BTCsiKLy8aPXBYHX/7OZtPAmzWAlPFkfUEmwlX+FCJvufT51EYHbF/aWUkuO79zJ3wiSmDB/Jsj/+4lFE+hZDZ5Ha2nxaeQ/SIt5GLTRxVxItjm4XlcuVc5nw1c9f2OQvLZCs+Ol9Pc5GcZn1gpRyTxJx86B4DJkjbXCjZAtScUC9CKUJNIu96Z+eP8vT82eTjGNPM0haefHzlS1NwSoVAdDFx7N39vwU5+UqAazSoB5VG9YnMEd2Pvr1J+q1aUVQSMKqQd+/PYRZP/7MihkzmTbyO16r3ZDpo8YQHeW6PhxHY03onF0L1AZQeyYiwKiBK97aYiJJY4/opVb47BE7T6td2tLnNwll2PIo4JlQ1n8zcMOs+fNVfZ6pbvI040uU4dK5UVzb2M3T82fJWtL6/FqDANry0BgE0NN+THNq9ezG9SNKJf3AgqWUadqI0MpJOXq3jkEAnflV5+3jwzezZ6DT6fDyUr7LGnVqz+yfLDtriIuJZfGUP9m2YRM9fh5DNgv9I578FWqLuDm6L3Dvhk0s+3MGJ/cfxDdTANlDC1CyYV1qv/ISPv6uHeCUkZAxMcTfuYcICMArV4jVwVu6ewktNF55bHf7a88YBkhd2WXLO1U/f2GXthqlBFs8vFxBcQxsia+llCOM4h5F8alWMUXGmI32NDv2F8rAl622engRwYGShqbO7JMSQAOufJCciZSSOf/7gGuHjwEQmDc3/WdOJSBbUqsc2YarRCU+Lo45P//KiplziHr8hPwVylKoSiUu7z/I7VMJNfochQvy+ozf8LMyUs3TRDAltbrUiKBOp+PPb8ew7I+/LB7PUbgg7T57X20tsEZaafmwhoyP59DKNcSHRygC5OeHyJIZn0KhCBtHQ9pLfHgEUYtWIJ8rIx69cuXEv00zvM1Gc+oePiZy0XLkY2UdXP82zfEtm/SKZ/aWVZCy8iol748l8dt2/DQ7B7xzUEpZw+4MHYzdUx3SEpbED5wjgOCZIvjozl2m9xlElP6Fqv1qd5q986ZD8naWoFj7YpRSql/MUkoOL1nJhnET0embhxq+2ZcG/aw5wk/A2O4nDx9yat9Bbly6RK3mTSlYskQSKR1DapozbRHAJw8fcmzXHh7ff4C3rw9SJ9m8aAkn9x1INm3VLh1o8vYbBGS1/IGUlsUvKjyCw+MnmtSuVPz9yNSpLd6h+RMfsxEpJfFXrxN//Sa6B4/wypoF3yoViLt4hZgdZr1FPj74N6qHd8H86J48RffgEbF7D6gCiY8PmV9/Ba+siXt6UlI2GbCnjHLE+23pXR5dp4Umfs4mpTU/SD+1P4CT6zezfPh3AGTOHsy7qxc4ZM6cs2tTtjSbHFq0nHVjlWZRv8yZeWflPPwyW5+nFBcTw84/Z3Fy3Sainz9XPwpAaXbt8mZ/egx5mwAXzfFMTgjtqe3Fxcay6u9ZzPn5V54ZXZc5pRrXp8XQ/+Hl5c3ZrTvYOnk6Mc+fq8ez5gqh9UfvUqpRfZN0ni58SfXdS52OyH8Xo7tnyWGVgsiahcx9eyJ8fe0+d3z4fWK27CD+ugN8dnt7E9CuJT4lipoEp0b0wHU1PgPW3l9N/FyAufhlROED5cX/uU1XtaB/e9kcAu3oTzDG3c2H5i+ULj6eaa+8wf2r1wEo07wRDfr3IUfBAngbFWJx0THcPHGKHX/8ozYDWyNPwVD+N+prqjdp5PgLsEJq+/aklIzsN5D9m/6zGsfLy4s6fXrQcMBreHknuPl8fC+MdT9M4MKO3SbxQytXoE7vHpSoV4vtJ5MeNOZoHD0XL/b0OaLXJqx76lOpPCLAHxkVRdyxhHP5NaqLX/UqNucro6KJ2b2f2KMnwIay1KdMSeLvhiEfPLQcwd+fTC+0xbtAPjUotaIHjiuj7Hn/tWZPN2IsfhlV+AxM7zOQu+cU3+N9/5pEvrL2Odd3t+glxYq//mHKV4nXNPX29cUvcyaklCY1PGOEtxd5S5cCpEkfIkCxOjWp9Uo3MgcH8SQsnCdh4cQ+jyK4QD5yFAolR8FQvHxMfUW76z4d272Xz19OaPLNHVqAyvXrInU6YmNiyF+kCFlqVyFXsSIW00spObNpK+vHTeS5WcGcOX8+CrRuTs5aNRJdr73YI2pSpyP+8lXi79wDnQ58fPDKmgUREIDU6ZQwneIgyiskB145QxAW7JNxcTyfOR/58BEAvnVq4F834aM49ugJojdvV3Z8fQno2BrdvXDiLl1BPnmK8PfDO7QA3oUK4BUcjIyMRPf0Kbrbd4k9eRZijQa2C4FPhbIIPz9iDx5JZEvtn78Hby9urd9M2J796GLjCMidk4CcIWTKk5tcdWrinyO7zffIVpxRTiX1rFur9XmS+LlrJXeXYavoQfr2+pI5e7C6/ey+Lc51FDxZ9Ay07dWTw9t3sm+jyfKPxMfGEvnI8oyb+v17U6PbC/hmyoRvgD9Sp+PoirX8N2maKpSX9uzn0p79FtMDZAoOokzThpRv3ZzQyhUQQiR66V11/1b9PUvdbtSpPUN/+gFfP9PRm0k1IwshKNuiCUVqVmPL5D85tnIdurg4AJ7fus35v2ZxddkqCrRsSu4GdfEJsG9wSHKiJ3U6iI1FxsQiI6OIv3iZ2BOnkU+fJZnOBG9vfEqXwK9eLbz0g7riw8KJ3rxdFT78/fAzG9TjU74sMfsPK67FYmOJWrzS1LYnoAu/T+yRpKY3g3fBAvg1qY93zhCklMSdv6gOXgHAywvh7Y13gD+FOrWjUKd2tl+bB2L8PNnynHtas3m6rvkl5d7MnPQsfACrvxvH0eVrAGj69gDq9H452TRpQfgMxMXGsnnRUg78t4VTBw7x6P59ZLwuIYIQ5CgUSsHKFajyQnvyly9jMZ9n9x+weeJUTqzZaFMzloGyLZvS5uMhSY6kddb9DL9zh351m6gDfyZtWE3h0iVN4tg77PzxvTCW/DqVO9t2oYuOTnTcJ2tW/IID8QsOwi8oSPkfHIRfYCBS6oiPiiY+Moqb168jY2KQMTEQE2v032g7NgZi41J+A8zx9sYrb26IikIXYfqh59+iMb4VE7/rsWfPE716Y4pO55UjO351a+JdsphJX3rcxctELV+r7ueqU5NS/fuk6BypwVPKKyP3Zh5R89PEj/QvfABHlq5izZjxgDLgoev3X1uNm5ZEzxo7bl4hLjpGGcghIVNQoF1Ndvev32TfnAVc2r0f30wBZM2Vk2y5cuLj78fDm7e4d/5Sohp0ruJF6PfPFJP+NGs44h5LKbl67jy/fPAp548ptZIKdWoxZv5sk3gpmW9lKKjinj3n9pbt3N60hViD02UXIjJnwqdMKUSmAGRsLPLJU0U0vbwQXl7g7Q2xccTfC0M+epxERgK/BrXxrV7F6mCv2LMXiD14FBkTg1dIdnyKF8U7f150jx4Tf+0m8TdvISOjEAH+iKxZ8QrMineRQngXsux0vXK5cjw6e56Hp8/ikzkT+Zo2wisFg2lSiyeUWca1Pk8Rv3Tf7JkcGUH4APKXT7D93oVLVuOlB+EDaFCgCDtvXcU3IGUuYXMULECbT96zelzqdNw4dpJDi1dwar3S3Bp28Qr3r90gZ9Hk7+HOW1cVcY6KpGXZShbjREVGcuP8RR6Eh/MoIoKH4RE8irjPw/AIHoaHc+X0WR6EmY5e7DrwjUTnsRfjgsonS2YKtm9N/pZNubdrL7c3byPyzl27asU24+uL8PMDP1+8grLhU64MPiWKImz4mACIu36TmB170N25lxDo5YVP8aL41q6Od66kR9b6li6Bb+nEU128goPwsdMxvKFcCSpdkiCzWriGZ5BhxS+jiJ6BLEad6NEW+lHSi+i5CuHlRcEqFcmWO5cqfgD75izkwc1bxMfGEZw/LxXatqBorepKLcWIs1t2sOLrMcTFxLCheWOK161NSNFChMYJTu0/yMn9B7h4/CRxsbZ5CfT28eHNEV9Qs3lTNSy1wmeSv58f+Zo0JF+ThsogmsdPiHn0iJiHj7h0+gy6p8+Qz54jnz9XamV+fgg/X2USua/+v1+CuCUc14f5+qZ6+o1PwQL49OyKLuI+usdPEH5+eOXKqZzHhThidGZ6wtP6+gxkSPHLaMIHEPk4oUnI32zibHoVPle4WDq0aLnJ/tEVa9Ttm8dPcnLdJoLy5aViu5bkLlFMafbS6Vj86Qg13qn1/3FqvfUpCkmRJTCQinVr03XgG5StUU0Nd6TwmSO8vPALDuL0rZvg641vpfJ2n8uZeIXkwMvIJ6yr8ETRSy/llzPIcOKXEYUP4NbJM+p2joKhQPoVPWOcLYC2NKs+un2HHX/OTFH+ocWLkSt/PoJyhhAUEkJwSAjBuZT/OfPno1CpknibNQs6U/gMeOqaeO7CU4TP08osT631QQYSv/Q6f89WTq5NGMlWqFqlDCF8rqBun548f/SYE6s3EB8XS/7yZanQujlB+fNycdc+jq9eb3WOISheaer06s61w8d4/uAhmYKDyFOyOAWrViS0UgUyBwcBtn+opAXhS26VlZRgz5QmR+Mu4UtvZZSryRCjPTO68D28dYfJXXuDlAgvL/7avYWc+fIlnzAd4S4P83HRMZzbtpPrR47z+M49JBKpk9w9e57cpYrT9tOhBOXNY3N+KZlYnBSuFD5niF5yOFsUXSl8aa1csvZsaaM9XUCmTAEZXvgAdv01Wx2dV61RgwwnfK7CqpDkzUumNnkx9hZq+AWOht2HsPtqeHLPn7WlpVwh7ikVPneIXlLndpQgOlv43FUWmT/H6bFMhHQufvaSHn/ku+cucGxlwkTbzm+8blf6/5Ys4+iOXTR9sTOV69d1tHkuw5l9f47s17B1rUhHrK9oj91pUfiskdzansnhLNHzFLGz9XhS9npyX58BTfz0pCfhMxSIUkqGvf+Fump3jWaNqdqogc35zPv1N2aOVSbGb160lB+XLaBUZctz0jIiznzBtx0/bdMzmVJBd7bweaLoOQJHCp+7y5zUPr+W0rv7muwh3YtfzOMn+GTOhJeP5Ut11Y9lyxd6SgqypPLdu2ETx3Yp64h5eXvTf9inNud79vARZo/7Rd3X6XSc3n8wTYufo2t/jSqWTRNfuOY4y+b0KngG3LGkkDNx1PNr6brSwruRrsUv8s5d9n/wOT5ZMlPhoyFkKaAsVOnshzClTVGOHIEZHx/P9FHfq/vte79i80KtUkqmjfwOnU5nEh4VGekw+9yF4R47SgQNz5KjX3RnPKMpsdGWWl9aEb2UNnW6avFYd2DJPkf1+Zmn8zQxTNfip4uOART/hF4nTtGoTXOnnMcTpw2c3LufW5evAMpE6J5D37E57bVzFzhz8HCi8LgY27yNpAWcUQsEz3vBDThD+NKC6LlD8MDzRS8pnGW7Id+dTsndftK1+Bnz4PoNh+XliWJnzrYVq9Ttpi++QGB229cI27V2ncXwf3+ZyK2rV6nRtDH127bBL4V+Mz0FR9cCwbTgSKkQOrrwcYYge7LwuXMwS1oWvYxGhhE/8wU6bSUtCJ058XFx7FqTIGAN2re1K/3utevV7X5ffMqcnyYQ9fw5AFuXrmDr0hXMGD2Wr/6aSrHynuHZIjU4QwTBMUKYWlJ63qRqfZ4ofKmdvpCemzY1LJOuxS9HoVDuX78JUnLv4mVinkfilzlTkmnSotiZc3zPPh7rl9vJkScP5WpWtzntjYuXuHRSKTB9/Hxp07M7pSpXZNyQDwm7dVuNF3HnLsN6vsZHE3+iWqOGDrO9UqCp5/1jjyMclndyOHM6hK3Noo4sSNN7jc8R8/U00cu4pGvx88ucmVzFihB28TIyXse5rTup0LaFejw9CJ0lblxMWLKoUr3aeJmtKGANKSXTvh6l7sfFxPL08RMq1K7Fn7u2cOnEKfb/t4VFk6cR9fw5Tx4+ZOTrAxk6/gcad+qQbP7mwmYLrhZDZ9UCDSRVG/QU4bNW6/MU4ctItTx3ODPIKKRr8QMoWrsGYRcvA/Dw0HHq9+/vZovsJyoykscR98mZP59NQpYlMJu6/dhswdWkuHj8JAe3bDMJ61+vCWWqVaVouTIUKVOKKg3qU61RA74bOJiIO3eJi41l7OChbJy3kOYvvUiWwEAalilPqTKWV0pPLa4SQ+NCxx1CmBqcIXyegrv68zxlSlRKPtg1wbRMuha/rL5+NK5Xj31zFgBwav8B4uPi8LYy58/d3Lh4iYsnT1GweDGKlitLTHQ0078dw7p/5xMXG0vJypX4ZuZ0suqdHVvjrtHgnvxFi9h8/kunExeaUkpOHzzE6YOH1LB8hQvR5pWX+W/JcnVE6eHtOzm8PWEcV4cunZkwbSo+Tr7XxmLobCF0ZiHiiMLVmf2KiWp9D/Uu2YJdt3SQq4XPU6dEpfY8mhgqeKYKOJD6bVszNSQHjyLuE3HnLluWrqB5ty4Oyz8uNpa42FgCMmdOVT5rZ89l4mdfqvuFSpbg6eMn3L97Vw07f/QYPSrVYOyS+ZStXtViPlJKDm3doe4Xr2D7Sx+SxzYHy7evXmP2TxP47OsRXLl0ibn/zMTcQfrKJUupVqMGb7z9P5vPb4mYmBiWLVjI3l27KFK8OP0GvknmLFksxnW2ELpCBFOKI4QvRc2dLhJBV05ZcJboeUo3iytaNdIC6XpVh5KVKsqfVy3h318mqt5K8hQMZcKa5SZNg/Zw5+o1Ni1cwtGdu7l48hTR+onf2XPlolj5srTt1ZPaLZtbXZVaSsmB/7ayY+Vqnj99Su2WzWn6YmcGNm7JnWvXbbIhX5HCTNmy3mIT6Jaly/nx3Q8A8PLyYuq2jeQtVNCmfONiYxncqoPaZ5glMBs/r1zCzctXiL5yg9MnTrBhzVqePX0KQLbAbGw7dJAnT56w6N+5HD96lMsXLnL54kUAfH19eW3AG9Rr1IjGzZvh62vfitoR4eH069GTwwcOqmEVKldm3KSJlK1g2wKqzuwj9JSCw1E1PkviZ1H4Ht5PHGbASSKYEvFz99qdniJ29uCKZ3p0nRYesapDhhC/Z4+f0K9eE57pVzOvXL8eA7/+giyBgTy4F8a9mzc5vnsv544dp3K9urz6/ruJmkajnj/n7zE/snrWv8THxSV3Xl79YAjVmzQyEcGH4RFM/PQL9qzfaBLf28fHJE8vb2908fGAMuJy4IgvCcyRndGDEiaqfzzxZxp1am+Sz5OHD3mrWRsehisF/gv9+zLgq2G23i5AaTJdPPVPou+GM/Ddd6hdz9SZ9YP79+nQtDnXryovyfBR35rU7qKjo2ldvyGXLlwwSVe3QQPmrlhm9aPAnLi4OF55oQt7dlqeEvv+Z5/y3icf23xd6VUEPUr4jHGgCNorfLaKnqMFLy2KnT046jnXxM8FGMQPYOvylYwdPNSmdJ0H9OONLz9T93U6Hd/0H8T+Tf8liuvl5YWXtzdxsYm9n5SpXpW2r/SgSNnS7N2wmZV/z0x2AEqbV16m90dDObB5K7GxsVRtWJ88+pXXJ30+nDWz/lXO6+1N21496fHu22TPlZPHDx4wvFc/Lhw/AUBI3jxM3ryWzFmz2nTN9ozEnPP333w6RLmX5StWZM32rSbHr1y6xKA+fTl14oRJ+Okb18hioz1z/5nJx+8OAUAIQbWaNTh66DBxRh8JnV/qRofOnanfuJHN+YLzhNCVIujo/j2bxM9W4TMmlSJoj/C5Q/TSu+DZg6Xn39L96VCopCZ+zqZS1apy1ZbN6v74Md8zfsz3SaRQ8PX3Y/yKxRQpo7x4/y1ZxrghH6rHy9eqQfs+vahYtzbBOUPQ6XTcuXqNNbPnsvqf2cRERyd7jqZdXsDL24vNi5aq/WUFSxTnu7kzyZ47l8U0D8MjGNqhi8l8O/+AAOq3b8uF4ye4du68Gv7FH5Op06qFpWxU7J16oNPpiIuLIyoyiuqlyxAdFQXAuh3bEzVDxsfHM/qrEUydOEkN69GnNz9M+AVb6NS8BUf0g2ze+fADPvpiGGdPneKz9z/gwJ69JnFz5c7NzEULKVexgl3XkxZF0BmDWhxe67NECkTQ0cLnCNHTxC71aOLnAszFD+C/DRuY+89Mtm/Zgp+fP3ny5iV33jyUKlOGaZN+U+P5+vrSpmMHanTpyKTPvuTejZsAtH+tF4NGDrfafBdx5y4LfpvC2jlzLfrCzB9agEFjvlEnht+8fIUzBw6RNTiIao0b4uvnl+Q1Rdy5y7j3PlRXazBHCMHgMd/Sumf3xPcjBfPsDJw8dpwBr/YiIiKCdp06sWjuXPWYedOngaioKErlzW8S9u+ypdRv3CjZ89UsW567txWR/2r0d/QbNBAhBFFRUQx5cyBrlq8wiV+tZg2WblhvKatkSSsi6KzRnObi53DhM2CHANoqfK6o7WmC51g08XMBlsQvKQ4fOEC3tu2JtdCECRAUHMzUHZvJEpgtWSG5deMGi+cvYM+OHZw7c4YSpUrR87U+tG7fHr9kBC45pJRsXr+B4R99zPVr19Rwb29vfp7yOy9065qq/M25fPEifbv3UAeymPPWe0P4bMRXFo9duXyZRlVNPcy8Ofhtvvj2myTPOeDV3qxbleCftFCRInTt8TJ93xxAcPbs7Nu1m9kzZrB0wUI1zusD36RL95eoUt12jzYGMrIAOr3mlwZFTxM856GJnwuwV/wADu7bx6jhXyVqWgP44puRvPnOYEeZl2rCw8KY/PMvREZGkjdfPlp3aE/pso7rz3j08BETxo5lxtRpVj8IAH6Y8As9+vS2evzXH8cx7rvRJkskrdyymUpVqlhNc+3KVXp2esFE3EEZYTp7yWKqVK9OeFgYNUqXNclXCMFf8+bSrFVLG64wMc4QwbQggOBAEXSC2IFzBc8TxC41LTPWcKV7QFvRxM8FpET8DJw+cZI5f//NulWrePTwEQPfGcx7n3xss6uwtM6RgwcZ0KuP2vRooPNL3ahYuTJZA7MRFxtH9pActH/hhWRHcR49dIiOzRL6IKfNmknrDu2TSAF3bt1i9IiRbFizmqdPnqrhHbp0Zvh3o8idJw+TfhrP2G9HmaRr1qolM+bPs/VSE5GRa4GQgsEvThI7cN50BXeKnTNELjk8SQQ18XMBqRG/jMzZ06fp3LK1Op8PoEad2nz13SgqV6tmV163btzg919+Zd7s2UTqV4YAKBAaSvYcOWjepjVdur9EsRLWF9qNjo5mybz56uhPA63ataN3/9fp3fUlk/BmrVsxY95cUkNaEUADbm0OTQJnip0BW0XPlYLnDoFLDk8RQE38XIAmfvaj0+lo06ARZ/QFX3D27Hw7biwdu3SxeY6egcsXL9KpeUsePXyYZDwfHx9+nvo7nV58kcePHjPuu+9YumAhPj4+VKxahfc/+5SKlSvTsl59zp0+Y5J24DuDmfLrRHW/eMmS/PrHNCpUrmSXrdZIC82g1nDWHEBrAujsiejmuEv0PFHYbMUTBFATPxegiZ/9nD19mpZ16wOKKK3euoUyKVyzb9x3o/nlh7E2xc0REsKOI4fo9WJXDu0/YHIsU+bM/P73X2QLDOTF1kmvTbhi80a7a6fJkZYF0BLOWNXdVlzlXNpRgpeWhc4a7hZATfxcgCZ+9rNr23Z6dHoBUJo6F69dk+K8Thw9xkvtO5g0n2bKnJlmrVrSvvML6HQ6Bvd7Qz1WoVIlThw7ZjEvHx8fRv30I63ataNqiVJWz1mqbBlWbfkPf3/HrjKf1ppB7cVWQbRVBN21gkJqRC89Cl1SuEsENfFzAZr42c/Ordvo+UJnACpXq8aKzRuTTpAM169e4+fvvycuLp5W7dvSrGVLMhk5Af/t518YM+LrROm69exJ34EDGNT7NW5cT/B56h8QoE6uNyZT5sxqn+KocT/Su3+/VNltCWuFxdOHj1jw2xT2b/qPqMhIylSrwoCvviB7rpw25espAmjAFiE0FkF3LxWUUsHLaGJnCXcIoCZ+LkATP9u5euUKG1atZvrvU1SxqdugAfNWLnfqeZ8+eUKreg1MBM7Pz48dRw+TN18+7ty+TZ+uL6l9kOYEBgbyy7SpnDtzhtFfjQCgVt26LFyzymJ8R2BeYHzQ+SXOHjpiEtaqx0u8+8N3NufpaQJowFH9hp7gOFoTO8u4QgCN732h4BweIX7pfkkjDctER0ezce1aDuzZy86t2yyKyyt9X3O6HVmzZWPuiuWM+vJL9u7aTYGCBRny8UfkzZcPgLz58rFg9Sp+/fFHVi1dxs0bN/APCKBKtWrUqV+PXv37kSdvXkqULqWKn7XJ+I6iUmCIWmDcu3krkfABHPhvW6KwpPDU5ZLMRcsWMfQkh9Ga4CWP8fPsjLw9Fa3mlwG5d/cur3TukmjkpIFMmTPz/mef8ObgwXaP8HQmUkrC7t0jOHv2RF5y4uPjKZU3vzoZ3x4n2inlYPhtFkyawpzxExIdC84ZwqxDll3Q2YqnCaEzcMb0A08rcEN4TASB7jbDJlIjgrbed63ml04J4XGycdz1Ikgp2bRuPV998qm6JJEBf39/6jdpTKt2bWndvj0hOW3rr3IGxvfQ+F4JIchtZcFdb29vQgsVUmt9Vy9fsdvRtT3ExcUxtt9b7NpmuYb3MDyC7wa+Tbbg7HR8vbfqJN0e0suio66YX+dowbPlPXZVfq4sL2ypBXrax0VK0cQvGRz9Ehjn6cqH+vmzZ7zzxptsWJMwetPb25t+gwZSp0ED6jVs4PSakiWSu7/mx5O6ZyVKlVLFb8qvE/nh118cPurTwL9//2NV+AzsWqM42t68eAk/LJxLycoVU3w+T20WNcbVXlMcUQg74/12NK4uL9KLuCVHhhI/T3vQXflQj/n6GxPhCwwMZOzEX2nbqaPTz23AEfffWq0Q4MUe3dVrXDJ/Pls3baJrj5fp0ac3JUvbX/NKivWrVycKa/9aLx7ff8D2FaaDbWKjY5g7YRJf/vl7qs+bmtqgJ/ivNMeVBa2nvf/2ktSzr2E/6brPr1rVSnLHlhXJR/QQnPVAP3/2jKolS6tTAbr17Mmwb752atOmOwqaMF1W3uzVx6Iw1W3QgC++/YaKVSo75FyTf5mgDrAx0HfAALp9+TGXTp7iwomT3L97j1k//gyAn78/sw7vsXlx4fSCu2sRaV3wkiMtiqDW56eRCGfVBNevXqMKX8kypRn320SnDGRxd0GTy+spc/8az5iJ1Zj111/c0q/BCLB7xw66tGrN7CWLqV2/XqrPFVqoYKKw3PnyUikwhEp1G3JM7xVn69IVXL9wkZjoaP78ZgzvfP9tqs/tibhb5Ixx93PoStzRhZJeyBhLFKQxQnjs0Bd48byEFQ4aN2vmcOFztL2pwd/fn8EfvM/Oo0f4Z+F82nbqiI+P8o0XExPDx+8OwRGtHSePHU8UdvnCBXXbIAbdB7+lhq37dx6n9h9M9bk9hUqBIeqfJ+BJz6GG55Os+AkhugkhFgkhrgohIoUQZ4UQo4UQ2SzErSOEWCuEeCiEeCaEOC6E6GEWp4kQ4owQ4rEQYooQws/oWBEhhNT/NbOQ/w4hxJYUXmuaw1EvcozRivJbNm40Wf8upRgKGk8tbLy9vWnSogVT/vmbNdu3EpApE6DMAfxkyHtcuXw5VfnXrFMnUdiiufN48jjhflQKDOHd116nbPUEX6NnjxxN1XndhbHQeZLggSZ6kLFqu47Clprfh0A88DnQBpgMvAVsEEKo6YUQ7YFtwB3gFeAFYBoQYBQnCzBfH94FqAqYrlOTwCgr4RmKpF5sYwFK6u+N3gkru184d54bx3anSLw8XfCsUbpsWTobrW4/95+ZNK5Wg+9HfpPiWmDz1q344puRJmG58+ZJNGJWCEHpYsXU/UxZsqTofK7GU4XOQFp9FjU8B1v6/DpKKcOM9rcKIe4DfwNNgM36WuBfwG9SyveM4po7hiwLXJdSjgMQQnwDvAmYu/5fD7QSQnSUUqadEStOJDUvuZeXaTNnJn0tyBF5pxU++3oEp06c5Njhw4Ay53HST+MRQvDRF8MQQhAfH8+eHTuJiAincbPmBAUHWc1v5dKliRbR/WT4cIuLHQcGJeSzc/VaWr7cDW9vbwddWerRRlymD9LSZHpPIFnxMxM+A/v1/wvo/78E5ALGJZPdNaCEEKIJcBzoBZyzEG8hkBP4VgixUqbnIalO5s+/ZvPu0GHqfvlyZShdqrgbLXIP2XPkYNnG9WzZuInJP//Cvt27AZg47id2b99O+86dWbdyFXt37QKU1SEmz/iLRw8fcj/iPg/v3yc4Rw4aNWuK1On4aPC7REdHA5Ala1a+/2U8nbp2tXjudp068c8ffwJweNsOZoweS7OunclftAj+AQEW0zgLd9Ti0prgxT1I3J9rwCd7yudqanjWs5CiqQ5CiEEozZ81pZQHhBDTUZo5ewPfo9TwbgN/AN9KKeON0r4D/IQivAeANlLKCP2xIsBlYABwE1gN9JRSztUf3wHESSmb2GJnWpvq4GjuhYVTuXpTHj9+AkCRwgWZ/+8flC/n2DlvnkZyX78xMTEMeLUX/22wf8WK8hUrMmDw27w3cBAA+QrkZ87SJRQvWTLJdKOGf8WUCb+ahOXIk4fvF8wmX5H05eLLkwo4SyQlbrbiySLoqbU/w3ORJbiIR0x1sFv8hBAFgMPAUSllS33YWqAxEA18AxwEWgCfAr9KKYea5ZEdCAEuSSl1RuFF0IuflPIPIcR2IA9QTkoZZ4v4CSHeRGlKpWDBAtXPHN9p1/WlJ4Z++CVT/5gJQKmSxdi6aRmBgYnGKaU7bHn5o6Oj+Wn0GKZNnERcXFyKz9W7fz9Gjfsx2Xg6nY7eXbux/b8tJuFFypTmlzXLUtQM6kl9cZ4seI4QO2t4ogh6mviZPxueIn52zfMTQmQFlgFxwOtGh7xQBrYMk1L+pA/bIoQIAd4WQoyQUj4yRJZSPgAe2HDKz1EG0fRFqUUmi5RyKjAVlJqfLWnSI9HR0cybv1TdHz3qywwhfLbi7+/PZyO+4rU3+rNgzr8cP3KUoOAgXntzANs2beb3Cb8SFRlJTEwMzVq34tmTp2qTqDE5cuSw6XxeXl58N/4nmlSvSXy82hDClTNnKeEdwGUSRuR6kqhZw5PFDpwreJbO44ki6G48/RmxWfyEEAHAcqAY0FhKecPosMET6gazZOuBQUB5IHHJkQxSyu36WuVwIcRMe9NnZP7buotHRs2drVs2ca9BHkr+0FCGfPyRSVilKlUY/MH7JmFSSvp2fzlRU2mj5olm5FilcJEiZM+Rg/Aw0270bIGBVLLTblfi6YUYuE7skju/J4igJwx8SQvPjE2T3IUQvsAioBbQTkpp/qSd1P83r2kZhhmmZmLZMCAURUQ1bGThooS+zhc6tfWopYnSIkIIfpk2lRZt2gCQOUsWhn83yuJ8P2tIKS1Ordi/J3VLHzkSS1NlPJW4B8fVP0/B0+xxNZ7+zBiTbM1PP5dvNtAcaC+ltPSmLkXp62sDnDAKbw1EmYXZhZTykBBiEUoT6C3gUTJJMjxr1m7i33mL1f0uL7R1ozXph+DgYKbPnUNUZCTePj74+vralV4IwZ//zmZgn77cvX1bDb947rxdIuooPLmQSusC4u6aoDtqf578PFnClmbPSShTGUYBz4QQxm/pDSnlDSnlCSHEDGCkXiwPoQx4eQP4Rkr5NJV2fokioLmBranMK92zaEnCqgIFCuSjejXHOHPWUAgwmydpD9Vq1mTp+nXUrZjQ0FkyBWv9pQRPKJzSuqjZi7tF0BV4wnOVEmwRP0O1YZj+z5ivgRH67YEo0xPeQRmheQV4X0r5S2qNlFKe0ff59U1tXhmBbNkSvIh0e7GjxYnXGu5j5Oefq9slSpWkSvXqTjmPuwuljCZ0SRH34LjLBdAVtT93P2OpwZZJ7kVsyUhKGQN8of9LEVLKKyT0E5ofex3TEaYaVjCex3fz6hm3vHgallm/eg1rVqxU90ePH+8wby/uLIg0octYpGXRM6AtaZSOMBRAFYsmNMut3rCX6OhYyADNLwZseTHdMRru2dOnDP/4Y3X/5V6vpnp5JU3w0g7uqv2BY5/39CB8oIlfusG4IKpWOcHbyPPIaI6cuEDt6mXVeBlBAJMjqRfYWcK4btVqdY3BHCEhfD7y6xTnpYmehj04YhX49CJ6BjTxS+NYKoiEEFSrVJJDx84D8L+PfmH32l/x8/NFSsmJfavYfjiMPfsOEpIjO/1ffzXduzyzB2ctEHrm1Cl1++Xevchu4wR5YzTRS9t4wsdnSoQwvQkfaOKXpkmqMPr28368+NpXREXHcOHyTf5dvJmsWTMz9te5nD53zSTulGn/0OWFdkye+APZsmW1kmPGw9EiGBeb4MXFz88viZjWbXEHmuilX2wRwvQofKCJX5rElsKofu0KvDeoK2N++ReAdz+bmGT8JctWE3H/AYvn/0WmTK5dacDTcZQIlquY8MVvaSX4pM7tDjTRcw6eUPuzhLkQplfRM6CNgU9D2Os9os/LrciWNfGctCyZA+jYpi5jhg+gQ+u6avi27bvp1fd/xMTEOMTe9EZqvVdUqlpF3T525IhTz5UaMrqXEo30W9szJkVLGqUV0suSRqkpiPYePM0bQ37k5p1wQvPnokeXprzZpwM5QxIWWB3/+0JGfP+3ut+1S3v++mOCRy246mmkpBYYHx9P+UJFeP7sGQD7Tp0gb/78JnG0ml7GwRNrf64gTa7qoOF6Ulsg1a5eluM7/kRKadW/59BB3Xj6NJIfJ80HFA8x0dEx/DzuW/Lly5Oq86dXUtIU6u3tTcXKldXVIS4f3kX5/K2cYp89aKKnkRHRmj09FEc3PSXn2PqLD3ox8LUO6v7K1RuoWqs5kyZPT9V6d+md5JonzZ1E165WXj22bMVaV5hoEU90Cp3R0O69e9GaPT0Md74QOp2OT76extR/VpqEV6pYjgnjR1GzRtUk01uyPaM27Vhj/4HDNGnRBQBfX19OH9vh0tq1VuB6Fhnx/fCUZk+t5ucheMJXuJeXF2O/HsiKOaMoVTxUDT92/BQt2nRj8b9TTGoM5n+WcPc1eRo1a1Slbh3lvY+NjeX3aX8nkyL1aLU8z0X7TdyHJn5uxhMLpUZ1K7Fz9QSGf9SHTAHKfLS4uHhef+cHNm49aHd+nniN7uSd/72hbs+dv9TiGn+OQLvvGhrW0cTPTXh6weTn58sH/3uJPesnUaJoAUARwBE//JPiPD35el1J+3YtVGcCN27c4tLlqw7LW6vlpT2038o9aOLnYtJawVSkYF4W/T1C3b905Vaq8ktr1+8MfHx8aFCvtrq/c9e+VOep3VcNDfvQpjq4gLReKBUOzYO3txfx8TqePY8iOjoWf3/7VjE3x1O9XLiKbIEJbuRS2uqZ1p8rDYWM/B64E038nEx6KKCEEGQPzkZ4xCMATp+/SpUKJVKdb0YWwCtXEvyrFitayO706eG5yohk1OfdE9GaPZ1IeiqgQvPnUrebd/mQj76awo1bYanONz3dI3u4fOW6ul20iH3il1HvWVrDJ3vFRH8anoMmfho28dHg7nh5KY9LXFw8U/9ZSbPOH3D7bkSq885ohfnTp88ICwsHlNUd7Jnnl9HuladjSeA0oUsbaOKnYRMdWtVl0YwRVCxbVA27G/aAAUN/4sGjp6nOPyMV6vfvP1C3c+UKsdmHaka6R+4mKVHTBC59oPX5OYn0WFA1a1iVpg2qMOnPZQwb9ScA23cfo2G7d1kzfwwFC+S2KR+dTseeA6cpkD8nhUMTaj0ZpQ8wxmhdvwB/fzdaknHICM+Vhn1o4qdhF0II3u7/Atdu3GXK34obtOu3wni5/ze8M6ALWbIEkCnAj/JlipI/b0ii9PcfPmHosEksXb0TgFrVyvDJuz1o0bg6kDEEMCbGeFFb20bNpsePKWeS3p8hjdSj+fZ0AhmloPp30WYGfTje4jEvLy86t6vP8I/6ULRQXp4+i2TI5xNZuHybxfgTv3+X3t1bqvvpufA6cvQE9RsrTsQrVSzH7u2rk4yfUZ6n1JCen5f0hqf49tRqfhoppmfXZpy9eJ3xkxcmOqbT6Vi8cjur1u+hd/eWHDp2nkPHzlvNa/AnE3j85Blv9+8MOK7A98RCMTzivrodEJB0s6cmfJbxxN9VI22hiZ+DyWiF1Vcf9aFJ/Sr8t+MwN26FERUVw8074Rw+dgGA6JhY/phlWrPx9fUhb67s9OzajDWb9nP81CUAho2aTt2a5alWqaTD7DP8Hp5UWG7YuFXdrlrFul0Z7VlKCk/6/TTSB5r4aaQKIQRN6lemSf3KJuH7D5/hoxFTVBE08MUHvfho8Mvq/luvd6LjK8M4ceYKUkqWr93lUPEzYCwk7i5I167brG63bdPcjZZ4Hu7+bTQyDpr4ORDtSz2BmlXLsHnJONZtPsDOfSeIioqhXcvaNGtouiZgjuyBNK5fmRNnrgDw5Mlzp9vmTiG8cPEyFy5eBiBz5kw0rF/bYrz0/ixpIqfhbjTx03AaXl5etG1Ri7YtalmNExkVzfylCc2A1auUcoVpKq4WQuNaX7MmDQgICEjSpvSEJnganoQmfhpuZf1/BwiLeKjud+3QyG22uKJ/8PCRE+p2s6YNrdqQXtAEL+VEEKhuh/DYjZakTzTxcxDprdByFX6+pvPcNm8/nGRN0RU4szZ44eIldbtMaVPn4OnhGdLELnUYC555uCaAjkVzb6bhVlo3q0Ht6mXV/ZUb9rjRmsQ4enHYO3cTnIGHhuY3OU9aRHP3lXoiCFT/koun4Ti0mp+GW/Hy8mLImy/yysBRAMyav4HypQvTu3tLsmbJhBDCzRYm4AjvMyE5snPjhrIg8IMHD9V8U4ImNq7BkuikthaWUiEzpNNqgalHq/k5CK0gSjltW9SiZZPq6v5n3/xBaMWXqd3qbQ4cPutGyxKT2hpagfz51O3zFy6nOB/teXMOxrWwpGpjluLZWntzRA3OUflkZLSanwPxyV4xzTZfuRMvLy9mTPyE9j0/58jxhHmBZy9cp/mLH9KySXX8/Xx5+iyKuLg4OrdrwIA+7d1mb2pqgNWqVmT12o0A7Ni5lx7dO7P/8BnOX7pJZFQMPt5eNG9UzWT9RGM00XMczhIPV4qSVhNMOZpvTwejiV/KefDoKV+NmcGmbQe5cSs8ybizp3xOh1Z1XWSZZVIiRDt27qV1+4RJ/jlDcpi4OwPFcUCzhlXp3b0l7VrUxt/fVxM9B5ARakppQQQ9xbenJn5OQBPA1HP+4g26vzGSS1duWzz+StdmTP5xqIutSoy9ohQXF0e1Wi24eOmKTfFDcmTn5e6d6dOrOxUrlE0+gYYJGUHwzPF0AfQU8dP6/JyA9pWeekoWD2X/hslsWvwj03/9mPq1ypscz5HdMwo1ez90fHx8+Pmnb/HySnj1goMC6dK+AX17tqaxmZu4iPsP+O33v6jToC0Nm3Zi2p8zefjwkUNsT6/Y2v+WXsnI124PWs3PSWi1P8cQExNLjwHfsmnbITUsMFtmdqyeYLIQrrux94PnwsXL7N13iOzBQTRrqnh6MfQlXr16nVlzFjJz9kKu37iZKG1AgD8vdGrLa72607BBHRMhzchoBb513FkbNP9dCgXn8IianyZ+TkQTwNTz67QlfPHddHW/fOkiTPnpfSqWK+pGqyzj6Bq/Tqfjv607+WfWfFasXEd0dEyiOEUKF6T3qy/Rtk1zypUtha+vbYvjphc0wUs5zhBEW34PTfxcgLvFD9KfAEZHx3Lxyi2uXLtDntzZqVy+OD4+3iZx7ty7z7Ub9/D19SEwa2YKF8yTKI4x8fHxrNqwl6fPImndtAYhOYLUYy/1+5r1/x0AoHO7+kwb/4HNq5+7A2c1ed9/8JD5C5bxz6z5HD120mIcf38/KlYoS9UqFalapRJVq1SgbJmS6UoQdTod98LCeUA2/P0D8A/w58LZc8z66y+uXLpM9Vo16fvmAHLlzu1uU9MctoihIz42NPFzAZr4OZbZCzfywZeTiYxKqIHkCgmma8eGtGtZm5pVSzPml7lMmLoY4+fK38+XyhWK06lNPbq0b2AyjD8+Pp6ufUfw344jatymDarQsU09dDod73z6qxr351Fv8/orbZx/oQ7Amf2+R46eYOasBcxbsJQHyfT/BQT4U7FCWapVrUTdOjVo37YlmTNncpptjkBKSVh4BBcvXuHIhdtcvnSJSxcucOXiJa5cvkzk86RX/vAPCKBH71707NOHshXKu9VRgk6nIzwsjFs3bvDo4UPyFShAocKFCciUietXr7Fl40ZOHDuGj48P2QIDKV+pIjVq1SJfgQJus9nZaOLnAjxB/CB9COC9sAdUafImz55HpTqv2tXLUrViCXLnys7h4+dZsXa3TemW/DMy0ZJIno4zRTAqKoqVqzewdNkaDh0+xtVrN5JNExiYje7dOvFa75epWqWiiTDEx8dz7vwljhw9wZGjJzh56ixCCHLmzEHOkBzkyhlCYGA2Tpw8w569B7h7N4zQ0Px0eaEdPbp3pmDBAhw9dpLR3//C/QcPqVmjKkPeGUCe3JbnLBq4Fe3P3l27WLtiJccOH+HyxQs8efwk1fcHIFeePDRq2pTGzZvRsGkTQnLmTDZN2L17HD9ylJCcIVSqWtWqeOp0OmZMncb6Vat5/vwZOXLmJCQkhPh4Hbdu3ODWzZvcuXWLmJjEzdXZArMleY1Va1Tnldde46VXX0l3fbqa+LkATxE/SPsCuHDFNvq/O1bdb1inIucu3uBu2AOL8Qvky0lIjkDCwh9y++59i3Hs5cHFZWm2IHDFCODwiPscOXqCw4ePc/jIcQ4dPm5xwIyBCuXLULFCOby9vTh/4RLHT5zm+fPIFJ8/a9YsPH8eiU6nU8OCgwL58IO3qValIrFxcZy6Fs6Na9e5ef06169d48a169y9bXk6izUCg4Lw9/cnKiqSqMgoMmfJQv3GjahRuzbLFi7i6KFDFtMJIahQuTKNmzejcbNmVKtVU20SllJy/eo1lsyfz68/jlMFq2HTJkyf+y/+/v4AxMTE8MWHH3H04CFOn7Tc/OxIevTpzQ8TfnH6eVyJJn4uQBM/x7Fo5Xb6vfMDAB3b1GXW5M+Jj49n2+7jLF+7i+27j3H+0k0yZ/Kn3ytt+frTvmo/X3jEI9Zs2sfildvZuuso8fG6RPnnCglm7/qJPHrynJXrdrNi3W72HTqjHm9QuwIr//3Oo3x9pgRXT4MJC4/g8JHj7N9/mHkLltk8v9DdZMmalaLFilG0RHH9/xIULV6MosWLkz1HDqvppJTs2LqVeTNnsf2/LTy4b/3DK3OWLIQWKkjOXLm5cukit6x8KHR8sQuD33+frNmyMfmXX5g1/S+7riUoOJgCoaEEBQdz88YNbly7hk6nw9/fn7oNG9CgcWP8AwK4e+cOh/YfYP/u3cTGxqrpCxctSvFSJcmVKxcdunSmcfPmdp3f09DEzwV4kvhB2hbAdZv3073/SABaNqnOwr9GJIpz/8FjsmXNjK+vda954RGP2LLrKLfvRHAv/CH3wh4QFJiFAb3bU7J4qEncu2EPuHr9LlJKqlUqmWS+aQ13zAWVUrJz1z7+njmPJctWExmZuAk7X748VKlUgSqVy1O5Unn8/P0ID79PePh9wsLDefDgEYUKFqBe3ZqUKFGMrdt2KYNwjp7g4SNlwEThokXp0ac3c/6awfVr15K1y8vLi4KFC9O8dSuat2lNqTJlyJ0nT6o/dOLj4zlx9ChbN21m6+bNHNq3n/j4+FTlaYnCRYsy9tcJPH70iIiIcASC/KEFyB8aSv4CBcicJYtJ/JiYGO7evkPOXDnJlDlzovwe3L/Px+8MYd2qVRbPN+qncfTu97rDr8NVaOLnAjTxcxw79hynfc/PAahXszxr5o9xs0XpA3c5RHj06DHbtu/m0eMnxMTEkD9/PqpULk/ePCkbJSml5F5YODeeCgoVKYKXlxeRz5+zaN58dm/fzu1bt/D28ia0UCFCCxWkYKFC+u1C5CuQ3yUjUh8/esyubdvYunkz2zZtTiTMgYGBlKtYkWatW9L3zTd5/63/sXLJUqv59ejTm8DAQN56b4hNfYn28OzpU4a8OYj1q1cnOubt7c3X34+hd/9+abIlRBM/F6CJn+NYvnYXvd8aDUCrpjVYMP0rN1uUvkgPXoHS0pw7KSX3IyK4c+s2YffuEpw9OxUqV8bHx8ckzsJ/57Jq2TKuXLxEZORzsmfPQcUqlRny8ceEFirodDsjwsPZ/t8WLl24wJL5C7h6OWElkDLlytG4RXOKlShOaKFCFC5SlEJFCjvdptTiKeKXftqR0gBpedWHq9fvqtue5FklveCItQI1bEcIQUjOnPoam+X7LoTgpVd68tIrPV1rnBEhOXPS+aVuAPTq9zp9X3qZE8eOAXDm1CnOnDplEr9ugwZM/vsvcoSEuNzWtEayQ+eEEN2EEIuEEFeFEJFCiLNCiNFCiGxGcYoIIaSVv2Cz/JoIIc4IIR4LIaYIIfys5NPMgi07hBBbUnfJGinBRPwKauKnYUpaqvWlVXLnycPidWsY+O47BGSyPFdz944d/K9vP+7dvWvxuEYCtowb/xCIBz4H2gCTgbeADUII8/Sjgbpmf+pkFiFEFmA+MA3oAlQFhlg57yibr0LD6Zw8c0XdLhSqec9wBmm1VSC9C9+xxxEcexzhbjMACMiUiWEjv+bAmdNMmzWTIR99yIsvv0zVGgmLQe/avp065Ssy5M2BXLty1Y3Weja2NHt2lFKGGe1vFULcB/4GmgCbjY5dklLuSSKvssB1KeU4ACHEN8CbwFizeOuBVkKIjlJKz+m0y6Ccu3idXfuVOU1eXl7UrFrGzRZpaNhPagXMkL5SoPubFAODAmndoT2tOyQs6jx+zPeMH/M9oCydtWT+AlYvW870ef/SsEkTN1nquSRb8zMTPgP79f/t9cFzDSihb/oMAXoB5yzEWwgcAr4VaXE4Uzri4eOn6kAXgFZNqpM/r/tf/vRKWqv9eXKtz1Bjc3TNzVNqgea898nHTJz+B7XqJizyHB0dzfCPPiE9D2xMKSl1l9FY//+0WfhoIUScEOKREGK5EMKkJ1lKeQ/4AtgAhAPFgO8s5C/18SoBL1s4nmZJa4Maho+ewZnz1wHw8/Ph43d6uNkiDQ3rOEPsrJ3H0xBC0OnFF1m4ZhVjfhmvhl88f552jZpw/MhRN1rnedgtfkKIAsBIYKOU8oA+OBqYAgwEmqL0E1YEdgkhTJafllL+CuQGSgK1pZQWnyIp5RpgBzBSCGHzqFQhxJtCiANCiAPhEY5xq5WR2bor4YX55bvBVK9Syo3WZAzSSu3PU2p9rhI8a+f1RF7u1YtceRIGpp08fpz2TZoyf9Zsp0z0T4vYJX5CiKzAMiAOUF0MSClvSykHSSkXSym3SymnAY1QanDDzPORUj6QUl6QUib2c2XK5ygi2ddWG6WUU6WUNaSUNXKGWHeDlBF59PgZC5Zt4fsJ//LXnLWEhT9MMv7VG3e5fvOeut+pTT0nW6hhwNMF0N3C5y7Bs2aLp+Ht7c2MeXMpUqyYSfiHg9+hXaMm7jHKw7BZ/IQQAcBylKbK1lLKJF3ISymvo9TcaqbUOCnldmAtMFwI4Z/SfDwNVzd93n/wmJFj/6Fcvdd5471xfDd+Du8Nm0T15oNYsc7yigrx8fF88OVk1Q9nvZrlyZrFs5fC0Uj/eIrgmeOJNlWsUplthw6wYPUq1TE3wOmTJ+nWtn2yS0Old2wSPyGEL7AIqAW0k1La+lkqUGp/qWEYEAoMSmU+GQ4pJeN/X0jFhm8w7rcFPH1m6rH/0eNnvP7OD+w9aN51C8PHzGDDloPq/rD3X3W6vRqmeHrtz5V4qugZ46k21q5Xl/W7dpiE7du9my8/+thNFnkGtkxy9wJmA82BF5KZymCcrhBQH9ibGgOllIdQhPdzIEsy0TWMOHT0PCO+/9tE9EoVD+WNXu3UEZuxsXF8MPx3k9FgcxZtYuIfS9X99wZ1pUGdtDVQR8N5uLrJ0xMFJSlcYe/eXbsZ8uYg2jZszHsD32Ll0qU8f/bMavyixYuzYNVK6jZooIYt/Hcud27dcrqtnootNb9JwEvAj8AzIUQdo79QACHEOCHEeCFEdyFEUyHEIGA7oMPyaE57+RIIAao4IC+PwBVNn75+puOEBvRuz971kxj3zVusXfA9mQIU5zrHT11i+JgZ3At7wO27EXzy9VQ1TYdWdfjqoz5Ot1XDMhm59uepNSlbcKbdP40ew0vt2rNk/nxOHj/O4nnz+F/fftSrVIW/p/1hshySMbXr12PeyuXqhHidTseh/Qcsxs0I2CJ+bfX/hwG7zf7e0B87CTRAGfG5ARgB7EQZzXk2tUZKKc8AM1ObDyiFSVJ/6YlK5YrR88UEL3FPn0Wqi8EWDs1D/doV1GMTpi6mZK0+lKnTl8dPlL6AEkULMOWn99PsArIajscVtb60LHrGOOMaYmNjmf77FIvH7kdE8OVHH9Oybn3Wr1qdaG7fs6dPWb96DadOJCzCq0t2zGH6JcOs6pBaYXNGTc0VYnvo2HmavvA+AJkz+XP58BwC/JUa34Spi/lytPWFOZfP/pbG9So73UaN5PGU+aGuEr/0hCM9wjy4f5/KxUqo+3/+O4djhw+zcM6/3LxhOgaxSYvmfP39GLZs3MSGNWvYs2MncXFx6vHAoCB2HD1McHCww+yzBU9Z1SHdi9+WJY5odU0eewsnV9UydTod2Yu/oO7vWDWBiuWKKjbExbN6414OHTvP3gOnOXD0LDExcfj4ePPFB70YOqibS2zUsA1NANMWznCDJqWkdvkK3Ll1G4C/5s2leetWREVFMWPqVCb++BOPHz9ONh8hBL/+OY1OL77ocBuTQxM/F1C1Ukm5dfn45COmU6SUDP5kArMWbFTDDm76nRLFLHuli4qO4ebtcHLnDCZb1sQrTGu4H08RQNBE0BKu8Ps56svhTPl1IgDNW7fmr3n/qsfuR0TQsVkLrl+17NC6TLly1KpXlxe6daVmnTqEkLxQGuOI31wTPxeQkcXv4uVb1Gz5ljpPD2Dgax34YcRAN1ql4Qg8SQBBE0FXO7q+dOECTWrUAiBbYDZOXjMVuqdPnvDZ0PdZtXQZXl5eNGlcj/ZtW9C2dXMKFMjncHvs/f018XMBGVn82nb/VF2JAaBL+wb8+cuHeHt7u9EqDUeREQUQPEsE3bW6g5SSwtkTzn3lfjheXl6JanGxsbEIIUxWp3cVST0PniJ+2kru6ZDDxy+YCF/B/LkYO2KgJnzpCEOfsaeIoKHgdbYImguOq8XQE5YzMl6oNmvWLOTyemoxnq+vr6tMSkQIj93uAi85NPFLZ4z44W/GT16o7nt5ebF/02QyBaQb73AaRsQ9OO4xAgiuE0EDlsTIEYLoCSJnwLxG9+/ihD6+yhXLu9ocm3H1s2AvmvilI+Li4k08swAM/6i3JnzpHEsjh90tiO788rdVED1J4IxJahCKlJIZM+ep+z17dHGFSanCU2uBmvilI+7cu09sbMI8nqk/vU/3zk3cZ5CG27A2lcaVouhJX/6eKnSQtNiZc+DgEU6fVtb/zpIlM91e7OgssxyKJz0LBjTxS0fsOXBK3a5SsQQvd2nqRms0PBFzUXSFGHrql787sHdqgTkz/kmo9XXt0oFs2bKm1iSXktrrdySa+KUToqNjGfH93+p+pXLFkoitoaHgqoEznvjl7yocVeA/efKUBYuWq/t9+7zskHwzKprTxnTC4pXbuX4rDIDswdn4dEhPN1ukkZZwlcehEB571Ne/szBcpyOvdfGSVTx7pvjdLVO6BLVqVnNY3hkRreaXTti2+6i63eulFhTIl9ON1mikRVw5fSK91gSdKewzZs5Vt1/r3QMhhF3pU/OB4+4BVM5AE790wunz19TtX6ctIcDfj2Hvv2r3C6Kh4crpE+lBBF1Rk71w8TL79h8GlPl71kZ5OqsG746+YmejiV86oVCBPBw+dkHdHztxHmVLF6Zrh4ZutEojreLq+YPGApIWhNDVTbdbtu5Ut1s0a0R271vEPXDfQrTpQQy1Pr90wm9jh/DZe68QFJiw2P0HX07m5Jkr7jNKI03jrjUuPblf0NW2GX6D7VvWq2ENaxZx2fltJS2uiaqJXzoha5ZMfDqkJ0e2TFUF8MHDJ3w8wvLClxoatuKuAs0Zg0ZScm532GEuJMYfsXWql3OZHSkhrQig1uyZzsiRPZDpEz6ia98RAJy9cCPpBBoaNuBuN2pJCU9Km0k9rXZpTTR0Oh1Xrt1R94sXy+8qk9I1mvilQ7Q5fhrOwN0CaA1PEzF7sKWWtGHLQSKjYgDIGRJEcKDnT2z31GfFGE380jkRDx4jpdRGfWo4hLRQqHk6tjYLxsXF89ectXz1/Qw1rEOrOk6yKuOh9fmlQzJl8sfLS/lpdTodv05b4maLNNITaaVPx9OwZ0BIVHQML/X7mg+/+p1nz6MAyJE9bTmv8PTnRBO/dEi2rJkZ0Luduv/l6L94ddB3/LfjCOl58WIN15HWRva5A+MRkPbeqz9nrWbz9sPqfrEi+Vg+axT58niug+60hiZ+6ZRRw/pTqXxC39/Kdbvp3PtLmnZ+n5Xrd6PT6dxonUZ6QRNBUxw15H/DloPqds8Xm7Frza9ULFc0tea5HE9+NjTxS6f4+vowalh/MgX4mYQfPnaBVwd+R7227zB/6Rbi4uLdZKFGeiIji6Az5rgZmjoBXn2phbYmpxPQxC8d06huJU7v+ZtFM75mQO/2BPgnCOHpc9cYMHQc1ZsP4q85a4mOjnWjpRrphbQ42dleUtOcaSu5QoLU7fsP0u5oVvDc2p8mfumc7EFZadG4Gj+OHMTx7X8wZGBXsmbJpB6/cu0O7w2bRJUmA/ht+jKTL04NjdSQHkTQXOhcdT05Q4LV7XvhD11yzoyGJn4ZiNy5sjPy074c3/Ennw99hezB2dRjt+5E8Nk3f1CxYX/GTpzHw8dP3WipRnrC00XQksC52+bswQlz+R4+1N5FZ6CJXwYkR3A2Pnm3J8e3/8E3n71OnlzZ1WMR9x/z7bhZVGzQn5Fj/yE84pEbLdVIT7hDVJISNncLXFJcvxmmboeEeL6j7+TwxPss0vPQ96qVSsqty8e72wyPJyo6hlkLNvLL74u4dvOeybFMAX707dmGdwZ00dYI1NBwAA8ePWXn3uME+PuRI3sgITkCCckeSOZM/jx89JT5S7fw6Td/qNOSVs8dTf3aFdxsdeoxOEfIElzkoJSyhpvN0cRPI4HY2DgWLN/KT78t4PylmybHfH19+PDt7nz4dnd8fLzdZKGGRtomLi6eWi3/x8Urti1H1LBORZbP/lZ1WmErYRe3AZCreCO7bXQmPtkrauLnCjTxSxnx8fGsWLeHHyfN5/ipSybH6tUsz7SfPyA0fy6b8zMMosmSOcChdmpopBV0Oh17D55m1oKNzFqw0aY0RQvnY+OiseQMCVLFLLW4Www9Sfy0Pj+NRHh7e9O5XX22r/yZhX99RfXKpdRju/afpH67d1mxbrdNec1fuoUCFbpToEJ3GncayuoNezUvMxoZCiklnfsMp033Ty0KX4F8OfH38wUgW9ZMVChThO++6M/W5ePJaTTlQcOxaDU/jWSJj4/np98WMvqXOcTHJ3iGadawKjWqlCJL5kxkyRxA5sz+FArNQ53qZfH19SEyKpoKDfonGjTTuH5lpv/ykfZia2QITpy+TP1271o9fvnwHLIHZSU+Xpdkl0Jqa3/urvUZCCra0SNqftqqDhrJ4u3tzUfvvEzDuhV5Y8iPXL+ljETbvP2wif9BA0GBWWjVtAb7D5+1OFp0686jvDpoFCtmj8JP/8WroZFeuX03Isnj98IekCM4W7J96bmKN3JY86eG1uypYQd1apRj++oJdG5XP8l4jx4/Y8GyrSYLcA4b+ioDerdXl1bac+A0I3+c6VR7NTQ8gfJlEnxy+vn58NO3/6NksQIAVChThBJFC9icV67ijVJUg/OUWp8nodX8NOwie1BW/p70KSfPXGH/4bPcuhPOs+dRPI+M5snT5+zef5Ibt8JN0jRvVI0PB3fHy8uLggVyM3zMXwDMWrCRbz/v547L0NBwGfnzhlCiaAEuXL5JTEwcZUsWYv/GyYSFPyQoMGuKRk9rtcDUo4mfRoooX6YI5csUSRQupeTYqUus/+8AT55Gkj9PDnp1b6kO1X73zS6M+WUOzyOjefDwCfcfPiGHkacZDY30SN7c2blwWZk+FBMbhxCC3EbOJVKCJoCpQxM/DYcihKBy+eJULl/c6vGihfJx8uwVQBkM0KhuJRdaqKHhGKSUDB8zg6WrdlC4YB4qVyhO1YolKFuqMKWKh+LrqxSvOp2OE2euqOkK5HXcmnyG5sykRFBr8rSMJn4aLqd8mSKq+O07dEYTPw2PRkrJ9xPmcvTERV5oW48eLzYDYOHyrUyYuhiAazfvsX1Pgguvgvlz8d+yn8iVM5jjpy/z8JHinzNPruyUKGZ7H5+taLVA+9EGvGi4FCklG7YmLNQZpnms1/Bwlq3Zxeif57B6414GfjCeLTuPAlgc6Wzg+q0w5i/bAsD23Qmi2KBORXXQl6OxVMPTan3W0cRPwyXExsbxz7z11Gr5Px48fKKGd+2ovZwano3xxxrAxD+WAKbLDhXMn4sP3+5uEu/0uWsAbN99TA1rWKeik6xUSOlo0IyIJn4aTicmJpYX+37FO5/+yrmLN9TwAb3bU6taGTdapqGRPKfPXjXZ37DlIKfPXTURsuDgbHz5YW/+nPCRGjZ74Samz1lj0hzqqiZ+TQCTR+vz03A6sxduYtuuhK9fLy8vurRvwBcf9nKjVRoayaPT6Thz/lqi8M69h1OkUB51/+mzSADaNq9F4YJ5uHr9LjqdjqHDflPjFArNTbEi+ZxvtB5NAJNGq/lpOJ09B06p2x1a1eHUrulMn/ARwYFZk0iloeF+rt28pzpmB9T+ujv37rPnwGk13FCjy5I5gNVzR1OmZMFEefV7ta3T+vs07EcTPw2nkytnsLpdolgB8uVx3FBvDQ17iI+P5/6Dx8TGxtkUf/WGvep24/qV+W3sELJlzWQSp3zpIoz45DV1PzR/LtbM/55XujYjOCgrgdkyM/C1Drw7oItjLkLDIWjNnhpOJ2/uHOp2xP3HbrREIyOi0+n45OtpLFq5jfsPniClxN/Plwpli1KlYnGqVChBxXLFyJMrO9myZuJe+ENu3Apj176T/Pz7IjWfzu3q80rX5rRsXJ21m/dz+04EZUoVonXTmvj7m/qozRGcjck/DlVXMNFqfJ6HJn4aTmeHUYd/udKF3WiJRkZk5fo9TP1npUlYdEwsB4+e4+DRczblUahAbrq/0ARQWjJ6d29pUzpN9DyXZJs9hRDdhBCLhBBXhRCRQoizQojRQgirPqmEEFOEEFIIMcvCsSZCiDNCiMf6eH5Gx4ro00khRDMLaXcIIbbYcX0aHoDxqtVPnj53oyUaGZFJfy412TdvtkyOwgXzMGvK52TNYl86Dc/Glprfh8A14HPgBlAVGAE0FULUk1LqjCMLIeoBrwKJ2reEEFmA+cD3wBFgNDAEGGvhvKOAujZeh4YHU7ViCXWKw3fj5/Dw0VNGfNw3UVORhoYzOHH6irp9bPsfFA7NQ3jEI46cuMiRExc4cuICFy7d5P6DJzx+8oycOYLIlzeEksUK0KxRNTq0qkOAv5/1E2ikSWwRv45SyjCj/a1CiPvA30ATYLPhgBDCF5iKIlwDLeRVFrgupRynj/8N8CaJxW890EoI0VFKucLGa9HwUEZ80pcde09w87ay2sNv05ezffdxtq38WXV4raHhDKSUPI+MVvcL5M0JQM6QIFo0rkaLxtXcZZqGm0m25DETPgP79f/NndR9BHgD46xkdw0ooW/6DAF6AZYa3RcCh4BvhdZonubJnzeE+X8ONwk7fvqy6uVeQ8NZ3A17gE6nNE5lzuSfouWDNNInKR3w0lj/X53oIoQoDnwBtJdSxljSLCnlPSHEF8AG/bkPAP+zkL/U57UaeBmYm0I7NTyECmWLUjB/LnUV+JwhQRQt5LoJvxoZh4uXb7Fg+Vbu3LvPkRMX1PDqlUu50SoNT8Nu8RNCFABGAhullAeMDv0OLJZS/pdUeinlr/qBMCHAJfM+Q6N4a4QQO4CRQoiFUkrbJuZoeCQXr9xShQ9g8tj31CVfNDQcxaQ/l/Ll6L+Ij09crDRwsl9NjbSFXR0uQoiswDIgDnjdKLwXUBNlcEyySCkfSCkvWBM+Iz4HSgJ97bDxTSHEASHEgYiIR7Ym03AywYFZ8PNLELvswZp3Fw3HMnP+Bj7/9k+Lwpc5kz8vdWpsIZVGRsVm8RNCBADLgWJAaynlDX14VuAnlBGcUUKIYCFEsD5vX/1+iob1SSm3A2uB4UIIfxvTTJVS1pBS1ggJCUrJaTWcQEiOIHWeFMCmbdaXg9HQsJcbt8L45Oup6n6ViiX4dEhPWjapTpf2DVg261uKF83vRgs1PA2b2p304rUIqAW0kFIeNzqcE8gFfKf/M6Yg0B3oAixNoY3DUPoGB6UwvYaHULNqGWYt2AjAJaO5fxoaqeXTb6apPjhLlyjI6rmjyZI5wM1WaXgyyYqfEMILmA00RxnMsscsyh2gqYWkc4HjKNMeTqTUQCnlISHEIpQm0FuA1paZBpFSsv/IWXVf6+/TcBTr/zvAirW71f1fvnvbovD5ZFf6/OIeHE90TCPjYUsJNAl4CUXEngkh6hgdu6Fv/txinkgIEQXclVImOpYCvkQR0NzAVgfkp+FCdDodw0b9yaz5G9SwujXLu9EijfSClJLPv/1D3e/1UguLz5ZB+AzbmgBq2NLn11b/fxiw2+zvDSfZZYKU8gww0xXn0nAMcXHxxMfH8+DRU/oP+ZHfpi9Xj7VoXI0eXSw1Fmho2Mf5Szc4f0mZL5o1SyZGftrX5LhP9oomwmccrpGxSbbmJ6UskpKMU5JOSnkFsDipXUr5OkYjTDU8DyklsxZsZPTPc7h5OxwhhOrV3kCnNvWY9vMH2mRjDYdg7L3F39+XwGxZ1P3kBE6rAWZsNN9SGg5j1oKNDP5kgurGzFz43ujVjhkTP9b8JGo4jDIlCxGSIxBQlstasmoHYHvNzlrNUCP9o4mfhsP4e+66RGFCCEqXKMjvPw7lx5GD8PbWanwajiPA3483erVT99ds2pciMdMEMOOhDbnTcBjGTqr/+vVjOrauS7xOp9X0NJxKrpzB6raXf7DVeMmhjQbNWGjip+EQIqOiuX03Qt339/PF19cHbdEiDWezYl3CNIdqVSqlOj9NBDMGWrOnhkP4dtwsrt24B0BgtsyaH0UNl3DjVhjbdh0DlCb2l7p2dFjeWn9g+kYTP41U8/RZJNP+WaXuj/z0dYICsySRQkPDMfw9d506sKppkwbkz5/X4efQBDB9ojV7aqSasIhHRMfEqvsvvaA5ENZwHrv2nWTB8q2cOnuFPQfUVdV4tWdXp53TmgBqTaNpF038NFJN4dDcJmv17dx7gtbNarrZKo30yKZth3jxta8ShZcvV4auXdq73B5ba4VxD44TExPLxq2HCL//iOaNqlEgX84k00Tcf8SaTftZuW43N26F8el7PenQqq56XEqJttZ3ytHETyPVeHl5kStnsCp+2gup4SzG/jovUVjjRvX4feIP+Pp67vAqn+wV+fij4UyZ9g8AITkCWTf/e0oWD7UY/99Fm3lv2CSiomPUsH7vjGXrivHkzhnMiB/+YfHK7VStVJIvP+hF7eplXXId6QlhPhE5PVG1Ukm5dfl4d5uR7nkeGUWhyj2JjVXWG758aDY5sge62SqN9EiRqq/w4OETABrWr83PP42iTOkSbrYqeR49ekyh4tWIi0tYk7tsqUJsXf4z/v6mor1y/W56DRqdyEkEQOUKxckelI0tO4+oYd7eXmxf+QvlyxRxlvkOJahox4NSyhrutkMb8KKRag4dPa8KX6nioZrwaTiNksUKqNvbd+7l9TfeJTIyyo0W2caly9dMhA/g9LlrvPPpBHS6hMV3z1+8waAPxqvCF5o/J5+994o6V/boiYsmwgcQH69j94FTzr2AdIgmfhqpZs/BhEEHdWqUc6MlGumdt/t3Ntk/dvwUi5asdI8xdvDs2TOL4fOWbuH9LycjpeTJ0+f0eus7njyNBKBIobxsW/Gzsihv0+rJ5O/5HwCehtbnp5Fq9pqIn9b3oOE88hSukijsypVrrjfETjJnzqRuV65UnurVKjF9xr8A/DVnLSdOXyYs4hFXrt0BFLdtMyd/RkiOIACa1K9ismahOdUrl3Si9ekTreankWrOXbyhbn/y9VRu6Ae+aGg4CsOE83kLlpmG+/jwihOnODiKrFkT5r2GhUfwy0+j6Pnyi2rY/sNnVeEDGD/qf1QqV0zdf7FDQ3KFBFvOO0smalUr43ij0zma+GmkmuJF8qvbT55GMu63BW60RsOZ3H/4hNUb9jJrwUaOnrzo9POZe1m5fuOmyfFZMyZRrGhhp9uRWooVLazW/m7dusOtW3f4fdIPdH/pBZN4/n6+TPphCK90bW4SniM4G7N+/4zswdnIFRLM2BED1WO5cwXj5+e5I109Fa3ZUyPVjPvmLao0HqDuz1qwgXKlC9O2eS1C8+dyo2UajuLgkXNMmLaY1Rv3EhOTMHDjtR6tmTB6sMvsKFQwYcBLn17d6dihtcvOnRp8fHyoUb0K27YrTZd79x+ia5cOTJ/6M71ffYndu/cTGlqAVi0akyvgnsU86tQox4X9M9X+wY9GTAHgXthD4uPjtRVT7ESr+WmkmqKF8jL4jc7qfkxMHB8O/50azQexZedR9xmmYTdSSvoPGUvRaq/wwZeTefzkOTduhdGy20csXb3TRPhAcS9m7NDc0Zh7UOnaJcF358zZCzh85ITTzu1o6tROGLSye88BQJkT26xJA4Z9NpTXencnX748SfoU9fHxxtfXh+zB2citX83i6bNIE083GrahiZ+GQxj4WsdEfRKRUTG8OnCU1geYhrh1J4KFy7dx/8ET/pi1moKVXqZSozeIj9clmW7xyu3MX7qFC5duJhkvtTRpXI+2rZUmQSklH306wuJ8OE/EWPz27juUbPykvMcIIejUpp66b1jEV8N2NPHTcAiFQnOzdcV43v/fS3Tt2Eh1bP30WSSff/unm63TsJV8eXIkCrMmfN989jqXDs6iWecPeP2dHxgwdBw1WrzFP/PWO9XG0aOGqd5cdu85wPqNW5x6PkdRq2Y1dfvosZM8e/Y82TRJ1QI7t2+gbi9bs5P4+PjUG5mB0MRPw2EUyJeTrz7qw/QJHzF32pdq+LI1O1m4YpsbLdOwFS8vL9bOH5NsvBc7NOTdN1/k6o173LqT0OwppWTk2JlOLYhLlijGG/1eVff//iexyzNPJHtwEGXLKFMS4uPjOXT4mM1pDSJoLIT1apZTmz7vhT9k135tors9aOKn4RTq1SpPzxebqftvDh3H6J/nEB0dm0QqDU+gbs3ynNjxJwNf64CPj+VBFLFxcWzceohRP81KdCws4iF3wx46zB5LKyf06/uKur1t++40U+upUjlBvM5fuJSiPAwi6J+zCi+0ra+GL1m1PdX2ZSQ08dNwGqOG9VPdUcXH6xjzy7/UaDGITdsOMWzUn5Sq1YfBn0zgydPkm380XEvBArn5YcRAIs4vJezsYjYt/tHk+Iq1u+na9ys2brXcd+Xl5Vzn5mXLlCRPHmUk8YOHj1ix0rlNrc7Az88v1Xl069FH3V6+bj9xcWnjI8AT0MRPw2mE5Ahi5b/fUbNqaTXs2o17vPjaV0z8Yyl3wx4wc/4Ghn7xmxutTN84ojD08/MlZ84gu9JkCvBP9XmTQghBl07t1P3X+r/D8K+/N/GT6WnExcVx7HhC02SWLJlTnWfdOjXUj4CwsHCOXdFpK9DbiCZ+Gk4lb+4crFvwPT9+PchqnNNnr7rQoozDxq2HKFK1J9WbDWL1hr2pysvPjuWCXu3WXB3w5Ew++fgdcudW1sSLi4tj3PjJTPszcTOsp/Drb39y8tQZAPz9/ahTO/ULG3h7e1OvTsLamZevXFe3LfUTaiSgTXLXcDre3t4M6NOevHly0GvQd4mOF8if9KKeGinjz1mrefI0kidPb9LzzW9pXL8yr7zYjHYt6xCYzb5ah5+v5aKiYd1KICVSSnJkD6R/r3Y0rlfJEeYnS+5cOdm4diH9BgzhwEFlPunM2QsYOKBPMintJ4KElUpCeGxXWikl/8ycz1df/6CGff7pe+TLm9shtoWGJnhYunb9hsU4BgHUVp5PQBM/DZfRoVUdvvigF5u3HWbX/pNqePuWddxoVfolUybTpsetO4+ydedRvLy8KF4kH+XLFKF86SLK/7JFKFQgN15elhuD1m85kChs4vfv0rt7S6fYbk7cg+MWazDFixVh6aJ/CC1SGYATJ88QExPjkP40A8bCZ2nfHIM4hoVHMPvfRcz4e67J4JYqlSswZPAAa8ntxtjrzekz55OMa3wPM7oQauKn4TKEEHw0+GVqVi3DC72+ACAwW2a6dWrsZsvSJ1993IeV63YTHWM6wlan03H+0k3OX7rJ0tU71fBsWTNRrnQRypUuTPkyRahQpgjlShfB19ebr8bMSJR/xXJFnX0JNpE9OIhiRQtz6fJVYmNj2bl7P00b108+oZO4HRPA6K9GMPPP6cTExJgcK1O6BAvnTXfoqvPGk+cXLFxO08b16f3qS8mmc6UQemLTqyZ+Gi5n+uw16naPLs3IkjnAjdakXwqH5uHUrr8Y/fMc/pi1Otn4T55GsvfgaZMlqpLC18dzio/WLZsyeeoMAFasXOcw8UuulmdObGwsr7/cg+3/bTEJzxaYjVf69mXoJx/jlyULEdjffGqNqlUqUq9uTXbt3o9Op+PdocNo0qgeBY1qhMnhDCH0RMEzRqQV10ApoWqlknLr8vHuNkPDiDv37lO+fj91FOKedRMpW8rzvfKndc5dvM7w0TNYs2mfxeN+vj7ExMZZPGaNfRt+o3SJgo4wzyaSKky3bd9N2449AcgZkoPjh7cSGJgtVeezV/gARnz6GdN/n6LuV6palT79+9GhS2cyZ7E+CCi1QngvLJxmLV/ksn5twz+mjKfny11SlaezyBJc5KCUMvWjfVKJNtpTw6X8M3e9Knz1apbXhM9FlCpekLl/fMmKOaOoXKF4ouP2Ch9AWPhDB1jmGOrVrakO/AiPuE+12i34Z9b8FOeXEuFbsWSJifC9/f5QVmzeSPderyYpfIbzGf5SQu5cOalcqby6v2DR8kRNrhqmaOKn4TJiY+P4e946db9/r7ZutCZj0qhuJbYs+4kp44ZSIJ/to2y9vAR1a5SjR5emath/O444wULrJNUc5+Pjw+efvKfu3759l7ff/ZQbN27ZfZ6UCNDDhw/56uNP1f22HTvw8ZdfIIT9k/1TKoLGfX/r1v/HLxOn2Z1HRkITPw2X8dPkBdy4FQ5AzpAgOraul0wKDWfg5eVFjxebcWDTZN4ZYFvTmE4n2X3glMkCtj9Omk+ZOq/RsutH3H/gmP6r1NCn10sEGE2u1+l0PHvuGu9B3389kvAwZfWSvPnz8eOkiSkSPmPsFcFBb75G0yYJzq63bd+TqvOndzTx03AJR09e5IdfExwQvzewK/7+2urT7iRzpgC+/bwfXTs2sjnN6XPXTFyX3b57n32HztDxlWHOMNEuhBAmC7q2bd2c0qVKOP28p46fYPZfM9T9kd9/T7bAlDVfWsJWAfT19eVlo5Xhc+QIdpgN6RFN/DRcwldjZqh9fXVqlOV//Tq52SINA9990Z/CBfPYHF+nk3h7mxYdgdmc79HFFgoVClW3q1Qun0RMy6SkuXH2jBnqdrPWrWjdob3deSSHrbVAndHyU1GRUQ63Iz2hiZ+G07l9N8Kkf2jimHdNvtA13Eve3DnYteZXfhs7hDd6tSN7cNZk0wz/yNSLSvGi+a3EdC1D3x2obu+xYcHY1BIVGcmyBQvV/UHvvJPq5s6kSE4E69Qx6vfbsIWI+w+cZktaRxM/Dafz+ElCv0vOkCBKFg9NIraGO8iaJROvdmvBuG/e4vTuGUwYPZgWjatRtHA+AvwTe0uJiYllwujB6v6KdbuJjIp2pckWqV6tsrp98eJldfvM2Qu06/QKlas3pXW77mzeknjl85TU+v7bsJHHj5X+zsJFi1K7vmv6sa3ZWqpkcXWKR2xsLNeuWXZ3pqGJn4YLyJs7h7ouXHjEI4aN+pOLVxJG4cXHx7Nz7wn+XbSZ3ftPamv+uZlMAf681qM1i2Z8zZEtU7lzeiFXjvzLoL4d1TjfT5hLnlzZ1f2Hj55yN8z5tYzkJmAXLVJQddF2/cYtoqKiePbsOd1e7sfWbbu4cPEyO3bto1OX3kyeMiPV9kREJCzkW71WLafW+hKd20ItcOu23Tx+/ASAzJkzUbJEMZfZk9bwHBcNGumWoMAsvNqtBX/PVaY5TPxjKRP/WEqp4qG0aFyN3QdOcfjYBTV+YLbMtG5Wk46t69KicXXNA4ybEUKQPSgro4b1Z+PWQ1y4fJO4uHim/L3SJF6+3CFusjABf39/Cobm5+q1G0gpuXzlOkePnVQnfxuQUvLhJyO4cfM23379KfeFfUs2GShUuJC6fePatSRiOo8IAgnhMVJKRo5KWHexR/fOZM3qGX2xnogmfhou4etP+3Li9GUOHj2nhp27eINzFxM3yzx+8pwFy7ayYNlWAvz9aNuiFgXy5SQoWxZ6vNiMQqGO8YavYR8xsbFcuHxT3d+8/bC6XbNqaY8ZvVu8eFGu6pv7Ll68zP79CXY2rF+bJ0+fceToCQB+njCFEsWL0Om1gRbzSo6ixRNGkx49dIiwe/fIldv1z2cEgRzcv4+9+n5OPz8/Pv5gcDKpMjZas6eGS8gelJU188bw65h3aNu8FpkCTPuRvL29aNmkeqJRh1HRMSxZtYOJfyxl1PjZtHjxQ54+i3Sl6Rp6Hj56ZvXYh293d6ElSVOieBF1+8KlKzx49Ejd79P7ZebPMZ38PXjIZyk+V2ihglSqWhWA6OhoZkx138TyPTt3qdvdu3Wyy7dnRkQTPw2X4e/vS5+XWzH3jy+5fHgO8/8czjsDujBkYFe2LB/Pwr9GcHTrNHasmsAn7/agXOnErs/uhj3gyrU7brBeI1+eHBbDK1coTutmNS0ecwfFixVRty9evIwgoR9OSkmBAvl412xJod8nTEjRuYQQDBryjrq/btWqFOXjCJ48TnA0kL9EWbfZkVbQxE/DLWQK8Kd1s5p8+3k/Rn7al0rllI55IQQVyxXl86GvsnvtRJMRhQDZg7NRopj2ResOhBCUL10kUXi1SiVdOtAjOUoUT1hq6cLFK+pgK4Dneo8vo0Z+Rq2aVdXwv6f+keLzNWvZUh1kc/7MWRMRciWxRr48fX19UuUrNCOgiZ+Gx7Jx6yE++mqKSdiPIwdZHHqv4RpCQhIXpp42IKm4UbPnxUtXKFkyYcTj4SNKX5+XlxdLF/6tht+8cYNbN1I2LSBzliyULa9MqJdScvTw4WRSOIfMmTOr2xHhCaNQNRG0jCZ+Gh7J+v8O0PPNb9SFWIOyZeHfqV/QzQ5XXBqOJ3tQ4mWCPE38ihQuqDpRuHnzNmVLl1SP7d13UN0OCgqkfuOEhZQXz1+Q4nNWrZmwQs+hfftTnE9qKF2+nLp95uTJRMc1ETRFEz8Nj2PNxn28OmgUMTHKMjsF8+fiv+U/0a5lbTdbljGJj49nxA9/07b7pyxbszPR8VIe5rTA19eXShUThCA8/L4qhmfOXuDBQ2UATASBdOvZQ423doXp1A17qFYzoc9z7YqVuGOdVEPtE+D0yVNW42kiqKCJn4ZHse/QGXr/b7QqfIUL5mHVvNEUL+IZ7rMyGvHx8Qz64GfGT17Irv2JaxMAFcs5fyK1T/aK6p8tdGzfSt1eumINZStUUPc3HzirFv4t2rTBR78i/bHDh1Pc9NmiTWv8A5Qa8Iljxzi03/W1vyLFiqk23L19m/tGE/AtkdEFUBM/DY9BSsmnI6cRq19YtWjhfKz69zsKh9rudFkj5cTHxzN9zhpefO0r2vf4jE6vDqNiwzeYv2yL1TSZAvwo4SS/nvYKnjGNOnZVt9dv2MKJo0fV/TOnEmpFQcFB1G2YsAzQ+tVrUmRrtsBASpRMaF7dsGZtivJJDd7e3pQumzDK80wStT8NG8RPCNFNCLFICHFVCBEphDgrhBgthMhmFKe6EGKtEOKmECJKCHFHCLFaCFHXQn5NhBBnhBCPhRBThBB+RseKCCGk/q+ZhbQ7hBBbUnG9Gh7MwSPn1Enw/n6+LPlnJAULaBPaXcVvfy1n6LDf2LTtEDv2nmDrrmPcvB2eZJoC+XI51El5SgXPeCX0CAIpVaYMPXr3shjXfLmhNh06qNtrV9o/VeHooUPUq1SZk8cTXK9lSWbldmdR1qjf77SFfj9zMnLtz5aa34dAPPA50AaYDLwFbBBCGNIHAxeAD4DWwDv6sK1CiFqGjIQQWYD5wDSgC1AVGGLlvKPsuxQNTyPs4jb1zxau3bynbrdoXI2ihfI6yzQNC8xZuCnZONmDs7Fs1jfq/uVrt7l1J+nmteRIieCZi50lRo79gcrVqiUKDy1Y0GS/RZvW6vaubduSbS4056fRY7h9M8FXbZ58+ejRp7ddeTiKMkb9fpYGvVgiowqgLeLXUUrZXUo5W0q5VUr5M/AuUBtoAiCl3CSlHCylnKuPswBFBCVg/BSUBa5LKcdJKTcB3wCWhu+tB+oIITpaOKaRBrFFAJ89T1h/LDgo+WV1NByLv59l92TeXl6ULaU4HHjw8And+42kpH6uZXy8jrET51lMlxSpreHZQkBAALOXLOZ/Q9+jQqVKCCEoUbECWSuZTgDPV6AAefPnU/e7d+ho84CVk8eO89+Gjep+psyZmb9yuVtcnIHtg140bBA/KWWYhWBDb25Ss42fAdGAsYv+a0AJfdNnCNALOGch7ULgEPCt8KTZsxo2Y0nskqsFPnj4RN3OmiWTU+zSsE7NqqUthvv4eHH63FV1PzomlvOXEnx8Tp+9hn8Xbbb5PCnpw0vJCMVjjyO4ImJpN/RtxqxcxNKLpxi/cjG+/v4cexxh8tf0pYQ+wnOnz/Dg/v3k8z9yhNe6v6zuV6palVPXr1K0eHG77HQkpcqWUbcvX7yQRExTMmLtL6UDXgyTY04bBwohvIQQvkKIQsBEfbDqOkFKeQ/4AtgAhAPFgO8s5C/18SoBL1s4ruHBJFfLsyaCxo6SSxTVvLi4mtbNaiUK8/LyIlo/8jYp3hs2icPHky9sUyp8tmAuaOZ4+/hY9UTzyvvvmuxvO3/aJA8pJXFxceh0Os6ePs3f0/7g5Q6duHdHcbWXOUsWJkyb4vZFmv39/dVtd0y3SEvYLX5CiALASGCjlPKA2eH5QAxwFegKtJNSmtS9pZS/ArmBkkBtKaXFBnYp5RpgBzBSCGHz6hNCiDeFEAeEEAciIh4ln0DDbRgLoE6nY8feE+p++1Z13GFShqZZwyoma/RlyeyPTqcDlCknW5aP59bJBTSqVylR2qjoGHoP+o7wJN45RwtfcmJnD0IIKtVLeOaG9ejD2HffZ/b61Xz/20TKFCxEybz5qVqiFC3r1ufLjz7m2dOnAAQGBTFj3lyKlShhLXuXEa//vQC8vOwT4oxW+7NL/IQQWYFlQBzwuoUoHwO1UITvBLBSCFHDPJKU8oGU8oKUUmd+zIzPUUSyr602SimnSilrSClrhISkbI0ujZRj6+AW4/hhF7cRExunTnEAyJY1cxKpNJyBl5cXo4b1U/efPU9Ymf21Hq05e/4a3fqO4PpNSz0hcP1WGK+/+wNxcfGJjjmqby81Yrfz1tUkj3d96021Zvjk4UO2Ll3BZ917Menz4UQ+fUZ8XFyi5tC8+fOxeN0a6jSob7c9zkAXn3DvU1ILzUgCaLP4CSECgOUoTZWtpZSJZoNKKS9JKfdLKRcDbYF7wLcpNU5KuR1YCwwXQvgnF1/DvdgrfMY8ubGH0LwJHyv9h4wlPj5xIarhXLp1akyT+lUShY8c+w8DPxjPrv0nuXz1ttX023YdY8QPCT4zUzqoxRIpFTzDn/G+Jao3bshHv44nMEd2i8cNZA0KomXbtnw+cgQbd++mVJkyScZ3JTqjml98XJzW9JkENomfEMIXWIRSq2snpTyeTBKklDHAMSC1bQHDgFBgUCrz0fBwhr5uNNn4vwNM+nOZG63JmAghmDBmMDmyJ/bhmRTGg2V+nbaEY6cuOby2ZwvGYpdUTc/a8Uad2vPP/p18M+svk3Avb2+++msqE9evZNah3fz572wGvfsugUGeVVPKniMH2QKV3+7x48dcv2r/6vIZpfZnyyR3L2A20Bx4QUq5x5aMhRCZgRrAxdQYKKU8hCK8nwPumTmqkSypqfUZeKF5Od58OWHQxQ+/zuXRY+sLqGo4h8Khefh86KsmYRXKFqVV0xoM6N3eojCePHOFJg0qq/vLN1saxG2dlNb2bBW7pNKvOXKA5dP/5tC27QD4+PpStVEDXnpb+d7OV7gQX/4xmZrNm1KkTGl8fH1T3cfoLLy9valaI6Gnafrvv7vRGs/GlprfJOAl4EfgmRCijtFfKIDeU8toIURXIURjIUQfYAuQj1Q0exrxJRACVHFAXhoezNDXG1C8kLJo6pOnkfw9d52bLcp4xMTE4u1tWjScOH2Znl2bMWTgi8yd9iUhOUzFKjIqhtZNEpw7nzhxxubz2SN8qRU7c6ROx9x3P2HqiG8Z3qsfx/fsVY+99skHzDtxiKnbNlKzeVOb7PMEXujWTd2e/vsUurZtx/JFi+xqAs0ItT9bRlG21f8fpv8z5mtgBLAXeAN4E6V2dlMf1t+WJtLkkFKeEULMxI6BLxquwxG1PgO+Pt70f6kmn49TRG/Sn8vo27MNgdm0ATCu4NqNe7Tv+TnXbtxNdOz1wT+o29Url6JXtxY8evKMBw+f0qZ5TapUSOjh2LBpK+fOX6RUSetz3uyt7aVU7LYdP50orFFFZaL7/Ru3iLiS0DS45cB+HhfKS/38yqT+LIFJN/8eexxBpcCQFNnlLLr17MGa5SvYuFbxL7p/9x72797DhXPnef+zT23OJ4JAQnDPwryuQKTnDtGqlUrKrcvHu9uMdI0jhc9AdEwcjV+dQvgDZdXtTAF+dO3UmK8+7E3uXEkPRtBIOVHRMTRo967JBPakyJ0zmMk/vkeLxtUBZXBL2w492LZD6Rl5oWMb5sy03OzmTOGzJHaWaFSxLPvnLWbj+N/UsA5ffULFti3VfYMIJoenCeDDhw8Z9v4HrF623GTg2IZdOyhdrlwSKU1xhvhlCS5yUEqZaBaAq9FWddDwOPz9fPiwf4LXu8ioGGbN30C7Hp8RHR2bREqN1LBs9c5khS9/3oRC/l74Q74bP4cpM1YQHx9P3IPjjB71hXp8+cp13Lp1x2I+1gpVR4hIo4pl1ZpdcuydbbqAbeHqVUz2bW1idcRcQ0cSHBzMpOl/sufkcQoXLaqGH9i3z41WeRY2Tx7X0DDHGbU+A93aVMQ3qCg/TpzH7bvK3Krzl26ycetBbQK8k9i49ZDJfsliBZBSmThdp3pZfhw5iKxZMrF5+2F6DfqOZ8+jOHhUWYnj8rU7jBk+gAqFJPVrlWfnvpNIKdmz7yAvdm5v8XwGATSvBRoE0FhMjGtgttYCkxLAuOgYji5fw5N7CXMW85YuSWDuXFbT7Lx1NdmaoKc1g+bJm5cXur7IhB/HAXDHyAF3cqTnJk/QxE/DQ8lVvBFvFIf+r7alfY/P2LlP8VAf8SB9v5Du4vGT56zbbLoA687Vv+Lvn+Ds+vS5qwz68GeOWHBjNvmv5TSsU5H2repQq3pZ9ffaunGVVfEzYI8IgvWmSFtF8dn9B8z+3wcmfX0ANV7ukmzatCiA+UITXAXeumlbk3Z6Fz7Qmj01Uogza325iic0eQohTPwx5s4Z7LTzZkTi4+MZ8vlEitd4lUdPLE8riY2NY9aCjbTq9rFF4TMwYdpiABrXS5jyMG/pf0Rc3UPcg+THvYXw2GKhWykwxCYxqZ+/sNU/Y1aM/D6R8AGEVqqQKMwSaa0ZNF/+BPG7fSv5ml9GED7Qan4aKcCZwmfOg0dP1QVuQZlvpuEY4uPj+eybP5jxr+XpJLfvRZAtSya6vj6Cw8eSd1pdsWwxABrXq0Sp4qGcu3iDJ08jWbd5P907N1EFMLnJ78nVBMG+aQZr58xj+4rV+Pj5Eps1E5f3mLskVpo8gwvks5BawXgQjaE5Na3UAvMXSBC/a1esi3ZGET0DmvhpeBTGtT6dTse7n/5KZFQMAKWKh1IgX053mZaueB4ZRZc+w9lzwPrIyOGjZxAbG2eT8L3WoxVjvx4IKD5CO7Suy0+/KYNJRo2fTZvmtdTpKsa1wKSE0JoIQvIDYwziGHbrNhM//SLJuAB3zp7nwfWb5CgUmuiY+ejRbcdPpykBLFqiOH5+fsTExHDtyhVu3bhB/lDT68xowgdas6eGnbiquRNg+py1LF+7S93/fOirVpek0bCP/7YfSVL4AJat2cnqjQmTvr28EooL83mXR05cNPltXu/ZhmxZlTUZr1y7w8ix/1icZB334Lj6Zw1Dc6itBXR8fDznVm3gk/YvMvr1N21KA7Duh1+sTgQ/euoUR08lLFBjLIi29DW6swnU39+fStWqqvsfvP0Ojx8p99Ke+5re0MRPwyMwFz6Af+atV7df69GaLu0bJIqjkTJqVy9rdy3a4DS5WJF8nNnzN9eOzsXXV2k8OnriIjduJYycLBSam5GfJSz8Mm3mKvoO/t7E8bI59grhypl/8EKTxrSsV592jZvSr8crzJ4xg6ULFvL+W//j5PHjnDtt3dNM4RpVyW40GOTKgcPsmTnXJI55rS+tCuCbb7+tbu/cupVOzVvw7FrGXuldEz8Nm3FlXx9gssTRC23rufTc6Z2cIUFsW/Ezb/RqZ/cgohfa1idL5gCCArPQoHbCIJGlq3eaxOvRpSklixUwOb5szS5sITkhjI+P58NPvuLwkeOcPXWaE0ePsnHtWj57733Gj7LsUdHX15cRY0bz04pFDBj+OZ1HfcEbc6YRUqSQGmfLb38y971PObtlB1Iv1MaCZ76fVgSwTccOJt5dLl24QJ9+gzP0yima+GnYhCubOw1Uq1RS3V68aofTzp9RyRkSxLhv3uLs3r9ZNGMEr3RtxudDX2Hkp4mX6vTxSVgbrmmDKup253YJtfEpf68wWcsvc6YAVs0dTf1a5dWwvoO/59dpS9iw0rSGZUxcXDynz13l6bNIZd+CEB49dpLnzyMtpr923fJw/jMndtJv0EC6NWzKC2+8TuagIHz8/Oj3z++EVk4Q8ct7DrD40xH8MeRTtRn06fmzPD1/NuH8aVAA3/vkY2b8OQEfH6W2vv/AEbZu3+0WWzwBTfzSCIZFX9Mb1oQPoG/P1ur2kpXbiYnRvLs4Ay8vL1o0rs7kH4fyybs96dYp4TfxEoL8eUNUUcsU4Eed6gnusbp3bqyu8nDtxj3mLf3PJO88ubIzftTbJmFffDedbu/MZtyPP6vPteHZPnj0HBUa9KNO68EUqfoKl6+ZeogxiOAXX3xp1zW++UZv8ubJbdK/ZRio4uPnR49fxlC+dXOTNOH7D3Fg5hyTsLQsgCE85qWunej96ktq2N69B11uh6egiZ8HY14wGIe52g5nkJTwAdSoUprCBfMA8Ox5FMdPX3aKHRqm5M2dHT8/pXagk5K3Xu+kHqtfu4LJxPfMmQJ4q2/C8e/GzyYqOsYkv9IlClKtfP5E55m94ojJftjFbfw5fabq0Sc2No73v/gtUTqAbFltc3SeOZM/b/Rqx4ihnUxqjuajL30DAuj09WcMnD+Dcq2aqeExO/bydI/pKm5pTQDNB7WUL5ew9uKdu/dcYoMnoomfB2KLwDlbBC0Jr6sRQlC1YsJKAcYjPzWch7e3t8lq7sZuz8qULJQo/v/6v0DOkCAAbtwKZ8KUxeoxwzM06asX6NO5Gp2aJbgcu3gtgt2HTUWifRPTVdE3bz/MmYNrEz2PY758gw6t61q9hn6vtmXfht+4dnQu4755iyyZA9RjBiGoFBiSaJpCjkKhBHXpSLbi+vmkUsKhk3DvLjy8r8azVQBtmQzvTCyN5MydO2Gg07174U49vyejiZ8HkRKxcaRAuVLwkqv1GWjfMsGP5+TpywkLf+gkizSMeaVrQhPguYs31O3goKyJ4mbNkslk8duxk+axYtEsk+coV46sDB/cnJ8+70CLegkfNB9+v5romISBTbUqFWTYW6Zr502cafrRE3ZxGwFRZ/j5owac3/AhW2a9yQ8ftyVXjoS1rg8fPkrpEgXV0agGDLU/S82fBrx8fCj95uuITHrBjI6BM1dAJ+0WQEi+FugsAbQ2hSF3LiPxC9PET8ONOEJwUpOHq2t4tgofQLdOjahUXvEcEh0Ty/xlW5xklYYxhnsO8MxoYMm+Q5anDvTt0YoKpZQm6piYON4ZuZzwB5bdpQ0f3JxsmZQBNHfDn9J78B8cXr9WPf5Kxyom8WcuO8zWfZabvIUQhOYN4sVWFejetpJRuOnHnPEznlTzp0G4zty5jX+7hKWNePwMrupdgzlBAB1JcnP38uRJcN59926Y1XjpHU383IgzRCcl+eUq3ijZP0eQkry8vLx4o1c7dX+tmfNlDccSHx/Pxq0HGfLZRDXs8ZPn6vb6/w7Qf8hYIu4/Mknn7e3NpK9eIHeIUvt68DiSbyZtTpT/rX2b4coB+jRNcCV26NITBk0+w4lN67i1bzMRR7ZRsXAWk3R/zdzArX2blfQWkFKybFOC+HRtbdlzjPH7EcJjbly7TsVsOdTan/FKED6FQqF0wkcAN8Mg/CEE51CDspZM6D+rbLZOnj0C6Kjany0T1rNmSbi3zyMtj5jNCGji5wacWdNylFBZyjc1gpgauxrUTijIzp6/nuJ8NJImNjaOdj0+o2vfEWzfY32i+cLl26jdanCieX0F8gQx9mOjD5VtZ02aNAHy11IGk7xULzc9G+ZRwyOexNLjxxP87/czvPTDcY5fNa01Hrn8lHid9YW3z10O58YdRZCzZvajS8vyVuOGXdxG7P1jfDXyBxpUqcryRYv5YfB7lIhXaqONKpZVhSxL21aQ26h2eOE6PH1O1pKlkxQ+A7YurAuuGwATGRWlbmcKCEgiZvpGEz8Xk56mK9gqiKkV5K27j6rbuiQKQI3UsXL9niRdnhl7lguLeMhrb49hwHvjeB6pFKb/b++846Mo3j/+niQESCCQBEKX0HvvvStIFZGmIEqx8VXBgooUkfITK0VAEBGUroh0BOm9S++9hxBagJAyvz/2bu/2Wi4h/eb9et0rt7OzU+4u+9mZeeZ5chdrSL1qoRTKqxm/xMZJLly947AsLy/BW60K8tELFgOax9FxHL4YyY07T+zyP3gcy+ajd3TxtOb85Qje/mKxftygehF8M3nb5bPmz3mz+Oa7ScTFxfG/Pn3ZtGQ5X/Z5i6o5tPUwswAKIfB/sT2YDWZiYvE6dBIZrW27qVS2rFPhM5MQK9CUEMBHj6zEL6sSP0UykxLrask16ktoG5JyyvTPZZsZMNhi7p7FysxekbQsXmHvSKB+rfK6T08pIbOvDyG5A/XzC/7eQNe+Iw0+MYs+Y5kWPHPR9c28bY3c9H02Pz7eRp+t3l5Qo0QARfNm1dO+XXqVBSsP8uDhE46evsEfqw4x6OuVtHnjVy5cuQNootqjQxXiY/pC+4jm548d5/uBg6iTtxBgJYBZMpO1Qxvw1gQ1Lvw2fnv+o2IZ96LFQ8K3QSQn0dGW/bLOfJl6Akr8UoCMNNpLaTZsOWA4vnQ1jD+XbU6dxmRwtuw8bDi+c3YJy+eNYdPSH3Q3ZVFPYqhSoTivdO+k59u49T/WbNA2S+cu1pAShS3WhOu2n4m33h6N87H404pMfbs04/uU5Lf3y/HP8Cp8+1oJFkzqTd7c2ib6u/cf89m3q6ncbhzt3pzFJ9+s4s/Vh3kcpU2t+mbS1h1rVizksr6jp2+wbb8Wz8/Ly4uP+nfRz21buZq5P0w0rAFWKlsW7zy5ydy0gZ4vbMdubu1K2AZxdwUwuUd/RYsU1p2Qnzx1lsuX3Y/unpFQ4peMpKQVZVoY9SUH77/5osHyEGDI6F88+ok1OYh8+Jhb4UYjliem9boKZYsw5ZsBevqaDXv5YtjH9Hyls57261wra82Xu+rvl284zt7Dlq0SgMOpywA/H0oX9Kdy0ewUDslC4brNyV+zKTkDsjJ+SFtyZnc9PZc1iw/zf+hOi3olXOYD+NdKkJ+rX4LPP3iFN3u11dPm/jCBLctX2glg9c4vElLPsvXm/KIlxEUnzOtQWhDAHDkCaNRQ85UbFxfHjJnOXc1lZJT4JRNqtJc0FAvNz6alP7Bu8bd62pVrtzh/6UYqtirliIuLY/jYmbwzaDz7Dp5KtnoOHjGO0MqWKmzw5FK9SindR2dcXBwLFi6h/9u99fPWbatasQQVSuYF4El0LF3en8uare61PX/NpnbiWLVsAdb/1o+Br9XHL6vWJtvIVo8ex3D6gnt71rJmtuz9C8iWmbAzmxg1uLdhY/+4Dz7h7JGjdlagRbp0JFN2ba/jk9sRXF23Md76njYcUnLw2quWB5R/13vmvUqJXxKTGl5RMuqoz4wQgmqVStK8UVU9baVVnLmMyoXLNwgs1p7vJ//B7wvW8O4nE1Ks7snfvG+X1rK1ZXT06ecjOX78pH587cZt3QGBEIJpEz4nV6AfXl6aSr09fDE/L9ztdMTuSPSsyZ4tM97eXjx8pI20HBWzaff5eHqlUbpYiP5++4GLxMVJIi5sZcbEjykaqm3BePTwIV/1fYeHDx4YBNAna1YKtW2lX395+T9EP3C8n9GWhApgco7+qlWtpL935gg8o6PEL4lIbVdgnsDzVt5eJk3/2xDyKKNx8swlaj9rdAhd+Jm8yVZfzaqlqV+rPH5ZM/PrxEFULm/xwuITWAGfwAqEhRlvxuN/nG443r7HcnMvU7Iw877vTonC2jYBKeH/ftrA59//Y7DYjU/0zEgpWfTPYZd5alVyvdZnpmrZ/GT3zwzAxat32LL3PACx4fuZN22IHoT3yuXLXNmk+fW0FsA8DeqRJUTbKB776BGXV6x2WtfThkNKLgF8plABsmTRPoMbN8K4FX47nisyHkr8koDUFL2MPuqzplvHJroPyUtXw1iyOmOGYzl87BytunzKw0dRhvTxo99xcsXT4+3tzbK5o7l0cL4haLBPoGWP5e3bEYZr9h8w7gX8fvIfhuMajdoz6+suVCtniek3f8VBvpm+yW3RMxMbJzlz0fkNumDeHLRr5p71pV9WXzq1tIQwGj9rK9GmqBVB4hxvWjnqvnD0gO4FxiyAjauUp3BHS55r6zfz2IWbMFfhkFILb29vypQuqR8fOeI86G9GRYnfU5DSo73jZ2/Sa9BCXuz/O59/v5qw2w9SrO60gF/WLLzWraV+vG2n65FAeuHshWusWLOTh48ec/V6OC/2Gm5nfDL6894EB+VI1nYIIQxx+6yFDyBXLqMrMNtAqPsOnuLOPeNvsnS1lsz6ujPtm1v2wk2dv4vtBy4mqG3eXoJubSo5PNe4ZlHmfNsVv6y+bpf3SvsqeJumZA8cu8a4mZYN+4UCLV5Pjpmmdm0F8IVXu+rOr2VMDBcWL7OrQxe5iLuw8z8ezvuLqI3b9CC5kLqjv/LlLE7Ejxw94SJnxsQn/iwKR6TGaO+HX7fqUzT/Hb/GriNhbF7WhGz+WV1fmIEIyG4JZXPpavoPx3L3XiR1nuvP46gnlCxWkOzZ/Lh+0zjCCX0mL692fc5JCUmPreiZ6dSxLT+M/8npdZkz+5KzQA24b9won9nXh7EfteLE2TCOn9V8SV67Gb8bLmuEEIx4rwWNahbl77VHiYmNJW+u7LRvXpbKZezDJcVH4fyBvN+rPt/+om2bmTJ3J1FPYni+UWkOn7TEEBQxDwjmHuEEUDEgmIP3wqmXvzBbr16gw8fv8dsb7wNwa9de8rdoSvZQY9SLB6dOwOGTcPc+cUDctet4hxbiPy8vfXP8pkPHdIOarVcv2DnaBk0Abf2QPi3WoY0Oe+DIT4lfIkitac7gnMYYZmfPX+PvlVt5uVPzVGlPajBz3j/6e+t1qfTK6bNX9Ph31tETzGTK5MOMCR+n2AOOM+EDqFK5PFVr1mDfLsf+VYUQSCmxMcQkd7GGhJ3ZxJ37Fs8i5YrnwR1iY+OYtXgfG3adJWvmTLz4XHnGfd5WN6R5Gt7oWosd/11k615txDXjz73M+NO4d692jbLERBwiOLCCvQACJRvV5+RGzTnAjU1bdfHTR32xsXD3vqFM4een50mIACY15ctbpomPHPU88VPTngkkNdf33n65NlkyG59Xtu9O/fWDlOJx1BNOn9Ms04QQvNO7Q+o2KAnIl9f10/yIT3pRtWL8e9eSAlfCBxBOAF9PGK97fLHl8eModu854LCcG7cecD1ME4GsWTJRrLB9v2Nj44h8ZHRttn7nWUZNXs/WvRdYu+00bw1bTJt+v3Lg2NNvzPbyEnz3SWvDmqTt+ZoltL7GRBwyxAEEbQq0ZrcX9fwRh44gpdSF78GpE9qUpzV+WXkUYYmkkBADmKSe/rQe+R09dpI4q+lYT0CJXwJIbWvOAnly8MHbXQxptmtDGRnfTD66JZ6U0m59KT2SP28wZUraB4gFeL55LUMU9eTEHeEDKFGqFJWrV3Oa7+Qpxx5dLty1uDwrXyIPPt7GW8/N8Ac8+/p0qnecyKy/LMFzT56zD7lz8vwtug2cZ5ieTCzBgf7M+6Ebk7/oQO3Kz1C6aG4a1yxKl+crMm1kR0qG5jKEQjKHCzIL4EvPtiRLgOaB5smduzy6ZtOmEzahmPLlBiESHQ0+KQUwJHcuPbDtw4ePOHc+Yeuw6R017ekmqSV8ttacrZqfY9T3s/Xj/46cIS4uzunTeEbCy8uLapVKsWHrAQB27ztO4YLuTZ8lN+cvXWftxn20aFwtwW0qUbQgx04abzwF8+fix6/f091QJQWOBM4vh3vTa9YT7kWfKex06rNK9YZamTblHr5gscxt+GwXijUbazg/pHt33T/nqCkb6PXBNIoUKYJcPhCw+Bz19/cnMjISX98srD8RxLO9viBr1qefEi7eHN4c6jrPvfPLiIk4hE9gBV0AD94Lp1y1quxdr212f3jtBmT1RT6JhjMX7Ud++bQ9hs4iQliHVEoJypUtzc2b2ud7+PBxihUNTdH6U5OMf8dMh7hyCl2+TKhh/efq9XCXnvgzGjWrWm4a23YfScWWWFj17y4qNezLB0Mm8+KrwxLkeu1B5CO7fnh7ezF93EcE5czu8BrzvruEvmxxV/hsuX7d+YirSJEiDtP379+vv69Ro4bh3KNHj/jzzz/149jYWP74Q9s2ER5uGelMnz6dgwcPAhAZGcm4ceMYNWpUwjuQSAJC2wDGaPAVA4IpUCRUz5NHxpHvzn0if/wZjp02FuDjg3/16rrwWUeEaFihTIoLH9hafHrWup8SPzdIiVGfu1EQhBB202QLl8TvYimjUM8qtt+CxRvsLCOTi8dRTxyKWsTdB3Tp86V+HBUVnaDR2oSZW+ymrocM/oD6Lbq4LWKJIbHCJ6Xk1Cnnrsqc9f3hQ0tA3Dx5jCPjvXv38uSJca1v1y4t6sLt25bvNygoiKJFi/LZZ5/paaNGjWLnzpTz9uNIAGuVs3wnm36awakZvzu8NkubZ/XPJzVHe9Z4ssWnEr94SM6gs4kN+2P2sG/mwKHTTnJqJNUNMy3QsE4FfaP7/QePGDJ6RrLX+fWE+RSq2IWKDftw/pJx1DNx2l+G43Yt67pVpk9gBW48zMW4iVMN6XnzhvBe/75P1+B4sBa+jRs38t577/Hjjz/y4EH8a6g7d+7kxg2jX9VMmeIPM2UtiraGFVev2huv3LqlbRq/c+eOnhYYqIVSGjRoECVKWIyAFi5cGG/9SYmtAFYu7nqrhQjITpZ2LfEpUjhNjPasKV/O2uLTs/b6qTW/FCSpvLEUL1rQcPzfkTOcvXCNooU1v4SOxM4nsIL+z5qe8fLyIjbWcvNcvHIL0374INnqi4mJZezEeTx5EsPFyzcZ/d1spn6v1ffvpn188+MCQ/4Bb3VyVAxg/70M//JrQ2BRgL6vv4Kvr/ubtd0lnACCuWcQvri4OFq3bk1kpOabctmyZaxcudJlOZMmWWIrZsuWjejoaGJiNDdzQgiyZ3c8VWu9Jm07gjYLnTXZsmnOo61jz5k/l4CAAL777jvattV8jf7zzz921yc3AaFt9DXAEsUdT/UClOn/BoEVyiKs+v+0gpeUe/5KlyqOl5cXcXFxnDl7nsjIh/j7+8V/YQZAjfxckNrWnc4oWcwofrGxcfR6dxyRXoVdjvIyygjQ2vQ/OjrWRc6n58r1W3poH4C/VmwhKkq7IY+dYAwFkyd3oD4qNeNsuvLc+YvMmbfIrr5Xe3a1S3NGOAFuv8B+qjM2NpaoKIsLtVWrVvH4sVGMrQkLC2P+/Pn68Zo1a1i4cKHu6aVkyZL4+Tm+cVqLn+3Ib/Nm+/iMpUuX1ttoxtvb4n2mXr16+vuzZ886bXNyYh4BhmQNcyoYxyYanQIkVPiSO+pD1qxZdPGWUuoebTwBJX4pRFL64KxXq7zdVNN/B4/wUtc+3Aq/zZGjJ+jdbwDvDvjM7maWlOtGqcXLL1k29UspkzW47QWb0ElPnsQQYdq0HHbLuFYXkiun/j6+zzky8qFdmr+/H3lCcjnI7VjoEkKhHIF2aUIIfdRmxlpgbPnll1/0tbmaNWtSu3Ztvv3WEmqqdevWTq91Jn579uxh3jz7eHJr164FMLTPum3+/v76+8ePH9v1I6UICG2DEIISRZ1PfRb39koTU5zOMBi9HPGcqU8lfk5Ia6M+6xFESJG6vP3ma3Z5tm7fReFiValZ9znmLfiL6TPmMH3GHKflpVdeeL6eIbzROx/9wP541j0Ty8XL9i7UMmf2ZfOOQ5w5b1yrqlu/gdsPF+XLlebZFo0NaZGRD1mwesdTC50tjoQP4PBho2/UChUqOF2/Cw8P5/vvv9eP33nnHTZu3MjGjZqxlY+PD//73/+ctsGZ+C1YsMBRdk6f1r5P65Gpj49llcbX15e8ebUoF7GxsVy4kDpx8UATwFfSsZelcmUt4nfoiOdYjivxc0BSC9/Tjvoc3UyHff4BtWpWdZDbyMefjmDMV+O4cuWaW+UmNTfCIvhw6BRef/drfpy+2M4ZcmLw8vJi+viPdMOfR4+f8PIbo7h95348VyYcW0vMrFl8iYp6Qre+X9rlff9//RJU9ht9etqlDf7gAx5GuhcfLj7Onj5NzO07Ts9bbz8AuHTpEo8ePbLLd+DAARo3bqwbuuTPn5/OnTszYsQIPc+rr75KaGio07qcid/Jk46n2bJkycKTJ090EQQM5T948MCwHnj3buo6exjw+Y80bVDFLj1faGE6NmmWIu7KEounOrhW4pfMJIfwAWTOnJk/5v9CmTIlHZ63ZuSY7ylZrg6Nm3dg3IRp3LljuVEktwCO+HoW035bzp9LN/HZyOn8tXxL/Be5Qc6AbMybNoQc2bXpryvXbtlZXiYF2bIZN1DnCsrBbwvWcP+BUSTmz57KM88Y12Ljo1HDumTOksWQdv3qNdatWeN2GQfvhTt8TftzAY2r16REiRLs3bvX4bUBAcYR5Z07d1i0yLIOefDgQVq1akWVKlUMo8Rp06axZ88e1q1bB2jTkdbbDxzhyNozLi6OPXv2OMxfqlQpjh49qgtckSJFyJHDsp763Xff6XsACxYsSLly5VzWn9x4eXmxbPVWur7QRE/Lkyc3f69cgY9pNF0vf+E0KYLWI78jR44naJ9qekaJnw1pabozPmEKCszJ0r9+p2H92i7zmdm95wCfDRlF+coN+W7cFP0mlFwCGBcXx9JVxph7SemLtHjRAnw38i39eO6idUn+j5szRzbD8fWwCG7csc/XonmjBJUbTgAPs4ZQplxZu3MXzp13et3Be+HsDbvK2mOH2BfufLP5l73fBLQpwV9//dVhntatWxu2DAD6Hr41a9ZQs2ZNVq1aZTj/xhtvULhwYT766CM9rUePHhQtWtRpW8DxyG/Xrl1cueI4injHjh31dT+ASpUs4YzOnj3L6NGj9ePhw4eTOXNml/WnBFmzZqXdS5ZtKvXq1KRcPn8qBgQbrDOTQgST0s3ZM88UIHt27XcefjuC6zfsXcolFWlJWJX4WZGWpjvdFaR8eUNYvmQOfy+axTsDB9D55e40b9mSgoWcR7WOuHOXIcP+j2+/n5zg+hLCTzOXcfe+cQrPdiT1tHR4vr4++rt6PZyLV5I2zFHOAKP4RUfHEB4eYZfvq68nul2m9RpeqTL2RhCXLxpdnZlHc7uuX2LK0BG8UKI8r9dpxNj+AxyWH3Ld2L5r1+ynvEGbWrT1tmL20PLee+/p621eXl689NJL/Pzzz1y+fJny5cuzY8cO/Zr4Rn22bTCvK5rXC61p06YN1atXp3379gaBszamGTJkiN62qlWr8uqrr8Zbf0ph3osIcOrEUZYt/4f965YhpXQogu6Q3BafXl5elLWaQbL29BIXF8fFi5dZv3Erc+f/ZZg1SgxJ6a7vaVH7/JKJlBA+MxFeOanStA1VmrYxpIfdvMm61f+wcM5cdm23j3r+84zZfDjwbf0HmZR7AR89juKHKX/apXdqq42QboZFcO3mbUIL5SVHgL9dPncIv32XH6f/bRDYm2ERServM6eDtu3as58unTswf8FiPe27cVPo26cH+fKGuG6zjfGKI/Hbv3uP3ZO9lJLB3V/lxL4DetrRPfbTma0LFefF9180pFmPmqz55ptvmDPHaBDVpk0brly5wrFjmuGDl5cXBw4c4NChQ7z88st2ZZQrV85u9GjLnj179OlNHx8f6tSpA2hribZUqlSJuXPn0rZtWyIiNBEvXLgw3bt3B+D33383tHn8+PEGQ5jUplatWnpop0PHztHlZW0deNjnH/Lxh/31sEiAHhoJkl/gnBEdHc3Un39j5y6LM/GHVpbIX4z8hrnz/6JcmZL8s3YjwUGBjP9+NB3at0qN5iYpauRnIq1Md7orfO5YAuYOCaFLj1dYsHwpfd5+y+785ctX7aY4kmoEuHbjPjvXYx++0xl//yy89PoXlKjZk4Zt3qdMnV6cPHMpUXV8/MVUvp1k9O4RmMPxJuvEEvyMvVHR5ctXqVq5guGmGx0dze9znHsacfZdlShdyi7t+NGjPLIxejm2Z59B+ACKNKjD1qsX2Hr1Aku2bWZMt14IIQzrdgDPPWcfCPfRo0eGqUuADz/8kODgYMP2hUaNGrF+/XqHwgea2zJXU1kPHz6kR48e+nGrVq300dH9+/YGSj4+PvTu3ZsNGzYA2khh5syZ7N+/nzZt2hjK6tChg2G/X1ogMDCQxo0b26VP/1UTbHNUCMAwEkyt9cA33vmIjz8dYUgLDtYicEgpmfrzb1y5co11G7S1+vDbEbz86lv0eWNgokaBaSlskhI/E4lxM+asjMSW447wJMb03cvLi3cGDnAY+eGwA9PmpxXAuLg4RltFngDo1K4hrZ+tTd2W/flnvcXIIfLhY46eSFwolfDbxn++ri80oXhRx7HZXOHKGXTOnDkcXjNn3iJKlTQG092z50CC686RM6ddWlxcHPduG6cuZ4w2RkGo+mI7mr+nPdDsmvsHU7u+ztatW+3Katasmd3UJsCZM/ahhz799FMOHDjA+PHj9bTs2bPz3nvvOW3/uXPn2Lt3L9988w2HDtnPGnzyySccP65No/n7+xu2S4SE2I+SHz58aNj+MGrUKO7fv0+DBg1Yvny5nl6yZEkmTJjgtF2pycCBA+3SMvtgmFVJKyK4ZKlxTbdBvVrUrKFZrcbFxen7UWNiYsmTx/J9zZ2/iJr1WrJ5yw7c5Vb4bQYPHZMErU4a0s58QRohPuEyjxCTctO6GXO4FFeY/2ESKoC+vr74+PjYORA+8N9hWjSzN9YwtyMx06Anz1zm6AnjNE6Pzs/Stc+XPHpsrL9xvcq0blErwXXExcVx4LDRs0eT+pWBpF2/zJnD8ef830H7iBJPux5iTbTV9ySl5Nhey7SUf0AAI77/lq1XL7Bz9gLWTZjqqAgyZ87MjBkzHK6zONoXd/HiRd544w19O4qXlxdLlixx2U4fHx9dXMeOHcuNGzf0+tasWWMQqB9++IFixYrpxwMGDOD333/XLTorVqxo5x5t2rRpnDtnjInXs2dPJk6c6NSVWmrTunVrmjdvbjDYGTOkD2D/Px7MPf1/2RwiCUix6dAa1SqzySRgXTp3YPpP3+vfn5eXF22eb8HfJoFcOHcak3+aydz52szClSvXaPtCD36a9A1dXmrvsp6IO3dp1LQ95y8kbpYnOVAjvwSSFCNEV8REHHJLcMxPjtZPkK4YNXSYnfABzJ7zp8tpq8QIyZNoe28bfy7dxI0w42jmjVfb8MeMYWTK5P4zmHlEdvleTiJs9vUVKlEjyQ13MmXKRJ3a1d3KW6lSeafnzN/T4U2raFStBs/kDKJBlWq83rW7w/yhPhbDoIU/Gl1kteii+Q+9sWytU+Hr1KkT586do5ATw6fZs2fbpVWpUkWPpgDuTVFZe1YJCwtDCMHPP/+MEIJnn31WP9e2bVt69+5tuLZChQqsW7eOTz75hJkzZ7J161a6d+9uiM9nLXy+vr6sW7eOmTNnplnhA22q1nbz/n+HHQf5TW1e7GixE7h06YrhQan3GwO4FX6bZwppsyn58+Xl55++Y/bMyQQHaVPX0dHRvN73PcZNmOaynrHfTExTwgduiJ8QopMQ4k8hxAUhxCMhxAkhxBghRHarPM2EEL8LIc6Y8pwRQkwWQtjNawghGgshjgsh7gkhfhJC+FqdCxVCSNOrqYNrtwghNjxFf9MNCR1xuRLDnyZMYM6vM/XjlzpZooOfOn2We/dcbw5PqKDkCrKfKpw139758JghfZwKX3zhfLyE/U83tLBzC9enYd7sqYz/fhRly9qvz5kRQtCtywvxlvX9+J84Z5pyvHDuHLfCHJuVR0U9pkL2IFaNm8yssd8azj2OjGTR1On8MvL/DOl58uTh1q1bxMbGsnDhQvLly+ew7AULFjB37tx425pQChcuzKhRo+jb1xiVInfu3EybNs3hCLR+/fqMGTOGnj17ki1bNooVK8aKFSuoWLGiIV/NmjXZu3cvTZo0sSsjLRIYGGh4wNi0I206lW/XtqW+HLJt+26DM4wNG7eyddsuLl66Qs8encmXTzMk69C+Fds2LadMaYuh02dDRjHosy8dPjBduXKNKVNn2qWnNu6M/D4EYoHPgJbAZOAtYI0Q+h3oTSAYGGnKMwZoB+wQQui24kIIf2ABMA14AagCOFtQSLkolWkUd0eBjgjmHv6PbzL6owGMGjJMT2/WtAG7d1s8ezzbojE5nEztWZMQAcyXJ4hC+XPHm6/Ws+9w+Ni5ePM5onDhguTNY6zjaDI55c0VHETbNs8RFuZ8b1Wvnl2pUjn+z6hAfseC9PaA96nb0DKjcO3KVZb+9RcTv/3OLu/NU2fshK9s2bLs37+f4OBgh2u7Znbs2EGvXr30Y39/f2bNmqWPtnx8fKhQIXGj58qVK/P5558b0nx9fZk5c6ZdDD9XNG7cmP/++4+wsDAOHTrEiRMn2LFjB+XLOx9Zp0UaNbIsJ+zed5zHUfYzL6lNSO5cNLDaJ7xh0zb9fWyMxRvT0M+MkVMKFszPmlV/UK9OTT1t4qTpDPhwiF0da9dt1medKruYHUlp3BG/tlLKzlLK2VLKjVLKH4B3gVpAY1Oet6WUraSUM0x5fga6AUWAzlZllQEuSSm/lVL+C3wJOJpD/AeoLYRom7huZSzcFUEpJdOm/0avPu/y6uv9qVitCVOmWZ64qlSuQHh4hD794O/vx/df27vpeloiHz7m3gOj42ZH2xlOnb1C1z5fEm0zTeqO0AohGPr5h4a0Pm8M4Nr1xO3zcxURISwuG/WatCcszD70jpkvhn3sVj1f/98wPvrgHTJnNoYtevf1l6hXw9LvxQv/4N9Vq+2uzxkYyJlTRj+mjZs3Y/fu3U5HetYMGjTI4MIsMjKS/v3762kxMTGcP3/erb5Y07RpU/7++29DWuXKldmwYQOtWiXOLD5XrlyUL1+ekiVLpqn9Ye5SoEABfRvI46gn7D2QNiMm1K9rEbD9B7T7zLXrN3ls5Vf12vUbdtcF5szBkr9m0b5tSz3t519mM3PWfK5du8EXI7/hVvht9h84qJ93ZkCWGsQrflJKR/Myu01/C7ibx8RFoLhp6jMYeAVw9Iv4A9gHjBTp8VefTJhF0Pplza+z5vH+B0NY+McS/li0zDCF0bFDa4qEPsOB/zQ3VUIIZkwbR2io+1OF7o7+Phgymbv3jKb6wUEBrF30tV3eS1fD2LjtoF26O3Tv2tFwfOfOPf5v7Lh4r0uo4+ib169z9bJjTyQA9Rs3gqDCbhkh+fllZfiQjzh3cg8lS1i8omzassMwbbph7Rq8Y40ROcqXK81HQz7nrlWAVyEE02b/7jSUkDWXL19m27Ztdun37hmnyR1tQTATFBTkMN3a0rRp06Y8fvyY/fv363v6PBXradotO7X/17QWV9N6xmL3nv20bv8yxUvX5MEDy/9w3jyO969myZKF3379kU4vWsYpX4z6htbtX2bsNxP59PORTJtuiWy/YaO9RXJqkViDF/N43pULcLs8UsqbwOfAGuAWUBQYbX8p0pSvItAlkW30CKyF8PzJ/Xbnc+fOxQ/ffknzpg1ZtNhiKj5qxGe0fr5FvOXbikN8Anjm3FXm/bXeLj1PrkBuhTs2zLn/wD68D8CTJ08Y+81E3v7fIOZZbSg3kylTJooXMwYS/XPRMrt1h6eNkBCSNy9Fixd3er5EKctaoLvl58gRwHPPWpa1L1y4RKmSxSkS+gwAjx9H8cefSw3XHD5ynMEDjdNPz7ZoTP7MUbjDiBEjnjr0T7du3RwKmtnjSvbs2Zk5c2aacDeWFjBMfe5Pm06jK1uJ3779h+wEqluXjuTPn9fp9d7e3kyeMFY3grlxI4wTJ7XZiQULXVsLpyYJFj8hRAFgBLBWSunQK63JGOYHNOFbbH1OSjkBCAFKALWklA4XUqSUK4EtwAghhNvmgEKIfkKIPUKIPeHhSWd6/rQ4C2qalJQqbhzFzZs2hAPrJ/FK2/J8OcaydvRqjy68279PvOVZ38jdvanv3n/cYXqn9o34dOTPdum+vj7Uq2lxSmz9+Xwx8lu+GPkNM3+bT+9+77Nxk/2opVixUMNxxJ27XH7okyCxi42NZczwL+je4QWW/mXvHNvLy4u333e+1+0ZF9EMXGG9XSLUJHpt29hvSHdFOzfzX7lyhV9++SXefF9/bT86N5M7d25+/PFHxo4dy/bt2+3CH/n4+DB58mQKFkyYg++MjDnsEsDjqGgXOVOPfHlDdGMW6wfHCuXLMPiT9/lxfPx78/z8stKkSX279GzZtOWOtBgdPkHiZzJe+RuIAewDyml5fIC5aNOdXaWUdo+aUsoIKeVpKWV8ttSfoYlkL3fbKKWcKqWsLqWsHhyc+vPLKRU8Ni4uzmBR2bRBFZ5tUo0jx8+zZNVWrl3T5uzz5MnNN18Nj3cNxZVo+ARWIDY2lpnzVrNg8QZDmCJHuyaqVSpJjux+nLtg72Py/4b2IyS3fbw5KSW//Gp0vbXgD/unSEcWnpl8fe3SXPHHnLlM/mEcWzZsZOCbbxNx+7Zdng6dX6KAk5t6ocLGTcnuPiiYvxOAnL53iYk4xPuvNaJoaPxrdwC1a1Xj5W4vxp8RWL9+fbzhpLJmzcoHH3xgMHgpXbo0hQsXJlOmTISZLFMbNGjAc889x/fff09QUBDBwcG89dZbHDt2zKknGIXmlCEtOXa2pkf3TlSranGD9+3YL9ixZSWfffK+26N4RwZf0yZ/S62aVenUUZsWrVG9cpK0NylwW/yEEFmAJWhTlc9JKS87yOMFzASaAx2klIlbzDEhpdwMrAKGCiHS1TyKK9FLDjFcuno7m03m1EII+vZoTdvug3m208e8/u43er7Klcrj55c459LWN/W5K47z7qcT6TvgW6o3f0tf48ua1f5r2vvfSfq8bzTX9/Hx5rfJn9L7ZcfGEHFxcYZ4baCtaW7arPkovXjxMlu27mT7DuPkQ8lSpfBNoPht+Pdf/X1UVBSTZ/9mCA8EmtViz75ORsuJvKFZ32yGjPmF6OgYgoNysHT2KNq2rEOmTD6E5MrJoplfMOlr48iz9yut+HP6IO5f28e6FbMdxuGz5ujR+KNptG7dmnnz5hk8tWTJkoULFy7YfRf37t2jYsWKhIeHc+vWLSZNmkRxF1PDnoq1F5ujJy4w6Ze/XeRORYRg777/AGjzfAve7JdwZ+GNGmjT4XlMVtgFCuSjRfNGrF4+n+FDPmLxnzNZu+qPpGvzU+LWdKIQIhPwJ1ATaC6ldLZiOwVtja6TyZozKRgM7EHbTpHmcVfYEupE2pXvUSklX33/m378zuvtWfnvLrbusvdCcuxY/BZn1iJnvvmb3S+FE0Aw9/R/FICz568xfuoihnzYg1g3ffe1bFaTdi3rGtKsPztvb2/q1qnBv+s2G/K0atsNX19fhxv2Aeo1dj+0kO482iZyw7xxE2n6Ygf8smUz5Lse5Xht0mwwsnPrNj4dOJAKlSrx1fhxFMji2rR98Kfvs2TpCh4+iuL4qUv8uXQTXTs2pWD+3Pw++TOioqIRAnx9M/HOxxZDnjd7teWrYf04ffYK1Zpp/xavvnrSaegi0ALVmvH29nY4CvTz89MdSAMEBwc7dD5tZvXq1TRo0MBlHz2ZM2fO0LJlS0PalBlLead3h9RpkAvq1rG4wLt4yblxlyuqVK7A6C8H06FdSxYvWUX9ejX1qfGQkFwOPUmlJu5scvcCZgPNgPZSSofO3IQQ3wJ9gNeklIuTqoFSyn1owvsZkDj3/ylAck5vxud0e8ve8xw5pU2hZfb1oUllf35bYL+pHLQf9iUXP25HwmfLtWs37KYgwyM0Adiw5YDLtpqxjZPniI8/6O8w3ZnwAVSrae/H0hrbER1As5dsrEZvhbN+kf0T+vF99gZFACduXmNv2FXe7teP0ydO8teChYy22lvpjGdy3uO9NyzTloOGT+b4npWEndlE2JlN3Lu8nbuXthN2ZhM3rp7X89U1rZHWfPZtPW3LFtdBgq1Hfs6mP2fNmqW/Dw4OJqcDv6PWOPIZqtC4fv06zZo1s4tXePHKzTS5369Wjar6/tBDh4/F6/jCGe/9ry+FCxfivf/1NcxspEXcmfb8EXgJ+AaIFELUtnoVBBBCDAIGAjOAUzZ5ijkv2m2GoG2ir5wEZSU5iRU9d65zJ9rElLk79fedW1Vg7fYzLmfijhx1bHXmSvisj8dPX2AwgwbInyeYe/cf8udS5+3NGWCJWu7vYHrUlvr1ajHMZi9ffPj5OxZVW8Gz5pkS9tN1x/dahC4uLo45309g+ypLhPWyNSwuzyLv32fNgj8Iu3JVT/t12jSO3zRuVbDGPOp/uVMzPe3O/ccsXHXYYf6HjyzTjrH3TnNg21JiYy2jbEeOqvVy79xh/37Hwm3tSsxMo0aNOHz4sMsy//nnH9q3d+3P0ZMZNGiQQ/+pAF+Nn8ePk38h3MZ5eWoSEJCdEsU1y2kpJRcu2q1qZTjcET/zosxgYLvNq49Nntcd5LHf8p9ApJTHgd/izZjCJLcxizvCt+/oFXb+p01p+Xh70adzDXb959qH3qOI0y7PO8MsHttsRhm+vr706NKCP5ZuJPKh8xu+l5WRTe5cOQ3nnH2OH3/Ynw1r/6Jrj1fsrAsdsW/3bv29o1GeLVGPHzOsZ2+7dGvH0pM+G8qc7y2RDkpUqkhwXovHEm9vH+ZPmIwtzkZYZuGb/9d6aj9rDDUV9cTxVoTbdy1rek+iYxn0tdEbv6MwOmZWrFjh1NDitddeM6yR1q1bN15n1r/++istWsS/TcZTiY6OtvPtac13kxby8acjePPtj5zmSQ2sozbcdOHQIaMQ75qflDLUjTyNk6IxUsrzgEMzRCnlazixME0Nkkr0nK39ORK+q7vW2aVNWXpHf9+2aRkK5MnBpet37PJZ8/NvK2jzbG0yBVn8Jzob9W29esEuxIqtU+HcuYPx98vKr3ONHkkyZfImOtoiAPceWPajtW5RG3cpWr0RY6s3ovdbb/LWa69z+oTzdct/Vqyg5Xv2sQudMXXYSI7sst+xExOofR57N25m1Zz5enr5WjVo+uILTBg0WE+LvHePcBsPGEWKFSNP3ryANn305MkTTpw8Qx6/2wQFBjDqu98ZO2G+4ZpM3oKOz5bDlvuRUZw4Z/Ej8cYQ++0YH37oeIR85coVhg8f7vAcaCGHBgwYwJ9//kn58uVp1aoVXl5eDtcP/fz8OHbsGM8884zT8hRa1PrHj7WHwGzZsvHgwQOH+S45cJxgHdkhpYm0CmKbNUsWFzkzBiqkUSIICG0Tf6aEkMM+fpejOoo1Mx7Pnj2bddtf0Y9H/rCAYmXLkiNoMTfDTzmtbsPWA6zZG0WnTpZ6rXfhFMph2XrQupD9lGCrFs+yfo0lXMuVK9fo/MYPdp7rO3ToyMKFWoBXf39/Ik0BWsuXL0/t595x2j5bzG0rVKceO7dtp0yZMty86diN2cljxykb402RIkUcnrfm6NGjrJ473+G58e9+QI1CxZn/jyXQZ7t27fi///s/qlWrpo+kmjRpwoBXXuWPycboCpcuXGDi6P+jYcOGXLx4kS+//JLr168DWsSFP/6wWL0FBQXRunVr3njjDYfBWS9dukRc3Hi7dGuef/55u7QtW7bQqVMnbtzQhNnHx8ewyb1q1ap61IdBgwYZrnVkPbp48WIlfG6QJ08ePZq7M+ED+OgD9/8HUoLLVtP2hQrmT8WWpAwqpFECSXLhSwTHjh2jXr16vPKKRfi6dOlC2bJlAejXrx+1atVyGfZlwIABLv8xXfH666+TxebJcPv27YbjbNmyGSwBc+e2OKG2DnWTUIKCglyOZACWLtU8o0gp2b59O5s2bTJM+z18+JB+/fpRrpz9KAugevXqujHHw4eWp+H27dvzf//3f7owFC1alDlz5lC3bl06depkKCMmJoavv/6atm3b8s477+jCBxiEr0WLFpw7d45Zs2Y5jUpeqFAhvvrqKwICnO8fXLVqlT7NKqVk0qRJNGnSRBc+b29vOx+bX3zxhdPyevfuTY8ePfD19eX555/n6NGjaqrTTTJnzhzvQ0KHdq148YXUv5eYefLkCTdvalOdXl5e+qb3jIwSvwSQ2sL38OFDxo4dS5UqVQw+GgsXLsyPP/6oH3/wwQe88MILuo9GRzfNy5cv8+WXmlPrzZs3M2/ePDsfj87w8vLSp3Wc8eDBA2bOtDjVthY/ayFIDPH5i5w2bRoXL16ke/fu1K1bl0aNGhmCqi5YsIBp04zxx6pWraq/tzbkMD9QAJw6dcpg+v/jjz/qHjymTJmS4FFR+fLlmTdvnktRM/Pxxx9z5coVJkyYwFtv2U/rPv/884SGhtKrVy8aN27MO++8o4/ycuXKxZo1a/jpp59o2bIllStXZtGiRbRp4/z3nCtXLmbNmkVUVBTLly+nTJkyCeqbp+PKyXiO7P589ME73I64w/nzl+z2UKYGV6/e0B8Q8+YNwccn408KZvweJhGpLXz379+ndu3aBpP1TJky0aNHD0aNGkVwcLCeHhcXZxDDIUOGsGbNGv75x7j9Ydy4cZQpU4bXXtOWUnPlysX69evjDR3j6ObriL179+rvixQpwm6TMcp///3n7BK3KFOmjNO9agCHDx+msI3XlZkzZ/Luu+8C9o6ca9SoQalSpdi3T4uWbu2eq0ABi1/2GzduGETf2lIyODiYRYsW0aRJEzvH0HXr1qVly5bcv3+fJUuWULhwYbp160b37t0TtCE/W7Zs9O+vbf+oU6cOH3zwge51BbQHGusHDtBE/a+//tKFeeXKlW7Xp0gcUkpOnHDuxzM6JoZ6jSz3k9CiRVm5aQP+2eLf/pNcWK8/Fizgnoeh9I4a+blBagsfaDdva+GrXLkye/fuZfr06Qb/gQD//vuvvqk5V65c/O9//zOMbMxERUUZRkS3bt3Sb9LOePjwIYsXL05w+60tNZ1FFweIiIhg8uTJzJkzx6m4Zc6cmZIlSyao/mPHjun9st2/Nm3aNCIiLGbngYGWNU/rzeFBQUHUr2/xX7hu3Tq9zRs3buT8+fNMnTqVHDmMbvU+/PBDhgwZwtixYzl+/DirV6+mV69eCfZEY02PHj04f/48a9asYeDAgeTKlcsuz5tvvsmWLVvUOl0Kc/HiRcPvyZaHj4yOyM+fPcvhg6kb6eGyVQSYggUy/nofqJFfvKQF4Vu1apXBIKFp06asXLnS6c3T2oHxK6+8QubMmR2KH0Dz5s31EQ9o1oGTJk2yM4AwM27cON2Dv7v4+voapvaspxJt6dOnD4sWLQK0kdaAAQMc5qtSpQrHjrkKKmLk0aNHLFiwgN69exsEzN/fnzJlyhjWBM2bfW/cuMHPP1uccVepUgUhhP75bt68mfHjxzNw4EBdqL28vOymjJIrwoGfnx/NmzenefPmjBkzhs2bN3Ps2DGyZs1KgwYNEvyAoEganO2pdEWpsqk7rWxt7FLQA4xdQI38XJLawnf37l3eeustWrVqpRteBAUFMX36dKfCd/v2bf6yikzw+uuvA8apPOubsyN/jKtWrbJLMzN16lSH6fEJ2m0rZ9HO8j558kQXPoCJEyc6LdMdt1peXl76uibAjBkzAM1QxTxSioyM5MyZM4bR3o4dOzh79izNmzfXDUby58/Piy++aBhh7dy5k6FDhxpGqHFxcQYPNFWqVLFzcZUc+Pr60qxZM/r370/v3r2V8KUiiRG/sBv2wWJTksuXrcRPTXt6NqkpfBEREYwYMYIiRYowZcoUPb1gwYJs2bKFUBchdObOnavffKtXr6576Lde57IeiQQHB9tZPW7YsIGRI0faGbXcvn1bj/KdNWtWQzl///03f//9N2PHjmX16tWMHDlSPxcXF2eYsnVmZWltBQlw/vx5p8YAHTt2xNvb2+E563pr166ti/3WrVs5efIkDx484O5dS7irvHnzGjaJjx49mmLFinH4sOZtxcvLi2nTppElSxYqV66sP3g8fPjQUI4ttWrVYtGiRfpIUuEZ3LqVsA3iDRvUwTdzZsITeF1ScuWKxQjNU6Y91X+lA1JL+G7cuMEnn3xC4cKFGTZsmGHdoF27duzcuTNeqzvrKU/zqA8gPNyycda8304IQf369XnhBUsEcTNDhgyhf//+nDt3joULF3L8+HHuWEUQz5Url8EY5NGjR7Rr146GDRsyZswYPv/8c/1cqVKlDAYAzvowebLRS0pcXByXLzt2sxQSEuJwb5s1efLkoU6dOrRu3VpP+/XXX5kyZYouqiVKlCAwMJBXXnmFKlWq2JXh6+vLr7/+qtcVEhLC6NGO4i9rWzhOnTrFjBkzmDdvHlu3bnX5oKLImCR0S8gzhQrQoHJVqhQvycnjjuNhukMw7llrOyI6xvKQmTlz4tei0xNK/GxIDeGLjY3lq6++okiRInz11VcGg5OiRYsyf/58Fi9eTP78rp/ITp8+bXCk261bNwDmzJnDm2/aB8Xo3LkzISEhDsUPYPr06RQtWpTOnTtTvXp1wyjs8uXLBsMRsxXh559/zoYNGwzllC1bVh+NFihQwM4gZMOGDeTJk8ehc2bzSNMREydOdLqZ3c/Pj1mzZuHv72+Y5t23b5/ByOfVV7XQLVmyZGH16tWULl1aP5c/f342bdpEjx49DGUPGDCApk2bYkvRokUpXrw4vXr1okuXLvGOTBUZk/bt2+sW1O7w+xzLjEevl7okaVvcjRyTM4dlTf5uIp1apzeU+FmRGsJ37tw5GjduzCeffGLwqlG2bFl+++03Tpw4QefOneMNPgtaiBnzGlWjRo3ImTMnly5d4tVXX7Wz4PT39+eHH34AtHUp6zUvR0RGRvLkyRN9rU1KyenTFh+hM2fOREppN8X3xhtvGNbJHDlSHjRokFOPLa7E75lnnmHTpk34+9sH+5gwYQLPPvssT548MaxhVq1a1bA94Ouvv9ZHl7lz52bz5s2MGTOGcePG8d9//1GrVi27sr28vJg3b55hs36LFi349ttv7fIqPA8hhL6tJqFcvuTaL29iiIk4FK8I5rAWv7uJH0GmJ5S1p4nkFL4HDx6wZcsWtm7dyo0b2mbSbNmycf/+febNm6dPQwJUqlSJoUOH0qFDhwSvFR08aIkd3K5dO0Bb33O0ZaBOnTr6FgkhBJ06dbLb+G1NoUKFKFeuHIMHD9YNOKxHgkePHmX//v2GbQxFixZl/PjxREVF6fvyTp8+za5du6hZsyaRkZG8+eab7Nq1y2m9M2fOpGDBglSpUsWhOX/BggXp06cP48aNM6SPHTuWnj17cvHiRcPnW7FiRcNDxt27dzly5IhuEJQrVy4++eQTp+0xkzt3blatWsXmzZu5fv06L7zwgluOtxWeQWhoqJ07OV9fH1bN/4rPR09n227nwYVjY2PjnTUwx9dMCGYBdOSXOCDA4g3qrpvOLtI7SvxIeuF7/Pgx27dvZ926daxfv56dO3ca/gkc4e3tzdChQ/nss88S7V3BWiyHDRvG+vXrKV26NFmzZjW46QI4dOiQ4Z8svrWpMmXK4OXlRbVq1fQ027h627ZtM+wp69y5M76+vvj6+tK5c2fmzp0LaG61li9fztixY/n9999d1rtx40Y2btyIj48PAwcO5IsvvtBdq61du5br16/z3HPP6eJnFtkrV65w6NAhSpUqhZ+fn95/81SwmTp16jicwnQHIQQNGzZM1LWKjE3OnDlp3Lgxa9dqPnDrVnmG6ZNGkD9vMF9/8Sb1nnc+MoyLiUnWKfOYiEN2AuiJIz+Pn/ZMCuGLi4tj+/btjBo1imbNmpEzZ06aNm3KyJEj2bp1a7zCV7JkSbZt28bQoUOfyq2Q9drdgwcPWLZsGd98841B+MxThDdu3GDIkCFEREQgpWTZsmUuy37y5AknTpwwGNFYb7fw9fWlWLFiDBtmCeJqvf44ZMgQfep2xYoV7N69284fqCtiYmIYO3YsVatWZdu2bcyaNYsWLVrQo0cPPv74Yz1fcHAw77//PmfPnqVKlSr4+fk53SvYtWtXVqxYoUZsimTBdi09f15ttFa+TBHatHbu3zZTMu0LtcZ2KjSnB4qfR4/8nlb4Lly4wIwZM5gxYwYXL150mbdixYo0adKEUqVK4e3tzYMHD4iJiaF69eo0aNAgSW7ALVq04L333rObAjTj5eVF165dmT59OgBjxoxh4sSJfP311/EK0YYNGwzGIACtWrXS9+U1atTIzn2a9TRlmTJl6Ny5M/Pna1EURo4cSVBQkNP6cuTIwRdffMHhw4fZtWuXPqVrduptjXlLAmhrpd9//73h/IgRIyhZsiRTp04lKiqKChUq0Lt3b6eOpBWKpKB9+/a8844WuWHXwctERUWTObP2f96hXSuWLf/H7poGTRqnYAsto0BPHPl5tPglhqioKP7++29WrlypG3k4olSpUjRt2pSmTZvSqFEjg2Pn5EIIwQ8//ED//v05fvw4jx49YtWqVWzcuBE/Pz+GDRtGw4YNmTNnjr7udf/+fYeWoKC5ULtx4wbXrl2zO9exY0fDWmJISIhhKwTYO6Du3r27Ln6bN29m7Nix+rEtd+/e5aOPPmLEiBFMnjyZn3/+mQ8//NCwfucI60gXZry8vOjZsyc9e/Z0ea1CkZQUKFCAQoUKcenSJWJi47h8NYxiRTSL7QrlHW/3+XjI5w7Tk5OYiEMGD0yeYu2pxM8Bly9fJioqiqJFiyKE4NGjRxw4cIC5c+cye/Zsbt++Te3atQ3CFxwcTNu2bWnWrBlNmjQx7IFLaYoXL657bnnppZfszg8aNCjesEA1a9ZkwYIF/PTTT4wZM0ZPb9GiBe+++y5Xr17ljTfe0NNnz55tuD5Xrlx07NjRkDZnzhz9fYkSJXj55Zfp27evw/rNQUA//fRTLl68yKRJk2jZsiWDBw9m7ty5hs8+JCSE0NBQ+vfv71D8FIrUokiRIrp/2POXruvi52h05ePjQ6HChXG8szV5UdOeHoiUklWrVvHLL79w9uxZIiMj9Q3ZuXLlIjg4mFOnThEXF2e4bu/evQQHB1O9enV69+5Nu3btks2HY1IzZMgQWrZsyaxZs5g0aZLDPGvXriV79uwMGzaMUqVKcfbsWWrXrk3Lli0RQtCoUSOXdXzzzTd2i/Znz57V3+/atcsQicKavHnzkjdvXj180OTJk3nnnXcoV64cs2fP5quvvuLixYuULFnSoQWoQpFWsP593n9gsTLes9c+ssmATwYRFBzM5VSI5K6mPT0IKSUrV65k+PDhTk3tb9265dBVUWhoKK+99hqvvvqqXeic9ICXlxe1atUiIiLCofjVrVtXD4SbOXNmfSO4NdbOsB3haH/cyJEjadeune4Y23rLQa5cufTPOiAggO+++85ghbl7927dLVrBggUNvkoVirRIbGyswbNRZl/Luv7uPUb/ny9170b/Dwa6XfbBe+GJ2u7gDOuR3x0PET+Ps/aUUrJ2416ad/yI559/3uUeMzNCCEqVKkXPnj1Zu3YtZ86cYejQoelS+Kxp0qSJwUG0t7c3b731FqtXr4732qJFizo99/HHH9sZx4Dm/mvt2rXUqlVLHyVnz56dAQMGGNb+Tp48abf9IL2MqhUKMz/88ANHjhwBwNtLULZ0YSLuPgDg+MnThrwNmzZ1y5FFQnDXuwuokV+G58z5q7z7yQS27DxsSM+cOTP9+vWjW7duZM6cmaJFi5IjRw5OnjxJZGQkpUuXxs/PL5VanXxkzpyZjRs3cvToUe7fv0/x4sXdnkbs1q2bYVO9mYMHD+rOtB1Rv359duzYgZSS8PBwcuTIQaZMmYiOjiZPnjy6hxpr/P39ee6559zvmEKRBvj777/197FxkkoN+yKlJFMmH6KjjdufBg/8gDYvdOBI5J0UbqVG1qxZ9E35UVFPePz4sb6fNqPiEeIXFxfHTzOX8cXYmTx6bNmY7evrS79+/fjkk08cGqiUKlUqJZuZKgghnEZZcMXHH39McHAwEydO5MGDB7Ro0YJ+/fq5FD7beq2FNlOmTKxevZrRo0ezatUq/P39KVmyJCEhIbz99tsut0UoFGmREiVKsHnzZv3YbKRlK3ygRV0ZM2w47T5+P6WaZ0AIQc4cAdwK10KP3b13X4lfeify4WNeeXM06zZb5ti9vQTd2lZmzMQlau0okXh5edG3b1+n1pqJoVKlSk63PigU6Y3nn3/eEGUlPtb9849B/LZevZCoeiPu3CUwZ474M9oQGJhTF7/w8AjyhCT/9qzUJEOv+cXFxdGlz5cG4StVJBd//tiD4f9rroRPoVAkG+3ataNu3bqGtF7dnqNpg8p2eStVrcpHnzvf4xefEMbExDBy9HccPHiUwsWq0rJ1FzZus7codUWeEMtMzJWr9nt7MxoZeuR39vw1HkRaLAr7danJ+73q45tJhZpRKBTJS6ZMmVizZg1fDmzN6QvhNGrcmBaNqlG6Ti89T+7cudi0fx/+2bIBmhVnQpFSMviDD5k7cxa//DqX2NhYNm/dyfade1g2ZxR1ari3rFGyZDG2bNMMAA/8d5gWzVxvZ3KGI9+haZEMLX7Wwvdh74a82c3e/F6hUCiSCz8/P/q8VAOA3MUa2kVYadGsoS58CeH0oSPMWfgXuXLlYtnivzlrCi9246YlXFdMTCyfjvyZDX9/76wYA9WrVuaXXzXn83sd7EN0h4RYmKY2GXra08zA1+or4VMoFKmOt7c3L7a1RALZvGUnx484D2/kiLu3b/N591eZ8+tM9u3Zw9nTp8kdEgJAty4d2brR4qR+/8HT+vaK+KhWrZL+fvvOvfE65LclPQkfeID4vfdqPd5+uU78GRUKhSIFeLffC7r3o0uXr9CtfQfCnARzdsQfk6by4O5dAG5cuw7AgE8H8d7/+jFpwv9RuVJ5ypQpqec/dPSsw3JsKVO6BHnyaEYut26Fs2HTNrfbZEt6EMIMLX4hQf78r0ddh+eu7lqXwq1RKBQKqFy+OBPHjSFLFs1xQ/itW4wd8aVb18bFxbFpiWVkV69RQ2YunE/zli0Z/eVnepixWjWq6nl6v/s1X37zG3+v3Mrm7QdZvmYHU2cuY82GPSxZtY37Dx4SE3EIb29vOnVsq183f8Fit/uUHsTOFuEsKkFGoELJvHLxZHtP/mbha/DpnpRukkKh8DDO/KvFm8xdzDLd6RNYgVX/rOfFzq/paUv+XYNXiVD92NbCs17+wpzYf4AP2mvO6nMGBrLv1Ak9BmgwFs8s/x08QoMm7ezWGAF8vL2JiY2lVtXS7Nx3nIIF87Nzy0py5szBvv0HadCkHQDZsvlz7uQe/PyyuuyfM+FzZvTinzN0r5SyustCU4AMLX7Vq1eXe/YogVMoFGmT9u3bs2TJEkDzh7tt2za8vIwTcp/t/BeAuJhYlg0czJFd2j2t+Usd+WXaz4a81gK4ZOkq3n3/E8LC7xjylC5dguPHT5E5sy9RUZrTj6GDP2DQR/9DSkmVGs04dVqbKp01YyIvvuA67qmrUZ8jAUwr4pehpz0VCoUiLfPdd9/pU5U7d+7kt99+s8szulYzALb88psufF5eXrTq0d1l2e3atuTY4R3M+/0n+vZ+hdatmlOjemVeaNeKHi+/RNEiFt/EEydN58GDSIQQdO7UTk+Pb+ozPU53mlEjP4VCoUhFBg8ezOjRowHIkycPJ06cIEcOo4eWS5cuUbhIKDJWC632yofv0/VdLUq8bXQH69GfK2JiYqhUrQnnL2jxBn+ZNo4uL7XnzNnzVKzaGND2Kl69cNDp1Kc74mc7+lMjP4VCoVDw6aef6r6Fb9y4wY8//miXZ8WKFbrwlahUkZfeefOp6/Xx8aFr5xf04/0HNCErVjSUbNn8AYiOjuaETQSKjIISP4VCoUhFsmXLxogRI/Tj5cuX2+WxjnZSpUE9Q6BoW68w4QTgLpUqltXfHzCJ34+Tf+HBg0g9PVdwxnQqn6E9vCgUCkV6oEWLFvr706ftR1rZrLzA5Hxib8GZWKpXq6y/37JtF01adGTXbkug6pc6taNQIfuIN+D+el9adXemRn4KhUKRyliv8d27Z79mV758ef39wYMHaV2ouOF8Ykd/+fPnpXataoAW089a+OrUrs7470a5VU56RImfQqFQpDJXrlzR3+fLl8/ufOnSpfX3Z89q2xBsBTCx/N+ozylbthQ9X+6sp73aowuL/5hJQED2JKkjLVqFqmlPhUKhSGXOnTunvw8NDbU7HxlpWYOzngJtXag4yy9p06QH74UbLD/DCXDL8rNG9Srs2LyC7Tv2kCdPblo0b0yVyuVdXpMWxSyhKPFTKBSKVMZa/IoUKWJ3/tAhi9iUKFHCcM5aABOLt7c39evVon695AsAkNbW/tS0p0KhUKQyt27d0t/nzZvX7vzevXv195UrV7Y772wKNCGWn56GEj+FQqFIZXLmzKm/P3DggN35m1ZRHzJlyuSwDCWACUOJn0KhUKQyTZo00d+vWLGC7783BqCtX7++/n7y5MmGaVBrCuUIdJgeTkCSieDTrPelpbVCJX4KhUKRylSsWJGuXbvqxwMHDmT27Nn6cZcuXciTJw8A4eHh1K9fnyNHjjgsy5kAghoFWqPET6FQKNIAv/zyi2GE16tXL9at08KvZcuWjXnz5pE9u7b14N69ewwdOtRpWUoA40eJn0KhUKQBsmbNypIlSyhXrhygOZ5++eWXuX37NgCNGzc2uD5btGgRS5cuTVRdTyOAPoEVEm21qaw9FQqFQmFHYGAgq1evJiQkBIDr168zapTFy0qDBg1o2NASFLd9+/a88cYbDoPWxsfTjgATKmRpSfjADfETQnQSQvwphLgghHgkhDghhBgjhMhulSe7EOIbIcQGIcQ9IYQUQjR2Ul5jIcRxU76fhBC+VudCTddKIURTB9duEUJsSFRPFQqFIh1QoEABJk6cqB9PnDjRsL43efJkPQqElJKpU6fy1VdfpXg7wX1BS2vCB+6N/D4EYoHPgJbAZOAtYI0Qwnx9MPA6EAOscVaQEMIfWABMA14AqgDvOcmecZ3KKRQKhQs6depE3bp1AXjy5AlNmjRh48aNAJQtW5Z9+/ZRsmRJPf/gwYPtRn8H74Xb+fy0JSnW/+ITtrQofOCe+LWVUnaWUs6WUm6UUv4AvAvUAhqb8lyQUgZJKZujiaMzygCXpJTfSin/Bb4EGjrI9w9QWwjR1t2OKBQKRUZBCMHUqVPx8/MDICwsjObNmzNhwgSklISEhPD8888brrl+/brDslJTANOq8IEb4ielDHOQvNv0t4Apj7vh4C8CxU1Tn8HAK8BJB/n+APYBI4UQws2yFQqFIsNQrlw5Vq1apa//xcTE8O677zJgwAAAzp8/b8h/8eJFp2WllABai11aFj5IvMFLI9PfYwm5SEp5E/gcbWr0FlAUGO0oqylfRaBLItuoUCgU6ZoGDRqwZ88eatSooaeNGzeOrVu3Gpxdg2vxg5QRQHg6a9CUJMHiJ4QoAIwA1kop9yT0einlBCAEKAHUklI6/EaklCuBLcAIIYTbDriFEP2EEHuEEHvCwhwNWhUKhSL9UKhQITZt2mQIePv333/z6NEjQ774xA9STgDTAwkSPyFENuBvNMOW1xJbqZQyQkp5WkoZF0/Wz9BEslcCyp4qpawupayeO3fuxDZRoVAo0gxZsmShf//++vG///5LlixZDHmsI0O4QgmghtviJ4TIAixBm6p8Tkp5OdlaZUJKuRlYBQwVQmRO7voUCoUirdKoUSO8vLRb9v79+3VjGDNLlizhwYMHbpUVnwB6Am6JnxAiE/AnUBN4XkqZkt5JBwMFgTdTsE6FQqFIU+TIkUNf+5NSsn//fsP5K1eu8MknnxjStl69kKi6PGH0584mdy9gNtAMaC+l3JHsrbJCSrkPTXg/A/xTsm6FQqFIS7Rp00Z/f+nSJbvzkyZN4sIFTfDMIY6cCaCnT3+6M/L7EXgJ+AaIFELUtnoVNGcSQrQSQnQCGpiSGpm8w7RKgnYOQdtIXzkJylIoFIp0ybvvvusw2K0ZKSW///67XboSQHvcET+zeA0Gttu8+ljlmwwsBMyuxoebjl1tencLKeVx4LenLUehUCjSMwEBAfG6Mps1axaOtl4/jQBmRBEU7u9PT39Ur15d7tmT4N0YCoVCkWaJi4ujXr167NjhfAVq586d1KxZ05C2/NJpp/krBgTHW28w99xvpAv8c4bulVJWT5LCngK3988pFAqFIvXx8vJi/Pjx1KpVy+EID7TRn634mdcA3eXS3QjDcTgBSSaAaQEV0kihUCjSGTVq1OD11193en7u3Lk8efLkqepwFBA3I01/KvFTKBSKdMjo0aMJCHAsRrdv32bFihVPXUdGFkAlfgqFQpEOCQkJYejQoU7Pz5o1K0nqcSSAGQElfgqFQpFOeeONN8iZM6fDc8uWLSM8PGk8udgKYEYY/WVo8cvIlqwKhUKRLVs2+vXr5/BcdHQ0f//9d5LVldEEMEOL382bN1O7CQqFQpGs9O/fH19fX4fntm7dmqR1ZSQBzNDid/36daKjo1O7GQqFQpFsFCpUiOnTpzs8t23btqSvL4OsAWZo8YuJiWHMmDGMGTOGe/cyzv4UhUKhsOaVV15h1qxZlCxZkiZNmujpx48fZ+7cuQleAlq9ejWDBw/mxIkTDs9bC2B6Hf1laA8vQgi9c0OHDuWLL75IzeYoFApFitC1a1fmz5+vH9eoUYNp06ZRqVKleK8NCwujYMGC+j7B7777jvfffx8hhF1e643w7m6ATyseXjL0yM8aFdhWoVB4CsOHDydHjhz68e7du6lcuTIlS5ZkxowZLq/19/c3bJAfOHAgU6ZMcZg3PY8APWbk9/jxYzJnVvFwFQqFZ3DmzBlGjBjB3Llz7WwftmzZQr169Zxe+8ILL7B48WL9OEuWLJw7d85pRImEjADVyC+F8PPz4969e0r4FAqFR1GsWDFmzpzJwYMHee655wznevbsyfnz551eO2PGDEOk+MePHzNw4ECn+dOjEUyGFr/AwEBu3bpF9uzZU7spCoVCkSqULl2aVatWcfjwYX0QcPbsWerXr8+xY8ccXpMzZ06+/vprQ9rcuXP5559/nNZjFsD0Mv2ZocWvaNGiZM2aNbWboVAoFKlOuXLlWLhwob4n8MqVKzRp0sTpfui33nrLbsTYtm1brl275rQOawFM6yKYocVPoVAoFBbatm3LypUr8ff3B+DGjRtOpzOFEHbGMU+ePKFHjx5ub50wi2BaFEIlfgqFQuFBNG3alIULF+rHCxcudBr+KF++fPz111+GtH///Zfly5cnuN60JoJK/BQKhcLDaNWqFc888wygjeaOHj3qNG+HDh2oXt1onDl69OhkbV9KoMRPoVAoPBBrQVuzZo3LvEWLFjUc79u3j9jY2GRpV0qhxE+hUCg8kAYNGujvhw8fzrJly5zmLViwoOE4KiqKc+fOER4ezuXLl9OlD2UlfgqFQuGB9O3bl2LFigHw8OFD2rdvz+TJkx3mtRU/0KZDc+XKRaFChShQoIBhHTE9oMRPoVAoPBB/f3+WL19OaGgoAHFxcbz99tsMGjSIuLg4Q15H4nfkyBH9fVhYGC+//DKnTp1K1jYnJUr8FAqFwkMpVaoUO3bsMKz/jR07lu7du/P48WM9rXbt2g4dW1sTHR3NokWLOHgvXH+lZZT4KRQKhQeTJ08eNmzYQNu2bfW0+fPn06JFCyIiNJ+dhQoVMoRKcobtyC8ti6ASP4VCofBw/P39+euvv3j77bf1tC1bttC9e3d9CvTVV191eK21F62rV686zGMWwT03HZ9PDZT4KRQKhQJvb28mTpxo8Om5atUqxo0bB0CbNm0M+atVq8awYcMM/j6diZ+ZiLCwJGzx0+GT2g1QKBQKRdpACMGHH37IzZs3dREcMWIEb775JpGRkXq+oKAg9uzZAxgFz5XfT4CoR4+SodWJQ438FAqFQmFg5MiR+sb2O3fu8McffxgiQJQuXVp/HxISohvD3Lx5kygrQxlbAoKCkqnFCUeJn0KhUCgM+Pr60q9fP/34p59+4vTp0/pxqVKl9Pc+Pj4ULlxYP57+5RhiY2Iclps9MGfSNzaRKPFTKBQKhR29evXCx0dbGdu6datB/GyjOlgL5Yrf5jC4W08e3LWP6O7llXYkJ+20RKFQKBRphjx58tChQwf92Dq6w61btwx5P/zwQ1588UX9+PDO3fRv8hx7Z8zh8a7/eDZvYVoXKk4Vbz/SCkr8FAqFQuEQ6xHd+fPn9fe24pcpUyYWLFjAl19+acgzbNgwOnXqRMuWLYmOjmbHjh3J3mZ3UeKnUCgUCoc0a9aMIkWK2KWHh9tvXN+9e7fT6BDr1q0jPDw8TYVCUuKnUCgUCod4eXkZRn9mrEd+kZGRDBgwgDp16rBp0yaH5Xz00UcsW7aMffv2JVtbE4pwNxx9eqR69erSvBdFoVAoFAnn/v37lClThitXrhjSY2JiWL9+PX379jVMiQIUL16c6tWr06ZNG1q3bs2lS5eoXbs2Dx8+BNgrpTRGx00F1CZ3hUKhUDgle/bszJkzh0aNGulpvr6+/P7777z22msGy89nn32WKVOmGKZK79y5Q8eOHc3Cl2ZQ054KhUKhcEnDhg356quv9ONOnTrRp08fXfgCAwOZOXMmq1atMghfXFwcPXr0MGyTSCuokZ9CoVAo4uWjjz4iKCiIyMhI9u7dS4xpI3vFihVZvXo1efPmtbtm5MiRLiPEpyZqzU+hUCgUCaJgwYL6GuC2bduoU6eOXZ5Dhw5RqVIluw3xpJE1PzXtqVAoFIoEYb3VYeLEiTx48MAuz8iRI3Xhq1+/PgEBASnWPndQ4qdQKBSKBNGtWzf9/Zw5c6hevToHDhzQ044ePcrChQv140GDBnHvnr27s9REiZ9CoVAoEsSUKVPo0aOHfnzixAlq1arFjz/+iJTSMOpr06aNW1HgUxq15qdQKBSKRDFr1izefvttQ6y/jh07smjRIv14586dRERE0LJlS3OSWvNTKBQKRfqlZ8+e7N27l0qVKulp1sLXsmVLypYtS9u2bVOjeS5R4qdQKBSKRFOqVCm2bt1KuXLlDOmBgYG8++67qdSq+FHip1AoFIqnwt/fnzVr1vDaa69Rp04dOnToQHR0NM8//zzdu3cnJCQktZtoh9rkrlAoFIqnJl++fPzyyy8AtG3bVt/+sHTpUj0obloi3pGfEKKTEOJPIcQFIcQjIcQJIcQYIUR2m3yBQoifhRC3hBCRQoi1QogKDsprLIQ4LoS4J4T4SQjha3UuVAghTa+mDq7dIoTYkMi+KhQKhSIFcOQEO63hzrTnh0As8BnQEpgMvAWsEUJ4AQghBLDEdP5/wItAJmC9EKKguSAhhD+wAJgGvABUAd5zUu+oRPRHoVAoFKmMdVT3tIo74tdWStlZSjlbSrlRSvkD8C5QC2hsytMOqA/0kFLOlVKuMqV5AR9blVUGuCSl/FZK+S/wJdDQQZ3/ALWFEGnPREihUCgULvnkk0/IkyePXXquXLlSoTWOiVf8pJRhDpJ3m/4WMP1tB1yVUq63uu4usBRob3XdRaC4aeozGHgFOOmg/D+AfcBI06hSoVAoFOkEb29v+vbta5fu6+vrIHfqkFhrT3Ngp2Omv+WAww7yHQGeEUJkA5BS3gQ+B9YAt4CigKO49tKUryLQJZFtVCgUCkUq8fHHH9uN/q5evZpKrbEnwSY4QogCwAhgrZTS7D4lCDjvIPtt099A4AGAlHKCEOJ3IBg4K6WMc1SPlHKlEGILMEII8YeU0q0VUyFEP6CfuX4hxDl3rssA5EJ7oPAUVH8zNp7UX0/qK0CW1G4AJFD8TCO4v4EY4DXrU2ijNbtLHJUjpYwAItyo8jNgE9AL+NmdNkoppwJTTe3dkxbc6KQEntRXUP3N6HhSfz2pr6D1N7XbAAmY9hRCZEGz6CwKPCelvGx1+jba6M+WQNNfd4TODinlZmAVMFQIkTkxZSgUCoVCYYtb4ieEyAT8CdQEnpdSHrLJcgRt3c+WssBFKaV9sCf3GQwUBN58ijIUCoVCodBxZ5O7FzAbaAa0l1LucJBtCVBACNHI6roAoK3pXKKRUu5DE97PAP8EXj71aepOZ3hSX0H1N6PjSf31pL5CGulvvCGNhBCT0UZdo4BlNqcvSykvmwRyC1AI+AhtmvNTNGvNSlLKS241RohQ4BzQV0r5s1V6aTRrUm9go5SysTvlKRQKhULhCHemPVuZ/g4Gttu8+gCYLDbboG1hmAT8heYVpom7wucKKeVx4LenLUehUCgUCsjgwWwVCoVCoXBEmg1pJISoJ4T4Rwhx0+QEe58Q4nWr879aOcG2fR23KctdZ9qOXpVTu6+mPOWEEIuEEFdNjsOPCCE+EEL42ORL031NQH8rCyFWCSEemPIsEUIUd1BWeuhvE5NT9kdCiNtCiN+EEHa+n0TSO4dP8T6701chRHYhxDdCiA2mPkghRGMn5aXZvpra4E5/mwkhfhdCnDHlOyOEmCyEsIvzk0H6W830v3tFCPFYCHFdCLFCCFEnTfVXSpnmXmhrhY+A9Wju0VoAP6HtJXzLlKcYUNvm1dWUZ6xVWf7ATeADNKOdXcBHVudDTdeMdlBebcAvDfQ1PxAGHAA6A03R1mDjgK/SS18T0N8SwH20qfX2aI7SDwJXgZB01t8GQDTaevnzQA/gAtoadmarfALYDFwGuqE5id+Itvm5YHrocwL6Goq2PWotmjGbBBo7KC/N9jWB/V0IrETbG90IbbnoCnAWyJYB+9sMmIh2P24EvARsA54ANdNKf5P1H/8pPuTRpg8qm036DmC7i+uGmD6sclZp1YG9VsdtgaUOPuA+abWvaB5rJFDSJs884Fp66WsC+vszcAfIaXW+IPAY44NNeujvWuA04GOVVsPUrret0tqb0ppYpeVAE4nx6aHPCeirsHrfHOfil2b7msD+5nZwbUNTvtczWn+dXJsdiAImpJX+ptVpT1+0J4xHNul3cD1V2xPtwzxileauM+3Uwp2+mqcC7rnIA2m/r+Bef2ujCeEd80mpOVU4jBYKy0x66G9tYI20cs8npdwNhGPsS1I7h08N3OqrNN3Z3CAt9xXc7687wQEgg/TXCZFo4hdtlZaq/U2r4ver6e94IUR+IUROIURftKHx944uEELUA4oDM63TpfvOtL2EED42L++k6Y5LfjX9ddXXhWhtnyiEKCKECBBCvIA27fCtuaB00Fdwr7+xaKNDW6KAYkLzNpRe+uuqL+WtjpPaOXxq9NndvrpFGu8rPF1/zXuizcEBMlx/hRBeQohMQohn0KZBwcpNZar3NzWGz24OsWugrX9I0+sJ0NtF/p9MeXI5OR+IJo5eNumhVnXYvh6klb6a2n7EKk8cMDS99dWd/qIFPL4MZLJKy442OpRAvvTSX7R1jJ02aYVN31+UVdpJYJ6D6/uY2lsorffZ3b7anHc67ZmW+5rY/lr9lo8DR7GaQsxo/UULTWdu3w2gflr6fhMc1SElEEKUQFsIP4K2wf4R2tTPFCHEYynlbJv8mdEMQZZJKR16R5fxO9Meiea025rYxPXAfdzpqxAiN7AIbeqgE9o0Q1PgcyFElJTyK+sy02pfwe3vdhzaIvkUIcRQNAfs3wLZTMUYIoGk5f6i9eV3IcRIYDyaD9ypaH2w7kdSO4dPjT6729cEkUb7Conor9Css+eiTXfWkw6i1WSg/n4MfIXm/OQdYJkQorm0RAMCUrG/yf20kMgnjIXAGaye/E3ps9GGx7ZPCJ3RbhztE1FXKKm7iBxvX4Gv0db7Am3yjMLFaDet9TUh3y3wNnAXy5PeWmA62hRLJjfrSvX+mtrxJZrIm0fsc9Hc/p21yrMTWO3g2o9N12Vzs67U/j3H21eb/PGO/NJqXxPaX9P/8mw0w61mGb2/Ntf5os1urEor/U2ra34VgP+klNE26bvQ4gDa7o95Fe3GuSIF2pbUuNPXCsBpqT0h2ebJhDZlkF5w67uVUk4yvS8PPCOlbI625WOng2vTNFLKIWgx2yqiTdl2Q9vOscUqW3I6h08x3OxrhiGB/Z2CFpy7q5Ty35RrZdKR2O9XSvkEbbtSmrlXpVXxuw5Utt7waKIW2lOTOUgupg2WzwJz0ttN0YQ7fb2OZhUV6CAPaHuG0gtuf7dSyigp5REp5SWhbfZuDkxOuaYmHVLKSCnlISnlDSFES6A02s3QTLI5h09p3OhrhsKd/gohvkVbv31NSrk4FZqZZCTm+xVC+KFtbTiTEm10hzS55odmGbQQWCqEmIQ2zG6Htvn3e9NThJmX0fox066UhFFUCFHbQfpJKeVtB+lJRbx9FUJMQevnP0KIr9HW/BoDHwJ/yYT7T02tvoJ7/S0IvIW2MTYKqIYW1WORlHJuIupMtf4KIaqg+cfdZ0qqj+b8fayUcptV1iVom/p/F0JYO4cXwNhEVJ3ifU5AXxFCtELb5Gz2YNNICJELiJRSrkxg1any/brbXyHEIGAg8AtwyqatYVLKhApCWu/vT2gPsXvQZuQKA/2BfGgW6gklefqbWnPHbsz3tgI2oHk2uY/m3eRtwNsm33/AoaeoJxTnFkUS6JQW+oq2x2YFcA3N8OUImplw1vTUV3f6C+RBW+O7hSZ+R9G8QNhZxqX1/qJNZW5Bs1R9hHbjeM1J3iC0G+Rt4CHwL1pUlHTR5wT29byT9p1PD31NSH9Nv3Vnbfw1A/b3dbQH13C02ZwzwBygQlr6LSvH1gqFQqHwONLqmp9CoVAoFMmGEj+FQqFQeBxK/BQKhULhcSjxUygUCoXHocRPoVAoFB6HEj+FQqFQeBxK/BQKhULhcSjxUygUCoXHocRPoVAoFB6HEj+FQqFQeBxK/BQKhULhcSjxUygUCoXHocRPoVAoFB6HEj+FQqFQeBxK/BQKhULhcSjxUygUCoXHocRPoVAoFB6HEj+FQqFQeBxK/BQKhULhcSjxUygUCoXHocRPoVAoFB6HEj+FQqFQeBxK/BQKhULhcSjxUygUCoXHocRPoVAoFB6HEj+FQqFQeBxK/BQKhULhcSjxUygUCoXHocRPoVAoFB6HEj+FQqFQeBxK/BQKhULhcSjxUygUCoXHocRPoVAoFB6HEj+FQqFQeBxK/BQKhULhcSjxUygUCoXHocRPoVAoFB6HEj+FQqFQeBxK/BQKhULhcSjxUygUCoXHocRPoVAoFB6HEj+FQqFQeBxK/BQKhULhcSjxUygUCoXHocRPoVAoFB6HEj+FQqFQeBxK/BQKhULhcSjxUygUCoXHocRPoVAoFB6HEj+FQqFQeBxK/BQKhULhcSjxUygUCoXHocRPoVAoFB6HEj+FQqFQeBxK/BQKhULhcfikdgPSO0IIATQGQlK5KQqFQpFY9kspT6Z2I1ISJX5PQdOSPjJ3NoGfL+QPSP5BdL6gzMleR0hIYLLXARBQqFiy1+EfVDTZ6/Dyy5vsdQA8JEuy13HtcWSy1wFw4d6dZK/j7PWbyV7HtRs3kr0OgCe3wpK/kqvXEflywfXwvFLKlOlYKqPELxEIIYoWzCnOxMRB5QLe5MgqCMme/OJXKTRrstdRpkzK3Mzz16yV7HXkLtYw2evwCayQ7HUAhBOQ7HUcvBee7HUAbL16IdnreHLoWLLXEX70aLLXAfDk1InkryQ4G4TfhfsPr4vC+eDi9WxSypR5GkollPglACFEcPHcXreC/ARFg71SRPAUCoUi2RECcuWEoAC4Hg5+WR6IEs/A6Us+UsrY1G5ecqDEzw2EEFkq5PN6lCMLBGUVVMrvhbbUp1AoFBkILy/InxtCguDyDciWNUaUKwZHz3pJKWVqNy8pUeLnAiGEV41nvGNzZAEENC3pg7eXEj2FQpHB8fGG0PwQ9QQuXIOc2eKEENWklPtSu2lJhZq3c0LD4j4yyE/E3nkkaVjch1Ih3kr4FAqFZ5HZF0oW1oQwZ/a9IiRICiEKp3azkgI18rNBCFE+b4A45OMFNQt7ky2zEjyFQuHhZPOD8sUg4h48ijovCuaBKzeDpJQRqd20xKLEz4QQokBokLicO5ugbB4vgvzVoFihUCgMBAZAzuxw8zb4ZbktihaAc1ezSCmjUrtpCUWJn4l8AeLyo2ioX1RNbyoUCoVThIA8wRCQDQ6eguKFHgPp7qaphjcmrt2TfrmzCdadjOFiRBwZzLBJoVAokoaYWDh/DU6chxKF4PSldKkjauRnQkr5CM1bWa7bkTLsdFgc5fOpvXwKhUIBQJyE67e0fYD5c8ODR5nkkbMxqd2sxKLEzwYp5S00ESx+5lbcqVNhcVTI701AlnQ3qlcoFIqnR0rN+8ulGxCcAx4+zi5PXXyQ2s16WpT4OUFKeRoQTUv6yH2XYsmeBcrm9SZrJiWCCoXCQ7gXCeevgl8WiHyUXz54eC21m5RUKPGLh3UnY4QQQpTI7R239WwM+QK8KBXihY+3EkGFQpFBeRSliZ6UcC+ynLz7IGUcmaYgSvzcwOTWRwghMoUG8WT9qRiK5fImNFjgpdycKRSKjEJ0DFy8Dg8ewf3IJlLKDandpORCiV8CkFJGo4lgwMNoeXf9yTjK5PUiX4ASQIVCkY6JjYOrYXArAgrmgWu3vKWUcandrOREKJP+xCOEKBgaJC49iIKQ7MkvgEHZMiV7HYGB2ZO9DgC/3PmTvY4sAfmSvQ6vzEHJXgfAY5L/u7/9JGX2Kd94eD/Z67h2+06y1xEekTLOTWLu3U3eCqSE8AjNmfX59LlhPTEo8UsChBChQB/gr2Su6oUMUkdK1ZNR6kipelRf0l4dKVVPfSnluGSuI02hxC+JEELskVJWV3WknXoySh0pVY/qS9qrI6XqSam+pCXUDm6FQqFQeBxK/BQKhULhcSjxSzqmqjrSXD0ZpY6Uqkf1Je3VkVL1pFRf0gxqzU+hUCgUHoca+SkUCoXC41Dip1AoFAqPQ4lfAhBCDBRCLBVCXBNCSCHEcCf5NpjO277ed5C3gxBivxDisRDighBiRXx1CCHyCSHGCCH2CCHuCiHChBD/CiEaOsj7q5O2nI2vH6br+wohjgshooQQJ4QQbzrJZ9uPz4UQ3jZ5ejlpi/mVNzGfoYO2nHdybYfE9s/mmpJCiHFCiINCiAemz3GJEKKSg7xP049CQog/TN/xPSHEIiHEM/Fd56SsTkKIP03fzSNTX8cIIbJb5Ql18d3kdLOexk6uv2OTL1AI8bMQ4pYQIlIIsVYIUcHNOpx9plIIsSoxfRFCFBRCTBBCbBdCPDTlC3WQz612CyGyCCG+Nv02HpnKfTG+OoQQzYQQvwshzpiuOyOEmCyECHFQh7P+PetGPW5/Pk76YnevSW8o92YJoy9wD1gMxHeTPAi8YZN23vpACPEc8CcwHRgIVAG+Aa7HU0c1oAswA9gB+AJvAxuEEO2klMts8ocB7ayO5wJ3gdWu+iGE6Av8BIwB1gLNgElCCCGlnBxPP0YD2YFBVkUuB+rYVgMsBc5KKa/bnIv3M3TBamC4TdoJQ8Vu9s8BzwJNgJnAPiAn8DGwUwhRT0q592n7IYTwA9YBUcCrgARGAuuFEBWllJGurnfAh8BF4DPgMtp3NBxoIoSoa+PKagywxOb6hLpleRfYbXWsx30TQghT+UWA/wERwKdofasspbwcT9lvAwE2aXWA7xy0292+FAc6A3uBzWjfsYEEtns60Br4CDgLvAPMAR4AO53Vgfb/mA3tuz4LlAC+AJ4zfe+2oYR+RfsNW5Mjvr5Y4c7n46gvq4UQdaSUB1yUnbaRUqqXmy/Ay/TXB+1mNNxJvg3AFjfK2w9stEkbBjwBCjirA+1m62OT5oN2c99kk/4rcDmh/TCduwnMtEn/BbgFZIqnH0NN/cgbz2fQwNSGdxLzGTop8zzwezx53O6fg2tzYTIWs0rLgXYznJUU/QDeA2KB4lZpRdBEZGAiysvtIK2n6bNvajoONR33ScznbiqjsamM5i7ytDflaWLz+d0Gxiey3uloDwpBiemL+X/C9L6P6drQxLQbqGTK95rN7+0EsCSeOhx9Tw1NeV+3SZfAyET2xa3Px52+pNeXmvZMADIJHb0KIQoBlYHfbU7NAjIBLV20446UMsYmLQY4gCaaLnGzH3WA3A7a9xsQDNQHl/34Da0freKp51U0kZznRpuSErf65wgp5S1pugtYpd0FTuLG5+8m7YAdUosraa7jHLAViqjMjAAADSJJREFU7SacIKSUYQ6SzSOzpGqzu7QDrkop15sTTJ/fUhLRNyFEVuAlYKmU8nZiGuTm/4S77W4HRAPzrfLFoP3GnxNCZHbRjqf+npLyPsVT9CWto8Qv+agitLWaaKGtDfW2OV/O9PewdaLpBvcQKJOQyoQQvmg39GMOToeY1ihihBAnhRCDhM16nAMctg84Yvpb1lU+q36UxQlWN61lUspwB1ni+wxd0da03hElhNgh7Nf73O2fWwghgoDyOP78E9OPcg7aZm5fgtrmgkamv7ZtHmP6rdwV2lqmW2txNswWQsQKIcKFEHOEca3SVd+eEUJkS2BdHdGm2Gc6OJcUfTHjbrvLAeeklA8d5PNFm2JNCM6+J4C3TL/xh0KIdUKIBgksO77PJ6n7kmZQa37JwyZgNtpIICfa9NLPQoh8UsqRpjzmcACOXMNHWJ13l+FAQeBlm/QDaHP/R4AsaE5yx6CtJbhat3TWvts255+mHx3Q1m4c3bTc+QydsRTtafkckAfoD/wlhOghpTSP9Nztn7tMQFu//MEmPbH9CHLQNnP7AhPYNjuEEAWAEcBaKeUeU3IU2vrRP2jrxKXR1gi3CSFqSikd3XxtuQt8C2xEWx+vYipjuxCiipTyJlrfzju41vzZB6KtjblLT7Qp7JVWaUnRF1vcbber785cjlsIzSDpBzThW2xz+ndgGXAVKIy2JrdOCNFCxh+Hz93PJ8n6kuZI7XnX1HoBzdHmsuN7bXBwrcs1v6etA7iCtvaULHUA35vSSjurAxhsOpfZSd+HPM1naCprFdpNyyepP0ObMrzRxPCSo/4lQT8+xcGajIv2/AU8ArK5yPMEGOMgfRQQ85S//WzAHrSbZsF48hZCEzGXa6jxlFEVba1ypOn4FDDXQb6+ps+xUALKzo+2NvqdG3nd6gvO18ncajewBtjuIF8LU74Gzupw8L+2DM0ApaIb/csOXMBqjdmdelx9Pu705Wl+i6n58uSR3zbcm1q0He4nto6WaKLTDW001gDNpVA3Uz5rcmJ5soqPHGhz8ovRjEycYd2PucD7aFajzrB+srtmlR5kdX4b0A9LPw7YlLHPVNcXtoULIfKhic4EabN+aYOrz9Aap9+TlDJWCLEQ+Mo04rqGsX/WdQShrat9iWad57IOoW2NGA18LqX8xUU/rJmLNuqtAGx3ksfZqDkQx0/ibiGEyIJm3VcUaCTjsayUUl4SQmwBaiS2TinlPiHESasybuO8b5Cw/r2CtnzjaPbAth1P2xd3230bcLQlJdDqvEuEEOY+NQdaSykPxneNlPK+EGI5kJDlAevrHX0+T92XtIrHip/U5rCPp1QdwrIH7LyU8rgQwnwjzSalvGi+xrQfxw/H8/sGhBDN0KbU/gK6SfcXus2Rd6WLPOa1r3IYxc+83nRUSvlQCLHadJxNSql/nqZ+ZEV7Cr2IPa+gjchc3rRcfYaurnOAbZ/1/kkp11rV0diUvj6+OoQQPYBJwLdSylFP0RZHHMGyLmlNWeBoAuqyVCpEJrQtKTXRrDEPuXsprtua0DKO4Nj8vixwUdqb87uiJ/CflPK/RLQjobjb7iPAC0IIP2lcKyuLNqI/jf2WH1umoG1n6iSl/DcBbXza78r2enf6ki5RBi8pR3e0qa5DACZB+A/7NbpX0EZyq1wVJoSoA/wN/Au8kgDhM7dFok19OWM7msm/o/bdRhsdudOPlTimJ3BQJmyfkOEzdBchhA+aYc1FadlL6Fb/XJT5Ato+y5+llB8mpD24148lQG0hRFGrOkOBetjvy4oX00hiNtpexvZSyh1uXveMqc6dCa3TqozqQEmrMpYABYQQjazyBABtSUDfTOWWw41Rnyn/0/bF3XYvQbN0fskqnw+amP0j44mULoT4Fm268jUp5WJ3G2dqS2sS2T8nn89T9SUt47Ejv8Rg+mcLxfLQUFYI0cn0foVpJNQA+ARYhLY4ngPNnL8d8Ik0bk7+DFgmhPgJbSqsCtpa2kq0H6GzOkqjbRi/BXwNVNP232qYb2xCiMJopvvz0J7QMqMZvPRCm8uv7KwOKWW0EGII2qbvK2ibwJsCrwP/k1I+iacfnwPjpP3GdYQQVdEsIz+wPWc6n5DP0Pbabmhm5yuAS2gGL++gTfF2s/qMEtI/2zoamvp5EPhVCFHb6nSUlHL/0/YDmIZmqPO3EOJztIeVL019st3U7A4/ot3ARgGRNm2+LKW8bLrpeqE9GIQBpdDWM+PQpnbjRQgxG83QaB9wB+238CnaOvYEU7Ylpjp+F0J8hGWzuADGJqBPPdHWEm2np0lMX6z+B8zLAa2EEGFAmJRyo7vtllIeEELMB34wjbbPAW+h7dP8xVSPwzqEEIPQHEX8Apyy+Z7CpJRnTG390NSn9VgMXj4E8gIvx9cXdz+fePpi++CYvkjtRcf09ELbMO7MGCLUlKc4mnhdQbOoeoC2ptTNSZkd0UZOUWgeOPa7UUcvF3mkVdlBaGuBF4DHaKONfWheYVzWYVXGG2iWilFoC/5vu9mPoYC3k7zj0EaFeZycT9BnaHNtbTTPKDdMddxFE7bnnOR3q3821wx38fmdT4p+mK5/Bm2a8h6a0cNi2+8nAb/d8y7aPNyU53U0w6AINFG5jiYspRJQz6doDwV3TZ//JbQ14Xw2+YLQbvC30dZS/wUqJaCeTGg37aVOzie4Ly4+nw0JbTfalP93pnofo42mGsdXB5pTBGd5frUqvy3a7MQt0+ccjibONd3pS0I+H2d9SczvMC29VEgjhUKhUHgcas1PoVAoFB6HEj+FQqFQeBxK/BQKhULhcSjxUygUCoXHocRPoVAoFB6HEj+FQqFQeBxK/BSKDIQQIlQIMdzaM4xCobBHiZ9CkbEIBYahOa5WKBROUOKnUCQDIh1HuFYoPAElfgqPxDQ1KIUQFYQQ602RsK8JIUaYnECb8+USQkwWQlwxRcw+LoToZ1NWL1NZDYUQC4UQdzA5BxZC+AghBgkhjgohHgshwoQQq0z+WRNTR20hxGwhxD0hxFUhxHhTmCJzRIr1pkvWmPJLc6QKIURXoUX7DhNCPBBC7BdCvOrgs8kthJhrqiNCCDFDCNHOuiyrvB2FEDtMn98dU/8dhcBRKNIUyrG1wtNZjOarcQzwHJpj8ThguMlL/lY034bD0Zz6PgdMFkJkllJOsClrNprD605Y/rfmocXu+wHNx2gWoCGQDzieiDp+M9XRES0sznA0/4zD0Py2voPmxPpdNN+NYAmBVBT4A/g/Ux8bokWVzyqlnGJVxyK0WIOfojlEfxGLU2odocUynIwW3WIEWjDV4cBGIURFKeV922sUijRDajsXVS/1So0XFufUn9ikT0NzIp0TTQgfAyUc5LmFKQI9Fkfj39vka2pKf9dFOxJaxxc2+ZYBJ62OG5vyNY+n/15oAj0NLR6eOf1Z0/WdbfIvMaU3Nh1nQ3Ne/YtNvlC0OG/vp/Z3rF7q5eqlpj0Vns4Cm+N5aDf28miR43cC50zTlz6mWGargWAsgX3N/GVzbBaSaS7qT2gdy22OD+E40rYdQogSpunMK2iRAKLR4saVsspWG4h10Jc/bI7rAAHAbJt2X0YLDNzQnTYpFKmFmvZUeDo3nBwXAELQwhJFO7k22Ob4moPzt6WUj1zUn9A6btscR6HFaXSJECIbWgzHh2gxBs+gjdDeQgtvYyYfECGltG2P7ecUYvq71kmVEfG1SaFITZT4KTydPMBZm2PQYvCFAzeB95xce8Lm2DY+2C0gyLSm5kwAE1pHYqmDFvC0gZRyiznRNFqz5hoQKITIZCOAeWzyhZv+9gKOOKhPrfcp0jRK/BSeTmc0AxAzXdGCzh4GVgH/Ay5KKW8moux/0EZZfXBgMGLiaeuwJcr0N6tNup/pry5oQohAtKj31uwAvIEXME4Jv2STbxuawBWXUs58mgYrFKmBEj+Fp9PXtLVhN5qVZR+0yOZ3hBDfA12Azab3JwB/oDTaCMpWOAxIKdcLIf4EvhNCFEKLMJ8JbT1suZRyA/BUdTjgJFpk7teFELfRxPAEmljdA34UQgwz1fE52ug0h1Wb/xFCbAGmCiFyoVl7dgIqmbLEmfLdE0J8ZCovN1rE+rto08WN0CKGz0lg2xWKFEMZvCg8nfZACzRrxleAkcCXAFLKu0BdYAUwCM0I5RfTNesdFeaArmiWpR1MdfwClMO0PphEdehIKcOB/mhitRFN1KtJKcPQRnPeaMYrY4Cfgd8dFNMRbUT6FdroLwuaVSpoAmeu6yegHZrBzG9oAvgF2kP1gYS2XaFISYSUtssUCkXGRwgxHG1vXCYpZUwqNyfNI4T4EW19L0hKGRVPdoUizaOmPRUKhQEhRC+0qdAjgC/adow3ga+V8CkyCkr8FAqFLZHA+0AxtG0U54DPgK9TsU0KRZKipj0VCoVC4XEogxeFQqFQeBxK/BQKhULhcSjxUygUCoXHocRPoVAoFB6HEj+FQqFQeBz/D5GXFZeWnxCrAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x684 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting bias percentage \n",
    "\n",
    "#plotting with cartopy\n",
    "import cartopy.feature as cfeature\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize=(12,9.5))\n",
    "\n",
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "ax.set_extent([88,93,20,27])\n",
    "\n",
    "\n",
    "m1 = ax.contourf(bias_percentage['lon'][:], bias_percentage['lat'][:],bias_percentage[:,:],\n",
    "                levels=np.arange(-150,150+25,25),transform = ccrs.PlateCarree(),cmap='BrBG',extend='both')\n",
    "\n",
    " \n",
    "# Define the xticks for longitude\n",
    "ax.set_xticks(np.arange(87,94,1), crs=ccrs.PlateCarree())\n",
    "lon_formatter = cticker.LongitudeFormatter()\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "\n",
    "# Define the yticks for latitude\n",
    "ax.set_yticks(np.arange(20,28,1), crs=ccrs.PlateCarree())\n",
    "lat_formatter = cticker.LatitudeFormatter()\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "\n",
    "\n",
    "plt.colorbar(m1,ticks=np.arange(-150,150+25,25), orientation = 'horizontal',shrink=0.5, fraction = 0.04 , label = 'percentage')\n",
    "ax.coastlines(linewidth=3)\n",
    "ax.add_feature(cfeature.BORDERS,linewidth=3)\n",
    " \n",
    "    \n",
    "plt.title('Seasonal Bias-Percentage(RegCM NORESM-CRU)',fontsize=17)\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/Seasonal Bias_percentage(noresm-cru).png\")\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "220503a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Colormap CET_D1A is not recognized. Possible values are: Accent, Accent_r, Blues, Blues_r, \\nBrBG, BrBG_r, BuGn, BuGn_r, BuPu, BuPu_r, CMRmap, CMRmap_r, Dark2, Dark2_r, GnBu, GnBu_r, Greens,\\nGreens_r, Greys, Greys_r, OrRd, OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, \\nPastel2_r, PiYG, PiYG_r, PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Purples_r, RdBu, RdBu_r, RdGy,\\nRdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, \\nSpectral_r, Wistia, Wistia_r, YlGn, YlGnBu, YlGnBu_r, YlGn_r, YlOrBr, YlOrBr_r, YlOrRd, YlOrRd_r, afmhot, afmhot_r, autumn,\\nautumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, cividis, cividis_r, cool, cool_r, coolwarm, coolwarm_r, \\ncopper, copper_r, cubehelix, cubehelix_r, flag, flag_r, gist_earth, gist_earth_r, gist_gray, gist_gray_r, gist_heat,\\ngist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r,\\ngnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r, hsv, hsv_r, inferno, inferno_r, jet, jet_r, magma,\\nmagma_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, \\nseismic, seismic_r, spring, spring_r, summer, summer_r, tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, \\nter'"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#cma colors\n",
    "'''Colormap CET_D1A is not recognized. Possible values are: Accent, Accent_r, Blues, Blues_r, \n",
    "BrBG, BrBG_r, BuGn, BuGn_r, BuPu, BuPu_r, CMRmap, CMRmap_r, Dark2, Dark2_r, GnBu, GnBu_r, Greens,\n",
    "Greens_r, Greys, Greys_r, OrRd, OrRd_r, Oranges, Oranges_r, PRGn, PRGn_r, Paired, Paired_r, Pastel1, Pastel1_r, Pastel2, \n",
    "Pastel2_r, PiYG, PiYG_r, PuBu, PuBuGn, PuBuGn_r, PuBu_r, PuOr, PuOr_r, PuRd, PuRd_r, Purples, Purples_r, RdBu, RdBu_r, RdGy,\n",
    "RdGy_r, RdPu, RdPu_r, RdYlBu, RdYlBu_r, RdYlGn, RdYlGn_r, Reds, Reds_r, Set1, Set1_r, Set2, Set2_r, Set3, Set3_r, Spectral, \n",
    "Spectral_r, Wistia, Wistia_r, YlGn, YlGnBu, YlGnBu_r, YlGn_r, YlOrBr, YlOrBr_r, YlOrRd, YlOrRd_r, afmhot, afmhot_r, autumn,\n",
    "autumn_r, binary, binary_r, bone, bone_r, brg, brg_r, bwr, bwr_r, cividis, cividis_r, cool, cool_r, coolwarm, coolwarm_r, \n",
    "copper, copper_r, cubehelix, cubehelix_r, flag, flag_r, gist_earth, gist_earth_r, gist_gray, gist_gray_r, gist_heat,\n",
    "gist_heat_r, gist_ncar, gist_ncar_r, gist_rainbow, gist_rainbow_r, gist_stern, gist_stern_r, gist_yarg, gist_yarg_r,\n",
    "gnuplot, gnuplot2, gnuplot2_r, gnuplot_r, gray, gray_r, hot, hot_r, hsv, hsv_r, inferno, inferno_r, jet, jet_r, magma,\n",
    "magma_r, nipy_spectral, nipy_spectral_r, ocean, ocean_r, pink, pink_r, plasma, plasma_r, prism, prism_r, rainbow, rainbow_r, \n",
    "seismic, seismic_r, spring, spring_r, summer, summer_r, tab10, tab10_r, tab20, tab20_r, tab20b, tab20b_r, tab20c, tab20c_r, \n",
    "ter'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "87f4ea28",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "20e38f40",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "21be7cc5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}