Bd_pr_MERRA.ipynb

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   "source": [
    "#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\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "eabdcdf5",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 505, bnds: 2, lon: 576, lat: 361)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1980-01-01T12:00:00 ... 2022-01-01T12:00:00\n",
       "  * lon        (lon) float64 -180.0 -179.4 -178.8 -178.1 ... 178.1 178.8 179.4\n",
       "  * lat        (lat) float64 -90.0 -89.5 -89.0 -88.5 ... 88.5 89.0 89.5 90.0\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) datetime64[ns] 1980-01-01T00:30:00 ... 2022-01-16...\n",
       "    PRECTOT    (time, lat, lon) float32 ...\n",
       "Attributes: (12/34)\n",
       "    CDI:                               Climate Data Interface version 1.9.9rc...\n",
       "    history:                           Thu Jun 16 11:24:03 2022: cdo mergetim...\n",
       "    Conventions:                       CF-1\n",
       "    History:                           Original file generated: Sat May 31 17...\n",
       "    Comment:                           GMAO filename: d5124_m2_jan79.tavg1_2d...\n",
       "    Filename:                          MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4\n",
       "    ...                                ...\n",
       "    RangeBeginningTime:                00:00:00.000000\n",
       "    RangeEndingDate:                   1980-01-01\n",
       "    RangeEndingTime:                   23:59:59.000000\n",
       "    frequency:                         mon\n",
       "    NCO:                               netCDF Operators version 4.8.1 (Homepa...\n",
       "    CDO:                               Climate Data Operators version 1.9.9rc...</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-1f326bcf-9551-4a92-bbfa-d67988f1cd95' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1f326bcf-9551-4a92-bbfa-d67988f1cd95' 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>: 505</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 576</li><li><span class='xr-has-index'>lat</span>: 361</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e9fd9421-b43f-43fe-832f-710b0ed0a2b7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e9fd9421-b43f-43fe-832f-710b0ed0a2b7' 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'>1980-01-01T12:00:00 ... 2022-01-...</div><input id='attrs-0da070fc-5df5-49a1-9134-2f3b4c5fdfb0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0da070fc-5df5-49a1-9134-2f3b4c5fdfb0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a58aac6-cb21-4a50-adf2-1f8cc2517075' class='xr-var-data-in' type='checkbox'><label for='data-0a58aac6-cb21-4a50-adf2-1f8cc2517075' title='Show/Hide data 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([&#x27;1980-01-01T12:00:00.000000000&#x27;, &#x27;1980-02-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1980-03-01T12:00:00.000000000&#x27;, ..., &#x27;2021-11-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;2021-12-01T12:00:00.000000000&#x27;, &#x27;2022-01-01T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -179.4 ... 178.8 179.4</div><input id='attrs-e4a46cef-0ec9-4697-bdb0-8756a5acb3f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e4a46cef-0ec9-4697-bdb0-8756a5acb3f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44db7376-d051-43b8-a6ae-ef892b83953f' class='xr-var-data-in' type='checkbox'><label for='data-44db7376-d051-43b8-a6ae-ef892b83953f' title='Show/Hide data 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([-180.   , -179.375, -178.75 , ...,  178.125,  178.75 ,  179.375])</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'>-90.0 -89.5 -89.0 ... 89.5 90.0</div><input id='attrs-204f4766-8fc2-43f2-92bd-682330a17b6a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-204f4766-8fc2-43f2-92bd-682330a17b6a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0aa41b5e-861b-4997-aa90-717995c74592' class='xr-var-data-in' type='checkbox'><label for='data-0aa41b5e-861b-4997-aa90-717995c74592' title='Show/Hide data 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([-90. , -89.5, -89. , ...,  89. ,  89.5,  90. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6c80dc9e-68d6-4e11-acc0-5cfaed5a5214' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6c80dc9e-68d6-4e11-acc0-5cfaed5a5214' 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'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a15cae88-60a7-4b14-8a8b-7e300db157a1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a15cae88-60a7-4b14-8a8b-7e300db157a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c348b67-1369-41a0-a185-7d0fa21d6453' class='xr-var-data-in' type='checkbox'><label for='data-9c348b67-1369-41a0-a185-7d0fa21d6453' title='Show/Hide data 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;1980-01-01T00:30:00.000000000&#x27;, &#x27;1980-01-31T23:30:00.000000000&#x27;],\n",
       "       [&#x27;1980-02-01T00:30:00.000000000&#x27;, &#x27;1980-02-29T23:30:00.000000000&#x27;],\n",
       "       [&#x27;1980-03-01T00:30:00.000000000&#x27;, &#x27;1980-03-31T23:30:00.000000000&#x27;],\n",
       "       ...,\n",
       "       [&#x27;2021-11-01T00:30:00.000000000&#x27;, &#x27;2021-11-30T23:30:00.000000000&#x27;],\n",
       "       [&#x27;2021-12-01T00:30:00.000000000&#x27;, &#x27;2021-12-31T23:30:00.000000000&#x27;],\n",
       "       [&#x27;2022-01-16T00:30:00.000000000&#x27;, &#x27;2022-01-16T23:30:00.000000000&#x27;]],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRECTOT</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-5e58e84a-9171-4cc1-aa70-21e45a94582d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e58e84a-9171-4cc1-aa70-21e45a94582d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1fc5582b-a489-48f3-8a8c-e0f8ac355ec8' class='xr-var-data-in' type='checkbox'><label for='data-1fc5582b-a489-48f3-8a8c-e0f8ac355ec8' title='Show/Hide data 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>total_precipitation</dd><dt><span>long_name :</span></dt><dd>total_precipitation</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>fmissing_value :</span></dt><dd>1000000000000000.0</dd><dt><span>vmax :</span></dt><dd>1000000000000000.0</dd><dt><span>vmin :</span></dt><dd>-1000000000000000.0</dd></dl></div><div class='xr-var-data'><pre>[105007680 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8c6091eb-f6e9-42ac-b7d9-dc48c196053f' class='xr-section-summary-in' type='checkbox'  ><label for='section-8c6091eb-f6e9-42ac-b7d9-dc48c196053f' class='xr-section-summary' >Attributes: <span>(34)</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>history :</span></dt><dd>Thu Jun 16 11:24:03 2022: cdo mergetime 198001PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198001.nc4 198002PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198002.nc4 198003PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198003.nc4 198004PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198004.nc4 198005PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198005.nc4 198006PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198006.nc4 198007PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198007.nc4 198008PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198008.nc4 198009PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198009.nc4 198010PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198010.nc4 198011PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198011.nc4 198012PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198012.nc4 198101PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198101.nc4 198102PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198102.nc4 198103PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198103.nc4 198104PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198104.nc4 198105PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198105.nc4 198106PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198106.nc4 198107PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198107.nc4 198108PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198108.nc4 198109PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198109.nc4 198110PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198110.nc4 198111PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198111.nc4 198112PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198112.nc4 198201PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198201.nc4 198202PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198202.nc4 198203PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198203.nc4 198204PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198204.nc4 198205PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198205.nc4 198206PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198206.nc4 198207PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198207.nc4 198208PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198208.nc4 198209PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198209.nc4 198210PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198210.nc4 198211PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198211.nc4 198212PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198212.nc4 198301PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198301.nc4 198302PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198302.nc4 198303PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198303.nc4 198304PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198304.nc4 198305PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198305.nc4 198306PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198306.nc4 198307PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198307.nc4 198308PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198308.nc4 198309PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198309.nc4 198310PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198310.nc4 198311PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198311.nc4 198312PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198312.nc4 198401PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198401.nc4 198402PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198402.nc4 198403PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198403.nc4 198404PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198404.nc4 198405PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198405.nc4 198406PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198406.nc4 198407PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198407.nc4 198408PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198408.nc4 198409PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198409.nc4 198410PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198410.nc4 198411PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198411.nc4 198412PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198412.nc4 198501PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198501.nc4 198502PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198502.nc4 198503PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198503.nc4 198504PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198504.nc4 198505PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198505.nc4 198506PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198506.nc4 198507PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198507.nc4 198508PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198508.nc4 198509PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198509.nc4 198510PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198510.nc4 198511PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198511.nc4 198512PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198512.nc4 198601PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198601.nc4 198602PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198602.nc4 198603PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198603.nc4 198604PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198604.nc4 198605PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198605.nc4 198606PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198606.nc4 198607PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198607.nc4 198608PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198608.nc4 198609PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198609.nc4 198610PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198610.nc4 198611PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198611.nc4 198612PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198612.nc4 198701PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198701.nc4 198702PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198702.nc4 198703PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198703.nc4 198704PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198704.nc4 198705PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198705.nc4 198706PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198706.nc4 198707PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198707.nc4 198708PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198708.nc4 198709PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198709.nc4 198710PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198710.nc4 198711PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198711.nc4 198712PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198712.nc4 198801PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198801.nc4 198802PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198802.nc4 198803PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198803.nc4 198804PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198804.nc4 198805PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198805.nc4 198806PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198806.nc4 198807PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198807.nc4 198808PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198808.nc4 198809PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198809.nc4 198810PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198810.nc4 198811PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198811.nc4 198812PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198812.nc4 198901PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198901.nc4 198902PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198902.nc4 198903PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198903.nc4 198904PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198904.nc4 198905PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198905.nc4 198906PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198906.nc4 198907PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198907.nc4 198908PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198908.nc4 198909PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198909.nc4 198910PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198910.nc4 198911PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198911.nc4 198912PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198912.nc4 199001PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199001.nc4 199002PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199002.nc4 199003PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199003.nc4 199004PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199004.nc4 199005PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199005.nc4 199006PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199006.nc4 199007PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199007.nc4 199008PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199008.nc4 199009PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199009.nc4 199010PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199010.nc4 199011PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199011.nc4 199012PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199012.nc4 199101PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199101.nc4 199102PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199102.nc4 199103PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199103.nc4 199104PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199104.nc4 199105PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199105.nc4 199106PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199106.nc4 199107PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199107.nc4 199108PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199108.nc4 199109PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199109.nc4 199110PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199110.nc4 199111PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199111.nc4 199112PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199112.nc4 199201PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199201.nc4 199202PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199202.nc4 199203PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199203.nc4 199204PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199204.nc4 199205PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199205.nc4 199206PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199206.nc4 199207PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199207.nc4 199208PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199208.nc4 199209PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199209.nc4 199210PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199210.nc4 199211PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199211.nc4 199212PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199212.nc4 199301PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199301.nc4 199302PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199302.nc4 199303PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199303.nc4 199304PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199304.nc4 199305PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199305.nc4 199306PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199306.nc4 199307PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199307.nc4 199308PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199308.nc4 199309PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199309.nc4 199310PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199310.nc4 199311PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199311.nc4 199312PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199312.nc4 199401PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199401.nc4 199402PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199402.nc4 199403PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199403.nc4 199404PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199404.nc4 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201305PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201305.nc4 201306PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201306.nc4 201307PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201307.nc4 201308PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201308.nc4 201309PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201309.nc4 201310PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201310.nc4 201311PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201311.nc4 201312PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201312.nc4 201401PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201401.nc4 201402PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201402.nc4 201403PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201403.nc4 201404PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201404.nc4 201405PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201405.nc4 201406PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201406.nc4 201407PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201407.nc4 201408PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201408.nc4 201409PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201409.nc4 201410PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201410.nc4 201411PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201411.nc4 201412PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201412.nc4 201501PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201501.nc4 201502PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201502.nc4 201503PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201503.nc4 201504PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201504.nc4 201505PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201505.nc4 201506PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201506.nc4 201507PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201507.nc4 201508PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201508.nc4 201509PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201509.nc4 201510PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201510.nc4 201511PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201511.nc4 201512PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201512.nc4 201601PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201601.nc4 201602PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201602.nc4 201603PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201603.nc4 201604PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201604.nc4 201605PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201605.nc4 201606PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201606.nc4 201607PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201607.nc4 201608PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201608.nc4 201609PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201609.nc4 201610PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201610.nc4 201611PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201611.nc4 201612PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201612.nc4 201701PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201701.nc4 201702PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201702.nc4 201703PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201703.nc4 201704PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201704.nc4 201705PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201705.nc4 201706PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201706.nc4 201707PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201707.nc4 201708PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201708.nc4 201709PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201709.nc4 201710PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201710.nc4 201711PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201711.nc4 201712PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201712.nc4 201801PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201801.nc4 201802PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201802.nc4 201803PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201803.nc4 201804PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201804.nc4 201805PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201805.nc4 201806PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201806.nc4 201807PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201807.nc4 201808PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201808.nc4 201809PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201809.nc4 201810PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201810.nc4 201811PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201811.nc4 201812PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201812.nc4 201901PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201901.nc4 201902PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201902.nc4 201903PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201903.nc4 201904PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201904.nc4 201905PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201905.nc4 201906PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201906.nc4 201907PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201907.nc4 201908PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201908.nc4 201909PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201909.nc4 201910PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201910.nc4 201911PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201911.nc4 201912PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201912.nc4 202001PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202001.nc4 202002PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202002.nc4 202003PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202003.nc4 202004PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202004.nc4 202005PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202005.nc4 202006PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202006.nc4 202007PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202007.nc4 202008PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202008.nc4 202009PRECTOT_MERRA2_401.tavg1_2d_flx_Nx.202009.nc4 202010PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202010.nc4 202011PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202011.nc4 202012PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202012.nc4 202101PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202101.nc4 202102PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202102.nc4 202103PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202103.nc4 202104PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202104.nc4 202105PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202105.nc4 202106PRECTOT_MERRA2_401.tavg1_2d_flx_Nx.202106.nc4 202107PRECTOT_MERRA2_401.tavg1_2d_flx_Nx.202107.nc4 202108PRECTOT_MERRA2_401.tavg1_2d_flx_Nx.202108.nc4 202109PRECTOT_MERRA2_401.tavg1_2d_flx_Nx.202109.nc4 202110PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202110.nc4 202111PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202111.nc4 202112PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202112.nc4 202201PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202201.nc ..//../monthly/PRECTOT_MERRA2.tavg1_2m_flx_Nx.1980-2021.nc\n",
       "Thu Jun 16 11:14:20 2022: cdo monavg ./1980/PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198001.nc4 tmp/PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198001.nc4\n",
       "Tue Mar  1 13:15:53 2022: ncrcat PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800102.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800103.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800104.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800105.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800106.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800107.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800108.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800109.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800110.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800111.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800112.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800113.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800114.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800115.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800116.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800117.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800118.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800119.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800120.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800121.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800122.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800123.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800124.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800125.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800126.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800127.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800128.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800129.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800130.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800131.nc4 1980/PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198001.nc\n",
       "Tue Mar 01 12:51:15 2022: cdo -f nc4 -z zip_3 -L dayavg -selvar,PRECTOT MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4</dd><dt><span>Conventions :</span></dt><dd>CF-1</dd><dt><span>History :</span></dt><dd>Original file generated: Sat May 31 17:44:24 2014 GMT</dd><dt><span>Comment :</span></dt><dd>GMAO filename: d5124_m2_jan79.tavg1_2d_flx_Nx.19800101.nc4</dd><dt><span>Filename :</span></dt><dd>MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4</dd><dt><span>Institution :</span></dt><dd>NASA Global Modeling and Assimilation Office</dd><dt><span>References :</span></dt><dd>http://gmao.gsfc.nasa.gov</dd><dt><span>Format :</span></dt><dd>NetCDF-4/HDF-5</dd><dt><span>SpatialCoverage :</span></dt><dd>global</dd><dt><span>VersionID :</span></dt><dd>5.12.4</dd><dt><span>TemporalRange :</span></dt><dd>1980-01-01 -&gt; 2016-12-31</dd><dt><span>identifier_product_doi_authority :</span></dt><dd>http://dx.doi.org/</dd><dt><span>ShortName :</span></dt><dd>M2T1NXFLX</dd><dt><span>GranuleID :</span></dt><dd>MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4</dd><dt><span>ProductionDateTime :</span></dt><dd>Original file generated: Sat May 31 17:44:24 2014 GMT</dd><dt><span>LongName :</span></dt><dd>MERRA2 tavg1_2d_flx_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Surface Flux Diagnostics</dd><dt><span>Title :</span></dt><dd>MERRA2 tavg1_2d_flx_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Surface Flux Diagnostics</dd><dt><span>SouthernmostLatitude :</span></dt><dd>-90.0</dd><dt><span>NorthernmostLatitude :</span></dt><dd>90.0</dd><dt><span>WesternmostLongitude :</span></dt><dd>-180.0</dd><dt><span>EasternmostLongitude :</span></dt><dd>179.375</dd><dt><span>LatitudeResolution :</span></dt><dd>0.5</dd><dt><span>LongitudeResolution :</span></dt><dd>0.625</dd><dt><span>DataResolution :</span></dt><dd>0.5 x 0.625</dd><dt><span>Contact :</span></dt><dd>http://gmao.gsfc.nasa.gov</dd><dt><span>identifier_product_doi :</span></dt><dd>10.5067/7MCPBJ41Y0K6</dd><dt><span>RangeBeginningDate :</span></dt><dd>1980-01-01</dd><dt><span>RangeBeginningTime :</span></dt><dd>00:00:00.000000</dd><dt><span>RangeEndingDate :</span></dt><dd>1980-01-01</dd><dt><span>RangeEndingTime :</span></dt><dd>23:59:59.000000</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>NCO :</span></dt><dd>netCDF Operators version 4.8.1 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)</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: 505, bnds: 2, lon: 576, lat: 361)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1980-01-01T12:00:00 ... 2022-01-01T12:00:00\n",
       "  * lon        (lon) float64 -180.0 -179.4 -178.8 -178.1 ... 178.1 178.8 179.4\n",
       "  * lat        (lat) float64 -90.0 -89.5 -89.0 -88.5 ... 88.5 89.0 89.5 90.0\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) datetime64[ns] ...\n",
       "    PRECTOT    (time, lat, lon) float32 ...\n",
       "Attributes: (12/34)\n",
       "    CDI:                               Climate Data Interface version 1.9.9rc...\n",
       "    history:                           Thu Jun 16 11:24:03 2022: cdo mergetim...\n",
       "    Conventions:                       CF-1\n",
       "    History:                           Original file generated: Sat May 31 17...\n",
       "    Comment:                           GMAO filename: d5124_m2_jan79.tavg1_2d...\n",
       "    Filename:                          MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4\n",
       "    ...                                ...\n",
       "    RangeBeginningTime:                00:00:00.000000\n",
       "    RangeEndingDate:                   1980-01-01\n",
       "    RangeEndingTime:                   23:59:59.000000\n",
       "    frequency:                         mon\n",
       "    NCO:                               netCDF Operators version 4.8.1 (Homepa...\n",
       "    CDO:                               Climate Data Operators version 1.9.9rc..."
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = xr.open_dataset('/home/mkibria/Academic/pr_of_thesis/reanalysis/MERRA/PRECTOT_MERRA2.tavg1_2m_flx_Nx.1980-2021.nc')\n",
    " \n",
    "\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "396c1435",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<xarray.IndexVariable 'time' (time: 505)>\n",
      "array(['1980-01-01T12:00:00.000000000', '1980-02-01T12:00:00.000000000',\n",
      "       '1980-03-01T12:00:00.000000000', ..., '2021-11-01T12:00:00.000000000',\n",
      "       '2021-12-01T12:00:00.000000000', '2022-01-01T12:00:00.000000000'],\n",
      "      dtype='datetime64[ns]')\n",
      "Attributes:\n",
      "    standard_name:  time\n",
      "    long_name:      time\n",
      "    bounds:         time_bnds\n",
      "    axis:           T\n",
      "<xarray.Variable (time: 505, bnds: 2)>\n",
      "array([['1980-01-01T00:30:00.000000000', '1980-01-31T23:30:00.000000000'],\n",
      "       ['1980-02-01T00:30:00.000000000', '1980-02-29T23:30:00.000000000'],\n",
      "       ['1980-03-01T00:30:00.000000000', '1980-03-31T23:30:00.000000000'],\n",
      "       ...,\n",
      "       ['2021-11-01T00:30:00.000000000', '2021-11-30T23:30:00.000000000'],\n",
      "       ['2021-12-01T00:30:00.000000000', '2021-12-31T23:30:00.000000000'],\n",
      "       ['2022-01-16T00:30:00.000000000', '2022-01-16T23:30:00.000000000']],\n",
      "      dtype='datetime64[ns]')\n",
      "<xarray.IndexVariable 'lon' (lon: 576)>\n",
      "array([-180.   , -179.375, -178.75 , ...,  178.125,  178.75 ,  179.375])\n",
      "Attributes:\n",
      "    standard_name:  longitude\n",
      "    long_name:      longitude\n",
      "    units:          degrees_east\n",
      "    axis:           X\n",
      "<xarray.IndexVariable 'lat' (lat: 361)>\n",
      "array([-90. , -89.5, -89. , ...,  89. ,  89.5,  90. ])\n",
      "Attributes:\n",
      "    standard_name:  latitude\n",
      "    long_name:      latitude\n",
      "    units:          degrees_north\n",
      "    axis:           Y\n",
      "<xarray.Variable (time: 505, lat: 361, lon: 576)>\n",
      "[105007680 values with dtype=float32]\n",
      "Attributes:\n",
      "    standard_name:   total_precipitation\n",
      "    long_name:       total_precipitation\n",
      "    units:           kg m-2 s-1\n",
      "    cell_methods:    time: mean\n",
      "    fmissing_value:  1000000000000000.0\n",
      "    vmax:            1000000000000000.0\n",
      "    vmin:            -1000000000000000.0\n"
     ]
    }
   ],
   "source": [
    "for v in data.variables.values():\n",
    "    print(v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "149f737b",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 430, bnds: 2, lon: 576, lat: 361)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1980-02-01T12:00:00 ... 2015-11-16\n",
       "  * lon        (lon) float64 -180.0 -179.4 -178.8 -178.1 ... 178.1 178.8 179.4\n",
       "  * lat        (lat) float64 -90.0 -89.5 -89.0 -88.5 ... 88.5 89.0 89.5 90.0\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) datetime64[ns] 1980-02-01T00:30:00 ... 2015-11-30...\n",
       "    PRECTOT    (time, lat, lon) float32 ...\n",
       "Attributes: (12/34)\n",
       "    CDI:                               Climate Data Interface version 1.9.9rc...\n",
       "    history:                           Thu Jun 16 11:24:03 2022: cdo mergetim...\n",
       "    Conventions:                       CF-1\n",
       "    History:                           Original file generated: Sat May 31 17...\n",
       "    Comment:                           GMAO filename: d5124_m2_jan79.tavg1_2d...\n",
       "    Filename:                          MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4\n",
       "    ...                                ...\n",
       "    RangeBeginningTime:                00:00:00.000000\n",
       "    RangeEndingDate:                   1980-01-01\n",
       "    RangeEndingTime:                   23:59:59.000000\n",
       "    frequency:                         mon\n",
       "    NCO:                               netCDF Operators version 4.8.1 (Homepa...\n",
       "    CDO:                               Climate Data Operators version 1.9.9rc...</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-dab0a0c7-09a4-4e54-9491-3b69d920619c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-dab0a0c7-09a4-4e54-9491-3b69d920619c' 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>: 430</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 576</li><li><span class='xr-has-index'>lat</span>: 361</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-405db114-1ff5-4443-9891-55ffc11b5ad4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-405db114-1ff5-4443-9891-55ffc11b5ad4' 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'>1980-02-01T12:00:00 ... 2015-11-16</div><input id='attrs-9f6dc40b-6f33-43b3-b720-e18eb59d1745' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f6dc40b-6f33-43b3-b720-e18eb59d1745' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4446585-5c27-45de-b92c-12b264e5869c' class='xr-var-data-in' type='checkbox'><label for='data-a4446585-5c27-45de-b92c-12b264e5869c' title='Show/Hide data 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([&#x27;1980-02-01T12:00:00.000000000&#x27;, &#x27;1980-03-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1980-04-16T00:00:00.000000000&#x27;, ..., &#x27;2015-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2015-10-16T12:00:00.000000000&#x27;, &#x27;2015-11-16T00:00:00.000000000&#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'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -179.4 ... 178.8 179.4</div><input id='attrs-7d9daa23-2fd6-43d9-af54-59431ddbafae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d9daa23-2fd6-43d9-af54-59431ddbafae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7720d6e8-9d9e-4f8d-a78d-ef4d933e1ae8' class='xr-var-data-in' type='checkbox'><label for='data-7720d6e8-9d9e-4f8d-a78d-ef4d933e1ae8' title='Show/Hide data 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([-180.   , -179.375, -178.75 , ...,  178.125,  178.75 ,  179.375])</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'>-90.0 -89.5 -89.0 ... 89.5 90.0</div><input id='attrs-20e7699c-3add-4ed6-af70-618f7b0273b7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-20e7699c-3add-4ed6-af70-618f7b0273b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4de348a-2fd4-45ec-9755-dc272aea6b78' class='xr-var-data-in' type='checkbox'><label for='data-e4de348a-2fd4-45ec-9755-dc272aea6b78' title='Show/Hide data 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([-90. , -89.5, -89. , ...,  89. ,  89.5,  90. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0d8991b9-8cdd-481e-9b66-e68b1b35e0e1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0d8991b9-8cdd-481e-9b66-e68b1b35e0e1' 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'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1980-02-01T00:30:00 ... 2015-11-...</div><input id='attrs-da8deac4-a6f7-45f2-9708-b0da5ad216d3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-da8deac4-a6f7-45f2-9708-b0da5ad216d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af9ec271-38fd-4d94-bfe8-c9a2676de33d' class='xr-var-data-in' type='checkbox'><label for='data-af9ec271-38fd-4d94-bfe8-c9a2676de33d' title='Show/Hide data 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;1980-02-01T00:30:00.000000000&#x27;, &#x27;1980-02-29T23:30:00.000000000&#x27;],\n",
       "       [&#x27;1980-03-01T00:30:00.000000000&#x27;, &#x27;1980-03-31T23:30:00.000000000&#x27;],\n",
       "       [&#x27;1980-04-01T00:30:00.000000000&#x27;, &#x27;1980-04-30T23:30:00.000000000&#x27;],\n",
       "       ...,\n",
       "       [&#x27;2015-09-01T00:30:00.000000000&#x27;, &#x27;2015-09-30T23:30:00.000000000&#x27;],\n",
       "       [&#x27;2015-10-01T00:30:00.000000000&#x27;, &#x27;2015-10-31T23:30:00.000000000&#x27;],\n",
       "       [&#x27;2015-11-01T00:30:00.000000000&#x27;, &#x27;2015-11-30T23:30:00.000000000&#x27;]],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRECTOT</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-111912f6-cd91-4a83-9bf6-e9bb2e794d6c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-111912f6-cd91-4a83-9bf6-e9bb2e794d6c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d517b5e-9214-4682-beb5-ae1fa218a308' class='xr-var-data-in' type='checkbox'><label for='data-0d517b5e-9214-4682-beb5-ae1fa218a308' title='Show/Hide data 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>total_precipitation</dd><dt><span>long_name :</span></dt><dd>total_precipitation</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>fmissing_value :</span></dt><dd>1000000000000000.0</dd><dt><span>vmax :</span></dt><dd>1000000000000000.0</dd><dt><span>vmin :</span></dt><dd>-1000000000000000.0</dd></dl></div><div class='xr-var-data'><pre>[89412480 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8e82b5bc-d0da-415b-8ea5-9748e5de10ed' class='xr-section-summary-in' type='checkbox'  ><label for='section-8e82b5bc-d0da-415b-8ea5-9748e5de10ed' class='xr-section-summary' >Attributes: <span>(34)</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>history :</span></dt><dd>Thu Jun 16 11:24:03 2022: cdo mergetime 198001PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198001.nc4 198002PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198002.nc4 198003PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198003.nc4 198004PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198004.nc4 198005PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198005.nc4 198006PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198006.nc4 198007PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198007.nc4 198008PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198008.nc4 198009PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198009.nc4 198010PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198010.nc4 198011PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198011.nc4 198012PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198012.nc4 198101PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198101.nc4 198102PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198102.nc4 198103PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198103.nc4 198104PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198104.nc4 198105PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198105.nc4 198106PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198106.nc4 198107PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198107.nc4 198108PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198108.nc4 198109PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198109.nc4 198110PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198110.nc4 198111PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198111.nc4 198112PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198112.nc4 198201PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198201.nc4 198202PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198202.nc4 198203PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198203.nc4 198204PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198204.nc4 198205PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198205.nc4 198206PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198206.nc4 198207PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198207.nc4 198208PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198208.nc4 198209PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198209.nc4 198210PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198210.nc4 198211PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198211.nc4 198212PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198212.nc4 198301PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198301.nc4 198302PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198302.nc4 198303PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198303.nc4 198304PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198304.nc4 198305PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198305.nc4 198306PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198306.nc4 198307PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198307.nc4 198308PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198308.nc4 198309PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198309.nc4 198310PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198310.nc4 198311PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198311.nc4 198312PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198312.nc4 198401PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198401.nc4 198402PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198402.nc4 198403PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198403.nc4 198404PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198404.nc4 198405PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198405.nc4 198406PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198406.nc4 198407PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198407.nc4 198408PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198408.nc4 198409PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198409.nc4 198410PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198410.nc4 198411PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198411.nc4 198412PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198412.nc4 198501PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198501.nc4 198502PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198502.nc4 198503PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198503.nc4 198504PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198504.nc4 198505PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198505.nc4 198506PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198506.nc4 198507PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198507.nc4 198508PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198508.nc4 198509PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198509.nc4 198510PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198510.nc4 198511PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198511.nc4 198512PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198512.nc4 198601PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198601.nc4 198602PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198602.nc4 198603PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198603.nc4 198604PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198604.nc4 198605PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198605.nc4 198606PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198606.nc4 198607PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198607.nc4 198608PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198608.nc4 198609PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198609.nc4 198610PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198610.nc4 198611PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198611.nc4 198612PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198612.nc4 198701PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198701.nc4 198702PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198702.nc4 198703PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198703.nc4 198704PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198704.nc4 198705PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198705.nc4 198706PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198706.nc4 198707PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198707.nc4 198708PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198708.nc4 198709PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198709.nc4 198710PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198710.nc4 198711PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198711.nc4 198712PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198712.nc4 198801PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198801.nc4 198802PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198802.nc4 198803PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198803.nc4 198804PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198804.nc4 198805PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198805.nc4 198806PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198806.nc4 198807PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198807.nc4 198808PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198808.nc4 198809PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198809.nc4 198810PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198810.nc4 198811PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198811.nc4 198812PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198812.nc4 198901PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198901.nc4 198902PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198902.nc4 198903PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198903.nc4 198904PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198904.nc4 198905PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198905.nc4 198906PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198906.nc4 198907PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198907.nc4 198908PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198908.nc4 198909PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198909.nc4 198910PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198910.nc4 198911PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198911.nc4 198912PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198912.nc4 199001PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199001.nc4 199002PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199002.nc4 199003PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199003.nc4 199004PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199004.nc4 199005PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199005.nc4 199006PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199006.nc4 199007PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199007.nc4 199008PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199008.nc4 199009PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199009.nc4 199010PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199010.nc4 199011PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199011.nc4 199012PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199012.nc4 199101PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199101.nc4 199102PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199102.nc4 199103PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199103.nc4 199104PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199104.nc4 199105PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199105.nc4 199106PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199106.nc4 199107PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199107.nc4 199108PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199108.nc4 199109PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199109.nc4 199110PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199110.nc4 199111PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199111.nc4 199112PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.199112.nc4 199201PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199201.nc4 199202PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199202.nc4 199203PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199203.nc4 199204PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199204.nc4 199205PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199205.nc4 199206PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199206.nc4 199207PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199207.nc4 199208PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199208.nc4 199209PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199209.nc4 199210PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199210.nc4 199211PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199211.nc4 199212PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199212.nc4 199301PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199301.nc4 199302PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199302.nc4 199303PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199303.nc4 199304PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199304.nc4 199305PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199305.nc4 199306PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199306.nc4 199307PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199307.nc4 199308PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199308.nc4 199309PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199309.nc4 199310PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199310.nc4 199311PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199311.nc4 199312PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199312.nc4 199401PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199401.nc4 199402PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199402.nc4 199403PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199403.nc4 199404PRECTOT_MERRA2_200.tavg1_2d_flx_Nx.199404.nc4 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201305PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201305.nc4 201306PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201306.nc4 201307PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201307.nc4 201308PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201308.nc4 201309PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201309.nc4 201310PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201310.nc4 201311PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201311.nc4 201312PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201312.nc4 201401PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201401.nc4 201402PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201402.nc4 201403PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201403.nc4 201404PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201404.nc4 201405PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201405.nc4 201406PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201406.nc4 201407PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201407.nc4 201408PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201408.nc4 201409PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201409.nc4 201410PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201410.nc4 201411PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201411.nc4 201412PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201412.nc4 201501PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201501.nc4 201502PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201502.nc4 201503PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201503.nc4 201504PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201504.nc4 201505PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201505.nc4 201506PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201506.nc4 201507PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201507.nc4 201508PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201508.nc4 201509PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201509.nc4 201510PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201510.nc4 201511PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201511.nc4 201512PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201512.nc4 201601PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201601.nc4 201602PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201602.nc4 201603PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201603.nc4 201604PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201604.nc4 201605PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201605.nc4 201606PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201606.nc4 201607PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201607.nc4 201608PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201608.nc4 201609PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201609.nc4 201610PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201610.nc4 201611PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201611.nc4 201612PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201612.nc4 201701PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201701.nc4 201702PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201702.nc4 201703PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201703.nc4 201704PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201704.nc4 201705PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201705.nc4 201706PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201706.nc4 201707PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201707.nc4 201708PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201708.nc4 201709PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201709.nc4 201710PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201710.nc4 201711PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201711.nc4 201712PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201712.nc4 201801PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201801.nc4 201802PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201802.nc4 201803PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201803.nc4 201804PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201804.nc4 201805PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201805.nc4 201806PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201806.nc4 201807PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201807.nc4 201808PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201808.nc4 201809PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201809.nc4 201810PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201810.nc4 201811PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201811.nc4 201812PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201812.nc4 201901PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201901.nc4 201902PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201902.nc4 201903PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201903.nc4 201904PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201904.nc4 201905PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201905.nc4 201906PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201906.nc4 201907PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201907.nc4 201908PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201908.nc4 201909PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201909.nc4 201910PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201910.nc4 201911PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201911.nc4 201912PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201912.nc4 202001PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202001.nc4 202002PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202002.nc4 202003PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202003.nc4 202004PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202004.nc4 202005PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202005.nc4 202006PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202006.nc4 202007PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202007.nc4 202008PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202008.nc4 202009PRECTOT_MERRA2_401.tavg1_2d_flx_Nx.202009.nc4 202010PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202010.nc4 202011PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202011.nc4 202012PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202012.nc4 202101PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202101.nc4 202102PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202102.nc4 202103PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202103.nc4 202104PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202104.nc4 202105PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202105.nc4 202106PRECTOT_MERRA2_401.tavg1_2d_flx_Nx.202106.nc4 202107PRECTOT_MERRA2_401.tavg1_2d_flx_Nx.202107.nc4 202108PRECTOT_MERRA2_401.tavg1_2d_flx_Nx.202108.nc4 202109PRECTOT_MERRA2_401.tavg1_2d_flx_Nx.202109.nc4 202110PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202110.nc4 202111PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202111.nc4 202112PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202112.nc4 202201PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202201.nc ..//../monthly/PRECTOT_MERRA2.tavg1_2m_flx_Nx.1980-2021.nc\n",
       "Thu Jun 16 11:14:20 2022: cdo monavg ./1980/PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198001.nc4 tmp/PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198001.nc4\n",
       "Tue Mar  1 13:15:53 2022: ncrcat PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800102.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800103.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800104.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800105.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800106.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800107.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800108.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800109.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800110.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800111.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800112.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800113.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800114.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800115.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800116.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800117.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800118.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800119.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800120.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800121.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800122.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800123.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800124.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800125.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800126.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800127.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800128.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800129.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800130.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800131.nc4 1980/PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198001.nc\n",
       "Tue Mar 01 12:51:15 2022: cdo -f nc4 -z zip_3 -L dayavg -selvar,PRECTOT MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4</dd><dt><span>Conventions :</span></dt><dd>CF-1</dd><dt><span>History :</span></dt><dd>Original file generated: Sat May 31 17:44:24 2014 GMT</dd><dt><span>Comment :</span></dt><dd>GMAO filename: d5124_m2_jan79.tavg1_2d_flx_Nx.19800101.nc4</dd><dt><span>Filename :</span></dt><dd>MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4</dd><dt><span>Institution :</span></dt><dd>NASA Global Modeling and Assimilation Office</dd><dt><span>References :</span></dt><dd>http://gmao.gsfc.nasa.gov</dd><dt><span>Format :</span></dt><dd>NetCDF-4/HDF-5</dd><dt><span>SpatialCoverage :</span></dt><dd>global</dd><dt><span>VersionID :</span></dt><dd>5.12.4</dd><dt><span>TemporalRange :</span></dt><dd>1980-01-01 -&gt; 2016-12-31</dd><dt><span>identifier_product_doi_authority :</span></dt><dd>http://dx.doi.org/</dd><dt><span>ShortName :</span></dt><dd>M2T1NXFLX</dd><dt><span>GranuleID :</span></dt><dd>MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4</dd><dt><span>ProductionDateTime :</span></dt><dd>Original file generated: Sat May 31 17:44:24 2014 GMT</dd><dt><span>LongName :</span></dt><dd>MERRA2 tavg1_2d_flx_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Surface Flux Diagnostics</dd><dt><span>Title :</span></dt><dd>MERRA2 tavg1_2d_flx_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Surface Flux Diagnostics</dd><dt><span>SouthernmostLatitude :</span></dt><dd>-90.0</dd><dt><span>NorthernmostLatitude :</span></dt><dd>90.0</dd><dt><span>WesternmostLongitude :</span></dt><dd>-180.0</dd><dt><span>EasternmostLongitude :</span></dt><dd>179.375</dd><dt><span>LatitudeResolution :</span></dt><dd>0.5</dd><dt><span>LongitudeResolution :</span></dt><dd>0.625</dd><dt><span>DataResolution :</span></dt><dd>0.5 x 0.625</dd><dt><span>Contact :</span></dt><dd>http://gmao.gsfc.nasa.gov</dd><dt><span>identifier_product_doi :</span></dt><dd>10.5067/7MCPBJ41Y0K6</dd><dt><span>RangeBeginningDate :</span></dt><dd>1980-01-01</dd><dt><span>RangeBeginningTime :</span></dt><dd>00:00:00.000000</dd><dt><span>RangeEndingDate :</span></dt><dd>1980-01-01</dd><dt><span>RangeEndingTime :</span></dt><dd>23:59:59.000000</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>NCO :</span></dt><dd>netCDF Operators version 4.8.1 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)</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: 430, bnds: 2, lon: 576, lat: 361)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1980-02-01T12:00:00 ... 2015-11-16\n",
       "  * lon        (lon) float64 -180.0 -179.4 -178.8 -178.1 ... 178.1 178.8 179.4\n",
       "  * lat        (lat) float64 -90.0 -89.5 -89.0 -88.5 ... 88.5 89.0 89.5 90.0\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) datetime64[ns] 1980-02-01T00:30:00 ... 2015-11-30...\n",
       "    PRECTOT    (time, lat, lon) float32 ...\n",
       "Attributes: (12/34)\n",
       "    CDI:                               Climate Data Interface version 1.9.9rc...\n",
       "    history:                           Thu Jun 16 11:24:03 2022: cdo mergetim...\n",
       "    Conventions:                       CF-1\n",
       "    History:                           Original file generated: Sat May 31 17...\n",
       "    Comment:                           GMAO filename: d5124_m2_jan79.tavg1_2d...\n",
       "    Filename:                          MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4\n",
       "    ...                                ...\n",
       "    RangeBeginningTime:                00:00:00.000000\n",
       "    RangeEndingDate:                   1980-01-01\n",
       "    RangeEndingTime:                   23:59:59.000000\n",
       "    frequency:                         mon\n",
       "    NCO:                               netCDF Operators version 4.8.1 (Homepa...\n",
       "    CDO:                               Climate Data Operators version 1.9.9rc..."
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#to select the year from 1980 to 2015\n",
    "data = data.sel(time=slice('1980-01-16T12:00:00.000000000','2015-12-16T00:00:00.000000000'))\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "66f463e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 144, bnds: 2, lon: 576, lat: 361)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1980-06-16 ... 2015-09-16\n",
       "  * lon        (lon) float64 -180.0 -179.4 -178.8 -178.1 ... 178.1 178.8 179.4\n",
       "  * lat        (lat) float64 -90.0 -89.5 -89.0 -88.5 ... 88.5 89.0 89.5 90.0\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) datetime64[ns] 1980-06-01T00:30:00 ... 2015-09-30...\n",
       "    PRECTOT    (time, lat, lon) float32 ...\n",
       "Attributes: (12/34)\n",
       "    CDI:                               Climate Data Interface version 1.9.9rc...\n",
       "    history:                           Thu Jun 16 11:24:03 2022: cdo mergetim...\n",
       "    Conventions:                       CF-1\n",
       "    History:                           Original file generated: Sat May 31 17...\n",
       "    Comment:                           GMAO filename: d5124_m2_jan79.tavg1_2d...\n",
       "    Filename:                          MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4\n",
       "    ...                                ...\n",
       "    RangeBeginningTime:                00:00:00.000000\n",
       "    RangeEndingDate:                   1980-01-01\n",
       "    RangeEndingTime:                   23:59:59.000000\n",
       "    frequency:                         mon\n",
       "    NCO:                               netCDF Operators version 4.8.1 (Homepa...\n",
       "    CDO:                               Climate Data Operators version 1.9.9rc...</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-03550104-dac4-498c-9978-fd1d8e6c2012' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-03550104-dac4-498c-9978-fd1d8e6c2012' 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>: 144</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 576</li><li><span class='xr-has-index'>lat</span>: 361</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-109b23de-f7cc-4e47-b9df-e0f619bc96cb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-109b23de-f7cc-4e47-b9df-e0f619bc96cb' 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'>1980-06-16 ... 2015-09-16</div><input id='attrs-70e1566d-048e-4776-85d8-8353aea1b914' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-70e1566d-048e-4776-85d8-8353aea1b914' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1fdc6973-57cd-4312-9755-71f36a07b705' class='xr-var-data-in' type='checkbox'><label for='data-1fdc6973-57cd-4312-9755-71f36a07b705' title='Show/Hide data 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([&#x27;1980-06-16T00:00:00.000000000&#x27;, &#x27;1980-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1980-08-01T12:00:00.000000000&#x27;, &#x27;1980-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-06-01T12:00:00.000000000&#x27;, &#x27;1981-07-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1981-08-01T12:00:00.000000000&#x27;, &#x27;1981-09-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1982-06-01T12:00:00.000000000&#x27;, &#x27;1982-07-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1982-08-01T12:00:00.000000000&#x27;, &#x27;1982-09-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1983-06-01T12:00:00.000000000&#x27;, &#x27;1983-07-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1983-08-01T12:00:00.000000000&#x27;, &#x27;1983-09-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1984-06-01T12:00:00.000000000&#x27;, &#x27;1984-07-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1984-08-01T12:00:00.000000000&#x27;, &#x27;1984-09-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1985-06-01T12:00:00.000000000&#x27;, &#x27;1985-07-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1985-08-01T12:00:00.000000000&#x27;, &#x27;1985-09-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1986-06-01T12:00:00.000000000&#x27;, &#x27;1986-07-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1986-08-01T12:00:00.000000000&#x27;, &#x27;1986-09-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1987-06-01T12:00:00.000000000&#x27;, &#x27;1987-07-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1987-08-01T12:00:00.000000000&#x27;, &#x27;1987-09-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1988-06-01T12:00:00.000000000&#x27;, &#x27;1988-07-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1988-08-01T12:00:00.000000000&#x27;, &#x27;1988-09-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1989-06-01T12:00:00.000000000&#x27;, &#x27;1989-07-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1989-08-01T12:00:00.000000000&#x27;, &#x27;1989-09-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1990-06-01T12:00:00.000000000&#x27;, &#x27;1990-07-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1990-08-01T12:00:00.000000000&#x27;, &#x27;1990-09-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1991-06-01T12:00:00.000000000&#x27;, &#x27;1991-07-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1991-08-01T12:00:00.000000000&#x27;, &#x27;1991-09-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1992-06-01T12:00:00.000000000&#x27;, &#x27;1992-07-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1992-08-01T12:00:00.000000000&#x27;, &#x27;1992-09-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1993-06-01T12:00:00.000000000&#x27;, &#x27;1993-07-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1993-08-01T12:00:00.000000000&#x27;, &#x27;1993-09-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1994-06-01T12:00:00.000000000&#x27;, &#x27;1994-07-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1994-08-01T12:00:00.000000000&#x27;, &#x27;1994-09-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1995-06-01T12:00:00.000000000&#x27;, &#x27;1995-07-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1995-08-01T12:00:00.000000000&#x27;, &#x27;1995-09-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1996-06-01T12:00:00.000000000&#x27;, &#x27;1996-07-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1996-08-01T12:00:00.000000000&#x27;, &#x27;1996-09-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1997-06-01T12:00:00.000000000&#x27;, &#x27;1997-07-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1997-08-01T12:00:00.000000000&#x27;, &#x27;1997-09-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1998-06-01T12:00:00.000000000&#x27;, &#x27;1998-07-01T12:00:00.000000000&#x27;,\n",
       "       &#x27;1998-08-01T12:00:00.000000000&#x27;, &#x27;1998-09-01T12:00:00.000000000&#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",
       "       &#x27;2006-06-16T00:00:00.000000000&#x27;, &#x27;2006-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2006-08-16T12:00:00.000000000&#x27;, &#x27;2006-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2007-06-16T00:00:00.000000000&#x27;, &#x27;2007-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2007-08-16T12:00:00.000000000&#x27;, &#x27;2007-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2008-06-16T00:00:00.000000000&#x27;, &#x27;2008-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2008-08-16T12:00:00.000000000&#x27;, &#x27;2008-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2009-06-16T00:00:00.000000000&#x27;, &#x27;2009-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2009-08-16T12:00:00.000000000&#x27;, &#x27;2009-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2010-06-16T00:00:00.000000000&#x27;, &#x27;2010-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2010-08-16T12:00:00.000000000&#x27;, &#x27;2010-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-06-16T00:00:00.000000000&#x27;, &#x27;2011-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2011-08-16T12:00:00.000000000&#x27;, &#x27;2011-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-06-15T12:00:00.000000000&#x27;, &#x27;2012-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2012-08-16T12:00:00.000000000&#x27;, &#x27;2012-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-06-16T00:00:00.000000000&#x27;, &#x27;2013-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2013-08-16T12:00:00.000000000&#x27;, &#x27;2013-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2014-06-16T00:00:00.000000000&#x27;, &#x27;2014-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2014-08-16T12:00:00.000000000&#x27;, &#x27;2014-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2015-06-16T00:00:00.000000000&#x27;, &#x27;2015-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2015-08-16T12:00:00.000000000&#x27;, &#x27;2015-09-16T00:00:00.000000000&#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'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -179.4 ... 178.8 179.4</div><input id='attrs-7a4be48c-fa15-4ea2-8c7f-dec3cb0dbd38' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a4be48c-fa15-4ea2-8c7f-dec3cb0dbd38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c6c2e09-8424-4169-a795-323331996b31' class='xr-var-data-in' type='checkbox'><label for='data-1c6c2e09-8424-4169-a795-323331996b31' title='Show/Hide data 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([-180.   , -179.375, -178.75 , ...,  178.125,  178.75 ,  179.375])</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'>-90.0 -89.5 -89.0 ... 89.5 90.0</div><input id='attrs-cfb0af4d-8ba6-478a-93ee-785750099de7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cfb0af4d-8ba6-478a-93ee-785750099de7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d64fa37f-1352-47e9-8109-62339e41eab1' class='xr-var-data-in' type='checkbox'><label for='data-d64fa37f-1352-47e9-8109-62339e41eab1' title='Show/Hide data 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([-90. , -89.5, -89. , ...,  89. ,  89.5,  90. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3b0a7712-ce98-43f6-b351-099a86f64f1a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3b0a7712-ce98-43f6-b351-099a86f64f1a' 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'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1980-06-01T00:30:00 ... 2015-09-...</div><input id='attrs-98208dd7-041f-454b-a705-fdba5b1da546' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-98208dd7-041f-454b-a705-fdba5b1da546' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4beffd3a-f4b7-4a5e-8a0f-383138cf0dcf' class='xr-var-data-in' type='checkbox'><label for='data-4beffd3a-f4b7-4a5e-8a0f-383138cf0dcf' title='Show/Hide data 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;1980-06-01T00:30:00.000000000&#x27;, &#x27;1980-06-30T23:30:00.000000000&#x27;],\n",
       "       [&#x27;1980-07-01T00:30:00.000000000&#x27;, &#x27;1980-07-31T23:30:00.000000000&#x27;],\n",
       "       [&#x27;1980-08-01T00:30:00.000000000&#x27;, &#x27;1980-08-31T23:30:00.000000000&#x27;],\n",
       "       ...,\n",
       "       [&#x27;2015-07-01T00:30:00.000000000&#x27;, &#x27;2015-07-31T23:30:00.000000000&#x27;],\n",
       "       [&#x27;2015-08-01T00:30:00.000000000&#x27;, &#x27;2015-08-31T23:30:00.000000000&#x27;],\n",
       "       [&#x27;2015-09-01T00:30:00.000000000&#x27;, &#x27;2015-09-30T23:30:00.000000000&#x27;]],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRECTOT</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-015a51bc-b015-42b1-a7b0-7e3fbbda5e2e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-015a51bc-b015-42b1-a7b0-7e3fbbda5e2e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c2b1e76-c7cf-4125-8517-ead2b822f525' class='xr-var-data-in' type='checkbox'><label for='data-8c2b1e76-c7cf-4125-8517-ead2b822f525' title='Show/Hide data 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>total_precipitation</dd><dt><span>long_name :</span></dt><dd>total_precipitation</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>fmissing_value :</span></dt><dd>1000000000000000.0</dd><dt><span>vmax :</span></dt><dd>1000000000000000.0</dd><dt><span>vmin :</span></dt><dd>-1000000000000000.0</dd></dl></div><div class='xr-var-data'><pre>[29942784 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-19deef54-fd5b-4cbe-89c6-a6e0d4d28092' class='xr-section-summary-in' type='checkbox'  ><label for='section-19deef54-fd5b-4cbe-89c6-a6e0d4d28092' class='xr-section-summary' >Attributes: <span>(34)</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>history :</span></dt><dd>Thu Jun 16 11:24:03 2022: cdo mergetime 198001PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198001.nc4 198002PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198002.nc4 198003PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198003.nc4 198004PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198004.nc4 198005PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198005.nc4 198006PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198006.nc4 198007PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198007.nc4 198008PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198008.nc4 198009PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198009.nc4 198010PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198010.nc4 198011PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198011.nc4 198012PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198012.nc4 198101PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198101.nc4 198102PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198102.nc4 198103PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198103.nc4 198104PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198104.nc4 198105PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198105.nc4 198106PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198106.nc4 198107PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198107.nc4 198108PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198108.nc4 198109PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198109.nc4 198110PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198110.nc4 198111PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198111.nc4 198112PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198112.nc4 198201PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198201.nc4 198202PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198202.nc4 198203PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198203.nc4 198204PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198204.nc4 198205PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198205.nc4 198206PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198206.nc4 198207PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198207.nc4 198208PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198208.nc4 198209PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198209.nc4 198210PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198210.nc4 198211PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198211.nc4 198212PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198212.nc4 198301PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198301.nc4 198302PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198302.nc4 198303PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198303.nc4 198304PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198304.nc4 198305PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198305.nc4 198306PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198306.nc4 198307PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198307.nc4 198308PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198308.nc4 198309PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198309.nc4 198310PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198310.nc4 198311PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198311.nc4 198312PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198312.nc4 198401PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198401.nc4 198402PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198402.nc4 198403PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198403.nc4 198404PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198404.nc4 198405PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198405.nc4 198406PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198406.nc4 198407PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198407.nc4 198408PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198408.nc4 198409PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198409.nc4 198410PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198410.nc4 198411PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198411.nc4 198412PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198412.nc4 198501PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198501.nc4 198502PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198502.nc4 198503PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198503.nc4 198504PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198504.nc4 198505PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198505.nc4 198506PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198506.nc4 198507PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198507.nc4 198508PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198508.nc4 198509PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198509.nc4 198510PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198510.nc4 198511PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198511.nc4 198512PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198512.nc4 198601PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198601.nc4 198602PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198602.nc4 198603PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198603.nc4 198604PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198604.nc4 198605PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198605.nc4 198606PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198606.nc4 198607PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198607.nc4 198608PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198608.nc4 198609PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198609.nc4 198610PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198610.nc4 198611PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198611.nc4 198612PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198612.nc4 198701PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198701.nc4 198702PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198702.nc4 198703PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198703.nc4 198704PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198704.nc4 198705PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198705.nc4 198706PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198706.nc4 198707PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198707.nc4 198708PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198708.nc4 198709PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198709.nc4 198710PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198710.nc4 198711PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198711.nc4 198712PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198712.nc4 198801PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198801.nc4 198802PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198802.nc4 198803PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198803.nc4 198804PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198804.nc4 198805PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198805.nc4 198806PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198806.nc4 198807PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198807.nc4 198808PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198808.nc4 198809PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198809.nc4 198810PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198810.nc4 198811PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198811.nc4 198812PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198812.nc4 198901PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198901.nc4 198902PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198902.nc4 198903PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198903.nc4 198904PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198904.nc4 198905PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198905.nc4 198906PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198906.nc4 198907PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198907.nc4 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201003PRECTOT_MERRA2_300.tavg1_2d_flx_Nx.201003.nc4 201004PRECTOT_MERRA2_300.tavg1_2d_flx_Nx.201004.nc4 201005PRECTOT_MERRA2_300.tavg1_2d_flx_Nx.201005.nc4 201006PRECTOT_MERRA2_300.tavg1_2d_flx_Nx.201006.nc4 201007PRECTOT_MERRA2_300.tavg1_2d_flx_Nx.201007.nc4 201008PRECTOT_MERRA2_300.tavg1_2d_flx_Nx.201008.nc4 201009PRECTOT_MERRA2_300.tavg1_2d_flx_Nx.201009.nc4 201010PRECTOT_MERRA2_300.tavg1_2d_flx_Nx.201010.nc4 201011PRECTOT_MERRA2_300.tavg1_2d_flx_Nx.201011.nc4 201012PRECTOT_MERRA2_300.tavg1_2d_flx_Nx.201012.nc4 201101PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201101.nc4 201102PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201102.nc4 201103PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201103.nc4 201104PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201104.nc4 201105PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201105.nc4 201106PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201106.nc4 201107PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201107.nc4 201108PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201108.nc4 201109PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201109.nc4 201110PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201110.nc4 201111PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201111.nc4 201112PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201112.nc4 201201PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201201.nc4 201202PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201202.nc4 201203PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201203.nc4 201204PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201204.nc4 201205PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201205.nc4 201206PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201206.nc4 201207PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201207.nc4 201208PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201208.nc4 201209PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201209.nc4 201210PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201210.nc4 201211PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201211.nc4 201212PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201212.nc4 201301PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201301.nc4 201302PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201302.nc4 201303PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201303.nc4 201304PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201304.nc4 201305PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201305.nc4 201306PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201306.nc4 201307PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201307.nc4 201308PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201308.nc4 201309PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201309.nc4 201310PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201310.nc4 201311PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201311.nc4 201312PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201312.nc4 201401PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201401.nc4 201402PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201402.nc4 201403PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201403.nc4 201404PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201404.nc4 201405PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201405.nc4 201406PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201406.nc4 201407PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201407.nc4 201408PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201408.nc4 201409PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201409.nc4 201410PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201410.nc4 201411PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201411.nc4 201412PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201412.nc4 201501PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201501.nc4 201502PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201502.nc4 201503PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201503.nc4 201504PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201504.nc4 201505PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201505.nc4 201506PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201506.nc4 201507PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201507.nc4 201508PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201508.nc4 201509PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201509.nc4 201510PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201510.nc4 201511PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201511.nc4 201512PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201512.nc4 201601PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201601.nc4 201602PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201602.nc4 201603PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201603.nc4 201604PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201604.nc4 201605PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201605.nc4 201606PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201606.nc4 201607PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201607.nc4 201608PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201608.nc4 201609PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201609.nc4 201610PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201610.nc4 201611PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201611.nc4 201612PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201612.nc4 201701PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201701.nc4 201702PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201702.nc4 201703PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201703.nc4 201704PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201704.nc4 201705PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201705.nc4 201706PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201706.nc4 201707PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201707.nc4 201708PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201708.nc4 201709PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201709.nc4 201710PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201710.nc4 201711PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201711.nc4 201712PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201712.nc4 201801PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201801.nc4 201802PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201802.nc4 201803PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201803.nc4 201804PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201804.nc4 201805PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201805.nc4 201806PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201806.nc4 201807PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201807.nc4 201808PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201808.nc4 201809PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201809.nc4 201810PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201810.nc4 201811PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201811.nc4 201812PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201812.nc4 201901PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201901.nc4 201902PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201902.nc4 201903PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201903.nc4 201904PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201904.nc4 201905PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201905.nc4 201906PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201906.nc4 201907PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201907.nc4 201908PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201908.nc4 201909PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201909.nc4 201910PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201910.nc4 201911PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201911.nc4 201912PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.201912.nc4 202001PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202001.nc4 202002PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202002.nc4 202003PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202003.nc4 202004PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202004.nc4 202005PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202005.nc4 202006PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202006.nc4 202007PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202007.nc4 202008PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202008.nc4 202009PRECTOT_MERRA2_401.tavg1_2d_flx_Nx.202009.nc4 202010PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202010.nc4 202011PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202011.nc4 202012PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202012.nc4 202101PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202101.nc4 202102PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202102.nc4 202103PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202103.nc4 202104PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202104.nc4 202105PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202105.nc4 202106PRECTOT_MERRA2_401.tavg1_2d_flx_Nx.202106.nc4 202107PRECTOT_MERRA2_401.tavg1_2d_flx_Nx.202107.nc4 202108PRECTOT_MERRA2_401.tavg1_2d_flx_Nx.202108.nc4 202109PRECTOT_MERRA2_401.tavg1_2d_flx_Nx.202109.nc4 202110PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202110.nc4 202111PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202111.nc4 202112PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202112.nc4 202201PRECTOT_MERRA2_400.tavg1_2d_flx_Nx.202201.nc ..//../monthly/PRECTOT_MERRA2.tavg1_2m_flx_Nx.1980-2021.nc\n",
       "Thu Jun 16 11:14:20 2022: cdo monavg ./1980/PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198001.nc4 tmp/PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198001.nc4\n",
       "Tue Mar  1 13:15:53 2022: ncrcat PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800102.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800103.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800104.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800105.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800106.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800107.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800108.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800109.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800110.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800111.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800112.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800113.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800114.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800115.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800116.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800117.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800118.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800119.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800120.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800121.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800122.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800123.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800124.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800125.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800126.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800127.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800128.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800129.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800130.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800131.nc4 1980/PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.198001.nc\n",
       "Tue Mar 01 12:51:15 2022: cdo -f nc4 -z zip_3 -L dayavg -selvar,PRECTOT MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4 PRECTOT_MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4</dd><dt><span>Conventions :</span></dt><dd>CF-1</dd><dt><span>History :</span></dt><dd>Original file generated: Sat May 31 17:44:24 2014 GMT</dd><dt><span>Comment :</span></dt><dd>GMAO filename: d5124_m2_jan79.tavg1_2d_flx_Nx.19800101.nc4</dd><dt><span>Filename :</span></dt><dd>MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4</dd><dt><span>Institution :</span></dt><dd>NASA Global Modeling and Assimilation Office</dd><dt><span>References :</span></dt><dd>http://gmao.gsfc.nasa.gov</dd><dt><span>Format :</span></dt><dd>NetCDF-4/HDF-5</dd><dt><span>SpatialCoverage :</span></dt><dd>global</dd><dt><span>VersionID :</span></dt><dd>5.12.4</dd><dt><span>TemporalRange :</span></dt><dd>1980-01-01 -&gt; 2016-12-31</dd><dt><span>identifier_product_doi_authority :</span></dt><dd>http://dx.doi.org/</dd><dt><span>ShortName :</span></dt><dd>M2T1NXFLX</dd><dt><span>GranuleID :</span></dt><dd>MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4</dd><dt><span>ProductionDateTime :</span></dt><dd>Original file generated: Sat May 31 17:44:24 2014 GMT</dd><dt><span>LongName :</span></dt><dd>MERRA2 tavg1_2d_flx_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Surface Flux Diagnostics</dd><dt><span>Title :</span></dt><dd>MERRA2 tavg1_2d_flx_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Surface Flux Diagnostics</dd><dt><span>SouthernmostLatitude :</span></dt><dd>-90.0</dd><dt><span>NorthernmostLatitude :</span></dt><dd>90.0</dd><dt><span>WesternmostLongitude :</span></dt><dd>-180.0</dd><dt><span>EasternmostLongitude :</span></dt><dd>179.375</dd><dt><span>LatitudeResolution :</span></dt><dd>0.5</dd><dt><span>LongitudeResolution :</span></dt><dd>0.625</dd><dt><span>DataResolution :</span></dt><dd>0.5 x 0.625</dd><dt><span>Contact :</span></dt><dd>http://gmao.gsfc.nasa.gov</dd><dt><span>identifier_product_doi :</span></dt><dd>10.5067/7MCPBJ41Y0K6</dd><dt><span>RangeBeginningDate :</span></dt><dd>1980-01-01</dd><dt><span>RangeBeginningTime :</span></dt><dd>00:00:00.000000</dd><dt><span>RangeEndingDate :</span></dt><dd>1980-01-01</dd><dt><span>RangeEndingTime :</span></dt><dd>23:59:59.000000</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>NCO :</span></dt><dd>netCDF Operators version 4.8.1 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)</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: 144, bnds: 2, lon: 576, lat: 361)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1980-06-16 ... 2015-09-16\n",
       "  * lon        (lon) float64 -180.0 -179.4 -178.8 -178.1 ... 178.1 178.8 179.4\n",
       "  * lat        (lat) float64 -90.0 -89.5 -89.0 -88.5 ... 88.5 89.0 89.5 90.0\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) datetime64[ns] 1980-06-01T00:30:00 ... 2015-09-30...\n",
       "    PRECTOT    (time, lat, lon) float32 ...\n",
       "Attributes: (12/34)\n",
       "    CDI:                               Climate Data Interface version 1.9.9rc...\n",
       "    history:                           Thu Jun 16 11:24:03 2022: cdo mergetim...\n",
       "    Conventions:                       CF-1\n",
       "    History:                           Original file generated: Sat May 31 17...\n",
       "    Comment:                           GMAO filename: d5124_m2_jan79.tavg1_2d...\n",
       "    Filename:                          MERRA2_100.tavg1_2d_flx_Nx.19800101.nc4\n",
       "    ...                                ...\n",
       "    RangeBeginningTime:                00:00:00.000000\n",
       "    RangeEndingDate:                   1980-01-01\n",
       "    RangeEndingTime:                   23:59:59.000000\n",
       "    frequency:                         mon\n",
       "    NCO:                               netCDF Operators version 4.8.1 (Homepa...\n",
       "    CDO:                               Climate Data Operators version 1.9.9rc..."
      ]
     },
     "execution_count": 5,
     "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": 6,
   "id": "1b40f47b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#to select the x and y coordinates\n",
    "#jjas_data = jjas_data.sel(lon=slice(85.0,96.0),lat=slice(18.0,29.0))\n",
    "#jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c8ca89be",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;PRECTOT&#x27; (lat: 361, lon: 576)&gt;\n",
       "array([[1.90493563e-06, 1.90493563e-06, 1.90493563e-06, ...,\n",
       "        1.90493563e-06, 1.90493563e-06, 1.90493563e-06],\n",
       "       [2.01234207e-06, 2.01548914e-06, 2.01861894e-06, ...,\n",
       "        2.00282830e-06, 2.00601448e-06, 2.00918362e-06],\n",
       "       [2.01164153e-06, 2.01833882e-06, 2.02513843e-06, ...,\n",
       "        1.99213514e-06, 1.99853912e-06, 2.00504383e-06],\n",
       "       ...,\n",
       "       [1.22261081e-05, 1.22182628e-05, 1.22103602e-05, ...,\n",
       "        1.22496385e-05, 1.22418242e-05, 1.22339889e-05],\n",
       "       [1.21143867e-05, 1.21106305e-05, 1.21068351e-05, ...,\n",
       "        1.21255789e-05, 1.21218636e-05, 1.21181356e-05],\n",
       "       [1.18877915e-05, 1.18877915e-05, 1.18877915e-05, ...,\n",
       "        1.18877915e-05, 1.18877915e-05, 1.18877915e-05]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 -180.0 -179.4 -178.8 -178.1 ... 178.1 178.8 179.4\n",
       "  * lat      (lat) float64 -90.0 -89.5 -89.0 -88.5 -88.0 ... 88.5 89.0 89.5 90.0</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'>'PRECTOT'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 361</li><li><span class='xr-has-index'>lon</span>: 576</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-76ff10c7-d7ff-4986-a3a8-dee147825e87' class='xr-array-in' type='checkbox' checked><label for='section-76ff10c7-d7ff-4986-a3a8-dee147825e87' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.905e-06 1.905e-06 1.905e-06 ... 1.189e-05 1.189e-05 1.189e-05</span></div><div class='xr-array-data'><pre>array([[1.90493563e-06, 1.90493563e-06, 1.90493563e-06, ...,\n",
       "        1.90493563e-06, 1.90493563e-06, 1.90493563e-06],\n",
       "       [2.01234207e-06, 2.01548914e-06, 2.01861894e-06, ...,\n",
       "        2.00282830e-06, 2.00601448e-06, 2.00918362e-06],\n",
       "       [2.01164153e-06, 2.01833882e-06, 2.02513843e-06, ...,\n",
       "        1.99213514e-06, 1.99853912e-06, 2.00504383e-06],\n",
       "       ...,\n",
       "       [1.22261081e-05, 1.22182628e-05, 1.22103602e-05, ...,\n",
       "        1.22496385e-05, 1.22418242e-05, 1.22339889e-05],\n",
       "       [1.21143867e-05, 1.21106305e-05, 1.21068351e-05, ...,\n",
       "        1.21255789e-05, 1.21218636e-05, 1.21181356e-05],\n",
       "       [1.18877915e-05, 1.18877915e-05, 1.18877915e-05, ...,\n",
       "        1.18877915e-05, 1.18877915e-05, 1.18877915e-05]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-3b948fb5-4c70-4641-b33c-61c0fb060772' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3b948fb5-4c70-4641-b33c-61c0fb060772' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -179.4 ... 178.8 179.4</div><input id='attrs-e487353f-8735-42da-b3d8-1f4a128cc976' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e487353f-8735-42da-b3d8-1f4a128cc976' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7210aa30-4122-4db8-9f7d-968e86f1ba34' class='xr-var-data-in' type='checkbox'><label for='data-7210aa30-4122-4db8-9f7d-968e86f1ba34' title='Show/Hide data 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([-180.   , -179.375, -178.75 , ...,  178.125,  178.75 ,  179.375])</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'>-90.0 -89.5 -89.0 ... 89.5 90.0</div><input id='attrs-270f8147-5490-4786-87ee-f5ea9ea0e775' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-270f8147-5490-4786-87ee-f5ea9ea0e775' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56c8eb6b-8b20-4cdf-bb56-03f95792b7d5' class='xr-var-data-in' type='checkbox'><label for='data-56c8eb6b-8b20-4cdf-bb56-03f95792b7d5' title='Show/Hide data 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([-90. , -89.5, -89. , ...,  89. ,  89.5,  90. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e0e817ab-0fa4-4106-bfc7-1af354efa4e6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e0e817ab-0fa4-4106-bfc7-1af354efa4e6' 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 'PRECTOT' (lat: 361, lon: 576)>\n",
       "array([[1.90493563e-06, 1.90493563e-06, 1.90493563e-06, ...,\n",
       "        1.90493563e-06, 1.90493563e-06, 1.90493563e-06],\n",
       "       [2.01234207e-06, 2.01548914e-06, 2.01861894e-06, ...,\n",
       "        2.00282830e-06, 2.00601448e-06, 2.00918362e-06],\n",
       "       [2.01164153e-06, 2.01833882e-06, 2.02513843e-06, ...,\n",
       "        1.99213514e-06, 1.99853912e-06, 2.00504383e-06],\n",
       "       ...,\n",
       "       [1.22261081e-05, 1.22182628e-05, 1.22103602e-05, ...,\n",
       "        1.22496385e-05, 1.22418242e-05, 1.22339889e-05],\n",
       "       [1.21143867e-05, 1.21106305e-05, 1.21068351e-05, ...,\n",
       "        1.21255789e-05, 1.21218636e-05, 1.21181356e-05],\n",
       "       [1.18877915e-05, 1.18877915e-05, 1.18877915e-05, ...,\n",
       "        1.18877915e-05, 1.18877915e-05, 1.18877915e-05]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 -180.0 -179.4 -178.8 -178.1 ... 178.1 178.8 179.4\n",
       "  * lat      (lat) float64 -90.0 -89.5 -89.0 -88.5 -88.0 ... 88.5 89.0 89.5 90.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#getting the mean for JJAS data\n",
    "jjas_mean = jjas_data.PRECTOT.mean('time')\n",
    " \n",
    "jjas_mean "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2eab95c7",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;PRECTOT&#x27; (lat: 361, lon: 576)&gt;\n",
       "array([[0.16458644, 0.16458644, 0.16458644, ..., 0.16458644, 0.16458644,\n",
       "        0.16458644],\n",
       "       [0.17386635, 0.17413826, 0.17440868, ..., 0.17304436, 0.17331965,\n",
       "        0.17359346],\n",
       "       [0.17380583, 0.17438447, 0.17497196, ..., 0.17212048, 0.17267378,\n",
       "        0.17323579],\n",
       "       ...,\n",
       "       [1.05633574, 1.0556579 , 1.05497512, ..., 1.05836877, 1.05769361,\n",
       "        1.05701664],\n",
       "       [1.04668301, 1.04635847, 1.04603056, ..., 1.04765002, 1.04732902,\n",
       "        1.04700692],\n",
       "       [1.02710519, 1.02710519, 1.02710519, ..., 1.02710519, 1.02710519,\n",
       "        1.02710519]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 -180.0 -179.4 -178.8 -178.1 ... 178.1 178.8 179.4\n",
       "  * lat      (lat) float64 -90.0 -89.5 -89.0 -88.5 -88.0 ... 88.5 89.0 89.5 90.0</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'>'PRECTOT'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 361</li><li><span class='xr-has-index'>lon</span>: 576</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-d3ab08d7-5d2c-4f26-aac8-67bab97321d8' class='xr-array-in' type='checkbox' checked><label for='section-d3ab08d7-5d2c-4f26-aac8-67bab97321d8' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.1646 0.1646 0.1646 0.1646 0.1646 ... 1.027 1.027 1.027 1.027 1.027</span></div><div class='xr-array-data'><pre>array([[0.16458644, 0.16458644, 0.16458644, ..., 0.16458644, 0.16458644,\n",
       "        0.16458644],\n",
       "       [0.17386635, 0.17413826, 0.17440868, ..., 0.17304436, 0.17331965,\n",
       "        0.17359346],\n",
       "       [0.17380583, 0.17438447, 0.17497196, ..., 0.17212048, 0.17267378,\n",
       "        0.17323579],\n",
       "       ...,\n",
       "       [1.05633574, 1.0556579 , 1.05497512, ..., 1.05836877, 1.05769361,\n",
       "        1.05701664],\n",
       "       [1.04668301, 1.04635847, 1.04603056, ..., 1.04765002, 1.04732902,\n",
       "        1.04700692],\n",
       "       [1.02710519, 1.02710519, 1.02710519, ..., 1.02710519, 1.02710519,\n",
       "        1.02710519]])</pre></div></div></li><li class='xr-section-item'><input id='section-7537a94d-e7e8-4aa3-9041-961fd5dd31ca' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7537a94d-e7e8-4aa3-9041-961fd5dd31ca' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -179.4 ... 178.8 179.4</div><input id='attrs-655d88e2-ec71-4917-83f3-cc7239d595c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-655d88e2-ec71-4917-83f3-cc7239d595c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6dea5629-2e77-4f87-b2c9-d633ca933358' class='xr-var-data-in' type='checkbox'><label for='data-6dea5629-2e77-4f87-b2c9-d633ca933358' title='Show/Hide data 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([-180.   , -179.375, -178.75 , ...,  178.125,  178.75 ,  179.375])</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'>-90.0 -89.5 -89.0 ... 89.5 90.0</div><input id='attrs-1f556c3c-6b34-4f04-a95c-ee9924255488' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f556c3c-6b34-4f04-a95c-ee9924255488' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20d62af1-d910-4b6b-8363-6ac8ff436783' class='xr-var-data-in' type='checkbox'><label for='data-20d62af1-d910-4b6b-8363-6ac8ff436783' title='Show/Hide data 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([-90. , -89.5, -89. , ...,  89. ,  89.5,  90. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-500b45fa-1436-4338-bb79-33e63952c67d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-500b45fa-1436-4338-bb79-33e63952c67d' 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 'PRECTOT' (lat: 361, lon: 576)>\n",
       "array([[0.16458644, 0.16458644, 0.16458644, ..., 0.16458644, 0.16458644,\n",
       "        0.16458644],\n",
       "       [0.17386635, 0.17413826, 0.17440868, ..., 0.17304436, 0.17331965,\n",
       "        0.17359346],\n",
       "       [0.17380583, 0.17438447, 0.17497196, ..., 0.17212048, 0.17267378,\n",
       "        0.17323579],\n",
       "       ...,\n",
       "       [1.05633574, 1.0556579 , 1.05497512, ..., 1.05836877, 1.05769361,\n",
       "        1.05701664],\n",
       "       [1.04668301, 1.04635847, 1.04603056, ..., 1.04765002, 1.04732902,\n",
       "        1.04700692],\n",
       "       [1.02710519, 1.02710519, 1.02710519, ..., 1.02710519, 1.02710519,\n",
       "        1.02710519]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 -180.0 -179.4 -178.8 -178.1 ... 178.1 178.8 179.4\n",
       "  * lat      (lat) float64 -90.0 -89.5 -89.0 -88.5 -88.0 ... 88.5 89.0 89.5 90.0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#the data is in kg m-2 s-1 so we multiply by 86400 to convert to mm/day\n",
    "\n",
    "pr_mm = jjas_mean*86400\n",
    "pr_mm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4323ee93",
   "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 with cartopy jjas_pr_mean\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",
    " \n",
    "m1 = ax.contourf(pr_mm['lon'][:], pr_mm['lat'][:],pr_mm,\n",
    "                 np.arange(1,35+1,5),transform = ccrs.PlateCarree(),cmap='YlGnBu',extend='both')\n",
    "\n",
    "\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",
    "\n",
    "\n",
    "plt.colorbar(m1, orientation = 'horizontal',shrink=0.5, fraction = 0.04 , label = 'rain_rate mm/day')\n",
    "ax.coastlines(linewidth=3)\n",
    "ax.add_feature(cfeature.BORDERS,linewidth=3)\n",
    "plt.title('MERRA Mean jjas precip rate in mm/day')\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/bd_pr_merra_jjas_mean.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "06a5ec91",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;PRECTOT&#x27; (lat: 361, lon: 576)&gt;\n",
       "array([[1.8663519e-06, 1.8663519e-06, 1.8663519e-06, ..., 1.8663519e-06,\n",
       "        1.8663519e-06, 1.8663519e-06],\n",
       "       [1.9811250e-06, 1.9834720e-06, 1.9858003e-06, ..., 1.9739743e-06,\n",
       "        1.9763741e-06, 1.9787572e-06],\n",
       "       [2.0254288e-06, 2.0310063e-06, 2.0366579e-06, ..., 2.0091111e-06,\n",
       "        2.0144817e-06, 2.0199207e-06],\n",
       "       ...,\n",
       "       [8.8177430e-06, 8.8132765e-06, 8.8088200e-06, ..., 8.8312672e-06,\n",
       "        8.8267452e-06, 8.8222369e-06],\n",
       "       [8.8621582e-06, 8.8598563e-06, 8.8575298e-06, ..., 8.8691195e-06,\n",
       "        8.8668048e-06, 8.8644802e-06],\n",
       "       [8.8394190e-06, 8.8394190e-06, 8.8394190e-06, ..., 8.8394190e-06,\n",
       "        8.8394190e-06, 8.8394190e-06]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 -180.0 -179.4 -178.8 -178.1 ... 178.1 178.8 179.4\n",
       "  * lat      (lat) float64 -90.0 -89.5 -89.0 -88.5 -88.0 ... 88.5 89.0 89.5 90.0</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'>'PRECTOT'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 361</li><li><span class='xr-has-index'>lon</span>: 576</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-d073d171-256d-4989-8000-131575de943a' class='xr-array-in' type='checkbox' checked><label for='section-d073d171-256d-4989-8000-131575de943a' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.866e-06 1.866e-06 1.866e-06 ... 8.839e-06 8.839e-06 8.839e-06</span></div><div class='xr-array-data'><pre>array([[1.8663519e-06, 1.8663519e-06, 1.8663519e-06, ..., 1.8663519e-06,\n",
       "        1.8663519e-06, 1.8663519e-06],\n",
       "       [1.9811250e-06, 1.9834720e-06, 1.9858003e-06, ..., 1.9739743e-06,\n",
       "        1.9763741e-06, 1.9787572e-06],\n",
       "       [2.0254288e-06, 2.0310063e-06, 2.0366579e-06, ..., 2.0091111e-06,\n",
       "        2.0144817e-06, 2.0199207e-06],\n",
       "       ...,\n",
       "       [8.8177430e-06, 8.8132765e-06, 8.8088200e-06, ..., 8.8312672e-06,\n",
       "        8.8267452e-06, 8.8222369e-06],\n",
       "       [8.8621582e-06, 8.8598563e-06, 8.8575298e-06, ..., 8.8691195e-06,\n",
       "        8.8668048e-06, 8.8644802e-06],\n",
       "       [8.8394190e-06, 8.8394190e-06, 8.8394190e-06, ..., 8.8394190e-06,\n",
       "        8.8394190e-06, 8.8394190e-06]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-a1b740f6-ada0-45ff-862f-31f6f2d05c0d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a1b740f6-ada0-45ff-862f-31f6f2d05c0d' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -179.4 ... 178.8 179.4</div><input id='attrs-4a3e6a3e-ee06-43f5-98df-09e2c523f7cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a3e6a3e-ee06-43f5-98df-09e2c523f7cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27d81ff1-876e-4fa1-9c3b-0ecbf13bfdee' class='xr-var-data-in' type='checkbox'><label for='data-27d81ff1-876e-4fa1-9c3b-0ecbf13bfdee' title='Show/Hide data 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([-180.   , -179.375, -178.75 , ...,  178.125,  178.75 ,  179.375])</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'>-90.0 -89.5 -89.0 ... 89.5 90.0</div><input id='attrs-1f367d0d-11f1-4395-a787-b8b0f9fd6ad6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f367d0d-11f1-4395-a787-b8b0f9fd6ad6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1648540-dac9-4bfd-9b6d-e56d9d43eff9' class='xr-var-data-in' type='checkbox'><label for='data-a1648540-dac9-4bfd-9b6d-e56d9d43eff9' title='Show/Hide data 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([-90. , -89.5, -89. , ...,  89. ,  89.5,  90. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6514ed64-dc9d-44df-acb5-dd6384d3a145' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6514ed64-dc9d-44df-acb5-dd6384d3a145' 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 'PRECTOT' (lat: 361, lon: 576)>\n",
       "array([[1.8663519e-06, 1.8663519e-06, 1.8663519e-06, ..., 1.8663519e-06,\n",
       "        1.8663519e-06, 1.8663519e-06],\n",
       "       [1.9811250e-06, 1.9834720e-06, 1.9858003e-06, ..., 1.9739743e-06,\n",
       "        1.9763741e-06, 1.9787572e-06],\n",
       "       [2.0254288e-06, 2.0310063e-06, 2.0366579e-06, ..., 2.0091111e-06,\n",
       "        2.0144817e-06, 2.0199207e-06],\n",
       "       ...,\n",
       "       [8.8177430e-06, 8.8132765e-06, 8.8088200e-06, ..., 8.8312672e-06,\n",
       "        8.8267452e-06, 8.8222369e-06],\n",
       "       [8.8621582e-06, 8.8598563e-06, 8.8575298e-06, ..., 8.8691195e-06,\n",
       "        8.8668048e-06, 8.8644802e-06],\n",
       "       [8.8394190e-06, 8.8394190e-06, 8.8394190e-06, ..., 8.8394190e-06,\n",
       "        8.8394190e-06, 8.8394190e-06]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 -180.0 -179.4 -178.8 -178.1 ... 178.1 178.8 179.4\n",
       "  * lat      (lat) float64 -90.0 -89.5 -89.0 -88.5 -88.0 ... 88.5 89.0 89.5 90.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "annual_mean = data.PRECTOT.mean('time')\n",
    "annual_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b1a634f5",
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   "outputs": [
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;PRECTOT&#x27; (lat: 361, lon: 576)&gt;\n",
       "array([[0.1612528 , 0.1612528 , 0.1612528 , ..., 0.1612528 , 0.1612528 ,\n",
       "        0.1612528 ],\n",
       "       [0.1711692 , 0.17137198, 0.17157314, ..., 0.17055138, 0.17075872,\n",
       "        0.17096462],\n",
       "       [0.17499705, 0.17547894, 0.17596724, ..., 0.1735872 , 0.17405121,\n",
       "        0.17452114],\n",
       "       ...,\n",
       "       [0.761853  , 0.76146709, 0.76108205, ..., 0.76302149, 0.76263079,\n",
       "        0.76224126],\n",
       "       [0.76569047, 0.76549158, 0.76529057, ..., 0.76629192, 0.76609194,\n",
       "        0.76589109],\n",
       "       [0.7637258 , 0.7637258 , 0.7637258 , ..., 0.7637258 , 0.7637258 ,\n",
       "        0.7637258 ]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 -180.0 -179.4 -178.8 -178.1 ... 178.1 178.8 179.4\n",
       "  * lat      (lat) float64 -90.0 -89.5 -89.0 -88.5 -88.0 ... 88.5 89.0 89.5 90.0</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'>'PRECTOT'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 361</li><li><span class='xr-has-index'>lon</span>: 576</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-168ebbcf-6e05-493a-b275-92d2f699c49a' class='xr-array-in' type='checkbox' checked><label for='section-168ebbcf-6e05-493a-b275-92d2f699c49a' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.1613 0.1613 0.1613 0.1613 0.1613 ... 0.7637 0.7637 0.7637 0.7637</span></div><div class='xr-array-data'><pre>array([[0.1612528 , 0.1612528 , 0.1612528 , ..., 0.1612528 , 0.1612528 ,\n",
       "        0.1612528 ],\n",
       "       [0.1711692 , 0.17137198, 0.17157314, ..., 0.17055138, 0.17075872,\n",
       "        0.17096462],\n",
       "       [0.17499705, 0.17547894, 0.17596724, ..., 0.1735872 , 0.17405121,\n",
       "        0.17452114],\n",
       "       ...,\n",
       "       [0.761853  , 0.76146709, 0.76108205, ..., 0.76302149, 0.76263079,\n",
       "        0.76224126],\n",
       "       [0.76569047, 0.76549158, 0.76529057, ..., 0.76629192, 0.76609194,\n",
       "        0.76589109],\n",
       "       [0.7637258 , 0.7637258 , 0.7637258 , ..., 0.7637258 , 0.7637258 ,\n",
       "        0.7637258 ]])</pre></div></div></li><li class='xr-section-item'><input id='section-4563695b-6d10-4d6b-b4f1-64afb4cda8b1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4563695b-6d10-4d6b-b4f1-64afb4cda8b1' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-180.0 -179.4 ... 178.8 179.4</div><input id='attrs-d58634c0-86da-44f9-8e98-f2a7fdb5a3e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d58634c0-86da-44f9-8e98-f2a7fdb5a3e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54588353-3008-49e2-9847-e2f795efbe4c' class='xr-var-data-in' type='checkbox'><label for='data-54588353-3008-49e2-9847-e2f795efbe4c' title='Show/Hide data 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([-180.   , -179.375, -178.75 , ...,  178.125,  178.75 ,  179.375])</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'>-90.0 -89.5 -89.0 ... 89.5 90.0</div><input id='attrs-8f8be26c-d8ae-4d3c-b870-d1a96c846e00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f8be26c-d8ae-4d3c-b870-d1a96c846e00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16ceb3f3-0452-42c8-8f23-bb70fdc716de' class='xr-var-data-in' type='checkbox'><label for='data-16ceb3f3-0452-42c8-8f23-bb70fdc716de' title='Show/Hide data 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([-90. , -89.5, -89. , ...,  89. ,  89.5,  90. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6f559927-34eb-4186-966a-064cbc43978c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6f559927-34eb-4186-966a-064cbc43978c' 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 'PRECTOT' (lat: 361, lon: 576)>\n",
       "array([[0.1612528 , 0.1612528 , 0.1612528 , ..., 0.1612528 , 0.1612528 ,\n",
       "        0.1612528 ],\n",
       "       [0.1711692 , 0.17137198, 0.17157314, ..., 0.17055138, 0.17075872,\n",
       "        0.17096462],\n",
       "       [0.17499705, 0.17547894, 0.17596724, ..., 0.1735872 , 0.17405121,\n",
       "        0.17452114],\n",
       "       ...,\n",
       "       [0.761853  , 0.76146709, 0.76108205, ..., 0.76302149, 0.76263079,\n",
       "        0.76224126],\n",
       "       [0.76569047, 0.76549158, 0.76529057, ..., 0.76629192, 0.76609194,\n",
       "        0.76589109],\n",
       "       [0.7637258 , 0.7637258 , 0.7637258 , ..., 0.7637258 , 0.7637258 ,\n",
       "        0.7637258 ]])\n",
       "Coordinates:\n",
       "  * lon      (lon) float64 -180.0 -179.4 -178.8 -178.1 ... 178.1 178.8 179.4\n",
       "  * lat      (lat) float64 -90.0 -89.5 -89.0 -88.5 -88.0 ... 88.5 89.0 89.5 90.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#converting from kg m-2 s-1 to mm/day\n",
    "\n",
    "annual_pr_mm = annual_mean*86400\n",
    "annual_pr_mm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9d357dd5",
   "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",
    "\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(annual_pr_mm['lon'], annual_pr_mm['lat'],annual_pr_mm,\n",
    "                 np.arange(1,35+1,5),transform = ccrs.PlateCarree(),cmap='YlGnBu',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, 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",
    "#ax.add_feature(cfeature.STATES)\n",
    "plt.title('MERRA Annual mean precip rate in mm/day')\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/bd_pr_merra_annual_mean.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c33dddfb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "df49651d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6bb50b71",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "35f8f0bc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4ee3a4cd",
   "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",
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}