bd_gcm_pr_miroc5.ipynb

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    "#writing some conda package or module\n",
    "#!pip install netCDF4\n",
    "%matplotlib inline\n",
    "import warnings\n",
    "from netCDF4 import Dataset\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "#!pip install cartopy\n",
    "import cartopy.feature as cfeature\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.mpl.ticker as cticker\n",
    "from cartopy.util import add_cyclic_point\n"
   ]
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   "cell_type": "code",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 1956, bnds: 2, lat: 128, lon: 256)\n",
       "Coordinates:\n",
       "  * time       (time) object 1850-01-16 12:00:00 ... 2012-12-16 12:00:00\n",
       "  * lat        (lat) float64 -88.93 -87.54 -86.14 -84.74 ... 86.14 87.54 88.93\n",
       "  * lon        (lon) float64 0.0 1.406 2.812 4.219 ... 354.4 355.8 357.2 358.6\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1850-01-01 00:00:00 ... 2013-01-01 00:00:00\n",
       "    lat_bnds   (lat, bnds) float64 -90.0 -88.28 -88.28 ... 88.28 88.28 90.0\n",
       "    lon_bnds   (lon, bnds) float64 -0.7031 0.7031 0.7031 ... 357.9 357.9 359.3\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/27)\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    experiment_id:          historical\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    model_id:               MIROC5\n",
       "    forcing:                GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG ...\n",
       "    ...                     ...\n",
       "    table_id:               Table Amon (31 January 2011) 53b766a395ac41696af4...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6</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-83732094-c246-4b82-86d1-90cca479dc05' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-83732094-c246-4b82-86d1-90cca479dc05' 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>: 1956</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 128</li><li><span class='xr-has-index'>lon</span>: 256</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-3b254b9c-e6d2-4812-8585-91d653292cab' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3b254b9c-e6d2-4812-8585-91d653292cab' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-16 12:00:00 ... 2012-12-...</div><input id='attrs-4171536a-4a2a-4845-83bf-4a77fd8c0cc5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4171536a-4a2a-4845-83bf-4a77fd8c0cc5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2722cd6e-226d-4e2e-9066-1e2f23d4156f' class='xr-var-data-in' type='checkbox'><label for='data-2722cd6e-226d-4e2e-9066-1e2f23d4156f' 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>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(1850, 2, 15, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(1850, 3, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       ...,\n",
       "       cftime.DatetimeNoLeap(2012, 10, 16, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2012, 11, 16, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2012, 12, 16, 12, 0, 0, 0, has_year_zero=True)],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-88.93 -87.54 ... 87.54 88.93</div><input id='attrs-b2feafdb-9e91-4e13-8249-fd42fd209ef0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2feafdb-9e91-4e13-8249-fd42fd209ef0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f791b485-a3e6-4803-b677-9e964344e72f' class='xr-var-data-in' type='checkbox'><label for='data-f791b485-a3e6-4803-b677-9e964344e72f' 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-88.927735, -87.538705, -86.141472, -84.742386, -83.342596, -81.942466,\n",
       "       -80.542146, -79.14171 , -77.741196, -76.340629, -74.940023, -73.539389,\n",
       "       -72.138732, -70.738059, -69.337372, -67.936673, -66.535966, -65.135251,\n",
       "       -63.73453 , -62.333803, -60.933072, -59.532337, -58.131598, -56.730857,\n",
       "       -55.330112, -53.929366, -52.528617, -51.127867, -49.727115, -48.326361,\n",
       "       -46.925606, -45.52485 , -44.124093, -42.723335, -41.322576, -39.921816,\n",
       "       -38.521056, -37.120294, -35.719532, -34.31877 , -32.918007, -31.517244,\n",
       "       -30.11648 , -28.715716, -27.314951, -25.914186, -24.513421, -23.112655,\n",
       "       -21.71189 , -20.311124, -18.910357, -17.509591, -16.108824, -14.708057,\n",
       "       -13.30729 , -11.906523, -10.505756,  -9.104989,  -7.704221,  -6.303454,\n",
       "        -4.902687,  -3.501919,  -2.101151,  -0.700384,   0.700384,   2.101151,\n",
       "         3.501919,   4.902687,   6.303454,   7.704221,   9.104989,  10.505756,\n",
       "        11.906523,  13.30729 ,  14.708057,  16.108824,  17.509591,  18.910357,\n",
       "        20.311124,  21.71189 ,  23.112655,  24.513421,  25.914186,  27.314951,\n",
       "        28.715716,  30.11648 ,  31.517244,  32.918007,  34.31877 ,  35.719532,\n",
       "        37.120294,  38.521056,  39.921816,  41.322576,  42.723335,  44.124093,\n",
       "        45.52485 ,  46.925606,  48.326361,  49.727115,  51.127867,  52.528617,\n",
       "        53.929366,  55.330112,  56.730857,  58.131598,  59.532337,  60.933072,\n",
       "        62.333803,  63.73453 ,  65.135251,  66.535966,  67.936673,  69.337372,\n",
       "        70.738059,  72.138732,  73.539389,  74.940023,  76.340629,  77.741196,\n",
       "        79.14171 ,  80.542146,  81.942466,  83.342596,  84.742386,  86.141472,\n",
       "        87.538705,  88.927735])</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'>0.0 1.406 2.812 ... 357.2 358.6</div><input id='attrs-7142e9a6-4652-412f-a054-c86aa82a94af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7142e9a6-4652-412f-a054-c86aa82a94af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e4ae586-2ae6-46c0-9c9f-34085eb27b95' class='xr-var-data-in' type='checkbox'><label for='data-7e4ae586-2ae6-46c0-9c9f-34085eb27b95' 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.     ,   1.40625,   2.8125 , ..., 355.78125, 357.1875 , 358.59375])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b018b878-1b78-4a6f-9ce1-db7d4ed1a38b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b018b878-1b78-4a6f-9ce1-db7d4ed1a38b' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ce05385f-a163-49d5-87ab-8d91fcd1f749' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ce05385f-a163-49d5-87ab-8d91fcd1f749' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c71bf9b1-20d7-4082-bab0-2a37e883c84b' class='xr-var-data-in' type='checkbox'><label for='data-c71bf9b1-20d7-4082-bab0-2a37e883c84b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[cftime.DatetimeNoLeap(1850, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1850, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1850, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1850, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1850, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1850, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       ...,\n",
       "       [cftime.DatetimeNoLeap(2012, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2012, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2012, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2012, 12, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2012, 12, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2013, 1, 1, 0, 0, 0, 0, has_year_zero=True)]],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c5a056d0-5566-45d3-a3c4-6bbad13333e7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c5a056d0-5566-45d3-a3c4-6bbad13333e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45fa3e39-16c8-40f5-a49d-e85e3b17752c' class='xr-var-data-in' type='checkbox'><label for='data-45fa3e39-16c8-40f5-a49d-e85e3b17752c' 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([[-90.      , -88.282245],\n",
       "       [-88.282245, -86.866422],\n",
       "       [-86.866422, -85.459991],\n",
       "       ...,\n",
       "       [ 85.459991,  86.866422],\n",
       "       [ 86.866422,  88.282245],\n",
       "       [ 88.282245,  90.      ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0684afbb-a0a1-4ff0-abd5-fdc39e8f647a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0684afbb-a0a1-4ff0-abd5-fdc39e8f647a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11db03f9-7b99-4128-81c8-d09e4d0c525a' class='xr-var-data-in' type='checkbox'><label for='data-11db03f9-7b99-4128-81c8-d09e4d0c525a' 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([[ -0.703125,   0.703125],\n",
       "       [  0.703125,   2.109375],\n",
       "       [  2.109375,   3.515625],\n",
       "       ...,\n",
       "       [355.078125, 356.484375],\n",
       "       [356.484375, 357.890625],\n",
       "       [357.890625, 359.296875]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-588e17c5-a625-4fba-82b9-437d5f2332c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-588e17c5-a625-4fba-82b9-437d5f2332c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0e88259-4b64-47de-a627-50e80cdae75c' class='xr-var-data-in' type='checkbox'><label for='data-b0e88259-4b64-47de-a627-50e80cdae75c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>comment :</span></dt><dd>at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>original_name :</span></dt><dd>PRCP</dd><dt><span>original_units :</span></dt><dd>kg/m**2/s</dd><dt><span>history :</span></dt><dd>2011-04-23T09:11:46Z altered by CMOR: Converted units from &#x27;kg/m**2/s&#x27; to &#x27;kg m-2 s-1&#x27;. 2011-04-23T09:11:46Z altered by CMOR: replaced missing value flag (-999) with standard missing value (1e+20). 2011-04-23T09:11:46Z altered by CMOR: Inverted axis: lat.</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MIROC5_historical_r0i0p0.nc areacella: areacella_fx_MIROC5_historical_r0i0p0.nc</dd></dl></div><div class='xr-var-data'><pre>[64094208 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ee47c009-97df-481a-a0c1-add44a0fed54' class='xr-section-summary-in' type='checkbox'  ><label for='section-ee47c009-97df-481a-a0c1-add44a0fed54' class='xr-section-summary' >Attributes: <span>(27)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>institution :</span></dt><dd>AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan), NIES (National Institute for Environmental Studies, Ibaraki, Japan), JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan)</dd><dt><span>institute_id :</span></dt><dd>MIROC</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>source :</span></dt><dd>MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); ocean: COCO (COCO4.5, 256x224 L50); sea ice: COCO (COCO4.5); land: MATSIRO (MATSIRO, L6); aerosols: SPRINTARS (SPRINTARS 5.00, T85L40)</dd><dt><span>model_id :</span></dt><dd>MIROC5</dd><dt><span>forcing :</span></dt><dd>GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG includes CO2, N2O, methane, and fluorocarbons; Oz includes OH and H2O2; LU excludes change in lake fraction)</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>150015.0</dd><dt><span>contact :</span></dt><dd>Masahiro Watanabe (hiro@aori.u-tokyo.ac.jp), Seita Emori (emori@nies.go.jp), Masayoshi Ishii (ism@jamstec.go.jp), Masahide Kimoto (kimoto@aori.u-tokyo.ac.jp)</dd><dt><span>references :</span></dt><dd>Watanabe et al., 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 6312-6335</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>a906be44-c850-4f0c-b8c4-2b165051669a</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>creation_date :</span></dt><dd>2011-04-23T09:11:46Z</dd><dt><span>history :</span></dt><dd>2011-04-23T09:11:46Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (31 January 2011) 53b766a395ac41696af40aab76a49ae5</dd><dt><span>title :</span></dt><dd>MIROC5 model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>1</dd><dt><span>cmor_version :</span></dt><dd>2.5.6</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (time: 1956, bnds: 2, lat: 128, lon: 256)\n",
       "Coordinates:\n",
       "  * time       (time) object 1850-01-16 12:00:00 ... 2012-12-16 12:00:00\n",
       "  * lat        (lat) float64 -88.93 -87.54 -86.14 -84.74 ... 86.14 87.54 88.93\n",
       "  * lon        (lon) float64 0.0 1.406 2.812 4.219 ... 354.4 355.8 357.2 358.6\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object ...\n",
       "    lat_bnds   (lat, bnds) float64 ...\n",
       "    lon_bnds   (lon, bnds) float64 ...\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/27)\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    experiment_id:          historical\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    model_id:               MIROC5\n",
       "    forcing:                GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG ...\n",
       "    ...                     ...\n",
       "    table_id:               Table Amon (31 January 2011) 53b766a395ac41696af4...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = xr.open_dataset('/home/mkibria/Academic/pr_of_thesis/GCM/MIROC5/pr_Amon_MIROC5_historical_r1i1p1_185001-201212.nc')\n",
    "\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/mkibria/miniconda3/envs/esp-sp/lib/python3.9/site-packages/xarray/coding/times.py:351: FutureWarning: Index.ravel returning ndarray is deprecated; in a future version this will return a view on self.\n",
      "  sample = dates.ravel()[0]\n",
      "/tmp/ipykernel_19667/3137857967.py:3: RuntimeWarning: Converting a CFTimeIndex with dates from a non-standard calendar, 'noleap', to a pandas.DatetimeIndex, which uses dates from the standard calendar.  This may lead to subtle errors in operations that depend on the length of time between dates.\n",
      "  datetimeindex = data.indexes['time'].to_datetimeindex()\n"
     ]
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       "\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: 1956, bnds: 2, lat: 128, lon: 256)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1850-01-16T12:00:00 ... 2012-12-16T12:00:00\n",
       "  * lat        (lat) float64 -88.93 -87.54 -86.14 -84.74 ... 86.14 87.54 88.93\n",
       "  * lon        (lon) float64 0.0 1.406 2.812 4.219 ... 354.4 355.8 357.2 358.6\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1850-01-01 00:00:00 ... 2013-01-01 00:00:00\n",
       "    lat_bnds   (lat, bnds) float64 -90.0 -88.28 -88.28 ... 88.28 88.28 90.0\n",
       "    lon_bnds   (lon, bnds) float64 -0.7031 0.7031 0.7031 ... 357.9 357.9 359.3\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/27)\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    experiment_id:          historical\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    model_id:               MIROC5\n",
       "    forcing:                GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG ...\n",
       "    ...                     ...\n",
       "    table_id:               Table Amon (31 January 2011) 53b766a395ac41696af4...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6</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-27ad4144-fae3-4fbe-8f34-45098aed8351' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-27ad4144-fae3-4fbe-8f34-45098aed8351' 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>: 1956</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 128</li><li><span class='xr-has-index'>lon</span>: 256</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-5a253821-683b-4b70-a8ba-db4059ccce95' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5a253821-683b-4b70-a8ba-db4059ccce95' 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'>1850-01-16T12:00:00 ... 2012-12-...</div><input id='attrs-828c42ed-4caa-42e7-9d39-4ac4bfcc1d1e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-828c42ed-4caa-42e7-9d39-4ac4bfcc1d1e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be22500a-fa2f-42d7-bb2d-3cc18a08b135' class='xr-var-data-in' type='checkbox'><label for='data-be22500a-fa2f-42d7-bb2d-3cc18a08b135' 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;1850-01-16T12:00:00.000000000&#x27;, &#x27;1850-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;1850-03-16T12:00:00.000000000&#x27;, ..., &#x27;2012-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2012-11-16T00:00:00.000000000&#x27;, &#x27;2012-12-16T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-88.93 -87.54 ... 87.54 88.93</div><input id='attrs-7e63e2e5-8c69-4e56-8558-b397c709fe11' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e63e2e5-8c69-4e56-8558-b397c709fe11' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9823bb7-422b-495a-bd21-00121dcd72a1' class='xr-var-data-in' type='checkbox'><label for='data-c9823bb7-422b-495a-bd21-00121dcd72a1' 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-88.927735, -87.538705, -86.141472, -84.742386, -83.342596, -81.942466,\n",
       "       -80.542146, -79.14171 , -77.741196, -76.340629, -74.940023, -73.539389,\n",
       "       -72.138732, -70.738059, -69.337372, -67.936673, -66.535966, -65.135251,\n",
       "       -63.73453 , -62.333803, -60.933072, -59.532337, -58.131598, -56.730857,\n",
       "       -55.330112, -53.929366, -52.528617, -51.127867, -49.727115, -48.326361,\n",
       "       -46.925606, -45.52485 , -44.124093, -42.723335, -41.322576, -39.921816,\n",
       "       -38.521056, -37.120294, -35.719532, -34.31877 , -32.918007, -31.517244,\n",
       "       -30.11648 , -28.715716, -27.314951, -25.914186, -24.513421, -23.112655,\n",
       "       -21.71189 , -20.311124, -18.910357, -17.509591, -16.108824, -14.708057,\n",
       "       -13.30729 , -11.906523, -10.505756,  -9.104989,  -7.704221,  -6.303454,\n",
       "        -4.902687,  -3.501919,  -2.101151,  -0.700384,   0.700384,   2.101151,\n",
       "         3.501919,   4.902687,   6.303454,   7.704221,   9.104989,  10.505756,\n",
       "        11.906523,  13.30729 ,  14.708057,  16.108824,  17.509591,  18.910357,\n",
       "        20.311124,  21.71189 ,  23.112655,  24.513421,  25.914186,  27.314951,\n",
       "        28.715716,  30.11648 ,  31.517244,  32.918007,  34.31877 ,  35.719532,\n",
       "        37.120294,  38.521056,  39.921816,  41.322576,  42.723335,  44.124093,\n",
       "        45.52485 ,  46.925606,  48.326361,  49.727115,  51.127867,  52.528617,\n",
       "        53.929366,  55.330112,  56.730857,  58.131598,  59.532337,  60.933072,\n",
       "        62.333803,  63.73453 ,  65.135251,  66.535966,  67.936673,  69.337372,\n",
       "        70.738059,  72.138732,  73.539389,  74.940023,  76.340629,  77.741196,\n",
       "        79.14171 ,  80.542146,  81.942466,  83.342596,  84.742386,  86.141472,\n",
       "        87.538705,  88.927735])</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'>0.0 1.406 2.812 ... 357.2 358.6</div><input id='attrs-2620f84f-a938-4e25-86ed-921a9a484131' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2620f84f-a938-4e25-86ed-921a9a484131' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-550e08b2-c2b2-4d89-b4d7-dd85d60c0f20' class='xr-var-data-in' type='checkbox'><label for='data-550e08b2-c2b2-4d89-b4d7-dd85d60c0f20' 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.     ,   1.40625,   2.8125 , ..., 355.78125, 357.1875 , 358.59375])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dd4f4e9b-bae0-4039-bf52-be91dc4dd55a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-dd4f4e9b-bae0-4039-bf52-be91dc4dd55a' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-01 00:00:00 ... 2013-01-...</div><input id='attrs-d188835d-06e4-4649-95ba-d314d9f692d4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d188835d-06e4-4649-95ba-d314d9f692d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecf91359-8f9e-4cfd-ab7f-46f60eebf82e' class='xr-var-data-in' type='checkbox'><label for='data-ecf91359-8f9e-4cfd-ab7f-46f60eebf82e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[cftime.DatetimeNoLeap(1850, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1850, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1850, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1850, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1850, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1850, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       ...,\n",
       "       [cftime.DatetimeNoLeap(2012, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2012, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2012, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2012, 12, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2012, 12, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2013, 1, 1, 0, 0, 0, 0, has_year_zero=True)]],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.28 -88.28 ... 88.28 90.0</div><input id='attrs-a3413e40-5e89-40e3-82d0-d183c5b5071b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a3413e40-5e89-40e3-82d0-d183c5b5071b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97bdd6d6-32e2-44ec-994a-4e1352376083' class='xr-var-data-in' type='checkbox'><label for='data-97bdd6d6-32e2-44ec-994a-4e1352376083' 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([[-90.      , -88.282245],\n",
       "       [-88.282245, -86.866422],\n",
       "       [-86.866422, -85.459991],\n",
       "       ...,\n",
       "       [ 85.459991,  86.866422],\n",
       "       [ 86.866422,  88.282245],\n",
       "       [ 88.282245,  90.      ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.7031 0.7031 ... 357.9 359.3</div><input id='attrs-e1735505-0798-4846-bce2-343661352bf3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e1735505-0798-4846-bce2-343661352bf3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-898782f3-fb56-44be-a8bb-5c19b592cebc' class='xr-var-data-in' type='checkbox'><label for='data-898782f3-fb56-44be-a8bb-5c19b592cebc' 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([[ -0.703125,   0.703125],\n",
       "       [  0.703125,   2.109375],\n",
       "       [  2.109375,   3.515625],\n",
       "       ...,\n",
       "       [355.078125, 356.484375],\n",
       "       [356.484375, 357.890625],\n",
       "       [357.890625, 359.296875]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-741ff2ad-1685-40a3-8c89-f690e89ab16b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-741ff2ad-1685-40a3-8c89-f690e89ab16b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b15844b9-2579-48a1-9159-10beff062a1d' class='xr-var-data-in' type='checkbox'><label for='data-b15844b9-2579-48a1-9159-10beff062a1d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>comment :</span></dt><dd>at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>original_name :</span></dt><dd>PRCP</dd><dt><span>original_units :</span></dt><dd>kg/m**2/s</dd><dt><span>history :</span></dt><dd>2011-04-23T09:11:46Z altered by CMOR: Converted units from &#x27;kg/m**2/s&#x27; to &#x27;kg m-2 s-1&#x27;. 2011-04-23T09:11:46Z altered by CMOR: replaced missing value flag (-999) with standard missing value (1e+20). 2011-04-23T09:11:46Z altered by CMOR: Inverted axis: lat.</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MIROC5_historical_r0i0p0.nc areacella: areacella_fx_MIROC5_historical_r0i0p0.nc</dd></dl></div><div class='xr-var-data'><pre>[64094208 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4b994df3-73be-43a2-8109-c5312db1e375' class='xr-section-summary-in' type='checkbox'  ><label for='section-4b994df3-73be-43a2-8109-c5312db1e375' class='xr-section-summary' >Attributes: <span>(27)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>institution :</span></dt><dd>AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan), NIES (National Institute for Environmental Studies, Ibaraki, Japan), JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan)</dd><dt><span>institute_id :</span></dt><dd>MIROC</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>source :</span></dt><dd>MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); ocean: COCO (COCO4.5, 256x224 L50); sea ice: COCO (COCO4.5); land: MATSIRO (MATSIRO, L6); aerosols: SPRINTARS (SPRINTARS 5.00, T85L40)</dd><dt><span>model_id :</span></dt><dd>MIROC5</dd><dt><span>forcing :</span></dt><dd>GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG includes CO2, N2O, methane, and fluorocarbons; Oz includes OH and H2O2; LU excludes change in lake fraction)</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>150015.0</dd><dt><span>contact :</span></dt><dd>Masahiro Watanabe (hiro@aori.u-tokyo.ac.jp), Seita Emori (emori@nies.go.jp), Masayoshi Ishii (ism@jamstec.go.jp), Masahide Kimoto (kimoto@aori.u-tokyo.ac.jp)</dd><dt><span>references :</span></dt><dd>Watanabe et al., 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 6312-6335</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>a906be44-c850-4f0c-b8c4-2b165051669a</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>creation_date :</span></dt><dd>2011-04-23T09:11:46Z</dd><dt><span>history :</span></dt><dd>2011-04-23T09:11:46Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (31 January 2011) 53b766a395ac41696af40aab76a49ae5</dd><dt><span>title :</span></dt><dd>MIROC5 model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>1</dd><dt><span>cmor_version :</span></dt><dd>2.5.6</dd></dl></div></li></ul></div></div>"
      ],
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       "<xarray.Dataset>\n",
       "Dimensions:    (time: 1956, bnds: 2, lat: 128, lon: 256)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1850-01-16T12:00:00 ... 2012-12-16T12:00:00\n",
       "  * lat        (lat) float64 -88.93 -87.54 -86.14 -84.74 ... 86.14 87.54 88.93\n",
       "  * lon        (lon) float64 0.0 1.406 2.812 4.219 ... 354.4 355.8 357.2 358.6\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1850-01-01 00:00:00 ... 2013-01-01 00:00:00\n",
       "    lat_bnds   (lat, bnds) float64 -90.0 -88.28 -88.28 ... 88.28 88.28 90.0\n",
       "    lon_bnds   (lon, bnds) float64 -0.7031 0.7031 0.7031 ... 357.9 357.9 359.3\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/27)\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    experiment_id:          historical\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    model_id:               MIROC5\n",
       "    forcing:                GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG ...\n",
       "    ...                     ...\n",
       "    table_id:               Table Amon (31 January 2011) 53b766a395ac41696af4...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#changing time dim to datetime64[ns] dtype\n",
    "\n",
    "datetimeindex = data.indexes['time'].to_datetimeindex()\n",
    "data['time']=datetimeindex\n",
    "data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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       "}\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: 311, bnds: 2, lat: 128, lon: 256)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1980-01-16T12:00:00 ... 2005-11-16\n",
       "  * lat        (lat) float64 -88.93 -87.54 -86.14 -84.74 ... 86.14 87.54 88.93\n",
       "  * lon        (lon) float64 0.0 1.406 2.812 4.219 ... 354.4 355.8 357.2 358.6\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1980-01-01 00:00:00 ... 2005-12-01 00:00:00\n",
       "    lat_bnds   (lat, bnds) float64 -90.0 -88.28 -88.28 ... 88.28 88.28 90.0\n",
       "    lon_bnds   (lon, bnds) float64 -0.7031 0.7031 0.7031 ... 357.9 357.9 359.3\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/27)\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    experiment_id:          historical\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    model_id:               MIROC5\n",
       "    forcing:                GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG ...\n",
       "    ...                     ...\n",
       "    table_id:               Table Amon (31 January 2011) 53b766a395ac41696af4...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6</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-83c7d716-3b06-4e7e-9a0b-b3638a08938c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-83c7d716-3b06-4e7e-9a0b-b3638a08938c' 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>: 311</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 128</li><li><span class='xr-has-index'>lon</span>: 256</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f47ba82f-7aa4-4512-95b5-1cc2ffd2811f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f47ba82f-7aa4-4512-95b5-1cc2ffd2811f' 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'>1980-01-16T12:00:00 ... 2005-11-16</div><input id='attrs-0c0fd8b8-0476-4b93-b858-b14b9911a7b2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0c0fd8b8-0476-4b93-b858-b14b9911a7b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0414792d-27e3-44dd-a937-38a5d5bd0a19' class='xr-var-data-in' type='checkbox'><label for='data-0414792d-27e3-44dd-a937-38a5d5bd0a19' 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;1980-01-16T12:00:00.000000000&#x27;, &#x27;1980-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;1980-03-16T12:00:00.000000000&#x27;, ..., &#x27;2005-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-10-16T12:00:00.000000000&#x27;, &#x27;2005-11-16T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-88.93 -87.54 ... 87.54 88.93</div><input id='attrs-a304f4a8-96b3-4ad9-85c4-0b6dcc46c800' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a304f4a8-96b3-4ad9-85c4-0b6dcc46c800' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3c23e41-d57a-4cb9-926f-7185ed4c6977' class='xr-var-data-in' type='checkbox'><label for='data-a3c23e41-d57a-4cb9-926f-7185ed4c6977' 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-88.927735, -87.538705, -86.141472, -84.742386, -83.342596, -81.942466,\n",
       "       -80.542146, -79.14171 , -77.741196, -76.340629, -74.940023, -73.539389,\n",
       "       -72.138732, -70.738059, -69.337372, -67.936673, -66.535966, -65.135251,\n",
       "       -63.73453 , -62.333803, -60.933072, -59.532337, -58.131598, -56.730857,\n",
       "       -55.330112, -53.929366, -52.528617, -51.127867, -49.727115, -48.326361,\n",
       "       -46.925606, -45.52485 , -44.124093, -42.723335, -41.322576, -39.921816,\n",
       "       -38.521056, -37.120294, -35.719532, -34.31877 , -32.918007, -31.517244,\n",
       "       -30.11648 , -28.715716, -27.314951, -25.914186, -24.513421, -23.112655,\n",
       "       -21.71189 , -20.311124, -18.910357, -17.509591, -16.108824, -14.708057,\n",
       "       -13.30729 , -11.906523, -10.505756,  -9.104989,  -7.704221,  -6.303454,\n",
       "        -4.902687,  -3.501919,  -2.101151,  -0.700384,   0.700384,   2.101151,\n",
       "         3.501919,   4.902687,   6.303454,   7.704221,   9.104989,  10.505756,\n",
       "        11.906523,  13.30729 ,  14.708057,  16.108824,  17.509591,  18.910357,\n",
       "        20.311124,  21.71189 ,  23.112655,  24.513421,  25.914186,  27.314951,\n",
       "        28.715716,  30.11648 ,  31.517244,  32.918007,  34.31877 ,  35.719532,\n",
       "        37.120294,  38.521056,  39.921816,  41.322576,  42.723335,  44.124093,\n",
       "        45.52485 ,  46.925606,  48.326361,  49.727115,  51.127867,  52.528617,\n",
       "        53.929366,  55.330112,  56.730857,  58.131598,  59.532337,  60.933072,\n",
       "        62.333803,  63.73453 ,  65.135251,  66.535966,  67.936673,  69.337372,\n",
       "        70.738059,  72.138732,  73.539389,  74.940023,  76.340629,  77.741196,\n",
       "        79.14171 ,  80.542146,  81.942466,  83.342596,  84.742386,  86.141472,\n",
       "        87.538705,  88.927735])</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'>0.0 1.406 2.812 ... 357.2 358.6</div><input id='attrs-9ab04991-9b1d-4a06-952a-e94e6ca6ad2b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ab04991-9b1d-4a06-952a-e94e6ca6ad2b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a770f14e-aa28-4924-b905-68dce0ea862a' class='xr-var-data-in' type='checkbox'><label for='data-a770f14e-aa28-4924-b905-68dce0ea862a' 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.     ,   1.40625,   2.8125 , ..., 355.78125, 357.1875 , 358.59375])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e7f074cf-5608-4e0f-9505-d83eedfa588a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e7f074cf-5608-4e0f-9505-d83eedfa588a' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1980-01-01 00:00:00 ... 2005-12-...</div><input id='attrs-111d730b-2153-4301-9739-8102f58201b2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-111d730b-2153-4301-9739-8102f58201b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c6330c9-6751-4942-99d3-1d6199e00412' class='xr-var-data-in' type='checkbox'><label for='data-0c6330c9-6751-4942-99d3-1d6199e00412' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[cftime.DatetimeNoLeap(1980, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1980, 2, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1980, 2, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1980, 3, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1980, 3, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1980, 4, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       ...,\n",
       "       [cftime.DatetimeNoLeap(2005, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 10, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 10, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 11, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 11, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 12, 1, 0, 0, 0, 0, has_year_zero=True)]],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.28 -88.28 ... 88.28 90.0</div><input id='attrs-e7c3af51-08bc-45af-a8b4-30b1bf8373d8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e7c3af51-08bc-45af-a8b4-30b1bf8373d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-735da618-21b7-4711-a0ba-717984251205' class='xr-var-data-in' type='checkbox'><label for='data-735da618-21b7-4711-a0ba-717984251205' 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([[-90.      , -88.282245],\n",
       "       [-88.282245, -86.866422],\n",
       "       [-86.866422, -85.459991],\n",
       "       ...,\n",
       "       [ 85.459991,  86.866422],\n",
       "       [ 86.866422,  88.282245],\n",
       "       [ 88.282245,  90.      ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.7031 0.7031 ... 357.9 359.3</div><input id='attrs-37cf644c-4422-451a-a3d5-79105e747de5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-37cf644c-4422-451a-a3d5-79105e747de5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ed9fcd7-c9ff-4636-ab97-0d0bb3f6831c' class='xr-var-data-in' type='checkbox'><label for='data-9ed9fcd7-c9ff-4636-ab97-0d0bb3f6831c' 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([[ -0.703125,   0.703125],\n",
       "       [  0.703125,   2.109375],\n",
       "       [  2.109375,   3.515625],\n",
       "       ...,\n",
       "       [355.078125, 356.484375],\n",
       "       [356.484375, 357.890625],\n",
       "       [357.890625, 359.296875]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-94fa4565-0adf-4ffe-9344-ce4492aafd96' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94fa4565-0adf-4ffe-9344-ce4492aafd96' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11b4ee83-b173-4b9d-8ad5-29d4ee7d6825' class='xr-var-data-in' type='checkbox'><label for='data-11b4ee83-b173-4b9d-8ad5-29d4ee7d6825' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>comment :</span></dt><dd>at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>original_name :</span></dt><dd>PRCP</dd><dt><span>original_units :</span></dt><dd>kg/m**2/s</dd><dt><span>history :</span></dt><dd>2011-04-23T09:11:46Z altered by CMOR: Converted units from &#x27;kg/m**2/s&#x27; to &#x27;kg m-2 s-1&#x27;. 2011-04-23T09:11:46Z altered by CMOR: replaced missing value flag (-999) with standard missing value (1e+20). 2011-04-23T09:11:46Z altered by CMOR: Inverted axis: lat.</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MIROC5_historical_r0i0p0.nc areacella: areacella_fx_MIROC5_historical_r0i0p0.nc</dd></dl></div><div class='xr-var-data'><pre>[10190848 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e75bdecb-7bba-4a29-a50b-aec2379590ec' class='xr-section-summary-in' type='checkbox'  ><label for='section-e75bdecb-7bba-4a29-a50b-aec2379590ec' class='xr-section-summary' >Attributes: <span>(27)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>institution :</span></dt><dd>AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan), NIES (National Institute for Environmental Studies, Ibaraki, Japan), JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan)</dd><dt><span>institute_id :</span></dt><dd>MIROC</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>source :</span></dt><dd>MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); ocean: COCO (COCO4.5, 256x224 L50); sea ice: COCO (COCO4.5); land: MATSIRO (MATSIRO, L6); aerosols: SPRINTARS (SPRINTARS 5.00, T85L40)</dd><dt><span>model_id :</span></dt><dd>MIROC5</dd><dt><span>forcing :</span></dt><dd>GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG includes CO2, N2O, methane, and fluorocarbons; Oz includes OH and H2O2; LU excludes change in lake fraction)</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>150015.0</dd><dt><span>contact :</span></dt><dd>Masahiro Watanabe (hiro@aori.u-tokyo.ac.jp), Seita Emori (emori@nies.go.jp), Masayoshi Ishii (ism@jamstec.go.jp), Masahide Kimoto (kimoto@aori.u-tokyo.ac.jp)</dd><dt><span>references :</span></dt><dd>Watanabe et al., 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 6312-6335</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>a906be44-c850-4f0c-b8c4-2b165051669a</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>creation_date :</span></dt><dd>2011-04-23T09:11:46Z</dd><dt><span>history :</span></dt><dd>2011-04-23T09:11:46Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (31 January 2011) 53b766a395ac41696af40aab76a49ae5</dd><dt><span>title :</span></dt><dd>MIROC5 model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>1</dd><dt><span>cmor_version :</span></dt><dd>2.5.6</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (time: 311, bnds: 2, lat: 128, lon: 256)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1980-01-16T12:00:00 ... 2005-11-16\n",
       "  * lat        (lat) float64 -88.93 -87.54 -86.14 -84.74 ... 86.14 87.54 88.93\n",
       "  * lon        (lon) float64 0.0 1.406 2.812 4.219 ... 354.4 355.8 357.2 358.6\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1980-01-01 00:00:00 ... 2005-12-01 00:00:00\n",
       "    lat_bnds   (lat, bnds) float64 -90.0 -88.28 -88.28 ... 88.28 88.28 90.0\n",
       "    lon_bnds   (lon, bnds) float64 -0.7031 0.7031 0.7031 ... 357.9 357.9 359.3\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/27)\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    experiment_id:          historical\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    model_id:               MIROC5\n",
       "    forcing:                GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG ...\n",
       "    ...                     ...\n",
       "    table_id:               Table Amon (31 January 2011) 53b766a395ac41696af4...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6"
      ]
     },
     "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','2005-12-16T00:00:00.000000000'))\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 104, bnds: 2, lat: 128, lon: 256)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1980-06-16 ... 2005-09-16\n",
       "  * lat        (lat) float64 -88.93 -87.54 -86.14 -84.74 ... 86.14 87.54 88.93\n",
       "  * lon        (lon) float64 0.0 1.406 2.812 4.219 ... 354.4 355.8 357.2 358.6\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1980-06-01 00:00:00 ... 2005-10-01 00:00:00\n",
       "    lat_bnds   (lat, bnds) float64 -90.0 -88.28 -88.28 ... 88.28 88.28 90.0\n",
       "    lon_bnds   (lon, bnds) float64 -0.7031 0.7031 0.7031 ... 357.9 357.9 359.3\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/27)\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    experiment_id:          historical\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    model_id:               MIROC5\n",
       "    forcing:                GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG ...\n",
       "    ...                     ...\n",
       "    table_id:               Table Amon (31 January 2011) 53b766a395ac41696af4...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6</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-fa5f1bff-51a7-4d2f-bbac-e2e84aa1b29b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-fa5f1bff-51a7-4d2f-bbac-e2e84aa1b29b' 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>: 104</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 128</li><li><span class='xr-has-index'>lon</span>: 256</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ef300818-ec7a-41d8-beb0-d3f326c199ed' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ef300818-ec7a-41d8-beb0-d3f326c199ed' 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 ... 2005-09-16</div><input id='attrs-c9dadf89-fdbe-4ea2-9500-d4b3238d548c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c9dadf89-fdbe-4ea2-9500-d4b3238d548c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-732ced4e-d7fc-42b1-ad22-abe647e5a80e' class='xr-var-data-in' type='checkbox'><label for='data-732ced4e-d7fc-42b1-ad22-abe647e5a80e' 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;1980-06-16T00:00:00.000000000&#x27;, &#x27;1980-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1980-08-16T12:00:00.000000000&#x27;, &#x27;1980-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-06-16T00:00:00.000000000&#x27;, &#x27;1981-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1981-08-16T12:00:00.000000000&#x27;, &#x27;1981-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-06-16T00:00:00.000000000&#x27;, &#x27;1982-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1982-08-16T12:00:00.000000000&#x27;, &#x27;1982-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1983-06-16T00:00:00.000000000&#x27;, &#x27;1983-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1983-08-16T12:00:00.000000000&#x27;, &#x27;1983-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-06-16T00:00:00.000000000&#x27;, &#x27;1984-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1984-08-16T12:00:00.000000000&#x27;, &#x27;1984-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1985-06-16T00:00:00.000000000&#x27;, &#x27;1985-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1985-08-16T12:00:00.000000000&#x27;, &#x27;1985-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-06-16T00:00:00.000000000&#x27;, &#x27;1986-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1986-08-16T12:00:00.000000000&#x27;, &#x27;1986-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1987-06-16T00:00:00.000000000&#x27;, &#x27;1987-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1987-08-16T12:00:00.000000000&#x27;, &#x27;1987-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-06-16T00:00:00.000000000&#x27;, &#x27;1988-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1988-08-16T12:00:00.000000000&#x27;, &#x27;1988-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1989-06-16T00:00:00.000000000&#x27;, &#x27;1989-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1989-08-16T12:00:00.000000000&#x27;, &#x27;1989-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-06-16T00:00:00.000000000&#x27;, &#x27;1990-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1990-08-16T12:00:00.000000000&#x27;, &#x27;1990-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1991-06-16T00:00:00.000000000&#x27;, &#x27;1991-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1991-08-16T12:00:00.000000000&#x27;, &#x27;1991-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-06-16T00:00:00.000000000&#x27;, &#x27;1992-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1992-08-16T12:00:00.000000000&#x27;, &#x27;1992-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1993-06-16T00:00:00.000000000&#x27;, &#x27;1993-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1993-08-16T12:00:00.000000000&#x27;, &#x27;1993-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-06-16T00:00:00.000000000&#x27;, &#x27;1994-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1994-08-16T12:00:00.000000000&#x27;, &#x27;1994-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1995-06-16T00:00:00.000000000&#x27;, &#x27;1995-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1995-08-16T12:00:00.000000000&#x27;, &#x27;1995-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-06-16T00:00:00.000000000&#x27;, &#x27;1996-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1996-08-16T12:00:00.000000000&#x27;, &#x27;1996-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1997-06-16T00:00:00.000000000&#x27;, &#x27;1997-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1997-08-16T12:00:00.000000000&#x27;, &#x27;1997-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-06-16T00:00:00.000000000&#x27;, &#x27;1998-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1998-08-16T12:00:00.000000000&#x27;, &#x27;1998-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;1999-06-16T00:00:00.000000000&#x27;, &#x27;1999-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;1999-08-16T12:00:00.000000000&#x27;, &#x27;1999-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-16T00:00:00.000000000&#x27;, &#x27;2000-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2000-08-16T12:00:00.000000000&#x27;, &#x27;2000-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-06-16T00:00:00.000000000&#x27;, &#x27;2001-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2001-08-16T12:00:00.000000000&#x27;, &#x27;2001-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-06-16T00:00:00.000000000&#x27;, &#x27;2002-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-16T12:00:00.000000000&#x27;, &#x27;2002-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-06-16T00:00:00.000000000&#x27;, &#x27;2003-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2003-08-16T12:00:00.000000000&#x27;, &#x27;2003-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-06-16T00:00:00.000000000&#x27;, &#x27;2004-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2004-08-16T12:00:00.000000000&#x27;, &#x27;2004-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-06-16T00:00:00.000000000&#x27;, &#x27;2005-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2005-08-16T12:00:00.000000000&#x27;, &#x27;2005-09-16T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-88.93 -87.54 ... 87.54 88.93</div><input id='attrs-50539e10-0a87-4df0-b992-41be65159200' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-50539e10-0a87-4df0-b992-41be65159200' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6ab05ee-3625-42ff-be01-c9d06a43953d' class='xr-var-data-in' type='checkbox'><label for='data-b6ab05ee-3625-42ff-be01-c9d06a43953d' 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-88.927735, -87.538705, -86.141472, -84.742386, -83.342596, -81.942466,\n",
       "       -80.542146, -79.14171 , -77.741196, -76.340629, -74.940023, -73.539389,\n",
       "       -72.138732, -70.738059, -69.337372, -67.936673, -66.535966, -65.135251,\n",
       "       -63.73453 , -62.333803, -60.933072, -59.532337, -58.131598, -56.730857,\n",
       "       -55.330112, -53.929366, -52.528617, -51.127867, -49.727115, -48.326361,\n",
       "       -46.925606, -45.52485 , -44.124093, -42.723335, -41.322576, -39.921816,\n",
       "       -38.521056, -37.120294, -35.719532, -34.31877 , -32.918007, -31.517244,\n",
       "       -30.11648 , -28.715716, -27.314951, -25.914186, -24.513421, -23.112655,\n",
       "       -21.71189 , -20.311124, -18.910357, -17.509591, -16.108824, -14.708057,\n",
       "       -13.30729 , -11.906523, -10.505756,  -9.104989,  -7.704221,  -6.303454,\n",
       "        -4.902687,  -3.501919,  -2.101151,  -0.700384,   0.700384,   2.101151,\n",
       "         3.501919,   4.902687,   6.303454,   7.704221,   9.104989,  10.505756,\n",
       "        11.906523,  13.30729 ,  14.708057,  16.108824,  17.509591,  18.910357,\n",
       "        20.311124,  21.71189 ,  23.112655,  24.513421,  25.914186,  27.314951,\n",
       "        28.715716,  30.11648 ,  31.517244,  32.918007,  34.31877 ,  35.719532,\n",
       "        37.120294,  38.521056,  39.921816,  41.322576,  42.723335,  44.124093,\n",
       "        45.52485 ,  46.925606,  48.326361,  49.727115,  51.127867,  52.528617,\n",
       "        53.929366,  55.330112,  56.730857,  58.131598,  59.532337,  60.933072,\n",
       "        62.333803,  63.73453 ,  65.135251,  66.535966,  67.936673,  69.337372,\n",
       "        70.738059,  72.138732,  73.539389,  74.940023,  76.340629,  77.741196,\n",
       "        79.14171 ,  80.542146,  81.942466,  83.342596,  84.742386,  86.141472,\n",
       "        87.538705,  88.927735])</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'>0.0 1.406 2.812 ... 357.2 358.6</div><input id='attrs-af3a06b6-860f-4d3a-a16d-aec3095c3106' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af3a06b6-860f-4d3a-a16d-aec3095c3106' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f1b167e-29fb-4422-88a9-8ef74462fbe7' class='xr-var-data-in' type='checkbox'><label for='data-5f1b167e-29fb-4422-88a9-8ef74462fbe7' 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.     ,   1.40625,   2.8125 , ..., 355.78125, 357.1875 , 358.59375])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8dfb9794-78d4-4e8a-a78e-30e4f63dc735' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8dfb9794-78d4-4e8a-a78e-30e4f63dc735' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1980-06-01 00:00:00 ... 2005-10-...</div><input id='attrs-e9e3511c-0b7c-409c-b6d3-d5523a2d1e6c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e9e3511c-0b7c-409c-b6d3-d5523a2d1e6c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a632c48-8b4d-4aa0-b891-7e14b86681b8' class='xr-var-data-in' type='checkbox'><label for='data-2a632c48-8b4d-4aa0-b891-7e14b86681b8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[cftime.DatetimeNoLeap(1980, 6, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1980, 7, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1980, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1980, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(1980, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(1980, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       ...,\n",
       "       [cftime.DatetimeNoLeap(2005, 7, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 8, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 8, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 9, 1, 0, 0, 0, 0, has_year_zero=True)],\n",
       "       [cftime.DatetimeNoLeap(2005, 9, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "        cftime.DatetimeNoLeap(2005, 10, 1, 0, 0, 0, 0, has_year_zero=True)]],\n",
       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.28 -88.28 ... 88.28 90.0</div><input id='attrs-8e60b28f-6ff5-4ff1-b92d-b6cc4c7ac58a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8e60b28f-6ff5-4ff1-b92d-b6cc4c7ac58a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05e01e80-2eed-492a-b402-8d49a5c1747c' class='xr-var-data-in' type='checkbox'><label for='data-05e01e80-2eed-492a-b402-8d49a5c1747c' 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([[-90.      , -88.282245],\n",
       "       [-88.282245, -86.866422],\n",
       "       [-86.866422, -85.459991],\n",
       "       ...,\n",
       "       [ 85.459991,  86.866422],\n",
       "       [ 86.866422,  88.282245],\n",
       "       [ 88.282245,  90.      ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.7031 0.7031 ... 357.9 359.3</div><input id='attrs-8376b3dc-3ff5-48ef-9a14-7c846cbf3dad' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8376b3dc-3ff5-48ef-9a14-7c846cbf3dad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-831df11e-bf12-4d6a-9211-d6b802428899' class='xr-var-data-in' type='checkbox'><label for='data-831df11e-bf12-4d6a-9211-d6b802428899' 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([[ -0.703125,   0.703125],\n",
       "       [  0.703125,   2.109375],\n",
       "       [  2.109375,   3.515625],\n",
       "       ...,\n",
       "       [355.078125, 356.484375],\n",
       "       [356.484375, 357.890625],\n",
       "       [357.890625, 359.296875]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-34730aac-5411-461d-a372-6816f7322e8d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34730aac-5411-461d-a372-6816f7322e8d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-306f2a4b-eec8-47d1-9954-5c74df10c674' class='xr-var-data-in' type='checkbox'><label for='data-306f2a4b-eec8-47d1-9954-5c74df10c674' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>comment :</span></dt><dd>at surface; includes both liquid and solid phases from all types of clouds (both large-scale and convective)</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>original_name :</span></dt><dd>PRCP</dd><dt><span>original_units :</span></dt><dd>kg/m**2/s</dd><dt><span>history :</span></dt><dd>2011-04-23T09:11:46Z altered by CMOR: Converted units from &#x27;kg/m**2/s&#x27; to &#x27;kg m-2 s-1&#x27;. 2011-04-23T09:11:46Z altered by CMOR: replaced missing value flag (-999) with standard missing value (1e+20). 2011-04-23T09:11:46Z altered by CMOR: Inverted axis: lat.</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_MIROC5_historical_r0i0p0.nc areacella: areacella_fx_MIROC5_historical_r0i0p0.nc</dd></dl></div><div class='xr-var-data'><pre>[3407872 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-193c57ed-5d5b-4d22-aa0e-8020d558c276' class='xr-section-summary-in' type='checkbox'  ><label for='section-193c57ed-5d5b-4d22-aa0e-8020d558c276' class='xr-section-summary' >Attributes: <span>(27)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>institution :</span></dt><dd>AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba, Japan), NIES (National Institute for Environmental Studies, Ibaraki, Japan), JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan)</dd><dt><span>institute_id :</span></dt><dd>MIROC</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>source :</span></dt><dd>MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); ocean: COCO (COCO4.5, 256x224 L50); sea ice: COCO (COCO4.5); land: MATSIRO (MATSIRO, L6); aerosols: SPRINTARS (SPRINTARS 5.00, T85L40)</dd><dt><span>model_id :</span></dt><dd>MIROC5</dd><dt><span>forcing :</span></dt><dd>GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG includes CO2, N2O, methane, and fluorocarbons; Oz includes OH and H2O2; LU excludes change in lake fraction)</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_experiment_rip :</span></dt><dd>r1i1p1</dd><dt><span>branch_time :</span></dt><dd>150015.0</dd><dt><span>contact :</span></dt><dd>Masahiro Watanabe (hiro@aori.u-tokyo.ac.jp), Seita Emori (emori@nies.go.jp), Masayoshi Ishii (ism@jamstec.go.jp), Masahide Kimoto (kimoto@aori.u-tokyo.ac.jp)</dd><dt><span>references :</span></dt><dd>Watanabe et al., 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 6312-6335</dd><dt><span>initialization_method :</span></dt><dd>1</dd><dt><span>physics_version :</span></dt><dd>1</dd><dt><span>tracking_id :</span></dt><dd>a906be44-c850-4f0c-b8c4-2b165051669a</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>experiment :</span></dt><dd>historical</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>creation_date :</span></dt><dd>2011-04-23T09:11:46Z</dd><dt><span>history :</span></dt><dd>2011-04-23T09:11:46Z CMOR rewrote data to comply with CF standards and CMIP5 requirements.</dd><dt><span>Conventions :</span></dt><dd>CF-1.4</dd><dt><span>project_id :</span></dt><dd>CMIP5</dd><dt><span>table_id :</span></dt><dd>Table Amon (31 January 2011) 53b766a395ac41696af40aab76a49ae5</dd><dt><span>title :</span></dt><dd>MIROC5 model output prepared for CMIP5 historical</dd><dt><span>parent_experiment :</span></dt><dd>pre-industrial control</dd><dt><span>modeling_realm :</span></dt><dd>atmos</dd><dt><span>realization :</span></dt><dd>1</dd><dt><span>cmor_version :</span></dt><dd>2.5.6</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (time: 104, bnds: 2, lat: 128, lon: 256)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1980-06-16 ... 2005-09-16\n",
       "  * lat        (lat) float64 -88.93 -87.54 -86.14 -84.74 ... 86.14 87.54 88.93\n",
       "  * lon        (lon) float64 0.0 1.406 2.812 4.219 ... 354.4 355.8 357.2 358.6\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) object 1980-06-01 00:00:00 ... 2005-10-01 00:00:00\n",
       "    lat_bnds   (lat, bnds) float64 -90.0 -88.28 -88.28 ... 88.28 88.28 90.0\n",
       "    lon_bnds   (lon, bnds) float64 -0.7031 0.7031 0.7031 ... 357.9 357.9 359.3\n",
       "    pr         (time, lat, lon) float32 ...\n",
       "Attributes: (12/27)\n",
       "    institution:            AORI (Atmosphere and Ocean Research Institute, Th...\n",
       "    institute_id:           MIROC\n",
       "    experiment_id:          historical\n",
       "    source:                 MIROC5 2010 atmosphere: MIROC-AGCM6 (T85L40); oce...\n",
       "    model_id:               MIROC5\n",
       "    forcing:                GHG, SA, Oz, LU, Sl, Vl, SS, Ds, BC, MD, OC (GHG ...\n",
       "    ...                     ...\n",
       "    table_id:               Table Amon (31 January 2011) 53b766a395ac41696af4...\n",
       "    title:                  MIROC5 model output prepared for CMIP5 historical\n",
       "    parent_experiment:      pre-industrial control\n",
       "    modeling_realm:         atmos\n",
       "    realization:            1\n",
       "    cmor_version:           2.5.6"
      ]
     },
     "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,
   "metadata": {},
   "outputs": [],
   "source": [
    "#data[\"pr\"][\"x\"][379:429].values\n",
    "#data[\"pr\"][\"y\"][237:337].values\n",
    "#data[\"pr\"][\"time\"].values\n",
    "#jjas_data[\"pr\"][\"lat\"][:].values\n",
    "\n",
    "#jjas_data[\"pr\"][\"lon\"][:].values\n",
    "\n",
    "\n",
    "#data[\"pr\"][\"x\"].values\n",
    "\n",
    "#data.x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#data[\"pr\"][\"y\"][287:337].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#to select the x and y coordinates\n",
    "#jjas_data = jjas_data.sel(x=slice(4125000.,5350000.),y=slice(2975000.,4200000.))\n",
    "#jjas_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (lat: 128, lon: 256)&gt;\n",
       "array([[1.15539422e-06, 1.14948443e-06, 1.14279112e-06, ...,\n",
       "        1.17554760e-06, 1.16925355e-06, 1.16207570e-06],\n",
       "       [1.88219258e-06, 1.87360217e-06, 1.86568150e-06, ...,\n",
       "        1.90439562e-06, 1.89695379e-06, 1.88982824e-06],\n",
       "       [1.69459940e-06, 1.68878876e-06, 1.68348572e-06, ...,\n",
       "        1.72177295e-06, 1.71116233e-06, 1.70190947e-06],\n",
       "       ...,\n",
       "       [9.72515591e-06, 9.75703824e-06, 9.76447063e-06, ...,\n",
       "        9.63018738e-06, 9.66072184e-06, 9.68647782e-06],\n",
       "       [1.00939706e-05, 1.00860261e-05, 1.00778725e-05, ...,\n",
       "        1.00945072e-05, 1.01152555e-05, 1.01194801e-05],\n",
       "       [8.14148552e-06, 8.14163468e-06, 8.14073974e-06, ...,\n",
       "        8.11566315e-06, 8.12682447e-06, 8.13207043e-06]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lat      (lat) float64 -88.93 -87.54 -86.14 -84.74 ... 86.14 87.54 88.93\n",
       "  * lon      (lon) float64 0.0 1.406 2.812 4.219 ... 354.4 355.8 357.2 358.6</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'pr'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 128</li><li><span class='xr-has-index'>lon</span>: 256</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-772b1284-a1c3-441f-9471-dd8f70dd0b12' class='xr-array-in' type='checkbox' checked><label for='section-772b1284-a1c3-441f-9471-dd8f70dd0b12' 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>1.155e-06 1.149e-06 1.143e-06 ... 8.116e-06 8.127e-06 8.132e-06</span></div><div class='xr-array-data'><pre>array([[1.15539422e-06, 1.14948443e-06, 1.14279112e-06, ...,\n",
       "        1.17554760e-06, 1.16925355e-06, 1.16207570e-06],\n",
       "       [1.88219258e-06, 1.87360217e-06, 1.86568150e-06, ...,\n",
       "        1.90439562e-06, 1.89695379e-06, 1.88982824e-06],\n",
       "       [1.69459940e-06, 1.68878876e-06, 1.68348572e-06, ...,\n",
       "        1.72177295e-06, 1.71116233e-06, 1.70190947e-06],\n",
       "       ...,\n",
       "       [9.72515591e-06, 9.75703824e-06, 9.76447063e-06, ...,\n",
       "        9.63018738e-06, 9.66072184e-06, 9.68647782e-06],\n",
       "       [1.00939706e-05, 1.00860261e-05, 1.00778725e-05, ...,\n",
       "        1.00945072e-05, 1.01152555e-05, 1.01194801e-05],\n",
       "       [8.14148552e-06, 8.14163468e-06, 8.14073974e-06, ...,\n",
       "        8.11566315e-06, 8.12682447e-06, 8.13207043e-06]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-06b55844-fea4-4a08-be3a-76e2805ca1f1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-06b55844-fea4-4a08-be3a-76e2805ca1f1' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-88.93 -87.54 ... 87.54 88.93</div><input id='attrs-1c5e263e-6fe4-4d74-997d-824c5b72b78b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c5e263e-6fe4-4d74-997d-824c5b72b78b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-670cd8ac-59db-4051-a34d-1d8ee5c8af37' class='xr-var-data-in' type='checkbox'><label for='data-670cd8ac-59db-4051-a34d-1d8ee5c8af37' 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-88.927735, -87.538705, -86.141472, -84.742386, -83.342596, -81.942466,\n",
       "       -80.542146, -79.14171 , -77.741196, -76.340629, -74.940023, -73.539389,\n",
       "       -72.138732, -70.738059, -69.337372, -67.936673, -66.535966, -65.135251,\n",
       "       -63.73453 , -62.333803, -60.933072, -59.532337, -58.131598, -56.730857,\n",
       "       -55.330112, -53.929366, -52.528617, -51.127867, -49.727115, -48.326361,\n",
       "       -46.925606, -45.52485 , -44.124093, -42.723335, -41.322576, -39.921816,\n",
       "       -38.521056, -37.120294, -35.719532, -34.31877 , -32.918007, -31.517244,\n",
       "       -30.11648 , -28.715716, -27.314951, -25.914186, -24.513421, -23.112655,\n",
       "       -21.71189 , -20.311124, -18.910357, -17.509591, -16.108824, -14.708057,\n",
       "       -13.30729 , -11.906523, -10.505756,  -9.104989,  -7.704221,  -6.303454,\n",
       "        -4.902687,  -3.501919,  -2.101151,  -0.700384,   0.700384,   2.101151,\n",
       "         3.501919,   4.902687,   6.303454,   7.704221,   9.104989,  10.505756,\n",
       "        11.906523,  13.30729 ,  14.708057,  16.108824,  17.509591,  18.910357,\n",
       "        20.311124,  21.71189 ,  23.112655,  24.513421,  25.914186,  27.314951,\n",
       "        28.715716,  30.11648 ,  31.517244,  32.918007,  34.31877 ,  35.719532,\n",
       "        37.120294,  38.521056,  39.921816,  41.322576,  42.723335,  44.124093,\n",
       "        45.52485 ,  46.925606,  48.326361,  49.727115,  51.127867,  52.528617,\n",
       "        53.929366,  55.330112,  56.730857,  58.131598,  59.532337,  60.933072,\n",
       "        62.333803,  63.73453 ,  65.135251,  66.535966,  67.936673,  69.337372,\n",
       "        70.738059,  72.138732,  73.539389,  74.940023,  76.340629,  77.741196,\n",
       "        79.14171 ,  80.542146,  81.942466,  83.342596,  84.742386,  86.141472,\n",
       "        87.538705,  88.927735])</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'>0.0 1.406 2.812 ... 357.2 358.6</div><input id='attrs-2d073b03-ee11-41a6-bda5-5896526a0f52' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2d073b03-ee11-41a6-bda5-5896526a0f52' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cbba234-f0de-40c9-b8aa-8ebab3c36640' class='xr-var-data-in' type='checkbox'><label for='data-2cbba234-f0de-40c9-b8aa-8ebab3c36640' 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.     ,   1.40625,   2.8125 , ..., 355.78125, 357.1875 , 358.59375])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8df09c61-491d-49ce-8b7e-aecab622ced1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8df09c61-491d-49ce-8b7e-aecab622ced1' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'pr' (lat: 128, lon: 256)>\n",
       "array([[1.15539422e-06, 1.14948443e-06, 1.14279112e-06, ...,\n",
       "        1.17554760e-06, 1.16925355e-06, 1.16207570e-06],\n",
       "       [1.88219258e-06, 1.87360217e-06, 1.86568150e-06, ...,\n",
       "        1.90439562e-06, 1.89695379e-06, 1.88982824e-06],\n",
       "       [1.69459940e-06, 1.68878876e-06, 1.68348572e-06, ...,\n",
       "        1.72177295e-06, 1.71116233e-06, 1.70190947e-06],\n",
       "       ...,\n",
       "       [9.72515591e-06, 9.75703824e-06, 9.76447063e-06, ...,\n",
       "        9.63018738e-06, 9.66072184e-06, 9.68647782e-06],\n",
       "       [1.00939706e-05, 1.00860261e-05, 1.00778725e-05, ...,\n",
       "        1.00945072e-05, 1.01152555e-05, 1.01194801e-05],\n",
       "       [8.14148552e-06, 8.14163468e-06, 8.14073974e-06, ...,\n",
       "        8.11566315e-06, 8.12682447e-06, 8.13207043e-06]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lat      (lat) float64 -88.93 -87.54 -86.14 -84.74 ... 86.14 87.54 88.93\n",
       "  * lon      (lon) float64 0.0 1.406 2.812 4.219 ... 354.4 355.8 357.2 358.6"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#getting the mean for JJAS data\n",
    "jjas_mean = jjas_data.pr.mean('time')\n",
    " \n",
    "jjas_mean "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The pr is given in kg m $^{-2}$  s $^{-1}$ so we have to convert it into mm/day.\n",
    "\n",
    "The formula is 1 kgm$^{-2}$ s$^{-1}$  = 86400 mm/day. \n",
    "\n",
    "so we have to divide pr value by 86400\n",
    "\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (lat: 128, lon: 256)&gt;\n",
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       "       [0.70342435, 0.70343724, 0.70335991, ..., 0.7011933 , 0.70215763,\n",
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       "Coordinates:\n",
       "  * lat      (lat) float64 -88.93 -87.54 -86.14 -84.74 ... 86.14 87.54 88.93\n",
       "  * lon      (lon) float64 0.0 1.406 2.812 4.219 ... 354.4 355.8 357.2 358.6</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'pr'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 128</li><li><span class='xr-has-index'>lon</span>: 256</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-6d545770-2574-4e1d-b7e2-d7a2fda5606d' class='xr-array-in' type='checkbox' checked><label for='section-6d545770-2574-4e1d-b7e2-d7a2fda5606d' 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>0.09983 0.09932 0.09874 0.0981 0.09762 ... 0.7004 0.7012 0.7022 0.7026</span></div><div class='xr-array-data'><pre>array([[0.09982606, 0.09931546, 0.09873715, ..., 0.10156731, 0.10102351,\n",
       "        0.10040334],\n",
       "       [0.16262144, 0.16187923, 0.16119488, ..., 0.16453978, 0.16389681,\n",
       "        0.16328116],\n",
       "       [0.14641339, 0.14591135, 0.14545317, ..., 0.14876118, 0.14784443,\n",
       "        0.14704498],\n",
       "       ...,\n",
       "       [0.84025347, 0.8430081 , 0.84365026, ..., 0.83204819, 0.83468637,\n",
       "        0.83691168],\n",
       "       [0.87211906, 0.87143266, 0.87072818, ..., 0.87216542, 0.87395807,\n",
       "        0.87432308],\n",
       "       [0.70342435, 0.70343724, 0.70335991, ..., 0.7011933 , 0.70215763,\n",
       "        0.70261089]])</pre></div></div></li><li class='xr-section-item'><input id='section-e88d8f60-2a1f-4c43-8bba-871984b105d8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e88d8f60-2a1f-4c43-8bba-871984b105d8' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-88.93 -87.54 ... 87.54 88.93</div><input id='attrs-86e67d17-b1e7-40ec-88c0-bfd005f8f355' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-86e67d17-b1e7-40ec-88c0-bfd005f8f355' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48c42b10-5e20-48fd-a13e-a704beb6d033' class='xr-var-data-in' type='checkbox'><label for='data-48c42b10-5e20-48fd-a13e-a704beb6d033' 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-88.927735, -87.538705, -86.141472, -84.742386, -83.342596, -81.942466,\n",
       "       -80.542146, -79.14171 , -77.741196, -76.340629, -74.940023, -73.539389,\n",
       "       -72.138732, -70.738059, -69.337372, -67.936673, -66.535966, -65.135251,\n",
       "       -63.73453 , -62.333803, -60.933072, -59.532337, -58.131598, -56.730857,\n",
       "       -55.330112, -53.929366, -52.528617, -51.127867, -49.727115, -48.326361,\n",
       "       -46.925606, -45.52485 , -44.124093, -42.723335, -41.322576, -39.921816,\n",
       "       -38.521056, -37.120294, -35.719532, -34.31877 , -32.918007, -31.517244,\n",
       "       -30.11648 , -28.715716, -27.314951, -25.914186, -24.513421, -23.112655,\n",
       "       -21.71189 , -20.311124, -18.910357, -17.509591, -16.108824, -14.708057,\n",
       "       -13.30729 , -11.906523, -10.505756,  -9.104989,  -7.704221,  -6.303454,\n",
       "        -4.902687,  -3.501919,  -2.101151,  -0.700384,   0.700384,   2.101151,\n",
       "         3.501919,   4.902687,   6.303454,   7.704221,   9.104989,  10.505756,\n",
       "        11.906523,  13.30729 ,  14.708057,  16.108824,  17.509591,  18.910357,\n",
       "        20.311124,  21.71189 ,  23.112655,  24.513421,  25.914186,  27.314951,\n",
       "        28.715716,  30.11648 ,  31.517244,  32.918007,  34.31877 ,  35.719532,\n",
       "        37.120294,  38.521056,  39.921816,  41.322576,  42.723335,  44.124093,\n",
       "        45.52485 ,  46.925606,  48.326361,  49.727115,  51.127867,  52.528617,\n",
       "        53.929366,  55.330112,  56.730857,  58.131598,  59.532337,  60.933072,\n",
       "        62.333803,  63.73453 ,  65.135251,  66.535966,  67.936673,  69.337372,\n",
       "        70.738059,  72.138732,  73.539389,  74.940023,  76.340629,  77.741196,\n",
       "        79.14171 ,  80.542146,  81.942466,  83.342596,  84.742386,  86.141472,\n",
       "        87.538705,  88.927735])</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'>0.0 1.406 2.812 ... 357.2 358.6</div><input id='attrs-7c00a53e-e9b5-4d23-a288-d78f4d84ecd6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c00a53e-e9b5-4d23-a288-d78f4d84ecd6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4ccb877-3a56-4d81-a473-02409b042925' class='xr-var-data-in' type='checkbox'><label for='data-a4ccb877-3a56-4d81-a473-02409b042925' 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.     ,   1.40625,   2.8125 , ..., 355.78125, 357.1875 , 358.59375])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f335721f-8180-4b74-bfc5-38351bc21c31' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f335721f-8180-4b74-bfc5-38351bc21c31' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'pr' (lat: 128, lon: 256)>\n",
       "array([[0.09982606, 0.09931546, 0.09873715, ..., 0.10156731, 0.10102351,\n",
       "        0.10040334],\n",
       "       [0.16262144, 0.16187923, 0.16119488, ..., 0.16453978, 0.16389681,\n",
       "        0.16328116],\n",
       "       [0.14641339, 0.14591135, 0.14545317, ..., 0.14876118, 0.14784443,\n",
       "        0.14704498],\n",
       "       ...,\n",
       "       [0.84025347, 0.8430081 , 0.84365026, ..., 0.83204819, 0.83468637,\n",
       "        0.83691168],\n",
       "       [0.87211906, 0.87143266, 0.87072818, ..., 0.87216542, 0.87395807,\n",
       "        0.87432308],\n",
       "       [0.70342435, 0.70343724, 0.70335991, ..., 0.7011933 , 0.70215763,\n",
       "        0.70261089]])\n",
       "Coordinates:\n",
       "  * lat      (lat) float64 -88.93 -87.54 -86.14 -84.74 ... 86.14 87.54 88.93\n",
       "  * lon      (lon) float64 0.0 1.406 2.812 4.219 ... 354.4 355.8 357.2 358.6"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr_mm = jjas_mean*86400\n",
    "pr_mm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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",
    "\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",
    " \n",
    "\n",
    "plt.title('GCM MIROC5 Mean jjas precip rate in mm/day')\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/bd_pr_gcm_miroc5_jjas_mean.png\")\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now I will plot the annual precipitation rate in mm/day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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       "\n",
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       "  display: none;\n",
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       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
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       "  display: inline-block;\n",
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       "\n",
       ".xr-dim-list {\n",
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       "\n",
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       ".xr-var-list,\n",
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       "  display: contents;\n",
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       ".xr-var-item > .xr-var-name span {\n",
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       ".xr-var-item > .xr-var-name:hover span {\n",
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       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
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       ".xr-var-dims:hover,\n",
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       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
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       "\n",
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       "  display: block;\n",
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       "\n",
       ".xr-var-data > table {\n",
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       "\n",
       ".xr-var-name span,\n",
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       "\n",
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       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
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       "}\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",
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       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
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       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (lat: 128, lon: 256)&gt;\n",
       "array([[1.1444860e-06, 1.1404799e-06, 1.1358239e-06, ..., 1.1577439e-06,\n",
       "        1.1530580e-06, 1.1488692e-06],\n",
       "       [1.8707394e-06, 1.8676566e-06, 1.8655284e-06, ..., 1.8810017e-06,\n",
       "        1.8778356e-06, 1.8747237e-06],\n",
       "       [1.8706703e-06, 1.8666018e-06, 1.8626365e-06, ..., 1.8959269e-06,\n",
       "        1.8853108e-06, 1.8769289e-06],\n",
       "       ...,\n",
       "       [6.6059324e-06, 6.6286198e-06, 6.6449170e-06, ..., 6.5361769e-06,\n",
       "        6.5602417e-06, 6.5823792e-06],\n",
       "       [6.3846446e-06, 6.3759048e-06, 6.3679936e-06, ..., 6.4032470e-06,\n",
       "        6.4048236e-06, 6.4020901e-06],\n",
       "       [4.8590969e-06, 4.8594607e-06, 4.8631000e-06, ..., 4.8563147e-06,\n",
       "        4.8587808e-06, 4.8582074e-06]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lat      (lat) float64 -88.93 -87.54 -86.14 -84.74 ... 86.14 87.54 88.93\n",
       "  * lon      (lon) float64 0.0 1.406 2.812 4.219 ... 354.4 355.8 357.2 358.6</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'pr'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 128</li><li><span class='xr-has-index'>lon</span>: 256</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-80f41f52-a805-4c86-af29-a4b6d96b6529' class='xr-array-in' type='checkbox' checked><label for='section-80f41f52-a805-4c86-af29-a4b6d96b6529' 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>1.144e-06 1.14e-06 1.136e-06 ... 4.856e-06 4.859e-06 4.858e-06</span></div><div class='xr-array-data'><pre>array([[1.1444860e-06, 1.1404799e-06, 1.1358239e-06, ..., 1.1577439e-06,\n",
       "        1.1530580e-06, 1.1488692e-06],\n",
       "       [1.8707394e-06, 1.8676566e-06, 1.8655284e-06, ..., 1.8810017e-06,\n",
       "        1.8778356e-06, 1.8747237e-06],\n",
       "       [1.8706703e-06, 1.8666018e-06, 1.8626365e-06, ..., 1.8959269e-06,\n",
       "        1.8853108e-06, 1.8769289e-06],\n",
       "       ...,\n",
       "       [6.6059324e-06, 6.6286198e-06, 6.6449170e-06, ..., 6.5361769e-06,\n",
       "        6.5602417e-06, 6.5823792e-06],\n",
       "       [6.3846446e-06, 6.3759048e-06, 6.3679936e-06, ..., 6.4032470e-06,\n",
       "        6.4048236e-06, 6.4020901e-06],\n",
       "       [4.8590969e-06, 4.8594607e-06, 4.8631000e-06, ..., 4.8563147e-06,\n",
       "        4.8587808e-06, 4.8582074e-06]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-a306df89-b2e4-423a-9f3d-f40dccab9144' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a306df89-b2e4-423a-9f3d-f40dccab9144' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-88.93 -87.54 ... 87.54 88.93</div><input id='attrs-7ddeffa7-2a44-448d-a6b8-faab7072ee3d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ddeffa7-2a44-448d-a6b8-faab7072ee3d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cd3c623-422a-4e9b-aaa1-8da0e28aa8b4' class='xr-var-data-in' type='checkbox'><label for='data-2cd3c623-422a-4e9b-aaa1-8da0e28aa8b4' 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-88.927735, -87.538705, -86.141472, -84.742386, -83.342596, -81.942466,\n",
       "       -80.542146, -79.14171 , -77.741196, -76.340629, -74.940023, -73.539389,\n",
       "       -72.138732, -70.738059, -69.337372, -67.936673, -66.535966, -65.135251,\n",
       "       -63.73453 , -62.333803, -60.933072, -59.532337, -58.131598, -56.730857,\n",
       "       -55.330112, -53.929366, -52.528617, -51.127867, -49.727115, -48.326361,\n",
       "       -46.925606, -45.52485 , -44.124093, -42.723335, -41.322576, -39.921816,\n",
       "       -38.521056, -37.120294, -35.719532, -34.31877 , -32.918007, -31.517244,\n",
       "       -30.11648 , -28.715716, -27.314951, -25.914186, -24.513421, -23.112655,\n",
       "       -21.71189 , -20.311124, -18.910357, -17.509591, -16.108824, -14.708057,\n",
       "       -13.30729 , -11.906523, -10.505756,  -9.104989,  -7.704221,  -6.303454,\n",
       "        -4.902687,  -3.501919,  -2.101151,  -0.700384,   0.700384,   2.101151,\n",
       "         3.501919,   4.902687,   6.303454,   7.704221,   9.104989,  10.505756,\n",
       "        11.906523,  13.30729 ,  14.708057,  16.108824,  17.509591,  18.910357,\n",
       "        20.311124,  21.71189 ,  23.112655,  24.513421,  25.914186,  27.314951,\n",
       "        28.715716,  30.11648 ,  31.517244,  32.918007,  34.31877 ,  35.719532,\n",
       "        37.120294,  38.521056,  39.921816,  41.322576,  42.723335,  44.124093,\n",
       "        45.52485 ,  46.925606,  48.326361,  49.727115,  51.127867,  52.528617,\n",
       "        53.929366,  55.330112,  56.730857,  58.131598,  59.532337,  60.933072,\n",
       "        62.333803,  63.73453 ,  65.135251,  66.535966,  67.936673,  69.337372,\n",
       "        70.738059,  72.138732,  73.539389,  74.940023,  76.340629,  77.741196,\n",
       "        79.14171 ,  80.542146,  81.942466,  83.342596,  84.742386,  86.141472,\n",
       "        87.538705,  88.927735])</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'>0.0 1.406 2.812 ... 357.2 358.6</div><input id='attrs-d790def3-c4ce-4de7-b2aa-59419b555524' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d790def3-c4ce-4de7-b2aa-59419b555524' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48a4a8e9-57a4-4981-82e6-81f0b31ba799' class='xr-var-data-in' type='checkbox'><label for='data-48a4a8e9-57a4-4981-82e6-81f0b31ba799' 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.     ,   1.40625,   2.8125 , ..., 355.78125, 357.1875 , 358.59375])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-eb913770-b13b-4f59-8a38-1e4569bcffc4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-eb913770-b13b-4f59-8a38-1e4569bcffc4' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'pr' (lat: 128, lon: 256)>\n",
       "array([[1.1444860e-06, 1.1404799e-06, 1.1358239e-06, ..., 1.1577439e-06,\n",
       "        1.1530580e-06, 1.1488692e-06],\n",
       "       [1.8707394e-06, 1.8676566e-06, 1.8655284e-06, ..., 1.8810017e-06,\n",
       "        1.8778356e-06, 1.8747237e-06],\n",
       "       [1.8706703e-06, 1.8666018e-06, 1.8626365e-06, ..., 1.8959269e-06,\n",
       "        1.8853108e-06, 1.8769289e-06],\n",
       "       ...,\n",
       "       [6.6059324e-06, 6.6286198e-06, 6.6449170e-06, ..., 6.5361769e-06,\n",
       "        6.5602417e-06, 6.5823792e-06],\n",
       "       [6.3846446e-06, 6.3759048e-06, 6.3679936e-06, ..., 6.4032470e-06,\n",
       "        6.4048236e-06, 6.4020901e-06],\n",
       "       [4.8590969e-06, 4.8594607e-06, 4.8631000e-06, ..., 4.8563147e-06,\n",
       "        4.8587808e-06, 4.8582074e-06]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lat      (lat) float64 -88.93 -87.54 -86.14 -84.74 ... 86.14 87.54 88.93\n",
       "  * lon      (lon) float64 0.0 1.406 2.812 4.219 ... 354.4 355.8 357.2 358.6"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "annual_mean = data.pr.mean('time')\n",
    "annual_mean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;pr&#x27; (lat: 128, lon: 256)&gt;\n",
       "array([[0.09888359, 0.09853746, 0.09813519, ..., 0.10002907, 0.09962421,\n",
       "        0.0992623 ],\n",
       "       [0.16163189, 0.16136553, 0.16118165, ..., 0.16251855, 0.162245  ,\n",
       "        0.16197613],\n",
       "       [0.16162591, 0.16127439, 0.16093179, ..., 0.16380808, 0.16289085,\n",
       "        0.16216665],\n",
       "       ...,\n",
       "       [0.57075256, 0.57271275, 0.57412083, ..., 0.56472568, 0.56680488,\n",
       "        0.56871757],\n",
       "       [0.5516333 , 0.55087818, 0.55019465, ..., 0.55324054, 0.55337676,\n",
       "        0.55314058],\n",
       "       [0.41982597, 0.4198574 , 0.42017184, ..., 0.41958559, 0.41979866,\n",
       "        0.41974912]])\n",
       "Coordinates:\n",
       "  * lat      (lat) float64 -88.93 -87.54 -86.14 -84.74 ... 86.14 87.54 88.93\n",
       "  * lon      (lon) float64 0.0 1.406 2.812 4.219 ... 354.4 355.8 357.2 358.6</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'pr'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 128</li><li><span class='xr-has-index'>lon</span>: 256</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-51cb29f9-a859-4094-86a8-a8091c114a71' class='xr-array-in' type='checkbox' checked><label for='section-51cb29f9-a859-4094-86a8-a8091c114a71' 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>0.09888 0.09854 0.09814 0.09769 ... 0.4193 0.4196 0.4198 0.4197</span></div><div class='xr-array-data'><pre>array([[0.09888359, 0.09853746, 0.09813519, ..., 0.10002907, 0.09962421,\n",
       "        0.0992623 ],\n",
       "       [0.16163189, 0.16136553, 0.16118165, ..., 0.16251855, 0.162245  ,\n",
       "        0.16197613],\n",
       "       [0.16162591, 0.16127439, 0.16093179, ..., 0.16380808, 0.16289085,\n",
       "        0.16216665],\n",
       "       ...,\n",
       "       [0.57075256, 0.57271275, 0.57412083, ..., 0.56472568, 0.56680488,\n",
       "        0.56871757],\n",
       "       [0.5516333 , 0.55087818, 0.55019465, ..., 0.55324054, 0.55337676,\n",
       "        0.55314058],\n",
       "       [0.41982597, 0.4198574 , 0.42017184, ..., 0.41958559, 0.41979866,\n",
       "        0.41974912]])</pre></div></div></li><li class='xr-section-item'><input id='section-da2b02c5-784b-44b0-895d-f9989e3412e4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-da2b02c5-784b-44b0-895d-f9989e3412e4' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-88.93 -87.54 ... 87.54 88.93</div><input id='attrs-598010f3-8a74-461f-8577-5c9c260986e9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-598010f3-8a74-461f-8577-5c9c260986e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-567ecc1f-9457-4c38-b72f-8696fda294de' class='xr-var-data-in' type='checkbox'><label for='data-567ecc1f-9457-4c38-b72f-8696fda294de' 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-88.927735, -87.538705, -86.141472, -84.742386, -83.342596, -81.942466,\n",
       "       -80.542146, -79.14171 , -77.741196, -76.340629, -74.940023, -73.539389,\n",
       "       -72.138732, -70.738059, -69.337372, -67.936673, -66.535966, -65.135251,\n",
       "       -63.73453 , -62.333803, -60.933072, -59.532337, -58.131598, -56.730857,\n",
       "       -55.330112, -53.929366, -52.528617, -51.127867, -49.727115, -48.326361,\n",
       "       -46.925606, -45.52485 , -44.124093, -42.723335, -41.322576, -39.921816,\n",
       "       -38.521056, -37.120294, -35.719532, -34.31877 , -32.918007, -31.517244,\n",
       "       -30.11648 , -28.715716, -27.314951, -25.914186, -24.513421, -23.112655,\n",
       "       -21.71189 , -20.311124, -18.910357, -17.509591, -16.108824, -14.708057,\n",
       "       -13.30729 , -11.906523, -10.505756,  -9.104989,  -7.704221,  -6.303454,\n",
       "        -4.902687,  -3.501919,  -2.101151,  -0.700384,   0.700384,   2.101151,\n",
       "         3.501919,   4.902687,   6.303454,   7.704221,   9.104989,  10.505756,\n",
       "        11.906523,  13.30729 ,  14.708057,  16.108824,  17.509591,  18.910357,\n",
       "        20.311124,  21.71189 ,  23.112655,  24.513421,  25.914186,  27.314951,\n",
       "        28.715716,  30.11648 ,  31.517244,  32.918007,  34.31877 ,  35.719532,\n",
       "        37.120294,  38.521056,  39.921816,  41.322576,  42.723335,  44.124093,\n",
       "        45.52485 ,  46.925606,  48.326361,  49.727115,  51.127867,  52.528617,\n",
       "        53.929366,  55.330112,  56.730857,  58.131598,  59.532337,  60.933072,\n",
       "        62.333803,  63.73453 ,  65.135251,  66.535966,  67.936673,  69.337372,\n",
       "        70.738059,  72.138732,  73.539389,  74.940023,  76.340629,  77.741196,\n",
       "        79.14171 ,  80.542146,  81.942466,  83.342596,  84.742386,  86.141472,\n",
       "        87.538705,  88.927735])</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'>0.0 1.406 2.812 ... 357.2 358.6</div><input id='attrs-27c07300-7b0c-4c68-9f3b-0cb5ec0e962b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-27c07300-7b0c-4c68-9f3b-0cb5ec0e962b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b9e5ce0-160e-4e19-b082-33cef4f5d235' class='xr-var-data-in' type='checkbox'><label for='data-7b9e5ce0-160e-4e19-b082-33cef4f5d235' 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.     ,   1.40625,   2.8125 , ..., 355.78125, 357.1875 , 358.59375])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3828f26a-42bf-416c-8383-f39765acb27a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3828f26a-42bf-416c-8383-f39765acb27a' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'pr' (lat: 128, lon: 256)>\n",
       "array([[0.09888359, 0.09853746, 0.09813519, ..., 0.10002907, 0.09962421,\n",
       "        0.0992623 ],\n",
       "       [0.16163189, 0.16136553, 0.16118165, ..., 0.16251855, 0.162245  ,\n",
       "        0.16197613],\n",
       "       [0.16162591, 0.16127439, 0.16093179, ..., 0.16380808, 0.16289085,\n",
       "        0.16216665],\n",
       "       ...,\n",
       "       [0.57075256, 0.57271275, 0.57412083, ..., 0.56472568, 0.56680488,\n",
       "        0.56871757],\n",
       "       [0.5516333 , 0.55087818, 0.55019465, ..., 0.55324054, 0.55337676,\n",
       "        0.55314058],\n",
       "       [0.41982597, 0.4198574 , 0.42017184, ..., 0.41958559, 0.41979866,\n",
       "        0.41974912]])\n",
       "Coordinates:\n",
       "  * lat      (lat) float64 -88.93 -87.54 -86.14 -84.74 ... 86.14 87.54 88.93\n",
       "  * lon      (lon) float64 0.0 1.406 2.812 4.219 ... 354.4 355.8 357.2 358.6"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#converting from kgm-2s-2 to mm/day\n",
    "\n",
    "annual_pr_mm = annual_mean*86400\n",
    "annual_pr_mm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x684 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=(12.5,9.5))\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",
    "\n",
    "#plt.title('GCM MIROC5 Annual mean precip rate in mm/day',fontweight=\"bold\", fontsize=15)\n",
    "\n",
    "plt.title('GCM MIROC5 Annual mean precip rate in mm/day')\n",
    "\n",
    "\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/bd_pr_gcm_miroc5_annual_mean.png\")\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
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 },
 "nbformat": 4,
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}