pdf_regcm_mpiesm.ipynb

{
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    "#writing some conda package or module\n",
    "#!pip install netCDF4\n",
    "%matplotlib inline\n",
    "import warnings\n",
    "from netCDF4 import Dataset\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "#!pip install cartopy\n",
    "import cartopy.feature as cfeature\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.mpl.ticker as cticker\n",
    "from cartopy.util import add_cyclic_point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9b4e84e2",
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    "rain_minimum = 1.0\n",
    "rain_maximum = 250.0\n",
    "rain_step = 1.0\n",
    "spd = 86400.0\n",
    "sph = 3600.0\n",
    "mpy = 30.4167\n",
    "\n",
    "nrainbin = int((rain_maximum-rain_minimum)/rain_step) + 1\n",
    "\n",
    "rain_pdf = np.linspace(rain_minimum,rain_maximum, num=nrainbin, endpoint=True)\n",
    "rain_bin = np.zeros((nrainbin-1))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3e1b1bb0",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (time: 432, bnds: 2, y: 337, x: 429)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1970-01-16T12:00:00 ... 2005-12-16T12:00:00\n",
       "    lon        (y, x) float64 ...\n",
       "    lat        (y, x) float64 ...\n",
       "  * x          (x) float64 -5.35e+06 -5.325e+06 -5.3e+06 ... 5.325e+06 5.35e+06\n",
       "  * y          (y) float64 -4.2e+06 -4.175e+06 -4.15e+06 ... 4.175e+06 4.2e+06\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) datetime64[ns] 1970-01-01 1970-02-01 ... 2006-01-01\n",
       "    crs        |S1 b&#x27;&#x27;\n",
       "    pr         (time, y, x) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Mon Jun 27 15:35:42 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment:                              MPI-M-MPI-ESM-MR, histor...\n",
       "    driving_model_id:                                MPI-M-MPI-ESM-MR\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    CDO:                                             Climate Data Operators v...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-671b23dd-93f2-4174-a1d7-073ecca583a0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-671b23dd-93f2-4174-a1d7-073ecca583a0' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 432</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>y</span>: 337</li><li><span class='xr-has-index'>x</span>: 429</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c02ee450-c25c-46e3-8766-bb4b4fef8e06' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c02ee450-c25c-46e3-8766-bb4b4fef8e06' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1970-01-16T12:00:00 ... 2005-12-...</div><input id='attrs-7467309e-68b9-47a8-84ec-ddd9fa70ce6c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7467309e-68b9-47a8-84ec-ddd9fa70ce6c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-648b0143-ac0e-4151-8b0d-d0600684e890' class='xr-var-data-in' type='checkbox'><label for='data-648b0143-ac0e-4151-8b0d-d0600684e890' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1970-01-16T12:00:00.000000000&#x27;, &#x27;1970-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;1970-03-16T12:00:00.000000000&#x27;, ..., &#x27;2005-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2005-11-16T00:00:00.000000000&#x27;, &#x27;2005-12-16T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cf9d8a5a-4c2b-4f77-92b9-6e8b4a8f1cac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cf9d8a5a-4c2b-4f77-92b9-6e8b4a8f1cac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-007af1e9-786b-4569-9525-3feacff29a18' class='xr-var-data-in' type='checkbox'><label for='data-007af1e9-786b-4569-9525-3feacff29a18' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>Longitude on Cross Points</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd></dl></div><div class='xr-var-data'><pre>[144573 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fe0807bd-6069-4353-868f-25873910d8db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fe0807bd-6069-4353-868f-25873910d8db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5f535f5-7a08-48ad-b8ca-130eb4494525' class='xr-var-data-in' type='checkbox'><label for='data-d5f535f5-7a08-48ad-b8ca-130eb4494525' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>Latitude on Cross Points</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd></dl></div><div class='xr-var-data'><pre>[144573 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.35e+06 -5.325e+06 ... 5.35e+06</div><input id='attrs-c9ab5e3f-2544-48a9-8fb3-881665123d8f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c9ab5e3f-2544-48a9-8fb3-881665123d8f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67e0dd32-5f83-4b2e-9b42-3df9e584b4a4' class='xr-var-data-in' type='checkbox'><label for='data-67e0dd32-5f83-4b2e-9b42-3df9e584b4a4' 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>projection_x_coordinate</dd><dt><span>long_name :</span></dt><dd>x-coordinate in Cartesian system</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-5350000., -5325000., -5300000., ...,  5300000.,  5325000.,  5350000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.2e+06 -4.175e+06 ... 4.2e+06</div><input id='attrs-24b9158c-3b06-493b-bb54-a8a8eae8f74d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24b9158c-3b06-493b-bb54-a8a8eae8f74d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0331e448-bdbe-46e4-a7fa-20ff8d5304f4' class='xr-var-data-in' type='checkbox'><label for='data-0331e448-bdbe-46e4-a7fa-20ff8d5304f4' 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>projection_y_coordinate</dd><dt><span>long_name :</span></dt><dd>y-coordinate in Cartesian system</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-4200000., -4175000., -4150000., ...,  4150000.,  4175000.,  4200000.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d7a375b2-d45b-424e-9fb1-6a9c875f1215' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d7a375b2-d45b-424e-9fb1-6a9c875f1215' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7d410575-2695-4d5c-b114-7982bf02f15a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7d410575-2695-4d5c-b114-7982bf02f15a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c4c6d254-feb8-4eae-acac-ca2b148f06b3' class='xr-var-data-in' type='checkbox'><label for='data-c4c6d254-feb8-4eae-acac-ca2b148f06b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;1970-01-01T00:00:00.000000000&#x27;, &#x27;1970-02-01T00:00:00.000000000&#x27;],\n",
       "       [&#x27;1970-02-01T00:00:00.000000000&#x27;, &#x27;1970-03-01T00:00:00.000000000&#x27;],\n",
       "       [&#x27;1970-03-01T00:00:00.000000000&#x27;, &#x27;1970-04-01T00:00:00.000000000&#x27;],\n",
       "       ...,\n",
       "       [&#x27;2005-10-01T00:00:00.000000000&#x27;, &#x27;2005-11-01T00:00:00.000000000&#x27;],\n",
       "       [&#x27;2005-11-01T00:00:00.000000000&#x27;, &#x27;2005-12-01T00:00:00.000000000&#x27;],\n",
       "       [&#x27;2005-12-01T00:00:00.000000000&#x27;, &#x27;2006-01-01T00:00:00.000000000&#x27;]],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>crs</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S1</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4b98e2db-d20b-481b-83a0-063ca5d9a07e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b98e2db-d20b-481b-83a0-063ca5d9a07e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a842110-c9a2-420f-8a0c-9b8b3df792a5' class='xr-var-data-in' type='checkbox'><label for='data-0a842110-c9a2-420f-8a0c-9b8b3df792a5' 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>proj4_params :</span></dt><dd>+proj=omerc +lat_0=13.00 +alpha=89.999999 +lonc=70.00 +x_0=-12500. +y_0=-12500. +ellps=sphere +a=6371229. +b=6371229. +units=m +no_defs</dd><dt><span>semi_major_axis :</span></dt><dd>6371229.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>azimuth_of_central_line :</span></dt><dd>89.999999</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>13.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>70.0</dd><dt><span>scale_factor_at_projection_origin :</span></dt><dd>1.0</dd><dt><span>false_easting :</span></dt><dd>-12500.0</dd><dt><span>false_northing :</span></dt><dd>-12500.0</dd><dt><span>grid_mapping_name :</span></dt><dd>oblique_mercator</dd></dl></div><div class='xr-var-data'><pre>array(b&#x27;&#x27;, dtype=&#x27;|S1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pr</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ffd36474-cc2b-4dc4-9ad9-eb5724a9f0b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ffd36474-cc2b-4dc4-9ad9-eb5724a9f0b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-87dc18d1-43cf-45e6-a814-13e82e877527' class='xr-var-data-in' type='checkbox'><label for='data-87dc18d1-43cf-45e6-a814-13e82e877527' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>precipitation_flux</dd><dt><span>long_name :</span></dt><dd>Precipitation</dd><dt><span>units :</span></dt><dd>kg m-2 s-1</dd><dt><span>grid_mapping :</span></dt><dd>crs</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd></dl></div><div class='xr-var-data'><pre>[62455536 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b7b4b7a3-5574-44da-ab64-6ba32b6464cb' class='xr-section-summary-in' type='checkbox'  ><label for='section-b7b4b7a3-5574-44da-ab64-6ba32b6464cb' class='xr-section-summary' >Attributes: <span>(165)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 1.9.9rc1 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>history :</span></dt><dd>Mon Jun 27 15:35:42 2022: cdo mergetime pr_WAS-22_MPI-M-MPI-ESM-MR_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_197001-198012.nc pr_WAS-22_MPI-M-MPI-ESM-MR_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_198101-199012.nc pr_WAS-22_MPI-M-MPI-ESM-MR_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_199101-200012.nc pr_WAS-22_MPI-M-MPI-ESM-MR_historical_r1i1p1_ICTP-RegCM4-7_v0_mon_200101-200512.nc mpiesm_pr_197001-200512.nc\n",
       "2019-05-16 03:08:44 : Created by RegCM RegCM Model program</dd><dt><span>source :</span></dt><dd>RegCM Model output file</dd><dt><span>institution :</span></dt><dd>Oak Ridge National Laboratory</dd><dt><span>project_id :</span></dt><dd>CORDEX</dd><dt><span>ipcc_scenario_code :</span></dt><dd>HISTORICAL</dd><dt><span>institute_id :</span></dt><dd>ORNL</dd><dt><span>note :</span></dt><dd>The domain is larger than WAS-22</dd><dt><span>comment :</span></dt><dd>RegCM CORDEX SAsia25 run</dd><dt><span>experiment :</span></dt><dd>WAS-22</dd><dt><span>driving_model_ensemble_member :</span></dt><dd>r1i1p1</dd><dt><span>creation_date :</span></dt><dd>2019-09-13T16:14:09Z</dd><dt><span>CORDEX_domain :</span></dt><dd>WAS-22</dd><dt><span>rcm_version_id :</span></dt><dd>v0</dd><dt><span>ICTP_version_note :</span></dt><dd>Model run at ORNL on Titan</dd><dt><span>contact :</span></dt><dd>mashfaq@ornl.gov</dd><dt><span>product :</span></dt><dd>output</dd><dt><span>tracking_id :</span></dt><dd>83ebbad8-8c3d-11e9-81e7-7845c4fae25e</dd><dt><span>title :</span></dt><dd>ICTP Regional Climatic model V4</dd><dt><span>references :</span></dt><dd>http://gforge.ictp.it/gf/project/regcm</dd><dt><span>model_revision :</span></dt><dd>tag-4.7.0</dd><dt><span>projection :</span></dt><dd>ROTMER</dd><dt><span>grid_size_in_meters :</span></dt><dd>25000.0</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>13.0</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>70.0</dd><dt><span>grid_north_pole_latitude :</span></dt><dd>13.0</dd><dt><span>grid_north_pole_longitude :</span></dt><dd>70.0</dd><dt><span>grid_factor :</span></dt><dd>0.0</dd><dt><span>landsurface_model :</span></dt><dd>clm4.5</dd><dt><span>model_icbc_data_source :</span></dt><dd>MP_85</dd><dt><span>model_sst_data_source :</span></dt><dd>MP_85</dd><dt><span>boundary_nspgx :</span></dt><dd>30</dd><dt><span>boundary_nspgd :</span></dt><dd>30</dd><dt><span>boundary_high_nudge :</span></dt><dd>8.0</dd><dt><span>boundary_medium_nudge :</span></dt><dd>6.0</dd><dt><span>boundary_low_nudge :</span></dt><dd>4.0</dd><dt><span>boundary_nm :</span></dt><dd>-1.0</dd><dt><span>boundary_dm :</span></dt><dd>-1.0</dd><dt><span>model_is_restarted :</span></dt><dd>No</dd><dt><span>model_simulation_initial_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_start :</span></dt><dd> 1970-01-01 00:00:00 UTC</dd><dt><span>model_simulation_end :</span></dt><dd> 2005-12-31 00:00:00 UTC</dd><dt><span>atmosphere_time_step_in_seconds :</span></dt><dd>24.0</dd><dt><span>surface_interaction_time_step_in_seconds :</span></dt><dd>480.0</dd><dt><span>convection_time_step_in_seconds :</span></dt><dd>288.0</dd><dt><span>radiation_scheme_time_step_in_seconds :</span></dt><dd>1800.0</dd><dt><span>absorption_emission_time_step_in_seconds :</span></dt><dd>64800.0</dd><dt><span>dynamical_core :</span></dt><dd>1</dd><dt><span>asselin_filter_nu_1 :</span></dt><dd>0.0625</dd><dt><span>asselin_filter_nu_2 :</span></dt><dd>0.0625</dd><dt><span>diffusion_hgt_factor :</span></dt><dd>1</dd><dt><span>upstream_mode :</span></dt><dd>Yes</dd><dt><span>off_centering_max :</span></dt><dd>0.25</dd><dt><span>stability_enhance :</span></dt><dd>Yes</dd><dt><span>temperature_extreme_gradient :</span></dt><dd>5.0</dd><dt><span>cloud_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>vapor_extreme_gradient_fraction :</span></dt><dd>0.2</dd><dt><span>tracer_extreme_gradient_fraction :</span></dt><dd>0.5</dd><dt><span>lateral_boundary_condition_scheme :</span></dt><dd>5</dd><dt><span>semi_lagrangian_advection_scheme :</span></dt><dd>0</dd><dt><span>boundary_layer_scheme :</span></dt><dd>2</dd><dt><span>cumulus_convection_scheme_lnd :</span></dt><dd>4</dd><dt><span>cumulus_convection_scheme_ocn :</span></dt><dd>5</dd><dt><span>moisture_scheme :</span></dt><dd>1</dd><dt><span>ocean_flux_scheme :</span></dt><dd>2</dd><dt><span>zeng_ocean_roughness_formula :</span></dt><dd>1</dd><dt><span>zeng_ocean_roughness_method :</span></dt><dd>1</dd><dt><span>pressure_gradient_scheme :</span></dt><dd>0</dd><dt><span>surface_emissivity_factor_computed :</span></dt><dd>0</dd><dt><span>lake_model_activated :</span></dt><dd>0</dd><dt><span>chemical_aerosol_scheme_activated :</span></dt><dd>0</dd><dt><span>diurnal_cycle_sst_scheme :</span></dt><dd>0</dd><dt><span>ocean_precipitaion_cooling_effect :</span></dt><dd>0</dd><dt><span>ocean_albedo_from_whitecapping :</span></dt><dd>0</dd><dt><span>simple_sea_ice_scheme :</span></dt><dd>0</dd><dt><span>seasonal_desert_albedo :</span></dt><dd>0</dd><dt><span>convective_lwp_as_large_scale :</span></dt><dd>0</dd><dt><span>large_scale_cloud_fraction_scheme :</span></dt><dd>0</dd><dt><span>ocean_stratiform_clouds_scheme :</span></dt><dd>1</dd><dt><span>rrtm_radiation_scheme_activated :</span></dt><dd>0</dd><dt><span>climatic_ozone_input_dataset :</span></dt><dd>0</dd><dt><span>climatic_aerosol_input_dataset :</span></dt><dd>0</dd><dt><span>static_solar_constant_used :</span></dt><dd>0</dd><dt><span>cumulus_cloud_model :</span></dt><dd>1</dd><dt><span>sun_year_offset :</span></dt><dd>0.0</dd><dt><span>fix_solar_parameters :</span></dt><dd>0</dd><dt><span>cloud_bottom_level_with_no_clouds :</span></dt><dd>1</dd><dt><span>cloud_rh_with_fcc_one :</span></dt><dd>1.01</dd><dt><span>cloud_rh_threshold_for_land :</span></dt><dd>0.8</dd><dt><span>cloud_rh_threshold_for_ocean :</span></dt><dd>0.9</dd><dt><span>cloud_rh1_limit_temperature :</span></dt><dd>238.0</dd><dt><span>cloud_cloud_fraction_maximum :</span></dt><dd>0.75</dd><dt><span>cloud_condensation_threshold :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_fraction_max_for_convection :</span></dt><dd>1.0</dd><dt><span>cloud_cloud_liqwat_max_for_convection :</span></dt><dd>0.0003</dd><dt><span>cloud_shallow_convective_cf_param :</span></dt><dd>0.07</dd><dt><span>cloud_deep_convective_cf_param :</span></dt><dd>0.14</dd><dt><span>cloud_k2_convective_cf_param :</span></dt><dd>500.0</dd><dt><span>cloud_surface_radiation_hack :</span></dt><dd>No</dd><dt><span>cloud_arctic_cloud_correction :</span></dt><dd>Yes</dd><dt><span>subex_auto_conversion_rate_for_land :</span></dt><dd>0.00025</dd><dt><span>subex_auto_conversion_rate_for_ocean :</span></dt><dd>0.00025</dd><dt><span>subex_gultepe_factor_when_rain_for_land :</span></dt><dd>0.4</dd><dt><span>subex_gultepe_factor_when_rain_for_ocean :</span></dt><dd>0.4</dd><dt><span>subex_land_raindrop_evaporation_rate :</span></dt><dd>0.0002</dd><dt><span>subex_ocean_raindrop_evaporation_rate :</span></dt><dd>0.0001</dd><dt><span>subex_land_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>subex_ocean_raindrop_accretion_rate :</span></dt><dd>3.0</dd><dt><span>mit_lowest_convection_sigma :</span></dt><dd>0.95</dd><dt><span>mit_autoconversion_threshold_mixing_over_ocean :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_mixing_over_land :</span></dt><dd>0.00011</dd><dt><span>mit_autoconversion_threshold_temperature :</span></dt><dd>-55.0</dd><dt><span>mit_mixing_coefficient_in_entrainment :</span></dt><dd>1.5</dd><dt><span>mit_fractional_area_unsaturated_downdraft :</span></dt><dd>0.05</dd><dt><span>mit_fractional_precip_outside_cloud :</span></dt><dd>0.12</dd><dt><span>mit_pressure_velocity_of_rain :</span></dt><dd>50.0</dd><dt><span>mit_pressure_velocity_of_snow :</span></dt><dd>5.5</dd><dt><span>mit_rain_evaporation_coefficient :</span></dt><dd>1.0</dd><dt><span>mit_snow_evaporation_coefficient :</span></dt><dd>0.8</dd><dt><span>mit_momentum_transport_coefficient :</span></dt><dd>0.7</dd><dt><span>mit_downdraft_velocity_coefficient :</span></dt><dd>10.0</dd><dt><span>mit_max_parcel_neg_temp_perturbation :</span></dt><dd>0.9</dd><dt><span>mit_approach_rate_quasi_eq_coeff_a :</span></dt><dd>0.2</dd><dt><span>mit_approach_rate_quasi_eq_coeff_d :</span></dt><dd>0.1</dd><dt><span>mit_maximum_land_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>mit_maximum_ocean_precipitation_efficiency :</span></dt><dd>0.999</dd><dt><span>tiedtke_actual_scheme :</span></dt><dd>4</dd><dt><span>tiedtke_entrainment_rate_downdraft :</span></dt><dd>0.0003</dd><dt><span>tiedtke_entrainment_rate_deep_land :</span></dt><dd>0.00075</dd><dt><span>tiedtke_entrainment_rate_deep_ocean :</span></dt><dd>0.00075</dd><dt><span>tiedtke_penetrative :</span></dt><dd>Yes</dd><dt><span>tiedtke_midlevel :</span></dt><dd>Yes</dd><dt><span>tiedtke_shallow :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_downdraft :</span></dt><dd>Yes</dd><dt><span>tiedtke_prognostic_cloud :</span></dt><dd>Yes</dd><dt><span>tiedtke_cumulus_friction :</span></dt><dd>Yes</dd><dt><span>tiedtke_ke_dissipation :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_transport :</span></dt><dd>Yes</dd><dt><span>tiedtke_tracer_smooth_massflux :</span></dt><dd>No</dd><dt><span>tiedtke_shallow_wstar_closure :</span></dt><dd>No</dd><dt><span>tiedtke_detrainment_rate_deep_land :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_detrainment_rate_deep_ocean :</span></dt><dd>7.5e-05</dd><dt><span>tiedtke_shallow_entrainment :</span></dt><dd>2.0</dd><dt><span>tiedtke_cloud_cover_evap_over_land :</span></dt><dd>0.05</dd><dt><span>tiedtke_cloud_cover_evap_over_ocean :</span></dt><dd>0.05</dd><dt><span>tiedtke_coeff_evap_over_land :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_coeff_evap_over_ocean :</span></dt><dd>5.55e-05</dd><dt><span>tiedtke_critical_rh_over_land :</span></dt><dd>0.9</dd><dt><span>tiedtke_critical_rh_over_ocean :</span></dt><dd>0.9</dd><dt><span>tiedtke_cloud_water_conv_over_land :</span></dt><dd>0.03</dd><dt><span>tiedtke_cloud_water_conv_over_ocean :</span></dt><dd>0.0014</dd><dt><span>tiedtke_cape_adjustment_timescale :</span></dt><dd>2400.0</dd><dt><span>uwpbl_advection_scheme :</span></dt><dd>0</dd><dt><span>uwpbl_cloud_evap_entr_incr_efficiency :</span></dt><dd>15.0</dd><dt><span>uwpbl_eddy_LS_stable_PBL_scaling :</span></dt><dd>1.5</dd><dt><span>uwpbl_czero :</span></dt><dd>5.869</dd><dt><span>uwpbl_nuk :</span></dt><dd>5.0</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>driving_experiment :</span></dt><dd>MPI-M-MPI-ESM-MR, historical, r1i1p1</dd><dt><span>driving_model_id :</span></dt><dd>MPI-M-MPI-ESM-MR</dd><dt><span>driving_experiment_name :</span></dt><dd>historical</dd><dt><span>model_id :</span></dt><dd>ICTP-RegCM4-7</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.9rc1 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (time: 432, bnds: 2, y: 337, x: 429)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1970-01-16T12:00:00 ... 2005-12-16T12:00:00\n",
       "    lon        (y, x) float64 ...\n",
       "    lat        (y, x) float64 ...\n",
       "  * x          (x) float64 -5.35e+06 -5.325e+06 -5.3e+06 ... 5.325e+06 5.35e+06\n",
       "  * y          (y) float64 -4.2e+06 -4.175e+06 -4.15e+06 ... 4.175e+06 4.2e+06\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) datetime64[ns] ...\n",
       "    crs        |S1 ...\n",
       "    pr         (time, y, x) float32 ...\n",
       "Attributes: (12/165)\n",
       "    CDI:                                             Climate Data Interface v...\n",
       "    Conventions:                                     CF-1.7\n",
       "    history:                                         Mon Jun 27 15:35:42 2022...\n",
       "    source:                                          RegCM Model output file\n",
       "    institution:                                     Oak Ridge National Labor...\n",
       "    project_id:                                      CORDEX\n",
       "    ...                                              ...\n",
       "    experiment_id:                                   historical\n",
       "    driving_experiment:                              MPI-M-MPI-ESM-MR, histor...\n",
       "    driving_model_id:                                MPI-M-MPI-ESM-MR\n",
       "    driving_experiment_name:                         historical\n",
       "    model_id:                                        ICTP-RegCM4-7\n",
       "    CDO:                                             Climate Data Operators v..."
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "pr = xr.open_dataset('/home/mkibria/Academic/pr_of_thesis/regcm driven by gcm/MPI-ESM-MR/mpiesm_pr_197001-200512.nc')\n",
    "\n",
    "pr\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c6e12424",
   "metadata": {},
   "outputs": [],
   "source": [
    "#pr = pr.sel(time=slice('1980-01-16T12:00:00.000000000','2015-12-16T00:00:00.000000000'))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a7bc5951",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "#interpolating to new lat and lon\n",
    "\n",
    "#new_lon = np.arange(85,94,0.5)\n",
    "#new_lat = np.arange(17,28,0.5)\n",
    "#pr = pr.interp(latitude=new_lat,longitude=new_lon)\n",
    "#pr\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2100d68b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(432, 337, 429)\n"
     ]
    }
   ],
   "source": [
    "size = pr.pr.shape\n",
    "print(size)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "77d6e633",
   "metadata": {},
   "outputs": [],
   "source": [
    "for time in range(size[0]):\n",
    "        data = pr.pr[time,Ellipsis] * spd\n",
    "        nzd  = data.values[tuple(np.where(data >= rain_minimum))]\n",
    "        hist = np.histogram(nzd,\n",
    "                            bins = nrainbin-1,\n",
    "                            range = (rain_minimum, rain_maximum))\n",
    "        rain_bin = rain_bin + hist[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "307f9480",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(1, 1, 1)\n",
    "plt.plot(rain_bin, 'mo')\n",
    "ax.set_yscale('log')\n",
    "ax.set_xscale('log')\n",
    "plt.xlabel('Precipitation [mm/day]')\n",
    "plt.ylabel('Event Number [#]')\n",
    "plt.title('Precipitation daily PDF-regcm_mpiesm')\n",
    "plt.savefig(\"/home/mkibria/Academic/pr_of_thesis/figures/pdf_regcm_mpiesm.png\")\n",
    "\n",
    "\n",
    "\n",
    "plt.show( )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a43f36ef",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
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