co_evolution_plotting.ipynb

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    "## This script will calulate the time lag of wave precipitation and plot them\n",
    "\n",
    " Author:    Fouzia Fahrin (ffahrin@iastate.edu)"
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    "import numpy as np \n",
    "import matplotlib.pyplot as plt\n",
    "import xarray as xr\n",
    "from netCDF4 import Dataset\n",
    "import pandas as pd\n",
    "import netCDF4\n",
    "\n",
    "from cartopy import config\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfeature\n",
    "from cartopy.util import add_cyclic_point\n",
    "\n",
    "from mpl_toolkits.axes_grid1 import ImageGrid\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,\n",
    "                               AutoMinorLocator)\n",
    "\n",
    "import h5py\n",
    "from datetime import datetime\n",
    "import scipy.stats\n",
    "from scipy import stats\n",
    "import tol_colors as tc"
   ]
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   "source": [
    "wave = \"Kelvin\"  #change accordingly"
   ]
  },
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   "id": "0c316b8a-e6f4-4b94-ac61-26a4eb60a5ae",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:           (time: 7792, lat: 71, lon: 360)\n",
       "Coordinates:\n",
       "  * time              (time) datetime64[ns] 2000-06-01 2000-06-02 ... 2021-09-30\n",
       "  * lat               (lat) float64 -35.0 -34.0 -33.0 -32.0 ... 33.0 34.0 35.0\n",
       "  * lon               (lon) float64 0.0 1.0 2.0 3.0 ... 356.0 357.0 358.0 359.0\n",
       "Data variables:\n",
       "    precipitationCal  (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    creation_date:  Mon Nov 13 03:33:26 PM CST 2023\n",
       "    years:          2000-2021\n",
       "    symmetry:       none\n",
       "    wave_type:      Kelvin wave\n",
       "    title:          IMERG_20000601-20210930_anom_final filtered anomalies</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-5fe75ddd-2038-4f47-9fcc-669e4d657229' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5fe75ddd-2038-4f47-9fcc-669e4d657229' 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>: 7792</li><li><span class='xr-has-index'>lat</span>: 71</li><li><span class='xr-has-index'>lon</span>: 360</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-01582ebb-f3ce-431f-abfc-f386021c4021' class='xr-section-summary-in' type='checkbox'  checked><label for='section-01582ebb-f3ce-431f-abfc-f386021c4021' 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'>2000-06-01 ... 2021-09-30</div><input id='attrs-5a71bf7e-b860-4e1e-8ae2-ef7c0e5504d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a71bf7e-b860-4e1e-8ae2-ef7c0e5504d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47477f80-1653-4e25-8366-b696d790b067' class='xr-var-data-in' type='checkbox'><label for='data-47477f80-1653-4e25-8366-b696d790b067' 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>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2000-06-01T00:00:00.000000000&#x27;, &#x27;2000-06-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-03T00:00:00.000000000&#x27;, ..., &#x27;2021-09-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-09-29T00:00:00.000000000&#x27;, &#x27;2021-09-30T00:00:00.000000000&#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'>-35.0 -34.0 -33.0 ... 34.0 35.0</div><input id='attrs-f8cf2d44-9850-4d91-ba3b-de899a79a650' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f8cf2d44-9850-4d91-ba3b-de899a79a650' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-119c4b1a-ad62-4e46-859d-67d9daad583f' class='xr-var-data-in' type='checkbox'><label for='data-119c4b1a-ad62-4e46-859d-67d9daad583f' 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>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>degrees_north</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([-35., -34., -33., -32., -31., -30., -29., -28., -27., -26., -25., -24.,\n",
       "       -23., -22., -21., -20., -19., -18., -17., -16., -15., -14., -13., -12.,\n",
       "       -11., -10.,  -9.,  -8.,  -7.,  -6.,  -5.,  -4.,  -3.,  -2.,  -1.,   0.,\n",
       "         1.,   2.,   3.,   4.,   5.,   6.,   7.,   8.,   9.,  10.,  11.,  12.,\n",
       "        13.,  14.,  15.,  16.,  17.,  18.,  19.,  20.,  21.,  22.,  23.,  24.,\n",
       "        25.,  26.,  27.,  28.,  29.,  30.,  31.,  32.,  33.,  34.,  35.])</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 1.0 2.0 ... 357.0 358.0 359.0</div><input id='attrs-da5f9327-e2ee-4d29-9056-a1e6f3c7e09f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da5f9327-e2ee-4d29-9056-a1e6f3c7e09f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0501aff2-1622-4ef0-928d-73776191e015' class='xr-var-data-in' type='checkbox'><label for='data-0501aff2-1622-4ef0-928d-73776191e015' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   1.,   2., ..., 357., 358., 359.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-742630de-b54a-4316-9ad4-93870916a722' class='xr-section-summary-in' type='checkbox'  checked><label for='section-742630de-b54a-4316-9ad4-93870916a722' class='xr-section-summary' >Data variables: <span>(1)</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>precipitationCal</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-1ba4ee57-4737-41ac-aa12-d36337f5e9ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ba4ee57-4737-41ac-aa12-d36337f5e9ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba680f54-c7b3-4b63-8980-f38a2974868e' class='xr-var-data-in' type='checkbox'><label for='data-ba680f54-c7b3-4b63-8980-f38a2974868e' 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>waveName :</span></dt><dd>Kelvin</dd><dt><span>depth :</span></dt><dd>[ 8 90]</dd><dt><span>period :</span></dt><dd>[ 2.5 14. ]</dd><dt><span>wavenumber :</span></dt><dd>[ 1 14]</dd><dt><span>lat :</span></dt><dd>35.0</dd><dt><span>long_name :</span></dt><dd>Daily accumulated precipitation (combined microwave-IR) estimate</dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>title :</span></dt><dd>GPM IMERG Final Precipitation L3 1 day 0.1 degree x 0.1 degree (GPM_3IMERGDF)</dd><dt><span>history_L34RS :</span></dt><dd>Created by L34RS v1.4.3 @ NASA GES DISC on January 17 2023 20:05:40. Spatial: -180.0 180.0 -50.0 50.0. Regrid: remapbil cfsr1.0. Variables: precipitationCal</dd><dt><span>missing_values :</span></dt><dd>Missing values linearly interpolated one dimension at a time</dd></dl></div><div class='xr-var-data'><pre>[199163520 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d3601c84-e2b2-464e-bb91-328cbab06345' class='xr-section-summary-in' type='checkbox'  ><label for='section-d3601c84-e2b2-464e-bb91-328cbab06345' class='xr-section-summary' >Indexes: <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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b901fe00-668e-4b2c-af7d-d7240d83671c' class='xr-index-data-in' type='checkbox'/><label for='index-b901fe00-668e-4b2c-af7d-d7240d83671c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2000-06-01&#x27;, &#x27;2000-06-02&#x27;, &#x27;2000-06-03&#x27;, &#x27;2000-06-04&#x27;,\n",
       "               &#x27;2000-06-05&#x27;, &#x27;2000-06-06&#x27;, &#x27;2000-06-07&#x27;, &#x27;2000-06-08&#x27;,\n",
       "               &#x27;2000-06-09&#x27;, &#x27;2000-06-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2021-09-21&#x27;, &#x27;2021-09-22&#x27;, &#x27;2021-09-23&#x27;, &#x27;2021-09-24&#x27;,\n",
       "               &#x27;2021-09-25&#x27;, &#x27;2021-09-26&#x27;, &#x27;2021-09-27&#x27;, &#x27;2021-09-28&#x27;,\n",
       "               &#x27;2021-09-29&#x27;, &#x27;2021-09-30&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=7792, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-424f52cd-7ff4-46be-a1f7-ec2e7bb0f1b7' class='xr-index-data-in' type='checkbox'/><label for='index-424f52cd-7ff4-46be-a1f7-ec2e7bb0f1b7' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-35.0, -34.0, -33.0, -32.0, -31.0, -30.0, -29.0, -28.0, -27.0,\n",
       "              -26.0, -25.0, -24.0, -23.0, -22.0, -21.0, -20.0, -19.0, -18.0,\n",
       "              -17.0, -16.0, -15.0, -14.0, -13.0, -12.0, -11.0, -10.0,  -9.0,\n",
       "               -8.0,  -7.0,  -6.0,  -5.0,  -4.0,  -3.0,  -2.0,  -1.0,   0.0,\n",
       "                1.0,   2.0,   3.0,   4.0,   5.0,   6.0,   7.0,   8.0,   9.0,\n",
       "               10.0,  11.0,  12.0,  13.0,  14.0,  15.0,  16.0,  17.0,  18.0,\n",
       "               19.0,  20.0,  21.0,  22.0,  23.0,  24.0,  25.0,  26.0,  27.0,\n",
       "               28.0,  29.0,  30.0,  31.0,  32.0,  33.0,  34.0,  35.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8e395dc6-2ae7-4cc2-bbe5-f03b66cbb90c' class='xr-index-data-in' type='checkbox'/><label for='index-8e395dc6-2ae7-4cc2-bbe5-f03b66cbb90c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([  0.0,   1.0,   2.0,   3.0,   4.0,   5.0,   6.0,   7.0,   8.0,\n",
       "                9.0,\n",
       "              ...\n",
       "              350.0, 351.0, 352.0, 353.0, 354.0, 355.0, 356.0, 357.0, 358.0,\n",
       "              359.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=360))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b07270fc-5b06-4901-94dc-cf54bc4816b3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b07270fc-5b06-4901-94dc-cf54bc4816b3' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>creation_date :</span></dt><dd>Mon Nov 13 03:33:26 PM CST 2023</dd><dt><span>years :</span></dt><dd>2000-2021</dd><dt><span>symmetry :</span></dt><dd>none</dd><dt><span>wave_type :</span></dt><dd>Kelvin wave</dd><dt><span>title :</span></dt><dd>IMERG_20000601-20210930_anom_final filtered anomalies</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:           (time: 7792, lat: 71, lon: 360)\n",
       "Coordinates:\n",
       "  * time              (time) datetime64[ns] 2000-06-01 2000-06-02 ... 2021-09-30\n",
       "  * lat               (lat) float64 -35.0 -34.0 -33.0 -32.0 ... 33.0 34.0 35.0\n",
       "  * lon               (lon) float64 0.0 1.0 2.0 3.0 ... 356.0 357.0 358.0 359.0\n",
       "Data variables:\n",
       "    precipitationCal  (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    creation_date:  Mon Nov 13 03:33:26 PM CST 2023\n",
       "    years:          2000-2021\n",
       "    symmetry:       none\n",
       "    wave_type:      Kelvin wave\n",
       "    title:          IMERG_20000601-20210930_anom_final filtered anomalies"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "figfolder = './figures/'\n",
    "dataset = 'IMERG'\n",
    "dri = '/lss/research/agon-lab/IMERG-daily/NASA_interpolated/equ_waves/'\n",
    "fn = '1deg_IMERG_2000-2021_'+wave+'.nc'\n",
    "\n",
    "data_kw = xr.open_dataset(dri+fn)\n",
    "data_kw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "51401508-2c2a-4dcc-bc39-bf4a4388b748",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#chosen base latitude\n",
    "\n",
    "lats = -5.\n",
    "latn = -5.\n",
    "\n",
    "#chosen base longitude \n",
    "\n",
    "lonw = 255.\n",
    "lone = 255.\n",
    "\n",
    "#time \n",
    "\n",
    "mn0 = 2\n",
    "mnf = 4\n",
    "yr0 = 2001\n",
    "yrf = 2021\n",
    "time0 = str(yr0)+'-01-01T00:00:00.000000000'\n",
    "timef = str(yrf)+'-12-31T00:00:00.000000000'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "87330654-af57-495a-aaf6-369857b9ee35",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "time_all1 = data_kw['time']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "299ce2d4-6356-40a6-a1f8-2823f9737007",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# set up conditional statements \n",
    "cond1_fma = (time_all1['time.month'] >= mn0) & (time_all1['time.month'] <= mnf) # season of interest\n",
    "cond2_fma = (time_all1['time.year'] <= yrf) & (time_all1['time.year'] >= yr0) # season of interest\n",
    "\n",
    "# now find only the times when MJO amplitude is in season of interest AND exceeds some threshold\n",
    "time_fma = time_all1.where((cond1_fma)& (cond2_fma), drop=True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9006d441-833a-4332-82b4-1222a931c42c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 Base Point\n"
     ]
    },
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;precipitationCal&#x27; (time: 1874)&gt;\n",
       "array([-0.737789,  0.195228,  0.4688  , ..., -1.190183, -0.295238,  0.697945],\n",
       "      dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2001-02-01 2001-02-02 ... 2021-04-30\n",
       "    lat      float64 -5.0\n",
       "    lon      float64 255.0\n",
       "Attributes:\n",
       "    waveName:        Kelvin\n",
       "    depth:           [ 8 90]\n",
       "    period:          [ 2.5 14. ]\n",
       "    wavenumber:      [ 1 14]\n",
       "    lat:             35.0\n",
       "    long_name:       Daily accumulated precipitation (combined microwave-IR) ...\n",
       "    units:           mm\n",
       "    cell_methods:    time: mean\n",
       "    title:           GPM IMERG Final Precipitation L3 1 day 0.1 degree x 0.1 ...\n",
       "    history_L34RS:   Created by L34RS v1.4.3 @ NASA GES DISC on January 17 20...\n",
       "    missing_values:  Missing values linearly interpolated one dimension at a ...</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'>'precipitationCal'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1874</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-64eb0883-5be7-4646-8651-7b595f74d33c' class='xr-array-in' type='checkbox' checked><label for='section-64eb0883-5be7-4646-8651-7b595f74d33c' 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>-0.7378 0.1952 0.4688 -0.8297 ... -0.04624 -1.19 -0.2952 0.6979</span></div><div class='xr-array-data'><pre>array([-0.737789,  0.195228,  0.4688  , ..., -1.190183, -0.295238,  0.697945],\n",
       "      dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-b20e4944-d99b-4303-9c10-9eab13ae4689' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b20e4944-d99b-4303-9c10-9eab13ae4689' 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'>2001-02-01 ... 2021-04-30</div><input id='attrs-86c95453-4d00-4e7d-81c6-fdd690af42d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-86c95453-4d00-4e7d-81c6-fdd690af42d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75737a36-2c7b-4782-9681-d96aaf808656' class='xr-var-data-in' type='checkbox'><label for='data-75737a36-2c7b-4782-9681-d96aaf808656' 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>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2001-02-01T00:00:00.000000000&#x27;, &#x27;2001-02-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-02-03T00:00:00.000000000&#x27;, ..., &#x27;2021-04-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-04-29T00:00:00.000000000&#x27;, &#x27;2021-04-30T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.0</div><input id='attrs-ab6daeb0-6fac-49d4-bbae-84f987cac63c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ab6daeb0-6fac-49d4-bbae-84f987cac63c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0737c8c5-76bb-4b40-ab36-f8d54bada589' class='xr-var-data-in' type='checkbox'><label for='data-0737c8c5-76bb-4b40-ab36-f8d54bada589' 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>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>degrees_north</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(-5.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>255.0</div><input id='attrs-b6a35a02-ba60-4dea-ad00-456555900369' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b6a35a02-ba60-4dea-ad00-456555900369' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-743dd653-06d5-4417-9e86-d517f3f6fe76' class='xr-var-data-in' type='checkbox'><label for='data-743dd653-06d5-4417-9e86-d517f3f6fe76' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array(255.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bf7a5b43-cb71-420b-b70f-49cdefa137d5' class='xr-section-summary-in' type='checkbox'  ><label for='section-bf7a5b43-cb71-420b-b70f-49cdefa137d5' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-55f5ecf6-6350-4920-a3d5-30be4938b558' class='xr-index-data-in' type='checkbox'/><label for='index-55f5ecf6-6350-4920-a3d5-30be4938b558' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2001-02-01&#x27;, &#x27;2001-02-02&#x27;, &#x27;2001-02-03&#x27;, &#x27;2001-02-04&#x27;,\n",
       "               &#x27;2001-02-05&#x27;, &#x27;2001-02-06&#x27;, &#x27;2001-02-07&#x27;, &#x27;2001-02-08&#x27;,\n",
       "               &#x27;2001-02-09&#x27;, &#x27;2001-02-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2021-04-21&#x27;, &#x27;2021-04-22&#x27;, &#x27;2021-04-23&#x27;, &#x27;2021-04-24&#x27;,\n",
       "               &#x27;2021-04-25&#x27;, &#x27;2021-04-26&#x27;, &#x27;2021-04-27&#x27;, &#x27;2021-04-28&#x27;,\n",
       "               &#x27;2021-04-29&#x27;, &#x27;2021-04-30&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1874, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dd4bd682-75af-4e5c-8b63-312d30f652fc' class='xr-section-summary-in' type='checkbox'  ><label for='section-dd4bd682-75af-4e5c-8b63-312d30f652fc' class='xr-section-summary' >Attributes: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>waveName :</span></dt><dd>Kelvin</dd><dt><span>depth :</span></dt><dd>[ 8 90]</dd><dt><span>period :</span></dt><dd>[ 2.5 14. ]</dd><dt><span>wavenumber :</span></dt><dd>[ 1 14]</dd><dt><span>lat :</span></dt><dd>35.0</dd><dt><span>long_name :</span></dt><dd>Daily accumulated precipitation (combined microwave-IR) estimate</dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>title :</span></dt><dd>GPM IMERG Final Precipitation L3 1 day 0.1 degree x 0.1 degree (GPM_3IMERGDF)</dd><dt><span>history_L34RS :</span></dt><dd>Created by L34RS v1.4.3 @ NASA GES DISC on January 17 2023 20:05:40. Spatial: -180.0 180.0 -50.0 50.0. Regrid: remapbil cfsr1.0. Variables: precipitationCal</dd><dt><span>missing_values :</span></dt><dd>Missing values linearly interpolated one dimension at a time</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'precipitationCal' (time: 1874)>\n",
       "array([-0.737789,  0.195228,  0.4688  , ..., -1.190183, -0.295238,  0.697945],\n",
       "      dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2001-02-01 2001-02-02 ... 2021-04-30\n",
       "    lat      float64 -5.0\n",
       "    lon      float64 255.0\n",
       "Attributes:\n",
       "    waveName:        Kelvin\n",
       "    depth:           [ 8 90]\n",
       "    period:          [ 2.5 14. ]\n",
       "    wavenumber:      [ 1 14]\n",
       "    lat:             35.0\n",
       "    long_name:       Daily accumulated precipitation (combined microwave-IR) ...\n",
       "    units:           mm\n",
       "    cell_methods:    time: mean\n",
       "    title:           GPM IMERG Final Precipitation L3 1 day 0.1 degree x 0.1 ...\n",
       "    history_L34RS:   Created by L34RS v1.4.3 @ NASA GES DISC on January 17 20...\n",
       "    missing_values:  Missing values linearly interpolated one dimension at a ..."
      ]
     },
     "execution_count": 12,
     "metadata": {},
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    }
   ],
   "source": [
    "if (lats == latn) | (lonw == lone):\n",
    "    pr1 = data_kw['precipitationCal'].sel(lat=latn,lon=lonw, time = time_fma)\n",
    "    pr_FMA_std_lon = data_kw['precipitationCal'].sel(lat=latn,lon=slice(225,285),time = time_fma).mean('lon').std(dim='time')\n",
    "    print('1 Base Point')\n",
    "else:\n",
    "    pr1 = data_kw['precipitationCal'].sel(lat=slice(lats,latn),lon=slice(lonw,lone), time = time_fma).mean(dim=('lat','lon'))\n",
    "    pr_FMA_std_lon = data_kw['precipitationCal'].sel(lat=slice(lats,latn),lon=slice(225,285),time = time_fma).mean(dim=('lat','lon')).std(dim='time')\n",
    "    print('Base Region')\n",
    "\n",
    "std = pr1.std(dim=('time'))\n",
    "pr1"
   ]
  },
  {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;precipitationCal&#x27; (time: 1874)&gt;\n",
       "array([-0.737789,  0.195228,  0.4688  , ..., -1.190183, -0.295238,  0.697945],\n",
       "      dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2001-02-01 2001-02-02 ... 2021-04-30\n",
       "    lat      float64 -5.0\n",
       "    lon      float64 255.0\n",
       "Attributes:\n",
       "    waveName:        Kelvin\n",
       "    depth:           [ 8 90]\n",
       "    period:          [ 2.5 14. ]\n",
       "    wavenumber:      [ 1 14]\n",
       "    lat:             35.0\n",
       "    long_name:       Daily accumulated precipitation (combined microwave-IR) ...\n",
       "    units:           mm\n",
       "    cell_methods:    time: mean\n",
       "    title:           GPM IMERG Final Precipitation L3 1 day 0.1 degree x 0.1 ...\n",
       "    history_L34RS:   Created by L34RS v1.4.3 @ NASA GES DISC on January 17 20...\n",
       "    missing_values:  Missing values linearly interpolated one dimension at a ...</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'>'precipitationCal'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1874</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-599166e3-27d2-4a74-847c-ffc1a40ccaa2' class='xr-array-in' type='checkbox' checked><label for='section-599166e3-27d2-4a74-847c-ffc1a40ccaa2' 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>-0.7378 0.1952 0.4688 -0.8297 ... -0.04624 -1.19 -0.2952 0.6979</span></div><div class='xr-array-data'><pre>array([-0.737789,  0.195228,  0.4688  , ..., -1.190183, -0.295238,  0.697945],\n",
       "      dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-08ae8428-4d00-40e0-a7f1-f58bed0544a4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-08ae8428-4d00-40e0-a7f1-f58bed0544a4' 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'>2001-02-01 ... 2021-04-30</div><input id='attrs-a580b204-f77c-40dd-b8d5-aa02c1a19f0e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a580b204-f77c-40dd-b8d5-aa02c1a19f0e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6fc82038-6336-45c1-85f8-42c6a41c120a' class='xr-var-data-in' type='checkbox'><label for='data-6fc82038-6336-45c1-85f8-42c6a41c120a' 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>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2001-02-01T00:00:00.000000000&#x27;, &#x27;2001-02-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-02-03T00:00:00.000000000&#x27;, ..., &#x27;2021-04-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-04-29T00:00:00.000000000&#x27;, &#x27;2021-04-30T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.0</div><input id='attrs-660fe60c-2881-48c5-adf9-363f5628523a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-660fe60c-2881-48c5-adf9-363f5628523a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-87323f5c-54bf-4050-b93b-201a49fd3b28' class='xr-var-data-in' type='checkbox'><label for='data-87323f5c-54bf-4050-b93b-201a49fd3b28' 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>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>degrees_north</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(-5.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>255.0</div><input id='attrs-505835c3-0b45-4878-8d7e-c7bb13ca6756' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-505835c3-0b45-4878-8d7e-c7bb13ca6756' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d3af6d5-c33d-4973-8c59-f8ba5fe6f184' class='xr-var-data-in' type='checkbox'><label for='data-9d3af6d5-c33d-4973-8c59-f8ba5fe6f184' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array(255.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-76024521-a50f-4196-87d2-389918f5ad23' class='xr-section-summary-in' type='checkbox'  ><label for='section-76024521-a50f-4196-87d2-389918f5ad23' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-63caa9f4-669c-4f8f-81ab-638f33b9a512' class='xr-index-data-in' type='checkbox'/><label for='index-63caa9f4-669c-4f8f-81ab-638f33b9a512' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2001-02-01&#x27;, &#x27;2001-02-02&#x27;, &#x27;2001-02-03&#x27;, &#x27;2001-02-04&#x27;,\n",
       "               &#x27;2001-02-05&#x27;, &#x27;2001-02-06&#x27;, &#x27;2001-02-07&#x27;, &#x27;2001-02-08&#x27;,\n",
       "               &#x27;2001-02-09&#x27;, &#x27;2001-02-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2021-04-21&#x27;, &#x27;2021-04-22&#x27;, &#x27;2021-04-23&#x27;, &#x27;2021-04-24&#x27;,\n",
       "               &#x27;2021-04-25&#x27;, &#x27;2021-04-26&#x27;, &#x27;2021-04-27&#x27;, &#x27;2021-04-28&#x27;,\n",
       "               &#x27;2021-04-29&#x27;, &#x27;2021-04-30&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1874, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6f742721-76b1-454f-bd28-a3646585416d' class='xr-section-summary-in' type='checkbox'  ><label for='section-6f742721-76b1-454f-bd28-a3646585416d' class='xr-section-summary' >Attributes: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>waveName :</span></dt><dd>Kelvin</dd><dt><span>depth :</span></dt><dd>[ 8 90]</dd><dt><span>period :</span></dt><dd>[ 2.5 14. ]</dd><dt><span>wavenumber :</span></dt><dd>[ 1 14]</dd><dt><span>lat :</span></dt><dd>35.0</dd><dt><span>long_name :</span></dt><dd>Daily accumulated precipitation (combined microwave-IR) estimate</dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>title :</span></dt><dd>GPM IMERG Final Precipitation L3 1 day 0.1 degree x 0.1 degree (GPM_3IMERGDF)</dd><dt><span>history_L34RS :</span></dt><dd>Created by L34RS v1.4.3 @ NASA GES DISC on January 17 2023 20:05:40. Spatial: -180.0 180.0 -50.0 50.0. Regrid: remapbil cfsr1.0. Variables: precipitationCal</dd><dt><span>missing_values :</span></dt><dd>Missing values linearly interpolated one dimension at a time</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'precipitationCal' (time: 1874)>\n",
       "array([-0.737789,  0.195228,  0.4688  , ..., -1.190183, -0.295238,  0.697945],\n",
       "      dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2001-02-01 2001-02-02 ... 2021-04-30\n",
       "    lat      float64 -5.0\n",
       "    lon      float64 255.0\n",
       "Attributes:\n",
       "    waveName:        Kelvin\n",
       "    depth:           [ 8 90]\n",
       "    period:          [ 2.5 14. ]\n",
       "    wavenumber:      [ 1 14]\n",
       "    lat:             35.0\n",
       "    long_name:       Daily accumulated precipitation (combined microwave-IR) ...\n",
       "    units:           mm\n",
       "    cell_methods:    time: mean\n",
       "    title:           GPM IMERG Final Precipitation L3 1 day 0.1 degree x 0.1 ...\n",
       "    history_L34RS:   Created by L34RS v1.4.3 @ NASA GES DISC on January 17 20...\n",
       "    missing_values:  Missing values linearly interpolated one dimension at a ..."
      ]
     },
     "execution_count": 13,
     "metadata": {},
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   "source": [
    "pr = pr1\n",
    "pr"
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  },
  {
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   "id": "ff54479a-6483-4dcd-9ea6-36a86fd365ac",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;precipitationCal&#x27; (time: 1874)&gt;\n",
       "array([False, False, False, ..., False, False, False])\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2001-02-01 2001-02-02 ... 2021-04-30\n",
       "    lat      float64 -5.0\n",
       "    lon      float64 255.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'precipitationCal'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1874</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-dbc1e3d7-4391-43f2-b46a-023c8c11ec0e' class='xr-array-in' type='checkbox' checked><label for='section-dbc1e3d7-4391-43f2-b46a-023c8c11ec0e' 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>False False False False False False ... False False False False False</span></div><div class='xr-array-data'><pre>array([False, False, False, ..., False, False, False])</pre></div></div></li><li class='xr-section-item'><input id='section-5462e6f6-1874-4288-83bf-bedc296feef9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5462e6f6-1874-4288-83bf-bedc296feef9' 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'>2001-02-01 ... 2021-04-30</div><input id='attrs-240ee20a-bc47-473c-b1bd-d0eb52661e12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-240ee20a-bc47-473c-b1bd-d0eb52661e12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-107347ae-39b8-418a-a520-e0df037df008' class='xr-var-data-in' type='checkbox'><label for='data-107347ae-39b8-418a-a520-e0df037df008' 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>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2001-02-01T00:00:00.000000000&#x27;, &#x27;2001-02-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-02-03T00:00:00.000000000&#x27;, ..., &#x27;2021-04-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-04-29T00:00:00.000000000&#x27;, &#x27;2021-04-30T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.0</div><input id='attrs-cd2c663f-6bcb-4d4c-a176-4217dd4b0717' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd2c663f-6bcb-4d4c-a176-4217dd4b0717' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb8fd026-39b3-4df4-8b4f-0aee17c4d52c' class='xr-var-data-in' type='checkbox'><label for='data-fb8fd026-39b3-4df4-8b4f-0aee17c4d52c' 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>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>degrees_north</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(-5.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>255.0</div><input id='attrs-a6e5e783-af0e-4504-818e-4f742ad1d086' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a6e5e783-af0e-4504-818e-4f742ad1d086' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-552862ec-0f40-463f-9292-eb7f3b0a324d' class='xr-var-data-in' type='checkbox'><label for='data-552862ec-0f40-463f-9292-eb7f3b0a324d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array(255.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9fb2eb0c-b46e-41ff-a598-d781de4c23fc' class='xr-section-summary-in' type='checkbox'  ><label for='section-9fb2eb0c-b46e-41ff-a598-d781de4c23fc' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-01044a83-b8c3-46aa-81ab-70f8341d3b3d' class='xr-index-data-in' type='checkbox'/><label for='index-01044a83-b8c3-46aa-81ab-70f8341d3b3d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2001-02-01&#x27;, &#x27;2001-02-02&#x27;, &#x27;2001-02-03&#x27;, &#x27;2001-02-04&#x27;,\n",
       "               &#x27;2001-02-05&#x27;, &#x27;2001-02-06&#x27;, &#x27;2001-02-07&#x27;, &#x27;2001-02-08&#x27;,\n",
       "               &#x27;2001-02-09&#x27;, &#x27;2001-02-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2021-04-21&#x27;, &#x27;2021-04-22&#x27;, &#x27;2021-04-23&#x27;, &#x27;2021-04-24&#x27;,\n",
       "               &#x27;2021-04-25&#x27;, &#x27;2021-04-26&#x27;, &#x27;2021-04-27&#x27;, &#x27;2021-04-28&#x27;,\n",
       "               &#x27;2021-04-29&#x27;, &#x27;2021-04-30&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1874, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a8f6bc14-ebce-48a2-8ad7-c1fc0a50ff80' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a8f6bc14-ebce-48a2-8ad7-c1fc0a50ff80' 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 'precipitationCal' (time: 1874)>\n",
       "array([False, False, False, ..., False, False, False])\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2001-02-01 2001-02-02 ... 2021-04-30\n",
       "    lat      float64 -5.0\n",
       "    lon      float64 255.0"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cond = (pr >= std)\n",
    "cond"
   ]
  },
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;precipitationCal&#x27; (time: 184)&gt;\n",
       "array([ 3.5462508,  3.6259716,  4.7681584,  6.455778 ,  5.3269014,\n",
       "        9.713379 , 10.675033 , 11.228124 ,  5.3164043,  3.6199973,\n",
       "        4.399762 ,  3.5407395,  4.2440352,  5.259424 ,  4.687411 ,\n",
       "        6.9953027,  5.35451  ,  4.4805403,  5.066396 , 21.350473 ,\n",
       "       14.288392 ,  9.458473 ,  4.292097 ,  3.9099987,  5.13136  ,\n",
       "        4.864905 ,  4.096057 ,  6.673044 ,  3.9048216,  9.985805 ,\n",
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       "        5.8595405,  4.523765 ,  3.62591  ,  3.566575 ,  5.2470465,\n",
       "        8.587621 ,  6.217102 ,  3.8252287,  4.7451887,  4.8976026,\n",
       "        5.0293937,  5.844247 , 14.58664  , 19.404049 , 14.356658 ,\n",
       "        4.148955 ,  8.011762 ,  4.07293  ,  7.2584786,  6.379229 ,\n",
       "        3.932001 ,  4.9006953,  3.9042542,  9.8220215,  7.0553193,\n",
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       "        3.972464 , 12.912019 ,  5.207262 ,  4.2783384,  3.8171053,\n",
       "        4.8364205,  4.0547304,  5.760329 ,  4.072842 ,  4.6730385,\n",
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       "       13.383703 ,  9.065716 ,  4.607707 ,  5.800125 ,  5.0504355,\n",
       "       12.251077 ,  3.6139774,  3.9021423,  5.0339923,  3.6688004,\n",
       "        3.6768692, 10.601485 ,  8.888396 ,  5.2776   ,  4.327648 ,\n",
       "       15.297224 ,  7.079228 ,  5.5721383,  3.6762702,  4.547164 ,\n",
       "        3.6422055,  4.3702083,  3.9682996, 17.592579 ,  3.682062 ,\n",
       "        9.121534 ,  4.9280386,  5.428    ,  4.5369835,  3.6444328,\n",
       "        6.9455104,  5.363824 , 11.439827 ,  4.634728 ,  5.6461477,\n",
       "        3.8049166,  3.843246 ,  4.883838 ,  5.472546 ,  6.3252115,\n",
       "        4.2032533,  4.488427 ,  4.6680326,  3.9418476,  4.6018157,\n",
       "        4.132783 ,  5.0090723,  7.203761 , 10.904024 , 12.548245 ,\n",
       "        8.724494 , 12.0112295,  3.5949357,  3.624488 ,  5.224812 ,\n",
       "        8.538293 ,  8.770833 ,  7.0349717, 10.834534 , 14.452797 ,\n",
       "        5.9591928,  5.6223807,  9.403739 ,  5.6687694,  4.9229493,\n",
       "       12.302116 ,  6.2741756, 10.807182 ,  5.615202 ,  9.457176 ,\n",
       "        6.050267 ,  8.4565115,  7.3267875, 15.229051 , 12.261323 ,\n",
       "        3.8309646,  5.0908484,  5.4197145,  3.7519033,  5.457084 ,\n",
       "        5.2979546,  5.6802278,  5.237099 ,  3.6558645,  6.921174 ,\n",
       "        6.9580507,  3.9042723,  4.0810575,  3.7109916,  4.1984296,\n",
       "        6.4251795,  9.590438 ,  3.8518898,  3.5596187,  5.4065385,\n",
       "       11.233922 ,  4.147709 ,  4.5141993,  4.59452  ], dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2001-02-26 2001-03-07 ... 2021-03-25\n",
       "    lat      float64 -5.0\n",
       "    lon      float64 255.0\n",
       "Attributes:\n",
       "    waveName:        Kelvin\n",
       "    depth:           [ 8 90]\n",
       "    period:          [ 2.5 14. ]\n",
       "    wavenumber:      [ 1 14]\n",
       "    lat:             35.0\n",
       "    long_name:       Daily accumulated precipitation (combined microwave-IR) ...\n",
       "    units:           mm\n",
       "    cell_methods:    time: mean\n",
       "    title:           GPM IMERG Final Precipitation L3 1 day 0.1 degree x 0.1 ...\n",
       "    history_L34RS:   Created by L34RS v1.4.3 @ NASA GES DISC on January 17 20...\n",
       "    missing_values:  Missing values linearly interpolated one dimension at a ...</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'>'precipitationCal'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 184</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-1b753746-6ec6-44f4-9f02-ebdbbf624151' class='xr-array-in' type='checkbox' checked><label for='section-1b753746-6ec6-44f4-9f02-ebdbbf624151' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>3.546 3.626 4.768 6.456 5.327 9.713 ... 5.407 11.23 4.148 4.514 4.595</span></div><div class='xr-array-data'><pre>array([ 3.5462508,  3.6259716,  4.7681584,  6.455778 ,  5.3269014,\n",
       "        9.713379 , 10.675033 , 11.228124 ,  5.3164043,  3.6199973,\n",
       "        4.399762 ,  3.5407395,  4.2440352,  5.259424 ,  4.687411 ,\n",
       "        6.9953027,  5.35451  ,  4.4805403,  5.066396 , 21.350473 ,\n",
       "       14.288392 ,  9.458473 ,  4.292097 ,  3.9099987,  5.13136  ,\n",
       "        4.864905 ,  4.096057 ,  6.673044 ,  3.9048216,  9.985805 ,\n",
       "        4.2034225,  3.7441134,  5.2733107,  4.22852  ,  8.313119 ,\n",
       "        5.8595405,  4.523765 ,  3.62591  ,  3.566575 ,  5.2470465,\n",
       "        8.587621 ,  6.217102 ,  3.8252287,  4.7451887,  4.8976026,\n",
       "        5.0293937,  5.844247 , 14.58664  , 19.404049 , 14.356658 ,\n",
       "        4.148955 ,  8.011762 ,  4.07293  ,  7.2584786,  6.379229 ,\n",
       "        3.932001 ,  4.9006953,  3.9042542,  9.8220215,  7.0553193,\n",
       "        8.297647 ,  8.169968 ,  4.944167 ,  7.100869 ,  3.6278553,\n",
       "        4.053997 ,  4.651705 ,  7.7140675,  8.892337 ,  5.0741076,\n",
       "        3.972464 , 12.912019 ,  5.207262 ,  4.2783384,  3.8171053,\n",
       "        4.8364205,  4.0547304,  5.760329 ,  4.072842 ,  4.6730385,\n",
       "        7.103846 , 35.204773 , 21.501312 ,  3.6107523, 10.839357 ,\n",
       "       13.383703 ,  9.065716 ,  4.607707 ,  5.800125 ,  5.0504355,\n",
       "       12.251077 ,  3.6139774,  3.9021423,  5.0339923,  3.6688004,\n",
       "        3.6768692, 10.601485 ,  8.888396 ,  5.2776   ,  4.327648 ,\n",
       "       15.297224 ,  7.079228 ,  5.5721383,  3.6762702,  4.547164 ,\n",
       "        3.6422055,  4.3702083,  3.9682996, 17.592579 ,  3.682062 ,\n",
       "        9.121534 ,  4.9280386,  5.428    ,  4.5369835,  3.6444328,\n",
       "        6.9455104,  5.363824 , 11.439827 ,  4.634728 ,  5.6461477,\n",
       "        3.8049166,  3.843246 ,  4.883838 ,  5.472546 ,  6.3252115,\n",
       "        4.2032533,  4.488427 ,  4.6680326,  3.9418476,  4.6018157,\n",
       "        4.132783 ,  5.0090723,  7.203761 , 10.904024 , 12.548245 ,\n",
       "        8.724494 , 12.0112295,  3.5949357,  3.624488 ,  5.224812 ,\n",
       "        8.538293 ,  8.770833 ,  7.0349717, 10.834534 , 14.452797 ,\n",
       "        5.9591928,  5.6223807,  9.403739 ,  5.6687694,  4.9229493,\n",
       "       12.302116 ,  6.2741756, 10.807182 ,  5.615202 ,  9.457176 ,\n",
       "        6.050267 ,  8.4565115,  7.3267875, 15.229051 , 12.261323 ,\n",
       "        3.8309646,  5.0908484,  5.4197145,  3.7519033,  5.457084 ,\n",
       "        5.2979546,  5.6802278,  5.237099 ,  3.6558645,  6.921174 ,\n",
       "        6.9580507,  3.9042723,  4.0810575,  3.7109916,  4.1984296,\n",
       "        6.4251795,  9.590438 ,  3.8518898,  3.5596187,  5.4065385,\n",
       "       11.233922 ,  4.147709 ,  4.5141993,  4.59452  ], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-c97309db-77d7-4788-90a6-339d18bf02f2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c97309db-77d7-4788-90a6-339d18bf02f2' 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'>2001-02-26 ... 2021-03-25</div><input id='attrs-c85910f7-2fb2-4c3b-8b0c-e4318d0aae07' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c85910f7-2fb2-4c3b-8b0c-e4318d0aae07' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df3b9cbf-0c77-4748-8d89-9794ee6a4ac2' class='xr-var-data-in' type='checkbox'><label for='data-df3b9cbf-0c77-4748-8d89-9794ee6a4ac2' 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>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2001-02-26T00:00:00.000000000&#x27;, &#x27;2001-03-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-03-16T00:00:00.000000000&#x27;, &#x27;2001-03-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-03-23T00:00:00.000000000&#x27;, &#x27;2001-03-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-04-05T00:00:00.000000000&#x27;, &#x27;2001-04-06T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-04-12T00:00:00.000000000&#x27;, &#x27;2001-04-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-04-20T00:00:00.000000000&#x27;, &#x27;2002-02-09T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-02-12T00:00:00.000000000&#x27;, &#x27;2002-02-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-02-25T00:00:00.000000000&#x27;, &#x27;2002-03-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-03-10T00:00:00.000000000&#x27;, &#x27;2002-03-19T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-03-26T00:00:00.000000000&#x27;, &#x27;2002-04-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-04-06T00:00:00.000000000&#x27;, &#x27;2002-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-04-19T00:00:00.000000000&#x27;, &#x27;2003-02-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-03-09T00:00:00.000000000&#x27;, &#x27;2003-03-12T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-04-29T00:00:00.000000000&#x27;, &#x27;2003-04-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-03-13T00:00:00.000000000&#x27;, &#x27;2004-03-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-03-27T00:00:00.000000000&#x27;, &#x27;2004-03-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-04-01T00:00:00.000000000&#x27;, &#x27;2004-04-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-04-12T00:00:00.000000000&#x27;, &#x27;2004-04-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-04-20T00:00:00.000000000&#x27;, &#x27;2004-04-23T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-02-17T00:00:00.000000000&#x27;, &#x27;2005-03-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-03-18T00:00:00.000000000&#x27;, &#x27;2005-04-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-04-13T00:00:00.000000000&#x27;, &#x27;2006-02-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2006-03-06T00:00:00.000000000&#x27;, &#x27;2006-03-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2006-03-10T00:00:00.000000000&#x27;, &#x27;2006-03-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2006-03-16T00:00:00.000000000&#x27;, &#x27;2006-03-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2006-03-24T00:00:00.000000000&#x27;, &#x27;2006-03-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2006-04-04T00:00:00.000000000&#x27;, &#x27;2006-04-12T00:00:00.000000000&#x27;,\n",
       "       &#x27;2006-04-15T00:00:00.000000000&#x27;, &#x27;2006-04-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2006-04-23T00:00:00.000000000&#x27;, &#x27;2006-04-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2007-03-10T00:00:00.000000000&#x27;, &#x27;2007-03-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2007-03-21T00:00:00.000000000&#x27;, &#x27;2007-03-22T00:00:00.000000000&#x27;,\n",
       "       &#x27;2007-03-28T00:00:00.000000000&#x27;, &#x27;2007-04-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2007-04-17T00:00:00.000000000&#x27;, &#x27;2007-04-19T00:00:00.000000000&#x27;,\n",
       "       &#x27;2007-04-27T00:00:00.000000000&#x27;, &#x27;2008-02-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2008-03-02T00:00:00.000000000&#x27;, &#x27;2008-03-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2008-03-25T00:00:00.000000000&#x27;, &#x27;2008-03-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2008-04-01T00:00:00.000000000&#x27;, &#x27;2008-04-18T00:00:00.000000000&#x27;,\n",
       "       &#x27;2008-04-28T00:00:00.000000000&#x27;, &#x27;2008-04-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2009-02-15T00:00:00.000000000&#x27;, &#x27;2009-02-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2009-02-27T00:00:00.000000000&#x27;, &#x27;2009-03-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2009-03-07T00:00:00.000000000&#x27;, &#x27;2009-03-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2009-03-11T00:00:00.000000000&#x27;, &#x27;2009-03-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2009-03-26T00:00:00.000000000&#x27;, &#x27;2009-03-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2009-04-11T00:00:00.000000000&#x27;, &#x27;2009-04-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2009-04-21T00:00:00.000000000&#x27;, &#x27;2009-04-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2009-04-28T00:00:00.000000000&#x27;, &#x27;2010-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2010-02-08T00:00:00.000000000&#x27;, &#x27;2010-02-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2010-03-28T00:00:00.000000000&#x27;, &#x27;2011-03-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-03-27T00:00:00.000000000&#x27;, &#x27;2011-03-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-04-02T00:00:00.000000000&#x27;, &#x27;2011-04-03T00:00:00.000000000&#x27;,\n",
       "       &#x27;2011-04-21T00:00:00.000000000&#x27;, &#x27;2012-02-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-02-08T00:00:00.000000000&#x27;, &#x27;2012-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-03-04T00:00:00.000000000&#x27;, &#x27;2012-03-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-03-14T00:00:00.000000000&#x27;, &#x27;2012-04-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-04-02T00:00:00.000000000&#x27;, &#x27;2012-04-09T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-04-10T00:00:00.000000000&#x27;, &#x27;2012-04-26T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-03-01T00:00:00.000000000&#x27;, &#x27;2013-03-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-03-19T00:00:00.000000000&#x27;, &#x27;2013-03-26T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-03-31T00:00:00.000000000&#x27;, &#x27;2013-04-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-04-04T00:00:00.000000000&#x27;, &#x27;2013-04-05T00:00:00.000000000&#x27;,\n",
       "       &#x27;2014-03-15T00:00:00.000000000&#x27;, &#x27;2014-03-23T00:00:00.000000000&#x27;,\n",
       "       &#x27;2014-03-29T00:00:00.000000000&#x27;, &#x27;2014-04-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2015-03-17T00:00:00.000000000&#x27;, &#x27;2015-03-18T00:00:00.000000000&#x27;,\n",
       "       &#x27;2015-04-02T00:00:00.000000000&#x27;, &#x27;2015-04-03T00:00:00.000000000&#x27;,\n",
       "       &#x27;2015-04-19T00:00:00.000000000&#x27;, &#x27;2016-02-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2016-02-25T00:00:00.000000000&#x27;, &#x27;2016-03-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2016-03-04T00:00:00.000000000&#x27;, &#x27;2016-03-21T00:00:00.000000000&#x27;,\n",
       "       &#x27;2016-03-26T00:00:00.000000000&#x27;, &#x27;2016-03-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2016-03-30T00:00:00.000000000&#x27;, &#x27;2016-04-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2016-04-03T00:00:00.000000000&#x27;, &#x27;2016-04-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2016-04-09T00:00:00.000000000&#x27;, &#x27;2016-04-10T00:00:00.000000000&#x27;,\n",
       "       &#x27;2016-04-16T00:00:00.000000000&#x27;, &#x27;2017-02-06T00:00:00.000000000&#x27;,\n",
       "       &#x27;2017-02-14T00:00:00.000000000&#x27;, &#x27;2017-02-24T00:00:00.000000000&#x27;,\n",
       "       &#x27;2017-03-05T00:00:00.000000000&#x27;, &#x27;2017-03-06T00:00:00.000000000&#x27;,\n",
       "       &#x27;2017-03-12T00:00:00.000000000&#x27;, &#x27;2017-03-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2017-03-15T00:00:00.000000000&#x27;, &#x27;2017-03-22T00:00:00.000000000&#x27;,\n",
       "       &#x27;2017-03-23T00:00:00.000000000&#x27;, &#x27;2017-03-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2017-04-06T00:00:00.000000000&#x27;, &#x27;2017-04-07T00:00:00.000000000&#x27;,\n",
       "       &#x27;2017-04-12T00:00:00.000000000&#x27;, &#x27;2017-04-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2017-04-18T00:00:00.000000000&#x27;, &#x27;2017-04-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-03-17T00:00:00.000000000&#x27;, &#x27;2018-03-30T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-03-31T00:00:00.000000000&#x27;, &#x27;2018-04-03T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-04-07T00:00:00.000000000&#x27;, &#x27;2018-04-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-04-20T00:00:00.000000000&#x27;, &#x27;2019-02-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2019-02-23T00:00:00.000000000&#x27;, &#x27;2019-02-27T00:00:00.000000000&#x27;,\n",
       "       &#x27;2019-02-28T00:00:00.000000000&#x27;, &#x27;2019-03-08T00:00:00.000000000&#x27;,\n",
       "       &#x27;2019-03-09T00:00:00.000000000&#x27;, &#x27;2019-03-12T00:00:00.000000000&#x27;,\n",
       "       &#x27;2019-03-17T00:00:00.000000000&#x27;, &#x27;2019-03-23T00:00:00.000000000&#x27;,\n",
       "       &#x27;2019-03-27T00:00:00.000000000&#x27;, &#x27;2019-04-04T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-03-10T00:00:00.000000000&#x27;, &#x27;2020-03-11T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-03-19T00:00:00.000000000&#x27;, &#x27;2020-03-20T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-03-18T00:00:00.000000000&#x27;, &#x27;2021-03-25T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.0</div><input id='attrs-e8584017-950a-4058-8103-ee73b89e08a2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e8584017-950a-4058-8103-ee73b89e08a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8710c685-1868-4801-841b-5d6a8bfd9422' class='xr-var-data-in' type='checkbox'><label for='data-8710c685-1868-4801-841b-5d6a8bfd9422' 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>axis :</span></dt><dd>Y</dd><dt><span>units :</span></dt><dd>degrees_north</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(-5.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>255.0</div><input id='attrs-21614cf6-74b4-42bd-aa17-3ed2ed692f86' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21614cf6-74b4-42bd-aa17-3ed2ed692f86' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29bf2714-f0c9-409c-b98e-bf116b57ca7a' class='xr-var-data-in' type='checkbox'><label for='data-29bf2714-f0c9-409c-b98e-bf116b57ca7a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array(255.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-aae30557-c754-406f-a7c6-1357699d1486' class='xr-section-summary-in' type='checkbox'  ><label for='section-aae30557-c754-406f-a7c6-1357699d1486' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b430f266-503c-4712-95f7-0225672fa813' class='xr-index-data-in' type='checkbox'/><label for='index-b430f266-503c-4712-95f7-0225672fa813' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2001-02-26&#x27;, &#x27;2001-03-07&#x27;, &#x27;2001-03-16&#x27;, &#x27;2001-03-17&#x27;,\n",
       "               &#x27;2001-03-23&#x27;, &#x27;2001-03-30&#x27;, &#x27;2001-04-05&#x27;, &#x27;2001-04-06&#x27;,\n",
       "               &#x27;2001-04-12&#x27;, &#x27;2001-04-15&#x27;,\n",
       "               ...\n",
       "               &#x27;2019-03-17&#x27;, &#x27;2019-03-23&#x27;, &#x27;2019-03-27&#x27;, &#x27;2019-04-04&#x27;,\n",
       "               &#x27;2020-03-10&#x27;, &#x27;2020-03-11&#x27;, &#x27;2020-03-19&#x27;, &#x27;2020-03-20&#x27;,\n",
       "               &#x27;2021-03-18&#x27;, &#x27;2021-03-25&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=184, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-155c0bb8-a469-42ea-be9e-14366301bfb9' class='xr-section-summary-in' type='checkbox'  ><label for='section-155c0bb8-a469-42ea-be9e-14366301bfb9' class='xr-section-summary' >Attributes: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>waveName :</span></dt><dd>Kelvin</dd><dt><span>depth :</span></dt><dd>[ 8 90]</dd><dt><span>period :</span></dt><dd>[ 2.5 14. ]</dd><dt><span>wavenumber :</span></dt><dd>[ 1 14]</dd><dt><span>lat :</span></dt><dd>35.0</dd><dt><span>long_name :</span></dt><dd>Daily accumulated precipitation (combined microwave-IR) estimate</dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>title :</span></dt><dd>GPM IMERG Final Precipitation L3 1 day 0.1 degree x 0.1 degree (GPM_3IMERGDF)</dd><dt><span>history_L34RS :</span></dt><dd>Created by L34RS v1.4.3 @ NASA GES DISC on January 17 2023 20:05:40. Spatial: -180.0 180.0 -50.0 50.0. Regrid: remapbil cfsr1.0. Variables: precipitationCal</dd><dt><span>missing_values :</span></dt><dd>Missing values linearly interpolated one dimension at a time</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'precipitationCal' (time: 184)>\n",
       "array([ 3.5462508,  3.6259716,  4.7681584,  6.455778 ,  5.3269014,\n",
       "        9.713379 , 10.675033 , 11.228124 ,  5.3164043,  3.6199973,\n",
       "        4.399762 ,  3.5407395,  4.2440352,  5.259424 ,  4.687411 ,\n",
       "        6.9953027,  5.35451  ,  4.4805403,  5.066396 , 21.350473 ,\n",
       "       14.288392 ,  9.458473 ,  4.292097 ,  3.9099987,  5.13136  ,\n",
       "        4.864905 ,  4.096057 ,  6.673044 ,  3.9048216,  9.985805 ,\n",
       "        4.2034225,  3.7441134,  5.2733107,  4.22852  ,  8.313119 ,\n",
       "        5.8595405,  4.523765 ,  3.62591  ,  3.566575 ,  5.2470465,\n",
       "        8.587621 ,  6.217102 ,  3.8252287,  4.7451887,  4.8976026,\n",
       "        5.0293937,  5.844247 , 14.58664  , 19.404049 , 14.356658 ,\n",
       "        4.148955 ,  8.011762 ,  4.07293  ,  7.2584786,  6.379229 ,\n",
       "        3.932001 ,  4.9006953,  3.9042542,  9.8220215,  7.0553193,\n",
       "        8.297647 ,  8.169968 ,  4.944167 ,  7.100869 ,  3.6278553,\n",
       "        4.053997 ,  4.651705 ,  7.7140675,  8.892337 ,  5.0741076,\n",
       "        3.972464 , 12.912019 ,  5.207262 ,  4.2783384,  3.8171053,\n",
       "        4.8364205,  4.0547304,  5.760329 ,  4.072842 ,  4.6730385,\n",
       "        7.103846 , 35.204773 , 21.501312 ,  3.6107523, 10.839357 ,\n",
       "       13.383703 ,  9.065716 ,  4.607707 ,  5.800125 ,  5.0504355,\n",
       "       12.251077 ,  3.6139774,  3.9021423,  5.0339923,  3.6688004,\n",
       "        3.6768692, 10.601485 ,  8.888396 ,  5.2776   ,  4.327648 ,\n",
       "       15.297224 ,  7.079228 ,  5.5721383,  3.6762702,  4.547164 ,\n",
       "        3.6422055,  4.3702083,  3.9682996, 17.592579 ,  3.682062 ,\n",
       "        9.121534 ,  4.9280386,  5.428    ,  4.5369835,  3.6444328,\n",
       "        6.9455104,  5.363824 , 11.439827 ,  4.634728 ,  5.6461477,\n",
       "        3.8049166,  3.843246 ,  4.883838 ,  5.472546 ,  6.3252115,\n",
       "        4.2032533,  4.488427 ,  4.6680326,  3.9418476,  4.6018157,\n",
       "        4.132783 ,  5.0090723,  7.203761 , 10.904024 , 12.548245 ,\n",
       "        8.724494 , 12.0112295,  3.5949357,  3.624488 ,  5.224812 ,\n",
       "        8.538293 ,  8.770833 ,  7.0349717, 10.834534 , 14.452797 ,\n",
       "        5.9591928,  5.6223807,  9.403739 ,  5.6687694,  4.9229493,\n",
       "       12.302116 ,  6.2741756, 10.807182 ,  5.615202 ,  9.457176 ,\n",
       "        6.050267 ,  8.4565115,  7.3267875, 15.229051 , 12.261323 ,\n",
       "        3.8309646,  5.0908484,  5.4197145,  3.7519033,  5.457084 ,\n",
       "        5.2979546,  5.6802278,  5.237099 ,  3.6558645,  6.921174 ,\n",
       "        6.9580507,  3.9042723,  4.0810575,  3.7109916,  4.1984296,\n",
       "        6.4251795,  9.590438 ,  3.8518898,  3.5596187,  5.4065385,\n",
       "       11.233922 ,  4.147709 ,  4.5141993,  4.59452  ], dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2001-02-26 2001-03-07 ... 2021-03-25\n",
       "    lat      float64 -5.0\n",
       "    lon      float64 255.0\n",
       "Attributes:\n",
       "    waveName:        Kelvin\n",
       "    depth:           [ 8 90]\n",
       "    period:          [ 2.5 14. ]\n",
       "    wavenumber:      [ 1 14]\n",
       "    lat:             35.0\n",
       "    long_name:       Daily accumulated precipitation (combined microwave-IR) ...\n",
       "    units:           mm\n",
       "    cell_methods:    time: mean\n",
       "    title:           GPM IMERG Final Precipitation L3 1 day 0.1 degree x 0.1 ...\n",
       "    history_L34RS:   Created by L34RS v1.4.3 @ NASA GES DISC on January 17 20...\n",
       "    missing_values:  Missing values linearly interpolated one dimension at a ..."
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time_strong = pr.where(cond, drop=True)\n",
    "time_strong"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "cef56599-705d-4b5d-b604-e026b523d1ef",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "time_SH = time_strong['time']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "164090f5-a582-449e-a4f6-2d00e8c17a95",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "pr_SH_lag = data_kw['precipitationCal'].sel(lat=slice(-20,20),lon=slice(225,285), time = time_SH).mean(dim=('time'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "61784560-6a87-4b05-8a2f-650fc28afc14",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x2300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plot to choose latitude window for hovmoller plot\n",
    "\n",
    "color_map = plt.matplotlib.colormaps.get_cmap('Blues')\n",
    "\n",
    "npan = 1\n",
    "fig = plt.figure(figsize=(12, 23),constrained_layout=True)\n",
    "for j in range(0,npan,1):\n",
    "    ax1 = fig.add_subplot(npan,2,j+1,projection=ccrs.PlateCarree(central_longitude=180.))\n",
    "    ax1.coastlines('50m')\n",
    "    gl = ax1.gridlines(draw_labels=True, crs=ccrs.PlateCarree())\n",
    "    gl.top_labels = False\n",
    "    gl.right_labels = False\n",
    "    \n",
    "    # these are matplotlib.patch.Patch properties\n",
    "    props = dict(boxstyle='round', facecolor='wheat', alpha=0.5)\n",
    "    \n",
    "    if j == 0: \n",
    "        plt.title(wave, loc='left',fontsize=15)\n",
    "        cf = plt.contourf(pr_SH_lag['lon'], pr_SH_lag['lat'], pr_SH_lag, cmap=color_map, transform=ccrs.PlateCarree())\n",
    "        cb = plt.colorbar(cf, orientation='horizontal')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "9ba7248c-da99-4d02-9a45-45b5347b87e6",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#Chosen latitude  & longitude window\n",
    "\n",
    "latitude_s = -7.5\n",
    "latitude_n = -2.5\n",
    "\n",
    "longi_w= 100\n",
    "longi_e= 359"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "fdcff877-1f92-4e57-8ccf-8eb1ec0a0f67",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "pr_avg = data_kw['precipitationCal'].sel(lat=slice(latitude_s,latitude_n),lon=slice(longi_w,longi_e), time=time_SH).compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "18a34953-8919-44ff-80ee-a50a7697628b",
   "metadata": {
    "tags": []
   },
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (day: 31)&gt;\n",
       "array([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,\n",
       "        -2,  -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,\n",
       "        11,  12,  13,  14,  15])\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>day</span>: 31</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-fd0a4a5b-d553-4ee6-9612-723bd500b2c7' class='xr-array-in' type='checkbox' checked><label for='section-fd0a4a5b-d553-4ee6-9612-723bd500b2c7' 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>-15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 ... 5 6 7 8 9 10 11 12 13 14 15</span></div><div class='xr-array-data'><pre>array([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,\n",
       "        -2,  -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,\n",
       "        11,  12,  13,  14,  15])</pre></div></div></li><li class='xr-section-item'><input id='section-d9d41acb-2d67-4167-bd19-742a2604564a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d9d41acb-2d67-4167-bd19-742a2604564a' class='xr-section-summary' >Coordinates: <span>(1)</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'>day</span></div><div class='xr-var-dims'>(day)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-15 -14 -13 -12 -11 ... 12 13 14 15</div><input id='attrs-af33f652-b57d-4c28-8abd-1506471ae6e5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-af33f652-b57d-4c28-8abd-1506471ae6e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f76e1f06-ae2f-47d6-8c20-803b2167cbf4' class='xr-var-data-in' type='checkbox'><label for='data-f76e1f06-ae2f-47d6-8c20-803b2167cbf4' 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([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,  -2,\n",
       "        -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,\n",
       "        13,  14,  15])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-956af94f-703c-45c4-b0ba-0704bd51e0d7' class='xr-section-summary-in' type='checkbox'  ><label for='section-956af94f-703c-45c4-b0ba-0704bd51e0d7' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>day</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3f715a0d-8942-4c70-8222-2c6107dfb57c' class='xr-index-data-in' type='checkbox'/><label for='index-3f715a0d-8942-4c70-8222-2c6107dfb57c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,\n",
       "             -2,  -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,\n",
       "             11,  12,  13,  14,  15],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;day&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a6f65bcc-c789-4417-b96f-0296b29e5a9c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a6f65bcc-c789-4417-b96f-0296b29e5a9c' 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 (day: 31)>\n",
       "array([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,\n",
       "        -2,  -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,\n",
       "        11,  12,  13,  14,  15])\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15"
      ]
     },
     "execution_count": 21,
     "metadata": {},
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    }
   ],
   "source": [
    "day = np.arange(-15,16,1)\n",
    "nlag = len(day)\n",
    "lag_xr = xr.DataArray(day, coords=[day], dims=['day'])\n",
    "lag_xr"
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  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "29baac51-a049-4a98-abf1-759702cc1ca9",
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    {
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       "260"
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     "execution_count": 22,
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   ],
   "source": [
    "lon = pr_avg['lon']\n",
    "lat = pr_avg['lat']\n",
    "nlon = len(lon)\n",
    "nlat = len(lat)\n",
    "nlon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "93edb893-4910-41b6-b336-9d0561b118b4",
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    {
     "data": {
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       "(5, 260, 31)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kw_lag_avg = np.zeros((nlag,nlon))\n",
    "kw_lag_std = np.zeros((nlag,nlon))\n",
    "\n",
    "pr_kelvin_lreg_NH = np.zeros((nlat,nlon,nlag))\n",
    "pr_kelvin_corr_NH = np.zeros((nlat,nlon,nlag))\n",
    "pr_kelvin_lreg_NH.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "5b9d1f8a-05e7-4c1e-ae50-f1a9928c257e",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "for t in range(0,nlag,1):\n",
    "    lag = time_SH+np.timedelta64(int(lag_xr[t].values),'D')\n",
    "    kw_lag = data_kw['precipitationCal'].sel(time=lag, lat=slice(latitude_s,latitude_n),lon=slice(longi_w,longi_e))\n",
    "    kw_lag_avg[t,:] = kw_lag.mean(dim='lat').mean(dim='time')\n",
    "    kw_lag_std[t,:] = kw_lag.mean(dim='lat').std(dim='time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a2073820-7405-4542-bbbb-974152c91236",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "pr_kelvin_lag_avg_xr = xr.DataArray(kw_lag_avg, coords=[day, lon], dims=('day','lon'))\n",
    "pr_kelvin_lag_std_xr = xr.DataArray(kw_lag_std, coords=[day, lon], dims=('day','lon'))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f77727c0-d04b-4455-ac97-2ac34f56c842",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "dtime = 0.125\n",
    "lags_subdaily = np.arange(-15,15+dtime,dtime)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "0d2d8ec7-6bfe-459e-a6e9-456de147b9f5",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "kw_lag_avg_interp = pr_kelvin_lag_avg_xr.interp(day=lags_subdaily,method='cubic')\n",
    "kw_lag_std_interp = pr_kelvin_lag_std_xr.interp(day=lags_subdaily,method='cubic')\n",
    "\n",
    "day_subdaily = kw_lag_avg_interp['day']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7b04d08b-b0f9-4207-93e2-7233b8318d1a",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "pr_kelvin_lag_avg_xr.name = \"precipitationCal\"\n",
    "pr_kelvin_lag_std_xr.name = \"precipitationCal\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e9598983-d552-4deb-9143-299d1d783bb9",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "t_val = (kw_lag_avg_interp/kw_lag_std_interp) * (((len(time_SH)-1))**(1/2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "b0207eb6-5feb-4319-9bf2-187e9e52d2c5",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "p_val = scipy.stats.t.sf(abs(t_val), df=len(time_SH)-1)*2\n",
    "p_val_xr = xr.DataArray(p_val, coords=[day_subdaily, lon], dims=('day','lon'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "e1cd6b18-15da-43f1-bbab-fb1dd723f961",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "p_val_true = kw_lag_avg_interp.where(p_val<= 0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "65910cc9-1057-4ca9-b72f-2cfabf44c601",
   "metadata": {
    "tags": []
   },
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:     (time: 7791)\n",
       "Coordinates:\n",
       "  * time        (time) datetime64[ns] 2000-06-01 2000-06-02 ... 2021-09-30\n",
       "Data variables:\n",
       "    itcz_state  (time) float64 ...</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-3f45b10e-3e0f-4d31-93b2-9e330bfeb543' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3f45b10e-3e0f-4d31-93b2-9e330bfeb543' 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>: 7791</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-44876899-9e66-4513-a07b-96fdf491533a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-44876899-9e66-4513-a07b-96fdf491533a' class='xr-section-summary' >Coordinates: <span>(1)</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'>2000-06-01 ... 2021-09-30</div><input id='attrs-d23086dc-3df2-4925-868c-3dc8ec211bb2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d23086dc-3df2-4925-868c-3dc8ec211bb2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef60e3b6-9c6a-41fb-8d1b-4c29e128f7b3' class='xr-var-data-in' type='checkbox'><label for='data-ef60e3b6-9c6a-41fb-8d1b-4c29e128f7b3' 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>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;2000-06-01T00:00:00.000000000&#x27;, &#x27;2000-06-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-06-03T00:00:00.000000000&#x27;, ..., &#x27;2021-09-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-09-29T00:00:00.000000000&#x27;, &#x27;2021-09-30T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5e68e9c3-b8c2-4c93-a888-9807fb395985' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5e68e9c3-b8c2-4c93-a888-9807fb395985' class='xr-section-summary' >Data variables: <span>(1)</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>itcz_state</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f5d74d24-795c-436a-97d7-89bf90a4db23' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f5d74d24-795c-436a-97d7-89bf90a4db23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-651dde90-ea72-44b1-8def-3dd22a795c20' class='xr-var-data-in' type='checkbox'><label for='data-651dde90-ea72-44b1-8def-3dd22a795c20' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>IMERG daily ITCZ state</dd><dt><span>region :</span></dt><dd>East Pacific Ocean (90-135W)</dd><dt><span>method :</span></dt><dd>Algorithm developed for daily averaged precipitation rate</dd></dl></div><div class='xr-var-data'><pre>[7791 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fdf2b624-2e17-4d58-a832-7307bc99faf1' class='xr-section-summary-in' type='checkbox'  ><label for='section-fdf2b624-2e17-4d58-a832-7307bc99faf1' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7c15e93b-5c60-4ab1-b0f8-27c9f8c18b02' class='xr-index-data-in' type='checkbox'/><label for='index-7c15e93b-5c60-4ab1-b0f8-27c9f8c18b02' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2000-06-01&#x27;, &#x27;2000-06-02&#x27;, &#x27;2000-06-03&#x27;, &#x27;2000-06-04&#x27;,\n",
       "               &#x27;2000-06-05&#x27;, &#x27;2000-06-06&#x27;, &#x27;2000-06-07&#x27;, &#x27;2000-06-08&#x27;,\n",
       "               &#x27;2000-06-09&#x27;, &#x27;2000-06-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2021-09-21&#x27;, &#x27;2021-09-22&#x27;, &#x27;2021-09-23&#x27;, &#x27;2021-09-24&#x27;,\n",
       "               &#x27;2021-09-25&#x27;, &#x27;2021-09-26&#x27;, &#x27;2021-09-27&#x27;, &#x27;2021-09-28&#x27;,\n",
       "               &#x27;2021-09-29&#x27;, &#x27;2021-09-30&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=7791, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-304e4396-d62a-47ec-a1d8-8f6ef1976354' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-304e4396-d62a-47ec-a1d8-8f6ef1976354' 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>"
      ],
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       "<xarray.Dataset>\n",
       "Dimensions:     (time: 7791)\n",
       "Coordinates:\n",
       "  * time        (time) datetime64[ns] 2000-06-01 2000-06-02 ... 2021-09-30\n",
       "Data variables:\n",
       "    itcz_state  (time) float64 ..."
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#load ITCZ state data\n",
    "\n",
    "dri = '/home/ffahrin/test/IMERG/ITCZ_states/'\n",
    "fn  = 'IMERG_ITCZ_st_daily_EastPac_60prc.nc'\n",
    "\n",
    "data_itcz = xr.open_dataset(dri+fn)\n",
    "data_itcz"
   ]
  },
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       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2001-02-01 2001-02-02 ... 2021-04-30\n",
       "Attributes:\n",
       "    long_name:  IMERG daily ITCZ state\n",
       "    region:     East Pacific Ocean (90-135W)\n",
       "    method:     Algorithm developed for daily averaged precipitation rate</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'>'itcz_state'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1874</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-8490995c-78a3-4acc-98c3-37ce55be3184' class='xr-array-in' type='checkbox' checked><label for='section-8490995c-78a3-4acc-98c3-37ce55be3184' 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>...</span></div><div class='xr-array-data'><pre>[1874 values with dtype=float64]</pre></div></div></li><li class='xr-section-item'><input id='section-e71a2cd9-4bbb-4f89-921a-3ae0570c96af' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e71a2cd9-4bbb-4f89-921a-3ae0570c96af' class='xr-section-summary' >Coordinates: <span>(1)</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'>2001-02-01 ... 2021-04-30</div><input id='attrs-d10273b8-2283-4d54-8e85-f00fe6f75ab1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d10273b8-2283-4d54-8e85-f00fe6f75ab1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0109c8bf-cba2-4538-8bb5-7ed601c015af' class='xr-var-data-in' type='checkbox'><label for='data-0109c8bf-cba2-4538-8bb5-7ed601c015af' 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>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;2001-02-01T00:00:00.000000000&#x27;, &#x27;2001-02-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;2001-02-03T00:00:00.000000000&#x27;, ..., &#x27;2021-04-28T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-04-29T00:00:00.000000000&#x27;, &#x27;2021-04-30T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a4f06918-b38f-4e30-a8e8-572ee0c2c4b7' class='xr-section-summary-in' type='checkbox'  ><label for='section-a4f06918-b38f-4e30-a8e8-572ee0c2c4b7' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-880e6fd8-92e1-4a13-9a89-fd4b87a101d3' class='xr-index-data-in' type='checkbox'/><label for='index-880e6fd8-92e1-4a13-9a89-fd4b87a101d3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2001-02-01&#x27;, &#x27;2001-02-02&#x27;, &#x27;2001-02-03&#x27;, &#x27;2001-02-04&#x27;,\n",
       "               &#x27;2001-02-05&#x27;, &#x27;2001-02-06&#x27;, &#x27;2001-02-07&#x27;, &#x27;2001-02-08&#x27;,\n",
       "               &#x27;2001-02-09&#x27;, &#x27;2001-02-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2021-04-21&#x27;, &#x27;2021-04-22&#x27;, &#x27;2021-04-23&#x27;, &#x27;2021-04-24&#x27;,\n",
       "               &#x27;2021-04-25&#x27;, &#x27;2021-04-26&#x27;, &#x27;2021-04-27&#x27;, &#x27;2021-04-28&#x27;,\n",
       "               &#x27;2021-04-29&#x27;, &#x27;2021-04-30&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1874, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7d71129b-f571-4f24-bfd3-8acecf3034e8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7d71129b-f571-4f24-bfd3-8acecf3034e8' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>IMERG daily ITCZ state</dd><dt><span>region :</span></dt><dd>East Pacific Ocean (90-135W)</dd><dt><span>method :</span></dt><dd>Algorithm developed for daily averaged precipitation rate</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'itcz_state' (time: 1874)>\n",
       "[1874 values with dtype=float64]\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 2001-02-01 2001-02-02 ... 2021-04-30\n",
       "Attributes:\n",
       "    long_name:  IMERG daily ITCZ state\n",
       "    region:     East Pacific Ocean (90-135W)\n",
       "    method:     Algorithm developed for daily averaged precipitation rate"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "itcz_new_xr = data_itcz['itcz_state'].sel(time=time_fma)\n",
    "itcz_new_xr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "c6073bd5-bebd-4382-82db-4c15f0fbcdb8",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "cond_dITCZ = (itcz_new_xr == 1)\n",
    "cond_nITCZ = (itcz_new_xr == 2)\n",
    "cond_sITCZ = (itcz_new_xr == 3)\n",
    "cond_aITCZ = (itcz_new_xr == 4)\n",
    "cond_eITCZ = (itcz_new_xr == 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "1ac3a80e-0c14-4e78-97e4-0197ab5b1f22",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "prc_dITCZ = round(len(itcz_new_xr.where((cond_dITCZ), drop=True))/(len(time_fma))*100,1)\n",
    "prc_nITCZ = round(len(itcz_new_xr.where((cond_nITCZ), drop=True))/(len(time_fma))*100,1)\n",
    "prc_sITCZ = round(len(itcz_new_xr.where((cond_sITCZ), drop=True))/(len(time_fma))*100,1)\n",
    "prc_aITCZ = round(len(itcz_new_xr.where((cond_aITCZ), drop=True))/(len(time_fma))*100,1)\n",
    "prc_eITCZ = round(len(itcz_new_xr.where((cond_eITCZ), drop=True))/(len(time_fma))*100,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "8043426d-b056-494f-a70b-3571bcd4364c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Double     ITCZ happens 13.2% of the time.\n",
      "Northern   ITCZ happens 60.2% of the time.\n",
      "Southern   ITCZ happens 14.6% of the time.\n",
      "Absent     ITCZ happens 9.4% of the time.\n",
      "Equatorial ITCZ happens 2.6% of the time.\n"
     ]
    }
   ],
   "source": [
    "print('Double     ITCZ happens '+str(prc_dITCZ)+'% of the time.')\n",
    "print('Northern   ITCZ happens '+str(prc_nITCZ)+'% of the time.')\n",
    "print('Southern   ITCZ happens '+str(prc_sITCZ)+'% of the time.')\n",
    "print('Absent     ITCZ happens '+str(prc_aITCZ)+'% of the time.')\n",
    "print('Equatorial ITCZ happens '+str(prc_eITCZ)+'% of the time.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "13d1ebed-7195-49b5-81de-d7e54b128a54",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "time=time_SH"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "c45f83b4-6182-4cbd-8098-07e468981420",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "pr_dITCZ_st = np.zeros((nlag))\n",
    "pr_nITCZ_st = np.zeros((nlag))\n",
    "pr_sITCZ_st = np.zeros((nlag))\n",
    "pr_aITCZ_st = np.zeros((nlag))\n",
    "pr_eITCZ_st = np.zeros((nlag))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "729f2f53-08e4-4dff-b22d-bc36fb5ec64f",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "for t in range(0,nlag,1):\n",
    "    lag = time_SH+np.timedelta64(int(lag_xr[t].values),'D')\n",
    "    itcz_state_xr = data_itcz['itcz_state'].sel(time=lag)\n",
    "    cnd_dITCZ = (itcz_state_xr == 1)\n",
    "    cnd_nITCZ = (itcz_state_xr == 2)\n",
    "    cnd_sITCZ = (itcz_state_xr == 3)\n",
    "    cnd_aITCZ = (itcz_state_xr == 4)\n",
    "    cnd_eITCZ = (itcz_state_xr == 5)\n",
    "    pr_dITCZ_st[t] = round(len(itcz_state_xr.where((cnd_dITCZ), drop=True))/(len(time))*100,1)-prc_dITCZ\n",
    "    pr_nITCZ_st[t] = round(len(itcz_state_xr.where((cnd_nITCZ), drop=True))/(len(time))*100,1)-prc_nITCZ\n",
    "    pr_sITCZ_st[t] = round(len(itcz_state_xr.where((cnd_sITCZ), drop=True))/(len(time))*100,1)-prc_sITCZ\n",
    "    pr_aITCZ_st[t] = round(len(itcz_state_xr.where((cnd_aITCZ), drop=True))/(len(time))*100,1)-prc_aITCZ\n",
    "    pr_eITCZ_st[t] = round(len(itcz_state_xr.where((cnd_eITCZ), drop=True))/(len(time))*100,1)-prc_eITCZ"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "4fc6ac15-5dbe-4243-a05f-15fdf0c5854e",
   "metadata": {
    "tags": []
   },
   "outputs": [
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       ".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-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\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",
       ".xr-index-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",
       ".xr-index-data-in:checked ~ .xr-index-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-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-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",
       ".xr-no-icon {\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 (day: 31)&gt;\n",
       "array([   nan,    nan, -13.56, -15.52, -17.06, -17.92, -16.94, -18.36,\n",
       "       -18.46, -19.1 , -19.64, -20.2 , -19.32, -20.08, -20.4 , -19.42,\n",
       "       -18.86, -18.22, -16.48, -14.96, -14.64, -15.42, -14.32, -12.58,\n",
       "       -10.84,  -9.22,  -6.5 ,  -6.62,  -6.4 ,    nan,    nan])\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>day</span>: 31</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-ce23288e-65f0-4a96-8dea-a2acbf203ca2' class='xr-array-in' type='checkbox' checked><label for='section-ce23288e-65f0-4a96-8dea-a2acbf203ca2' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>nan nan -13.56 -15.52 -17.06 -17.92 ... -9.22 -6.5 -6.62 -6.4 nan nan</span></div><div class='xr-array-data'><pre>array([   nan,    nan, -13.56, -15.52, -17.06, -17.92, -16.94, -18.36,\n",
       "       -18.46, -19.1 , -19.64, -20.2 , -19.32, -20.08, -20.4 , -19.42,\n",
       "       -18.86, -18.22, -16.48, -14.96, -14.64, -15.42, -14.32, -12.58,\n",
       "       -10.84,  -9.22,  -6.5 ,  -6.62,  -6.4 ,    nan,    nan])</pre></div></div></li><li class='xr-section-item'><input id='section-7cdfb9fd-1814-4871-9b82-6dd0cac2f9f3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7cdfb9fd-1814-4871-9b82-6dd0cac2f9f3' class='xr-section-summary' >Coordinates: <span>(1)</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'>day</span></div><div class='xr-var-dims'>(day)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-15 -14 -13 -12 -11 ... 12 13 14 15</div><input id='attrs-6c562add-de4e-486b-9c86-50effb4fe749' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6c562add-de4e-486b-9c86-50effb4fe749' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5dcf2986-44d0-4e7d-8b61-a9801192d4fa' class='xr-var-data-in' type='checkbox'><label for='data-5dcf2986-44d0-4e7d-8b61-a9801192d4fa' 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([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,  -2,\n",
       "        -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,\n",
       "        13,  14,  15])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-79304f11-0884-4bd2-b734-0234e95151e6' class='xr-section-summary-in' type='checkbox'  ><label for='section-79304f11-0884-4bd2-b734-0234e95151e6' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>day</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c077f5b4-3c1d-4780-ad9a-3af15acc5eea' class='xr-index-data-in' type='checkbox'/><label for='index-c077f5b4-3c1d-4780-ad9a-3af15acc5eea' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,\n",
       "             -2,  -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,\n",
       "             11,  12,  13,  14,  15],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;day&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dc7827b5-8153-4bea-ad20-8d837e88f081' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-dc7827b5-8153-4bea-ad20-8d837e88f081' 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 (day: 31)>\n",
       "array([   nan,    nan, -13.56, -15.52, -17.06, -17.92, -16.94, -18.36,\n",
       "       -18.46, -19.1 , -19.64, -20.2 , -19.32, -20.08, -20.4 , -19.42,\n",
       "       -18.86, -18.22, -16.48, -14.96, -14.64, -15.42, -14.32, -12.58,\n",
       "       -10.84,  -9.22,  -6.5 ,  -6.62,  -6.4 ,    nan,    nan])\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr_nITCZ_st_xr=  xr.DataArray(pr_nITCZ_st, coords=[day], dims=('day'))\n",
    "pr_nITCZ_rolling = pr_nITCZ_st_xr.rolling(day=5,center=True).mean()\n",
    "pr_nITCZ_rolling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "b4f0453a-f957-4d52-b492-d3923b5f429c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
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       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
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       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
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       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
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       "\n",
       ".xr-var-data > table {\n",
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       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
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       "\n",
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       "\n",
       "dl.xr-attrs {\n",
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
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       "\n",
       ".xr-attrs dt {\n",
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       "\n",
       ".xr-attrs dt:hover span {\n",
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       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
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       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (day: 31)&gt;\n",
       "array([  nan,   nan,  9.4 ,  9.94, 10.5 , 10.82, 10.6 , 10.38,  9.2 ,\n",
       "        9.3 ,  9.42,  8.88,  9.44, 11.6 , 12.36, 11.7 , 10.5 ,  9.62,\n",
       "        8.86,  8.  ,  7.24,  8.66,  8.34,  7.04,  5.72,  5.72,  4.52,\n",
       "        3.98,  3.66,   nan,   nan])\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>day</span>: 31</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-65c5cd1e-eb8f-4703-8e87-395311d5fa8d' class='xr-array-in' type='checkbox' checked><label for='section-65c5cd1e-eb8f-4703-8e87-395311d5fa8d' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>nan nan 9.4 9.94 10.5 10.82 10.6 ... 5.72 5.72 4.52 3.98 3.66 nan nan</span></div><div class='xr-array-data'><pre>array([  nan,   nan,  9.4 ,  9.94, 10.5 , 10.82, 10.6 , 10.38,  9.2 ,\n",
       "        9.3 ,  9.42,  8.88,  9.44, 11.6 , 12.36, 11.7 , 10.5 ,  9.62,\n",
       "        8.86,  8.  ,  7.24,  8.66,  8.34,  7.04,  5.72,  5.72,  4.52,\n",
       "        3.98,  3.66,   nan,   nan])</pre></div></div></li><li class='xr-section-item'><input id='section-9297f606-1847-43da-b85f-9c7c9a249a7c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9297f606-1847-43da-b85f-9c7c9a249a7c' class='xr-section-summary' >Coordinates: <span>(1)</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'>day</span></div><div class='xr-var-dims'>(day)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-15 -14 -13 -12 -11 ... 12 13 14 15</div><input id='attrs-9652957b-43f7-428e-b24c-468caed28178' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9652957b-43f7-428e-b24c-468caed28178' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cdc22026-f708-409f-a7c3-9512399725cb' class='xr-var-data-in' type='checkbox'><label for='data-cdc22026-f708-409f-a7c3-9512399725cb' 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([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,  -2,\n",
       "        -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,\n",
       "        13,  14,  15])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-826c2f86-02b1-47db-ac8e-fba0306271a2' class='xr-section-summary-in' type='checkbox'  ><label for='section-826c2f86-02b1-47db-ac8e-fba0306271a2' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>day</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-fa146d66-a151-41ee-8fcc-04be3267755b' class='xr-index-data-in' type='checkbox'/><label for='index-fa146d66-a151-41ee-8fcc-04be3267755b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,\n",
       "             -2,  -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,\n",
       "             11,  12,  13,  14,  15],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;day&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1083a2f9-95d0-4cbd-aa15-846dce4578ed' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1083a2f9-95d0-4cbd-aa15-846dce4578ed' 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 (day: 31)>\n",
       "array([  nan,   nan,  9.4 ,  9.94, 10.5 , 10.82, 10.6 , 10.38,  9.2 ,\n",
       "        9.3 ,  9.42,  8.88,  9.44, 11.6 , 12.36, 11.7 , 10.5 ,  9.62,\n",
       "        8.86,  8.  ,  7.24,  8.66,  8.34,  7.04,  5.72,  5.72,  4.52,\n",
       "        3.98,  3.66,   nan,   nan])\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr_sITCZ_st_xr=  xr.DataArray(pr_sITCZ_st, coords=[day], dims=('day'))\n",
    "pr_sITCZ_rolling = pr_sITCZ_st_xr.rolling(day=5,center=True).mean()\n",
    "pr_sITCZ_rolling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "e9b064c3-f751-489f-8099-8a344a8155fc",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "total = len(pr_nITCZ_st_xr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "7759d34c-b6cf-48ba-932f-91e1d69130bc",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
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       "\n",
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       "\n",
       ".xr-var-data > table {\n",
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       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
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       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
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       "\n",
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
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       "\n",
       ".xr-attrs dt:hover span {\n",
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       "\n",
       ".xr-attrs dd {\n",
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       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
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       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (day: 31)&gt;\n",
       "array([ -8.6 , -10.7 , -13.56, -15.52, -17.06, -17.92, -16.94, -18.36,\n",
       "       -18.46, -19.1 , -19.64, -20.2 , -19.32, -20.08, -20.4 , -19.42,\n",
       "       -18.86, -18.22, -16.48, -14.96, -14.64, -15.42, -14.32, -12.58,\n",
       "       -10.84,  -9.22,  -6.5 ,  -6.62,  -6.4 , -11.3 ,  -4.2 ])\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>day</span>: 31</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-755ffd9a-9d32-450f-8da3-1dea5d4b0eef' class='xr-array-in' type='checkbox' checked><label for='section-755ffd9a-9d32-450f-8da3-1dea5d4b0eef' 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>-8.6 -10.7 -13.56 -15.52 -17.06 -17.92 ... -6.5 -6.62 -6.4 -11.3 -4.2</span></div><div class='xr-array-data'><pre>array([ -8.6 , -10.7 , -13.56, -15.52, -17.06, -17.92, -16.94, -18.36,\n",
       "       -18.46, -19.1 , -19.64, -20.2 , -19.32, -20.08, -20.4 , -19.42,\n",
       "       -18.86, -18.22, -16.48, -14.96, -14.64, -15.42, -14.32, -12.58,\n",
       "       -10.84,  -9.22,  -6.5 ,  -6.62,  -6.4 , -11.3 ,  -4.2 ])</pre></div></div></li><li class='xr-section-item'><input id='section-7fc66660-4d8e-47b3-bf88-41dba28fd9d6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7fc66660-4d8e-47b3-bf88-41dba28fd9d6' class='xr-section-summary' >Coordinates: <span>(1)</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'>day</span></div><div class='xr-var-dims'>(day)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-15 -14 -13 -12 -11 ... 12 13 14 15</div><input id='attrs-f7808b8b-4fdb-4bc7-a3b1-f09517739569' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f7808b8b-4fdb-4bc7-a3b1-f09517739569' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-155cfe28-162c-4365-b651-8ced16aa7a58' class='xr-var-data-in' type='checkbox'><label for='data-155cfe28-162c-4365-b651-8ced16aa7a58' 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([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,  -2,\n",
       "        -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,\n",
       "        13,  14,  15])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3519c879-6eda-4d02-b46a-eb63a4ae88f4' class='xr-section-summary-in' type='checkbox'  ><label for='section-3519c879-6eda-4d02-b46a-eb63a4ae88f4' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>day</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2bcd006e-d7a6-4e00-a142-833d973c04e9' class='xr-index-data-in' type='checkbox'/><label for='index-2bcd006e-d7a6-4e00-a142-833d973c04e9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,\n",
       "             -2,  -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,\n",
       "             11,  12,  13,  14,  15],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;day&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cdb5e828-4ddd-40fa-8a4a-ebc8eb1c8d2a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cdb5e828-4ddd-40fa-8a4a-ebc8eb1c8d2a' 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 (day: 31)>\n",
       "array([ -8.6 , -10.7 , -13.56, -15.52, -17.06, -17.92, -16.94, -18.36,\n",
       "       -18.46, -19.1 , -19.64, -20.2 , -19.32, -20.08, -20.4 , -19.42,\n",
       "       -18.86, -18.22, -16.48, -14.96, -14.64, -15.42, -14.32, -12.58,\n",
       "       -10.84,  -9.22,  -6.5 ,  -6.62,  -6.4 , -11.3 ,  -4.2 ])\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr_nITCZ_rolling[:2] = pr_nITCZ_st_xr[:2]\n",
    "pr_nITCZ_rolling[total-2:] = pr_nITCZ_st_xr[total-2:]\n",
    "pr_nITCZ_rolling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "ddc967e6-a926-437c-9658-2e9ee3832f4b",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "pr_nITCZ_rolling.name = \"percent\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "7f690ae6-2678-43da-a9ef-4cb1ca7f4845",
   "metadata": {
    "tags": []
   },
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (day: 31)&gt;\n",
       "array([ 8.2 ,  7.1 ,  9.4 ,  9.94, 10.5 , 10.82, 10.6 , 10.38,  9.2 ,\n",
       "        9.3 ,  9.42,  8.88,  9.44, 11.6 , 12.36, 11.7 , 10.5 ,  9.62,\n",
       "        8.86,  8.  ,  7.24,  8.66,  8.34,  7.04,  5.72,  5.72,  4.52,\n",
       "        3.98,  3.66,  5.  ,  3.9 ])\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>day</span>: 31</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e991f26f-8fc5-409e-b95d-4c51965c7d40' class='xr-array-in' type='checkbox' checked><label for='section-e991f26f-8fc5-409e-b95d-4c51965c7d40' 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>8.2 7.1 9.4 9.94 10.5 10.82 10.6 ... 5.72 5.72 4.52 3.98 3.66 5.0 3.9</span></div><div class='xr-array-data'><pre>array([ 8.2 ,  7.1 ,  9.4 ,  9.94, 10.5 , 10.82, 10.6 , 10.38,  9.2 ,\n",
       "        9.3 ,  9.42,  8.88,  9.44, 11.6 , 12.36, 11.7 , 10.5 ,  9.62,\n",
       "        8.86,  8.  ,  7.24,  8.66,  8.34,  7.04,  5.72,  5.72,  4.52,\n",
       "        3.98,  3.66,  5.  ,  3.9 ])</pre></div></div></li><li class='xr-section-item'><input id='section-afbc52ac-9279-48ea-ae26-16392ed464c8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-afbc52ac-9279-48ea-ae26-16392ed464c8' class='xr-section-summary' >Coordinates: <span>(1)</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'>day</span></div><div class='xr-var-dims'>(day)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-15 -14 -13 -12 -11 ... 12 13 14 15</div><input id='attrs-f101066e-71a5-4b66-b5df-c73514b1d458' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f101066e-71a5-4b66-b5df-c73514b1d458' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c4d45574-343d-4646-8d2b-8c0ea7b93bcc' class='xr-var-data-in' type='checkbox'><label for='data-c4d45574-343d-4646-8d2b-8c0ea7b93bcc' 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([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,  -2,\n",
       "        -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,\n",
       "        13,  14,  15])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2658d8b4-c27f-4009-afe2-f2d5ec60cddc' class='xr-section-summary-in' type='checkbox'  ><label for='section-2658d8b4-c27f-4009-afe2-f2d5ec60cddc' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>day</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-81142d98-7561-4e7c-bd11-3be085e84397' class='xr-index-data-in' type='checkbox'/><label for='index-81142d98-7561-4e7c-bd11-3be085e84397' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,\n",
       "             -2,  -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,\n",
       "             11,  12,  13,  14,  15],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;day&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a1760769-2e12-44f0-841b-014d476210ab' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a1760769-2e12-44f0-841b-014d476210ab' 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 (day: 31)>\n",
       "array([ 8.2 ,  7.1 ,  9.4 ,  9.94, 10.5 , 10.82, 10.6 , 10.38,  9.2 ,\n",
       "        9.3 ,  9.42,  8.88,  9.44, 11.6 , 12.36, 11.7 , 10.5 ,  9.62,\n",
       "        8.86,  8.  ,  7.24,  8.66,  8.34,  7.04,  5.72,  5.72,  4.52,\n",
       "        3.98,  3.66,  5.  ,  3.9 ])\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr_sITCZ_rolling[:2] = pr_sITCZ_st_xr[:2]\n",
    "pr_sITCZ_rolling[total-2:] = pr_sITCZ_st_xr[total-2:]\n",
    "pr_sITCZ_rolling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "eba94b5b-c0c2-4501-ac0e-346ab139356c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "pr_sITCZ_rolling.name = \"percent\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "6feaa575-f51e-4b04-be32-34915506f520",
   "metadata": {
    "tags": []
   },
   "outputs": [
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       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\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",
       "}\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",
       ".xr-no-icon {\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 (day: 31)&gt;\n",
       "array([ 1.7000000e+00,  7.0000000e-01, -8.8817842e-17, -1.0000000e-01,\n",
       "        1.0000000e-01,  9.8000000e-01,  1.2000000e+00,  1.4200000e+00,\n",
       "        1.6400000e+00,  1.6400000e+00,  9.8000000e-01,  8.6000000e-01,\n",
       "        7.6000000e-01,  6.4000000e-01,  4.4000000e-01,  7.6000000e-01,\n",
       "        7.6000000e-01,  9.8000000e-01,  6.6000000e-01,  6.6000000e-01,\n",
       "        8.8000000e-01,  1.3200000e+00,  1.4200000e+00,  1.4200000e+00,\n",
       "        1.0800000e+00,  4.4000000e-01,  2.2000000e-01, -1.0000000e-01,\n",
       "        2.0000000e-02, -4.0000000e-01,  7.0000000e-01])\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>day</span>: 31</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-6856f917-143c-40c6-b915-6d24725c06d3' class='xr-array-in' type='checkbox' checked><label for='section-6856f917-143c-40c6-b915-6d24725c06d3' 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>1.7 0.7 -8.882e-17 -0.1 0.1 0.98 1.2 ... 0.44 0.22 -0.1 0.02 -0.4 0.7</span></div><div class='xr-array-data'><pre>array([ 1.7000000e+00,  7.0000000e-01, -8.8817842e-17, -1.0000000e-01,\n",
       "        1.0000000e-01,  9.8000000e-01,  1.2000000e+00,  1.4200000e+00,\n",
       "        1.6400000e+00,  1.6400000e+00,  9.8000000e-01,  8.6000000e-01,\n",
       "        7.6000000e-01,  6.4000000e-01,  4.4000000e-01,  7.6000000e-01,\n",
       "        7.6000000e-01,  9.8000000e-01,  6.6000000e-01,  6.6000000e-01,\n",
       "        8.8000000e-01,  1.3200000e+00,  1.4200000e+00,  1.4200000e+00,\n",
       "        1.0800000e+00,  4.4000000e-01,  2.2000000e-01, -1.0000000e-01,\n",
       "        2.0000000e-02, -4.0000000e-01,  7.0000000e-01])</pre></div></div></li><li class='xr-section-item'><input id='section-fafd033e-2e7b-4d08-8ada-7d4220632659' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fafd033e-2e7b-4d08-8ada-7d4220632659' class='xr-section-summary' >Coordinates: <span>(1)</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'>day</span></div><div class='xr-var-dims'>(day)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-15 -14 -13 -12 -11 ... 12 13 14 15</div><input id='attrs-9b60ca74-1a16-47ee-80af-15c677b77d88' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9b60ca74-1a16-47ee-80af-15c677b77d88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1a5b843-0e26-4dcd-914f-693af8bdacac' class='xr-var-data-in' type='checkbox'><label for='data-b1a5b843-0e26-4dcd-914f-693af8bdacac' 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([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,  -2,\n",
       "        -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,\n",
       "        13,  14,  15])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0abd3238-06b2-4f41-9c18-b8ce89538148' class='xr-section-summary-in' type='checkbox'  ><label for='section-0abd3238-06b2-4f41-9c18-b8ce89538148' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>day</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1fde295c-205a-416b-8bca-8165bac75198' class='xr-index-data-in' type='checkbox'/><label for='index-1fde295c-205a-416b-8bca-8165bac75198' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,\n",
       "             -2,  -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,\n",
       "             11,  12,  13,  14,  15],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;day&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-28b55840-c50c-4e06-8b92-276eb40afc3d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-28b55840-c50c-4e06-8b92-276eb40afc3d' 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 (day: 31)>\n",
       "array([ 1.7000000e+00,  7.0000000e-01, -8.8817842e-17, -1.0000000e-01,\n",
       "        1.0000000e-01,  9.8000000e-01,  1.2000000e+00,  1.4200000e+00,\n",
       "        1.6400000e+00,  1.6400000e+00,  9.8000000e-01,  8.6000000e-01,\n",
       "        7.6000000e-01,  6.4000000e-01,  4.4000000e-01,  7.6000000e-01,\n",
       "        7.6000000e-01,  9.8000000e-01,  6.6000000e-01,  6.6000000e-01,\n",
       "        8.8000000e-01,  1.3200000e+00,  1.4200000e+00,  1.4200000e+00,\n",
       "        1.0800000e+00,  4.4000000e-01,  2.2000000e-01, -1.0000000e-01,\n",
       "        2.0000000e-02, -4.0000000e-01,  7.0000000e-01])\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr_eITCZ_st_xr=  xr.DataArray(pr_eITCZ_st, coords=[day], dims=('day'))\n",
    "pr_eITCZ_rolling = pr_eITCZ_st_xr.rolling(day=5,center=True).mean()\n",
    "\n",
    "pr_eITCZ_rolling[:2] = pr_eITCZ_st_xr[:2]\n",
    "pr_eITCZ_rolling[total-2:] = pr_eITCZ_st_xr[total-2:]\n",
    "pr_eITCZ_rolling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "6481c718-661e-43d8-a5d2-01e890bf15ae",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
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       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-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",
       ".xr-no-icon {\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 (day: 31)&gt;\n",
       "array([-1.8 ,  2.6 ,  2.78,  4.2 ,  4.3 ,  4.2 ,  3.98,  4.86,  5.72,\n",
       "        6.7 ,  8.1 ,  9.18,  9.18,  8.54,  8.44,  7.24,  6.82,  6.38,\n",
       "        5.82,  5.82,  7.02,  7.12,  6.9 ,  6.58,  6.46,  6.14,  4.94,\n",
       "        5.06,  5.5 ,  6.4 ,  4.2 ])\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>day</span>: 31</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-5fda23c8-36fc-43c6-b956-3d689d6ccb43' class='xr-array-in' type='checkbox' checked><label for='section-5fda23c8-36fc-43c6-b956-3d689d6ccb43' 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>-1.8 2.6 2.78 4.2 4.3 4.2 3.98 ... 6.46 6.14 4.94 5.06 5.5 6.4 4.2</span></div><div class='xr-array-data'><pre>array([-1.8 ,  2.6 ,  2.78,  4.2 ,  4.3 ,  4.2 ,  3.98,  4.86,  5.72,\n",
       "        6.7 ,  8.1 ,  9.18,  9.18,  8.54,  8.44,  7.24,  6.82,  6.38,\n",
       "        5.82,  5.82,  7.02,  7.12,  6.9 ,  6.58,  6.46,  6.14,  4.94,\n",
       "        5.06,  5.5 ,  6.4 ,  4.2 ])</pre></div></div></li><li class='xr-section-item'><input id='section-f3e315be-23ea-4dfb-88c0-01a86917461e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f3e315be-23ea-4dfb-88c0-01a86917461e' class='xr-section-summary' >Coordinates: <span>(1)</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'>day</span></div><div class='xr-var-dims'>(day)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-15 -14 -13 -12 -11 ... 12 13 14 15</div><input id='attrs-84bbdf72-a81d-4b08-b5c8-ef089da16d58' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-84bbdf72-a81d-4b08-b5c8-ef089da16d58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7269e9d-401f-44c9-b603-570f16ede8ae' class='xr-var-data-in' type='checkbox'><label for='data-b7269e9d-401f-44c9-b603-570f16ede8ae' 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([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,  -2,\n",
       "        -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,\n",
       "        13,  14,  15])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2f5a995a-c0be-4375-ac94-4cb27580e231' class='xr-section-summary-in' type='checkbox'  ><label for='section-2f5a995a-c0be-4375-ac94-4cb27580e231' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>day</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8621a5b3-1e27-48c6-9577-d9e27364f8f0' class='xr-index-data-in' type='checkbox'/><label for='index-8621a5b3-1e27-48c6-9577-d9e27364f8f0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,\n",
       "             -2,  -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,\n",
       "             11,  12,  13,  14,  15],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;day&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0a90992a-956c-418f-9d4e-2c5d375b6e09' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0a90992a-956c-418f-9d4e-2c5d375b6e09' 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 (day: 31)>\n",
       "array([-1.8 ,  2.6 ,  2.78,  4.2 ,  4.3 ,  4.2 ,  3.98,  4.86,  5.72,\n",
       "        6.7 ,  8.1 ,  9.18,  9.18,  8.54,  8.44,  7.24,  6.82,  6.38,\n",
       "        5.82,  5.82,  7.02,  7.12,  6.9 ,  6.58,  6.46,  6.14,  4.94,\n",
       "        5.06,  5.5 ,  6.4 ,  4.2 ])\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr_dITCZ_st_xr=  xr.DataArray(pr_dITCZ_st, coords=[day], dims=('day'))\n",
    "pr_dITCZ_rolling = pr_dITCZ_st_xr.rolling(day=5,center=True).mean()\n",
    "\n",
    "pr_dITCZ_rolling[:2] = pr_dITCZ_st_xr[:2]\n",
    "pr_dITCZ_rolling[total-2:] = pr_dITCZ_st_xr[total-2:]\n",
    "pr_dITCZ_rolling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "b14a6462-73ef-4eef-9645-7eb7c6ba09ae",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "pr_dITCZ_rolling.name = \"percent\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "c2aab066-2971-4fe9-9c90-a1c627af559d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
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       "}\n",
       "\n",
       "dl.xr-attrs {\n",
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       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\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",
       ".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",
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       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\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 (day: 31)&gt;\n",
       "array([  nan,   nan,  1.38,  1.48,  2.12,  1.9 ,  1.14,  1.68,  1.9 ,\n",
       "        1.48,  1.14,  1.24, -0.06, -0.7 , -0.82, -0.26,  0.82,  1.26,\n",
       "        1.14,  0.5 , -0.48, -1.66, -2.32, -2.42, -2.42, -3.08, -3.2 ,\n",
       "       -2.32, -2.76,   nan,   nan])\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>day</span>: 31</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-54139181-9c66-48b1-9ad6-3123a099aa92' class='xr-array-in' type='checkbox' checked><label for='section-54139181-9c66-48b1-9ad6-3123a099aa92' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>nan nan 1.38 1.48 2.12 1.9 1.14 ... -3.08 -3.2 -2.32 -2.76 nan nan</span></div><div class='xr-array-data'><pre>array([  nan,   nan,  1.38,  1.48,  2.12,  1.9 ,  1.14,  1.68,  1.9 ,\n",
       "        1.48,  1.14,  1.24, -0.06, -0.7 , -0.82, -0.26,  0.82,  1.26,\n",
       "        1.14,  0.5 , -0.48, -1.66, -2.32, -2.42, -2.42, -3.08, -3.2 ,\n",
       "       -2.32, -2.76,   nan,   nan])</pre></div></div></li><li class='xr-section-item'><input id='section-fbba1f92-0597-4fe3-a1f2-69b37a693cd8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fbba1f92-0597-4fe3-a1f2-69b37a693cd8' class='xr-section-summary' >Coordinates: <span>(1)</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'>day</span></div><div class='xr-var-dims'>(day)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-15 -14 -13 -12 -11 ... 12 13 14 15</div><input id='attrs-d1f6e965-38c1-4de7-baaf-da9695b2f3f3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d1f6e965-38c1-4de7-baaf-da9695b2f3f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4302a82f-6619-465d-87db-8b09db4c7538' class='xr-var-data-in' type='checkbox'><label for='data-4302a82f-6619-465d-87db-8b09db4c7538' 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([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,  -2,\n",
       "        -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,\n",
       "        13,  14,  15])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-33d06693-edfc-468c-acc4-fa7242d112d6' class='xr-section-summary-in' type='checkbox'  ><label for='section-33d06693-edfc-468c-acc4-fa7242d112d6' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>day</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f636a6f2-107b-4d84-80f8-7a23c78f0c37' class='xr-index-data-in' type='checkbox'/><label for='index-f636a6f2-107b-4d84-80f8-7a23c78f0c37' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,\n",
       "             -2,  -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,\n",
       "             11,  12,  13,  14,  15],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;day&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-26752e2b-80e9-4a54-9199-20a3e65617ea' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-26752e2b-80e9-4a54-9199-20a3e65617ea' 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 (day: 31)>\n",
       "array([  nan,   nan,  1.38,  1.48,  2.12,  1.9 ,  1.14,  1.68,  1.9 ,\n",
       "        1.48,  1.14,  1.24, -0.06, -0.7 , -0.82, -0.26,  0.82,  1.26,\n",
       "        1.14,  0.5 , -0.48, -1.66, -2.32, -2.42, -2.42, -3.08, -3.2 ,\n",
       "       -2.32, -2.76,   nan,   nan])\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr_aITCZ_st_xr=  xr.DataArray(pr_aITCZ_st, coords=[day], dims=('day'))\n",
    "pr_aITCZ_rolling = pr_aITCZ_st_xr.rolling(day=5,center=True).mean()\n",
    "pr_aITCZ_rolling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "91589ba0-95ce-462d-8398-27cbe7997963",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
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       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
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       "  fill: currentColor;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (day: 31)&gt;\n",
       "array([ 0.4 ,  0.4 ,  1.38,  1.48,  2.12,  1.9 ,  1.14,  1.68,  1.9 ,\n",
       "        1.48,  1.14,  1.24, -0.06, -0.7 , -0.82, -0.26,  0.82,  1.26,\n",
       "        1.14,  0.5 , -0.48, -1.66, -2.32, -2.42, -2.42, -3.08, -3.2 ,\n",
       "       -2.32, -2.76,  0.4 , -4.5 ])\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>day</span>: 31</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-96f89a05-553c-4402-8c95-5e595280fe55' class='xr-array-in' type='checkbox' checked><label for='section-96f89a05-553c-4402-8c95-5e595280fe55' 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>0.4 0.4 1.38 1.48 2.12 1.9 1.14 ... -3.08 -3.2 -2.32 -2.76 0.4 -4.5</span></div><div class='xr-array-data'><pre>array([ 0.4 ,  0.4 ,  1.38,  1.48,  2.12,  1.9 ,  1.14,  1.68,  1.9 ,\n",
       "        1.48,  1.14,  1.24, -0.06, -0.7 , -0.82, -0.26,  0.82,  1.26,\n",
       "        1.14,  0.5 , -0.48, -1.66, -2.32, -2.42, -2.42, -3.08, -3.2 ,\n",
       "       -2.32, -2.76,  0.4 , -4.5 ])</pre></div></div></li><li class='xr-section-item'><input id='section-db0b367a-c5d3-4a6e-ae16-18a9471eb429' class='xr-section-summary-in' type='checkbox'  checked><label for='section-db0b367a-c5d3-4a6e-ae16-18a9471eb429' class='xr-section-summary' >Coordinates: <span>(1)</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'>day</span></div><div class='xr-var-dims'>(day)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-15 -14 -13 -12 -11 ... 12 13 14 15</div><input id='attrs-1ae02725-f67c-496f-a10f-c8af892fb3d5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1ae02725-f67c-496f-a10f-c8af892fb3d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1fd2f91-b10d-4bc6-90c5-654244c54cde' class='xr-var-data-in' type='checkbox'><label for='data-d1fd2f91-b10d-4bc6-90c5-654244c54cde' 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([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,  -2,\n",
       "        -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,\n",
       "        13,  14,  15])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a2b8efaa-2289-451e-8e2d-b5a1003080d8' class='xr-section-summary-in' type='checkbox'  ><label for='section-a2b8efaa-2289-451e-8e2d-b5a1003080d8' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>day</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bb2d5073-e1c7-49bb-823d-ca8273f8895f' class='xr-index-data-in' type='checkbox'/><label for='index-bb2d5073-e1c7-49bb-823d-ca8273f8895f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,\n",
       "             -2,  -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,\n",
       "             11,  12,  13,  14,  15],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;day&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-073ae4a0-ae9b-46b5-bea1-c47c83d8b420' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-073ae4a0-ae9b-46b5-bea1-c47c83d8b420' 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 (day: 31)>\n",
       "array([ 0.4 ,  0.4 ,  1.38,  1.48,  2.12,  1.9 ,  1.14,  1.68,  1.9 ,\n",
       "        1.48,  1.14,  1.24, -0.06, -0.7 , -0.82, -0.26,  0.82,  1.26,\n",
       "        1.14,  0.5 , -0.48, -1.66, -2.32, -2.42, -2.42, -3.08, -3.2 ,\n",
       "       -2.32, -2.76,  0.4 , -4.5 ])\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pr_aITCZ_rolling[:2] = pr_aITCZ_st_xr[:2]\n",
    "pr_aITCZ_rolling[total-2:] = pr_aITCZ_st_xr[total-2:]\n",
    "pr_aITCZ_rolling"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0264aeca-a200-4c6a-8173-090c3e800b5f",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Call nc files to plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "887ade7f-850d-40ec-854d-40ab1173ccac",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:           (lon: 260, day: 241)\n",
       "Coordinates:\n",
       "  * lon               (lon) float64 100.0 101.0 102.0 ... 357.0 358.0 359.0\n",
       "  * day               (day) float64 -15.0 -14.88 -14.75 ... 14.75 14.88 15.0\n",
       "Data variables:\n",
       "    precipitationCal  (day, lon) float64 ...</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-cd75189b-a5a3-4102-b8a1-4cc3d3063bd9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cd75189b-a5a3-4102-b8a1-4cc3d3063bd9' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lon</span>: 260</li><li><span class='xr-has-index'>day</span>: 241</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d9be7dc7-363a-49ac-90dc-71e46da6e6ae' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d9be7dc7-363a-49ac-90dc-71e46da6e6ae' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>100.0 101.0 102.0 ... 358.0 359.0</div><input id='attrs-505d2fcc-b6df-4866-b14e-fec178bd8d7c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-505d2fcc-b6df-4866-b14e-fec178bd8d7c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56cf873a-75be-4fa1-99d0-96caebb21087' class='xr-var-data-in' type='checkbox'><label for='data-56cf873a-75be-4fa1-99d0-96caebb21087' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([100., 101., 102., ..., 357., 358., 359.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>day</span></div><div class='xr-var-dims'>(day)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-15.0 -14.88 -14.75 ... 14.88 15.0</div><input id='attrs-b2833231-d011-4853-828c-fad5a261e969' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b2833231-d011-4853-828c-fad5a261e969' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b28c181-759e-4bf3-957b-80c75967bbc5' class='xr-var-data-in' type='checkbox'><label for='data-5b28c181-759e-4bf3-957b-80c75967bbc5' 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([-15.   , -14.875, -14.75 , ...,  14.75 ,  14.875,  15.   ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1aa6070f-24c3-471b-aabf-50f1c8e701c1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1aa6070f-24c3-471b-aabf-50f1c8e701c1' class='xr-section-summary' >Data variables: <span>(1)</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>precipitationCal</span></div><div class='xr-var-dims'>(day, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a004874c-65ac-46e8-9838-c5cd56f51de4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a004874c-65ac-46e8-9838-c5cd56f51de4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be3edb46-6187-4a70-8fe9-21aca7ffabec' class='xr-var-data-in' type='checkbox'><label for='data-be3edb46-6187-4a70-8fe9-21aca7ffabec' 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>[62660 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-43779d37-21fa-4528-a8b3-209147ce9eaf' class='xr-section-summary-in' type='checkbox'  ><label for='section-43779d37-21fa-4528-a8b3-209147ce9eaf' class='xr-section-summary' >Indexes: <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-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f6894762-eaec-40cd-9004-a2704ec92a1e' class='xr-index-data-in' type='checkbox'/><label for='index-f6894762-eaec-40cd-9004-a2704ec92a1e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([100.0, 101.0, 102.0, 103.0, 104.0, 105.0, 106.0, 107.0, 108.0,\n",
       "              109.0,\n",
       "              ...\n",
       "              350.0, 351.0, 352.0, 353.0, 354.0, 355.0, 356.0, 357.0, 358.0,\n",
       "              359.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=260))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>day</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-58c103da-c0ad-4f34-9f04-ad61e1e3535b' class='xr-index-data-in' type='checkbox'/><label for='index-58c103da-c0ad-4f34-9f04-ad61e1e3535b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([  -15.0, -14.875,  -14.75, -14.625,   -14.5, -14.375,  -14.25,\n",
       "              -14.125,   -14.0, -13.875,\n",
       "              ...\n",
       "               13.875,    14.0,  14.125,   14.25,  14.375,    14.5,  14.625,\n",
       "                14.75,  14.875,    15.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;day&#x27;, length=241))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-597b1526-c307-4f88-afa0-2744a542468c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-597b1526-c307-4f88-afa0-2744a542468c' 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.Dataset>\n",
       "Dimensions:           (lon: 260, day: 241)\n",
       "Coordinates:\n",
       "  * lon               (lon) float64 100.0 101.0 102.0 ... 357.0 358.0 359.0\n",
       "  * day               (day) float64 -15.0 -14.88 -14.75 ... 14.75 14.88 15.0\n",
       "Data variables:\n",
       "    precipitationCal  (day, lon) float64 ..."
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dri = '/home/ffahrin/test/IMERG/rolling_avg/'\n",
    "fn = wave+'_NH_base_strong_pr.nc'\n",
    "    \n",
    "data_pr_NH = xr.open_dataset(dri+fn)\n",
    "data_pr_NH"
   ]
  },
  {
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   "id": "33ee63a1-5173-4f97-b53b-4ddb787a20f4",
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   },
   "outputs": [
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       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (day: 31)\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15\n",
       "Data variables:\n",
       "    percent  (day) float64 ...</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-f6b4d9ec-c25f-4efb-a13a-7a7a41eedc39' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f6b4d9ec-c25f-4efb-a13a-7a7a41eedc39' 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'>day</span>: 31</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-bcb187cd-6807-4071-a17c-f5ce998e56a3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bcb187cd-6807-4071-a17c-f5ce998e56a3' class='xr-section-summary' >Coordinates: <span>(1)</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'>day</span></div><div class='xr-var-dims'>(day)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-15 -14 -13 -12 -11 ... 12 13 14 15</div><input id='attrs-b49af1a1-f565-4c8c-b33f-29bfedab1cf4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b49af1a1-f565-4c8c-b33f-29bfedab1cf4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-619a15ad-7054-4948-b2b3-4dfc87e09579' class='xr-var-data-in' type='checkbox'><label for='data-619a15ad-7054-4948-b2b3-4dfc87e09579' 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([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,  -2,\n",
       "        -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,\n",
       "        13,  14,  15])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e57c3768-468c-44ef-ae11-2793c7338c16' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e57c3768-468c-44ef-ae11-2793c7338c16' class='xr-section-summary' >Data variables: <span>(1)</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>percent</span></div><div class='xr-var-dims'>(day)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a5786699-99ec-422e-a999-209625a4157e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a5786699-99ec-422e-a999-209625a4157e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-896ee5aa-cd90-4b0c-a90e-e051f07b8e5e' class='xr-var-data-in' type='checkbox'><label for='data-896ee5aa-cd90-4b0c-a90e-e051f07b8e5e' 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>[31 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2cb6d081-c767-4ff4-9329-8d03c5a4a077' class='xr-section-summary-in' type='checkbox'  ><label for='section-2cb6d081-c767-4ff4-9329-8d03c5a4a077' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>day</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-59fc8c6f-4629-4ef3-a3e6-c58184ca061a' class='xr-index-data-in' type='checkbox'/><label for='index-59fc8c6f-4629-4ef3-a3e6-c58184ca061a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,\n",
       "             -2,  -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,\n",
       "             11,  12,  13,  14,  15],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;day&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-eb86164e-2f01-483d-9086-5604ef163b62' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-eb86164e-2f01-483d-9086-5604ef163b62' 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.Dataset>\n",
       "Dimensions:  (day: 31)\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15\n",
       "Data variables:\n",
       "    percent  (day) float64 ..."
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dri = '/home/ffahrin/test/IMERG/rolling_avg/'\n",
    "fn = wave+'_NH_base_strong_nITCZ.nc'\n",
    "    \n",
    "data_pr_nITCZ = xr.open_dataset(dri+fn)\n",
    "data_pr_nITCZ"
   ]
  },
  {
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   "id": "1f9b725d-6b8a-4fd9-b745-5bfa0a5c5a09",
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    "tags": []
   },
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (day: 31)\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15\n",
       "Data variables:\n",
       "    percent  (day) float64 ...</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-597d327f-022d-4a36-841a-696f782e2cce' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-597d327f-022d-4a36-841a-696f782e2cce' 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'>day</span>: 31</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d1adb5b6-11df-4ae3-bc5f-f7b06ad5244f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d1adb5b6-11df-4ae3-bc5f-f7b06ad5244f' class='xr-section-summary' >Coordinates: <span>(1)</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'>day</span></div><div class='xr-var-dims'>(day)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-15 -14 -13 -12 -11 ... 12 13 14 15</div><input id='attrs-ec63994d-c782-470d-aac2-203aab5b39b4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ec63994d-c782-470d-aac2-203aab5b39b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d47be83-556b-47c5-b4e0-63c39cd1feeb' class='xr-var-data-in' type='checkbox'><label for='data-7d47be83-556b-47c5-b4e0-63c39cd1feeb' 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([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,  -2,\n",
       "        -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,\n",
       "        13,  14,  15])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d6eadb3a-62f7-48fa-abae-d779cf4f1650' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d6eadb3a-62f7-48fa-abae-d779cf4f1650' class='xr-section-summary' >Data variables: <span>(1)</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>percent</span></div><div class='xr-var-dims'>(day)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0557904d-1490-4339-8cc8-47b848d46e7f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0557904d-1490-4339-8cc8-47b848d46e7f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1624fb32-64f7-400c-856e-5caa489105ba' class='xr-var-data-in' type='checkbox'><label for='data-1624fb32-64f7-400c-856e-5caa489105ba' 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>[31 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-52f850ed-1c95-49e3-8265-29db5bca5bdd' class='xr-section-summary-in' type='checkbox'  ><label for='section-52f850ed-1c95-49e3-8265-29db5bca5bdd' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>day</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5f4aa170-11b4-4d1e-910c-a188191546ca' class='xr-index-data-in' type='checkbox'/><label for='index-5f4aa170-11b4-4d1e-910c-a188191546ca' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,\n",
       "             -2,  -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,\n",
       "             11,  12,  13,  14,  15],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;day&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a0785454-188e-405d-bca4-fc1d71beb817' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a0785454-188e-405d-bca4-fc1d71beb817' 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.Dataset>\n",
       "Dimensions:  (day: 31)\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15\n",
       "Data variables:\n",
       "    percent  (day) float64 ..."
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dri = '/home/ffahrin/test/IMERG/rolling_avg/'\n",
    "fn = wave+'_NH_base_strong_sITCZ.nc'\n",
    "    \n",
    "data_pr_sITCZ = xr.open_dataset(dri+fn)\n",
    "data_pr_sITCZ"
   ]
  },
  {
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   "id": "47bfa53f-7f18-4482-8f01-0a218281afca",
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   "outputs": [
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       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15\n",
       "Data variables:\n",
       "    percent  (day) float64 ...</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-5d4cf802-fe32-415d-8c81-9a2fac302c0c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5d4cf802-fe32-415d-8c81-9a2fac302c0c' 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'>day</span>: 31</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1b8afbcf-0c8b-4184-8203-be11f64ccd70' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1b8afbcf-0c8b-4184-8203-be11f64ccd70' class='xr-section-summary' >Coordinates: <span>(1)</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'>day</span></div><div class='xr-var-dims'>(day)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-15 -14 -13 -12 -11 ... 12 13 14 15</div><input id='attrs-513cb5d6-9c18-4105-a039-7329a34614c8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-513cb5d6-9c18-4105-a039-7329a34614c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-967607f1-120d-4d4b-a239-7f98b52c1cfe' class='xr-var-data-in' type='checkbox'><label for='data-967607f1-120d-4d4b-a239-7f98b52c1cfe' 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([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,  -2,\n",
       "        -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,  12,\n",
       "        13,  14,  15])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4694b6ab-73ca-440c-ab51-ced93e058405' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4694b6ab-73ca-440c-ab51-ced93e058405' class='xr-section-summary' >Data variables: <span>(1)</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>percent</span></div><div class='xr-var-dims'>(day)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b58ba3f0-8901-46fe-97e1-a39aed2e5d06' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b58ba3f0-8901-46fe-97e1-a39aed2e5d06' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2480fd7-24ca-431b-b314-1c1cb6a6b6be' class='xr-var-data-in' type='checkbox'><label for='data-b2480fd7-24ca-431b-b314-1c1cb6a6b6be' 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>[31 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4aa31aae-3dc7-4af4-a722-4d9c71f00435' class='xr-section-summary-in' type='checkbox'  ><label for='section-4aa31aae-3dc7-4af4-a722-4d9c71f00435' class='xr-section-summary' >Indexes: <span>(1)</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-index-name'><div>day</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7e02abde-784e-4ecf-b818-1030c69e3897' class='xr-index-data-in' type='checkbox'/><label for='index-7e02abde-784e-4ecf-b818-1030c69e3897' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Int64Index([-15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,\n",
       "             -2,  -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,\n",
       "             11,  12,  13,  14,  15],\n",
       "           dtype=&#x27;int64&#x27;, name=&#x27;day&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-21044937-ff25-4de3-b524-d497c8941d02' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-21044937-ff25-4de3-b524-d497c8941d02' 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.Dataset>\n",
       "Dimensions:  (day: 31)\n",
       "Coordinates:\n",
       "  * day      (day) int64 -15 -14 -13 -12 -11 -10 -9 -8 ... 8 9 10 11 12 13 14 15\n",
       "Data variables:\n",
       "    percent  (day) float64 ..."
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dri = '/home/ffahrin/test/IMERG/rolling_avg/'\n",
    "fn = wave+'_NH_base_strong_dITCZ.nc'\n",
    "    \n",
    "data_pr_dITCZ = xr.open_dataset(dri+fn)\n",
    "data_pr_dITCZ"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "3bf3507a-b55d-4f23-8918-eb476327a701",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "pr_NH = data_pr_NH['precipitationCal'].compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "05375a0d-a4e2-43d8-894c-ad819f5755d2",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "nITCZ_NH = data_pr_nITCZ['percent'].compute()\n",
    "sITCZ_NH = data_pr_sITCZ['percent'].compute()\n",
    "dITCZ_NH = data_pr_dITCZ['percent'].compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "9b46126b-540a-460b-bd26-3e1dd6b393eb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-0.9426583402864734\n"
     ]
    }
   ],
   "source": [
    "r_NH, p_NH = stats.pearsonr(nITCZ_NH, (sITCZ_NH+dITCZ_NH)) \n",
    "print(r_NH)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "7f494b78-c148-411c-aac2-e7022961f196",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-0.9246926048044601\n"
     ]
    }
   ],
   "source": [
    "r_SH, p_SH = stats.pearsonr(pr_nITCZ_rolling, (pr_sITCZ_rolling+pr_dITCZ_rolling)) \n",
    "print(r_SH)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "83b47479-218a-45b3-9085-9c9092bedd70",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "x = [150, 200, 250, 300, 350]\n",
    "labels = ['150$^{\\circ}$E', '160$^{\\circ}$W','110$^{\\circ}$W','60$^{\\circ}$W','10$^{\\circ}$W']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "4c1139e9-c9c1-486e-ada4-c5775eda1467",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1200 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cmap = tc.tol_cmap('BuRd')#.reversed()\n",
    "props = dict(boxstyle='square', facecolor='white', alpha=0.8)\n",
    "#level= np.arange(-2,2.5,0.5)\n",
    "level= np.arange(-3,3.5,0.5)\n",
    "#figfolder = '/home/ffahrin/test/IMERG/figures/'\n",
    "npan = 4\n",
    "# all of the sizes are double the size they'll be in the paper \n",
    "fig = plt.figure(figsize=(10,12),constrained_layout=True)#, tight_layout='true') #(10,12)\n",
    "for j in range(0,npan,1):\n",
    "    ax1 = fig.add_subplot(npan,2,j+1)\n",
    "    if j == 0: \n",
    "        cf =plt.contourf(pr_NH['lon'].sel(lon=slice(120,359)), pr_NH['day'], pr_NH.sel(lon=slice(120,359)), cmap=cmap, levels=level, extend='both')#,vmin=5)\n",
    "        #cb = plt.colorbar(cf, orientation='horizontal', pad=0.1,label='(mm/day)')\n",
    "        plt.ylabel('Lag (days)')\n",
    "        plt.xlabel('Longitude')\n",
    "        plt.title('a) 2.5$^{\\circ}$N - 7.5$^{\\circ}$N', fontsize=15,loc='left')\n",
    "        plt.annotate('base = 5$^{\\circ}$N, 105$^{\\circ}$W', xy=(0.68, 1.02), xycoords='axes fraction')#,bbox=props)\n",
    "        plt.axvline(225,color=\"#000000\",linestyle='-', alpha =0.6)\n",
    "        plt.axvline(285,color=\"#000000\",linestyle='-', alpha =0.6)\n",
    "        plt.axhline(0,color=\"#000000\",linestyle='--', alpha =0.2)\n",
    "        plt.xticks(x, labels)\n",
    "        #plt.annotate('base = 5$^{\\circ}$N, 105$^{\\circ}$W', xy=(0.68, 1.02), xycoords='axes fraction')#,bbox=props)\n",
    "        \n",
    "    if j == 1: \n",
    "        plt.plot(nITCZ_NH, nITCZ_NH['day'], color=\"#000000\",label=\"nITCZ\",linewidth=2)\n",
    "        plt.plot(sITCZ_NH, sITCZ_NH['day'], color=\"#DDAA33\",label=\"sITCZ\",linewidth=2)\n",
    "        plt.plot(dITCZ_NH, sITCZ_NH['day'], color=\"#004488\",label=\"dITCZ\",linewidth=2)\n",
    "        plt.plot(sITCZ_NH+dITCZ_NH, pr_sITCZ_rolling['day'], color=\"#CC3311\",label=\"sITCZ+dITCZ\",linewidth=2)\n",
    "        #plt.plot(pr_aITCZ_rolling, pr_aITCZ_rolling['day'], color=\"#000000\",label=\"aITCZ\")\n",
    "        plt.axhline(0,color='grey',linestyle='--')\n",
    "        plt.axvline(0,color='grey',linestyle='--')\n",
    "        plt.ylabel('Lag (days)',labelpad = .01)\n",
    "        plt.annotate('r = {:.2f}'.format(r_NH), xy=(0.02, 0.92), xycoords='axes fraction',bbox=props)\n",
    "        plt.xlim((-17,17))\n",
    "        plt.ylim((-15,15))\n",
    "        plt.xlabel('percent')\n",
    "        #plt.legend(loc=\"upper right\") \n",
    "        plt.title('b) 20$^{\\circ}$S - 20$^{\\circ}$N', fontsize=15,loc='left')\n",
    "        #plt.legend(loc=\"lower right\")\n",
    "        \n",
    "    if j == 2: \n",
    "        cf =plt.contourf(p_val_true['lon'].sel(lon=slice(120,359)), p_val_true['day'], p_val_true.sel(lon=slice(120,359)), cmap=cmap, levels=level, extend='both')#,vmin=5)\n",
    "        #cb = plt.colorbar(cf, orientation='horizontal', pad=0.05,label='(mm/day)')\n",
    "        #plt.axvline(250,color=\"#000000\",linestyle='--', alpha=0.5)\n",
    "        plt.axhline(0,color='grey',linestyle='--', alpha=0.5)\n",
    "        plt.axvline(225,color=\"#000000\",linestyle='-', alpha =0.6)\n",
    "        plt.axvline(285,color=\"#000000\",linestyle='-', alpha =0.6)\n",
    "        plt.ylabel('Lag (days)')\n",
    "        plt.xlabel('Longitude')\n",
    "        plt.xticks(x, labels)\n",
    "        #plt.annotate('base = 5$^{\\circ}$S, 255', xy=(0.68, 1.02), xycoords='axes fraction')#,bbox=props)\n",
    "        plt.annotate('base = 5$^{\\circ}$S, 105$^{\\circ}$W', xy=(0.68, 1.02), xycoords='axes fraction')#,bbox=props)\n",
    "        plt.title('c) 2.5$^{\\circ}$S - 7.5$^{\\circ}$S', fontsize=15,loc='left')\n",
    "        #fig.subplots_adjust(bottom=0.001)\n",
    "        cbar_ax = fig.add_axes([0.1, 0.42, 0.35, 0.02])\n",
    "        cbar= fig.colorbar(cf, cax=cbar_ax,orientation=\"horizontal\")\n",
    "        cbar.ax.tick_params(labelsize=10)\n",
    "        cbar.set_label(r'(mm/day)', fontsize=10)\n",
    "        #plt.xticks(x, labels)\n",
    "        #plt.xlabel('lat')\n",
    "        \n",
    "    if j == 3: \n",
    "        plt.plot(pr_nITCZ_rolling, pr_nITCZ_rolling['day'], color=\"#000000\",label=\"nITCZ\",linewidth=2)\n",
    "        plt.plot(pr_sITCZ_rolling, pr_sITCZ_rolling['day'], color=\"#DDAA33\",label=\"sITCZ\",linewidth=2)\n",
    "        plt.plot(pr_dITCZ_rolling, pr_dITCZ_rolling['day'], color=\"#004488\",label=\"dITCZ\",linewidth=2)\n",
    "        plt.plot(pr_sITCZ_rolling+pr_dITCZ_rolling, pr_sITCZ_rolling['day'], color=\"#CC3311\",label=\"sITCZ+dITCZ\",linewidth=2)\n",
    "        plt.axhline(0,color='grey',linestyle='--')\n",
    "        plt.axvline(0,color='grey',linestyle='--')\n",
    "        plt.title('d) 20$^{\\circ}$S - 20$^{\\circ}$N', fontsize=15,loc='left')\n",
    "        plt.annotate('r = {:.2f}'.format(r_SH), xy=(0.02, 0.92), xycoords='axes fraction',bbox=props)\n",
    "        plt.ylabel('Lag (days)',labelpad = .001)\n",
    "        plt.xlim((-30,30))\n",
    "        plt.ylim((-15,15))\n",
    "        plt.xlabel('percent')\n",
    "        #plt.legend(loc=\"upper right\")\n",
    "        plt.legend( loc=\"lower right\", ncol=4,fontsize=9,bbox_to_anchor=(0., -.4, 1., .102))\n",
    "plt.savefig(figfolder+wave+'_Pr_hov_ITCZ_lag.pdf', bbox_inches=\"tight\",transparent=False)                "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6526b318-0c7c-490d-8052-9dff7da90d3b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a9e54b97-f076-4980-875e-f7902ff6aa93",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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