Heatwave_Frequency_Duration_Cumulative_Heat_1973_2022.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3d87b65e-bc6f-478c-ad8f-09f5c7d16272",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/r/Roshan.Jha/.local/lib/python3.10/site-packages/gribapi/__init__.py:23: UserWarning: ecCodes 2.21.0 or higher is recommended. You are running version 2.16.0\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import xarray as xr\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.dates as mdates\n",
    "from matplotlib.dates import MonthLocator, DayLocator, DateFormatter\n",
    "from matplotlib.dates import date2num\n",
    "\n",
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfeature\n",
    "import cartopy.mpl.ticker as cticker\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.patches import Rectangle\n",
    "from matplotlib.colors import TwoSlopeNorm\n",
    "from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
    "from matplotlib.colors import ListedColormap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "5ab2bcad-ae76-48dc-84fa-b79b0d9bbaee",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1973\n",
      "1974\n",
      "1975\n",
      "1976\n",
      "1977\n",
      "1978\n",
      "1979\n",
      "1980\n",
      "1981\n",
      "1982\n",
      "1983\n",
      "1984\n",
      "1985\n",
      "1986\n",
      "1987\n",
      "1988\n",
      "1989\n",
      "1990\n",
      "1991\n",
      "1992\n",
      "1993\n",
      "1994\n",
      "1995\n",
      "1996\n",
      "1997\n",
      "1998\n",
      "1999\n",
      "2000\n",
      "2001\n",
      "2002\n",
      "2003\n",
      "2004\n",
      "2005\n",
      "2006\n",
      "2007\n",
      "2008\n",
      "2009\n",
      "2010\n",
      "2011\n",
      "2012\n",
      "2013\n",
      "2014\n",
      "2015\n",
      "2016\n",
      "2017\n",
      "2018\n",
      "2019\n",
      "2020\n",
      "2021\n",
      "2022\n"
     ]
    }
   ],
   "source": [
    "data_path = ('../ERA5_T2/')\n",
    "t2m_max =[]\n",
    "for year in range(1973, 2023):\n",
    "    print(year)\n",
    "    file_path = os.path.join(data_path,f'T2_hourly-{year}-1deg.nc')\n",
    "    t2m = xr.open_dataset(file_path)    \n",
    "    temp_max = t2m.resample(time='D').max()\n",
    "    t2m_max.append(temp_max)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "bcc974d7-8900-470d-b293-84e2057cdff9",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = xr.concat(t2m_max,dim='time')\n",
    "lsm= xr.open_dataset('land_sea_mask.nc')\n",
    "mask = lsm.lsm.values\n",
    "ds = ds.where(mask != 0, float('nan'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c496e881-7bed-413f-be09-cfe6e67e1d15",
   "metadata": {},
   "outputs": [],
   "source": [
    "Tmax_RP = ds - 273.15\n",
    "Tmax_RP = Tmax_RP.where(~((Tmax_RP['time.month'] == 2) & (Tmax_RP['time.day'] == 29)), drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "dc60f250-cc34-43af-a3ff-243f435dff04",
   "metadata": {},
   "outputs": [],
   "source": [
    "tmax_subset = Tmax_RP\n",
    "tmax_subset['dayofyear'] = tmax_subset['time.dayofyear']\n",
    "leap_years = (tmax_subset['time.year'] % 4 == 0) & ((tmax_subset['time.year'] % 100 != 0) | (tmax_subset['time.year'] % 400 == 0))\n",
    "tmax_subset['dayofyear'] = xr.where(leap_years & (tmax_subset['time.month'] > 2),\n",
    "                                               tmax_subset['dayofyear'] - 1,\n",
    "                                               tmax_subset['dayofyear'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "93c30711-e245-41a1-a2ce-287bb1fb2788",
   "metadata": {},
   "outputs": [],
   "source": [
    "Tmax_RP_ds = tmax_subset.groupby('dayofyear') - tmax_subset.groupby('dayofyear').mean(dim='time')\n",
    "tmax_grouped = tmax_subset.groupby('dayofyear')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "11c37873-1ed6-46de-9c39-edd5c4bd181c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Calculating 90th Percentile for each calendar day using 15 day moving window\n",
    "Tmax_90P = []\n",
    "for day in range(1, 366):\n",
    "    # Calculate the indices for the rolling window\n",
    "    window_indices = [(day + i) % 365 for i in range(-(15//2), 15//2+1)]\n",
    "    window_indices = [idx if idx != 0 else idx+365 for idx in window_indices]\n",
    "    \n",
    "    # Concatenate groups for each calendar day with the rolling window\n",
    "    selected_groups = [tmax_grouped[i] for i in window_indices]\n",
    "    concatenated_data = xr.concat(selected_groups, dim='time')\n",
    "    percentile_90p = np.percentile(concatenated_data.t2m, 90, axis=0)\n",
    "    \n",
    "    percentile_90p_dataarray = xr.DataArray(percentile_90p, coords={'latitude': tmax_subset.latitude, 'longitude': tmax_subset.longitude}, dims=['latitude', 'longitude'])\n",
    "    Tmax_90P.append(percentile_90p_dataarray)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "3299936d-3509-406e-a7df-f11503da27ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "Tmax_2022 = tmax_subset.t2m.sel(time=slice('2022-01-01','2022-12-31'),latitude=19,longitude=76)\n",
    "Tmax_90Pctle = xr.concat(Tmax_90P, dim=Tmax_2022.time)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "d3c3bd0d-7122-4b72-acc7-43320f22947d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f3784d5b460>]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Tmax_2022.plot()\n",
    "Tmax_90Pctle.sel(latitude=19,longitude=76).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "3239e43b-2568-471c-8c35-2ced22f4a8dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Calculating 90th Percentile for each calendar day using 15 day moving window\n",
    "tmax_grouped = Tmax_RP_ds.groupby('dayofyear')\n",
    "Tmax_90P = []\n",
    "for day in range(1, 366):\n",
    "    # Calculate the indices for the rolling window\n",
    "    window_indices = [(day + i) % 365 for i in range(-(15//2), 15//2+1)]\n",
    "    window_indices = [idx if idx != 0 else idx+365 for idx in window_indices]\n",
    "    \n",
    "    # Concatenate groups for each calendar day with the rolling window\n",
    "    selected_groups = [tmax_grouped[i] for i in window_indices]\n",
    "    concatenated_data = xr.concat(selected_groups, dim='time')\n",
    "    percentile_90p = np.percentile(concatenated_data.t2m, 90, axis=0)\n",
    "    \n",
    "    percentile_90p_dataarray = xr.DataArray(percentile_90p, coords={'latitude': tmax_subset.latitude, 'longitude': tmax_subset.longitude}, dims=['latitude', 'longitude'])\n",
    "    Tmax_90P.append(percentile_90p_dataarray)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3b51eb74-5b2f-46ca-b756-0c49788f1a9f",
   "metadata": {},
   "outputs": [],
   "source": [
    "Tmax_2022_Ano = Tmax_RP_ds.t2m.sel(time=slice('2022-01-01','2022-12-31'),latitude=19,longitude=76)\n",
    "Tmax_90Pctle_Ano = xr.concat(Tmax_90P, dim=Tmax_2022_Ano.time)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "f1dd5b57-4c65-4624-b530-6c4992d6cd7b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f3784f52560>]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Tmax_2022_Ano.plot()\n",
    "Tmax_90Pctle_Ano.sel(latitude=19,longitude=76).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e9bcfde8-6fb9-43f7-8714-067c03928379",
   "metadata": {},
   "outputs": [],
   "source": [
    "#data_path = ('../ERA5_T2/')\n",
    "#t2m_max =[]\n",
    "#for year in range(1973, 2023):\n",
    "    #print(year)\n",
    "    #file_path = os.path.join(data_path,f'T2_hourly-{year}-1deg.nc')\n",
    "    #t2m = xr.open_dataset(file_path)    \n",
    "    #temp_max = t2m.resample(time='D').max()\n",
    "    #t2m_max.append(temp_max)\n",
    "\n",
    "#ds1 = xr.concat(t2m_max,dim='time')\n",
    "#ds1 = ds1.where(mask != 0, float('nan'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "232c68fc-a2cb-43e8-90d5-7661a1e3b6c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "Tmax = Tmax_RP_ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "b32ac1cf-d316-4498-94d2-ea73f99c65b4",
   "metadata": {},
   "outputs": [
    {
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       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (longitude: 360, latitude: 91, time: 18250)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 -180.0 -179.0 -178.0 ... 177.0 178.0 179.0\n",
       "  * latitude   (latitude) float32 90.0 89.0 88.0 87.0 86.0 ... 3.0 2.0 1.0 0.0\n",
       "  * time       (time) datetime64[ns] 1973-01-01 1973-01-02 ... 2022-12-31\n",
       "    dayofyear  (time) int64 1 2 3 4 5 6 7 8 ... 358 359 360 361 362 363 364 365\n",
       "Data variables:\n",
       "    t2m        (time, latitude, longitude) float32 nan nan nan ... nan nan nan</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-f136cd12-4239-471f-b110-f26d433d3dfc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f136cd12-4239-471f-b110-f26d433d3dfc' 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'>longitude</span>: 360</li><li><span class='xr-has-index'>latitude</span>: 91</li><li><span class='xr-has-index'>time</span>: 18250</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-52463986-b4f0-4199-a188-f23fe578039f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-52463986-b4f0-4199-a188-f23fe578039f' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-180.0 -179.0 ... 178.0 179.0</div><input id='attrs-b20e96be-60b1-4019-9c91-572b12a1b4f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b20e96be-60b1-4019-9c91-572b12a1b4f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb0e173f-8e46-4b74-983f-62ed77c2168f' class='xr-var-data-in' type='checkbox'><label for='data-fb0e173f-8e46-4b74-983f-62ed77c2168f' 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>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([-180., -179., -178., ...,  177.,  178.,  179.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>90.0 89.0 88.0 87.0 ... 2.0 1.0 0.0</div><input id='attrs-57a5652c-79dd-426c-a2ee-614aa754a94c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-57a5652c-79dd-426c-a2ee-614aa754a94c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e764f17-ddf5-4e01-bc22-12258a901618' class='xr-var-data-in' type='checkbox'><label for='data-5e764f17-ddf5-4e01-bc22-12258a901618' 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>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77.,\n",
       "       76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63.,\n",
       "       62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49.,\n",
       "       48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35.,\n",
       "       34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21.,\n",
       "       20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10.,  9.,  8.,  7.,\n",
       "        6.,  5.,  4.,  3.,  2.,  1.,  0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1973-01-01 ... 2022-12-31</div><input id='attrs-3a22738c-9d88-427c-84ba-36f5e96628a2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3a22738c-9d88-427c-84ba-36f5e96628a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e612032-6611-469b-a544-dfae084dc672' class='xr-var-data-in' type='checkbox'><label for='data-6e612032-6611-469b-a544-dfae084dc672' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1973-01-01T00:00:00.000000000&#x27;, &#x27;1973-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1973-01-03T00:00:00.000000000&#x27;, ..., &#x27;2022-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2022-12-30T00:00:00.000000000&#x27;, &#x27;2022-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dayofyear</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 ... 361 362 363 364 365</div><input id='attrs-71ab9d5b-26d3-41f8-b0db-301f06887ede' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-71ab9d5b-26d3-41f8-b0db-301f06887ede' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55c929b8-c9c4-4917-9964-845c470e2fd8' class='xr-var-data-in' type='checkbox'><label for='data-55c929b8-c9c4-4917-9964-845c470e2fd8' 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([  1,   2,   3, ..., 363, 364, 365])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fdd8cbf5-ea01-4261-b32a-7c010e9b20b7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fdd8cbf5-ea01-4261-b32a-7c010e9b20b7' 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>t2m</span></div><div class='xr-var-dims'>(time, latitude, longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9ce8a5ac-44c3-44a1-b09b-04a186fd11b7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9ce8a5ac-44c3-44a1-b09b-04a186fd11b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e286db5-f5e4-4ffc-9e73-857c307da4fb' class='xr-var-data-in' type='checkbox'><label for='data-6e286db5-f5e4-4ffc-9e73-857c307da4fb' 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([[[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7dd09dd3-9d9b-4ab7-be3c-1fbbbd6d30ec' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7dd09dd3-9d9b-4ab7-be3c-1fbbbd6d30ec' 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:    (longitude: 360, latitude: 91, time: 18250)\n",
       "Coordinates:\n",
       "  * longitude  (longitude) float32 -180.0 -179.0 -178.0 ... 177.0 178.0 179.0\n",
       "  * latitude   (latitude) float32 90.0 89.0 88.0 87.0 86.0 ... 3.0 2.0 1.0 0.0\n",
       "  * time       (time) datetime64[ns] 1973-01-01 1973-01-02 ... 2022-12-31\n",
       "    dayofyear  (time) int64 1 2 3 4 5 6 7 8 ... 358 359 360 361 362 363 364 365\n",
       "Data variables:\n",
       "    t2m        (time, latitude, longitude) float32 nan nan nan ... nan nan nan"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Tmax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "13d00980-c501-44c2-ae31-b1fe70739882",
   "metadata": {},
   "outputs": [],
   "source": [
    "def heatwave_aspect(data):\n",
    "    hot_days_only = data.where(data >0, drop=True).squeeze()\n",
    "    if hot_days_only.size < 3:\n",
    "        return 0, 0, 0, 0\n",
    "    else:\n",
    "        df_hd = hot_days_only.to_dataframe()\n",
    "        df_hd['group'] = (df_hd.index.to_series().diff() != pd.Timedelta(days=1)).cumsum()\n",
    "        grouped = df_hd.groupby('group')\n",
    "        dataframes_list = [group.drop(columns='group') for _, group in grouped]\n",
    "        dataframe_df_filtered = [df for df in dataframes_list if len(df) >= 3]\n",
    "        hwf = sum(len(df) for df in dataframe_df_filtered)  # HWF: Total number of days in all dataframes\n",
    "        hwn = len(dataframe_df_filtered)  # HWN: Number of dataframes in the list\n",
    "        hwi = round(sum([df['hd'].cumsum().iloc[-1] for df in dataframe_df_filtered]), 2)\n",
    "        if len(dataframe_df_filtered) == 0:\n",
    "            hwd = 0\n",
    "        else:\n",
    "            hwd = max(len(df) for df in dataframe_df_filtered)  # HWD: Length of the dataframe with maximum values\n",
    "        return hwf, hwd, hwn, hwi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "53b153ed-7011-46de-b5c8-3aa7c75ad973",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1973\n",
      "1974\n",
      "1975\n",
      "1976\n",
      "1977\n",
      "1978\n",
      "1979\n",
      "1980\n",
      "1981\n",
      "1982\n",
      "1983\n",
      "1984\n",
      "1985\n",
      "1986\n",
      "1987\n",
      "1988\n",
      "1989\n",
      "1990\n",
      "1991\n",
      "1992\n",
      "1993\n",
      "1994\n",
      "1995\n",
      "1996\n",
      "1997\n",
      "1998\n",
      "1999\n",
      "2000\n",
      "2001\n",
      "2002\n",
      "2003\n",
      "2004\n",
      "2005\n",
      "2006\n",
      "2007\n",
      "2008\n",
      "2009\n",
      "2010\n",
      "2011\n",
      "2012\n",
      "2013\n",
      "2014\n",
      "2015\n",
      "2016\n",
      "2017\n",
      "2018\n",
      "2019\n",
      "2020\n",
      "2021\n",
      "2022\n"
     ]
    }
   ],
   "source": [
    "lats= Tmax.sel(latitude=slice(60,0),longitude=slice(30,100)).latitude.values\n",
    "lons= Tmax.sel(latitude=slice(60,0),longitude=slice(30,100)).longitude.values\n",
    "years = np.arange(1973, 2023)\n",
    "\n",
    "HWF = np.zeros([np.size(years),np.size(lats),np.size(lons)]) \n",
    "HWN = np.zeros([np.size(years),np.size(lats),np.size(lons)])\n",
    "HWD = np.zeros([np.size(years),np.size(lats),np.size(lons)])\n",
    "HWI = np.zeros([np.size(years),np.size(lats),np.size(lons)])\n",
    "\n",
    "for yr, year in enumerate(range(1973, 2023)):\n",
    "    print(year)\n",
    "    Tmax_year = Tmax.sel(time=f'{year}',latitude=slice(60,0),longitude=slice(30,100))\n",
    "    Tmax_90Pctle = xr.concat(Tmax_90P, dim=Tmax_year.time)\n",
    "    Tmax_Pctle =  Tmax_90Pctle.sel(latitude=slice(60,0),longitude=slice(30,100))                 \n",
    "    hot_days = xr.where(np.isnan(Tmax_year.t2m) | np.isnan(Tmax_Pctle),\n",
    "                       np.nan,\n",
    "                       (Tmax_year.t2m - Tmax_Pctle))\n",
    "    hot_days.name='hd'\n",
    "    hot_days_MAM = hot_days.sel(time=hot_days['time.season'] == 'MAM')\n",
    "    \n",
    "    for i,lat in enumerate(lats):\n",
    "        for j,lon in enumerate(lons):\n",
    "            data= hot_days_MAM[:,i,j]\n",
    "            if (np.isnan(hot_days_MAM[0,i,j])):\n",
    "                HWF[yr,i,j] = np.nan\n",
    "                HWN[yr,i,j] = np.nan\n",
    "                HWD[yr,i,j] = np.nan\n",
    "                HWI[yr,i,j] = np.nan\n",
    "            else:\n",
    "                [hwf,hwd,hwn,hwi] = heatwave_aspect(data)\n",
    "                HWF[yr,i,j] = hwf\n",
    "                HWN[yr,i,j] = hwn\n",
    "                HWD[yr,i,j] = hwd\n",
    "                HWI[yr,i,j] = hwi          "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "dfec79a9-13f8-4cc4-9ad7-732d4bbc124e",
   "metadata": {},
   "outputs": [],
   "source": [
    "HW_Aspect = xr.Dataset({\"HWF\": (('year','latitude','longitude'), HWF),\n",
    "                           \"HWN\": (('year','latitude','longitude'), HWN),\n",
    "                           \"HWD\": (('year','latitude','longitude'), HWD),\n",
    "                           \"HWI\": (('year','latitude','longitude'), HWI)},\n",
    "                           coords={'year':years,'latitude': lats, 'longitude': lons})\n",
    "\n",
    "HW_Aspect.to_netcdf('Heatwave_Aspect_New_Method_1973_2022.nc')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "efa6c36f-9ab1-4e16-b963-7c9c89757510",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f365667c6a0>"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "HW_Aspect.HWF[49,:,:].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "b4161678-dbc7-4193-9575-6180b8bf5b8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f365675f1c0>"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "HW_Aspect.HWI[49,:,:].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "0670a6e6-7887-417d-a4f2-efa255a3da73",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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       " *\n",
       " */\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-text-repr-fallback {\n",
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       "\n",
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       "  padding-bottom: 6px;\n",
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       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
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       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
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       "\n",
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       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
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       "\n",
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       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-sections {\n",
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       "  display: grid;\n",
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       "\n",
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       "  display: none;\n",
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       "\n",
       ".xr-section-item input + label {\n",
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       "\n",
       ".xr-section-item input:enabled + label {\n",
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       "\n",
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       "\n",
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       "\n",
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       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-section-summary-in + label:before {\n",
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       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
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       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
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       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
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       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
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       "\n",
       ".xr-array-wrap {\n",
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       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
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       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
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       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (year: 50, latitude: 61, longitude: 71)\n",
       "Coordinates:\n",
       "  * year       (year) int64 1973 1974 1975 1976 1977 ... 2019 2020 2021 2022\n",
       "  * latitude   (latitude) float32 60.0 59.0 58.0 57.0 56.0 ... 3.0 2.0 1.0 0.0\n",
       "  * longitude  (longitude) float32 30.0 31.0 32.0 33.0 ... 97.0 98.0 99.0 100.0\n",
       "Data variables:\n",
       "    HWF        (year, latitude, longitude) float64 ...\n",
       "    HWN        (year, latitude, longitude) float64 ...\n",
       "    HWD        (year, latitude, longitude) float64 ...\n",
       "    HWI        (year, latitude, longitude) 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-f080fd14-506b-4bc7-a356-fc0c8c98e69c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f080fd14-506b-4bc7-a356-fc0c8c98e69c' 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'>year</span>: 50</li><li><span class='xr-has-index'>latitude</span>: 61</li><li><span class='xr-has-index'>longitude</span>: 71</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-bce7c81b-c00a-4281-bbb0-7ba54c326a54' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bce7c81b-c00a-4281-bbb0-7ba54c326a54' 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'>year</span></div><div class='xr-var-dims'>(year)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1973 1974 1975 ... 2020 2021 2022</div><input id='attrs-f347a12b-8571-441d-b740-92498b3e5b21' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f347a12b-8571-441d-b740-92498b3e5b21' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ad489c8-ddc4-4de9-a4bd-c8607787dce0' class='xr-var-data-in' type='checkbox'><label for='data-5ad489c8-ddc4-4de9-a4bd-c8607787dce0' 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([1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984,\n",
       "       1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996,\n",
       "       1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008,\n",
       "       2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020,\n",
       "       2021, 2022])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>60.0 59.0 58.0 57.0 ... 2.0 1.0 0.0</div><input id='attrs-541f1625-99f0-4421-932a-efe9d0eb0f56' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-541f1625-99f0-4421-932a-efe9d0eb0f56' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a43dcee4-64b3-4a6c-aca8-baf5fe285687' class='xr-var-data-in' type='checkbox'><label for='data-a43dcee4-64b3-4a6c-aca8-baf5fe285687' 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([60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47.,\n",
       "       46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33.,\n",
       "       32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19.,\n",
       "       18., 17., 16., 15., 14., 13., 12., 11., 10.,  9.,  8.,  7.,  6.,  5.,\n",
       "        4.,  3.,  2.,  1.,  0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>30.0 31.0 32.0 ... 98.0 99.0 100.0</div><input id='attrs-1f65b4bf-3c33-4535-b046-c6ca4cf3f7a2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1f65b4bf-3c33-4535-b046-c6ca4cf3f7a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0deb7e76-67a7-4195-b701-3130c94fb88e' class='xr-var-data-in' type='checkbox'><label for='data-0deb7e76-67a7-4195-b701-3130c94fb88e' 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([ 30.,  31.,  32.,  33.,  34.,  35.,  36.,  37.,  38.,  39.,  40.,  41.,\n",
       "        42.,  43.,  44.,  45.,  46.,  47.,  48.,  49.,  50.,  51.,  52.,  53.,\n",
       "        54.,  55.,  56.,  57.,  58.,  59.,  60.,  61.,  62.,  63.,  64.,  65.,\n",
       "        66.,  67.,  68.,  69.,  70.,  71.,  72.,  73.,  74.,  75.,  76.,  77.,\n",
       "        78.,  79.,  80.,  81.,  82.,  83.,  84.,  85.,  86.,  87.,  88.,  89.,\n",
       "        90.,  91.,  92.,  93.,  94.,  95.,  96.,  97.,  98.,  99., 100.],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-17d1537e-e997-4e8a-9ac2-bb8b835ad9ae' class='xr-section-summary-in' type='checkbox'  checked><label for='section-17d1537e-e997-4e8a-9ac2-bb8b835ad9ae' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>HWF</span></div><div class='xr-var-dims'>(year, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a2633366-7830-4e7f-8c66-5d4285d01236' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a2633366-7830-4e7f-8c66-5d4285d01236' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6e9df18-8c0c-473a-a433-c1300bcd9d86' class='xr-var-data-in' type='checkbox'><label for='data-a6e9df18-8c0c-473a-a433-c1300bcd9d86' 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>[216550 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HWN</span></div><div class='xr-var-dims'>(year, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7d06988a-3afe-44dd-925b-dbd1cf0a449d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7d06988a-3afe-44dd-925b-dbd1cf0a449d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c02e303e-bd70-4ceb-a0a1-005d407c85cf' class='xr-var-data-in' type='checkbox'><label for='data-c02e303e-bd70-4ceb-a0a1-005d407c85cf' 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>[216550 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HWD</span></div><div class='xr-var-dims'>(year, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-88f6b2de-4c79-4e57-adfc-7ca44e6bcd40' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-88f6b2de-4c79-4e57-adfc-7ca44e6bcd40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8714ac7f-cb41-4d5d-b2f8-72297f7e4e48' class='xr-var-data-in' type='checkbox'><label for='data-8714ac7f-cb41-4d5d-b2f8-72297f7e4e48' 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>[216550 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HWI</span></div><div class='xr-var-dims'>(year, latitude, longitude)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d34d6740-ed29-4287-b6f4-3a2a6a413a6f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d34d6740-ed29-4287-b6f4-3a2a6a413a6f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32af7fff-8073-4902-8205-09c326068059' class='xr-var-data-in' type='checkbox'><label for='data-32af7fff-8073-4902-8205-09c326068059' 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>[216550 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ff929f76-5937-4423-ad58-cd25940f7ac4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ff929f76-5937-4423-ad58-cd25940f7ac4' 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:    (year: 50, latitude: 61, longitude: 71)\n",
       "Coordinates:\n",
       "  * year       (year) int64 1973 1974 1975 1976 1977 ... 2019 2020 2021 2022\n",
       "  * latitude   (latitude) float32 60.0 59.0 58.0 57.0 56.0 ... 3.0 2.0 1.0 0.0\n",
       "  * longitude  (longitude) float32 30.0 31.0 32.0 33.0 ... 97.0 98.0 99.0 100.0\n",
       "Data variables:\n",
       "    HWF        (year, latitude, longitude) float64 ...\n",
       "    HWN        (year, latitude, longitude) float64 ...\n",
       "    HWD        (year, latitude, longitude) float64 ...\n",
       "    HWI        (year, latitude, longitude) float64 ..."
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "146f94c7-ddfc-4d31-bd8a-6a64fbc3b066",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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