Metric_calcu_CESM2_CESM2_gw_NorESM.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "36f1b9e8",
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_2132675/122002074.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mscipy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mio\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mscio\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mnetCDF4\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnc\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mLoad_data\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mData_from_nc\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mxarray\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mxr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/readonly/dodrio/apps/RHEL8/zen2-ib/software/netcdf4-python/1.5.7-foss-2021b/lib/python3.9/site-packages/netCDF4/__init__.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# init for netCDF4. package\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;31m# Docstring comes from extension module _netCDF4.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0m_netCDF4\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0;31m# Need explicit imports for names beginning with underscores\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;34m.\u001b[0m\u001b[0m_netCDF4\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0m__doc__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32msrc/netCDF4/_netCDF4.pyx\u001b[0m in \u001b[0;36minit netCDF4._netCDF4\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "import scipy.io as scio\n",
    "import netCDF4 as nc\n",
    "import numpy as np\n",
    "from Load_data import Data_from_nc\n",
    "import xarray as xr\n",
    "import math\n",
    "import gc\n",
    "\n",
    "\n",
    "def get_data_from_nc(file, variable):\n",
    "    file_obj = nc.Dataset(file)\n",
    "    data = file_obj.variables[variable]\n",
    "    var_data = np.array(data)\n",
    "    var_data = var_data[:, :, :]\n",
    "    var_data = np.squeeze(var_data)\n",
    "    return var_data\n",
    "    \n",
    "\n",
    "def Apparent_temperature_calcu(TSA, RH, U10):\n",
    "    T_c = TSA - 273.15\n",
    "    T_f = T_c * 1.8 + 32\n",
    "    e_s = np.exp(53.67957 - 6743.769 / TSA - 4.8451 * np.log(TSA)) * 100\n",
    "    e_RH = (RH / 100) * e_s\n",
    "    AT = T_c + 3.3 * e_RH / 1000 - 0.7 * U10 - 4\n",
    "    return AT\n",
    "\n",
    "def Heat_index_calcu(TSA, RH):\n",
    "    T_c = TSA - 273.15\n",
    "    T_f = T_c * 1.8 + 32\n",
    "    HI = -42.379 + 2.04901523 * T_f + 10.14333127 * RH - 0.22475541 * T_f * RH -6.83783 * 0.001 * np.square(T_f) - 5.481717 * 0.01 * np.square(RH) + 1.22874 * 0.001 * np.square(T_f) * RH + 8.5282 * 0.0001 * T_f * np.square(RH) - 1.99 * 0.000001 * np.square(T_f) * np.square(RH)\n",
    "    return HI\n",
    "\n",
    "def Humidex_calcu(TSA, RH):\n",
    "    T_c = TSA - 273.15\n",
    "    T_f = T_c * 1.8 + 32\n",
    "    e_s = np.exp(53.67957 - 6743.769 / TSA - 4.8451 * np.log(TSA)) * 100\n",
    "    e_RH = (RH / 100) * e_s\n",
    "    HUMIDEX = T_c + 5/9 * (e_RH / 100 - 10)\n",
    "    return HUMIDEX\n",
    "\n",
    "def Wet_bulb_temperature_calcu(TSA, RH):\n",
    "    T_c = TSA - 273.15\n",
    "    T_w = T_c * np.arctan(0.151977 * np.sqrt(RH + 8.313659)) + np.arctan(T_c + RH) - np.arctan(RH - 1.676331) + 0.00391838 * np.power(RH, 3/2) * np.arctan(0.023101 * RH) - 4.68035\n",
    "    return T_w\n",
    "\n",
    "def Temperature_humidity_index_for_comfort_calcu(TSA, RH):\n",
    "    T_c = TSA - 273.15\n",
    "    T_w = Wet_bulb_temperature_calcu(TSA, RH)\n",
    "    THIC = 0.72 * T_w + 0.72 * T_c + 40.6\n",
    "    return THIC\n",
    "\n",
    "def Temperature_humidity_index_for_physiology_calcu(TSA, RH):\n",
    "    T_c = TSA - 273.15\n",
    "    T_w = Wet_bulb_temperature_calcu(TSA, RH)\n",
    "    THIP = 0.63 * T_w + 1.17 * T_c + 32\n",
    "    return THIP\n",
    "\n",
    "def Discomfort_index_calcu(TSA, RH):\n",
    "    T_c = TSA - 273.15\n",
    "    T_w = Wet_bulb_temperature_calcu(TSA, RH)\n",
    "    DI = 0.5 * T_w + 0.5 * T_c\n",
    "    return DI\n",
    "\n",
    "def Swamp_temperature_calcu(TSA, RH, eta):\n",
    "    T_c = TSA - 273.15\n",
    "    T_w = Wet_bulb_temperature_calcu(TSA, RH)\n",
    "    T_s = T_c - eta / 100 * (T_c - T_w)\n",
    "    return T_s\n",
    "\n",
    "\n",
    "data_surface = Data_from_nc('/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/surfdata_irrigation_method.nc')   #load the data\n",
    "data_irrigation_method = data_surface.load_variable('irrigation_method')\n",
    "data_lon = data_surface.load_variable('LONGXY')\n",
    "data_lon = data_lon[0,:]\n",
    "data_lat = data_surface.load_variable('LATIXY')\n",
    "data_lat = data_lat[:,0]\n",
    "data_lat = data_lat[:]\n",
    "\n",
    "# Here we calculate the metrics based on the NorESM. For CESM2 and CESM2_gw, adjustments are needed\n",
    "for exp in ['IRR01', 'IRR02', 'IRR03', 'NOI01', 'NOI02', 'NOI03']:\n",
    "    for period in [\"1901_1910\",\"1911_1920\",\"1921_1930\", \"1931_1940\",\"1941_1950\",\"1951_1960\",\"1961_1970\",\"1971_1980\",\"1981_1984\", \"1985_1994\",\"1995_2004\",\"2005_2014\"]:\n",
    "        TSA_daily = get_data_from_nc('/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/' + exp + '//3_hourly_mean/TSA/NorESM_' + exp + '_TSA_' + period + '.nc', 'TSA')\n",
    "        RH2M_daily = get_data_from_nc('/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/' + exp + '//3_hourly_mean/RH2M/NorESM_' + exp + '_RH2M_' + period + '.nc', 'RH2M')\n",
    "        U10_daily = get_data_from_nc('/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/' + exp + '//3_hourly_mean/U10/NorESM_' + exp + '_U10_' + period + '.nc', 'U10')\n",
    "        \n",
    "\n",
    "        TSA_daily[TSA_daily > 1000] = np.nan\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/TSA_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_1.mat\", {'TSA': TSA_daily[:7300, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/TSA_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_2.mat\", {'TSA': TSA_daily[7300: 14600, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/TSA_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_3.mat\", {'TSA': TSA_daily[14600: 21900, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/TSA_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_4.mat\", {'TSA': TSA_daily[21900:, :, :]})\n",
    "\n",
    "        \n",
    "        AT_daily = Apparent_temperature_calcu(TSA_daily, RH2M_daily, U10_daily)\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/AT_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_1.mat\", {'AT': AT_daily[:7300, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/AT_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_2.mat\", {'AT': AT_daily[7300: 14600, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/AT_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_3.mat\", {'AT': AT_daily[14600: 21900, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/AT_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_4.mat\", {'AT': AT_daily[21900:, :, :]})\n",
    "        \n",
    "        del AT_daily\n",
    "        gc.collect()\n",
    "        \n",
    "        HI_daily = Heat_index_calcu(TSA_daily, RH2M_daily)\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/HI_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_1.mat\", {'HI': HI_daily[:7300, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/HI_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_2.mat\", {'HI': HI_daily[7300: 14600, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/HI_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_3.mat\", {'HI': HI_daily[14600: 21900, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/HI_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_4.mat\", {'HI': HI_daily[21900:, :, :]})\n",
    "        \n",
    "        \n",
    "        del HI_daily\n",
    "        gc.collect()\n",
    "\n",
    "\n",
    "        HUMIDEX_daily = Humidex_calcu(TSA_daily, RH2M_daily)\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/HUMIDEX_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_1.mat\", {'HUMIDEX': HUMIDEX_daily[:7300, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/HUMIDEX_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_2.mat\", {'HUMIDEX': HUMIDEX_daily[7300: 14600, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/HUMIDEX_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_3.mat\", {'HUMIDEX': HUMIDEX_daily[14600: 21900, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/HUMIDEX_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_4.mat\", {'HUMIDEX': HUMIDEX_daily[21900:, :, :]})\n",
    "        \n",
    "        del HUMIDEX_daily\n",
    "        gc.collect()\n",
    "        \n",
    "        \n",
    "        T_w_daily = Wet_bulb_temperature_calcu(TSA_daily, RH2M_daily)\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/T_w_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_1.mat\", {'T_w': T_w_daily[:7300, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/T_w_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_2.mat\", {'T_w': T_w_daily[7300: 14600, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/T_w_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_3.mat\", {'T_w': T_w_daily[14600: 21900, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/T_w_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_4.mat\", {'T_w': T_w_daily[21900:, :, :]})\n",
    "        \n",
    "        del T_w_daily\n",
    "        gc.collect()\n",
    "        \n",
    "    \n",
    "        THIC_daily = Temperature_humidity_index_for_comfort_calcu(TSA_daily, RH2M_daily)\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/THIC_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_1.mat\", {'THIC': THIC_daily[:7300, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/THIC_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_2.mat\", {'THIC': THIC_daily[7300: 14600, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/THIC_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_3.mat\", {'THIC': THIC_daily[14600: 21900, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/THIC_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_4.mat\", {'THIC': THIC_daily[21900:, :, :]})\n",
    "        \n",
    "        del THIC_daily\n",
    "        gc.collect()\n",
    "        \n",
    "\n",
    "        THIP_daily = Temperature_humidity_index_for_physiology_calcu(TSA_daily, RH2M_daily)\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/THIP_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_1.mat\", {'THIP': THIP_daily[:7300, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/THIP_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_2.mat\", {'THIP': THIP_daily[7300: 14600, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/THIP_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_3.mat\", {'THIP': THIP_daily[14600: 21900, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/THIP_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_4.mat\", {'THIP': THIP_daily[21900:, :, :]})\n",
    "        \n",
    "        del THIP_daily\n",
    "        gc.collect()\n",
    "        \n",
    "\n",
    "        DI_daily = Discomfort_index_calcu(TSA_daily, RH2M_daily)\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/DI_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_1.mat\", {'DI': DI_daily[:7300, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/DI_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_2.mat\", {'DI': DI_daily[7300: 14600, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/DI_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_3.mat\", {'DI': DI_daily[14600: 21900, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/DI_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_4.mat\", {'DI': DI_daily[21900:, :, :]})\n",
    "        \n",
    "        del DI_daily\n",
    "        gc.collect()\n",
    "        \n",
    "\n",
    "        T_s_65_daily = Swamp_temperature_calcu(TSA_daily, RH2M_daily, 65)\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/T_s_65_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_1.mat\", {'T_s_65': T_s_65_daily[:7300, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/T_s_65_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_2.mat\", {'T_s_65': T_s_65_daily[7300: 14600, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/T_s_65_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_3.mat\", {'T_s_65': T_s_65_daily[14600: 21900, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/T_s_65_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_4.mat\", {'T_s_65': T_s_65_daily[21900:, :, :]})\n",
    "        \n",
    "        del T_s_65_daily\n",
    "        gc.collect()\n",
    "\n",
    "        T_s_80_daily = Swamp_temperature_calcu(TSA_daily, RH2M_daily, 80)\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/T_s_80_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_1.mat\", {'T_s_80': T_s_80_daily[:7300, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/T_s_80_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_2.mat\", {'T_s_80': T_s_80_daily[7300: 14600, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/T_s_80_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_3.mat\", {'T_s_80': T_s_80_daily[14600: 21900, :, :]})\n",
    "        scio.savemat(\"/dodrio/scratch/projects/2022_200/project_output/cesm/yi_yao_IRRMIP/after_process/NorESM/post_process/T_s_80_\" + \\\n",
    "                     period + \"_3_hourly_\" + exp + \"_4.mat\", {'T_s_80': T_s_80_daily[21900:, :, :]})\n",
    "        \n",
    "        del T_s_80_daily\n",
    "        gc.collect()\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "25e0507f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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