{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "729a6096-915a-4707-9eae-29b76d67a522",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "####################\n",
    "# import libraries #\n",
    "####################\n",
    "\n",
    "# import libraries\n",
    "import sys \n",
    "import numpy as np \n",
    "from netCDF4 import Dataset\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "############\n",
    "# settings #\n",
    "############\n",
    "\n",
    "EXP = 'noresm2-mm-seaclim_hindcast'\n",
    "IDIR = '/nird/datalake/NS9039K/users/ingo/Projects/SEACLIM/data/noresm/output/raw' \n",
    "VNAME_NORESM = 'TREFHT'\n",
    "CLIM_NORESM = 'noresm2-mm-seaclim_hindcast.cam.h0.clim.1993-2024.startmonth11.leadmonth1-64.mem1-10.nc'\n",
    "VNAME_ERA5 = 't2m'\n",
    "CLIM_ERA5 = 't2m_ERA5_f09_1993-2024_clim.nc'\n",
    "OFFSET_K2C = -273.15 \n",
    "SDATE = 19931101 \n",
    "YEAR1 = 1993  \n",
    "YEAR2 = 1999\n",
    "MONTH1 = 11 \n",
    "MONTH2 = 2 \n",
    "MEMBERS = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] # can use a subset e.g. [1, 2, 3, 4]\n",
    "LONIND = 25 # corresponding to 30E \n",
    "LATIND = 176 # corresponding to 75N \n",
    "\n",
    "#############\n",
    "# functions #\n",
    "#############\n",
    "\n",
    "def read_noresm_lonlat1(idir, exp, vname, sdate, members, year1, year2, month1, month2, lonind, latind):   \n",
    "    def fpath(member, sdate, year, month):  \n",
    "        return f'{idir}/{exp}/{exp}_{sdate}/{exp}_{sdate}_mem{member:0>3}/atm/hist/{exp}_{sdate}_mem{member:0>3}.cam.h0.{year}-{month:0>2}.nc' \n",
    "    nmember = len(members)\n",
    "    nmonth = (year2 - year1 + 1) * 12 - (month1 - 1)  - (12 - month2)    \n",
    "    data = np.zeros((nmember,nmonth))\n",
    "    for imember, member in enumerate(members):\n",
    "        imonth = 0 \n",
    "        for year in range(year1, year2+1):\n",
    "            m1 = month1 if year == year1 else 1 \n",
    "            m2 = month2 if year == year2 else 12    \n",
    "            for month in range(m1, m2+1):\n",
    "                imonth += 1 \n",
    "                #print(imonth, f'{year}-{month:0>2}', fpath(member,sdate,year,month))     \n",
    "                #print(nc['lon'][lonind-1],nc['lat'][latind-1])\n",
    "                nc = Dataset(fpath(member,sdate,year,month),'r')\n",
    "                data[imember-1,imonth-1] = nc[vname][0,latind-1,lonind-1] + OFFSET_K2C\n",
    "                nc.close()\n",
    "    return data\n",
    "\n",
    "def read_noresm_lonlat1_clim(exp, vname, lonind, latind):   \n",
    "    fpath_clim = 'noresm2-mm-seaclim_hindcast.cam.h0.clim.1993-2024.startmonth11.leadmonth1-64.mem1-10.nc'\n",
    "    nc = Dataset(fpath_clim,'r')\n",
    "    clim = nc[vname][:,latind-1,lonind-1] + OFFSET_K2C\n",
    "    nc.close()\n",
    "    return clim\n",
    "\n",
    "def read_era5_lonlat1(vname, year1, year2, month1, month2, lonind, latind):\n",
    "    fpath_era5 = 't2m_ERA5_f09_199301-202412.nc'     \n",
    "    nc = Dataset(fpath_era5,'r')\n",
    "    nmonth = (year2 - year1 + 1) * 12 - (month1 - 1)  - (12 - month2)    \n",
    "    data = np.zeros(nmonth)\n",
    "    imonth = 0 \n",
    "    for year in range(year1, year2+1):\n",
    "        m1 = month1 if year == year1 else 1 \n",
    "        m2 = month2 if year == year2 else 12    \n",
    "        for month in range(m1, m2+1):\n",
    "            imonth += 1 \n",
    "            data[imonth-1] = nc[vname][imonth-1+(year1-1993)*12+month1-1,latind-1,lonind-1] + OFFSET_K2C\n",
    "    nc.close()\n",
    "    return data\n",
    "\n",
    "def read_era5_lonlat1_clim(vname, year1, year2, month1, month2, lonind, latind):\n",
    "    fpath_era5_clim = 't2m_ERA5_f09_1993-2024_clim.nc'     \n",
    "    nc = Dataset(fpath_era5_clim,'r')\n",
    "    nmonth = (year2 - year1 + 1) * 12 - (month1 - 1)  - (12 - month2)    \n",
    "    data = np.zeros(nmonth)\n",
    "    imonth = 0 \n",
    "    for year in range(year1, year2+1):\n",
    "        m1 = month1 if year == year1 else 1 \n",
    "        m2 = month2 if year == year2 else 12    \n",
    "        for month in range(m1, m2+1):\n",
    "            imonth += 1 \n",
    "            data[imonth-1] = nc[vname][month-1,latind-1,lonind-1] + OFFSET_K2C\n",
    "    nc.close()\n",
    "    return data\n",
    "\n",
    "################\n",
    "# prepare data #\n",
    "################\n",
    "\n",
    "# ERA5 and NorESM climological time series for forecast period (lead time dependent for NorESM)\n",
    "clim_era5 = read_era5_lonlat1_clim(VNAME_ERA5, YEAR1, YEAR2, MONTH1, MONTH2, LONIND, LATIND)   \n",
    "clim_noresm = read_noresm_lonlat1_clim(EXP, VNAME_NORESM, LONIND, LATIND)    \n",
    "\n",
    "# ERA5 and NorESM forecast time series for forecast period  \n",
    "data_era5 = read_era5_lonlat1(VNAME_ERA5, YEAR1, YEAR2, MONTH1, MONTH2, LONIND, LATIND)   \n",
    "data_noresm = read_noresm_lonlat1(IDIR, EXP, VNAME_NORESM, SDATE, MEMBERS, YEAR1, YEAR2, MONTH1, MONTH2, LONIND, LATIND)   \n",
    "\n",
    "# calibrate\n",
    "data_noresm_calibrated = np.zeros(data_noresm.shape)\n",
    "for imember in range(len(MEMBERS)):\n",
    "    data_noresm_calibrated[imember,:] = data_noresm[imember,:] - clim_noresm + clim_era5\n",
    "\n",
    "########\n",
    "# plot #\n",
    "########\n",
    "\n",
    "# set font sizes\n",
    "SMALL_SIZE = 16 \n",
    "MEDIUM_SIZE = 18 \n",
    "BIGGER_SIZE = 20 \n",
    "plt.rc('font', size=SMALL_SIZE)          # controls default text sizes\n",
    "plt.rc('axes', titlesize=SMALL_SIZE)     # fontsize of the axes title\n",
    "plt.rc('axes', labelsize=MEDIUM_SIZE)    # fontsize of the x and y labels\n",
    "plt.rc('xtick', labelsize=SMALL_SIZE)    # fontsize of the tick labels\n",
    "plt.rc('ytick', labelsize=SMALL_SIZE)    # fontsize of the tick labels\n",
    "plt.rc('legend', fontsize=SMALL_SIZE)    # legend fontsize\n",
    "plt.rc('figure', titlesize=BIGGER_SIZE)  # fontsize of the figure title\n",
    "\n",
    "# make axes \n",
    "fig,ax = plt.subplots(nrows=1,ncols=2, sharex=False, sharey=False, figsize=[12,5])\n",
    "\n",
    "# scatter plot of NorESM ensemble mean versus ERA5 \n",
    "ax[0].plot([-20, 10], [-20, 10],color='gray')\n",
    "hunc, = ax[0].plot(data_era5,data_noresm.mean(axis=0),marker='.',markersize=10,linestyle=None,linewidth=0,color='black',label='uncalibrated')\n",
    "hcal, = ax[0].plot(data_era5,data_noresm_calibrated.mean(axis=0),marker='*',markersize=8,linestyle=None,linewidth=0,color='red',label='calibrated')\n",
    "ax[0].set_xlim(-20,10)\n",
    "ax[0].set_ylim(-20,10)\n",
    "ax[0].set_xlabel('SAT ERA5 (K)')\n",
    "ax[0].set_ylabel('SAT NorESM (K)')\n",
    "ax[0].set_aspect('equal','box')\n",
    "ax[0].legend([hcal, hunc], ['calibrated', 'uncalibrated'], loc='upper left',frameon=False)\n",
    "# box plot for NorESM (individual members) and ERA5\n",
    "ax[1].boxplot([data_era5, data_noresm_calibrated.flatten(), data_noresm.flatten()],tick_labels=['ERA5','calibrated','uncalibrated']) \n",
    "ax[1].set_ylabel('SAT (K)')\n",
    "\n",
    "# save plot\n",
    "fig.suptitle(f'SAT calibrated vs uncalibrated ([30E,75N], 1993-11 to 1999-02)')\n",
    "plt.savefig('seaclim_calibration_example_monthly.png',format='png',dpi=300,bbox_inches='tight')\n",
    "\n",
    "# show plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "17e0ef3f-eac3-47a6-9334-b1fa378cc2e3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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