TC_future_MIT/SI_TabS3-4-5.py at main · simonameiler/TC_future_MIT · GitHub

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"""
Adapted for code repository on 2023-06-22

description: Supplementary Information Table S3, S4, S5 -
             print out of hazard frequencies and intensities of present and future
             results of SI Tables are frequency and intensity changes, e.g. frequency
             future - frequency present.

@author: simonameiler
"""

import sys
import numpy as np

#Load Climada modules
from climada.util.constants import SYSTEM_DIR # loads default directory paths for data
from climada.hazard import TropCyclone

def main(region, period):


    ###########################################################################
    ############### A: define constants, functions, paths #####################
    ###########################################################################

    # define paths
    haz_dir = SYSTEM_DIR/"hazard/future"

    res = 300
    region = str(region) # AP, IO, SH, WP
    period = str(period) # 20thcal (1995-2014), cal (2041-2060), _2cal (2081-2100)


    # load hazard
    # make list
    h1_min, h1_max = (1, 9)
    h2_min, h2_max = (1, 3)
    h3_min, h3_max = (1, 1)

    model_key = {1: 'cesm2',
                 2: 'cnrm6',
                 3: 'ecearth6',
                 4: 'fgoals',
                 5: 'ipsl6',
                 6: 'miroc6',
                 7: 'mpi6',
                 8: 'mri6',
                 9: 'ukmo6'}

    ssp_haz_key = {1: 'ssp245',
                   2: 'ssp370',
                   3: 'ssp585'}

    wind_model_key = {1: '',
                      2: 'ER11_'}

    # present climate
    tc_haz_base_dict = {}
    for h1 in range(h1_min, h1_max+1):
        for h3 in range(h3_min, h3_max+1):
            haz_base_str = f"TC_{region}_0{res}as_{wind_model_key[h3]}MIT_{model_key[h1]}_20thcal.hdf5"
            tc_haz_base = TropCyclone.from_hdf5(haz_dir.joinpath(haz_base_str))
            tc_haz_base.check()
            tc_haz_base_dict[str(wind_model_key[h3])+str(model_key[h1])] = tc_haz_base

    # future climate
    tc_haz_fut_dict = {}
    for h1 in range(h1_min, h1_max+1):
        for h2 in range(h2_min, h2_max+1):
            for h3 in range(h3_min, h3_max+1):
                haz_fut_str = f"TC_{region}_0{res}as_{wind_model_key[h3]}MIT_{model_key[h1]}_{ssp_haz_key[h2]}{period}.hdf5"
                tc_haz_fut = TropCyclone.from_hdf5(haz_dir.joinpath(haz_fut_str))
                tc_haz_fut.check()
                tc_haz_fut_dict[str(wind_model_key[h3])+str(model_key[h1])+'_'+str(ssp_haz_key[h2])] = tc_haz_fut

    # store frequency information - present
    for h, haz in tc_haz_base_dict.items():
        print(h, haz.frequency.sum())

    # store frequency information - future
    for h, haz in tc_haz_fut_dict.items():
        print(h, haz.frequency.sum())

    # store intensity information - present
    for h, haz in tc_haz_base_dict.items():
        print(h, np.max(haz.intensity, axis=1).mean())

    # store intensity information - future
    for h, haz in tc_haz_fut_dict.items():
        print(h, np.max(haz.intensity, axis=1).mean())

if __name__ == "__main__":
    main(*sys.argv[1:])