#!/usr/bin/env python # Wenchang Yang (wenchang@princeton.edu) # Tue Jun 29 16:14:32 EDT 2021 if __name__ == '__main__': from misc.timer import Timer tt = Timer(f'start {__file__}') import sys, os.path, os, glob, datetime import xarray as xr, numpy as np, pandas as pd, matplotlib.pyplot as plt #more imports import geoxarray from misc.landmask import flagland # if __name__ == '__main__': tt.check('end import') # #start from here daname = 'Ts' daname_new = 'GMST' rename_grid = lambda x: x.rename(grid_xt='lon', grid_yt='lat') #lons = slice(360-123, 360-119) #lats = slice(45, 52) #long_name_region = f'{360-lons.start}-{360-lons.stop}W_{lats.start}-{lats.stop}N_land' #sel_region = lambda x: x.sel(lon=lons, lat=lats) sel_region = lambda x: x years = range(1870,2015) ofile_nc = __file__.replace('.py', '.nc') ofile_csv = __file__.replace('.py', '.csv') if os.path.exists(ofile_nc): da = xr.open_dataarray(ofile_nc) print('[loaded]:', ofile_nc) else: ifile = '../data_Ts_AM4urban_wasteCool_0urban_amip_5ens_1870-2020.nc' print('loading...') da = xr.open_dataarray(ifile).pipe(sel_region).load().sel(time=slice('1870', '2014')) #more ens ifile = './data_Ts_AM4urban_wasteCool_0urban_amip_new5ens_1870-2014.nc' da_more = xr.open_dataarray(ifile).pipe(sel_region).load() da = xr.concat([da, da_more], dim='en') print('calculating...') #da = da.geo.fldmean().groupby('time.year').max('time') da = da.geo.fldmean().groupby('time.year').mean('time') if da.max() > 200: da = da - 273.15 #units K -> C da.attrs['units'] = 'degC' print('saving...') da.to_dataset(name=daname_new).to_netcdf(ofile_nc) print('[saved]:', ofile_nc) da.rename(daname_new).transpose('year', 'en').to_pandas().to_csv(ofile_csv) print('[saved]:', ofile_csv) if __name__ == '__main__': from wyconfig import * #my plot settings da.plot(hue='en') #savefig if 'savefig' in sys.argv: figname = __file__.replace('.py', f'.png') wysavefig(figname) tt.check(f'**Done**') plt.show()