import cartopy.crs as ccrs import cartopy.feature as cfeature import matplotlib.pyplot as plt import metpy.calc from metpy.units import units from netCDF4 import num2date import numpy as np import xarray as xr import pickle ############################################22sept################################# data=xr.open_dataset('other/ap2pl_input1.nc') data=data.sel(plev=85000) data = data.metpy.parse_cf() data.QV.attrs['units'] = 'kg/kg' data['QV']=data['QV']/1000 data['air_pressure'] = data['air_pressure']/100 data.air_pressure.attrs['units'] = 'hPa' dewpoint=metpy.calc.dewpoint_from_specific_humidity(data['air_pressure'], data['T'], data['QV']) ap2pl_thetae=metpy.calc.equivalent_potential_temperature(data['air_pressure'], data['T'], dewpoint) ap2pl_thetae=np.array(ap2pl_thetae) with open("ap2pl_thetae22.pkl","wb") as f: pickle.dump(ap2pl_thetae,f) ###################################23sept############################################## data=xr.open_dataset('other/ap2pl_input2.nc') data=data.sel(plev=85000) data = data.metpy.parse_cf() data.QV.attrs['units'] = 'kg/kg' data['QV']=data['QV']/1000 data['air_pressure'] = data['air_pressure']/100 data.air_pressure.attrs['units'] = 'hPa' dewpoint=metpy.calc.dewpoint_from_specific_humidity(data['air_pressure'], data['T'], data['QV']) ap2pl_thetae=metpy.calc.equivalent_potential_temperature(data['air_pressure'], data['T'], dewpoint) ap2pl_thetae=np.array(ap2pl_thetae) with open("ap2pl_thetae23.pkl","wb") as f: pickle.dump(ap2pl_thetae,f) ####################################24sept############################################### data=xr.open_dataset('other/ap2pl_input3.nc') data=data.sel(plev=85000) data = data.metpy.parse_cf() data.QV.attrs['units'] = 'kg/kg' data['QV']=data['QV']/1000 data['air_pressure'] = data['air_pressure']/100 data.air_pressure.attrs['units'] = 'hPa' dewpoint=metpy.calc.dewpoint_from_specific_humidity(data['air_pressure'], data['T'], data['QV']) ap2pl_thetae=metpy.calc.equivalent_potential_temperature(data['air_pressure'], data['T'], dewpoint) ap2pl_thetae=np.array(ap2pl_thetae) with open("ap2pl_thetae24.pkl","wb") as f: pickle.dump(ap2pl_thetae,f)