datadir = atm.homedir() + 'datastore/merra/daily/'
year = 2014
subset = '_40E-120E_90S-90N'
def get_var(datadir, varnm, subset, year):
filenm = '%smerra_%s%s_%d.nc' % (datadir, varnm, subset, year)
with xray.open_dataset(filenm) as ds:
var = ds[varnm].load()
return var
uq_int = get_var(datadir, 'UFLXQV', subset, year)
vq_int = get_var(datadir, 'VFLXQV', subset, year)
mfc = atm.moisture_flux_conv(uq_int, vq_int, already_int=True)
mfcbar = mfc.mean(dim='YDim').mean(dim='XDim')
# Test atm.gradient
a = atm.constants.radius_earth.values
latdim, londim = 1, 2
lat = atm.get_coord(uq_int, 'lat')
latrad = np.radians(lat)
latrad[abs(lat) > 89] = np.nan
coslat = xray.DataArray(np.cos(latrad), coords={'YDim': lat})
lon = atm.get_coord(uq_int, 'lon')
lonrad = np.radians(lon)
mfc_x = atm.gradient(uq_int, lonrad, londim) / (a * coslat)
mfc_y = atm.gradient(vq_int * coslat, latrad, latdim) / (a * coslat)
mfc_test = mfc_x + mfc_y
import matplotlib.pyplot as plt
import pandas as pd
import atmos as atm
import precipdat
import merra
# ----------------------------------------------------------------------
#version, years = 'merra', np.arange(1979, 2015)
version, years = 'merra2', np.arange(1980, 2016)
datadir = atm.homedir() + 'datastore/%s/daily/' % version
months = np.arange(1, 13)
subset = '_40E-120E_90S-90N'
def get_var(datadir, version, varnm, subset, year):
filenm = '%s%s_%s%s_%d.nc' % (datadir, version, varnm, subset, year)
with xray.open_dataset(filenm) as ds:
var = ds[varnm].load()
return var
for year in years:
print('Calculating MFC %d' % year)
uq_int = get_var(datadir, version, 'UFLXQV', subset, year)
vq_int = get_var(datadir, version, 'VFLXQV', subset, year)
mfc = atm.moisture_flux_conv(uq_int, vq_int, already_int=True)
mfc.attrs['long_name'] = mfc.name
mfc.name = 'MFC'
savefile = datadir + '%s_MFC%s_%d.nc' % (version, subset, year)
print('Saving MFC to ' + savefile)
atm.save_nc(savefile, mfc)
#monthstr='apr-sep_'
def datafile(datadir, year, mon):
filn = datadir + 'merra_vimt_%d%02d.nc' % (year, mon)
return filn
def savefile(datadir, varnm, year, monthstr, pmin):
filn = datadir + 'merra_%s_ps-%.0fmb_%s%d.nc'
filn = filn % (varnm, pmin/100, monthstr, year)
return filn
# Read daily data from each year and month and concatenate together
for y, year in enumerate(years):
files = [datafile(datadir, year, mon) for mon in months]
ds = atm.load_concat(files, concat_dim='day')
pmin = ds['uq_int'].attrs['pmin']
filn = savefile(datadir, 'vimt', year, monthstr, pmin)
print('Saving VIMT to ' + filn)
ds.to_netcdf(filn)
# Compute moisture flux convergence and save to files
print('Calculating MFC')
mfc = atm.moisture_flux_conv(ds['uq_int'], ds['vq_int'], already_int=True)
mfc.attrs['long_name'] = mfc.name
mfc.name = 'MFC'
for key in ds['uq_int'].attrs:
mfc.attrs[key] = ds['uq_int'].attrs[key]
filn = savefile(datadir, 'MFC', year, monthstr, pmin)
print('Saving MFC to ' + filn)
atm.save_nc(filn, mfc)
