lon1, lon2 = 40, 100
lat1, lat2 = -15, 35
varlist = ['T']
pmin, pmax = 200e2, 600e2
years = range(1979, 2015)
months = [4, 5, 6, 7, 8, 9]
g = atm.constants.g.values
nperday = 8
subset_dict = {'lon' : (lon1, lon2), 'lat' : (lat1, lat2)}
for year in years:
for mon in months:
dayvals = atm.season_days(atm.month_str(mon), atm.isleap(year))
T = merra.read_daily(varlist, year, mon, subset_dict=subset_dict)
# Daily means of 3-hourly data
T = atm.daily_from_subdaily(T, nperday, dayvals=dayvals)
# Vertical integral
Tbar = atm.int_pres(T, pmin=pmin, pmax=pmax)
Tbar = Tbar * g / (pmax - pmin)
Tbar.name='Tbar'
Tbar.attrs['long_name'] = 'Vertical mean atmospheric temperature'
Tbar.attrs['pmin'] = pmin
Tbar.attrs['pmax'] = pmax
# Save to file
atm.save_nc(savefile(year, mon, pmin, pmax), T, Tbar)
lat1, lat2 = -20, 30
varlist = ['u', 'v', 'q']
pmin = 300e2
years = range(1979, 2015)
#months = [5, 6, 7, 8]
months = [4]
subset_dict = {'lon' : (lon1, lon2), 'lat' : (lat1, lat2)}
for year in years:
for mon in months:
dayvals = atm.season_days(atm.month_str(mon), atm.isleap(year))
ds = merra.read_daily(varlist, year, mon, subset_dict=subset_dict)
uq = ds['U'] * ds['QV']
vq = ds['V'] * ds['QV']
# Daily means of 3-hourly data
nperday = 8
uq = atm.daily_from_subdaily(uq, nperday, dayvals=dayvals)
vq = atm.daily_from_subdaily(vq, nperday, dayvals=dayvals)
# Vertical integral
uq_int = atm.int_pres(uq, pmin=pmin)
vq_int = atm.int_pres(vq, pmin=pmin)
uq_int.name='uq_int'
uq_int.attrs['pmin'] = pmin
vq_int.name='vq_int'
vq_int.attrs['pmin'] = pmin
# Save to file
atm.save_nc(savefile(year, mon), uq_int, vq_int)