def meanProfile(basedir, acronym, f, startindx, endindx, fileprefix):
# How many vertical levels depends on which set we look at
if suffix == '_PL2':
c = 120
elif suffix == '_PL':
c = 18
H = np.zeros((24,2,c))
for i in np.arange(startindx,endindx):
print(i)
prefix = file_prefix(i)
flx = xr.open_dataset(basedir + fileprefix + '_icon_tropic_' + prefix + str(i) + suffix + '.nc')
clch = xr.open_dataset(basedir + 'CLCONV_2D_icon_tropic_' + prefix + str(i) + '.nc').clch.isel(time=0,lev=0)
# The factor of -1 is because pressure decreases upward
temp = -1.*(flx.lwflxall.isel(time=0)-flx.lwflxclr.isel(time=0)).where(clch > f)
temp = temp.assign_coords(plev_2=temp.plev_2.values)
temp = temp.differentiate('plev_2')
# Factor of 86400 to convert K s-1 to K day-1.
H[i-startindx,0] = g/cp*86400*temp.mean(dim={'ncells'})
temp = -1.*(flx.swflxall.isel(time=0)-flx.swflxclr.isel(time=0)).where(clch > f)
temp = temp.assign_coords(plev_2=temp.plev_2.values)
temp = temp.differentiate('plev_2')
H[i-startindx,1] = g/cp*86400*temp.mean(dim={'ncells'})
print('Saving mean heating rates from ' + basedir + '...')
np.save('../output/H_' + acronym + suffix + '.npy',H)
return H
def meanProfile(basedir, acronym, f, startindx, endindx, fileprefix):
# How many vertical levels depends on which set we look at
if suffix == '_PL2':
c = 120
elif suffix == '_PL':
c = 18
QG = np.zeros((24,c))
for i in np.arange(startindx,endindx):
print(i)
prefix = file_prefix(i)
flx = xr.open_dataset(basedir + fileprefix + '_icon_tropic_' + prefix + str(i) + suffix + '.nc')
clch = xr.open_dataset(basedir + 'CLCONV_2D_icon_tropic_' + prefix + str(i) + '.nc').clch.isel(time=0,lev=0)
QG[i-startindx] = flx.qg.isel(time=0).where(clch > f).mean(dim={'ncells'})
print('Saving hourly mean profiles from ' + basedir + '...')
np.save('../output/QG_' + acronym + suffix + '.npy',QG)
return QG
def meanProfile(basedir, acronym, f, startindx, endindx, fileprefix):
# How many vertical levels depends on which set we look at
if suffix == '_PL2':
c = 120
elif suffix == '_PL':
c = 18
WT = np.zeros((2, 24, c))
for i in np.arange(startindx, endindx):
print(i)
prefix = file_prefix(i)
w = xr.open_dataset(basedir + fileprefix + '_icon_tropic_' + prefix +
str(i) + suffix + '.nc')
clch = xr.open_dataset(basedir + 'CLCONV_2D_icon_tropic_' + prefix +
str(i) + '.nc').clch.isel(time=0, lev=0)
WT[0, i - startindx] = w.omega.isel(time=0).where(clch > f).mean(
dim={'ncells'})
WT[1, i - startindx] = w.temp.isel(time=0).where(clch > f).mean(
dim={'ncells'})
print('Saving mean pressure velocity and temperature from ' + basedir +
'...')
np.save('../output/WT_' + acronym + suffix + '.npy', WT)
return WT