def climatology_shgt_slat(self, selhgt, sellat, time_mean):
shgt = np.where(self.dimdict['hgt'] >= selhgt)[0][0]
slat = np.where(self.dimdict['lat'] >= sellat)[0][0]
# select variable at height and latitude
var = self.var[:, shgt, slat]
# climatological monthly mean
var_tsub, nsubyrs = basic_functions.time_subset(
var, self.time0, self.tim1, self.tim2)
var_seas = basic_functions.seasonal_mean(var_tsub, nsubyrs, time_mean)
var_clim_seas = var_seas.mean()
print var_clim_seas.shape
return var_clim_seas
def climatology_lon_lat(self, time_mean):
# seasonal mean then average over climatological time period
clim_var = np.zeros(
[len(self.dimdict['lat']),
len(self.dimdict['lon'])])
for ilat in range(len(self.dimdict['lat'])):
for ilon in range(len(self.dimdict['lon'])):
var_tsub, nsubyrs = basic_functions.time_subset(
self.var[:, ilat, ilon], self.time0, self.tim1, self.tim2)
var_seas = basic_functions.seasonal_mean(
var_tsub, nsubyrs, time_mean)
var_clim_seas = np.mean(var_seas, axis=0)
clim_var[ilat, ilon] = var_clim_seas
return clim_var
def climatology_polar_hgt_mon(self):
# polar cap mean (70-90N)
var_amean = np.zeros(
[len(self.dimdict['tim']),
len(self.dimdict['hgt'])])
for itim in range(len(self.dimdict['tim'])):
for ihgt in range(len(self.dimdict['hgt'])):
var_amean[itim, ihgt] = basic_functions.latitude_mean(
self.var[itim, ihgt, :], self.dimdict['lat'], 70, 90)
# climatological monthly mean
clim_var = np.zeros([12, len(self.dimdict['hgt'])])
for ihgt in range(len(self.dimdict['hgt'])):
var_tsub, nsubyrs = basic_functions.time_subset(
var_amean[:, ihgt], self.time0, self.tim1, self.tim2)
var_seas = basic_functions.seasonal_mean(var_tsub, nsubyrs,
'clim_monthly')
clim_var[:, ihgt] = var_seas
return clim_var