# 2) difference of averages or average of 400 differences?
# control
print "Calculating climatology for CONTROL"
members_control = []
for i in range(1, 21):
if i in range(1, 4):
ncpath = "/dx03/ab4283/GLENS/control/" + var + "/zonal_mean_camelot/merged/b.e15.B5505C5WCCML45BGCR.f09_g16.control.0" + str(
i).zfill(2) + ".cam.h0zm." + var + ".201001-209912.nc"
else:
ncpath = "/dx03/ab4283/GLENS/control/" + var + "/zonal_mean_camelot/b.e15.B5505C5WCCML45BGCR.f09_g16.control.0" + str(
i).zfill(2) + ".cam.h0zm." + var + ".201001-203012.nc"
zmzw_inst = zonal_wind.zmzw(ncpath, time0=2010, tim1=2010, tim2=2030)
clim_lat_hgt = zmzw_inst.climatology_polar_hgt_mon()
members_control.append(clim_lat_hgt)
ensmean_control, ensstd_control, nens_control = ensemble_functions.calc_ensemble_mean(
members_control)
# RCP8.5
# only 3 members here!
print "Calculating climatology for RCP8.5"
members_rcp85 = []
for i in range(1, 4):
ncpath = "/dx03/ab4283/GLENS/control/" + var + "/zonal_mean_camelot/merged/b.e15.B5505C5WCCML45BGCR.f09_g16.control.0" + str(
i).zfill(2) + ".cam.h0zm." + var + ".201001-209912.nc"
zmzw_inst = zonal_wind.zmzw(ncpath, time0=2010, tim1=2075, tim2=2095)
clim_lat_hgt = zmzw_inst.climatology_polar_hgt_mon()
members_rcp85.append(clim_lat_hgt)
ensmean_rcp85, ensstd_rcp85, nens_rcp85 = ensemble_functions.calc_ensemble_mean(
members_rcp85)
# feedback runs
members_rcp85.append(clim_lon_lat)
ensmean_rcp85, ensstd_rcp85 = ensemble_functions.stats(members_rcp85)
quit()
#********************************************************************************************************
# feedback runs
print("Calculating climatology for FEEDBACK")
members_feedback = []
for i in range(1, 22):
ncpath = glob.glob(
"/Volumes/CESM-GLENS/GLENS/b.e15.B5505C5WCCML45BGCR.f09_g16.feedback.0"
+ str(i).zfill(2) +
"/atm/proc/tseries/month_1/Combined/b.e15.B5505C5WCCML45BGCR.f09_g16.feedback.0"
+ str(i).zfill(2) + ".cam.h0." + var + ".202001-*.nc")[0]
Ts_inst = surface_temp.Ts(ncpath, time0=2020, tim1=2075, tim2=2095)
clim_lon_lat = Ts_inst.climatology_lon_lat(season)
members_feedback.append(clim_lon_lat)
print(np.array(members_feedback).shape)
np.save("nparrays/" + var + "_feedback_" + season, np.array(members_feedback))
ensmean_feedback, ensstd_feedback, nens_feedback = ensemble_functions.calc_ensemble_mean(
members_feedback)
# save dimensions
# get lat and hgt off one instance
#lat = (Ts_inst.dimdict)['lat']
#lon = (Ts_inst.dimdict)['lon']
#np.save("nparrays/GLENS_lat", np.array(lat))
#np.save("nparrays/GLENS_lon", np.array(lon))