# 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))