# Loop through each ssp run being considered
for ssp_option in range(0, ssp_options_length):
ssp = ssp_options[ssp_option] # selecting the ssp scenario
# for loop for each cmip6 model
for model_i in range(0, n_models):
model = cmip6_models[model_i] # seleting the models
print(min_temperature, ssp, model)
#%%
# finding spatial profile for future temperature
# time averaged, area averaged historical/present day temperature
tas_preindustrial_cube = combine_netCDF_cmip6('/home/rmv203/cmip6_data/tas_Amon_'+model+'_historical*', model)
tas_preindustrial_cube = open_netCDF(tas_preindustrial_cube)
tas_preindustrial_cube = select_time(tas_preindustrial_cube, 1995, 2005)
tas_preindustrial_cube = time_average(tas_preindustrial_cube)
tas_preindustrial_cube = area_average(tas_preindustrial_cube, region_global)
tas_preindustrial_data = tas_preindustrial_cube.data # time averaged, area averaged historical temperature
# cube to find future temperature change
tas_cube = combine_netCDF_cmip6('/home/rmv203/cmip6_historical_'+ssp+'/tas_Amon_'+model+'_*', model)
tas_cube = open_netCDF(tas_cube)
tas_test_cube = annual_average(tas_cube)
# defining the time variable for years
tas_test_years = tas_test_cube.coord('year').points
tas_test_cube = area_average(tas_test_cube, region_global)
tas_test_data = tas_test_cube.data
# Loop through each ssp run being considered
for ssp_option in range(0, ssp_options_length):
ssp = ssp_options[ssp_option] # selecting the ssp scenario
# for loop for each CMIP5 model
for model_i in range(0, n_models):
model = cmip6_models[model_i] # seleting the models
print(ssp, model)
#%% modelled historical
# Soil Carbon (cSoil)
cSoil_historical_cube_new = combine_netCDF_cmip6('/home/rmv203/cmip6_data/cSoil_Emon_'+model+'_historical*', model)
cSoil_historical_cube_new = open_netCDF(cSoil_historical_cube_new)
# Near Surface Air Temperature (tas)
tas_historical_cube = combine_netCDF_cmip6('/home/rmv203/cmip6_data/tas_Amon_'+model+'_historical*', model)
tas_historical_cube = open_netCDF(tas_historical_cube)
# Select historical time period
cSoil_historical_cube_new = select_time(cSoil_historical_cube_new, lower_historical, upper_historical)
tas_historical_cube = select_time(tas_historical_cube, lower_historical, upper_historical)
# Time average
cSoil_historical_time_av_cube_new = time_average(cSoil_historical_cube_new)
tas_historical_cube = time_average(tas_historical_cube)
tas_historical_data = tas_historical_cube.data
# Converting from cubes to numpy_arrays
cSoil_historical_time_av_data_new = cSoil_historical_time_av_cube_new.data
historical_modelled_cSoil_new = cSoil_historical_time_av_data_new.copy()