tos_data,
map_type='regress')
reg_coeff_IOD, pvals_IOD = regress_map.regress_map(IOD,
tos_data,
map_type='regress')
reg_coeff_IOBM, pvals_IOBM = regress_map.regress_map(
IOBM, tos_data, map_type='regress')
reg_coeff_IOBM2, pvals_IOBM2 = regress_map.regress_map(
IOBM2, tos_data, map_type='regress')
reg_coeff_NINO34, pvals_NINO34 = regress_map.regress_map(
NINO34, tos_data, map_type='regress')
# save
new_file_name = saving_dir + '/SST_indices_' + model_name + '_' + id + '.nc'
description = 'Various indices of SSTs including the PDO index calculated as the first principal component time series of monthly 20N-70N SST with seasonal cycle removed, Interdecadal Pacific Oscillation, Indian Ocean Basin Mode, Indian Ocean Dipole and Nino 3.4 index. '
save = save_file(new_file_name, description)
# add dimension variables
save.add_dimension(lats, 'lats')
save.add_dimension(lons, 'lons')
save.add_times(times, calendar, t_units, time_name='times')
# add variables
save.add_variable(PDO, 'PDO', ('times', ))
save.add_variable(reg_coeff_PDO, 'reg_coeff_PDO', (
'lats',
'lons',
))
save.add_variable(pvals_PDO, 'pvals_PDO', (
'lats',
'lons',
))
save.add_variable(IOD, 'IOD', ('times', ))
calendar_SST,
t_units_SST,
N,
season=season)
NINO34_object = prep_index_regress_save('NINO34',
nc_SST,
times_SST,
calendar_SST,
t_units_SST,
N,
season=season)
# save file object
f = saving_dir + '/SST_index_circulation_regression_' + model_name + '_' + season + '.nc'
description = '' + model_name
save = save_file(f, description)
# add dimensions
save.add_dimension(lats_psl, 'lats')
save.add_dimension(lons_psl, 'lons')
save.add_times(years[halfN:][::-1][halfN - 1:][::-1],
calendar_psl,
t_units_psl,
time_name='running_mean_years')
# regression on SST indices and save
PDO_object.regress_variable(psl_rm, save, 'regress_coeff_PDO_psl',
'pval_PDO_psl')
IOD_object.regress_variable(psl_rm, save, 'regress_coeff_IOD_psl',
'pval_IOD_psl')
IPO_object.regress_variable(psl_rm, save, 'regress_coeff_IPO_psl',