def main():
global settings
set_settings()
steric_ensembles = np.load(settings['fn_steric_ensembles'],
allow_pickle=True).all()
grd_ensembles = np.load(settings['fn_grd_ensembles'],
allow_pickle=True).all()
budget_total = steric_ensembles[
'global'][:settings['num_ens'], :] + grd_ensembles['global'][
'total'][:settings['num_ens'], :]
budget_notws = steric_ensembles[
'global'][:settings['num_ens'], :] + grd_ensembles['global'][
'total'][:settings['num_ens'], :] - grd_ensembles['global'][
'tws'][:settings['num_ens'], :]
mass_frac = ['glac', 'GrIS', 'AIS', 'tws', 'total']
# Steric fractions
frac_steric = estimate_fraction_from_ensemble(
steric_ensembles['global'][:settings['num_ens'], :], budget_total)
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'frac_steric',
settings['years'], frac_steric)
frac_steric_notws = estimate_fraction_from_ensemble(
steric_ensembles['global'][:settings['num_ens'], :], budget_notws)
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'frac_steric_notws',
settings['years'], frac_steric_notws)
# Mass fractions
for process in mass_frac:
frac_proc = estimate_fraction_from_ensemble(
grd_ensembles['global'][process][:settings['num_ens'], :],
budget_total)
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'frac_' + process,
settings['years'], frac_proc)
if process == 'total':
frac_proc_notws = estimate_fraction_from_ensemble(
grd_ensembles['global'][process][:settings['num_ens'], :] -
grd_ensembles['global']['tws'][:settings['num_ens'], :],
budget_notws)
else:
frac_proc_notws = estimate_fraction_from_ensemble(
grd_ensembles['global'][process][:settings['num_ens'], :],
budget_notws)
gentools.gmt_save_tseries_ci(settings['dir_gmt'],
'frac_' + process + '_notws',
settings['years'], frac_proc_notws)
return
def main():
settings = {}
settings['dir_data'] = os.getenv('HOME') + '/Data/'
settings['dir_budget'] = settings['dir_data'] + 'Budget_20c/'
settings['fn_stats_ice6g'] = settings[
'dir_budget'] + 'results/stats_basin_global_ice6g.npy'
settings['fn_stats_caron'] = settings[
'dir_budget'] + 'results/stats_basin_global.npy'
settings['dir_gmt'] = os.getenv(
'HOME') + '/Scripts/GMT/Papers/Budget_20c/comp_ICE6G/'
settings['years'] = np.arange(1900, 2019)
stats_caron = np.load(settings['fn_stats_caron'], allow_pickle=True).all()
stats_ice6g = np.load(settings['fn_stats_ice6g'], allow_pickle=True).all()
# Save basin data
for basin in range(6):
gentools.gmt_save_tseries_ci(
settings['dir_gmt'], 'obs_caron_' + str(basin) + '_tseries',
settings['years'], stats_caron['basin'][basin]['obs']['tseries'])
gentools.gmt_save_tseries_ci(
settings['dir_gmt'], 'bdg_caron_' + str(basin) + '_tseries',
settings['years'],
stats_caron['basin'][basin]['budget']['tseries'])
gentools.gmt_save_tseries_ci(
settings['dir_gmt'], 'gia_caron_' + str(basin) + '_tseries',
settings['years'], stats_caron['basin'][basin]['gia']['tseries'])
gentools.gmt_save_tseries(
settings['dir_gmt'], 'obs_ice6g_' + str(basin) + '_tseries',
settings['years'],
stats_ice6g['basin'][basin]['obs']['tseries'][:, 1])
gentools.gmt_save_tseries(
settings['dir_gmt'], 'bdg_ice6g_' + str(basin) + '_tseries',
settings['years'],
stats_ice6g['basin'][basin]['budget']['tseries'][:, 1])
gentools.gmt_save_tseries(
settings['dir_gmt'], 'gia_ice6g_' + str(basin) + '_tseries',
settings['years'],
stats_ice6g['basin'][basin]['gia']['tseries'][:, 1])
# Global
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'obs_caron_glb_tseries',
settings['years'],
stats_caron['global']['obs']['tseries'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'bdg_caron_glb_tseries',
settings['years'],
stats_caron['global']['budget']['tseries'])
gentools.gmt_save_tseries(settings['dir_gmt'], 'obs_ice6g_glb_tseries',
settings['years'],
stats_ice6g['global']['obs']['tseries'][:, 1])
gentools.gmt_save_tseries(settings['dir_gmt'], 'bdg_ice6g_glb_tseries',
settings['years'],
stats_ice6g['global']['budget']['tseries'][:, 1])
# Plot global
plt.figure(figsize=(5, 4))
plt.fill_between(settings['years'],
stats_caron['global']['obs']['tseries'][:, 0],
stats_caron['global']['obs']['tseries'][:, 2],
color='C0',
alpha=0.4)
plt.fill_between(settings['years'],
stats_caron['global']['budget']['tseries'][:, 0],
stats_caron['global']['budget']['tseries'][:, 2],
color='C1',
alpha=0.4)
plt.plot(settings['years'],
stats_caron['global']['obs']['tseries'][:, 1],
'C0',
linewidth=2,
label='Observed sea level (This study)')
plt.plot(settings['years'],
stats_ice6g['global']['obs']['tseries'][:, 1],
'black',
linestyle='--',
linewidth=2,
label='Observed sea level (ICE6G_D)')
plt.plot(settings['years'],
stats_caron['global']['budget']['tseries'][:, 1],
'C1',
linewidth=2,
label='Sum of processes (This study)')
plt.plot(settings['years'],
stats_ice6g['global']['budget']['tseries'][:, 1],
'C3',
linestyle='--',
linewidth=2,
label='Sum of processes (ICE6G_D)')
plt.xlim([1900, 2018])
plt.ylim([-220, 50])
plt.ylabel('Height (mm)', fontsize=9)
plt.legend(fontsize=9)
plt.xticks(fontsize=9)
plt.yticks(fontsize=9)
plt.title('Global', fontsize=9)
plt.grid()
plt.tight_layout()
plt.savefig('Compare_ICE6G_D_global.png')
# Plot basin
region_names = [
'Subpolar North Atlantic', 'Indian Ocean-South Pacific',
'Subtropical North Atlantic', 'East Pacific', 'South Atlantic',
'Northwest Pacific'
]
plt.figure(figsize=(8, 8))
for basin in range(6):
plt.subplot(3, 2, basin + 1)
plt.fill_between(settings['years'],
stats_caron['basin'][basin]['obs']['tseries'][:, 0],
stats_caron['basin'][basin]['obs']['tseries'][:, 2],
color='C0',
alpha=0.4)
plt.fill_between(settings['years'],
stats_caron['basin'][basin]['budget']['tseries'][:,
0],
stats_caron['basin'][basin]['budget']['tseries'][:,
2],
color='C1',
alpha=0.4)
plt.plot(settings['years'],
stats_caron['basin'][basin]['obs']['tseries'][:, 1],
'C0',
linewidth=2,
label='Observed sea level (This study)')
plt.plot(settings['years'],
stats_ice6g['basin'][basin]['obs']['tseries'][:, 1],
'black',
linestyle='--',
linewidth=2,
label='Observed sea level (ICE6G_D)')
plt.plot(settings['years'],
stats_caron['basin'][basin]['budget']['tseries'][:, 1],
'C1',
linewidth=2,
label='Sum of processes (This study)')
plt.plot(settings['years'],
stats_ice6g['basin'][basin]['budget']['tseries'][:, 1],
'C3',
linestyle='--',
linewidth=2,
label='Sum of processes (ICE6G_D)')
plt.xlim([1900, 2018])
plt.ylim([-400, 100])
plt.ylabel('Height (mm)', fontsize=9)
if basin == 0: plt.legend(fontsize=9)
plt.xticks(fontsize=9)
plt.yticks(fontsize=9)
plt.title(region_names[basin], fontsize=9)
plt.grid()
plt.tight_layout()
plt.savefig('Compare_ICE6G_D_basin.png')
return
def save_tseries(stats, settings):
# Global time series of mean and uncertainty
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'obs_glb_tseries',
settings['years'],
stats['global']['obs']['tseries'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'alt_glb_tseries',
settings['years'],
stats['global']['altimetry']['tseries'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'steric_glb_tseries',
settings['years'],
stats['global']['steric']['tseries'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'grd_glb_tseries',
settings['years'],
stats['global']['grd_total']['tseries'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'glac_glb_tseries',
settings['years'],
stats['global']['grd_glac']['tseries'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'GrIS_glb_tseries',
settings['years'],
stats['global']['grd_GrIS']['tseries'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'AIS_glb_tseries',
settings['years'],
stats['global']['grd_AIS']['tseries'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'tws_glb_tseries',
settings['years'],
stats['global']['grd_tws']['tseries'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'dam_glb_tseries',
settings['years'],
stats['global']['grd_tws_dam']['tseries'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'gwd_glb_tseries',
settings['years'],
stats['global']['grd_tws_gwd']['tseries'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'nat_glb_tseries',
settings['years'],
stats['global']['grd_tws_natural']['tseries'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'budget_tseries',
settings['years'],
stats['global']['budget']['tseries'])
return
def save_sliding_trends(stats, settings):
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'obs_glb_sliding',
settings['years'],
stats['global']['obs']['sliding_trend'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'steric_glb_sliding',
settings['years'],
stats['global']['steric']['sliding_trend'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'grd_glb_sliding',
settings['years'],
stats['global']['grd_total']['sliding_trend'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'glac_glb_sliding',
settings['years'],
stats['global']['grd_glac']['sliding_trend'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'GrIS_glb_sliding',
settings['years'],
stats['global']['grd_GrIS']['sliding_trend'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'AIS_glb_sliding',
settings['years'],
stats['global']['grd_AIS']['sliding_trend'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'tws_glb_sliding',
settings['years'],
stats['global']['grd_tws']['sliding_trend'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'], 'budget_sliding',
settings['years'],
stats['global']['budget']['sliding_trend'])
return
def save_tseries(stats, settings):
# Global time series of mean and uncertainty
for basin in range(6):
gentools.gmt_save_tseries_ci(settings['dir_gmt'],
'obs_' + str(basin) + '_tseries',
settings['years'],
stats['basin'][basin]['obs']['tseries'])
gentools.gmt_save_tseries_ci(
settings['dir_gmt'], 'alt_' + str(basin) + '_tseries',
settings['years'], stats['basin'][basin]['altimetry']['tseries'])
gentools.gmt_save_tseries_ci(
settings['dir_gmt'], 'steric_' + str(basin) + '_tseries',
settings['years'], stats['basin'][basin]['steric']['tseries'])
gentools.gmt_save_tseries_ci(
settings['dir_gmt'], 'grd_' + str(basin) + '_tseries',
settings['years'], stats['basin'][basin]['grd_total']['tseries'])
gentools.gmt_save_tseries_ci(settings['dir_gmt'],
'gia_' + str(basin) + '_tseries',
settings['years'],
stats['basin'][basin]['gia']['tseries'])
gentools.gmt_save_tseries_ci(
settings['dir_gmt'], 'budget_' + str(basin) + '_tseries',
settings['years'], stats['basin'][basin]['budget']['tseries'])
return