From f67f19b87c317e82f65adb0c4ea926263fff19be Mon Sep 17 00:00:00 2001
From: Le Roux Erwan <erwan.le-roux@irstea.fr>
Date: Mon, 8 Feb 2021 18:35:20 +0100
Subject: [PATCH] [projections] improve comparison on the quantile period
---
.../main_comparison_on_quantile_period.py | 95 ++++++++++++-------
1 file changed, 59 insertions(+), 36 deletions(-)
diff --git a/projects/projected_snowfall/comparison_with_scm/main_comparison_on_quantile_period.py b/projects/projected_snowfall/comparison_with_scm/main_comparison_on_quantile_period.py
index d3259716..33af02fa 100644
--- a/projects/projected_snowfall/comparison_with_scm/main_comparison_on_quantile_period.py
+++ b/projects/projected_snowfall/comparison_with_scm/main_comparison_on_quantile_period.py
@@ -2,10 +2,12 @@ import numpy as np
import matplotlib
from extreme_data.meteo_france_data.adamont_data.adamont.adamont_snowfall import AdamontSnowfall
+from extreme_data.meteo_france_data.adamont_data.adamont_gcm_rcm_couples import \
+ get_year_min_and_year_max_used_to_compute_quantile
from extreme_data.meteo_france_data.adamont_data.adamont_scenario import AdamontScenario, gcm_rcm_couple_to_color, \
- gcm_rcm_couple_to_str
+ gcm_rcm_couple_to_str, load_gcm_rcm_couples
+from extreme_data.meteo_france_data.scm_models_data.safran.safran import SafranSnowfall1Day
from extreme_data.meteo_france_data.scm_models_data.safran.safran_max_snowf import SafranSnowfall2020
-from extreme_data.meteo_france_data.adamont_data.get_list_gcm_rcm_couples_adamont_v2 import get_year_min_and_year_max_used_to_compute_quantile
matplotlib.use('Agg')
@@ -38,43 +40,64 @@ def compute_bias_and_display_it(ax,
def main_comparaison_plot():
- altitudes = [600, 900, 1200, 1500, 1800, 2100, 2400, 2700, 3000, 3300, 3600]
- ax = plt.gca()
- gcm_rcm_couples = []
+ altitudes = [600, 900, 1200, 1500, 1800, 2100, 2400, 2700, 3000, 3300, 3600][:]
+ for adamont_version in [1, 2]:
+ ax = plt.gca()
+ gcm_rcm_couples = load_gcm_rcm_couples(adamont_scenario=AdamontScenario.histo, adamont_version=adamont_version)
- bias_in_the_mean = []
- for gcm_rcm_couple in gcm_rcm_couples:
- gcm, rcm = gcm_rcm_couple
- years_reanalysis, years_model = get_year_min_and_year_max_used_to_compute_quantile(rcm)
- reanalysis_altitude_studies = AltitudesStudies(study_class=SafranSnowfall2020,
- altitudes=altitudes,
- year_min=years_reanalysis[0],
- year_max=years_reanalysis[1])
- adamont_altitude_studies = AltitudesStudies(study_class=AdamontSnowfall,
- altitudes=altitudes,
- year_min=years_model[0],
- year_max=years_model[1],
- scenario=AdamontScenario.histo,
- gcm_rcm_couple=gcm_rcm_couple)
- bias_in_the_mean.extend(compute_bias_and_display_it(ax, reanalysis_altitude_studies,
- adamont_altitude_studies, gcm_rcm_couple))
+ study_class = SafranSnowfall2020 if adamont_version == 2 else SafranSnowfall1Day
+ comparaison_study_class = 'SAFRAN 2020' if adamont_version == 2 else 'SAFRAN 2019'
- bias_in_the_mean = np.array(bias_in_the_mean)
- min_bias, median_bias, max_bias = [f(bias_in_the_mean, axis=0) for f in [np.min, np.median, np.max]]
+ # Faster to load once the two cases
+ reanalysis_altitude_studies_1981 = AltitudesStudies(study_class=study_class,
+ altitudes=altitudes,
+ year_min=1981,
+ year_max=2011)
+ reanalysis_altitude_studies_1988 = AltitudesStudies(study_class=study_class,
+ altitudes=altitudes,
+ year_min=1988,
+ year_max=2011)
+ bias_in_the_mean = []
+ for gcm_rcm_couple in gcm_rcm_couples:
+ print(gcm_rcm_couple)
+ gcm, rcm = gcm_rcm_couple
+ years_reanalysis, years_model = get_year_min_and_year_max_used_to_compute_quantile(gcm)
+ assert years_reanalysis[0] in [1981, 1988]
+ if years_reanalysis[0] == 1981:
+ reanalysis_altitude_studies = reanalysis_altitude_studies_1981
+ else:
+ reanalysis_altitude_studies = reanalysis_altitude_studies_1988
+ adamont_altitude_studies = AltitudesStudies(study_class=AdamontSnowfall,
+ altitudes=altitudes,
+ year_min=years_model[0],
+ year_max=years_model[1],
+ scenario=AdamontScenario.histo,
+ gcm_rcm_couple=gcm_rcm_couple,
+ adamont_version=adamont_version)
+ bias_in_the_mean.append(compute_bias_and_display_it(ax, reanalysis_altitude_studies,
+ adamont_altitude_studies, gcm_rcm_couple))
- # Plot the range for the bias, and the median
- ax.yaxis.set_ticks(altitudes)
- color = 'k'
- ax.plot(median_bias, altitudes, label='Median bias', color=color)
- ax.fill_betweenx(altitudes, min_bias, max_bias, label='Range for the bias', alpha=0.2, color=color)
- ax.vlines(0, ymin=altitudes[0], ymax=altitudes[-1], color='k')
- study_str = STUDY_CLASS_TO_ABBREVIATION[type(reanalysis_altitude_studies.study)]
- plot_name = 'Bias for {}\n' \
- '(on the period used for the quantile correction)'.format(study_str)
- ax.set_ylim(top=altitudes[-1] + 500)
- ax.legend()
- reanalysis_altitude_studies.show_or_save_to_file(plot_name=plot_name)
- plt.close()
+ bias_in_the_mean = np.array(bias_in_the_mean)
+ min_bias, median_bias, max_bias = [f(bias_in_the_mean, axis=0) for f in [np.min, np.median, np.max]]
+
+ # Plot the range for the bias, and the median
+ ax.yaxis.set_ticks(altitudes)
+ color = 'k'
+ ax.plot(median_bias, altitudes, label='Median bias', color=color, linewidth=4)
+ # ax.fill_betweenx(altitudes, min_bias, max_bias, label='Range for the bias', alpha=0.2, color='whitesmoke')
+ ax.vlines(0, ymin=altitudes[0], ymax=altitudes[-1], color='k', linestyles='dashed')
+ study_str = STUDY_CLASS_TO_ABBREVIATION[type(reanalysis_altitude_studies.study)]
+ plot_name = 'Bias for annual maxima of {}'.format(study_str)
+ ax.set_ylim(top=altitudes[-1] + 1300)
+ study = adamont_altitude_studies.study
+ ax.legend(ncol=3, prop={'size': 7})
+ ax.set_ylabel('Altitude (m)', fontsize=10)
+ ax.set_xlabel('Bias in the mean annual maxima of {} for ADAMONT v{} members\n'
+ ' against {} on the quantile mapping period ({})'.format(study_str, adamont_version,
+ comparaison_study_class,
+ study.variable_unit), fontsize=10)
+ reanalysis_altitude_studies.show_or_save_to_file(plot_name=plot_name, no_title=True)
+ plt.close()
if __name__ == '__main__':
--
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