diff --git a/PE_CBL.py b/PE_CBL.py index 96a95492a52d36f7dec7d6d99cfbf2c53d1edf6f..7fd10112d570dfa8b69a0ddd5789c5a9a56087f3 100644 --- a/PE_CBL.py +++ b/PE_CBL.py @@ -41,7 +41,7 @@ if __name__ == '__main__': ######################################################################## # Manuscript figures - fig01 = False # CHECKED OK # Sensitivity to p + fig01 = True # CHECKED OK # Sensitivity to p fig02 = False # CHECKED OK # Successful PE experiment fig03 = False # CHECKED OK # Consistency checks fig04 = False # CHECKED OK # Experiments with varying weights @@ -49,14 +49,14 @@ if __name__ == '__main__': fig06 = False # CHECKED OK # Analysis increments in model error experiments fig07 = False # CHECKED OK # Experiment with error growth fig08 = False # CHECKED OK # Comparison successful vs unsuccessful PE - fig09 = False # CHECKED OK # Comparison EAKF vs LETKF - fig10 = True # CHECKED OK # DA diagnostics (profiles) for perfect-obs experiments + fig09 = False # CHECKED OK # Comparison EAKF vs LETKF + fig10 = False # CHECKED OK # DA diagnostics (profiles) for perfect-obs experiments # Other figures - opt01 = False # CHECKED OK # assimilation of a single observation - opt02 = False # CHECKED OK # assimilation of profiles at two times - opt03 = False # CHECKED OK # assimilation of real observations - opt04 = False # CHECKED OK # assimilation of real observations, different spinup times + opt01 = False # CHECKED OK # Assimilation of a single observation + opt02 = False # CHECKED OK # Assimilation of profiles at two times + opt03 = False # CHECKED OK # Assimilation of real observations + opt04 = False # CHECKED OK # Assimilation of real observations, different spinup times opt05 = False # CHECKED OK # Check impact of localization cutoff opt06 = False # CHECKED OK # Check impact of RTPS variance inflation factor for parameters opt07 = False # CHECKED OK # Check impact of RTPS variance inflation factor for state vector @@ -78,7 +78,7 @@ if __name__ == '__main__': maxtime = 21600 cbl_settings['maxtime'] = maxtime - # Panel a) deterministic run using default settings + # Panel c) deterministic run using default settings cbl_det = CBL(cbl_settings) cbl_det.initialize(1) cbl_det.run(output_full_history=True) @@ -93,18 +93,20 @@ if __name__ == '__main__': theta_profiles = [] for pfac in p_factors: cbl_settings['pfac'] = pfac + cbl_settings['do_parameter_estimation'] = False cbl_pf = CBL(cbl_settings) cbl_pf.initialize(1) cbl_pf.run() theta_profiles.append(cbl_pf.x[:cbl_pf.nz]) - # Panel c) spread induced by p + # Panel d) spread induced by p # Do a free ensemble run (ensemble size set expliclity) # Set size to 200 members with open(workdir+'/default_cbl.json', 'r') as fp: cbl_settings_free = json.load(fp) cbl_settings_free['maxtime'] = maxtime cbl_settings_free['perturb_ensemble_state'] = False + cbl_settings_free['do_parameter_estimation'] = False cbl_free = CBL(cbl_settings_free) cbl_free.initialize(200) cbl_free.run(output_full_history=True)