{"id":"W2129893852","doi":"10.5194/gmd-7-1451-2014","title":"Comparison of the ensemble Kalman filter and 4D-Var assimilation methods using a stratospheric tracer transport model","year":2014,"lang":"en","type":"article","venue":"Geoscientific model development","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Jet Propulsion Laboratory; National Aeronautics and Space Administration","keywords":"Microwave Limb Sounder; Data assimilation; Ensemble Kalman filter; Stratosphere; Kalman filter; Environmental science; Meteorology; TRACER; Assimilation (phonology); Observational error; Climatology; Statistics; Extended Kalman filter; Mathematics; Physics; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001037562,0.0001413694,0.0002321216,0.00004622318,0.0005479335,0.00005717741,0.0001831703,0.00007228032,0.0001801575],"category_scores_gemma":[0.00002019889,0.00009384019,0.00005007593,0.0002361515,0.0001695976,0.000100059,0.00001724222,0.0001051283,0.000003551906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007543948,"about_ca_system_score_gemma":0.0001461479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004799775,"about_ca_topic_score_gemma":0.0002044275,"domain_scores_codex":[0.9985123,0.0001019621,0.0004483592,0.0003463334,0.0003336393,0.0002574096],"domain_scores_gemma":[0.9993994,0.00007633242,0.0001432718,0.0002258915,0.00005411678,0.0001009405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008700214,0.00002576059,0.03526191,0.00001572283,0.000007187427,5.274304e-8,0.001237252,0.9459424,0.001644973,0.0003106627,0.00002124842,0.01552411],"study_design_scores_gemma":[0.0001203425,0.00001137902,0.09644575,0.000008389349,0.00001793915,4.070556e-7,0.0000307486,0.8977506,0.0006506826,0.004511754,0.0003315955,0.0001204717],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5308426,0.00003444618,0.4675072,0.00001988342,0.000105319,0.0001176956,0.00001246135,0.0000080385,0.001352299],"genre_scores_gemma":[0.7160692,7.173047e-7,0.2834635,0.0000821491,0.000005925629,0.000001099296,0.00002490903,0.000002490309,0.0003499451],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1852266,"threshold_uncertainty_score":0.4214316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1020410668971865,"score_gpt":0.3122573116337811,"score_spread":0.2102162447365946,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}