{"id":"W3089736811","doi":"10.5194/egusphere-egu2020-11428","title":"Can assimilating snow monitoring information offset the adverse effects of precipitation data scarcity in hydrological modelling applications?","year":2020,"lang":"en","type":"article","venue":"","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Environmental science; Data assimilation; Snow; Precipitation; Snowpack; Climatology; Meteorology; Ensemble Kalman filter; Water cycle; Water scarcity; Climate change; Computer science; Kalman filter; Water resources; Geography; Geology; Extended Kalman filter","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002806555,0.0004132789,0.0005943907,0.0006231433,0.0005332362,0.002362675,0.001142444,0.001332398,0.002254413],"category_scores_gemma":[0.01380228,0.0003339365,0.0003994476,0.001284235,0.0008012609,0.006213217,0.001330711,0.0007650017,0.0007478911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001014131,"about_ca_system_score_gemma":0.002811125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05860194,"about_ca_topic_score_gemma":0.09152541,"domain_scores_codex":[0.9994567,0.0001784848,0.00005109897,0.0001224438,0.0001068268,0.00008437499],"domain_scores_gemma":[0.9972589,0.0008862898,0.000320902,0.0004533288,0.0009068565,0.0001737405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00051093,0.0002320928,0.1154777,0.0009474512,0.0004185444,0.0002458231,0.000570252,0.1246493,0.0158962,0.01475581,0.01867012,0.7076258],"study_design_scores_gemma":[0.0001849494,0.0002850662,0.1351795,0.000752906,0.0003344003,0.0001428412,0.002657916,0.694383,0.01613738,0.05542962,0.09429855,0.0002137429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6881627,0.01196443,0.1553186,0.08917273,0.002016743,0.0002574705,0.004571787,0.003444134,0.04509143],"genre_scores_gemma":[0.9636872,0.003133883,0.02855764,0.001171153,0.0003185459,0.00004088434,0.0008279147,0.0002048446,0.002057956],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05860194,"threshold_uncertainty_score":0.1165217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06279092247245599,"score_gpt":0.2423032180306908,"score_spread":0.1795122955582348,"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."}}