{"id":"https://openalex.org/W3171163466","doi":"https://doi.org/10.1109/mis.2021.3088543","title":"Robust Precipitation Bias Correction Through an Ordinal Distribution Autoencoder","display_name":"Robust Precipitation Bias Correction Through an Ordinal Distribution Autoencoder","publication_year":2021,"publication_date":"2021-06-11","ids":{"openalex":"https://openalex.org/W3171163466","doi":"https://doi.org/10.1109/mis.2021.3088543","mag":"3171163466"},"language":"en","primary_location":{"id":"doi:10.1109/mis.2021.3088543","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mis.2021.3088543","pdf_url":null,"source":{"id":"https://openalex.org/S114241109","display_name":"IEEE Intelligent Systems","issn_l":"1541-1672","issn":["1541-1672","1941-1294"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Intelligent Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://scholarsphere.psu.edu/resources/57569697-999e-4ffe-9469-6b5d11ef6b4c/downloads/19884","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006993334","display_name":"Youcheng Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youcheng Luo","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102026552","display_name":"Xiaoyang Xu","orcid":"https://orcid.org/0000-0003-1772-8631"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyang Xu","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-1772-8631","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100668124","display_name":"Yiqun Liu","orcid":"https://orcid.org/0000-0002-4398-5298"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiqun Liu","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-4398-5298","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070759471","display_name":"Hanqing Chao","orcid":"https://orcid.org/0000-0001-5973-2343"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanqing Chao","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-5973-2343","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029578993","display_name":"Hai Chu","orcid":"https://orcid.org/0000-0001-9055-6640"},"institutions":[{"id":"https://openalex.org/I4210131507","display_name":"Shanghai Meteorological Bureau","ror":"https://ror.org/03tbkt876","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210131507"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hai Chu","raw_affiliation_strings":["Shanghai Central Meteorological Observatory, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Central Meteorological Observatory, Shanghai, China","institution_ids":["https://openalex.org/I4210131507"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333549","display_name":"Lei Chen","orcid":"https://orcid.org/0000-0003-1409-8371"},"institutions":[{"id":"https://openalex.org/I4210131507","display_name":"Shanghai Meteorological Bureau","ror":"https://ror.org/03tbkt876","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210131507"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Chen","raw_affiliation_strings":["Shanghai Central Meteorological Observatory, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Central Meteorological Observatory, Shanghai, China","institution_ids":["https://openalex.org/I4210131507"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100696429","display_name":"Junping Zhang","orcid":"https://orcid.org/0000-0002-5924-3360"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junping Zhang","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-5924-3360","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035813695","display_name":"Leiming Ma","orcid":"https://orcid.org/0000-0003-0103-5830"},"institutions":[{"id":"https://openalex.org/I4210131507","display_name":"Shanghai Meteorological Bureau","ror":"https://ror.org/03tbkt876","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210131507"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leiming Ma","raw_affiliation_strings":["Shanghai Central Meteorological Observatory, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-0103-5830","affiliations":[{"raw_affiliation_string":"Shanghai Central Meteorological Observatory, Shanghai, China","institution_ids":["https://openalex.org/I4210131507"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100687159","display_name":"James Z. Wang","orcid":"https://orcid.org/0000-0003-4379-4173"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James Z. Wang","raw_affiliation_strings":["The Pennsylvania State University, University Park, PA, USA"],"raw_orcid":"https://orcid.org/0000-0003-4379-4173","affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4823,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.62486198,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"37","issue":"1","first_page":"60","last_page":"70"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11234","display_name":"Precipitation Measurement and Analysis","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11234","display_name":"Precipitation Measurement and Analysis","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10466","display_name":"Meteorological Phenomena and Simulations","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.8455816507339478},{"id":"https://openalex.org/keywords/numerical-weather-prediction","display_name":"Numerical weather prediction","score":0.6900634765625},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6494307518005371},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5524076819419861},{"id":"https://openalex.org/keywords/quantitative-precipitation-forecast","display_name":"Quantitative precipitation forecast","score":0.5434215068817139},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.526324450969696},{"id":"https://openalex.org/keywords/ordinal-optimization","display_name":"Ordinal optimization","score":0.5188523530960083},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4848116934299469},{"id":"https://openalex.org/keywords/precipitation","display_name":"Precipitation","score":0.4478326439857483},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.44611552357673645},{"id":"https://openalex.org/keywords/weather-forecasting","display_name":"Weather forecasting","score":0.42579197883605957},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3957290053367615},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38907015323638916},{"id":"https://openalex.org/keywords/ordinal-regression","display_name":"Ordinal regression","score":0.34507060050964355},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15056970715522766},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.0921277403831482}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8455816507339478},{"id":"https://openalex.org/C147947694","wikidata":"https://www.wikidata.org/wiki/Q837552","display_name":"Numerical weather prediction","level":2,"score":0.6900634765625},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6494307518005371},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5524076819419861},{"id":"https://openalex.org/C140178040","wikidata":"https://www.wikidata.org/wiki/Q18402512","display_name":"Quantitative precipitation forecast","level":3,"score":0.5434215068817139},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.526324450969696},{"id":"https://openalex.org/C81386100","wikidata":"https://www.wikidata.org/wiki/Q7100792","display_name":"Ordinal optimization","level":3,"score":0.5188523530960083},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4848116934299469},{"id":"https://openalex.org/C107054158","wikidata":"https://www.wikidata.org/wiki/Q25257","display_name":"Precipitation","level":2,"score":0.4478326439857483},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.44611552357673645},{"id":"https://openalex.org/C21001229","wikidata":"https://www.wikidata.org/wiki/Q182868","display_name":"Weather forecasting","level":2,"score":0.42579197883605957},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3957290053367615},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38907015323638916},{"id":"https://openalex.org/C110313322","wikidata":"https://www.wikidata.org/wiki/Q7100793","display_name":"Ordinal regression","level":2,"score":0.34507060050964355},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15056970715522766},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0921277403831482},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/mis.2021.3088543","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mis.2021.3088543","pdf_url":null,"source":{"id":"https://openalex.org/S114241109","display_name":"IEEE Intelligent Systems","issn_l":"1541-1672","issn":["1541-1672","1941-1294"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Intelligent Systems","raw_type":"journal-article"},{"id":"pmh:oai:scholarsphere.psu.edu:44dd1a5c-775f-47c8-9015-139840fa2a37","is_oa":true,"landing_page_url":"https://scholarsphere.psu.edu/resources/44dd1a5c-775f-47c8-9015-139840fa2a37","pdf_url":"https://scholarsphere.psu.edu/resources/57569697-999e-4ffe-9469-6b5d11ef6b4c/downloads/19884","source":{"id":"https://openalex.org/S4306401507","display_name":"ScholarSphere (Penn State Libraries)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I3130638595","host_organization_name":"Pangasinan State University","host_organization_lineage":["https://openalex.org/I3130638595"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Intelligent Systems","raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:scholarsphere.psu.edu:44dd1a5c-775f-47c8-9015-139840fa2a37","is_oa":true,"landing_page_url":"https://scholarsphere.psu.edu/resources/44dd1a5c-775f-47c8-9015-139840fa2a37","pdf_url":"https://scholarsphere.psu.edu/resources/57569697-999e-4ffe-9469-6b5d11ef6b4c/downloads/19884","source":{"id":"https://openalex.org/S4306401507","display_name":"ScholarSphere (Penn State Libraries)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I3130638595","host_organization_name":"Pangasinan State University","host_organization_lineage":["https://openalex.org/I3130638595"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Intelligent Systems","raw_type":"Article"},"sustainable_development_goals":[{"display_name":"Climate action","score":0.6299999952316284,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309370","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10"},{"id":"https://openalex.org/F4320310419","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3171163466.pdf","grobid_xml":"https://content.openalex.org/works/W3171163466.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1485009520","https://openalex.org/W1522301498","https://openalex.org/W1696703109","https://openalex.org/W1852984854","https://openalex.org/W2035222601","https://openalex.org/W2058475745","https://openalex.org/W2124105163","https://openalex.org/W2150291840","https://openalex.org/W2173584915","https://openalex.org/W2232647241","https://openalex.org/W2313387664","https://openalex.org/W2417064059","https://openalex.org/W2440214111","https://openalex.org/W2565639579","https://openalex.org/W2963351448","https://openalex.org/W2963488291","https://openalex.org/W2963870721","https://openalex.org/W3011863222","https://openalex.org/W3013229294","https://openalex.org/W6628877408","https://openalex.org/W6631190155","https://openalex.org/W6678181790"],"related_works":["https://openalex.org/W1984083244","https://openalex.org/W156327249","https://openalex.org/W4399574212","https://openalex.org/W3099723579","https://openalex.org/W4392366894","https://openalex.org/W2058716166","https://openalex.org/W33026131","https://openalex.org/W4248085828","https://openalex.org/W2000049449","https://openalex.org/W3210652048"],"abstract_inverted_index":{"Numerical":[0],"precipitation":[1,82,118],"prediction":[2,28,119],"plays":[3],"a":[4,35,67,81,86,94],"crucial":[5],"role":[6],"in":[7,14,139,143,166],"weather":[8,27],"forecasting":[9],"and":[10,20,46,50,58,85,98,133,156],"has":[11],"broad":[12],"applications":[13],"public":[15],"services":[16],"including":[17,54],"aviation":[18],"management":[19],"urban":[21],"disaster":[22],"early-warning":[23],"systems.":[24],"However,":[25],"numerical":[26,117],"(NWP)":[29],"models":[30,147],"are":[31],"often":[32],"constrained":[33,55],"by":[34],"systematic":[36],"bias":[37,109,167],"due":[38],"to":[39],"coarse":[40],"spatial":[41],"resolution,":[42],"lack":[43],"of":[44,48,111],"parameterizations,":[45],"limitations":[47],"observation":[49],"conventional":[51],"meteorological":[52,122],"models,":[53,159],"sample":[56],"size":[57],"long-tail":[59],"distribution.":[60],"To":[61],"address":[62],"these":[63],"issues,":[64],"we":[65],"present":[66],"data-driven":[68],"deep":[69,157],"learning":[70,158],"model,":[71],"named":[72],"the":[73,125,144],"ordinal":[74,100],"distribution":[75,101],"autoencoder":[76,96],"(ODA),":[77],"which":[78],"principally":[79],"includes":[80],"confidence":[83],"network":[84,88],"combinatorial":[87],"that":[89],"contains":[90],"two":[91,145],"blocks,":[92],"i.e.,":[93],"denoising":[95],"block":[97],"an":[99,105,135],"regression":[102],"block.":[103],"As":[104],"expert-free":[106],"model":[107,137],"for":[108,128],"correction":[110],"precipitation,":[112],"it":[113],"can":[114],"effectively":[115],"correct":[116],"based":[120],"on":[121],"data":[123],"from":[124],"European":[126],"Centre":[127],"Medium-Range":[129],"Weather":[130],"Forecasts":[131],"(ECMWF)":[132],"SMS-WARMS,":[134],"NWP":[136,146],"used":[138],"East":[140],"China.":[141],"Experiments":[142],"demonstrate":[148],"that,":[149],"compared":[150],"with":[151],"several":[152],"classical":[153],"machine-learning":[154],"algorithms":[155],"our":[160],"proposed":[161],"ODA":[162],"generally":[163],"performs":[164],"better":[165],"correction.":[168]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
