{"id":"https://openalex.org/W4415821229","doi":"https://doi.org/10.1109/tgrs.2025.3621627","title":"SSRF-Net: A Stagewise Scheduled Rainfall Forecasting Network With an Asymmetric Architecture","display_name":"SSRF-Net: A Stagewise Scheduled Rainfall Forecasting Network With an Asymmetric Architecture","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4415821229","doi":"https://doi.org/10.1109/tgrs.2025.3621627"},"language":null,"primary_location":{"id":"doi:10.1109/tgrs.2025.3621627","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3621627","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033486978","display_name":"weidong Luo","orcid":"https://orcid.org/0009-0005-2620-5770"},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjie Luo","raw_affiliation_strings":["College of Computer Science and Engineering, Chongqing University of Technology, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0005-2620-5770","affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Chongqing University of Technology, Chongqing, China","institution_ids":["https://openalex.org/I50632499"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007621167","display_name":"Chaorong Li","orcid":"https://orcid.org/0000-0001-8336-2661"},"institutions":[{"id":"https://openalex.org/I4210131342","display_name":"Yibin University","ror":"https://ror.org/03w8m2977","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131342"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaorong Li","raw_affiliation_strings":["School of Computer Science and Technology (School of Artificial Intelligence), Yibin University, Yibin, China"],"raw_orcid":"https://orcid.org/0000-0001-8336-2661","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology (School of Artificial Intelligence), Yibin University, Yibin, China","institution_ids":["https://openalex.org/I4210131342"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023344529","display_name":"Xudong Ling","orcid":"https://orcid.org/0009-0009-1128-8322"},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xudong Ling","raw_affiliation_strings":["College of Computer Science and Engineering, Chongqing University of Technology, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0009-1128-8322","affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Chongqing University of Technology, Chongqing, China","institution_ids":["https://openalex.org/I50632499"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chuanhu Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuanhu Deng","raw_affiliation_strings":["College of Computer Science and Engineering, Chongqing University of Technology, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Chongqing University of Technology, Chongqing, China","institution_ids":["https://openalex.org/I50632499"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070568007","display_name":"Zhuo Wang","orcid":"https://orcid.org/0000-0002-8207-4489"},"institutions":[{"id":"https://openalex.org/I50632499","display_name":"Chongqing University of Technology","ror":"https://ror.org/04vgbd477","country_code":"CN","type":"education","lineage":["https://openalex.org/I50632499"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuo Wang","raw_affiliation_strings":["College of Computer Science and Engineering, Chongqing University of Technology, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Chongqing University of Technology, Chongqing, China","institution_ids":["https://openalex.org/I50632499"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9514,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.7823225,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11234","display_name":"Precipitation Measurement and Analysis","score":0.4092000126838684,"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":0.4092000126838684,"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":0.22200000286102295,"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"}},{"id":"https://openalex.org/T10466","display_name":"Meteorological Phenomena and Simulations","score":0.08720000088214874,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/nowcasting","display_name":"Nowcasting","score":0.5769000053405762},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.5167999863624573},{"id":"https://openalex.org/keywords/forcing","display_name":"Forcing (mathematics)","score":0.460099995136261},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4490000009536743},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.43309998512268066},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.42649999260902405},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.3874000012874603},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.38670000433921814}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7752000093460083},{"id":"https://openalex.org/C2781013037","wikidata":"https://www.wikidata.org/wiki/Q1433331","display_name":"Nowcasting","level":2,"score":0.5769000053405762},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.5167999863624573},{"id":"https://openalex.org/C197115733","wikidata":"https://www.wikidata.org/wiki/Q1003136","display_name":"Forcing (mathematics)","level":2,"score":0.460099995136261},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4490000009536743},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.43309998512268066},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.42649999260902405},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4099000096321106},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3874000012874603},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.38670000433921814},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.37049999833106995},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.3402999937534332},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33809998631477356},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32910001277923584},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.3249000012874603},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3215000033378601},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.31690001487731934},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.2992999851703644},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2924000024795532},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2879999876022339},{"id":"https://openalex.org/C2781395549","wikidata":"https://www.wikidata.org/wiki/Q4680762","display_name":"Adaptive sampling","level":3,"score":0.275299996137619},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.26919999718666077},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.2632000148296356}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2025.3621627","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3621627","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5492537575","display_name":null,"funder_award_id":"2023YY05","funder_id":"https://openalex.org/F4320321941","funder_display_name":"Harbin University of Science and Technology"},{"id":"https://openalex.org/G5734850265","display_name":null,"funder_award_id":"2024ZYD0089","funder_id":"https://openalex.org/F4320327051","funder_display_name":"Science and Technology Department of Henan Province"},{"id":"https://openalex.org/G6622628027","display_name":null,"funder_award_id":"2024XJYY03","funder_id":"https://openalex.org/F4320321941","funder_display_name":"Harbin University of Science and Technology"},{"id":"https://openalex.org/G6638837379","display_name":null,"funder_award_id":"2023YY02","funder_id":"https://openalex.org/F4320321941","funder_display_name":"Harbin University of Science and Technology"},{"id":"https://openalex.org/G68993859","display_name":null,"funder_award_id":"2025XJZD01","funder_id":"https://openalex.org/F4320321941","funder_display_name":"Harbin University of Science and Technology"}],"funders":[{"id":"https://openalex.org/F4320321941","display_name":"Harbin University of Science and Technology","ror":"https://ror.org/04e6y1282"},{"id":"https://openalex.org/F4320327051","display_name":"Science and Technology Department of Henan Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2024414272","https://openalex.org/W2042172159","https://openalex.org/W2114473878","https://openalex.org/W2594928006","https://openalex.org/W2734349601","https://openalex.org/W2945086703","https://openalex.org/W2963351448","https://openalex.org/W2963691377","https://openalex.org/W2963881378","https://openalex.org/W2964098128","https://openalex.org/W2967033144","https://openalex.org/W3001630685","https://openalex.org/W3003709258","https://openalex.org/W3009216045","https://openalex.org/W3109184532","https://openalex.org/W3126335003","https://openalex.org/W3133088081","https://openalex.org/W3199775909","https://openalex.org/W3200052951","https://openalex.org/W3202525453","https://openalex.org/W4293192773","https://openalex.org/W4294068833","https://openalex.org/W4308112140","https://openalex.org/W4312851276","https://openalex.org/W4383197616","https://openalex.org/W4383218913","https://openalex.org/W4385482745","https://openalex.org/W4386740901","https://openalex.org/W4388654737","https://openalex.org/W4389341455","https://openalex.org/W4392506769","https://openalex.org/W4393147339","https://openalex.org/W4400873121","https://openalex.org/W4405022975","https://openalex.org/W4405916824","https://openalex.org/W4406610713","https://openalex.org/W4407398394","https://openalex.org/W4407576398","https://openalex.org/W4408324188","https://openalex.org/W4409864547","https://openalex.org/W4409869147"],"related_works":[],"abstract_inverted_index":{"Deterministic":[0],"deep":[1],"learning":[2],"models":[3],"for":[4,47,100,165],"precipitation":[5],"nowcasting":[6],"often":[7],"face":[8],"several":[9],"limitations,":[10],"including":[11],"cumulative":[12],"error":[13,82],"in":[14],"long-sequence":[15],"predictions,":[16],"over-smoothing,":[17],"and":[18,77,84,104,114,132,136,155],"a":[19,44,62,68,95,140],"reduced":[20],"ability":[21],"to":[22,28,80,167,175],"capture":[23],"rare,":[24],"high-impact":[25],"rainfall":[26,40,50],"due":[27],"data":[29],"imbalance.":[30],"To":[31],"address":[32],"these":[33],"challenges,":[34],"we":[35],"propose":[36],"the":[37,153,184],"stagewise":[38],"scheduled":[39,78],"forecasting":[41],"network":[42],"(SSRF-Net),":[43],"convolutional":[45],"framework":[46,66],"continuous":[48],"multistep":[49],"prediction":[51,71],"that":[52,110,126,159],"achieves":[53],"lower":[54],"floating-point":[55],"operations":[56],"(FLOPs)":[57],"than":[58],"competitive":[59],"baselines":[60],"under":[61],"standardized":[63],"evaluation.":[64],"Our":[65],"introduces":[67],"multistage,":[69],"sliding-window":[70],"mechanism":[72],"trained":[73],"with":[74,187],"teacher":[75],"forcing":[76],"sampling":[79],"mitigate":[81],"accumulation":[83],"stabilize":[85],"training.":[86],"We":[87,117],"design":[88],"an":[89,105,120],"asymmetric":[90],"encoder\u2013decoder":[91],"(E\u2013D)":[92],"architecture":[93],"featuring":[94],"differential":[96],"selective":[97,101],"encoder":[98],"(DSE)":[99],"feature":[102],"compression":[103],"additive":[106],"fusion":[107],"decoder":[108],"(AFD)":[109],"progressively":[111],"reconstructs":[112],"details":[113],"alleviates":[115],"over-smoothing.":[116],"further":[118],"introduce":[119],"intensity-weighted":[121],"Gaussian":[122,129],"KL":[123,141],"divergence":[124],"loss":[125],"aligns":[127],"sequence-level":[128],"summaries":[130],"(means":[131],"variances)":[133],"of":[134],"predictions":[135],"ground":[137],"truth":[138],"via":[139],"term,":[142],"prioritizing":[143],"heavy-rain":[144],"events":[145],"without":[146],"assuming":[147],"pixelwise":[148],"Gaussianity.":[149],"Extensive":[150],"experiments":[151],"on":[152,170,190],"KNMI":[154],"SEVIR":[156],"datasets":[157],"show":[158],"SSRF-Net":[160],"outperforms":[161],"strong":[162],"baselines,":[163],"particularly":[164],"moderate":[166],"severe":[168],"precipitation;":[169],"KNMI,":[171],"it":[172],"yields":[173],"up":[174],"41.8%":[176],"higher":[177],"per-frame":[178],"critical":[179],"success":[180],"index":[181],"(CSI)":[182],"at":[183],"30-mm/h":[185],"threshold,":[186],"consistent":[188],"gains":[189],"SEVIR.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-03T00:00:00"}