{"id":"https://openalex.org/W4327971350","doi":"https://doi.org/10.3390/rs15061635","title":"Forecasting Precipitation from Radar Wind Profiler Mesonet and Reanalysis Using the Random Forest Algorithm","display_name":"Forecasting Precipitation from Radar Wind Profiler Mesonet and Reanalysis Using the Random Forest Algorithm","publication_year":2023,"publication_date":"2023-03-17","ids":{"openalex":"https://openalex.org/W4327971350","doi":"https://doi.org/10.3390/rs15061635"},"language":"en","primary_location":{"id":"doi:10.3390/rs15061635","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15061635","pdf_url":"https://www.mdpi.com/2072-4292/15/6/1635/pdf?version=1679061282","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/15/6/1635/pdf?version=1679061282","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101327080","display_name":"Yizhi Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]},{"id":"https://openalex.org/I4210133131","display_name":"Chinese Academy of Meteorological Sciences","ror":"https://ror.org/034b53w38","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210133131"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yizhi Wu","raw_affiliation_strings":["School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China","State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China"],"affiliations":[{"raw_affiliation_string":"School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China","institution_ids":["https://openalex.org/I200845125"]},{"raw_affiliation_string":"State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China","institution_ids":["https://openalex.org/I4210133131"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068048071","display_name":"Jianping Guo","orcid":"https://orcid.org/0000-0001-8530-8976"},"institutions":[{"id":"https://openalex.org/I4210133131","display_name":"Chinese Academy of Meteorological Sciences","ror":"https://ror.org/034b53w38","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210133131"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianping Guo","raw_affiliation_strings":["State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China","institution_ids":["https://openalex.org/I4210133131"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065442126","display_name":"Tianmeng Chen","orcid":"https://orcid.org/0000-0002-1564-7013"},"institutions":[{"id":"https://openalex.org/I4210133131","display_name":"Chinese Academy of Meteorological Sciences","ror":"https://ror.org/034b53w38","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210133131"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianmeng Chen","raw_affiliation_strings":["State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China","institution_ids":["https://openalex.org/I4210133131"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079575886","display_name":"Aijun Chen","orcid":"https://orcid.org/0000-0002-2076-0555"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aijun Chen","raw_affiliation_strings":["School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China"],"affiliations":[{"raw_affiliation_string":"School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, China","institution_ids":["https://openalex.org/I200845125"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5068048071"],"corresponding_institution_ids":["https://openalex.org/I4210133131"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.6946,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.81577463,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":"15","issue":"6","first_page":"1635","last_page":"1635"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10466","display_name":"Meteorological Phenomena and Simulations","score":0.9998999834060669,"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/T10466","display_name":"Meteorological Phenomena and Simulations","score":0.9998999834060669,"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/T11234","display_name":"Precipitation Measurement and Analysis","score":0.9991000294685364,"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/T10029","display_name":"Climate variability and models","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/random-forest","display_name":"Random forest","score":0.6927160620689392},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.6103253364562988},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.605190098285675},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.5927220582962036},{"id":"https://openalex.org/keywords/precipitation","display_name":"Precipitation","score":0.49086886644363403},{"id":"https://openalex.org/keywords/weather-radar","display_name":"Weather radar","score":0.4113761782646179},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.37177032232284546},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34475943446159363},{"id":"https://openalex.org/keywords/climatology","display_name":"Climatology","score":0.3246750235557556},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.20695415139198303},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.18444868922233582},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.17454791069030762}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6927160620689392},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.6103253364562988},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.605190098285675},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.5927220582962036},{"id":"https://openalex.org/C107054158","wikidata":"https://www.wikidata.org/wiki/Q25257","display_name":"Precipitation","level":2,"score":0.49086886644363403},{"id":"https://openalex.org/C92237259","wikidata":"https://www.wikidata.org/wiki/Q863343","display_name":"Weather radar","level":3,"score":0.4113761782646179},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.37177032232284546},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34475943446159363},{"id":"https://openalex.org/C49204034","wikidata":"https://www.wikidata.org/wiki/Q52139","display_name":"Climatology","level":1,"score":0.3246750235557556},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.20695415139198303},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.18444868922233582},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.17454791069030762},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs15061635","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15061635","pdf_url":"https://www.mdpi.com/2072-4292/15/6/1635/pdf?version=1679061282","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:867162e3fe26458a8c396153ed752550","is_oa":true,"landing_page_url":"https://doaj.org/article/867162e3fe26458a8c396153ed752550","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 15, Iss 6, p 1635 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/6/1635/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15061635","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 15; Issue 6; Pages: 1635","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15061635","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15061635","pdf_url":"https://www.mdpi.com/2072-4292/15/6/1635/pdf?version=1679061282","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3818744222","display_name":null,"funder_award_id":"U2142209","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4327971350.pdf"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W1977833064","https://openalex.org/W1997825153","https://openalex.org/W2001891785","https://openalex.org/W2030785787","https://openalex.org/W2060786871","https://openalex.org/W2084591845","https://openalex.org/W2105985344","https://openalex.org/W2136664483","https://openalex.org/W2139038373","https://openalex.org/W2155261478","https://openalex.org/W2255717465","https://openalex.org/W2338119854","https://openalex.org/W2345254164","https://openalex.org/W2463639542","https://openalex.org/W2614344964","https://openalex.org/W2758914739","https://openalex.org/W2795928357","https://openalex.org/W2888369678","https://openalex.org/W2902336780","https://openalex.org/W2911964244","https://openalex.org/W2912750253","https://openalex.org/W2913904793","https://openalex.org/W2954586028","https://openalex.org/W2985739459","https://openalex.org/W2989173953","https://openalex.org/W3004470311","https://openalex.org/W3017358076","https://openalex.org/W3025181668","https://openalex.org/W3044733120","https://openalex.org/W3044890802","https://openalex.org/W3080823251","https://openalex.org/W3104212954","https://openalex.org/W3122092312","https://openalex.org/W3133088081","https://openalex.org/W3158908037","https://openalex.org/W3202525453","https://openalex.org/W4213441324","https://openalex.org/W4224235642","https://openalex.org/W4225736959","https://openalex.org/W4285125734","https://openalex.org/W4295422248","https://openalex.org/W4301396080","https://openalex.org/W4310576926","https://openalex.org/W4312737810","https://openalex.org/W4366162581","https://openalex.org/W6791264106"],"related_works":["https://openalex.org/W2354666346","https://openalex.org/W4311063044","https://openalex.org/W2798120804","https://openalex.org/W2036324114","https://openalex.org/W2997500395","https://openalex.org/W2050024921","https://openalex.org/W1933455866","https://openalex.org/W1544437858","https://openalex.org/W2166923512","https://openalex.org/W2275457798"],"abstract_inverted_index":{"Data-driven":[0],"machine":[1,276],"learning":[2,277],"technology":[3],"can":[4],"learn":[5],"and":[6,21,45,90,106,133,149,158,226,247],"extract":[7],"features,":[8],"a":[9,275],"factor":[10],"which":[11],"is":[12,128,177],"well":[13],"recognized":[14],"to":[15,83,167,197,264],"be":[16],"powerful":[17],"in":[18,38,48,68,174,199,202,207,240,245],"the":[19,27,31,49,61,73,85,121,130,136,168,171,185,192,214,220,224,232,242,254,266,272],"warning":[20],"prediction":[22,267],"of":[23,30,79,87,142,163,170,187,209,269,274],"severe":[24,56],"weather.":[25],"With":[26],"large-scale":[28],"deployment":[29],"radar":[32],"wind":[33],"profile":[34],"(RWP)":[35],"observational":[36,189],"network":[37],"China,":[39],"dynamical":[40],"variables":[41],"with":[42,101,271],"higher":[43],"temporal":[44],"spatial":[46],"resolution":[47],"vertical":[50,91,150],"become":[51],"strong":[52],"supports":[53],"for":[54,114,129,135],"machine-learning-based":[55],"convection":[57,270],"prediction.":[58],"Based":[59],"on":[60,120],"RWP":[62,81,159,188,233,260],"mesonet":[63],"that":[64,184,228,253],"has":[65],"been":[66],"deployed":[67],"Beijing,":[69],"this":[70],"study":[71],"uses":[72],"measurements":[74,234,258],"from":[75,104,154,231,259],"four":[76],"triangles":[77],"composed":[78],"six":[80],"stations":[82],"determine":[84],"profiles":[86],"divergence,":[88,147],"vorticity,":[89,148],"velocity":[92,151],"before":[93],"rainfall":[94,116,137,210,221],"onsets.":[95],"These":[96],"dynamic":[97,143,256],"feature":[98,165],"variables,":[99],"combined":[100],"cloud":[102],"properties":[103],"Himawari-8":[105],"ERA-5":[107,155,215],"reanalysis,":[108],"serve":[109],"as":[110,146,191,217],"key":[111],"input":[112,195],"parameters":[113],"two":[115],"forecast":[117,132,204],"models":[118],"based":[119],"random":[122],"forest":[123],"(RF)":[124],"classification":[125],"algorithm.":[126],"One":[127],"rainfall/non-rainfall":[131,203],"another":[134],"grade":[138,222],"forecast.":[139],"The":[140,161,181],"roles":[141],"features":[144],"such":[145],"are":[152],"examined":[153],"reanalysis":[156],"data":[157,190,216],"measurements.":[160],"contribution":[162],"each":[164],"variable":[166,257],"performance":[169,201,244],"RF":[172,193],"model":[173,194,243],"independent":[175],"tests":[176],"also":[178],"discussed":[179],"here.":[180],"results":[182],"show":[183,238],"usage":[186],"tends":[196],"result":[198],"better":[200],"30":[205],"min":[206],"advance":[208],"onset":[211],"than":[212],"using":[213],"inputs.":[218],"For":[219],"forecast,":[223],"divergence":[225],"vorticity":[227],"were":[229],"estimated":[230],"at":[235],"800":[236],"hPa":[237],"importance":[239],"improving":[241],"heavy":[246],"moderate":[248],"rain":[249],"forecasts.":[250],"This":[251],"indicates":[252],"atmospheric":[255],"have":[261],"great":[262],"potential":[263],"improve":[265],"skill":[268],"aid":[273],"model.":[278]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3}],"updated_date":"2026-04-03T22:45:19.894376","created_date":"2023-03-21T00:00:00"}