{"id":"https://openalex.org/W4415740992","doi":"https://doi.org/10.21203/rs.3.rs-7651876/v1","title":"Beyond Accuracy: Evaluating the Data-Driven, Process-Informed DHR-SDP Model for Rainfall Prediction and Climate Signal Representation","display_name":"Beyond Accuracy: Evaluating the Data-Driven, Process-Informed DHR-SDP Model for Rainfall Prediction and Climate Signal Representation","publication_year":2025,"publication_date":"2025-10-31","ids":{"openalex":"https://openalex.org/W4415740992","doi":"https://doi.org/10.21203/rs.3.rs-7651876/v1"},"language":"en","primary_location":{"id":"doi:10.21203/rs.3.rs-7651876/v1","doi":"https://doi.org/10.21203/rs.3.rs-7651876/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-7651876/v1","pdf_url":"https://www.researchsquare.com/article/rs-7651876/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Research Square","raw_type":"posted-content"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.researchsquare.com/article/rs-7651876/latest.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102871320","display_name":"Daniel E. Mendoza","orcid":"https://orcid.org/0009-0006-3431-6566","observed_orcids":["https://orcid.org/0009-0006-3431-6566"]},"institutions":[{"id":"https://openalex.org/I189914110","display_name":"University of Cuenca","ror":"https://ror.org/04r23zn56","country_code":"EC","type":"education","lineage":["https://openalex.org/I189914110"]}],"countries":["EC"],"is_corresponding":true,"raw_author_name":"Daniel E. Mendoza","raw_affiliation_strings":["University of Cuenca"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Cuenca","institution_ids":["https://openalex.org/I189914110"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066349103","display_name":"Ana Ochoa\u2010S\u00e1nchez","orcid":"https://orcid.org/0000-0002-3026-4918","observed_orcids":["https://orcid.org/0000-0002-3026-4918"]},"institutions":[{"id":"https://openalex.org/I4210126183","display_name":"Universidad del Azuay","ror":"https://ror.org/037xrmj59","country_code":"EC","type":"education","lineage":["https://openalex.org/I4210126183"]}],"countries":["EC"],"is_corresponding":false,"raw_author_name":"Ana Ochoa-S\u00e1nchez","raw_affiliation_strings":["Universidad del Azuay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidad del Azuay","institution_ids":["https://openalex.org/I4210126183"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017371070","display_name":"Santiago N\u00fa\u00f1ez Mej\u00eda","orcid":"https://orcid.org/0000-0002-9633-5272","observed_orcids":["https://orcid.org/0000-0002-9633-5272"]},"institutions":[{"id":"https://openalex.org/I4210126183","display_name":"Universidad del Azuay","ror":"https://ror.org/037xrmj59","country_code":"EC","type":"education","lineage":["https://openalex.org/I4210126183"]}],"countries":["EC"],"is_corresponding":false,"raw_author_name":"Santiago N\u00fa\u00f1ez-Mej\u00eda","raw_affiliation_strings":["Universidad del Azuay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidad del Azuay","institution_ids":["https://openalex.org/I4210126183"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012648849","display_name":"Esteban P. Samaniego","orcid":"https://orcid.org/0000-0002-8728-491X","observed_orcids":["https://orcid.org/0000-0002-8728-491X"]},"institutions":[{"id":"https://openalex.org/I189914110","display_name":"University of Cuenca","ror":"https://ror.org/04r23zn56","country_code":"EC","type":"education","lineage":["https://openalex.org/I189914110"]}],"countries":["EC"],"is_corresponding":false,"raw_author_name":"Esteban P. Samaniego","raw_affiliation_strings":["University of Cuenca"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Cuenca","institution_ids":["https://openalex.org/I189914110"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102871320"],"corresponding_institution_ids":["https://openalex.org/I189914110"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10029","display_name":"Climate variability and models","score":0.986299991607666,"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"}},"topics":[{"id":"https://openalex.org/T10029","display_name":"Climate variability and models","score":0.986299991607666,"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"}},{"id":"https://openalex.org/T10330","display_name":"Hydrology and Watershed Management Studies","score":0.0032999999821186066,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"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/T11234","display_name":"Precipitation Measurement and Analysis","score":0.0032999999821186066,"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/rainfall-prediction","display_name":"precipitation forecasting","score":0.9739999771118164},{"id":"https://openalex.org/keywords/dynamic-harmonic-regression","display_name":"dynamic harmonic regression","score":0.8489999771118164},{"id":"https://openalex.org/keywords/state-dependent-parameters","display_name":"state-dependent parameters","score":0.972000002861023},{"id":"https://openalex.org/keywords/rainfall-trends","display_name":"rainfall trends","score":0.949999988079071},{"id":"https://openalex.org/keywords/southern-andes","display_name":"southern Andes","score":0.6420000195503235},{"id":"https://openalex.org/keywords/armax-model","display_name":"ARMAX model","score":0.5789999961853027},{"id":"https://openalex.org/keywords/autoregressive-neural-networks","display_name":"autoregressive neural networks","score":0.8529999852180481}],"concepts":[{"id":"https://openalex.org/C41156917","wikidata":"https://www.wikidata.org/wiki/Q682831","display_name":"Downscaling","level":3,"score":0.6111999750137329},{"id":"https://openalex.org/C49204034","wikidata":"https://www.wikidata.org/wiki/Q52139","display_name":"Climatology","level":1,"score":0.5716999769210815},{"id":"https://openalex.org/C168754636","wikidata":"https://www.wikidata.org/wiki/Q620920","display_name":"Climate model","level":3,"score":0.5698999762535095},{"id":"https://openalex.org/C132651083","wikidata":"https://www.wikidata.org/wiki/Q7942","display_name":"Climate change","level":2,"score":0.5679000020027161},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5077999830245972},{"id":"https://openalex.org/C2781162219","wikidata":"https://www.wikidata.org/wiki/Q26250693","display_name":"Replicate","level":2,"score":0.4781999886035919},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.47450000047683716},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4731999933719635},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.4708999991416931},{"id":"https://openalex.org/C134295995","wikidata":"https://www.wikidata.org/wiki/Q1506685","display_name":"Orographic lift","level":3,"score":0.4564000070095062},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.42800000309944153},{"id":"https://openalex.org/C47665787","wikidata":"https://www.wikidata.org/wiki/Q7834266","display_name":"Transient climate simulation","level":4,"score":0.39730000495910645},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.38580000400543213},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3741999864578247},{"id":"https://openalex.org/C2994067962","wikidata":"https://www.wikidata.org/wiki/Q3509184","display_name":"Climate system","level":3,"score":0.3718999922275543},{"id":"https://openalex.org/C194507410","wikidata":"https://www.wikidata.org/wiki/Q901704","display_name":"Orography","level":3,"score":0.365200012922287},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.33889999985694885},{"id":"https://openalex.org/C107054158","wikidata":"https://www.wikidata.org/wiki/Q25257","display_name":"Precipitation","level":2,"score":0.3264999985694885},{"id":"https://openalex.org/C143742823","wikidata":"https://www.wikidata.org/wiki/Q5513004","display_name":"GCM transcription factors","level":4,"score":0.31459999084472656},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.31279999017715454},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.31060001254081726},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C127491075","wikidata":"https://www.wikidata.org/wiki/Q7617825","display_name":"Stochastic modelling","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C111874474","wikidata":"https://www.wikidata.org/wiki/Q6005872","display_name":"Impact assessment","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C141452985","wikidata":"https://www.wikidata.org/wiki/Q650994","display_name":"General Circulation Model","level":3,"score":0.2574999928474426}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21203/rs.3.rs-7651876/v1","doi":"https://doi.org/10.21203/rs.3.rs-7651876/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-7651876/v1","pdf_url":"https://www.researchsquare.com/article/rs-7651876/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Research Square","raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.21203/rs.3.rs-7651876/v1","doi":"https://doi.org/10.21203/rs.3.rs-7651876/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-7651876/v1","pdf_url":"https://www.researchsquare.com/article/rs-7651876/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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":"Research Square","raw_type":"posted-content"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.9786999821662903}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415740992.pdf","grobid_xml":"https://content.openalex.org/works/W4415740992.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W1967992376","https://openalex.org/W1990471334","https://openalex.org/W2003068901","https://openalex.org/W2011227258","https://openalex.org/W2014928429","https://openalex.org/W2035301923","https://openalex.org/W2054282473","https://openalex.org/W2077387053","https://openalex.org/W2081819544","https://openalex.org/W2095559068","https://openalex.org/W2142635246","https://openalex.org/W2152388196","https://openalex.org/W2168352079","https://openalex.org/W2178225550","https://openalex.org/W2237826530","https://openalex.org/W2254223311","https://openalex.org/W2255188727","https://openalex.org/W2338714606","https://openalex.org/W2766801343","https://openalex.org/W2884855418","https://openalex.org/W2886231287","https://openalex.org/W2947753393","https://openalex.org/W2951276077","https://openalex.org/W3005992532","https://openalex.org/W3038241059","https://openalex.org/W3039590110","https://openalex.org/W3155470669","https://openalex.org/W4392284590","https://openalex.org/W4399037866"],"related_works":["https://openalex.org/W3038241059","https://openalex.org/W7160627013","https://openalex.org/W2990203556","https://openalex.org/W7128403980","https://openalex.org/W2999638341","https://openalex.org/W6973408420","https://openalex.org/W4382519145","https://openalex.org/W2031542355","https://openalex.org/W3210557849","https://openalex.org/W7132849206"],"abstract_inverted_index":{"Abstract":[0],"Rainfall":[1],"prediction":[2],"is":[3,164],"essential":[4],"for":[5,21],"understanding":[6],"and":[7,16,48,80,130,160,189,200,214,234,236,241,245],"mitigating":[8],"the":[9,70,75,152,172,206,227],"impacts":[10],"of":[11,77,86,171,208],"global":[12,240],"environmental":[13],"change.":[14],"Dynamic":[15],"statistical":[17,35,61],"models":[18,25,36,43,119],"are":[19,31,37,45,50],"used":[20],"this":[22],"purpose:":[23],"dynamic":[24],"simulate":[26],"underlying":[27],"physical":[28],"processes":[29],"but":[30],"computationally":[32],"intensive,":[33],"while":[34],"usually":[38],"more":[39],"cost-efficient.":[40],"Stochastic":[41],"climate":[42,72,87,157,217,243],"that":[44,93,182],"both":[46,78],"data-driven":[47,118],"process-informed":[49,105,210],"interesting,":[51],"as":[52],"they":[53],"often":[54],"show":[55,181],"enhanced":[56],"predictive":[57,97],"capabilities":[58],"over":[59],"conventional":[60],"models,":[62],"partly":[63],"due":[64,193],"to":[65,68,155,194,197,212,231],"their":[66,81],"ability":[67,154],"capture":[69],"inherent":[71],"dynamics.":[73],"Ensuring":[74],"reliability":[76],"predictions":[79,191],"conceptual":[82],"interpretations":[83],"(e.g.,":[84],"descriptions":[85],"patterns)":[88],"requires":[89],"a":[90,103,148,167],"robust":[91],"evaluation":[92,150,163],"extends":[94],"beyond":[95],"assessing":[96],"accuracy.":[98],"Here,":[99],"we":[100],"rigorously":[101],"assess":[102],"data-driven,":[104,209],"rainfall":[106,115,178,186],"model\u2014DHR-SDP":[107],"(Dynamic":[108],"Harmonic":[109],"Regression":[110],"with":[111,120,133,143],"State-Dependent":[112,134],"Parameters)\u2014against":[113],"mean-monthly":[114],"estimates,":[116],"alternative":[117],"exogenous":[121],"variables\u2014ARMAX":[122],"(Autoregressive":[123,127,132],"Moving":[124],"Average),":[125],"ANNX":[126],"Neural":[128],"Network),":[129],"ARX-SDP":[131],"Parameters)\u2014and":[135],"nineteen":[136],"GCM":[137],"monthly":[138,190],"hindcasts":[139],"at":[140],"1\u00b0":[141],"resolution":[142],"bias":[144],"correction.":[145],"We":[146],"consider":[147],"process-oriented":[149],"testing":[151],"model\u2019s":[153,228],"represent":[156],"patterns":[158],"(seasonality":[159],"trends).":[161],"This":[162],"conducted":[165],"in":[166,220],"complex":[168,221],"orographic":[169],"region":[170],"Southern":[173],"Andes":[174],"characterized":[175],"by":[176],"spatial":[177],"variability.":[179],"Results":[180],"DHR-SDP":[183],"reproduces":[184],"seasonal":[185],"dynamics,":[187],"trends,":[188],"reliably,":[192],"its":[195],"capacity":[196],"replicate":[198],"intra-":[199],"inter-annual":[201],"processes.":[202],"These":[203],"findings":[204],"underscore":[205],"potential":[207],"approaches":[211],"predict":[213],"conceptualize":[215],"local":[216,242],"behavior,":[218],"even":[219],"terrains.":[222],"Further":[223],"work":[224],"should":[225],"examine":[226],"broader":[229],"applicability":[230],"climate-change":[232],"modeling":[233],"projections":[235],"clarify":[237],"relationships":[238],"among":[239],"variables":[244],"phenomena.":[246]},"counts_by_year":[],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2025-10-31T00:00:00"}