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dc.contributor.authorMirones Alonso, Óscar 
dc.contributor.authorBedía Jiménez, Joaquín
dc.contributor.authorFernández de la Granja, Juan Antonio 
dc.contributor.authorHerrera García, Sixto 
dc.contributor.authorOrtega Van Vloten, Sara
dc.contributor.authorPozo Estívariz, Andrea
dc.contributor.authorCagigal Gil, Laura 
dc.contributor.authorMéndez Incera, Fernando Javier 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2023-02-27T13:32:02Z
dc.date.available2023-02-27T13:32:02Z
dc.date.issued2023-02
dc.identifier.issn0899-8418
dc.identifier.issn1097-0088
dc.identifier.otherPID2019-107053RB-I00es_ES
dc.identifier.otherPID2020-116595RB-I00es_ES
dc.identifier.urihttps://hdl.handle.net/10902/27910
dc.description.abstractThe South Pacific region is an area affected by characteristic precipitation patterns undergoing extreme events such as tropical cyclones and droughts. First, a daily weather typing of precipitation is presented, based on principal component analysis and k-means clustering using precipitation and atmospheric circulation variables derived from sea-level pressure and wind reanalysis fields. As a result, five weather types (WTs) are presented, able to capture distinct precipitation spatiotemporal patterns, interpretable in terms of salient regional climate features. Second, we undertake the calibration of the TRMM precipitation product using a set of rain gauge stations as reference and scaling and empirical quantile mapping (eQM) as calibration techniques. Furthermore, we build upon the weather-type classification to compare the results with a WTconditioned calibration approach. Overall, our results underpin the need of adjusting the existing TRMM biases, mostly relevant for the upper tail of their distribution, and advocate the use of correction techniques able to deal with quantile-dependent biases-such as eQM-instead of a simple scaling, in order to obtain a more realistic representation of extreme precipitation events. The conditioning has shown only a marginal added value over the simple approach, although this minor improvement may prove relevant for applications focused on extreme event analysis. Furthermore, the weather types created can be applied to a wide variety of conditioned analyses in this region.es_ES
dc.description.sponsorshipAFRICULTURES, Grant/Award Number: 774652; Beach4Cast, Grant/Award Number: PID2019-107053RB-I00; CORDyS, Grant/Award Number: PID2020-116595RB-I00; INDECIS, Grant/Award Number: 690462es_ES
dc.format.extent18 p.es_ES
dc.language.isoenges_ES
dc.publisherJohn Wiley and Sons Ltdes_ES
dc.rightsAttribution 4.0 Internationales_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceInternational Journal of Climatology, 2023, 43(2), 1193-1210es_ES
dc.subject.otherConditioned calibrationes_ES
dc.subject.otherExtreme precipitationes_ES
dc.subject.otherK-means clusteringes_ES
dc.subject.otherPrincipal component analysises_ES
dc.subject.otherQuantile mappinges_ES
dc.titleWeather-type-conditioned calibration of Tropical Rainfall Measuring Mission precipitation over the South Pacific Convergence Zonees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1002/joc.7905es_ES
dc.rights.accessRightsopenAccesses_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/774652/EU/Enhancing Food Security in AFRIcan AgriCULTUral Systems with the Support of REmote Sensing/AFRICULTURES/es_ES
dc.identifier.DOI10.1002/joc.7905
dc.type.versionpublishedVersiones_ES


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Attribution 4.0 InternationalExcepto si se señala otra cosa, la licencia del ítem se describe como Attribution 4.0 International