000163289 001__ 163289
000163289 005__ 20251024172259.0
000163289 0247_ $$2doi$$a10.1016/j.envsoft.2025.106717
000163289 0248_ $$2sideral$$a145748
000163289 037__ $$aART-2025-145748
000163289 041__ $$aeng
000163289 100__ $$aHuerta, Adrian
000163289 245__ $$aEnhancing daily precipitation reconstruction: An improved version of the reddPrec R package
000163289 260__ $$c2025
000163289 5060_ $$aAccess copy available to the general public$$fUnrestricted
000163289 5203_ $$aReconstructing high-quality daily precipitation series is essential for climate studies, hydrological modeling, and environmental applications. This work presents a new version of reddPrec, a versatile and flexible R package designed to reconstruct precipitation datasets through standard quality control, gap-filling, and grid creation procedures. The update introduces greater flexibility in spatial modeling, inclusion of dynamic covariates, and new modules for enhanced quality control and homogenization. Daily precipitation can now be predicted using machine learning approaches within a flexible, user-friendly framework, allowing users to select modeling approaches and customize settings. We demonstrate its capabilities through case studies in Switzerland and Spain, evaluating improvements in reconstruction accuracy, quality control, and homogenization. Enhanced quality control and homogenization procedures were specifically validated to ensure reliable adjustment and consistency of precipitation series. Overall, reddPrec provides a comprehensive and reliable tool for reconstructing precipitation series, supporting the creation of high-quality datasets for climate research and related fields.
000163289 536__ $$9info:eu-repo/grantAgreement/ES/MICINN/RYC2021-034330-I
000163289 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000163289 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000163289 700__ $$aBrönnimann, Stefan
000163289 700__ $$0(orcid)0000-0002-7585-3636$$aLuis, Martín de$$uUniversidad de Zaragoza
000163289 700__ $$0(orcid)0000-0002-3974-2947$$aBeguería, Santiago
000163289 700__ $$0(orcid)0000-0001-7663-1202$$aSerrano-Notivoli, Roberto$$uUniversidad de Zaragoza
000163289 7102_ $$13006$$2430$$aUniversidad de Zaragoza$$bDpto. Geograf. Ordenac.Territ.$$cÁrea Geografía Física
000163289 773__ $$g195 (2025), 106717 [12 pp.]$$pEnviron. model. softw.$$tENVIRONMENTAL MODELLING & SOFTWARE$$x1364-8152
000163289 8564_ $$s3528721$$uhttps://zaguan.unizar.es/record/163289/files/texto_completo.pdf$$yVersión publicada
000163289 8564_ $$s2401059$$uhttps://zaguan.unizar.es/record/163289/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000163289 909CO $$ooai:zaguan.unizar.es:163289$$particulos$$pdriver
000163289 951__ $$a2025-10-24-16:56:32
000163289 980__ $$aARTICLE