A novel spatial downscaling approach for climate change assessment in regions with sparse ground data networks

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Autor(es): dc.creatorKim, Yong-Tak-
Autor(es): dc.creatorKwon, Hyun-Han-
Autor(es): dc.creatorLima, Carlos Henrique Ribeiro-
Autor(es): dc.creatorSharma, Ashish-
Data de aceite: dc.date.accessioned2022-02-10T21:10:36Z-
Data de disponibilização: dc.date.available2022-02-10T21:10:36Z-
Data de envio: dc.date.issued2021-11-29-
Data de envio: dc.date.issued2021-11-29-
Data de envio: dc.date.issued2021-11-05-
Fonte completa do material: dc.identifierhttps://repositorio.unb.br/handle/10482/42478-
Fonte completa do material: dc.identifierhttps://doi.org/10.1029/2021GL095729-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/647148-
Descrição: dc.descriptionThis study proposes a novel approach that expands the existing QDM (quantile delta mapping) to address spatial bias, using Kriging within a Bayesian framework to assess the impact of using a point reference field. Our focus here is to spatially downscale daily rainfall sequences simulated by regional climate models (RCMs), coupled to the proposed QDM-spatial bias-correction, in which the distribution parameters are first interpolated onto a fine grid (rather than the observed daily rainfall). The proposed model is validated through a cross-validatory (CV) evaluation using rainfall data from a set of weather stations in South Korea and climate change scenarios simulated by three alternate RCMs. The results demonstrate the efficacy of the proposed model to simulate the bias-corrected daily rainfall sequences over large regions at fine resolutions. A discussion of the potential use of the proposed approach in the field of hydrometeorology is also offered.-
Formato: dc.formatapplication/pdf-
Publicador: dc.publisherWiley-
Direitos: dc.rightsAcesso Aberto-
Direitos: dc.rightsThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.-
Palavras-chave: dc.subjectMudanças climáticas-
Palavras-chave: dc.subjectKrigagem-
Título: dc.titleA novel spatial downscaling approach for climate change assessment in regions with sparse ground data networks-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional – UNB

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