| Campo DC | Valor | Idioma |
|---|
| dc.contributor.author | Kim, Yong-Tak | - |
| dc.contributor.author | Kwon, Hyun-Han | - |
| dc.contributor.author | Lima, Carlos Henrique Ribeiro | - |
| dc.contributor.author | Sharma, Ashish | - |
| dc.date.accessioned | 2021-11-30T00:46:41Z | - |
| dc.date.available | 2021-11-30T00:46:41Z | - |
| dc.date.issued | 2021-11-06 | - |
| dc.identifier.citation | KIM, Yong-Tak et al. A novel spatial downscaling approach for climate change assessment in regions with sparse ground data networks. Geophysical Research Letters, v. 48, n. 22, e2021GL095729, 2021. DOI: https://doi.org/10.1029/2021GL095729. | pt_BR |
| dc.identifier.uri | https://repositorio.unb.br/handle/10482/42478 | - |
| dc.language.iso | Inglês | pt_BR |
| dc.publisher | Wiley | pt_BR |
| dc.rights | Acesso Aberto | pt_BR |
| dc.title | A novel spatial downscaling approach for climate change assessment in regions with sparse ground data networks | pt_BR |
| dc.type | Artigo | pt_BR |
| dc.subject.keyword | Mudanças climáticas | pt_BR |
| dc.subject.keyword | Krigagem | pt_BR |
| dc.rights.license | This 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. | pt_BR |
| dc.identifier.doi | https://doi.org/10.1029/2021GL095729 | pt_BR |
| dc.description.abstract1 | This 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. | pt_BR |
| Aparece nas coleções: | Artigos publicados em periódicos e afins
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