A Novel Spatial Downscaling Approach for Climate Change Assessment in Regions With Sparse Ground Data Networks

Autor:	Yong-Tak Kim, Ashish Sharma, Carlos H.R. Lima, Hyun-Han Kwon
Rok vydání:	2021
Předmět:	Computer science Krigagem Climate change assessment Geophysics Kriging Climatology Climate change scenario Mudanças climáticas General Earth and Planetary Sciences Point (geometry) Climate model Downscaling Spatial bias Quantile
Zdroj:	Repositório Institucional da UnB Universidade de Brasília (UnB) instacron:UNB
ISSN:	1944-8007 0094-8276
DOI:	10.1029/2021gl095729
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::792ab0efb4b275fcd398884ef23dd45c https://doi.org/10.1029/2021gl095729 Zobrazit plný text záznamu Plný text