Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2020GL092058 |
Spatial, temporal, and multivariate bias in regional climate model simulations | |
Youngil Kim; Jason P. Evans; Ashish Sharma; Eytan Rocheta | |
2021-06-01 | |
发表期刊 | Geophysical Research Letters
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出版年 | 2021 |
英文摘要 | Correction of atmospheric variables to remove systematic biases in GCM simulations prior to downscaling offers a means of improving climate simulation accuracy in climate change impact assessments. Various mathematical approaches have been used to correct the lateral and lower boundary conditions of regional climate models (RCMs). Most of these techniques correct only the magnitude of each variable individually over time without regard to spatial and multivariate bias. Here we investigate how well a RCM is able to reproduce the dependence of an observed variable based on three aspects: temporal, spatial, and multivariate. Results show that the RCM simulations with univariate bias corrected GCM boundary conditions perform well in capturing both temporal and spatial dependence. However, all RCM simulations do not show improvement in the representation of dependence between variables, indicating the need for alternatives that correct systematic biases in multivariate dependence in both lateral and lower boundary conditions. |
领域 | 气候变化 |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/329769 |
专题 | 气候变化 |
推荐引用方式 GB/T 7714 | Youngil Kim,Jason P. Evans,Ashish Sharma,et al. Spatial, temporal, and multivariate bias in regional climate model simulations[J]. Geophysical Research Letters,2021. |
APA | Youngil Kim,Jason P. Evans,Ashish Sharma,&Eytan Rocheta.(2021).Spatial, temporal, and multivariate bias in regional climate model simulations.Geophysical Research Letters. |
MLA | Youngil Kim,et al."Spatial, temporal, and multivariate bias in regional climate model simulations".Geophysical Research Letters (2021). |
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