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DOI | 10.1175/JCLI-D-16-0654.1 |
Can Bias Correction of Regional Climate Model Lateral Boundary Conditions Improve Low-Frequency Rainfall Variability? | |
Rocheta, Eytan1; Evans, Jason P.2,3; Sharma, Ashish1 | |
2017-12-01 | |
发表期刊 | JOURNAL OF CLIMATE
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ISSN | 0894-8755 |
EISSN | 1520-0442 |
出版年 | 2017 |
卷号 | 30期号:24 |
文章类型 | Article |
语种 | 英语 |
国家 | Australia |
英文摘要 | Global climate model simulations inherently contain multiple biases that, when used as boundary conditions for regional climate models, have the potential to produce poor downscaled simulations. Removing these biases before downscaling can potentially improve regional climate change impact assessment. In particular, reducing the low-frequency variability biases in atmospheric variables as well as modeled rainfall is important for hydrological impact assessment, predominantly for the improved simulation of floods and droughts. The impact of this bias in the lateral boundary conditions driving the dynamical downscaling has not been explored before. Here the use of three approaches for correcting the lateral boundary biases including mean, variance, and modification of sample moments through the use of a nested bias correction (NBC) method that corrects for low-frequency variability bias is investigated. These corrections are implemented at the 6-hourly time scale on the global climate model simulations to drive a regional climate model over the Australian Coordinated Regional Climate Downscaling Experiment (CORDEX) domain. The results show that the most substantial improvement in low-frequency variability after bias correction is obtained from modifying the mean field, with smaller changes attributed to the variance. Explicitly modifying monthly and annual lag-1 autocorrelations through NBC does not substantially improve low-frequency variability attributes of simulated precipitation in the regional model over a simpler mean bias correction. These results raise questions about the nature of bias correction techniques that are required to successfully gain improvement in regional climate model simulations and show that more complicated techniques do not necessarily lead to more skillful simulation. |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000423492500001 |
WOS关键词 | SYSTEMATIC BIASES ; SIMULATIONS ; UNCERTAINTY ; CONVECTION ; RESOLUTION ; WEATHER ; WELL ; RAW ; ERA |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
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/20635 |
专题 | 气候变化 |
作者单位 | 1.Univ New South Wales, Sch Civil & Environm Engn, Sydney, NSW, Australia; 2.Univ New South Wales, Climate Change Res Ctr, Sydney, NSW, Australia; 3.Univ New South Wales, ARC Ctr Excellence Climate Syst Sci, Sydney, NSW, Australia |
推荐引用方式 GB/T 7714 | Rocheta, Eytan,Evans, Jason P.,Sharma, Ashish. Can Bias Correction of Regional Climate Model Lateral Boundary Conditions Improve Low-Frequency Rainfall Variability?[J]. JOURNAL OF CLIMATE,2017,30(24). |
APA | Rocheta, Eytan,Evans, Jason P.,&Sharma, Ashish.(2017).Can Bias Correction of Regional Climate Model Lateral Boundary Conditions Improve Low-Frequency Rainfall Variability?.JOURNAL OF CLIMATE,30(24). |
MLA | Rocheta, Eytan,et al."Can Bias Correction of Regional Climate Model Lateral Boundary Conditions Improve Low-Frequency Rainfall Variability?".JOURNAL OF CLIMATE 30.24(2017). |
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