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DOI | 10.1175/JCLI-D-17-0765.1 |
Climate Model Biases and Modification of the Climate Change Signal by Intensity-Dependent Bias Correction | |
Ivanov, Martin Aleksandrov1; Luterbacher, Juerg1,2; Kotlarski, Sven3 | |
2018-08-01 | |
发表期刊 | JOURNAL OF CLIMATE
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ISSN | 0894-8755 |
EISSN | 1520-0442 |
出版年 | 2018 |
卷号 | 31期号:16页码:6591-6610 |
文章类型 | Article |
语种 | 英语 |
国家 | Germany; Switzerland |
英文摘要 | Climate change impact research and risk assessment require accurate estimates of the climate change signal (CCS). Raw climate model data include systematic biases that affect the CCS of high-impact variables such as daily precipitation and wind speed. This paper presents a novel, general, and extensible analytical theory of the effect of these biases on the CCS of the distribution mean and quantiles. The theory reveals that misrepresented model intensities and probability of nonzero (positive) events have the potential to distort raw model CCS estimates. We test the analytical description in a challenging application of bias correction and downscaling to daily precipitation over alpine terrain, where the output of 15 regional climate models (RCMs) is reduced to local weather stations. The theoretically predicted CCS modification well approximates the modification by the bias correction method, even for the station-RCM combinations with the largest absolute modifications. These results demonstrate that the CCS modification by bias correction is a direct consequence of removing model biases. Therefore, provided that application of intensity-dependent bias correction is scientifically appropriate, the CCS modification should be a desirable effect. The analytical theory can be used as a tool to 1) detect model biases with high potential to distort the CCS and 2) efficiently generate novel, improved CCS datasets. The latter are highly relevant for the development of appropriate climate change adaptation, mitigation, and resilience strategies. Future research needs to focus on developing process-based bias corrections that depend on simulated intensities rather than preserving the raw model CCS. |
英文关键词 | Atmosphere Climate change Climatology Bias Statistics Policy |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000439094900001 |
WOS关键词 | SIMULATIONS |
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/20247 |
专题 | 气候变化 |
作者单位 | 1.Justus Liebig Univ Giessen, Dept Geog Climatol Climate Dynam & Climate Change, Giessen, Germany; 2.Justus Liebig Univ Giessen, Ctr Int Dev & Environm Res, Giessen, Germany; 3.Swiss Fed Off Meteorol & Climatol, Zurich, Switzerland |
推荐引用方式 GB/T 7714 | Ivanov, Martin Aleksandrov,Luterbacher, Juerg,Kotlarski, Sven. Climate Model Biases and Modification of the Climate Change Signal by Intensity-Dependent Bias Correction[J]. JOURNAL OF CLIMATE,2018,31(16):6591-6610. |
APA | Ivanov, Martin Aleksandrov,Luterbacher, Juerg,&Kotlarski, Sven.(2018).Climate Model Biases and Modification of the Climate Change Signal by Intensity-Dependent Bias Correction.JOURNAL OF CLIMATE,31(16),6591-6610. |
MLA | Ivanov, Martin Aleksandrov,et al."Climate Model Biases and Modification of the Climate Change Signal by Intensity-Dependent Bias Correction".JOURNAL OF CLIMATE 31.16(2018):6591-6610. |
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