IOCAS-IR  > 海洋环流与波动重点实验室
Statistical Bias Correction for Simulated Wind Speeds Over CORDEX-East Asia
Li, Delei1,2,3; Feng, Jianlong4; Xu, Zhenhua1,2,3; Yin, Baoshu1,2,3,5; Shi, Hongyuan6; Qi, Jifeng1,2,3
2019-02-01
Source PublicationEARTH AND SPACE SCIENCE
ISSN2333-5084
Volume6Issue:2Pages:200-211
Corresponding AuthorXu, Zhenhua(xuzhenhua@qdio.ac.cn) ; Yin, Baoshu(bsyin@qdio.ac.cn)
AbstractSurface wind is significant for ocean state climate, ocean mixing, and viability of wind energy techniques. However, surface wind simulated from the regional climate model generally features substantial bias from observation. For the first time, this study compares the performance of five bias correction techniques, (1) linear scaling, (2) variance scaling, (3) quantile mapping based on empirical distribution, (4) quantile mapping based on Weibull distribution, and (5) cumulative distribution functions transformation, in reducing the statistical bias of a regional climate model wind output, which was downscaled from a global climate model CNRM-CM5 during 1991-2000. The surface wind of JRA55 reanalysis data is used as reference. Results show that all bias correction methods are consistent in reducing the climatological mean bias in spatial patterns and intensities. The linear scaling method always performs the worst among all methods in correcting higher-order statistical biases such as skewness, kurtosis, and wind power density. The other four bias correction methods are generally similar in reducing the statistical biases of different measures based on spatial distribution maps. However, when it comes to spatial averaged mean of statistical measures over CORDEX-East Asia in January and July, the quantile mapping based on Weibull distribution generally shows the best skills among all methods in bias reduction. Plain Language Summary In the current stage, global climate model or regional climate model simulations generally feature substantial bias relative to observations, leading to an inaccurate assessment of climate change or inaccurate inputs for impact models. For the first time, we have compared five bias correction methods using various statistical measures to find out the most robust method for correcting statistical properties of simulated winds from regional climate model. Results show that the linear scaling method always performs the worst among all methods in correcting higher-order statistical biases of simulated winds. On average, the quantile mapping based on Weibull distribution shows the best skills among all methods in bias reduction in January and July. This study is of importance for climate change assessment of wind as well as deriving accurate wind forcing for driving ocean model.
DOI10.1029/2018EA000493
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41706019] ; National Natural Science Foundation of China[41706020] ; National Natural Science Foundation of China[91858103] ; Strategic Pioneering Research Program of CAS[XDA22050202] ; Strategic Pioneering Research Program of CAS[XDA19060202] ; National Key Research and Development Program of China[2017YFA0604101] ; National Key Research and Development Program of China[2017YFA0604102] ; China Postdoctoral Science Foundation[2017M612357] ; China Postdoctoral Science Foundation[2017T100520]
WOS Research AreaAstronomy & Astrophysics ; Geology
WOS SubjectAstronomy & Astrophysics ; Geosciences, Multidisciplinary
WOS IDWOS:000460720500001
PublisherAMER GEOPHYSICAL UNION
Citation statistics
Document Type期刊论文
Identifierhttp://ir.qdio.ac.cn/handle/337002/155296
Collection海洋环流与波动重点实验室
Corresponding AuthorXu, Zhenhua; Yin, Baoshu
Affiliation1.Chinese Acad Sci, Inst Oceanol, CAS Key Lab Ocean Circulat & Waves, Qingdao, Peoples R China
2.Chinese Acad Sci, Ctr Ocean Megasci, Qingdao, Peoples R China
3.Pilot Natl Lab Marine Sci & Technol Qingdao, Qingdao, Peoples R China
4.Tianjin Univ Sci & Technol, Coll Marine & Environm Sci, Tianjin, Peoples R China
5.Univ Chinese Acad Sci, Coll Earth & Planetary Sci, Beijing, Peoples R China
6.Ludong Univ, Sch Civil Engn, Yantai, Peoples R China
First Author AffilicationInstitute of Oceanology, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Oceanology, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Li, Delei,Feng, Jianlong,Xu, Zhenhua,et al. Statistical Bias Correction for Simulated Wind Speeds Over CORDEX-East Asia[J]. EARTH AND SPACE SCIENCE,2019,6(2):200-211.
APA Li, Delei,Feng, Jianlong,Xu, Zhenhua,Yin, Baoshu,Shi, Hongyuan,&Qi, Jifeng.(2019).Statistical Bias Correction for Simulated Wind Speeds Over CORDEX-East Asia.EARTH AND SPACE SCIENCE,6(2),200-211.
MLA Li, Delei,et al."Statistical Bias Correction for Simulated Wind Speeds Over CORDEX-East Asia".EARTH AND SPACE SCIENCE 6.2(2019):200-211.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Li, Delei]'s Articles
[Feng, Jianlong]'s Articles
[Xu, Zhenhua]'s Articles
Baidu academic
Similar articles in Baidu academic
[Li, Delei]'s Articles
[Feng, Jianlong]'s Articles
[Xu, Zhenhua]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Li, Delei]'s Articles
[Feng, Jianlong]'s Articles
[Xu, Zhenhua]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.