Statistical Bias Correction for Simulated Wind Speeds Over CORDEX-East Asia

doi:10.1029/2018EA000493

CORC > 海洋研究所 > 中国科学院海洋研究所 > 海洋环流与波动重点实验室

	Statistical Bias Correction for Simulated Wind Speeds Over CORDEX-East Asia
	Li, Delei 1,2,3; Feng, Jianlong 4; Xu, Zhenhua 1,2,3; Yin, Baoshu 1,2,3,5; Shi, Hongyuan 6; Qi, Jifeng 1,2,3
刊名	EARTH AND SPACE SCIENCE
	2019-02-01
卷号	6 期号:2 页码:200-211
ISSN号	2333-5084
DOI	10.1029/2018EA000493
通讯作者	Xu, Zhenhua(xuzhenhua@qdio.ac.cn) ; Yin, Baoshu(bsyin@qdio.ac.cn)
英文摘要	Surface 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.
资助项目	National 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研究方向	Astronomy & Astrophysics ; Geology
语种	英语
出版者	AMER GEOPHYSICAL UNION
WOS记录号	WOS:000460720500001
内容类型	期刊论文
源URL	[http://ir.qdio.ac.cn/handle/337002/155295]
专题	海洋研究所_海洋环流与波动重点实验室
通讯作者	Xu, Zhenhua; Yin, Baoshu
作者单位	1.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
推荐引用方式 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.