干旱区生态环境知识资源中心(Arid): Correcting GPM IMERG precipitation data over the Tianshan Mountains in China

Arid

DOI	10.1016/j.jhydrol.2019.06.019
	Correcting GPM IMERG precipitation data over the Tianshan Mountains in China
	Lu, Xinyu 1; Tang, Guoqiang 2; Wang, Xiuqin 3; Liu, Yan 1; Jia, Lihong 4; Xie, Guohui 3; Li, Shuai 1; Zhang, Yingxin 1
通讯作者	Tang, Guoqiang
来源期刊	JOURNAL OF HYDROLOGY
ISSN	0022-1694
EISSN	1879-2707
出版年	2019
卷号	575 页码:1239-1252
英文摘要	Point-scale gauge observations have inherent limitations, making it difficult to study the spatial and temporal distributions of precipitation in alpine regions due to gauge undercatch and complex terrains. The Global Precipitation Measurement (GPM) mission provides new-generation satellite precipitation products that are promising alternative data sources in mountainous areas. However, quality evaluations and bias corrections should be conducted prior to the application of satellite data. In this study, an unprecedentedly dense ground station network composed of more than 1000 automatic weather stations (AWSs) over the Tianshan Mountains in China are used for bias correction of the Integrated Multisatellite Retrievals for GPM (IMERG) product. First, universal kriging interpolation is used to downscale IMERG from 0.1 degrees to 500 m to ensure a fair comparison with the gauge observations. Then, the downscaled IMERG precipitation data over this region are corrected by two methods, i.e., stepwise regression (STEP) and geographically weighted regression (GWR). Both methods are established on various terrain factors and vegetation indexes that have strong relations with precipitation. The results show that (1) GWR outperform the conventional STEP method as well as the original IMERG; (2) the original IMERG performs best over the plain region (less than 1000 m), while the best correction effect was found in middle and low-elevation region (1000-1500 m); and (3) the performance of the GWR model is largely dependent on the number of available training stations in mountainous areas. Overall, the methods and results presented in this study provide insight into the correction of satellite precipitation data in mountainous areas with scarce ground observations.
英文关键词	Precipitation correction IMERG Geographically weighted regression Stepwise regression Tianshan Mountains
类型	Article
语种	英语
国家	Peoples R China
收录类别	SCI-E
WOS记录号	WOS:000488143000097
WOS关键词	GEOGRAPHICALLY WEIGHTED REGRESSION ; TIBETAN PLATEAU ; DOWNSCALING ALGORITHM ; DAY-1 IMERG ; ARID REGION ; PRODUCTS ; MULTISATELLITE ; TMPA ; RESOLUTION ; TRMM
WOS类目	Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向	Engineering ; Geology ; Water Resources
来源机构	清华大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/217168
作者单位	1.China Meteorol Adm, Inst Desert Meteorol, Urumqi, Peoples R China; 2.Tsinghua Univ, Dept Hydraul Engn, State Key Lab Hydrosci & Engn, Beijing, Peoples R China; 3.Xinjiang Meteorol Bur, Urumqi, Peoples R China; 4.Xinjiang Meteorol Observ, Urumqi, Peoples R China
推荐引用方式 GB/T 7714	Lu, Xinyu,Tang, Guoqiang,Wang, Xiuqin,et al. Correcting GPM IMERG precipitation data over the Tianshan Mountains in China[J]. 清华大学,2019,575:1239-1252.
APA	Lu, Xinyu.,Tang, Guoqiang.,Wang, Xiuqin.,Liu, Yan.,Jia, Lihong.,...&Zhang, Yingxin.(2019).Correcting GPM IMERG precipitation data over the Tianshan Mountains in China.JOURNAL OF HYDROLOGY,575,1239-1252.
MLA	Lu, Xinyu,et al."Correcting GPM IMERG precipitation data over the Tianshan Mountains in China".JOURNAL OF HYDROLOGY 575(2019):1239-1252.