干旱区生态环境知识资源中心(Arid): Performance of Multiple Satellite Precipitation Estimates over a Typical Arid Mountainous Area of China: Spatiotemporal Patterns and Extremes

Arid

DOI	10.1175/JHM-D-19-0167.1
	Performance of Multiple Satellite Precipitation Estimates over a Typical Arid Mountainous Area of China: Spatiotemporal Patterns and Extremes
	Chen, Cheng; Li, Zhe; Song, Yina; Duan, Zheng; Mo, Kangle; Wang, Zhiyuan; Chen, Qiuwen
通讯作者	Chen, QW
来源期刊	JOURNAL OF HYDROMETEOROLOGY
ISSN	1525-755X
EISSN	1525-7541
出版年	2020
卷号	21 期号:3 页码:533-550
英文摘要	Precipitation in arid mountainous areas is characterized by low rainfall intensity and large spatial heterogeneity, which challenges satellite-based monitoring by the spaceborne sensors. This study aims to comparatively evaluate the detection ability of spatiotemporal patterns and extremes of rainfall by a range of mainstream satellite precipitation products [TMPA, Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS), and PERSIANN-Climate Data Record (PERSIANN-CDR)] over a typical arid mountainous basin of China, benchmarking against rain gauge data from 2000 to 2015. Results showed that satellite precipitation estimates had relatively low accuracy at the daily scale, while a significant improvement of correlation coefficient (CC;>0.6) and a significant reduction of relative root-mean-square error (RRMSE;<1.0) were found as time scale increases beyond the monthly scale. CHIRPS tended to overestimate the gauge precipitation with positive relative bias (RB), while the negative RB values for TMPA and PERSIANN-CDR indicated there was an underestimation. CHIRPS had the most similar spatial pattern and slope trends of the seasonal precipitation and interannual variations of annual precipitation with gauge observations. With the increase in rainfall rates, the probability of detection (POD) and critical success index (CSI) were reduced and the false alarm ratio ( FAR) was increased significantly, demonstrating the limited capability for all the three satellite products for detecting heavy rainfall events. CHIRPS showed the best performance in detecting rainfall extremes compared to TMPA and PERSIANN-CDR, evidenced by the larger CSI values and similar extreme rainfall indices obtained from gauge records. This study provides valuable guidance for choosing satellite precipitation products instead of gauge observations for rainfall monitoring (especially rainfall extremes) and agricultural production management over arid mountainous area.
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000559755400005
WOS关键词	HYDROLOGIC APPLICATIONS ; MULTISCALE EVALUATION ; RIVER-BASIN ; PRODUCTS ; TMPA ; MICROWAVE ; MISSION ; EVENTS ; SCALES ; TREND
WOS类目	Meteorology & Atmospheric Sciences
WOS研究方向	Meteorology & Atmospheric Sciences
来源机构	南京大学 ; 河海大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/325626
作者单位	[Chen, Cheng; Mo, Kangle; Wang, Zhiyuan; Chen, Qiuwen] Nanjing Hydraul Res Inst, State Key Lab Hydrol Water Resources & Hydraul En, Nanjing, Peoples R China; [Chen, Cheng] Hohai Univ, Coll Water Conservancy & Hydroelect Power, Nanjing, Peoples R China; [Chen, Cheng; Mo, Kangle; Wang, Zhiyuan; Chen, Qiuwen] Nanjing Hydraul Res Inst, Ctr Ecoenvironm Res, Nanjing, Peoples R China; [Li, Zhe] Univ Wisconsin, Dept Civil & Environm Engn, Madison, WI 53706 USA; [Song, Yina] Nanjing Univ, Sch Geog & Ocean Sci, Dept Geog Informat Sci, Nanjing, Peoples R China; [Duan, Zheng] Lund Univ, Dept Phys Geog & Ecosyst Sci, Lund, Sweden
推荐引用方式 GB/T 7714	Chen, Cheng,Li, Zhe,Song, Yina,et al. Performance of Multiple Satellite Precipitation Estimates over a Typical Arid Mountainous Area of China: Spatiotemporal Patterns and Extremes[J]. 南京大学, 河海大学,2020,21(3):533-550.
APA	Chen, Cheng.,Li, Zhe.,Song, Yina.,Duan, Zheng.,Mo, Kangle.,...&Chen, Qiuwen.(2020).Performance of Multiple Satellite Precipitation Estimates over a Typical Arid Mountainous Area of China: Spatiotemporal Patterns and Extremes.JOURNAL OF HYDROMETEOROLOGY,21(3),533-550.
MLA	Chen, Cheng,et al."Performance of Multiple Satellite Precipitation Estimates over a Typical Arid Mountainous Area of China: Spatiotemporal Patterns and Extremes".JOURNAL OF HYDROMETEOROLOGY 21.3(2020):533-550.