干旱区生态环境知识资源中心(Arid): Evaluating the performance of global precipitation products for precipitation and extreme precipitation in arid and semiarid China

Arid

DOI	10.1016/j.jag.2024.103888
	Evaluating the performance of global precipitation products for precipitation and extreme precipitation in arid and semiarid China
	Yang, Liu; Shi, Zhengguo; Liu, Rui; Xing, Mengdao
通讯作者	Xing, MD
来源期刊	INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
ISSN	1569-8432
EISSN	1872-826X
出版年	2024
卷号	130
英文摘要	Arid and semiarid areas account for more than half of China, have fragile ecological environments, are sensitive to global climate change and human activities. Due to the advantages of wide coverage and high resolution, multi-sources remote sensing precipitation products play an important role in monitoring precipitation in areas where rainfall gauges are scarce. Therefore, evaluating the performance of different precipitation products becomes very important. Here, the annual and daily average precipitation data from different precipitation products in China were analyzed from 2000 to 2020. Nine precipitation datasets are included: two reanalysis datasets and seven remote sensing datasets. The results show that CHIRPS (Climate Hazards group Infrared Precipitation with Stations) is the best product for precipitation in arid and semiarid China, and the mean annual precipitation correlation coefficient between CHIRPS and observed data is 0.82. CPC (CPC Global Unified Gauge-Based Analysis of Daily Precipitation) shows less dispersion and deviation in the daily precipitation, and the correlation coefficient between CPC and CN05 (observation data) daily precipitation is 0.92. In addition, the performance of precipitation products is tailored to local conditions, with MSWEP (Multi-source weighted-Ensemble Precipitation) evaluating precipitation poorly in Northwestern China but better in the areas with more precipitation. Extreme precipitation in China has shown an increasing trend in the last 20 years, with a very significant increasing trend in extreme precipitation in semi-arid areas and a constant trend in extreme precipitation in arid areas. The PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) is the best product for extreme precipitation in arid and semiarid China.
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:001292536900001
WOS关键词	CLIMATE-CHANGE ; TEMPERATURE ; DATASET ; REGION ; CMORPH
WOS类目	Remote Sensing
WOS研究方向	Remote Sensing
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/404196
推荐引用方式 GB/T 7714	Yang, Liu,Shi, Zhengguo,Liu, Rui,et al. Evaluating the performance of global precipitation products for precipitation and extreme precipitation in arid and semiarid China[J],2024,130.
APA	Yang, Liu,Shi, Zhengguo,Liu, Rui,&Xing, Mengdao.(2024).Evaluating the performance of global precipitation products for precipitation and extreme precipitation in arid and semiarid China.INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,130.
MLA	Yang, Liu,et al."Evaluating the performance of global precipitation products for precipitation and extreme precipitation in arid and semiarid China".INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 130(2024).