Title
Accuracy of CHIRPS Satellite-Rainfall Products over Mainland China.
Abstract
Precipitation is the main component of global water cycle. At present, satellite quantitative precipitation estimates (QPEs) are widely applied in the scientific community. However, the evaluations of satellite QPEs have some limitations in terms of the deficiency in observation, evaluation methodology, the selection of time windows for evaluation and short periods for evaluation. The objective of this work is to make some improvements by evaluating the spatio-temporal pattern of the long-terms Climate Hazard Group InfraRed Precipitation Satellite's (CHIRPS's) QPEs over mainland China. In this study, we compared the daily precipitation estimates from CHIRPS with 2480 rain gauges across China and gridded observation using several statistical metrics in the long-term period of 1981-2014. The results show that there is significant difference between point evaluation and grid evaluation for CHIRPS. CHIRPS has better performance for a large amount of precipitation than it does for arid and semi-arid land. The change in good performance zones has strong relationship with monsoon's movement. Therefore, CHIRPS performs better in river basins of southern China and exhibits poor performance in river basins in northwestern and northern China. Moreover, CHIRPS exhibits better in warm season than in Winter, owing to its limited ability to detect snowfall. Nevertheless, CHIRPS is moderately sensitive to the precipitation from typhoon weather systems. The limitations for CHIRPS result from the Tropical Rainfall Measuring Mission (TRMM) 3B42 estimates' accuracy and valid spatial coverage.
Year
DOI
Venue
2018
10.3390/rs10030362
REMOTE SENSING
Keywords
Field
DocType
CN05.1,ungauged regions,PBias,CFSR,River Basin
Monsoon,Satellite,Typhoon,Drainage basin,Arid,Remote sensing,Climatology,Geology,Water cycle,Snow,Precipitation
Journal
Volume
Issue
ISSN
10
3
2072-4292
Citations 
PageRank 
References 
3
0.49
8
Authors
5
Name
Order
Citations
PageRank
Lei Bai130.83
Chunxiang Shi231.17
Lanhai Li331.85
Yanfen Yang430.83
Jing Wu530.49