Acta Geographica Sinica ›› 2019, Vol. 74 ›› Issue (7): 1305-1318.doi: 10.11821/dlxb201907003

• Climate Change and Surface Processes • Previous Articles     Next Articles

Evaluation of the GPM-based IMERG and GSMaP precipitation estimates over the Sichuan region

ZENG Suikang1,2,YONG Bin1,2()   

  1. 1.State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China
    2.School of Earth Sciences and Engineering, Hohai University, Nanjing 211100, China
  • Received:2018-12-03 Revised:2019-04-23 Online:2019-07-25 Published:2019-07-23
  • Contact: YONG Bin E-mail:yongbin_hhu@126.com
  • Supported by:
    National Key R&D Program of China(2018YFA0605402)

Abstract:

The Integrated Multi-satellitE Retrievals for GPM (IMERG) and Global Satellite Mapping of Precipitation (GSMaP) are two high precisely multi-satellite precipitation estimates in the GPM era. In order to evaluate the applicability of both IMERG and GSMaP series products (IMERG_Uncal and IMERG_Cal, GSMaP_MVK and GSMaP_Gauge) over the Sichuan region in China, six statistical indices are used to systematically analyze the error characteristics of these products, benchmarked by a set of ground-based dataset from China Meterological Administration (CMA). Results show that: (1) All products show the dramatic regional difference over Sichuan at both daily and hourly scales. The GSMaP series products overestimate precipitation and the most overestimations occur over the high altitude areas located in the Western Sichuan. GSMaP_Gauge shows relatively higher correlation coefficient and lower relative bias and root mean square error due to the employment of gauge-based adjustments. On the contrary, IMERG_Uncal shows underestimation over the mountainous areas, while the relatively slight overestimation appears in the basin area with lower elevation at both daily and hourly time scales, suggesting that gauge-calibrated dataset IMERG_Cal has effectively improved the relative bias in the mountainous areas but not in the flat basin area. (2) By synthesizing the three classified statistical indices, IMERG series products exhibit better potentials in detecting precipitation events. Although GSMaP_Gauge shows a higher hit rate of precipitation, it has more false alarm ratios of precipitation. All products show better hit rate and lower false alarm rate over basin area and southern Sichuan. Furthermore, it is found that the ground-based dataset has some errors in those areas without meteorological stations, which leads to the apparent uncertainty in assessing the accuracy of satellite precipitation products over the Northwest Sichuan Plateau. (3) IMERG_Cal performs better in capturing the rainfall amounts and events compared with other products, especially for the lowest and highest rainfall intensity ranges, demonstrating its application potential for monitoring the extreme weather events. Overall, both IMERG and GSMaP estimates have relatively high uncertainties over the mountainous areas than ones over the flat basin areas. Additionally, the gauge-calibrated products obviously outperform the uncalibrated datasets. On the basis of the findings, future efforts focus on reducing and correcting the errors and biases of satellite precipitation estimates by considering both spatio-temporal characteristics and the topographical information.

Key words: IMERG, GSMaP, satellite precipitation products, Sichuan, error characteristics, terrain