Abstract

Satellite quantitative precipitation estimation (QPE) can make up for the insufficiency of ground observations for monitoring precipitation. Using an Advanced Geosynchronous Radiation Imager (AGRI) on the FengYun-4A (FY-4A) satellite and rain gauges (RGs) for observations in the summer of 2020. The existing QPE of the FY-4A was evaluated and found to present poor accuracy over the complex topography of Western China. Therefore, to improve the existing QPE, first, cloud classification thresholds for the FY-4A were established with the dynamic clustering method to identify convective clouds. These thresholds consist of the brightness temperatures (TBs) of FY-4A water vapor and infrared channels, and their TB difference. Then, quantitative cloud growth rate correction factors were introduced to improve the QPE of the convective-stratiform technique. This was achieved using TB hourly variation rates of long-wave infrared channel 12, which is able to characterize the evolution of clouds. Finally, the dynamic time integration method was designed to solve the inconsistent time matching between the FY-4A and RGs. Consequently, the QPE accuracy of the FY-4A was improved. Compared with the existing QPE of the FY-4A, the correlation coefficient between the improved QPE of the FY-4A and the RG hourly precipitation increased from 0.208 to 0.492, with the mean relative error and root mean squared error decreasing from −47.4% and 13.78 mm to 8.3% and 10.04 mm, respectively. However, the correlation coefficient is not sufficiently high; thus, the algorithm needs to be further studied and improved.

Highlights

  • IntroductionPrecipitation plays an important role in the interaction of the hydrosphere, atmosphere and biosphere [1,2,3,4]; its uneven spatial and temporal distribution often lead to extreme weather events such as rainstorms and drought, which have a serious impact on human activities [5,6,7]

  • To validate the real-time quantitative precipitation estimation (QPE) of the FY-4A Advanced Geosynchronous Radiation Imager (AGRI) provided by NSMC, Figure 2 presents the comparison between rain gauges (RGs) hourly precipitation and NSMC QPE of the FY-4A AGRI from

  • QPE of the FY-4A is a national product that focuses on the whole national region and lacks specific validation over complex topography

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Summary

Introduction

Precipitation plays an important role in the interaction of the hydrosphere, atmosphere and biosphere [1,2,3,4]; its uneven spatial and temporal distribution often lead to extreme weather events such as rainstorms and drought, which have a serious impact on human activities [5,6,7]. It is vital to obtain accurate and timely spatial-temporal information of precipitation for meteorological study, flash flood monitoring, water resource management, climatological modeling and assessing groundwater storage [8,9,10]. The accurate acquisition of precipitation intensity and accumulated precipitation is conducive to understanding the global water cycle and the energy balance of the Earth system [11]

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