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Continental evaluation of GPM IMERG V07B precipitation on a sub-daily scale

Jinghua Xiong, Guoqiang Tang, Yuting Yang

2025Remote Sensing of Environment23 citationsDOIOpen Access PDF

Abstract

Satellite-based precipitation products have significantly advanced applications in hydrology, climate science, and related fields. Despite the significant role of the Global Precipitation Measurement (GPM) mission in monitoring global precipitation dynamics over the past decade, its performance on sub-daily time scales remains insufficiently explored on a global scale. This study provides a continental assessment of the Integrated Multi-satellitE Retrievals for GPM (IMERG) V07B Final Run using extensive hourly ground observations across contiguous United States (CONUS), West Europe, and East Asia. The results demonstrate that IMERG captures precipitation amounts with reasonable accuracy, yielding a median Kling–Gupta efficiency of 0.31 and a median relative bias of 7 %. This bias is primarily attributed to overestimated precipitation frequency and underestimated intensity. However, its performance varies significantly with seasons, land surface attributes, and precipitation types, with better performance generally observed in spring and fall, as well as in temperate and humid climates, and low-altitude regions. While IMERG performs well in detecting moderate precipitation, it struggles with drizzle and moderate-to-extreme events, particularly those exceeding 5 mm/h. Additionally, diurnal performance variability is evident, with the highest accuracy observed in the morning (0600–0900) and the lowest in the afternoon (1400–1700). These findings underscore the variable performance of IMERG and highlight the need for further improvements, especially in capturing extreme precipitation in regions with complex geo-topographic conditions.

Topics & Concepts

Global Precipitation MeasurementRemote sensingPrecipitationEnvironmental scienceScale (ratio)MeteorologyGeologyGeographyCartographyPrecipitation Measurement and AnalysisMeteorological Phenomena and SimulationsSoil Moisture and Remote Sensing
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