A Comprehensive Evaluation of Latest GPM IMERG V06 Early, Late and Final Precipitation Products across China

• Published in: Remote Sensing
• Main Authors: Linfei Yu, Guoyong Leng, Andre Python, Jian Peng
• Format: Article
• Language: English
• Published: MDPI AG 2021-03-01
• Subjects: satellite precipitation products; IMERG; accuracy evaluation; rain gauge; China
• Online Access: https://www.mdpi.com/2072-4292/13/6/1208

This study evaluated the performance of the early, late and final runs of IMERG version 06 precipitation products at various spatial and temporal scales in China from 2008 to 2017, against observations from 696 rain gauges. The results suggest that the three IMERG products can well reproduce the spatial patterns of precipitation, but exhibit a gradual decrease in the accuracy from the southeast to the northwest of China. Overall, the three runs show better performances in the eastern humid basins than the western arid basins. Compared to the early and late runs, the final run shows an improvement in the performance of precipitation estimation in terms of correlation coefficient, Kling–Gupta Efficiency and root mean square error at both daily and monthly scales. The three runs show similar daily precipitation detection capability over China. The biases of the three runs show a significantly positive (<i>p</i> < 0.01) correlation with elevation, with higher accuracy observed with an increase in elevation. However, the categorical metrics exhibit low levels of dependency on elevation, except for the probability of detection. Over China and major river basins, the three products underestimate the frequency of no/tiny rain events (<i>P</i> < 0.1 mm/day) but overestimate the frequency of light rain events (0.1 ≤ <i>P</i> < 10 mm/day). The three products converge with ground-based observation with regard to the frequency of rainstorm (<i>P</i> ≥ 50 mm/day) in the southern part of China. The revealed uncertainties associated with the IMERG products suggests that sustaining efforts are needed to improve their retrieval algorithms in the future.