Evaluation of the Integrated Multi-satellitE Retrievals (IMERG) for Global Precipitation Measurement (GPM) mission over the Mainland China at multiple scales

Abstract

Based on the hourly gauge precipitation data from the China Meteorological Administration, we used eight statistical metrics to evaluate the accuracy of the Final data from three IMERG (Integrated Multi-satellitE Retrievals for GPM) versions (i.e., Versions 3, 4 and 5) over Mainland China across multiple scales. We quantified the improvement of the latest Version 5 relative to previous versions and analyzed the problems in the current IMERG algorithm. Our result shows that: The IMERG data can well capture regional precipitation characteristics over Mainland China, but in northwest China where ground stations are sparse the error is larger and the accuracy is lower, making it difficult to estimate actual precipitation. The Versions 5 outperforms the Versions 3 and 4, with a higher correlation coefficient of 0.75 and a lower root mean squared error of 7.03 mm/d. Though partly corrected for the underestimate problem in northwest China, the Version 5 still performs poorly in winter and does not handle the overestimate problem. This latest version generally surfers from overestimate problems, and the ability to capturing and monitoring heavy rainfall events is less satisfying, and therefore cautions should be taken for the cases of heavy rainfall events. The correction algorithm is still imperfect, in particular for the historical data. Meanwhile, the algorithm may upraise satellite precipitation values in excess as a result of the correction for underestimate problems, leading to high false alarm rates and overestimate problems in the cases of heavy rainfall events. This has an impact on the quality of IMERG data that retrospect to TRMM (Tropical Rainfall Measuring Mission) times and also the follow-on data.