Monitoring the super typhoon lekima by GPM-based near-real-time satellite precipitation estimates

Abstract

As the fifth-largest super tropical cyclone landed on Mainland China in history, typhoon Lekima occurred in August 2019 caused at least 71 deaths, 14 million disaster victims, and cost RMB 65.37 billion in damages. Here we use six latest GPM-based near-real-time satellite precipitation estimates (IMERG-Early, IMERG-Late, GSMaP-NOW, GSMaP-NRT, GSMaP-MVK, and CMORPH-RT) to quantify the spatiotemporal pattern of typhoon rainfall and meanwhile the potentials of these satellite precipitation products in detecting heavy storms are systematically investigated. Retrieval results indicate that the expansive rain belt of typhoon Lekima brought approximately 93.2 billion m3 water in total onto the Chinese mainland during the typhoon period and the precipitation process maintained higher intensities on the earlier two days (August 10 and 11). Specifically, it is found that a “precipitation window” with higher precipitation intensities appeared between 5:00 a.m. and 10:00 a.m., implying that a greater probability of rainstorms may occur during this period. Moreover, at the storm center around the Dongying City of Shandong Province, the dual-frequency precipitation radar of GPM (GPM-DPR) successfully revealed the existence of precipitation columns with the peak value of 121 mm·h−1, which seem to play a key role in the regional torrential rainfall. Additionally, our evaluation shows IMERG-Late and CMORPH-RT perform better under higher rain rates relative to other satellite precipitation estimates. This can be primarily attributed to their sufficient inputs from PMW sensors and, respectively, the former benefits well from both DPR and GMI while the latter significantly reduces its IR inputs. This study illustrates an example of monitoring the extreme heavy precipitation storms by the latest GPM-based near-real-time satellite precipitation estimates and highlights future possible improvements for algorithm developers.