Extremely persistent flash heavy rainfalls (EPHRs) over the Sichuan Basin in China are influenced by both multiscale weather systems and complex underlying surfaces, making it difficult to understand the favorable dynamic mechanisms and to further improve operational numerical forecasting skills. In this study, EPHRs from 2010 to 2024 are objectively identified and then classified into three categories based on the SOM method. Precipitating characteristics for each category are further investigated from the perspective of the diurnal cycle and spatial features with the use of rain-gauge-based observations. Evaluations of the ERA5 reanalysis dataset, MSWX bias-corrected meteorological product, and CMORPH satellite-based precipitation product are performed to determine their capabilities in representing precipitating characteristics of different EPHR categories at different stages. The following results are obtained. During EPHR events, CMORPH outperforms MSWX and ERA5 in capturing heavy precipitation distribution, diurnal cycles, and evolution over the central basin. Both MSWX and ERA5 miss the central precipitation core, with MSWX showing premature peaks and ERA5 generating secondary evening peaks while overestimating precipitation duration. During events influenced by small-scale weather systems, all three products exhibit minimal false alarms but show the largest errors in intensity and diurnal variation. Under certain circulation types, MSWX and ERA5 significantly underestimate precipitation development with comparable metrics, while CMORPH achieves superior accuracy in precipitation intensity and correlations, yet it underestimates nighttime precipitation occurrences in steep western terrain. This study may help to facilitate not only theoretical studies but also numerical model developments for precipitation extremes.
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C. Liu
Jie Cao
Chengzhi Deng
Remote Sensing
Nanjing University of Information Science and Technology
China Meteorological Administration
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Liu et al. (Sat,) studied this question.
www.synapsesocial.com/papers/68a36de60a429f797333162c — DOI: https://doi.org/10.3390/rs17162761