Heavy and extreme precipitation events in the Sichuan Basin during the 2020 summer season in a set of kilometre-scale simulations

The Sichuan Basin (SB), a lowland region in southwest China located at the eastern slope of the Tibetan Plateau (TP), regularly experiences heavy and extreme precipitation events. These extreme events often lead to flooding that can pose a threat to life and livelihoods of people in this densely populated area. A notable example is the summer of 2020, during which large parts of East Asia were affected by anomalously high precipitation. In the SB, these events broke the previous record of daily accumulated rainfall at multiple stations.  

Since such events are expected to increase in both frequency and intensity in a warmer climate, understanding their causes and the physical processes involved is of high relevance in the SB region. Modelling the climate in mountainous regions with complex topography is challenging but recent developments in convection-permitting modelling make it possible to perform process-based studies.

The CORDEX Flagship Pilot Study Convection-Permitting Third Pole (CPTP) aims to improve our understanding of the water cycle over the TP and its surrounding regions using a multi-model ensemble of kilometre-scale simulations. Recent results using a set of CPTP simulations for one extreme precipitation event suggest that an accurate representation of the large-scale forcing is crucial to correctly simulate the event. In this study, we assess how well different kilometre-scale CPTP simulations capture multiple observed heavy and extreme precipitation events that occurred in the SB during the summer of 2020 by validating them against observations and reanalysis data. In addition, we analyse how the simulations differ among each other in representing the observed events and related important physical factors, e.g. large- and mesoscale circulation and moisture transport. A realistic representation of extreme events in climate models can provide a basis for more reliable future projections and uncertainty estimates.