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Assessing the influence of climate change on extreme (convective) rainfall is challenging. In particular with global climate models, it is virtually impossible to combine high resolution modelling to represent the physical processes adequately together with conducting long simulations to achieve statistical robustness. To complement global modelling efforts, we here present an event oriented system based on pseudo global warming (PGW). The system consists of continuous short-term forecast cycles (3 days long starting each day at midnight) running a small set of 12 km resolution simulations for the present-day climate, a cooler past climate, and three warmer climates. For extreme events these runs are further downscaled to convection permitting resolutions. This allows us to study the spatiotemporal characteristics of convective rainfall and associated phenomena, like wind gusts, hail, and lightning within a climate change context. At the same time, the system has sufficient signal-to-noise to study climate change effects in rare extreme events. We illustrate the application the system with three recent extreme rainfall events (storm Babet in the UK, October 2023; the Italy spring 2023 floods; and the Germany Bavaria 2024 floods) and discuss strengths and limitations of the method. One additional case with extreme convective wind gusts shows the potential further application of the system. All three rainfall events reveal climate change responses well beyond the commonly expected Clausius-Clapeyron rate, and two cases (in Italy and Germany) reveal a concentration of rainfall in more confined areas, disproportionally enhancing the potential for flash floods in a warming climate.
Lenderink et al. (Fri,) studied this question.