Dynamics and model representation of two contrasting extreme precipitation events in the Sahel

Abstract Two extreme flood‐inducing precipitation events in two cities in Mali, on August 8, 2012 in San (127 mm) and on August 25, 2019 in Kenieba (126 mm), are investigated with respect to rainfall structures, dynamical forcings, and the ability of the ICOsahedral Nonhydrostatic model (ICON) to represent their evolution. Two sets of experiments with convective parameterization enabled (PARAM) and disabled (EXPLC), both at 6.5‐km grid spacing, are conducted for each case. While the (thermo)dynamical fields of the simulations are compared with fifth‐generation European Centre for Medium‐Range Weather Forecasts (ECMWF) reanalysis (ERA5) data, the rainfall fields are tested against the satellite‐based precipitation dataset Integrated Multi‐satellitE Retrievals for Global Precipitation Measurement ( GPM ) (IMERG) by applying spatial verification methods based on the fractions skill score (FSS) and structure–amplitude–location (SAL) score. In addition, a spectral filtering of tropical waves is applied to investigate their impact on extreme events. The most prominent results are as follows. (1) Both cases were caused by organized convective systems associated with a westward‐propagating cyclonic vortex, but differ in their environmental setting. Although both cases featured an African easterly wave, the San case involved convective enhancement along dry Saharan airmasses, whereas the Kenieba case occurred within an unusual widespread wet environment extending deep into the Sahel. (2) Although EXPLC captures the rainfall distribution in the San case better than PARAM, it fails to organize convection in the moisture‐laden Kenieba case, which PARAM is capable of simulating. (3) The FSS confirms the case dependence of the ICON skill. The SAL method hints at a systematic deficiency of EXPLC in representing convective organization by producing too many scattered and weak rainfall systems, while PARAM is more effective in converting abundant moisture into excessive rainfall. The results stress the continued need for more research into capturing the complex convective dynamics to forecast the extremes of Sahelian rainfall better.