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Abstract The increase in extreme precipitation with global warming (GW) and associated uncertainties are major challenges for climate adaptation. To project future extreme precipitation on different time and intensity scales (return periods RPs from 1 to 100 a and durations from 1 h to 3 days), we use a novel convection‐permitting (CP), multi‐global climate model ensemble of COSMO‐CLM regional simulations with a transient projection time (1971–2100) over Germany. We find an added value of the CP scale (2.8 km) with respect to the representation of hourly extreme precipitation intensities compared to the coarser scale with parametrized deep convection (7 km). In general, the return levels (RLs) calculated from the CP simulations are in better agreement with those of the conventional observation‐based risk products for the region for short event durations than for longer durations, where an overestimation by the simulation‐based results was found. A maximum climate change signal of 6–8.5% increase per degree of GW is projected within the CP ensemble, with the largest changes expected for short durations and long RPs. Analysis of the uncertainty in the climate change signal shows a substantial residual standard deviation of a linear approximation, highlighting the need for transient data sets instead of time‐slice experiments to increase confidence in the estimates. Furthermore, the ensemble spread is found to be smallest for intensities of short duration, where changes are expected to be based mainly on thermodynamic contributions. The ensemble spread is larger for long, multi‐day durations, where a stronger dependence on the dynamical component is ascribed. In addition, an increase in spatial variance of the RLs with GW implies a more variable future climate and points to an increasing importance of accounting for uncertainties.
Hundhausen et al. (Thu,) studied this question.