| Summary: | This study considers two north-Alpine heavy-rainfall cases (20-22 May 1999 and 22-23 August 2005) in order to investigate the resolution-dependence of model skill. The simulations are conducted with the Penn State/NCAR mesoscale model MM5 with a variable number of nested domains, resulting in a finest mesh size of 9, 3, and 1 km, respectively. The results are validated against high-resolution raingauge data for western Austria and the adjacent northern foreland in Bavaria. It is found that refining the mesh size from 9 km to 1 km has a highly beneficial impact in the Alpine part of the area of investigation, which can be explained by the fact that a proper representation of the topography is a necessary precondition for simulating the observed small-scale precipitation variability. The model skill at small scales is found to be better for stable orographic precipitation than in the presence of embedded convective cells because the latter induce a stochastic component in the precipitation field. Moreover, the impact of the cloud microphysics scheme increases with increasing model resolution. In the Alpine foreland, the impact of enhancing the model resolution turns out to be small and not necessarily beneficial. There, precipitation variability is not dominated by topographic effects, and other factors (e.g. embedded convection) may not be predictable in a deterministic sense.
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