Abstract
The deterministic description of the subgrid-scale land–atmosphere interaction in regional climate model (RCM) simulations is changed by using stochastic soil and vegetation parameterizations. For this, the land–atmosphere interaction parameterized in a land surface model (LSM) is perturbed stochastically by adding a random value to the input parameters using a random number generator. In this way, a stochastic ensemble is created that represents the impact of the uncertainties in these subgrid-scale processes on the resolved scale circulation. In a first step, stochastic stand-alone simulations with the VEG3D LSM are performed to identify sensitive model parameters. Afterward, VEG3D is coupled to the Consortium for Small-Scale Modeling–Climate Limited-Area Modeling (COSMO-CLM) RCM and stochastically perturbed simulations driven by ERA-Interim (2001–10) are performed for the Coordinated Downscaling Experiment–European Domain (EURO-CORDEX) at a horizontal resolution of 0.22°. The simulation results reveal that the impact of stochastically varied soil and vegetation parameterizations on the simulated climate conditions differs regionally. In central Europe the impact on the mean temperature and precipitation characteristics is very weak. In southern Europe and North Africa, however, the resolved scale circulation is very sensitive to the local soil water conditions. Furthermore, it is demonstrated that the use of stochastic soil and vegetation parameterizations considerably improves the variability of monthly rainfall sums all over Europe by improving the representation of the land–atmosphere interaction in the stochastic ensemble on a daily basis. In particular, inland rainfall during summer is simulated much better.
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