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Tobias Selz, Lucas Fischer, and George C. Craig

atmosphere’s scale-dependence behavior appropriately, shortcomings in the numerics or parameterizations are likely. In the case of kinetic energy, the evaluation of scaling exponents has provided valuable insights into model performance ( Skamarock 2004 ; Hamilton et al. 2008 ; Bierdel et al. 2012 ; Fang and Kuo 2015 ). For water vapor, Schemann et al. (2013) investigated the scaling behaviors of a GCM, an NWP model, and a large-eddy simulation (LES) and the implication for cloud parameterizations

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Kirstin Kober and George C. Craig

the perturbation method is applicable in any atmospheric model that allows for calculation of the relevant physical process information. The observational data used to evaluate the forecasts and the selected case studies in which the parameterization is tested will be introduced briefly as well as the analysis strategy for the suggested method. a. Physically based stochastic perturbations in the boundary layer We propose a concept of process-based model error representation in terms of a

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Christian Barthlott and Corinna Hoose

precipitation to changes in the aerosol content and thermodynamical conditions of the atmosphere. Nevertheless, we have evaluated the respective reference runs at least in a qualitative way to ensure that the COSMO model simulates the main weather characteristics on the analyzed days reasonably well. The simulated 24-h precipitation amount of the reference runs with continental CCN displayed in Fig. 5 show good agreement with observations ( Fig. 4 ) for all days. Not only the convective or stratiform

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