Since April 2007, the numerical weather prediction model, COSMO (Consortium for Small Scale Modelling), has been used operationally in a convection-permitting configuration, named COSMO-DE, at the Deutscher Wetterdienst (DWD; German weather service). Here the authors discuss the model changes that were necessary for the convective scale, and report on the experience from the first years of operational application of the model. For COSMO-DE the ability of the numerical solver to treat small-scale structures has been improved by using a Runge–Kutta method, which allows for the use of higher-order upwind advection schemes. The one-moment cloud microphysics parameterization has been extended by a graupel class, and adaptations for describing evaporation of rain and stratiform precipitation processes were made. Comparisons with a much more sophisticated two-moment scheme showed only minor differences in most cases with the exception of strong squall-line situations. Whereas the deep convection parameterization was switched off completely, small-scale shallow convection was still parameterized by the appropriate part of the Tiedtke scheme. During the first year of operational use, convective events in synoptically driven situations were satisfactorily simulated. Also the daily cycles of summertime 10-m wind and 1-h precipitation sums were well captured. However, it became evident that the boundary layer description had to be adapted to enhance convection initiation in airmass convection situations. Here the asymptotic Blackadar length scale l∞ had proven to be a sensitive parameter.

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An updated version of the spectral (bin) microphysics cloud model developed at the Hebrew University of Jerusalem [the Hebrew University Cloud Model (HUCM)] is described. The model microphysics is based on the solution of the equation system for size distribution functions of cloud hydrometeors of seven types (water drops, plate-, columnar-, and branch-like ice crystals, aggregates, graupel, and hail/frozen drops) as well as for the size distribution function of aerosol particles playing the role of cloud condensational nuclei (CCN). Each size distribution function contains 33 mass bins. The conditions allowing numerical reproduction of a narrow droplet spectrum up to the level of homogeneous freezing in deep convective clouds developed in smoky air are discussed and illustrated using as an example Rosenfeld and Woodley's case of deep Texas clouds. The effects of breakup on precipitation are illustrated by the use of a new collisional breakup scheme. Variation of the microphysical structure of a melting layer is illustrated by using the novel melting procedure. It is shown that an increase in the aerosol concentration leads to a decrease in precipitation from single clouds both under continental and maritime conditions. To provide similar precipitation, a cloud developed in smoky air should have a higher top height. The mechanisms are discussed through which aerosols decrease precipitation efficiency. It is shown that aerosols affect the vertical profile of the convective heating caused by latent heat release.

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Large-eddy simulations (LES) with the newThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. R. Heinze et al.at building confidence in the model's ability to simulate small-to mesoscale variability in turbulence, clouds and precipitation. The results are encouraging: the high-resolution model matches the observed variability much better at small-to mesoscales than the coarser resolved reference model. In its highest grid resolution, the simulated turbulence profiles are realistic and column water vapour matches the observed temporal variability at short time-scales. Despite being somewhat too large and too frequent, small cumulus clouds are well represented in comparison with satellite data, as is the shape of the cloud size spectrum. Variability of cloud water matches the satellite observations much better in ICON than in the reference model. In this sense, it is concluded that the model is fit for the purpose of using its output for parametrization development, despite the potential to improve further some important aspects of processes that are also parametrized in the high-resolution model.

Cloud fraction, liquid and ice water contents derived from long-term radar, lidar, and microwave radiometer data are systematically compared to models to quantify and improve their performance.

The sensitivity of simulations of shallow cumulus convection to their microphysical representation is explored, with a focus on the parameter space spanned by two common bulk schemes (Seifert and Beheng, SB, versus Khairoutdinov and Kogan, KK). Large-eddy simulation, simple models, and a priori analysis of the underlying microphysical equations are used as the basis for our study. The simulations are initialized using data derived from the Rain in Cumulus Over the Ocean (RICO) field study. Simulated clouds depths range between two and three kilometers. Microphysical sensitivities can largely be rationalized based on the behavior of simpler models. In particular a parcel model consisting of auto-conversion and accretion acting on a parcel condensing water at a fixed rate provides useful insight into the behavior of the microphysical schemes in the full simulation. To a first approximation the number concentration simply selects the cloud depth at which rain begins to develop, with different schemes predicting different cloud depths. Because of the interaction of auto-conversion and accretion the dependence of this cloud depth on cloud-droplet number concentration is considerably reduced from what would be deduced by an examination of auto conversion alone-suggesting a somewhat diminished role for the regulation of rain by the atmospheric aerosol. Dynamic feedbacks, such as the tendency for non-precipitating clouds to deepen more readily, can further dampen (and even reverse) the expected sensitivity of rain-rate on droplet number concentrations. Our analysis suggests that the commonly assumed exponential distribution for rain drops can strongly distort the sedimentation process in two moment microphysical schemes and that processes such as self-collection and drop break-up can not be neglected for shallow cumulus convection. [References: 26

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