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.

The Cloudnet project aims to provide a systematic evaluation of clouds in forecast and climate models by comparing the model output with continuous ground-based observations of the vertical profiles of cloud properties. In the models, the properties of clouds are simplified and expressed in terms of the fraction of the model grid box, which is filled with cloud, together with the liquid and ice water content of the clouds. These models must get the clouds right if they are to correctly represent both their radiative properties and their key role in the production of precipitation, but there are few observations of the vertical profiles of the cloud properties that show whether or not they are successful. Cloud profiles derived from cloud radars, ceilometers, and dual-frequency microwave radiometers operated at three sites in France, Netherlands, and the United Kingdom for several years have been compared with the clouds in seven European models. The advantage of this continuous appraisal is that the feedback on how new versions of models are performing is provided in quasi-real time, as opposed to the much longer time scale needed for in-depth analysis of complex field studies. Here, two occasions are identified when the introduction of new versions of the ECMWF and Météo-France models leads to an immediate improvement in the representation of the clouds and also provides statistics on the performance of the seven models. The Cloudnet analysis scheme is currently being expanded to include sites outside Europe and further operational forecasting and climate models.

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.

Large‐eddy simulations (LES) with the new ICOsahedral Non‐hydrostatic atmosphere model (ICON) covering Germany are evaluated for four days in spring 2013 using observational data from various sources. Reference simulations with the established Consortium for Small‐scale Modelling (COSMO) numerical weather prediction model and further standard LES codes are performed and used as a reference. This comprehensive evaluation approach covers multiple parameters and scales, focusing on boundary‐layer variables, clouds and precipitation. The evaluation points to the need to work on parametrizations influencing the surface energy balance, and possibly on ice cloud microphysics. The central purpose for the development and application of ICON in the LES configuration is the use of simulation results to improve the understanding of moist processes, as well as their parametrization in climate models. The evaluation thus aims 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.