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.

Cloud properties from both ground-based as well as from geostationary passive satellite observations have been used previously for diagnosing aerosol–cloud interactions. In this investigation, a 2-year data set together with four selected case studies are analyzed with the aim of evaluating the consistency and limitations of current ground-based and satellite-retrieved cloud property data sets. The typically applied adiabatic cloud profile is modified using a sub-adiabatic factor to account for entrainment within the cloud. Based on the adiabatic factor obtained from the combination of ground-based cloud radar, ceilometer and microwave radiometer, we demonstrate that neither the assumption of a completely adiabatic cloud nor the assumption of a constant sub-adiabatic factor is fulfilled (mean adiabatic factor 0.63 ± 0.22). As cloud adiabaticity is required to estimate the cloud droplet number concentration but is not available from passive satellite observations, an independent method to estimate the adiabatic factor, and thus the influence of mixing, would be highly desirable for global-scale analyses. Considering the radiative effect of a cloud described by the sub-adiabatic model, we focus on cloud optical depth and its sensitivities. Ground-based estimates are here compared vs. cloud optical depth retrieved from the Meteosat SEVIRI satellite instrument resulting in a bias of −4 and a root mean square difference of 16. While a synergistic approach based on the combination of ceilometer, cloud radar and microwave radiometer enables an estimate of the cloud droplet concentration, it is highly sensitive to radar calibration and to assumptions about the moments of the droplet size distribution. Similarly, satellite-based estimates of cloud droplet concentration are uncertain. We conclude that neither the ground-based nor satellite-based cloud retrievals applied here allow a robust estimate of cloud droplet concentration, which complicates its use for the study of aerosol–cloud interactions.

This study presents Cloudnet retrievals of Arctic clouds from measurements conducted during a 3-month research expedition along the Siberian shelf during summer and autumn 2014. During autumn, we find a strong reduction in the occurrence of liquid clouds and an increase for both mixed-phase and ice clouds at low levels compared to summer. About 80 % of all liquid clouds observed during the research cruise show a liquid water path below the infrared black body limit of approximately 50 g m⁻². The majority of mixed-phase and ice clouds had an ice water path below 20 g m⁻². Cloud properties are analysed with respect to cloud-top temperature and boundary layer structure. Changes in these parameters have little effect on the geometric thickness of liquid clouds while mixed-phase clouds during warm-air advection events are generally thinner than when such events were absent. Cloud-top temperatures are very similar for all mixed-phase clouds. However, more cases of lower cloud-top temperature were observed in the absence of warm-air advection. Profiles of liquid and ice water content are normalized with respect to cloud base and height. For liquid water clouds, the liquid water content profile reveals a strong increase with height with a maximum within the upper quarter of the clouds followed by a sharp decrease towards cloud top. Liquid water content is lowest for clouds observed below an inversion during warm-air advection events. Most mixed-phase clouds show a liquid water content profile with a very similar shape to that of liquid clouds but with lower maximum values during events with warm air above the planetary boundary layer. The normalized ice water content profiles in mixed-phase clouds look different from those of liquid water content. They show a wider range in maximum values with the lowest ice water content for clouds below an inversion and the highest values for clouds above or extending through an inversion. The ice water content profile generally peaks at a height below the peak in the liquid water content profile – usually in the centre of the cloud, sometimes closer to cloud base, likely due to particle sublimation as the crystals fall through the cloud.

Air temperature data from five enclosed limestone sinkholes of various sizes and shapes on the Hetzkogel Plateau near Lunz, Austria (1300 m MSL), have been analyzed to determine the effect of sinkhole geometry on temperature minima, diurnal temperature ranges, temperature inversion strengths, and vertical temperature gradients. Data were analyzed for a non-snow-covered October night and for a snow-covered December night when the temperature fell as low as −28.5°C. A surprising finding is that temperatures were similar in two sinkholes with very different drainage areas and depths. A three-layer model was used to show that the sky-view factor is the most important topographic parameter controlling cooling for basins in this size range in near-calm, clear-sky conditions and that the cooling slows when net longwave radiation at the floor of the sinkhole is nearly balanced by the ground heat flux. Abstract Air temperature data from five enclosed limestone sinkholes of various sizes and shapes on the Hetzkogel Plateau near Lunz, Austria (1300 m MSL), have been analyzed to determine the effect of sinkhole geometry on temperature minima, diurnal temperature ranges, temperature inversion strengths, and vertical temperature gradients. Data were analyzed for a non-snow-covered October night and for a snow-covered December night when the temperature fell as low as −28.5°C. A surprising finding is that temperatures were similar in two sinkholes with very different drainage areas and depths. A three-layer model was used to show that the sky-view factor is the most important topographic parameter controlling cooling for basins in this size range in near-calm, clear-sky conditions and that the cooling slows when net longwave radiation at the floor of the sinkhole is nearly balanced by the ground heat flux.