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Large biases in climate model simulations of cloud radiative properties over the Southern Ocean cause large errors in modeled sea surface temperatures, atmospheric circulation, and climate sensitivity. Here, we combine cloud-resolving model simulations with estimates of the concentration of ice-nucleating particles in this region to show that our simulated Southern Ocean clouds reflect far more radiation than predicted by global models, in agreement with satellite observations. Specifically, we show that the clouds that are most sensitive to the concentration of ice-nucleating particles are low-level mixed-phase clouds in the cold sectors of extratropical cyclones, which have previously been identified as a main contributor to the Southern Ocean radiation bias. The very low ice-nucleating particle concentrations that prevail over the Southern Ocean strongly suppress cloud droplet freezing, reduce precipitation, and enhance cloud reflectivity. The results help explain why a strong radiation bias occurs mainly in this remote region away from major sources of ice-nucleating particles. The results present a substantial challenge to climate models to be able to simulate realistic ice-nucleating particle concentrations and their effects under specific meteorological conditions. [ABSTRACT FROM AUTHOR]

Foehn flows are typically associated with warm air temperatures. Though several theories for the so-called foehn air warming have been developed over the past century, no conclusion about the most important mechanism has been reached. The development of new methods to calculate accurate air-mass trajectories over complex topography has opened up a new perspective on this question. Air-mass-trajectories derived from wind-field data from COSMO model simulations with 20 s temporal resolution are used in this study to investigate the origin of the foehn air and the contribution of adiabatic and diabatic processes for two foehn events in the Swiss Alps, with a focus on the Rhine valley. The first foehn event investigated has no precipitation on the upstream side of the Alps. The majority of air parcels stem from upstream altitudes above 1.8 km and most of the foehn air warming is due to adiabatic descent (∼79%). In the second event investigated, significant upstream precipitation occurred. For this case, a significantly larger fraction of the foehn air parcels originate within the lowest 2 km of the upstream atmosphere (up to 70%). Adiabatic descent accounts for the largest part of the temperature change (∼70%), while moist diabatic processes explain about 60% of the potential temperature change. The vertical displacement across the Alpine range is correlated with the diabatic temperature change: parcels strongly heated by condensation, deposition and freezing are in general found at high altitudes above the foehn valley, while parcels affected by diabatic cooling through evaporation, sublimation and melting arrive closer to the valley floor. The high-resolution trajectories also indicate a much more complicated vertical and horizontal flow pattern than generally assumed, with several distinct air streams upstream of the mountain range and vertical 'scrambling' of air masses. [ABSTRACT FROM AUTHOR]

The precipitation produced by orographic clouds is the result of the interaction between nonlinear dynamical and microphysical processes. Focusing on warm-phase stable clouds, we propose that the precipitation efficiency is essentially controlled by the bulk Damköhler number of the system, i.e. the ratio of the characteristic advective to the microphysical time-scale of the cloud. These time-scales are investigated thoroughly for single air parcels along temporally highly resolved trajectories from quasi-two-dimensional numerical simulations with vertical Froude numbers between 0.38 and 2.31. Based on these results, analytical formulations for the Damköhler number of single parcels and for a bulk Damköhler number for the entire cloud are developed, which depend only on the far upstream flow properties and the cloud droplet number density. Relating the bulk Damköhler numbers to the precipitation efficiencies from the numerical simulations results in a unique scaling relation between the two non-dimensional numbers: no precipitation is observed for very small Damköhler numbers, while for large Damköhler numbers the precipitation efficiency asymptotically approaches a maximum value of about 0.8. For intermediate Damköhler numbers, the precipitation efficiency depends strongly on the microphysical properties of the clouds. [ABSTRACT FROM AUTHOR]

Secondary ice production via rime-splintering is considered to be an important process for rapid glaciation and high ice crystal numbers observed in mixed-phase convective clouds. An open question is how rime-splintering is triggered in the relatively short time between cloud formation and observations of high ice crystal numbers. We use idealised simulations of a deep convective cloud system to investigate the thermodynamic and cloud microphysical evolution of air parcels, in which the model predicts secondary ice formation. The Lagrangian analysis suggests that the "in-situ" formation of rimers either by growth of primary ice or rain freezing does not play a major role in triggering secondary ice formation. Instead, rimers are predominantly imported into air parcels through sedimentation form higher altitudes. While ice nucleating particles (INPs) initiating heterogeneous freezing of cloud droplets at temperatures warmer than −10 °C have no discernible impact of the occurrence of secondary ice formation, in a scenario with rain freezing secondary ice production is initiated slightly earlier in the cloud evolution and at slightly different places, although with no major impact on the abundance or spatial distribution of secondary ice in the cloud as a whole. These results suggest that for interpreting and analysing observational data and model experiments regarding cloud glaciation and ice formation it is vital to consider the complex vertical coupling of cloud microphysical processes in deep convective clouds via three-dimensional transport and sedimentation. [ABSTRACT FROM AUTHOR]

Cloud microphysics parametrizations control the transfer of water between phases and hydrometeor species in numerical weather prediction and climate models. As a fundamental component of weather modelling systems cloud microphysics can determine the intensity and timing of precipitation, the extent and longevity of cloud cover and its impact on radiative balance, and directly influence near surface weather metrics such as temperature and wind. In this paper we introduce and demonstrate the performance of a double moment cloud microphysical scheme (CASIM: Cloud AeroSol Interacting Microphysics) in both midlatitude and tropical settings using the same model configuration. Comparisons are made against a control configuration using the current operational single moment cloud microphysics, and CASIM configurations that use fixed in‐cloud droplet number or compute cloud droplet number concentration from the aerosol environment. We demonstrate that configuring CASIM as a single moment scheme results in precipitation rate histograms that match the operational single moment microphysics. In the midlatitude setting, results indicate that CASIM performs as well as the single moment microphysics configuration, but improves certain aspects of the surface precipitation field such as greater extent of light (<$$ < $$1 mm ·$$ \cdotp $$ hr−1$$ {}^{-1} $$) rain around frontal precipitation features. In the tropical setting, CASIM outperforms the single moment cloud microphysics as evident from improved comparison with radar derived precipitation rates. [ABSTRACT FROM AUTHOR]

Prediction of weather is a main goal of atmospheric science. Its importance to society is growing continuously due to factors such as vulnerability to natural disasters, the move to renewable energy sources, and the risks of climate change. But prediction is also a major scientific challenge due to the inherently limited predictability of a chaotic atmosphere, and has led to a revolution in forecasting methods as we have moved to probabilistic prediction. These changes provide the motivation for Waves to Weather (W2W), a major national research program in Germany with three main university partners in Munich, Mainz, and Karlsruhe. We are currently in the second 4-yr phase of our planned duration of 12 years and employ 36 doctoral and postdoctoral scientists. In the context of this large program, we address what we have identified to be the most important and challenging scientific questions in predictability of weather, namely, upscale error growth, errors associated with cloud processes, and probabilistic prediction of high-impact weather. This paper presents some key results of the first phase of W2W and discusses how they have influenced our understanding of predictability. The key role of interdisciplinary research linking atmospheric scientists with experts in visualization, statistics, numerical analysis, and inverse methods will be highlighted. To ensure a lasting impact on research in our field in Germany and internationally, we have instituted innovative programs for training and support of early-career scientists, and to support education, equal opportunities, and outreach, which are also described here. [ABSTRACT FROM AUTHOR]

This study presents results from a model intercomparison project, focusing on the range of responses in deep convective cloud updrafts to varying cloud condensation nuclei (CCN) concentrations among seven state-of-the-art cloud-resolving models. Simulations of scattered convective clouds near Houston, Texas, are conducted, after being initialized with both relatively low and high CCN concentrations. Deep convective updrafts are identified, and trends in the updraft intensity and frequency are assessed. The factors contributing to the vertical velocity tendencies are examined to identify the physical processes associated with the CCN-induced updraft changes. The models show several consistent trends. In general, the changes between the High-CCN and Low-CCN simulations in updraft magnitudes throughout the depth of the troposphere are within 15% for all of the models. All models produce stronger (~+5%–15%) mean updrafts from ~4–7 km above ground level (AGL) in the High-CCN simulations, followed by a waning response up to ~8 km AGL in most of the models. Thermal buoyancy was more sensitive than condensate loading to varying CCN concentrations in most of the models and more impactful in the mean updraft responses. However, there are also differences between the models. The change in the amount of deep convective updrafts varies significantly. Furthermore, approximately half the models demonstrate neutral-to-weaker (~−5% to 0%) updrafts above ~8 km AGL, while the other models show stronger (~+10%) updrafts in the High-CCN simulations. The combination of the CCN-induced impacts on the buoyancy and vertical perturbation pressure gradient terms better explains these middle- and upper-tropospheric updraft trends than the buoyancy terms alone. [ABSTRACT FROM AUTHOR]

The article discusses the International Cloud Modeling Workshop (CMW) which has been a longstanding tradition in the cloud microphysics modeling community and is held the week prior to the International Conference on Clouds and Precipitation (ICCP). It states that CMW was attended by more than 40 participants from ten countries at the Met Office in Exeter in Great Britain.