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.

Abstract. Dust aerosols are thought to be the main contributor to atmospheric ice nucleation. While there are case studies supporting this, a climatological sense of the importance of dust to atmospheric ice nucleating particle (INP) concentrations and its seasonal variability over Europe is lacking. Here, we use a mesoscale model to estimate Saharan dust concentrations over Europe in 2008. There are large differences in median dust concentrations between seasons, with the highest concentrations and highest variability in the lower to mid-troposphere. Laboratory-based ice nucleation parameterisations are applied to these simulated dust number concentrations to calculate the potential INP resulting from immersion freezing and deposition nucleation on these dust particles. The potential INP concentrations increase exponentially with height due to decreasing temperatures in the lower and mid-troposphere. When the ice-activated fraction increases sufficiently, INP concentrations follow the dust particle concentrations. The potential INP profiles exhibit similarly large differences between seasons, with the highest concentrations in spring (median potential immersion INP concentrations nearly 10 5 m −3 , median potential deposition INP concentrations at 120 % relative humidity with respect to ice over 10 5 m −3 ), about an order of magnitude larger than those in summer. Using these results, a best-fit function is provided to estimate the potential INPs for use in limited-area models, which is representative of the normal background INP concentrations over Europe. A statistical evaluation of the results against field and laboratory measurements indicates that the INP concentrations are in close agreement with observations.

Abstract. An aerosol model was used to simulate the generation and transport of aerosols over Germany during the HD(CP) 2 Observational Prototype Experiment (HOPE) field campaign of 2013. The aerosol number concentrations and size distributions were evaluated against observations, which shows satisfactory agreement in the magnitude and temporal variability of the main aerosol contributors to cloud condensation nuclei (CCN) concentrations. From the modelled aerosol number concentrations, number concentrations of CCN were calculated as a function of vertical velocity using a comprehensive aerosol activation scheme which takes into account the influence of aerosol chemical and physical properties on CCN formation. There is a large amount of spatial variability in aerosol concentrations; however the resulting CCN concentrations vary significantly less over the domain. Temporal variability is large in both aerosols and CCN. A parameterization of the CCN number concentrations is developed for use in models. The technique involves defining a number of best fit functions to capture the dependence of CCN on vertical velocity at different pressure levels. In this way, aerosol chemical and physical properties as well as thermodynamic conditions are taken into account in the new CCN parameterization. A comparison between the parameterization and the CCN estimates from the model data shows excellent agreement. This parameterization may be used in other regions and time periods with a similar aerosol load; furthermore, the technique demonstrated here may be employed in regions dominated by different aerosol species.

Abstract. State-of-the-art aerosol-dependent parameterisations describing each heterogeneous ice nucleation mode (contact, immersion, and deposition ice nucleation), as well as homogeneous nucleation, were incorporated into a large eddy simulation model. Several cases representing commonly occurring cloud types were simulated in an effort to understand which ice nucleation modes contribute the most to total concentrations of ice crystals. The cases include a completely idealised warm bubble, semi-idealised deep convection, an orographic cloud, and a stratiform case. Despite clear differences in thermodynamic conditions between the cases, the results are remarkably consistent between the different cloud types. In all the investigated cloud types and under normal aerosol conditions, immersion freezing dominates and contact freezing also contributes significantly. At colder temperatures, deposition nucleation plays only a small role, and homogeneous freezing is important. To some extent, the temporal evolution of the cloud determines the dominant freezing mechanism and hence the subsequent microphysical processes. Precipitation is not correlated with any one ice nucleation mode, instead occurring simultaneously when several nucleation modes are active. Furthermore, large variations in the aerosol concentration do affect the dominant ice nucleation mode; however, they have only a minor influence on the precipitation amount.

<p><strong>Abstract.</strong> State of the art aerosol dependent parameterisations describing each heterogeneous ice nucleation mode, as well as homogeneous nucleation, were incorporated into a large eddy simulation model. Several cases representing commonly occurring cloud types were simulated in an effort to understand which ice nucleation modes contribute the most to total concentrations of ice crystals. The cases include a completely idealised warm bubble, semi-idealised deep convection, an orographic cloud, and a stratiform case. Despite clear differences in thermodynamical conditions in each case, the results are remarkably consistent between the different cloud types. In all the investigated cloud types and under normal aerosol conditions, immersion freezing dominates and contact freezing also contributes significantly. At colder temperatures, deposition nucleation plays little role, and homogeneous freezing is important. To some extent, the temporal evolution of the cloud determines the dominant freezing mechanism, and hence the subsequent microphysical processes. Precipitation is not correlated with any one ice nucleation mode, instead occurs simultaneously when several nucleation modes are active. Furthermore, large variations in the aerosol concentration have only a minor influence on the precipitation amount.</p>

A parameterization for contact freezing is presented that combines theoretical expressions for determining the collision efficiency with experimentally determined freezing efficiency results. The parameterization has dependencies on aerosol and cloud droplet physical properties, including electric charges, as well as ambient temperature and humidity. The highest freezing rate is obtained at large aerosol and large cloud droplet sizes, and at cold temperatures and low relative humidities, with typical dust aerosol and droplet properties. The number concentration of ice nucleating particles (INPs) in the contact freezing mode are generally lower than those in the immersion freezing or deposition nucleation mode; however, under certain conditions contact INP concentrations can exceed those of the other modes. The new parameterization is used in a high-resolution, semi-idealized simulation of a deep convective cloud, and a number of sensitivity studies are performed. Results indicate the greatest sensitivity is to the best-fit function to laboratory data. The simulations show that droplet properties and ambient relative humidity contribute significantly to contact freezing.

Abstract. Dust aerosols are thought to be the main contributor to atmospheric ice nucleation. While there are case studies supporting this, a climatological sense of the importance of dust to atmospheric ice nucleating particle (INP) concentrations, and it's seasonal variability over Europe is lacking. Here, we use a mesoscale model to estimate Saharan dust concentrations over Europe in winter and summer of 2007–2008. There are large differences in median dust concentrations between seasons, with the highest concentrations and highest variability in the lowest 4 km. Laboratory based ice nucleation parameterisations are applied to these dust number concentrations to calculate the potential INP resulting from immersion freezing and deposition nucleation on these dust particles. The potential INP concentrations generally increase with height due to decreasing temperatures in the lower and mid-troposphere and exhibit a maximum in the upper troposphere where INP concentrations decrease again with altitude due to decreasing dust concentrations. The potential INP profiles exhibit similarly large differences between seasons, with the highest concentrations in winter (median potential immersion INP concentrations up to 103 m−3, median potential deposition INP concentrations at 120% relative humidity with respect to ice up to 105 m−3) occurring closer to the ground for both nucleation modes. Using these results, a best-fit function is provided to estimate the potential INPs for use in limited-area models, which is representative of the normal background INP concentrations over Europe. A statistical evaluation of the results against field and laboratory measurements indicates that the INP concentrations are in close agreement with observations.

<p><strong>Abstract.</strong> An aerosol model was used to simulate the generation and transportation of aerosols over Germany during the HD(CP)<sup>2</sup> Observational Prototype Experiment (HOPE) field campaign of 2013. The aerosol number concentrations and size distributions were evaluated against observations, which shows satisfactory agreement in the magnitude and temporal variability of the main aerosol contributors to cloud condensation nuclei (CCN) concentrations. From the modelled aerosol number concentrations, number concentrations of CCN were calculated as a function of vertical velocity using a comprehensive aerosol activation scheme which takes into account the influence of aerosol chemical and physical properties on CCN formation. There is a large amount of spatial variability in aerosol concentrations, however the resulting CCN concentrations vary significantly less over the domain. Temporal variability is large in both aerosols and CCN. A parameterisation of the CCN number concentrations is developed for use in models. The technique involves defining a number of best fit functions to capture the dependence of CCN on vertical velocity at different pressure levels. In this way, aerosol chemical and physical properties as well as thermodynamic conditions are taken into account in the new CCN parameterisation. A comparison between the parameterisation and the CCN estimates from the model data shows excellent agreement. This parameterisation may be used in other regions and time periods with a similar aerosol load, and furthermore, this technique demonstrated here may be employed in regions dominated by different aerosol species.</p>