Representing large-scale co-variability between variables related to aerosols, clouds and radiation is one of many aspects of agreement with observations desirable for a climate model. In this study such relations are investigated in terms of temporal correlations on monthly mean scale, to identify points of agreement and disagreement with observations. Ten regions with different meteorological characteristics and aerosol signatures are studied and correlation matrices for the selected regions offer an overview of model ability to represent present day climate variability. Global climate models with different levels of detail and sophistication in their representation of aerosols and clouds are compared with satellite observations and reanalysis assimilating meteorological fields as well as aerosol optical depth from observations. One example of how the correlation comparison can guide model evaluation and development is the often studied relation between cloud droplet number and water content. Reanalysis, with no parameterized aerosol-cloud coupling, shows weaker correlations than observations, indicating that microphysical couplings between cloud droplet number and water content are not negligible for the co-variations emerging on larger scale. These observed correlations are, however, not in agreement with those expected from dominance of the underlying microphysical aerosol-cloud couplings. For instance, negative correlations in subtropical stratocumulus regions show that suppression of precipitation and subsequent increase in water content due to aerosol is not a dominating process on this scale. Only in one of the studied models are cloud dynamics able to overcome the parameterized dependence of rain formation on droplet number concentration, and negative correlations in the stratocumulus regions are reproduced.

Abstract. The effects of different aerosol types on cloud albedo are analysed using the linear relation between total albedo and cloud fraction found on a monthly mean scale in regions of subtropical marine stratocumulus clouds and the influence of simulated aerosol variations on this relation. Model experiments from the Coupled Model Intercomparison Project phase 5 (CMIP5) are used to separately study the responses to increases in sulfate, non-sulfate and all anthropogenic aerosols. A cloud brightening on the month-tomonth scale due to variability in the background aerosol is found to dominate even in the cases where anthropogenic aerosols are added. The aerosol composition is of importance for this cloud brightening, that is thereby region dependent. There is indication that absorbing aerosols to some extent counteract the cloud brightening but scene darkening with increasing aerosol burden is generally not supported, even in regions where absorbing aerosols dominate. Month-to-month cloud albedo variability also confirms the importance of liquid water content for cloud albedo. Regional, monthly mean cloud albedo is found to increase with the addition of anthropogenic aerosols and more so with sulfate than non-sulfate. Changes in cloud albedo between experiments are related to changes in cloud water content as well as droplet size distribution changes, so that models with large increases in liquid water path and/or cloud droplet number show large cloud albedo increases with increasing aerosol. However, no clear relation between model sensitivities to aerosol variations on the month-to-month scale and changes in cloud albedo due to changed aerosol burden is found.

<p><strong>Abstract.</strong> The effects of different aerosol types on cloud albedo are analyzed using the linear relation between total albedo and cloud fraction found on monthly mean scale in regions of subtropical marine stratocumulus clouds, and the influence of Aerosol Optical Depth (AOD) on this relation. Model experiments from the Coupled Model Intercomparison Project phase 5 (CMIP5) are used to separately study the responses to increases in sulfate, non-sulfate and all anthropogenic aerosols. A cloud brightening on month-to month scale due to variability in the background aerosol is found to dominate even in the cases where anthropogenic aerosols are added. The aerosol composition is found to be of importance for this cloud brightening, that is thereby region dependent. There is indication that absorbing aerosols to some extent counteract the cloud brightening, but scene darkening with increasing aerosol burden is generally not supported, even in regions where absorbing aerosols dominate. Regional, monthly mean cloud albedo is found to increase with the addition of anthropogenic aerosols, and more so with sulfate than non-sulfate. The changes in AOD due to anthropogenic aerosols are typically small compared to the AOD variability within a given aerosol forcing scenario, and the magnitude of the change in cloud albedo due to anthropogenic aerosols is small and not directly related to the strength of the month-to-month cloud brightening due to aerosols. The diversity in changes in cloud albedo in this set of models is rather related to the different changes in cloud water content between the experiments.</p>

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<p>Forecasting high impact weather events is a major challenge for numerical weather prediction. Initial condition uncertainty plays a major role but so do potentially uncertainties arising from the representation of subgrid-scale processes, e.g. cloud microphysics. In this project, we investigate the impact of these uncertainties on the forecast of cloud properties, precipitation and hail of a selected severe convective storm over South-Eastern Germany.</p><p>Here, we focus the investigation on the effects of parametric uncertainty in a perturbed parameter ensemble, using the ICON model (with 2-moment cloud scheme, at 1 km grid spacing). A latin hypercube sampling is used to generate systematic variations of selected microphysical parameters from an eight-dimensional parameter space. Considered processes include riming, diffusional growth of ice and snow, CCN and INP activation, as well as the mass-diameter and mass-velocity relations. Isolated sensitivity experiments show distinct influences of all parameters on hail related variables, where the strongest impacts are found in simulations with reduced CCN and INP activation. We will present a detailed analysis of the simultaneous influence of parameter perturbations on the cloud microphysical evolution of the storm.</p>

Aerosol absorption constitutes a significant component of the total radiative effect of aerosols, and hence its representation in general circulation models is crucial to radiative forcing estimates. We use here multiple observations to evaluate the performance of CAM5.3-Oslo with respect to its aerosol representation. CAM5.3-Oslo is the atmospheric component of the earth system model NorESM1.2 and shows on average an underestimation of aerosol absorption in the focus region over East and South Asia and a strong aerosol absorption overestimation in desert and arid regions compared to observations and other AeroCom phase III models. We explore the reasons of the model spread and find that it is related to the column burden and residence time of absorbing aerosols, in particular black carbon and dust. We conduct further sensitivity simulations with CAM5.3-Oslo to identify processes which are most important for modelled aerosol absorption. The sensitivity experiments target aerosol optical properties, and contrast their impact with effects from changes in emissions and deposition processes, and the driving meteorology. An improved agreement with observations was found with the use of a refined emission data set, transient emissions and assimilation of meteorological observations. Changes in optical properties of absorbing aerosols can also reduce the under-and overestimation of aerosol absorption in the model. However, changes in aerosol absorption strength between the sensitivity experiments are small compared to the inter-model spread among the AeroCom phase III models.

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