Abstract

Abstract. We have extended the coupled mesoscale atmosphere and chemistry model COSMO-ART to account for the transformation of aerosol particles into cloud condensation nuclei and to quantify their interaction with warm cloud microphysics on the regional scale. The new model system aims to fill the gap between cloud resolving models and global scale models. It represents the very complex microscale aerosol and cloud physics as detailed as possible, whereas the continental domain size and efficient codes will allow for both studying weather and regional climate. The model system is applied in a first extended case study for Europe for a cloudy five day period in August 2005. The model results show that the mean cloud droplet number concentration of clouds is correlated with the structure of the terrain, and we present a terrain slope parameter TS to classify this dependency. We propose to use this relationship to parameterize the probability density function, PDF, of subgrid-scale cloud updraft velocity in the activation parameterizations of climate models. The simulations show that the presence of cloud condensation nuclei (CCN) and clouds are closely related spatially. We find high aerosol and CCN number concentrations in the vicinity of clouds at high altitudes. The nucleation of secondary particles is enhanced above the clouds. This is caused by an efficient formation of gaseous aerosol precursors above the cloud due to more available radiation, transport of gases in clean air above the cloud, and humid conditions. Therefore the treatment of complex photochemistry is crucial in atmospheric models to simulate the distribution of CCN. The mean cloud droplet number concentration and droplet diameter showed a close link to the change in the aerosol. To quantify the net impact of an aerosol change on the precipitation we calculated the precipitation susceptibility β for the whole model domain over a period of two days with an hourly resolution. The distribution function of β is slightly skewed to positive values and has a mean of 0.23. Clouds with a liquid water path LWP of approximately 0.85 kg m−2 are on average most susceptible to aerosol changes in our simulations with an absolute value of β of 1. The average β for LWP between 0.5 kg m−2 and 1 kg m−2 is approximately 0.4.

Highlights

  • The interaction of aerosol particles with clouds is still one of the largest uncertainties in modern climate studies (Forster et al, 2007)

  • The change in dynamics can change the emissions of sea salt, which can cause a strong change in the number of available cloud condensation nuclei (CCN) especially in clean marine air

  • From our findings we suggest a parameterization of the probability density function (PDF) of subgrid-scale vertical velocities in climate models which takes the effect of subgrid-scale terrain slope (TS) into account

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Summary

Introduction

The interaction of aerosol particles with clouds is still one of the largest uncertainties in modern climate studies (Forster et al, 2007) Depending on their chemical composition and size, atmospheric aerosol particles can act as cloud condensation nuclei (CCN) during cloud formation. Simulations of single clouds and cloud clusters showed that depending on the cloud type the influence of aerosol changes on cloud microphysics can affect precipitation amounts very differently (Khain, 2009 and references therein) Due to their comprehensive cloud microphysics and the used fine grid meshes such simulations are limited to small domains and short time scales. In this study we simulate the spatial distributions of aerosol particles and clouds as well as their interaction on the regional scale with a coupled mesoscale atmosphere and chemistry model. We calculate the precipitation susceptibility for the whole model domain in an hourly resolution to investigate and quantify the net response of the precipitation on the regional scale to a change in the aerosol

Model description
CCN calculation
Activation rate
Cloud scheme
Emissions
Results
16–20 August 2005 19–20 August 2005
Model setup
Aerosol number concentrations in the vicinity of clouds
Summary and conclusions
Full Text
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