1University of Athens, School of Physics, University of Athens Campus, Bldg. Phys-5, 15784 Athens, Greece
2Energy, Environment and Water Research Centre, The Cyprus Institute, Nicosia, Cyprus, Greece
3ATMET LLC P.O. Box 19195, Boulder, CO 80308-2195, USA
4School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, USA
5School of Earth and Atmospheric Sciences, Georgia Institute of Technology, USA
6Dept. of Geophysics and Planetary Sciences, Tel Aviv University, Tel Aviv, Israel
Abstract. This report addresses the effects of pollution on the development of precipitation in clean ("pristine") and polluted ("hazy") environments in the Eastern Mediterranean by using the Integrated Community Limited Area Modeling System (ICLAMS) (an extended version of the Regional Atmospheric Modeling System, RAMS). The use of this model allows one to investigate the interactions of the aerosols with cloud development. The simulations show that the onset of precipitation in hazy clouds is delayed compared to pristine conditions. Adding small concentrations of GCCN to polluted clouds promotes early-stage rain. The addition of GCCN to pristine clouds has no effect on precipitation amounts. Topography was found to be more important for the distribution of precipitation than aerosol properties. Increasing by 15% the concentration of hygroscopic dust particles for a case study over the Eastern Mediterranean resulted in more vigorous convection and more intense updrafts. The clouds that were formed extended about three kilometers higher, delaying the initiation of precipitation by one hour. Prognostic treatment of the aerosol concentrations in the explicit cloud droplet nucleation scheme of the model, improved the model performance for the twenty-four hour accumulated precipitation. The spatial distribution and the amounts of precipitation were found to vary greatly between the different aerosol scenarios. These results indicate the large uncertainty that remains and the need for more accurate description of aerosol feedbacks in atmospheric models and climate change predictions.