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
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. The amount of airborne particles that will nucleate and form cloud droplets under specific atmospheric conditions, depends on their number concentration, size distribution and chemical composition. Aerosol is affected by primary particle emissions, gas-phase precursors, their transformation and interaction with atmospheric constituents, clouds and dynamics. A comprehensive assessment of these interactions requires an integrated approach; most studies however decouple aerosol processes from cloud and atmospheric dynamics and cannot account for all the feedbacks involved in aerosol-cloud-climate interactions. This study addresses aerosol-cloud-climate interactions with the Integrated Community Limited Area Modeling System (ICLAMS) that includes online parameterization of the physical and chemical processes between air quality and meteorology. ICLAMS is an extended version of the Regional Atmospheric Modeling System (RAMS) and it has been designed for coupled air quality – meteorology studies. Model sensitivity tests for a single-cloud study as well as for a case study over the Eastern Mediterranean illustrate the importance of aerosol properties in cloud formation and precipitation. Mineral dust particles are often coated with soluble material such as sea-salt, thus exhibiting increased CCN efficiency. Increasing the percentage of salt-coated dust particles by 15% in the model resulted in more vigorous convection and more intense updrafts. The clouds that were formed extended about 3 km higher and the initiation of precipitation was delayed by one hour. Including on-line parameterization of the aerosol effects improved the model bias for the twenty-four hour accumulated precipitation by 7%. However, the spatial distribution and the amounts of precipitation varied greatly between the different aerosol scenarios. These results indicate the large portion of uncertainty that remains unresolved and the need for more accurate description of aerosol feedbacks in atmospheric models and climate change predictions.