The Effect of Giant CCN on Cloud Droplet Activation

Donifan Barahona (1), Rosaind E. L. West (3), Philip Stier (3), Sami Romakkaniemi (4), Harri Kokkola(5), Vlassis Karydis(2), and ATHANASIOS NENES (1, 2)

(1) School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, United States (2) School of Earth and Atmospheric Sciences, Georgia Institute of Technology, United States (3) Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, England (4) Department of Physics and Mathematics, University of Eastern Finland, Finland (5) Finnish Meteorological Institute, Kuopio Unit, Finland

     Abstract Number: 673
     Last modified: May 14, 2010

Abstract
Large cloud condensation nuclei (CCN) (e.g, aged dust particles and seasalt) cannot attain their equilibrium size during the typical timescale of cloud droplet activation. Cloud activation parameterizations applied to aerosol with a large fraction of large CCN often do not account for this limitation adequately and can give biased predictions of cloud droplet number concentration (CDNC). Here we present a simple approach to address this problem that can easily be incorporated into cloud activation parameterizations. This method is demonstrated with an activation parameterization based on “population splitting”; it is shown that accounting for large CCN effects eliminates a positive bias in CDNC where the aerosol dry geometric diameter is greater than 0.5 micro-m. The parameterization is implemented in the NASA Global Modeling Initiative (GMI) atmospheric and chemical and transport model to study the effect of giant CCN on global CDNC and aerosol indirect effect.