Comprehensively accounting for the effect of giant CCN in cloud activation parameterizations
1School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, USA
2School of Earth and Atmospheric Sciences, Georgia Institute of Technology, USA
3Atmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford, UK
4Department of Physics and Mathematics, University of Eastern Finland, Finland
5Finnish Meteorological Institute, Kuopio Unit, Finland
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 activation parameterizations based on the "population splitting" concept of Nenes and Seinfeld (2003); 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 μm. The method proposed here can also be extended to include the water vapor depletion from pre-existing droplets and ice crystals in global and regional atmospheric models.