In this paper we explore phase space for cloud processing of cloud condensation nuclei (CCN) via heterogeneous chemistry. A range of input CCN size spectra, parameterized as lognormal distributions, are used as input to a parcel model driven along trajectories derived from a large-eddy simulation of the stratocumulus-capped marine boundary layer. A simple sulfate chemistry model is coupled to the microphysical model. Gas phase concentrations of SO 2 , O 3 , H 2 O 2 , and NH 3 are varied so as to generate one case for which SO 2 processing is dominated by oxidation via O 3 and another case for which processing is dominated by oxidation via H 2 O 2 . The processed aerosol spectra are then used as input to an adiabatic parcel model that predicts the drop concentration for a given updraft velocity. Comparisons are made between predictions of drop concentration based on input of aerosol spectra that have experienced processing and an equivalent set that has not experienced processing. It is shown that for both of the chemical processing scenarios, heterogeneous processing can either enhance or suppress the number of drops activated in the subsequent cloud cycle, depending on the input CCN distribution and the magnitude of the updraft. Enhancement of drop concentration occurs in cases where the subsequent cloud cycle has low vertical velocity. A reduction in drop number occurs when updraft velocities in the subsequent cloud cycle are high. The size of the smallest CCN size category activated in the subsequent cloud cycle, relative to that experienced in the original cloud cycle, is important in determining the change in number of activated drops. By applying probability distribution functions of the vertical velocity, we calculate that, on average, drop concentrations are likely to be enhanced by between 10% and 20% for the cases examined. Nevertheless, the potential for both positive and negative changes in drop concentration due to cloud processing may complicate predictions of the indirect effect of aerosols on climate.
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