This thesis addresses a series of questions related to the problem of achieving reliable and physically consistent representations of aerosol-cloud interaction in global circulation models (GCM).In-situ data and modeling tools are used to develop and evaluate novel parameterization schemes for the process of aerosol activation for applications in GCM simulations. Atmospheric models of different complexity were utilized, ranging from detailed Lagrangian parcel model simulations of the condensational growth of droplets, to one-dimensional single column model with aerosol and cloud microphysics, and finally GCM simulations performed with the Community Atmosphere Model (CAM). A scheme for mapping the sub-grid scale variability of cloud droplet number concentrations (CDNC) to a number of microphysical process rates in a GCM was tested, finding that neglecting this impact can have substantial influences in the integrated cloud properties. A comprehensive comparison and evaluation of two widely used, physically-based activation parameterizations was performed in the framework of CAM5.1. This was achieved by utilizing a numerical adjoint sensitivity approach to comprehensively investigate their response under the wide range of aerosol and dynamical conditions encountered in GCM simulations. As a result of this, the specific variables responsible for the observed differences in the physical response across parameterizations are encountered, leading to further parameterization improvement.
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On the representation of sub-grid scale phenomena and its impact on clouds properties and climate
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