Modeling aerosol-cloud interactions with a self-consistent cloud scheme in a general circulation model Page: 4 of 60
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Abstract
This paper describes a self-consistent prognostic cloud scheme that is able
to predict cloud liquid water, amount and droplet number (Nd) from the same
updraft velocity field, and is suitable for modeling aerosol-cloud interactions in
general circulation models (GCMs). In the scheme, the evolution of droplets fully
interacts with the model meteorology. An explicit treatment of cloud condensation
nuclei (CCN) activation allows the scheme to take into account the contributions
to Nd of multiple types of aerosol (i.e., sulfate, organic and sea-salt aerosols) and
kinetic limitations of the activation process. An implementation of the prognostic
scheme in the Geophysical Fluid Dynamics Laboratory (GFDL) AM2 GCM yields
a vertical distribution of Nd characteristic of maxima in the lower troposphere
differing from that obtained through diagnosing Nd empirically from sulfate mass
concentrations. As a result, the agreement of model-predicted present-day cloud
parameters with satellite measurements is improved compared to using diagnosed
Nd.
The simulations with pre-industrial and present-day aerosols show that the
combined first and second indirect effects of anthropogenic sulfate and organic
aerosols give rise to a global annual mean flux change of -1.8 W m-2 consisting of
-2.0 W m-2 in shortwave and 0.2 W m-2 in longwave, as model response alters
cloud field, and subsequently longwave radiation. Liquid water path (LWP) and
total cloud amount increase by 19% and 0.6%, respectively. Largely owing to
high sulfate concentrations from fossil fuel burning, the Northern Hemisphere
mid-latitude land and oceans experience strong cooling. So does the tropical land
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Ming, Y; Ramaswamy, V; Donner, L J; Phillips, V T; Klein, S A; Ginoux, P A et al. Modeling aerosol-cloud interactions with a self-consistent cloud scheme in a general circulation model, article, May 2, 2005; Livermore, California. (https://digital.library.unt.edu/ark:/67531/metadc878103/m1/4/: accessed April 19, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT Libraries Government Documents Department.