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Model intercomparison of indirect aerosol effects

Modeled differences in predicted effects are increasingly used to help quantify the uncertainty of these effects. Here, we examine modeled differences in the aerosol indirect effect in a series of experiments that help to quantify how and why model-predicted aerosol indirect forcing
varies between models. The experiments start with an experiment
in which aerosol concentrations, the parameterization of droplet concentrations and the autoconversion scheme are all specified and end with an experiment that examines the predicted aerosol indirect forcing when only aerosol sources are specified. Although there are large differences in the predicted liquid water path among the models, the predicted aerosol first indirect effect for the first experiment is rather
similar, about −0.6Wm−2 to −0.7Wm−2. Changes to the autoconversion scheme can lead to large changes in the liquid water path of the models and to the response of the liquid water path to changes in aerosols. Adding an autoconversion scheme that depends on the droplet concentration caused a larger (negative) change in net outgoing shortwave radiation compared to the 1st indirect effect, and the increase varied from only 22% to more than a factor of three. The change
in net shortwave forcing in the models due to varying the autoconversion
scheme depends on the liquid water content of the clouds as well as their predicted droplet concentrations, and both increases and decreases in the net shortwave forcing can occur when autoconversion schemes are changed. The parameterization of cloud fraction within models is not
sensitive to the aerosol concentration, and, therefore, the response
of the modeled cloud fraction within the present models appears to be smaller than that which would be associated with model “noise”. The prediction of aerosol concentrations, given a fixed set of sources, leads to some of the largest differences in the predicted aerosol indirect radiative forcing among the models, with values of cloud forcing ranging from
−0.3Wm−2 to −1.4Wm−2. Thus, this aspect of modeling requires significant improvement in order to improve the prediction of aerosol indirect effects.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa.de:bsz:15-qucosa-186265
Date30 October 2015
CreatorsPenner, Joyce E., Quaas, Johannes, Storelvmo, Trude, Takemura , Toshihiko, Boucher, Olivier, Guo, Huan, Kirkevag, Alf, Kristjansson, Jon Egill, Seland, Ø.
ContributorsUniversity of Michigan, Department of Atmospheric, Oceanic and Space Sciences, Laboratoire de Météorologie Dynamique, CNRS, Institut Pierre Simon Laplace, University of Oslo, Department of Geosciences, Kyushu University, Research Institute for Applied Mechanics,, Universite de Lille I, Laboratoire d’Optique Atmosphérique, CNRS, Copernicus Publications,
PublisherUniversitätsbibliothek Leipzig
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typedoc-type:article
Formatapplication/pdf
SourceAtmospheric chemistry and physics (2006) 6, S. 3391-3405

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