References

ACP

Atmospheric Chemistry and Physics

ACP

1680-7324

Copernicus GmbH

Göttingen, Germany

10.5194/acp-6-3391-2006

Model intercomparison of indirect aerosol effects

Penner

J. E.

¹ Quaas

² ⁶ Storelvmo

³ Takemura

⁴ Boucher

⁵ ⁷ Guo

¹ Kirkevåg

³ Kristjánsson

J. E.

³ Seland

Ø.

University of Michigan, Department of Atmospheric, Oceanic and Space Sciences, Ann Arbor, USA

Laboratoire de Météorologie Dynamique, CNRS/Institut Pierre Simon Laplace, 4, place Jussieu, 75005 Paris, France

University of Oslo, Department of Geosciences, Oslo, Norway

Research Institute for Applied Mechanics, Kyushu University, Fukuoka, Japan

Laboratoire d'Optique Atmosphérique, CNRS/Universite de Lille I, 59655 Villeneuve d'Ascq Cedex, France

now at: Max Planck Institute for Meteorology, Bundesstraße 53, Hamburg, Germany

now at: Hadley Centre, Met Office, FitzRoy Road, Exeter EX1 3PB, UK

21 08 2006

6 11 3391 3405

This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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The full text article is available as a PDF file from http://www.atmos-chem-phys.net/6/3391/2006/acp-6-3391-2006.pdf

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 −0.6 Wm−2 to −0.7 Wm−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 −0.3 Wm−2 to −1.4 Wm−2. Thus, this aspect of modeling requires significant improvement in order to improve the prediction of aerosol indirect effects.

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