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Aerosol indirect effects

Authors :
Quaas, Johannes
Ming, Yi
Menon, Surabi
Takemura, Toshihiko
Wang, M.
Penner, Joyce E.
Gettelman, Andrew
Lohmann, Ulrike
Bellouin, Nicolas
Boucher, Olivier
Sayer, Andrew M.
Thomas, G. E.
McComiskey, Allison
Feingold, Graham
Hoose, Corinna
Kristjansson, Jon Egill
Liu, Xiaohong
Balkanski, Yves
Donner, Leo J.
Ginoux, Paul A.
Stier, Philip
Grandey, Benjamin
Feichter, Johann
Sednev, Igor
Bauer, Susanne E.
Koch, Dorothy
Grainger, Roy Gordon
Kirkevag, Alf
Iversen, Trond
Seland, Ø.
Easter, Richard
Ghan, Steven J.
Rasch, Philip J.
Morrison, Hugh
Lamarque, Jean-Francois
Iacono, Michael J.
Kinne, Sebastian
Schulz, M.
Copernicus Publications
Max-Planck-Institut für Meteorologie
Geophysical Fluid Dynamics Laboratory/NOAA
Lawrence Berkeley National Laboratory
Goddard Institute for Space Studies/NASA
Kyushu University
University of Michigan
National Center for Atmospheric Research
Eidgenössische Technische Hochschule Zürich
Met Office Hadley Centre
University of Oxford
NOAA Earth System Research Laboratory
University of Oslo
Pacific Northwest National Laboratory
Laboratoire des Sciences du Climat et de l’Environnement/IPSL
Norwegian Meteorological Institute
Atmospheric and Environmental Research Inc.
Source :
Atmospheric chemistry and physics (2009) 9, S. 8697-8717
Publication Year :
2009

Abstract

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterises aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (tau a) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. cloud droplet number concentration (N d) compares relatively well to the satellite data at least over the ocean. The relationship between (tau a) and liquid water path is simulated much too strongly by the models. This suggests that the implementation of the second aerosol indirect effect mainly in terms of an autoconversion parameterisation has to be revisited in the GCMs. A positive relationship between total cloud fraction (fcld) and tau a as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld–tau a relationship, our results indicate that none can be identified as a unique explanation. Relationships similar to the ones found in satellite data between tau a and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - tau a relationship show a strong positive correlation between tau a and fcld. The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of tau a, and parameterisation assumptions such as a lower bound on Nd. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of −1.5±0.5Wm−2. In an alternative approach, the radiative flux perturbation due to anthropogenic aerosols can be broken down into a component over the cloud-free portion of the globe (approximately the aerosol direct effect) and a component over the cloudy portion of the globe (approximately the aerosol indirect effect). An estimate obtained by scaling these simulated clearand cloudy-sky forcings with estimates of anthropogenic tau a and satellite-retrieved Nd–tau a regression slopes, respectively, yields a global, annual-mean aerosol direct effect estimate of −0.4±0.2Wm−2 and a cloudy-sky (aerosol indirect effect) estimate of −0.7±0.5Wm−2, with a total estimate of −1.2±0.4Wm−2.

Details

Language :
English
Database :
OpenAIRE
Journal :
Atmospheric chemistry and physics (2009) 9, S. 8697-8717
Accession number :
edsair.od......4178..9b0e9b1061860f3839f56358cc07f277