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 m...

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Main Authors: Penner, Joyce E., Quaas, Johannes, Storelvmo, Trude, Takemura , Toshihiko, Boucher, Olivier, Guo, Huan, Kirkevag, Alf, Kristjansson, Jon Egill, Seland, Ø.
Other Authors: University of Michigan, Department of Atmospheric, Oceanic and Space Sciences
Format: Article
Language:English
Published: Universitätsbibliothek Leipzig 2015
Subjects:
Online Access:http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-186265
http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-186265
http://www.qucosa.de/fileadmin/data/qucosa/documents/18626/penner_acp_2006.pdf
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spelling ndltd-DRESDEN-oai-qucosa.de-bsz-15-qucosa-1862652015-10-31T03:25:02Z Model intercomparison of indirect aerosol effects Penner, Joyce E. Quaas, Johannes Storelvmo, Trude Takemura , Toshihiko Boucher, Olivier Guo, Huan Kirkevag, Alf Kristjansson, Jon Egill Seland, Ø. Klima Atmosphäre Wolken Aerosol climate atmosphere clouds aerosol ddc:551 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. Universitätsbibliothek Leipzig University 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, 2015-10-30 doc-type:article application/pdf http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-186265 urn:nbn:de:bsz:15-qucosa-186265 issn:1680-7316 http://www.qucosa.de/fileadmin/data/qucosa/documents/18626/penner_acp_2006.pdf Atmospheric chemistry and physics (2006) 6, S. 3391-3405 eng
collection NDLTD
language English
format Article
sources NDLTD
topic Klima
Atmosphäre
Wolken
Aerosol
climate
atmosphere
clouds
aerosol
ddc:551
spellingShingle Klima
Atmosphäre
Wolken
Aerosol
climate
atmosphere
clouds
aerosol
ddc:551
Penner, Joyce E.
Quaas, Johannes
Storelvmo, Trude
Takemura , Toshihiko
Boucher, Olivier
Guo, Huan
Kirkevag, Alf
Kristjansson, Jon Egill
Seland, Ø.
Model intercomparison of indirect aerosol effects
description 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.
author2 University of Michigan, Department of Atmospheric, Oceanic and Space Sciences
author_facet University of Michigan, Department of Atmospheric, Oceanic and Space Sciences
Penner, Joyce E.
Quaas, Johannes
Storelvmo, Trude
Takemura , Toshihiko
Boucher, Olivier
Guo, Huan
Kirkevag, Alf
Kristjansson, Jon Egill
Seland, Ø.
author Penner, Joyce E.
Quaas, Johannes
Storelvmo, Trude
Takemura , Toshihiko
Boucher, Olivier
Guo, Huan
Kirkevag, Alf
Kristjansson, Jon Egill
Seland, Ø.
author_sort Penner, Joyce E.
title Model intercomparison of indirect aerosol effects
title_short Model intercomparison of indirect aerosol effects
title_full Model intercomparison of indirect aerosol effects
title_fullStr Model intercomparison of indirect aerosol effects
title_full_unstemmed Model intercomparison of indirect aerosol effects
title_sort model intercomparison of indirect aerosol effects
publisher Universitätsbibliothek Leipzig
publishDate 2015
url http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-186265
http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-186265
http://www.qucosa.de/fileadmin/data/qucosa/documents/18626/penner_acp_2006.pdf
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