Authors

Xiaohong Liu, University of Wyoming; Pacific Northwest National Laboratory, Richland, WA; University of MichiganFollow
N. Huneeus, Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, IPSL, Gif-sur-Yvette, France
M. Schulz, Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, IPSL, Gif-sur-Yvette, France; Meteorological Institut, Oslo, Norway
Y. Balkanski, Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, IPSL, Gif-sur-Yvette, France
J. Griesfeller, Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, IPSL, Gif-sur-Yvette, France; Meteorological Institut, Oslo, Norway
J. Prospero, University of Miami
S. Kinne, Max-Planck-Institut f̈ur Meteorologie, Hamburg, Germany
S. Bauer, Columbia University; NASA Goddard Institute for Space Studies, NY
O. Boucher, Met Office, Hadley Centre, Exeter, United Kingdom; Laboratoire de Ḿet́eorologie Dynamique, IPSL, CNRS/UPMC, Paris, France
M. Chin, NASA Goddard Space Flight Center, Greenbelt, MD
F. Dentener, European Comission, Joint Research Centre, Institute for Environment and Sustainability, Italy
T. Diehl, NASA, Goddard Space Flight Center, Greenbelt, MD; Universities Space Research Association, Columbia, MD
R. Easter, Pacific Northwest National Laboratory, Richland, WA
D. Fillmore, NCAR, Boulder, CO
S. Ghan, Pacific Northwest National Laboratory, Richland, WA
P. Ginoux, NOAA, Geophysical Fluid Dynamics Laboratory, Princeton, NJ
A. Grini, University of Oslo, Norway; Kongsberg Oil and Gas Technologies, Norway
L. Horowitz, NOAA, Geophysical Fluid Dynamics Laboratory, Princeton, NJ
D. Koch, Columbia University; NASA Goddard Institute for Space Studies, NY; US Department of Energy, Washington, DC
M.C. Krol, Utrecht University, Netherlands; Wageningen University, Meteorology and Air Quality, Netherlands
W. Landing, Florida State University
N. Mahowald, Cornell University
R. Miller, NASA Goddard Institute for Space Studies, NY; Columbia University
J. -J. Morcrette, European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom
G. Myhre, University of Oslo, Norway; Center for International Climate and Environmental Research-Oslo (CICERO), Norway
J. Penner, University of Michigan
J. Perlwitz, NASA Goddard Institute for Space Studies, NY; Columbia University
P. Stier, University of Oxford, United Kingdom
T. Takemura, Kyushu University, Fukuoka, Japan
C.S. Zender, University of California, Irvine

Document Type

Article

Publication Date

8-3-2011

Abstract

This study presents the results of a broad intercomparison of a total of 15 global aerosol models within the AeroCom project. Each model is compared to observations related to desert dust aerosols, their direct radiative effect, and their impact on the biogeochemical cycle, i.e., aerosol optical depth (AOD) and dust deposition. Additional comparisons to Angström exponent (AE), coarse mode AOD and dust surface concentrations are included to extend the assessment of model performance and to identify common biases present in models. These data comprise a benchmark dataset that is proposed for model inspection and future dust model development. There are large differences among the global models that simulate the dust cycle and its impact on climate. In general, models simulate the climatology of vertically integrated parameters (AOD and AE) within a factor of two whereas the total deposition and surface concentration are reproduced within a factor of 10. In addition, smaller mean normalized bias and root mean square errors are obtained for the climatology of AOD and AE than for total deposition and surface concentration. Characteristics of the datasets used and their uncertainties may influence these differences. Large uncertainties still exist with respect to the deposition fluxes in the southern oceans. Further measurements and model studies are necessary to assess the general model performance to reproduce dust deposition in ocean regions sensible to iron contributions. Models overestimate the wet deposition in regions dominated by dry deposition. They generally simulate more realistic surface concentration at stations downwind of the main sources than at remote ones. Most models simulate the gradient in AOD and AE between the different dusty regions. However the seasonality and magnitude of both variables is better simulated at African stations than Middle East ones. The models simulate the offshore transport of West Africa throughout the year but they overestimate the AOD and they transport too fine particles. The models also reproduce the dust transport across the Atlantic in the summer in terms of both AOD and AE but not so well in winter-spring nor the southward displacement of the dust cloud that is responsible of the dust transport into South America. Based on the dependency of AOD on aerosol burden and size distribution we use model bias with respect to AOD and AE to infer the bias of the dust emissions in Africa and the Middle East. According to this analysis we suggest that a range of possible emissions for North Africa is 400 to 2200 Tg yr-1 and in the Middle East 26 to 526 Tg yr-1. © 2011 Author(s).

DOI

10.5194/acp-11-7781-2011

Creative Commons License

Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.

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