Atmos. Chem. Phys. Discuss., 10, 23781-23864, 2010
www.atmos-chem-phys-discuss.net/10/23781/2010/
doi:10.5194/acpd-10-23781-2010
© Author(s) 2010. This work is distributed
under the Creative Commons Attribution 3.0 License.
Review Status
This discussion paper has been under review for the journal Atmospheric Chemistry and Physics (ACP). Please refer to the corresponding final paper in ACP.
Global dust model intercomparison in AeroCom phase I
N. Huneeus1, M. Schulz1,2, Y. Balkanski1, J. Griesfeller1,2, S. Kinne3, J. Prospero4, S. Bauer5,6, O. Boucher7, M. Chin8, F. Dentener9, T. Diehl10, R. Easter11, D. Fillmore12, S. Ghan11, P. Ginoux13, A. Grini14,15, L. Horowitz13, D. Koch5,6, M. C. Krol16,17, W. Landing18, X. Liu11,19, N. Mahowald20, R. Miller5,6, J.-J. Morcrette21, G. Myhre14,22, J. E. Penner19, J. Perlwitz5,6, P. Stier23, T. Takemura24, and C. Zender25
1Laboratoire des Sciences du Climat et de l'Environnement, Gif-sur-Yvette, France
2Meteorological Institut, Oslo, Norway
3Max-Planck-Institut fur Meteorologie, Hamburg, Germany
4Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, USA
5Columbia University, New York, USA
6NASA GISS, New York, NY, USA
7Met Office, Hadley Centre, Exeter, UK
8NASA Goddard Space Flight Center, Greenbelt, MD, USA
9European Commission, Joint Research Centre, Inst. for Environment and Sustainability, Italy
10University of Maryland Baltimore County, Baltimore, Maryland, USA
11Pacific Northwest National Laboratory, Richland, USA
12NCAR, Boulder, Colorado, USA
13NOAA, Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey, USA
14University of Oslo, Oslo, Norway
15Kongsberg Oil & Gas Technologies, Norway
16Utrecht University, Utrecht, The Netherlands
17Wageningen University, Wageningen, The Netherlands
18Departement of Earth, Ocean and Atmospheric Science, Florida State University, Tallahassee, Florida, USA
19University of Michigan, Ann Arbor, MI, USA
20Departement of Earth and Atmospheric Sciences, Cornell University, Ithaca, NY, USA
21European Centre for Medium-Range Weather Forecasts, Reading, UK
22Center for International Climate and Environmental Research – Oslo (CICERO) Oslo, Norway
23Atmospheric, Oceanic and Planetary Physics, University of Oxford, UK
24Kyushu University, Fukuoka, Japan
25University of California, Irvine, USA

Abstract. Desert dust plays an important role in the climate system through its impact on Earth's radiative budget and its role in the biogeochemical cycle as a source of iron in high-nutrient-low-chlorophyll regions. A large degree of diversity exists between the many global models that simulate the dust cycle to estimate its impact on climate. We present the results of a broad intercomparison of a total of 15 global aerosol models within the AeroCom project. Each model is compared to observations focusing on variables responsible for the uncertainties in estimating the direct radiative effect and the dust 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 concentration are included to extend the assessment of model performance. These datasets form a benchmark data set which is proposed for model inspection and future dust model developments. In general, models perform better in simulating climatology of vertically averaged integrated parameters (AOD and AE) in dusty sites than they do with total deposition and surface concentration. Almost all models overestimate deposition fluxes over Europe, the Indian Ocean, the Atlantic Ocean and ice core data. Differences among the models arise when simulating deposition at remote sites with low fluxes over the Pacific and the Southern Atlantic Ocean. This study also highlights important differences in models ability to reproduce the deposition flux over Antarctica. The cause of this discrepancy could not be identified but different dust regimes at each site and issues with data quality should be considered. Models generally simulate better surface concentration at stations downwind of the main sources than at remote ones. Likewise, they simulate better surface concentration at stations affected by Saharan dust than at stations affected by Asian dust. 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 also reproduce the dust transport across the Atlantic in terms of both AOD and AE; they simulate the offshore transport of West Africa throughout the year and limit the transport across the Atlantic to the summer months, yet overestimating the AOD and transporting too fine particles. However, most of the models do not reproduce the southward displacement of the dust cloud during the winter responsible of the transport of dust into South America. Based on the dependency of AOD on aerosol burden and size distribution we use model data bias with respect to AOD and AE and infer on the over/under estimation of the dust emissions. According to this we suggest the emissions in the Sahara be between 792 and 2271 Tg/yr and the one in the Middle East between 212 and 329 Tg/yr.

Citation: Huneeus, N., Schulz, M., Balkanski, Y., Griesfeller, J., Kinne, S., Prospero, J., Bauer, S., Boucher, O., Chin, M., Dentener, F., Diehl, T., Easter, R., Fillmore, D., Ghan, S., Ginoux, P., Grini, A., Horowitz, L., Koch, D., Krol, M. C., Landing, W., Liu, X., Mahowald, N., Miller, R., Morcrette, J.-J., Myhre, G., Penner, J. E., Perlwitz, J., Stier, P., Takemura, T., and Zender, C.: Global dust model intercomparison in AeroCom phase I, Atmos. Chem. Phys. Discuss., 10, 23781-23864, doi:10.5194/acpd-10-23781-2010, 2010.
 
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