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Volume 12, issue 6
Atmos. Chem. Phys., 12, 2933–2958, 2012
https://doi.org/10.5194/acp-12-2933-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 12, 2933–2958, 2012
https://doi.org/10.5194/acp-12-2933-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 23 Mar 2012

Research article | 23 Mar 2012

Atmospheric dust modeling from meso to global scales with the online NMMB/BSC-Dust model – Part 2: Experimental campaigns in Northern Africa

K. Haustein2,1,*, C. Pérez5,4,3, J. M. Baldasano6,1, O. Jorba1, S. Basart1, R. L. Miller4,3, Z. Janjic7, T. Black7, S. Nickovic8, M. C. Todd9, R. Washington2, D. Müller10,14,**, M. Tesche11, B. Weinzierl12, M. Esselborn13,12, and A. Schladitz14 K. Haustein et al.
  • 1Barcelona Supercomputing Center, Earth Science Department, Barcelona, Spain
  • 2Climate Research Group, Centre for the Environment, University of Oxford, Oxford, UK
  • 3NASA Goddard Institute for Space Studies, New York, USA
  • 4Department of Applied Physics and Applied Math, Columbia University, New York, USA
  • 5International Research Institute for Climate and Society, Palisades, New York, USA
  • 6Environmental Modeling Laboratory, Technical University of Catalonia, Barcelona, Spain
  • 7Environmental Modeling Center, National Centers for Environmental Prediction, Camp Springs, Maryland, USA
  • 8Research Department, World Meteorological Organization, Geneva, Switzerland
  • 9Department of Geography, University of Sussex, Brighton, UK
  • 10School of Environmental Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, South Korea
  • 11Department of Environmental Science, Stockholm University, Stockholm, Sweden
  • 12Deutsches Zentrum fur Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
  • 13European Southern Observatory, Technology Division, Garching, Germany
  • 14Leibniz Institute for Tropospheric Research, Leipzig, Germany
  • *now at: Climate Research Group, Centre for the Environment, University of Oxford, Oxford, UK
  • **now at: Science Systems and Applications Inc., NASA Langley Research Center, Hampton, Virginia, USA

Abstract. The new NMMB/BSC-Dust model is intended to provide short to medium-range weather and dust forecasts from regional to global scales. It is an online model in which the dust aerosol dynamics and physics are solved at each model time step. The companion paper (Pérez et al., 2011) develops the dust model parameterizations and provides daily to annual evaluations of the model for its global and regional configurations. Modeled aerosol optical depth (AOD) was evaluated against AERONET Sun photometers over Northern Africa, Middle East and Europe with correlations around 0.6–0.7 on average without dust data assimilation. In this paper we analyze in detail the behavior of the model using data from the Saharan Mineral dUst experiment (SAMUM-1) in 2006 and the Bodélé Dust Experiment (BoDEx) in 2005. AOD from satellites and Sun photometers, vertically resolved extinction coefficients from lidars and particle size distributions at the ground and in the troposphere are used, complemented by wind profile data and surface meteorological measurements. All simulations were performed at the regional scale for the Northern African domain at the expected operational horizontal resolution of 25 km. Model results for SAMUM-1 generally show good agreement with satellite data over the most active Saharan dust sources. The model reproduces the AOD from Sun photometers close to sources and after long-range transport, and the dust size spectra at different height levels. At this resolution, the model is not able to reproduce a large haboob that occurred during the campaign. Some deficiencies are found concerning the vertical dust distribution related to the representation of the mixing height in the atmospheric part of the model. For the BoDEx episode, we found the diurnal temperature cycle to be strongly dependant on the soil moisture, which is underestimated in the NCEP analysis used for model initialization. The low level jet (LLJ) and the dust AOD over the Bodélé are well reproduced. The remaining negative AOD bias (due to underestimated surface wind speeds) can be substantially reduced by decreasing the threshold friction velocity in the model.

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