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    Atmospheric dust modeling from meso to global scales with the online NMMB/BSC-Dust model – Part 2: Experimental campaigns in Northern Africa
    (München : European Geopyhsical Union, 2012) Haustein, K.; Pérez, C.; Baldasano, J.M.; Jorba, O.; Basart, S.; Miller, R.L.; Janjic, Z.; Black, T.; Nickovic, S.; Todd, M.C.; Washington, R.; Müller, D.; Tesche, M.; Weinzierl, B.; Esselborn, M.; Schladitz, A.
    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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    Airborne spectral radiation measurements to derive solar radiative forcing of Saharan dust mixed with biomass burning smoke particles
    (Milton Park : Taylor & Francis, 2017) Bauer, S.; Bierwirth, E.; Esselborn, M.; Petzold, A.; Macke, A.; Trautmann, T.; Wendisch, M.
    Airborne measurements of upward solar spectral irradiances were performed during the second Saharan Mineral dUst experiMent (SAMUM-2) campaign based on the Cape Verde Islands. Additionally, airborne high resolution lidar measurements of vertical profiles of particle extinction coefficients were collected in parallel to the radiation data. Aerosol layers of Saharan dust, partly mixed with biomass-burning smoke, were probed. With corresponding radiative transfer simulations the single scattering albedo and the asymmetry parameter of the aerosol particles were derived although with high uncertainty. The broad-band aerosol solar radiative forcing at the top of atmosphere was calculated and examined as a function of the aerosol types. However, due to uncertainties in both the measurements and the calculations the chemical composition cannot be identified. In addition, a mostly measurement-based method to derive the broad-band aerosol solar radiative forcing was used. This approach revealed clear differences of broad-band net irradiances as a function of the aerosol optical depth. The data were used to identify different aerosol types from different origins. Higher portions of biomass-burning smoke lead to larger broad-band net irradiances.