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- ItemProfiling of Saharan dust and biomass-burning smoke with multiwavelength polarization Raman lidar at Cape Verde(Milton Park : Taylor & Francis, 2017) Tesche, Matthias; Gross, Silke; Ansmann, Albert; Müller, Detlef; Althausen, Dietrich; Freudenthaler, Volker; Esselborn, MichaelExtensive lidar measurements of Saharan dust and biomass-burning smoke were performed with one airborne and three ground-based instruments in the framework of the second part of the SAharan Mineral dUst experiMent (SAMUM-2a) during January and February of 2008 at Cape Verde. Further lidar observations with one system only were conducted duringMay and June of 2008 (SAMUM-2b). The active measurements were supported by Sun photometer observations. During winter, layers of mineral dust from the Sahara and biomass-burning smoke from southern West Africa pass Cape Verde on their way to South America while pure dust layers cross the Atlantic on their way to the Caribbean during summer. The mean 500-nm aerosol optical thickness (AOT) observed during SAMUM-2a was 0.35 ± 0.18. SAMUM-2a observations showed transport of pure dust within the lowermost 1.5 km of the atmospheric column. In the height range from 1.5 to 5.0 km, mixed dust/smoke layers with mean lidar ratios of 67 ± 14 sr at 355 and 532 nm, respectively, prevailed. Within these layers, wavelength-independent linear particle depolarization ratios of 0.12–0.18 at 355, 532, and 710 nm indicate a large contribution (30–70%) of mineral dust to the measured optical properties. Ångstr¨om exponents for backscatter and extinction of around 0.7 support this finding. Mean extinction coefficients in the height range between 2 and 4 km were 66 ± 6 Mm−1 at 355 nm and 48 ± 5 Mm−1 at 532 nm. Comparisons with airborne high-spectral-resolution lidar observations show good agreement within the elevated layers. 3–5 km deep dust layers where observed during SAMUM-2b. These layers showed optical properties similar to the ones of SAMUM-1 in Morocco with a mean 500-nm AOT of 0.4 ± 0.2. Dust extinction coefficients were about 80 ± 6 Mm−1 at 355 and 532 nm. Dust lidar ratios were 53 ± 10 sr at 355 and 532 nm, respectively. Dust depolarization ratios showed an increase with wavelength from 0.31 ± 0.10 at 532 nm to 0.37 ± 0.07 at 710 nm.
- ItemRegional modelling of Saharan dust and biomass-burning smoke, Part I: Model description and evaluation(Milton Park : Taylor & Francis, 2017) Heinold, Bernd; Tegen, Ina; Schepanski, Kerstin; Tesche, Matthias; Esselborn, Michael; Freudenthaler, Volker; Gross, Silke; Kandler, Konrad; Knippertz, Peter; Müller, Detlef; Schladitz, Alexander; Toledano, Carlos; Weinzierl, Bernadett; Ansmann, Albert; Althausen, Dietrich; Müller, Thomas; Petzold, Andreas; Wiedensohler, AlfredThe spatio-temporal evolution of the Saharan dust and biomass-burning plume during the SAMUM-2 field campaign in January and February 2008 is simulated at 28 km horizontal resolution with the regional model-system COSMOMUSCAT. The model performance is thoroughly tested using routine ground-based and space-borne remote sensing and local field measurements. Good agreement with the observations is found in many cases regarding transport patterns, aerosol optical thicknesses and the ratio of dust to smoke aerosol. The model also captures major features of the complex aerosol layering. Nevertheless, discrepancies in the modelled aerosol distribution occur, which are analysed in detail. The dry synoptic dynamics controlling dust uplift and transport during the dry season are well described by the model, but surface wind peaks associated with the breakdown of nocturnal low-level jets are not always reproduced. Thus, a strong dust outbreak is underestimated. While dust emission modelling is a priori more challenging, since strength and placement of dust sources depend on on-line computed winds, considerable inaccuracies also arise in observation-based estimates of biomass-burning emissions. They are caused by cloud and spatial errors of satellite fire products and uncertainties in fire emission parameters, and can lead to unrealistic model results of smoke transport.