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    Doppler lidar studies of heat island effects on vertical mixing of aerosols during SAMUM-2
    (Milton Park : Taylor & Francis, 2017) Engelmann, Ronny; Ansmann, Albert; Horn, Stefan; Seifert, Patric; Althausen, Dietrich; Tesche, Matthias; Esselborn, Michael; Fruntke, Julia; Lieke, Kirsten; Freudenthaler, Volker; Gross, Silke
    A wind Doppler lidar was deployed next to three aerosol lidars during the SAMUM–2 campaign on the main island of Cape Verde. The effects of the differential heating of the island and the surrounding ocean and the orographic impact of the capital island Santiago and the small island on its luv side, Maio, are investigated. Horizontal and vertical winds were measured in the disturbed maritime boundary layer and compared to local radiosoundings. Lidar measurements from the research aircraft Falcon and a 3-D Large Eddy Simulation (LES) model were used in addition to study the heating effects on the scale of the islands. Indications are found that these effects can widely control the downward mixing from greater heights to the surface of African aerosols, mainly Saharan dust and biomass-burning smoke, which were detected in a complex layering over the Cape Verde region.
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    Modelling lidar-relevant optical properties of complex mineral dust aerosols
    (Milton Park : Taylor & Francis, 2017) Gasteiger, Josef; Wiegner, Matthias; Groß, Silke; Freudenthaler, Volker; Toledano, Carlos; Tesche, Matthias; Kandler, Konrad
    We model lidar-relevant optical properties of mineral dust aerosols and compare the modelling results with optical properties derived from lidar measurements during the SAMUM field campaigns. The Discrete Dipole Approximation is used for optical modelling of single particles. For modelling of ensemble properties, the desert aerosol type of the OPAC aerosol dataset is extended by mixtures of absorbing and non-absorbing irregularly shaped mineral dust particles. Absorbing and non-absorbing particles are mixed to mimic the natural mineralogical inhomogeneity of dust particles. A sensitivity study reveals that the mineralogical inhomogeneity is critical for the lidar ratio at short wavelengths; it has to be considered for agreement with the observed wavelength dependence of the lidar ratio. The amount of particles with low aspect ratios (about 1.4 and lower) affects the lidar ratio at any lidar wavelength; their amount has to be low for agreement with SAMUM observations. Irregularly shaped dust particles with typical refractive indices, in general, have higher linear depolarization ratios than corresponding spheroids, and improve the agreement with the observations.
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    Regional 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, Alfred
    The 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.