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    The sensitivity of the colour of dust in MSG-SEVIRI Desert Dust infrared composite imagery to surface and atmospheric conditions
    (Göttingen : Copernicus GmbH, 2019) Banks, J.R.; Hünerbein, A.; Heinold, B.; Brindley, H.E.; Deneke, H.; Schepanski, K.
    Infrared "Desert Dust" composite imagery taken by the Spinning Enhanced Visible and InfraRed Imager (SEVIRI), onboard the Meteosat Second Generation (MSG) series of satellites above the equatorial East Atlantic, has been widely used for more than a decade to identify and track the presence of dust storms from and over the Sahara Desert, the Middle East, and southern Africa. Dust is characterised by distinctive pink colours in the Desert Dust false-colour imagery; however, the precise colour is influenced by numerous environmental properties, such as the surface thermal emissivity and skin temperature, the atmospheric water vapour content, the quantity and height of dust in the atmosphere, and the infrared optical properties of the dust itself. For this paper, simulations of SEVIRI infrared measurements and imagery have been performed using a modelling system, which combines dust concentrations simulated by the aerosol transport model COSMO-MUSCAT (COSMO: COnsortium for Small-scale MOdelling; MUSCAT: MUltiScale Chemistry Aerosol Transport Model) with radiative transfer simulations from the RTTOV (Radiative Transfer for TOVS) model. Investigating the sensitivity of the synthetic infrared imagery to the environmental properties over a 6-month summertime period from 2011 to 2013, it is confirmed that water vapour is a major control on the apparent colour of dust, obscuring its presence when the moisture content is high. Of the three SEVIRI channels used in the imagery (8.7, 10.8, and 12.0 μm), the channel at 10.8 μm has the highest atmospheric transmittance and is therefore the most sensitive to the surface skin temperature. A direct consequence of this sensitivity is that the background desert surface exhibits a strong diurnal cycle in colour, with light blue colours possible during the day and purple hues prevalent at night. In dusty scenes, the clearest pink colours arise from high-altitude dust in dry atmospheres. Elevated dust influences the dust colour primarily by reducing the contrast in atmospheric transmittance above the dust layer between the SEVIRI channels at 10.8 and 12.0 μm, thereby boosting red and pink colours in the imagery. Hence, the higher the dust altitude, the higher the threshold column moisture needed for dust to be obscured in the imagery: for a sample of dust simulated to have an aerosol optical depth (AOD) at 550 nm of 2-3 at an altitude of 3-4 km, the characteristic colour of the dust may only be impaired when the total column water vapour is particularly moist ('39 mm). Meanwhile, dust close to the surface (altitude < 1 km) is only likely to be apparent when the atmosphere is particularly dry and when the surface is particularly hot, requiring column moisture/13 mm and skin temperatures '314 K, and is highly unlikely to be apparent when the skin temperature is/300 K. Such low-altitude dust will regularly be almost invisible within the imagery, since it will usually be beneath much of the atmospheric water vapour column. It is clear that the interpretation of satellite-derived dust imagery is greatly aided by knowledge of the background environment.
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    The impact of mineral dust on cloud formation during the Saharan dust event in April 2014 over Europe
    (Göttingen : Copernicus GmbH, 2018) Weger, M.; Heinold, B.; Engler, C.; Schumann, U.; Seifert, A.; Fößig, R.; Voigt, C.; Baars, H.; Blahak, U.; Borrmann, S.; Hoose, C.; Kaufmann, S.; Krämer, M.; Seifert, P.; Senf, F.; Schneider, J.; Tegen, I.
    A regional modeling study on the impact of desert dust on cloud formation is presented for a major Saharan dust outbreak over Europe from 2 to 5 April 2014. The dust event coincided with an extensive and dense cirrus cloud layer, suggesting an influence of dust on atmospheric ice nucleation. Using interactive simulation with the regional dust model COSMO-MUSCAT, we investigate cloud and precipitation representation in the model and test the sensitivity of cloud parameters to dust-cloud and dust-radiation interactions of the simulated dust plume. We evaluate model results with ground-based and spaceborne remote sensing measurements of aerosol and cloud properties, as well as the in situ measurements obtained during the ML-CIRRUS aircraft campaign. A run of the model with single-moment bulk microphysics without online dust feedback considerably underestimated cirrus cloud cover over Germany in the comparison with infrared satellite imagery. This was also reflected in simulated upper-Tropospheric ice water content (IWC), which accounted for only 20 % of the observed values. The interactive dust simulation with COSMO-MUSCAT, including a two-moment bulk microphysics scheme and dust-cloud as well as dust-radiation feedback, in contrast, led to significant improvements. The modeled cirrus cloud cover and IWC were by at least a factor of 2 higher in the relevant altitudes compared to the noninteractive model run. We attributed these improvements mainly to enhanced deposition freezing in response to the high mineral dust concentrations. This was corroborated further in a significant decrease in ice particle radii towards more realistic values, compared to in situ measurements from the ML-CIRRUS aircraft campaign. By testing different empirical ice nucleation parameterizations, we further demonstrate that remaining uncertainties in the ice-nucleating properties of mineral dust affect the model performance at least as significantly as including the online representation of the mineral dust distribution. Dust-radiation interactions played a secondary role for cirrus cloud formation, but contributed to a more realistic representation of precipitation by suppressing moist convection in southern Germany. In addition, a too-low specific humidity in the 7 to 10 km altitude range in the boundary conditions was identified as one of the main reasons for misrepresentation of cirrus clouds in this model study.