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    First triple-wavelength lidar observations of depolarization and extinction-to-backscatter ratios of Saharan dus
    (Katlenburg-Lindau : EGU, 2022) Haarig, Moritz; Ansmann, Albert; Engelmann, Ronny; Baars, Holger; Toledano, Carlos; Torres, Benjamin; Althausen, Dietrich; Radenz, Martin; Wandinger, Ulla
    Two layers of Saharan dust observed over Leipzig, Germany, in February and March 2021 were used to provide the first-ever lidar measurements of the dust lidar ratio (extinction-to-backscatter ratio) and linear depolarization ratio at all three classical lidar wavelengths (355, 532 and 1064gnm). The pure-dust conditions during the first event exhibit lidar ratios of 47g±g8, 50g±g5 and 69g±g14gsr and particle linear depolarization ratios of 0.242g±g0.024, 0.299g±g0.018 and 0.206g±g0.010 at wavelengths of 355, 532 and 1064gnm, respectively. The second, slightly polluted-dust case shows a similar spectral behavior of the lidar and depolarization ratio with values of the lidar ratio of 49g±g4, 46g±g5 and 57g±g9gsr and the depolarization ratio of 0.174g±g0.041, 0.298g±g0.016 and 0.242g±g0.007 at 355, 532 and 1064gnm, respectively. The results were compared with Aerosol Robotic Network (AERONET) version 3 (v3) inversion solutions and the Generalized Retrieval of Aerosol and Surface Properties (GRASP) at six and seven wavelengths. Both retrieval schemes make use of a spheroid shape model for mineral dust. The spectral slope of the lidar ratio from 532 to 1064gnm could be well reproduced by the AERONET and GRASP retrieval schemes. Higher lidar ratios in the UV were retrieved by AERONET and GRASP. The enhancement was probably caused by the influence of fine-mode pollution particles in the boundary layer which are included in the columnar photometer measurements. Significant differences between the measured and retrieved wavelength dependence of the particle linear depolarization ratio were found. The potential sources for these uncertainties are discussed.
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    Aerosol activation characteristics and prediction at the central European ACTRIS research station of Melpitz, Germany
    (Katlenburg-Lindau : EGU, 2022) Wang, Yuan; Henning, Silvia; Poulain, Laurent; Lu, Chunsong; Stratmann, Frank; Wang, Yuying; Niu, Shengjie; Pöhlker, Mira L.; Herrmann, Hartmut; Wiedensohler, Alfred
    Understanding aerosol particle activation is essential for evaluating aerosol indirect effects (AIEs) on climate. Long-term measurements of aerosol particle activation help to understand the AIEs and narrow down the uncertainties of AIEs simulation. However, they are still scarce. In this study, more than 4 years of comprehensive aerosol measurements were utilized at the central European research station of Melpitz, Germany, to gain insight into the aerosol particle activation and provide recommendations on improving the prediction of number concentration of cloud condensation nuclei (CCN, NCCN). (1) The overall CCN activation characteristics at Melpitz are provided. As supersaturation (SS) increases from 0.1% to 0.7%, the median NCCN increases from 399 to 2144cm-3, which represents 10% to 48% of the total particle number concentration with a diameter range of 10-800nm, while the median hygroscopicity factor (κ) and critical diameter (Dc) decrease from 0.27 to 0.19 and from 176 to 54nm, respectively. (2) Aerosol particle activation is highly variable across seasons, especially at low-SS conditions. At SSCombining double low line0.1%, the median NCCN and activation ratio (AR) in winter are 1.6 and 2.3 times higher than the summer values, respectively. (3) Both κ and the mixing state are size-dependent. As the particle diameter (Dp) increases, κ increases at Dp of 1/440 to 100nm and almost stays constant at Dp of 100 to 200nm, whereas the degree of the external mixture keeps decreasing at Dp of 1/440 to 200nm. The relationships of κ vs. Dp and degree of mixing vs. Dp were both fitted well by a power-law function. (4) Size-resolved κ improves the NCCN prediction. We recommend applying the κ-Dp power-law fit for NCCN prediction at Melpitz, which performs better than using the constant κ of 0.3 and the κ derived from particle chemical compositions and much better than using the NCCN (AR) vs. SS relationships. The κ-Dp power-law fit measured at Melpitz could be applied to predict NCCN for other rural regions. For the purpose of improving the prediction of NCCN, long-term monodisperse CCN measurements are still needed to obtain the κ-Dp relationships for different regions and their seasonal variations.