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    An overview of the first decade of PollyNET: An emerging network of automated Raman-polarization lidars for continuous aerosol profiling
    (München : European Geopyhsical Union, 2016) Baars, Holger; Kanitz, Thomas; Engelmann, Ronny; Althausen, Dietrich; Heese, Birgit; Komppula, Mika; Preißler, Jana; Tesche, Matthias; Ansmann, Albert; Wandinger, Ulla; Lim, Jae-Hyun; Ahn, Joon Young; Stachlewska, Iwona S.; Amiridis, Vassilis; Marinou, Eleni; Seifert, Patric; Hofer, Julian; Skupin, Annett; Schneider, Florian; Bohlmann, Stephanie; Foth, Andreas; Bley, Sebastian; Pfüller, Anne; Giannakaki, Eleni; Lihavainen, Heikki; Viisanen, Yrjö; Hooda, Rakesh Kumar; Pereira, Sérgio Nepomuceno; Bortol, Daniele; Wagner, Frank; Mattis, Ina; Janicka, Lucja; Markowicz, Krzysztof M.; Achtert, Peggy; Artaxo, Paulo; Pauliquevis, Theotonio; Souza, Rodrigo A.F.; Sharma, Ved Prakesh; van Zyl, Pieter Gideon; Beukes, Johan Paul; Sun, Junying; Rohwer, Erich G.; Deng, Ruru; Mamouri, Rodanthi-Elisavet; Zamorano, Felix
    A global vertically resolved aerosol data set covering more than 10 years of observations at more than 20 measurement sites distributed from 63° N to 52° S and 72° W to 124° E has been achieved within the Raman and polarization lidar network PollyNET. This network consists of portable, remote-controlled multiwavelength-polarization-Raman lidars (Polly) for automated and continuous 24/7 observations of clouds and aerosols. PollyNET is an independent, voluntary, and scientific network. All Polly lidars feature a standardized instrument design with different capabilities ranging from single wavelength to multiwavelength systems, and now apply unified calibration, quality control, and data analysis. The observations are processed in near-real time without manual intervention, and are presented online at http://polly.tropos.de/. The paper gives an overview of the observations on four continents and two research vessels obtained with eight Polly systems. The specific aerosol types at these locations (mineral dust, smoke, dust-smoke and other dusty mixtures, urban haze, and volcanic ash) are identified by their Ångström exponent, lidar ratio, and depolarization ratio. The vertical aerosol distribution at the PollyNET locations is discussed on the basis of more than 55 000 automatically retrieved 30 min particle backscatter coefficient profiles at 532 nm as this operating wavelength is available for all Polly lidar systems. A seasonal analysis of measurements at selected sites revealed typical and extraordinary aerosol conditions as well as seasonal differences. These studies show the potential of PollyNET to support the establishment of a global aerosol climatology that covers the entire troposphere.
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    Californian Wildfire Smoke Over Europe: A First Example of the Aerosol Observing Capabilities of Aeolus Compared to Ground‐Based Lidar
    (Hoboken, NJ : Wiley, 2021) Baars, Holger; Radenz, Martin; Floutsi, Athena Augusta; Engelmann, Ronny; Althausen, Dietrich; Heese, Birgit; Ansmann, Albert; Flament, Thomas; Dabas, Alain; Trapon, Dimitri; Reitebuch, Oliver; Bley, Sebastian; Wandinger, Ulla
    In September 2020, extremely strong wildfires in the western United States of America (i.e., mainly in California) produced large amounts of smoke, which was lifted into the free troposphere. These biomass-burning-aerosol (BBA) layers were transported from the US west coast toward central Europe within 3–4 days turning the sky milky and receiving high media attention. The present study characterizes this pronounced smoke plume above Leipzig, Germany, using a ground-based multiwavelength-Raman-polarization lidar and the aerosol/cloud product of ESA’s wind lidar mission Aeolus. An exceptional high smoke-AOT >0.4 was measured, yielding to a mean mass concentration of 8 μg m−3. The 355 nm lidar ratio was moderate at around 40–50 sr. The Aeolus-derived backscatter, extinction and lidar ratio profiles agree well with the observations of the ground-based lidar PollyXT considering the fact that Aeolus’ aerosol and cloud products are still preliminary and subject to ongoing algorithm improvements.
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    Large-eddy simulations over Germany using ICON: A comprehensive evaluation
    (Hoboken, NJ : Wiley, 2017) Heinze, Rieke; Dipankar, Anurag; Henken, Cintia Carbajal; Moseley, Christopher; Sourdeval, Odran; Trömel, Silke; Xie, Xinxin; Adamidis, Panos; Ament, Felix; Baars, Holger; Barthlott, Christian; Behrendt, Andreas; Blahak, Ulrich; Bley, Sebastian; Brdar, Slavko; Brueck, Matthias; Crewell, Susanne; Deneke, Hartwig; Di Girolamo, Paolo; Evaristo, Raquel; Fischer, Jürgen; Frank, Christopher; Friederichs, Petra; Göcke, Tobias; Gorges, Ksenia; Hande, Luke; Hanke, Moritz; Hansen, Akio; Hege, Hans-Christian; Hoose, Corinna; Jahns, Thomas; Kalthoff, Norbert; Klocke, Daniel; Kneifel, Stefan; Knippertz, Peter; Kuhn, Alexander; van Laar, Thriza; Macke, Andreas; Maurer, Vera; Mayer, Bernhard; Meyer, Catrin I.; Muppa, Shravan K.; Neggers, Roeland A.J.; Orlandi, Emiliano; Pantillon, Florian; Pospichal, Bernhard; Röber, Niklas; Scheck, Leonhard; Seifert, Axel; Seifert, Patric; Senf, Fabian; Siligam, Pavan; Simmer, Clemens; Steinke, Sandra; Stevens, Bjorn; Wapler, Kathrin; Weniger, Michael; Wulfmeyer, Volker; Zängl, Günther; Zhangl, Dan; Quaase, Johannes
    Large-eddy simulations (LES) with the new ICOsahedral Non-hydrostatic atmosphere model (ICON) covering Germany are evaluated for four days in spring 2013 using observational data from various sources. Reference simulations with the established Consortium for Small-scale Modelling (COSMO) numerical weather prediction model and further standard LES codes are performed and used as a reference. This comprehensive evaluation approach covers multiple parameters and scales, focusing on boundary-layer variables, clouds and precipitation. The evaluation points to the need to work on parametrizations influencing the surface energy balance, and possibly on ice cloud microphysics. The central purpose for the development and application of ICON in the LES configuration is the use of simulation results to improve the understanding of moist processes, as well as their parametrization in climate models. The evaluation thus aims at building confidence in the model's ability to simulate small- to mesoscale variability in turbulence, clouds and precipitation. The results are encouraging: the high-resolution model matches the observed variability much better at small- to mesoscales than the coarser resolved reference model. In its highest grid resolution, the simulated turbulence profiles are realistic and column water vapour matches the observed temporal variability at short time-scales. Despite being somewhat too large and too frequent, small cumulus clouds are well represented in comparison with satellite data, as is the shape of the cloud size spectrum. Variability of cloud water matches the satellite observations much better in ICON than in the reference model. In this sense, it is concluded that the model is fit for the purpose of using its output for parametrization development, despite the potential to improve further some important aspects of processes that are also parametrized in the high-resolution model.