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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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    Regional Saharan dust modelling during the SAMUM 2006 campaign
    (Milton Park : Taylor & Francis, 2017) Heinold, Bernd; Tegen, Ina; Esselborn, Michael; Kandler, Konrad; Knippertz, Peter; Müller, Detlef; Schladitz, Alexander; Tesche, Matthias; Weinzierl, Bernadett; Ansmann, Albert; Althausen, Dietrich; Laurent, Benoit; Massling, Andreas; Müller, Thomas; Petzold, Andreas; Schepanski, Kerstin; Wiedensohler, Alfred
    The regional dust model system LM-MUSCAT-DES was developed in the framework of the SAMUM project. Using the unique comprehensive data set of near-source dust properties during the 2006SAMUMfield campaign, the performance of the model system is evaluated for two time periods in May and June 2006. Dust optical thicknesses, number size distributions and the position of the maximum dust extinction in the vertical profiles agree well with the observations. However, the spatio-temporal evolution of the dust plumes is not always reproduced due to inaccuracies in the dust source placement by the model. While simulated winds and dust distributions are well matched for dust events caused by dry synoptic-scale dynamics, they are often misrepresented when dust emissions are caused by moist convection or influenced by small-scale topography that is not resolved by the model. In contrast to long-range dust transport, in the vicinity of source regions the model performance strongly depends on the correct prediction of the exact location of sources. Insufficiently resolved vertical grid spacing causes the absence of inversions in the model vertical profiles and likely explains the absence of the observed sharply defined dust layers.