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- ItemIce nucleating particles over the Eastern Mediterranean measured by unmanned aircraft systems(Katlenburg-Lindau : EGU, 2017) Schrod, Jann; Weber, Daniel; Drücke, Jaqueline; Keleshis, Christos; Pikridas, Michael; Ebert, Martin; Cvetković, Bojan; Nickovic, Slobodan; Marinou, Eleni; Baars, Holger; Ansmann, Albert; Vrekoussis, Mihalis; Mihalopoulos, Nikos; Sciare, Jean; Curtius, Joachim; Bingemer, Heinz G.During an intensive field campaign on aerosol, clouds, and ice nucleation in the Eastern Mediterranean in April 2016, we measured the abundance of ice nucleating particles (INPs) in the lower troposphere from unmanned aircraft systems (UASs). Aerosol samples were collected by miniaturized electrostatic precipitators onboard the UASs at altitudes up to 2.5 km. The number of INPs in these samples, which are active in the deposition and condensation modes at temperatures from -20 to -30 °C, were analyzed immediately after collection on site using the ice nucleus counter FRIDGE (FRankfurt Ice nucleation Deposition freezinG Experiment). During the 1-month campaign, we encountered a series of Saharan dust plumes that traveled at several kilometers' altitude. Here we present INP data from 42 individual flights, together with aerosol number concentrations, observations of lidar backscattering, dust concentrations derived by the dust transport model DREAM (Dust Regional Atmospheric Model), and results from scanning electron microscopy. The effect of the dust plumes is reflected by the coincidence of INPs with the particulate matter (PM), the lidar signal, and the predicted dust mass of the model. This suggests that mineral dust or a constituent related to dust was a major contributor to the ice nucleating properties of the aerosol. Peak concentrations of above 100 INPs std L-1 were measured at -30 °C. The INP concentration in elevated plumes was on average a factor of 10 higher than at ground level. Since desert dust is transported for long distances over wide areas of the globe predominantly at several kilometers' altitude, we conclude that INP measurements at ground level may be of limited significance for the situation at the level of cloud formation.
- ItemIs the near-spherical shape the "new black" for smoke?(Katlenburg-Lindau : EGU, 2020) Gialitaki, Anna; Tsekeri, Alexandra; Amiridis, Vassilis; Ceolato, Romain; Paulien, Lucas; Kampouri, Anna; Gkikas, Antonis; Solomos, Stavros; Marinou, Eleni; Haarig, Moritz; Baars, Holger; Ansmann, Albert; Lapyonok, Tatyana; Lopatin, Anton; Dubovik, Oleg; Groß, Silke; Wirth, Martin; Tsichla, Maria; Tsikoudi, Ioanna; Balis, DimitrisWe examine the capability of near-sphericalshaped particles to reproduce the triple-wavelength particle linear depolarization ratio (PLDR) and lidar ratio (LR) values measured over Europe for stratospheric smoke originating from Canadian wildfires. The smoke layers were detected both in the troposphere and the stratosphere, though in the latter case the particles presented PLDR values of almost 18% at 532 nm as well as a strong spectral dependence from the UV to the near-IR wavelength. Although recent simulation studies of rather complicated smoke particle morphologies have shown that heavily coated smoke aggregates can produce large PLDR, herein we propose a much simpler model of compact near-spherical smoke particles. This assumption allows for the reproduction of the observed intensive optical properties of stratospheric smoke, as well as their spectral dependence. We further examine whether an extension of the current Aerosol Robotic Network (AERONET) scattering model to include the near-spherical shapes could be of benefit to the AERONET retrieval for stratospheric smoke cases associated with enhanced PLDR. Results of our study illustrate the fact that triple-wavelength PLDR and LR lidar measurements can provide us with additional insight when it comes to particle characterization. © 2020 Author(s).
- ItemAn automatic observation-based aerosol typing method for EARLINET(Katlenburg-Lindau : EGU, 2018) Papagiannopoulos, Nikolaos; Mona, Lucia; Amodeo, Aldo; D'Amico, Giuseppe; Gumà Claramunt, Pilar; Pappalardo, Gelsomina; Alados-Arboledas, Lucas; Guerrero-Rascado, Juan Luís; Amiridis, Vassilis; Kokkalis, Panagiotis; Apituley, Arnoud; Baars, Holger; Schwarz, Anja; Wandinger, Ulla; Binietoglou, Ioannis; Nicolae, Doina; Bortoli, Daniele; Comerón, Adolfo; Rodríguez-Gómez, Alejandro; Sicard, Michaël; Papayannis, Alex; Wiegner, MatthiasWe present an automatic aerosol classification method based solely on the European Aerosol Research Lidar Network (EARLINET) intensive optical parameters with the aim of building a network-wide classification tool that could provide near-real-time aerosol typing information. The presented method depends on a supervised learning technique and makes use of the Mahalanobis distance function that relates each unclassified measurement to a predefined aerosol type. As a first step (training phase), a reference dataset is set up consisting of already classified EARLINET data. Using this dataset, we defined 8 aerosol classes: clean continental, polluted continental, dust, mixed dust, polluted dust, mixed marine, smoke, and volcanic ash. The effect of the number of aerosol classes has been explored, as well as the optimal set of intensive parameters to separate different aerosol types. Furthermore, the algorithm is trained with literature particle linear depolarization ratio values. As a second step (testing phase), we apply the method to an already classified EARLINET dataset and analyze the results of the comparison to this classified dataset. The predictive accuracy of the automatic classification varies between 59% (minimum) and 90% (maximum) from 8 to 4 aerosol classes, respectively, when evaluated against pre-classified EARLINET lidar. This indicates the potential use of the automatic classification to all network lidar data. Furthermore, the training of the algorithm with particle linear depolarization values found in the literature further improves the accuracy with values for all the aerosol classes around 80%. Additionally, the algorithm has proven to be highly versatile as it adapts to changes in the size of the training dataset and the number of aerosol classes and classifying parameters. Finally, the low computational time and demand for resources make the algorithm extremely suitable for the implementation within the single calculus chain (SCC), the EARLINET centralized processing suite.
- ItemMicrophysical characterization of long-range transported biomass burning particles from North America at three EARLINET stations(Katlenburg-Lindau : EGU, 2017) Ortiz-Amezcua, Pablo; Guerrero-Rascado, Juan Luis; Granados-Muñoz, María José; Benavent-Oltra, José Antonio; Böckmann, Christine; Samaras, Stefanos; Stachlewska, Iwona S.; Janicka, Łucja; Baars, Holger; Bohlmann, Stephanie; Alados-Arboledas, LucasStrong events of long-range transported biomass burning aerosol were detected during July 2013 at three EARLINET (European Aerosol Research Lidar Network) stations, namely Granada (Spain), Leipzig (Germany) and Warsaw (Poland). Satellite observations from MODIS (Moderate Resolution Imaging Spectroradiometer) and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) instruments, as well as modeling tools such as HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) and NAAPS (Navy Aerosol Analysis and Prediction System), have been used to estimate the sources and transport paths of those North American forest fire smoke particles. A multiwavelength Raman lidar technique was applied to obtain vertically resolved particle optical properties, and further inversion of those properties with a regularization algorithm allowed for retrieving microphysical information on the studied particles. The results highlight the presence of smoke layers of 1-2 km thickness, located at about 5 km a.s.l. altitude over Granada and Leipzig and around 2.5 km a.s.l. at Warsaw. These layers were intense, as they accounted for more than 30 % of the total AOD (aerosol optical depth) in all cases, and presented optical and microphysical features typical for different aging degrees: Color ratio of lidar ratios (LR532/LR355) around 2, α-related ängström exponents of less than 1, effective radii of 0.3 μm and large values of single scattering albedos (SSA), nearly spectrally independent. The intensive microphysical properties were compared with columnar retrievals form co-located AERONET (Aerosol Robotic Network) stations. The intensity of the layers was also characterized in terms of particle volume concentration, and then an experimental relationship between this magnitude and the particle extinction coefficient was established.