2019, Proestakis, Emmanouil, Amiridis, Vassilis, Marinou, Eleni, Binietoglou, Ioannis, Ansmann, Albert, Wandinger, Ulla, Hofer, Julian, Yorks, John, Nowottnick, Edward, Makhmudov, Abduvosit, Papayannis, Alexandros, Pietruczuk, Aleksander, Gialitaki, Anna, Apituley, Arnoud, Szkop, Artur, Muñoz Porcar, Constantino, Bortoli, Daniele, Dionisi, Davide, Althausen, Dietrich, Mamali, Dimitra, Balis, Dimitris, Nicolae, Doina, Tetoni, Eleni, Liberti, Gian Luigi, Baars, Holger, Mattis, Ina, Stachlewska, Iwona Sylwia, Voudouri, Kalliopi Artemis, Mona, Lucia, Mylonaki, Maria, Perrone, Maria Rita, Costa, Maria João, Sicard, Michael, Papagiannopoulos, Nikolaos, Siomos, Nikolaos, Burlizzi, Pasquale, Pauly, Rebecca, Engelmann, Ronny, Abdullaev, Sabur, Pappalardo, Gelsomina

We present the evaluation activity of the European Aerosol Research Lidar Network (EARLINET) for the quantitative assessment of the Level 2 aerosol backscatter coefficient product derived by the Cloud-Aerosol Transport System (CATS) aboard the International Space Station (ISS; Rodier et al., 2015). The study employs correlative CATS and EARLINET backscatter measurements within a 50km distance between the ground station and the ISS overpass and as close in time as possible, typically with the starting time or stopping time of the EARLINET performed measurement time window within 90min of the ISS overpass, for the period from February 2015 to September 2016. The results demonstrate the good agreement of the CATS Level 2 backscatter coefficient and EARLINET. Three ISS overpasses close to the EARLINET stations of Leipzig, Germany; Évora, Portugal; and Dushanbe, Tajikistan, are analyzed here to demonstrate the performance of the CATS lidar system under different conditions. The results show that under cloud-free, relative homogeneous aerosol conditions, CATS is in good agreement with EARLINET, independent of daytime and nighttime conditions. CATS low negative biases are observed, partially attributed to the deficiency of lidar systems to detect tenuous aerosol layers of backscatter signal below the minimum detection thresholds; these are biases which may lead to systematic deviations and slight underestimations of the total aerosol optical depth (AOD) in climate studies. In addition, CATS misclassification of aerosol layers as clouds, and vice versa, in cases of coexistent and/or adjacent aerosol and cloud features, occasionally leads to non-representative, unrealistic, and cloud-contaminated aerosol profiles. Regarding solar illumination conditions, low negative biases in CATS backscatter coefficient profiles, of the order of 6.1%, indicate the good nighttime performance of CATS. During daytime, a reduced signal-to-noise ratio by solar background illumination prevents retrievals of weakly scattering atmospheric layers that would otherwise be detectable during nighttime, leading to higher negative biases, of the order of 22.3%. © Author(s) 2019.

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, Dimitris

We 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).

2020, Papagiannopoulos, Nikolaos, D’Amico, Giuseppe, Gialitaki, Anna, Ajtai, Nicolae, Alados-Arboledas, Lucas, Amodeo, Aldo, Amiridis, Vassilis, Baars, Holger, Balis, Dimitris, Binietoglou, Ioannis, Comerón, Adolfo, Dionisi, Davide, Falconieri, Alfredo, Fréville, Patrick, Kampouri, Anna, Mattis, Ina, Mijić, Zoran, Molero, Francisco, Papayannis, Alex, Pappalardo, Gelsomina, Rodríguez-Gómez, Alejandro, Solomos, Stavros, Mona, Lucia

A stand-alone lidar-based method for detecting airborne hazards for aviation in near real time (NRT) is presented. A polarization lidar allows for the identification of irregular-shaped particles such as volcanic dust and desert dust. The Single Calculus Chain (SCC) of the European Aerosol Research Lidar Network (EARLINET) delivers high-resolution preprocessed data: the calibrated total attenuated backscatter and the calibrated volume linear depolarization ratio time series. From these calibrated lidar signals, the particle backscatter coefficient and the particle depolarization ratio can be derived in temporally high resolution and thus provide the basis of the NRT early warning system (EWS). In particular, an iterative method for the retrieval of the particle backscatter is implemented. This improved capability was designed as a pilot that will produce alerts for imminent threats for aviation. The method is applied to data during two diverse aerosol scenarios: first, a record breaking desert dust intrusion in March 2018 over Finokalia, Greece, and, second, an intrusion of volcanic particles originating from Mount Etna, Italy, in June 2019 over Antikythera, Greece. Additionally, a devoted observational period including several EARLINET lidar systems demonstrates the network's preparedness to offer insight into natural hazards that affect the aviation sector. © 2020 Author(s).

2017, Zerefos, Christos S., Eleftheratos, Kostas, Kapsomenakis, John, Solomos, Stavros, Inness, Antje, Balis, Dimitris, Redondas, Alberto, Eskes, Henk, Allaart, Marc, Amiridis, Vassilis, Dahlback, Arne, De Bock, Veerle, Diémoz, Henri, Engelmann, Ronny, Eriksen, Paul, Fioletov, Vitali, Gröbner, Julian, Heikkilä, Anu, Petropavlovskikh, Irina, Jarosławski, Janusz, Josefsson, Weine, Karppinen, Tomi, Köhler, Ulf, Meleti, Charoula, Repapis, Christos, Rimmer, John, Savinykh, Vladimir, Shirotov, Vadim, Siani, Anna Maria, Smedley, Andrew R.D., Stanek, Martin, Stübi, René

This study examines the adequacy of the existing Brewer network to supplement other networks from the ground and space to detect SO2 plumes of volcanic origin. It was found that large volcanic eruptions of the last decade in the Northern Hemisphere have a positive columnar SO2 signal seen by the Brewer instruments located under the plume. It is shown that a few days after the eruption the Brewer instrument is capable of detecting significant columnar SO2 increases, exceeding on average 2 DU relative to an unperturbed pre-volcanic 10-day baseline, with a mean close to 0 and σ = 0.46, as calculated from the 32 Brewer stations under study. Intercomparisons with independent measurements from the ground and space as well as theoretical calculations corroborate the capability of the Brewer network to detect volcanic plumes. For instance, the comparison with OMI (Ozone Monitoring Instrument) and GOME-2 (Global Ozone Monitoring Experiment-2) SO2 space-borne retrievals shows statistically significant agreement between the Brewer network data and the collocated satellite overpasses in the case of the Kasatochi eruption. Unfortunately, due to sparsity of satellite data, the significant positive departures seen in the Brewer and other ground networks following the Eyjafjallajökull, Bárðarbunga and Nabro eruptions could not be statistically confirmed by the data from satellite overpasses. A model exercise from the MACC (Monitoring Atmospheric Composition and Climate) project shows that the large increases in SO2 over Europe following the Bárðarbunga eruption in Iceland were not caused by local pollution sources or ship emissions but were clearly linked to the volcanic eruption. Sulfur dioxide positive departures in Europe following Bárðarbunga could be traced by other networks from the free troposphere down to the surface (AirBase (European air quality database) and EARLINET (European Aerosol Research Lidar Network)). We propose that by combining Brewer data with that from other networks and satellites, a useful tool aided by trajectory analyses and modelling could be created which can also be used to forecast high SO2 values both at ground level and in air flight corridors following future eruptions.

2018, Marinou, Eleni, Amiridis, Vassilis, Ansmann, Albert, Nenes, Athanasios, Balis, Dimitris, Schrod, Jann, Binietoglou, Ioannis, Solomos, Stavros, Mamali, Dimitra, Engelmann, Ronny, Baars, Holger, Kottas, Michael, Tsekeri, Alexandra, Proestakis, Emmanouil, Kokkalis, Panagiotis, Goloub, Philippe, Cvetkovic, Bojan, Nichovic, Slobodan, Mamouri, Rodanthi, Pikridas, Michael, Stavroulas, Iasonas, Keleshis, Christos, Sciare, Jean

By means of available ice nucleating particle (INP) parameterization schemes we compute profiles of dust INP number concentration utilizing Polly-XT and CALIPSO lidar observations during the INUIT-BACCHUS-ACTRIS 2016 campaign. The polarization-lidar photometer networking (POLIPHON) method is used to separate dust and non-dust aerosol backscatter, extinction, mass concentration, particle number concentration (for particles with radius > 250 nm) and surface area concentration. The INP final products are compared with aerosol samples collected from unmanned aircraft systems (UAS) and analyzed using the ice nucleus counter FRIDGE.

2018, Proestakis, Emmanouil, Amiridis, Vassilis, Kottas, Michael, Marinou, Eleni, Binietoglou, Ioannis, Ansmann, Albert, Wandinger, Ulla, Yorks, John, Nowottnick, Edward, Makhmudov, Abduvosit, Papayannis, Alexandros, Pietruczuk, Aleksander, Gialitaki, Anna, Apituley, Arnoud, Muñoz-Porcar, Constantino, Bortoli, Daniele, Dionisi, Davide, Althausen, Dietrich, Mamali, Dimitra, Balis, Dimitris, Nicolae, Doina, Tetoni, Eleni, Luigi Liberti, Gian, Baars, Holger, Stachlewska, Iwona S., Voudouri, Kalliopi-Artemis, Mona, Lucia, Mylonaki, Maria, Rita Perrone, Maria, João Costa, Maria, Sicard, Michael, Papagiannopoulos, Nikolaos, Siomos, Nikolaos, Burlizzi, Pasquale, Engelmann, Ronny, Abdullaev, Sabur F., Hofer, Julian, Pappalardo, Gelsomina, Nicolae, D., Makoto, A., Vassilis, A., Balis, D., Behrendt, A., Comeron, A., Gibert, F., Landulfo, E., McCormick, M.P., Senff, C., Veselovskii, I., Wandinger, U.

The Cloud-Aerosol Transport System (CATS) onboard the International Space Station (ISS), is a lidar system providing vertically resolved aerosol and cloud profiles since February 2015. In this study, the CATS aerosol product is validated against the aerosol profiles provided by the European Aerosol Research Lidar Network (EARLINET). This validation activity is based on collocated CATS-EARLINET measurements and the comparison of the particle backscatter coefficient at 1064nm.