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.

2019, Haarig, Moritz, Walser, Adrian, Ansmann, Albert, Dollner, Maximilian, Althausen, Dietrich, Sauer, Daniel, Farrell, David, Weinzierl, Bernadett

The present study aims to evaluate lidar retrievals of cloud-relevant aerosol properties by using polarization lidar and coincident airborne in situ measurements in the Saharan Air Layer (SAL) over the Barbados region. Vertical profiles of the number concentration of cloud condensation nuclei (CCN), large particles (diameter d > 500 nm), surface area, mass, and ice-nucleating particle (INP) concentration are derived from the lidar measurements and compared with CCN concentrations and the INP-relevant aerosol properties measured in situ with aircraft. The measurements were performed in the framework of the Saharan Aerosol Longrange Transport and Aerosol-Cloud-Interaction Experiment (SALTRACE) in summer 2013. The CCN number concentrations derived from lidar observations were up to a factor of 2 higher than the ones measured in situ aboard the research aircraft Falcon. Possible reasons for the difference are discussed. The number concentration of particles with a dry radius of more than 250 nm and the surface-area concentration obtained from the lidar observations and used as input for the INP parameterizations agreed well (< 30 %-50 % deviation) with the aircraft measurements. In a pronounced lofted dust layer during summer (10 July 2013), the lidar retrieval yielded 100-300 CCN per cubic centimeter at 0.2 % water supersaturation and 10-200 INPs per liter at-25?C. Excellent agreement was also obtained in the comparison of mass concentration profiles. During the SALTRACE winter campaign (March 2014), the dust layer from Africa was mixed with smoke particles which dominated the CCN number concentration. This example highlights the unique lidar potential to separate smoke and dust contributions to the CCN reservoir and thus to identify the sensitive role of smoke in trade wind cumuli developments over the tropical Atlantic during the winter season. © 2017 Georg Thieme Verlag. All rights reserved.