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Vertical profiles of aerosol mass concentration derived by unmanned airborne in situ and remote sensing instruments during dust events
2018, Mamali, Dimitra, Marinou, Eleni, Sciare, Jean, Pikridas, Michael, Kokkalis, Panagiotis, Kottas, Michael, Binietoglou, Ioannis, Tsekeri, Alexandra, Keleshis, Christos, Engelmann, Ronny, Baars, Holger, Ansmann, Albert, Amiridis, Vassilis, Russchenberg, Herman, Biskos, George
In situ measurements using unmanned aerial vehicles (UAVs) and remote sensing observations can independently provide dense vertically resolved measurements of atmospheric aerosols, information which is strongly required in climate models. In both cases, inverting the recorded signals to useful information requires assumptions and constraints, and this can make the comparison of the results difficult. Here we compare, for the first time, vertical profiles of the aerosol mass concentration derived from light detection and ranging (lidar) observations and in situ measurements using an optical particle counter on board a UAV during moderate and weak Saharan dust episodes. Agreement between the two measurement methods was within experimental uncertainty for the coarse mode (i.e. particles having radii > 0.5 μm), where the properties of dust particles can be assumed with good accuracy. This result proves that the two techniques can be used interchangeably for determining the vertical profiles of aerosol concentrations, bringing them a step closer towards their systematic exploitation in climate models.
EARLINET evaluation of the CATS Level 2 aerosol backscatter coefficient product
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.