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Measurements of particle backscatter, extinction, and lidar ratio at 1064 nm with the rotational raman method in Polly-XT

2018, Engelmann, Ronny, Haarig, Moritz, Baars, Holger, Ansmann, Albert, Kottas, Michael, Marinou, Eleni, 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.

We replaced a 1064-nm interference filter of a Polly-XT lidar system by a 1058-nm filter to observe pure rotational Raman backscattering from atmospheric Nitrogen and Oxygen. Polly-XT is compact Raman lidar with a Nd:YAG laser (20 Hz, 200 mJ at 1064 nm) and a 30-cm telescope mirror which applies photomultipliers in photoncounting mode. We present the first measured signals at 1058 nm and the derived extinction profile from measurements aboard RV Polarstern and in Leipzig. In combination with another Polly-XT system we could also derive particle backscatter and lidar ratio profiles at 1064 nm.

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Lidar Ice nuclei estimates and how they relate with airborne in-situ measurements

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.

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A methodology for cloud masking uncalibrated lidar signals

2018, Binietoglou, Ioannis, D’Amico, Giuseppe, Baars, Holger, Belegante, Livio, Marinou, Eleni, 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.

Most lidar processing algorithms, such as those included in EARLINET's Single Calculus Chain, can be applied only to cloud-free atmospheric scenes. In this paper, we present a methodology for masking clouds in uncalibrated lidar signals. First, we construct a reference dataset based on manual inspection and then train a classifier to separate clouds and cloud-free regions. Here we present details of this approach together with an example cloud masks from an EARLINET station.