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Aerosol absorption profiling from the synergy of lidar and sun-photometry: The ACTRIS-2 campaigns in Germany, Greece and Cyprus

2018, Tsekeri, Alexandra, Amiridis, Vassilis, Lopatin, Anton, Marinou, Eleni, Giannakaki, Eleni, Pikridas, Michael, Sciare, Jean, Liakakou, Eleni, Gerasopoulos, Evangelos, Duesing, Sebastian, Corbin, Joel C., Gysel, Martin, Bukowiecki, Nicolas, Baars, Holger, Engelmann, Ronny, Wehner, Birgit, Kottas, Michael, Mamali, Dimitra, Kokkalis, Panagiotis, Raptis, Panagiotis I., Stavroulas, Iasonas, Keleshis, Christos, Müller, Detlef, Solomos, Stavros, Binietoglou, Ioannis, Mihalopoulos, Nikolaos, Papayannis, Alexandros, Stachlewska, Iwona S., Igloffstein, Julia, Wandinger, Ulla, Ansmann, Albert, Dubovik, Oleg, Goloub, Philippe, 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.

Aerosol absorption profiling is crucial for radiative transfer calculations and climate modelling. Here, we utilize the synergy of lidar with sun-photometer measurements to derive the absorption coefficient and single scattering albedo profiles during the ACTRIS-2 campaigns held in Germany, Greece and Cyprus. The remote sensing techniques are compared with in situ measurements in order to harmonize and validate the different methodologies and reduce the absorption profiling uncertainties.

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Application of the Garrlic algorithm for the characterization of dust and marine particles utilizing the lidar-sunphotometer synergy

2016, Tsekeri, Alexandra, Amiridis, Vassilis, Lopatin, Anton, Marinou, Eleni, Kokkalis, Panos, Solomos, Stavros, Engelmann, Ronny, Baars, Holger, Wandinger, Ulla, Ansmann, Albert, Schüttemeyer, Dirk, Dubovik, Oleg

The importance of studying the vertical distribution of aerosol plumes is prominent in regional and climate studies. The new Generalized Aerosol Retrieval from Radiometer and Lidar Combined data algorithm (GARRLiC) provides this opportunity combining active and passive ground-based remote sensing from lidar and sunphotometer measurements. Here, we utilize GARRLiC capabilities for the characterization of Saharan dust and marine particles at the Eastern Mediterranean region during the Characterization of Aerosol mixtures of Dust And Marine origin Experiment (CHARADMExp). Two different case studies are presented, a dust-dominated case which we managed to characterize successfully in terms of the particle microphysical properties and their vertical distribution and a case of two separate layers of marine and dust particles for which the characterization proved to be more challenging.

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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.

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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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GARRLiC and LIRIC: Strengths and limitations for the characterization of dust and marine particles along with their mixtures

2017, Tsekeri, Alexandra, Lopatin, Anton, Amiridis, Vassilis, Marinou, Eleni, Igloffstein, Julia, Siomos, Nikolaos, Solomos, Stavros, Kokkalis, Panagiotis, Engelmann, Ronny, Baars, Holger, Gratsea, Myrto, Raptis, Panagiotis I., Binietoglou, Ioannis, Mihalopoulos, Nikolaos, Kalivitis, Nikolaos, Kouvarakis, Giorgos, Bartsotas, Nikolaos, Kallos, George, Basart, Sara, Schuettemeyer, Dirk, Wandinger, Ulla, Ansmann, Albert, Chaikovsky, Anatoli P., Dubovik, Oleg

The Generalized Aerosol Retrieval from Radiometer and Lidar Combined data algorithm (GARRLiC) and the LIdar-Radiometer Inversion Code (LIRIC) provide the opportunity to study the aerosol vertical distribution by combining ground-based lidar and sun-photometric measurements. Here, we utilize the capabilities of both algorithms for the characterization of Saharan dust and marine particles, along with their mixtures, in the south-eastern Mediterranean during the CHARacterization of Aerosol mixtures of Dust and Marine origin Experiment (CHARADMExp). Three case studies are presented, focusing on dust-dominated, marinedominated and dust-marine mixing conditions. GARRLiC and LIRIC achieve a satisfactory characterization for the dust-dominated case in terms of particle microphysical properties and concentration profiles. The marine-dominated and the mixture cases are more challenging for both algorithms, although GARRLiC manages to provide more detailed microphysical retrievals compared to AERONET, while LIRIC effectively discriminates dust and marine particles in its concentration profile retrievals. The results are also compared with modelled dust and marine concentration profiles and surface in situ measurements.

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Retrieval of ice-nucleating particle concentrations from lidar observations and comparison with UAV in situ measurements

2019, Marinou, Eleni, Tesche, Matthias, Nenes, Athanasios, Ansmann, Albert, Schrod, Jann, Mamali, Dimitra, Tsekeri, Alexandra, Pikridas, Michael, Baars, Holger, Engelmann, Ronny, Voudouri, Kalliopi-Artemis, Solomos, Stavros, Sciare, Jean, Groß, Silke, Ewald, Florian, Amiridis, Vassilis

Aerosols that are efficient ice-nucleating particles (INPs) are crucial for the formation of cloud ice via heterogeneous nucleation in the atmosphere. The distribution of INPs on a large spatial scale and as a function of height determines their impact on clouds and climate. However, in situ measurements of INPs provide sparse coverage over space and time. A promising approach to address this gap is to retrieve INP concentration profiles by combining particle concentration profiles derived by lidar measurements with INP efficiency parameterizations for different freezing mechanisms (immersion freezing, deposition nucleation). Here, we assess the feasibility of this new method for both ground-based and spaceborne lidar measurements, using in situ observations collected with unmanned aerial vehicles (UAVs) and subsequently analyzed with the FRIDGE (FRankfurt Ice nucleation Deposition freezinG Experiment) INP counter from an experimental campaign at Cyprus in April 2016. Analyzing five case studies we calculated the cloud-relevant particle number concentrations using lidar measurements (n250,dry with an uncertainty of 20 % to 40 % and Sdry with an uncertainty of 30 % to 50 %), and we assessed the suitability of the different INP parameterizations with respect to the temperature range and the type of particles considered. Specifically, our analysis suggests that our calculations using the parameterization of Ullrich et al. (2017) (applicable for the temperature range −50 to −33 ∘C) agree within 1 order of magnitude with the in situ observations of nINP; thus, the parameterization of Ullrich et al. (2017) can efficiently address the deposition nucleation pathway in dust-dominated environments. Additionally, our calculations using the combination of the parameterizations of DeMott et al. (2015, 2010) (applicable for the temperature range −35 to −9 ∘C) agree within 2 orders of magnitude with the in situ observations of INP concentrations (nINP) and can thus efficiently address the immersion/condensation pathway of dust and nondust particles. The same conclusion is derived from the compilation of the parameterizations of DeMott et al. (2015) for dust and Ullrich et al. (2017) for soot.