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- ItemIs the near-spherical shape the "new black" for smoke?(Katlenburg-Lindau : EGU, 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, DimitrisWe 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).
- ItemCalifornian Wildfire Smoke Over Europe: A First Example of the Aerosol Observing Capabilities of Aeolus Compared to Ground‐Based Lidar(Hoboken, NJ : Wiley, 2021) Baars, Holger; Radenz, Martin; Floutsi, Athena Augusta; Engelmann, Ronny; Althausen, Dietrich; Heese, Birgit; Ansmann, Albert; Flament, Thomas; Dabas, Alain; Trapon, Dimitri; Reitebuch, Oliver; Bley, Sebastian; Wandinger, UllaIn September 2020, extremely strong wildfires in the western United States of America (i.e., mainly in California) produced large amounts of smoke, which was lifted into the free troposphere. These biomass-burning-aerosol (BBA) layers were transported from the US west coast toward central Europe within 3–4 days turning the sky milky and receiving high media attention. The present study characterizes this pronounced smoke plume above Leipzig, Germany, using a ground-based multiwavelength-Raman-polarization lidar and the aerosol/cloud product of ESA’s wind lidar mission Aeolus. An exceptional high smoke-AOT >0.4 was measured, yielding to a mean mass concentration of 8 μg m−3. The 355 nm lidar ratio was moderate at around 40–50 sr. The Aeolus-derived backscatter, extinction and lidar ratio profiles agree well with the observations of the ground-based lidar PollyXT considering the fact that Aeolus’ aerosol and cloud products are still preliminary and subject to ongoing algorithm improvements.
- ItemRetrieval of ice-nucleating particle concentrations from lidar observations and comparison with UAV in situ measurements(Katlenburg-Lindau : EGU, 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, VassilisAerosols 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.