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- ItemThe potential of elastic and polarization lidars to retrieve extinction profiles(Katlenburg-Lindau : Copernicus, 2020) Giannakaki, Elina; Kokkalis, Panos; Marinou, Eleni; Bartsotas, Nikolaos S.; Amiridis, Vassilis; Ansmann, Albert; Komppula, MikaA new method, called ElEx (elastic extinction), is proposed for the estimation of extinction coefficient lidar profiles using only the information provided by the elastic and polarization channels of a lidar system. The method is applicable to lidar measurements both during daytime and nighttime under well-defined aerosol mixtures. ElEx uses the particle backscatter profiles at 532 nm and the vertically resolved particle linear depolarization ratio measurements at the same wavelength. The particle linear depolarization ratio and the lidar ratio values of pure aerosol types are also taken from literature. The total extinction profile is then estimated and compared well with Raman retrievals. In this study, ElEx was applied in an aerosol mixture of marine and dust particles at Finokalia station during the CHARADMExp campaign. Any difference between ElEx and Raman extinction profiles indicates that the nondust component could be probably attributed to polluted marine or polluted continental aerosols. Comparison with sun photometer aerosol optical depth observations is performed as well during daytime. Differences in the total aerosol optical depth are varying between 1.2 % and 72 %, and these differences are attributed to the limited ability of the lidar to correctly represent the aerosol optical properties in the near range due to the overlap problem. © 2020 Author(s).
- ItemApplication of the shipborne remote sensing supersite OCEANET for profiling of Arctic aerosols and clouds during Polarstern cruise PS106(Katlenburg-Lindau : Copernicus, 2020) Griesche, Hannes J.; Seifer, Patric; Ansmann, Albert; Baars, Holger; Velasco, Carola Barrientos; Bühl, Johannes; Engelmann, Ronny; Radenz, Martin; Zhenping, Yin; Macke, AndreasFrom 25 May to 21 July 2017, the research vessel Polarstern performed the cruise PS106 to the high Arctic in the region north and northeast of Svalbard. The mobile remote-sensing platform OCEANET was deployed aboard Polarstern. Within a single container, OCEANET houses state-of-the-art remote-sensing equipment, including a multiwavelength Raman polarization lidar PollyXT and a 14-channel microwave radiometer HATPRO (Humidity And Temperature PROfiler). For the cruise PS106, the measurements were supplemented by a motion-stabilized 35 GHz cloud radar Mira-35. This paper describes the treatment of technical challenges which were immanent during the deployment of OCEANET in the high Arctic. This includes the description of the motion stabilization of the cloud radar Mira-35 to ensure vertical-pointing observations aboard the moving Polarstern as well as the applied correction of the vessels heave rate to provide valid Doppler velocities. The correction ensured a leveling accuracy of ±0.5◦ during transits through the ice and an ice floe camp. The applied heave correction reduced the signal induced by the vertical movement of the cloud radar in the PSD of the Doppler velocity by a factor of 15. Low-level clouds, in addition, frequently prevented a continuous analysis of cloud conditions from synergies of lidar and radar within Cloudnet, because the technically determined lowest detection height of Mira-35 was 165 m above sea level. To overcome this obstacle, an approach for identification of the cloud presence solely based on data from the near-field receiver of PollyXT at heights from 50 m and 165 m above sea level is presented. We found low-level stratus clouds, which were below the lowest detection range of most automatic ground-based remote-sensing instruments during 25 % of the observation time. We present case studies of aerosol and cloud studies to introduce the capabilities of the data set. In addition, new approaches for ice crystal effective radius and eddy dissipation rates from cloud radar measurements and the retrieval of aerosol optical and microphysical properties from the observations of PollyXT are introduced. © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License.