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Ground-based remote-sensing observations of aerosol-cloud-dynamics interaction at Neumayer Station III, Antarctica, in 2023

Urheber*innen

Radenz,  Martin
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Engelmann,  Ronny
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Henning,  Silvia
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Frey,  Markus
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Schmithüsen,  Holger
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Baars,  Holger
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Bühl,  Johannes
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Muser,  Lukas Ole
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Wullenweber,  Nellie
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Weller,  Rolf
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Griesche,  Hannes Jascha
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Seifert,  Patric
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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Zitation

Radenz, M., Engelmann, R., Henning, S., Frey, M., Schmithüsen, H., Baars, H., Bühl, J., Muser, L. O., Wullenweber, N., Weller, R., Griesche, H. J., Seifert, P. (2023): Ground-based remote-sensing observations of aerosol-cloud-dynamics interaction at Neumayer Station III, Antarctica, in 2023, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-2345


Zitierlink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5018412
Zusammenfassung
The interaction of aerosol particles with radiation, clouds, and precipitation is a critical issue in understanding the atmosphere in the mid- and high latitudes of the southern hemisphere. The high abundance of supercooled liquid water in clouds above the Southern Ocean and coastal Antarctica is still puzzling. Atmospheric scientists cannot explain yet to which extent vertical dynamics or pristine aerosol conditions control the persistence of liquid layers. Furthermore, virtually nothing is known about how the abundant supercooled-liquid water influences precipitation formation and the radiative budget. This is especially true in the remote region of Antarctica, where detailed vertically resolved observations of aerosol, cloud, and precipitation are scarce and prevent one to capture the complex cloud processes. We will present a unique observation campaign that will help to address the open questions by contributing a one-year remote-sensing dataset for a coastal ice shelf in Dronning Maud Land in the Atlantic sector of Antarctica. The mobile ground-based remote-sensing supersite OCEANET-Atmosphere is deployed at Neumayer Station III (70.67°S, 8.27°W) in 2023. The synergistic combination of a multi-wavelength polarization Raman lidar, a 35-Ghz polarimetric cloud radar, a microwave radiometer, and a Doppler lidar provides valuable profile information of cloud and aerosol properties as well as their interaction. The remote-sensing data is augmented by the stations long-term records of meteorological parameters and aerosol physics and chemistry. Through case studies, we will demonstrate the supersites’ capabilities to relate cloud-relevant aerosol properties with cloud-microphysics and discuss the potential to address the science questions based on the dataset.