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Do sea ice conditions have a measurable influence on snowfall? A study based on MOSAiC wintertime observations
  • Pablo Saavedra Garfias,
  • Heike Kalesse-Los,
  • Johanna Beikert
Pablo Saavedra Garfias
Institute for Meteorology, Faculty of Physics and Geosciences *, University of Leipzig

Corresponding Author:[email protected]

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Heike Kalesse-Los
Institute for Meteorology, Faculty of Physics and Geosciences *, University of Leipzig
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Johanna Beikert
Institute for Meteorology, Faculty of Physics and Geosciences *, University of Leipzig

Abstract

During the wintertime 2019-2020 of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, state-of-the-art remote sensing techniques have been used to study the observed dependency of the micro- and macro-physical cloud properties of low level clouds on the presence of sea ice leads in the vicinity of the RV Polarstern. It has been suggested that the water vapor transport (WVT) can be used as a mechanism to relate the cloud properties to the influence of sea ice leads quantified by the magnitude of sea ice lead fraction (LF). Among the findings are that clouds influenced by sea ice leads show a significant increase of liquid water path, cloud thickness and decrease in liquid phase cloud base height, as well as a slight dependency of total ice water content. Moreover, it has been found that the fraction of ice water content within the lowest cloud layer has a substantial difference when depicted as a function of cloud top temperature and segregated by the coupling status to the sea ice leads via the water vapor transport \cite{saavedra_garfias_asymmetries_2023}. This finding, however, considers the ice water fraction including the precipitating part of the cloud down to the surface. Therefore, the present contribution aims to study whether or not the snowfall shows a similar sea ice lead presence dependency when separated by the coupling status of the cloud-WVT-LF system. The extensive and meticulous study on the differences of snowfall estimated during the MOSAiC expedition performed by \citet{matrosov_high_2022a} , is exploited to easily add the different snowfall estimate dataset to the MOSAiC wintertime cloud properties dataset by \citet{garfias2023_datamosaic}.
Presented at: 4th International Summer Snowfall Workshop, 11-13 September 2023, Leipzig, Germany.
17 Oct 2023Submitted to ESS Open Archive
19 Oct 2023Published in ESS Open Archive