Learning from local snow properties for large-scale Antarctic ice pack volume: SNOWflAke

• Applicant: Dr. Stefanie Arndt
• Subject Area: Oceanography
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 493362232

Snow depth on sea ice is an essential climate variable, as it dominates the energy and momentum exchanges across the atmosphere-ice-ocean interfaces and actively contributes to the sea ice mass balance. The Antarctic sea ice is characterized by a year-round snow cover preventing surface melt in summer, and amplifying sea ice growth through extensive snow-to-ice conversion processes. The lack of knowledge on both snow depth and the complex seasonal stratigraphy causes substantial uncertainties in large-scale data products from satellite remote sensing. Also, the accurate representation of these small-scale processes within the snowpack in numerical models, in particular in climate models, remains a major challenge. This leads to essential uncertainties in the Antarctic sea ice energy and mass budgets as outlined in the IPCC “Special Report on the Ocean and Cryosphere in a Changing Climate” (Ch. 3.7). SNOWflake will therefore test the hypothesis that seasonal variations of snowpack properties on Antarctic sea ice are sensitive indicators for changing atmospheric forcing as they could trigger snow-albedo feedbacks that accelerate sea ice melting and retreat. This hypothesis is important as snow has so far contributed to a positive Antarctic sea ice mass balance due to widespread snow-to-ice conversion processes. The present climate warming might reverse this evolution and lead to increased surface melting, as currently prevalent for Arctic sea ice, with potential feedbacks for the Earths’ climate. However, those feedbacks are not yet thoroughly investigated. Addressing this gap, I therefore propose within SNOWflAke to (1) develop and apply modern and new techniques to generate state of the art observational snow and sea ice datasets which will be used to (2) describe the temporal evolution of seasonal processes and properties of the Antarctic snowpack across all spatial scales. The resulting improved snow parameterization will be linked to satellite remote sensing measurements in order to (3) develop a novel and more accurate Antarctic sea ice thickness data product. Finally, the improved snow process formulations will be introduced into climate models to (4) achieve an enhanced atmospheric sensitivity, and thus reduced uncertainties in sea ice forecasts for the Southern Ocean. These results will then allow us to (5) understand implications for the occurrence of characteristic Arctic snow processes, such as melt pond formation, also on Antarctic sea ice, and vice versa, in order to draw appropriate conclusions on snow as an indicator for climate warming in the polar regions. Through this highly investigative and linked working program of observations, model development, and model evaluation, SNOWflAke will significantly improve our process understanding of Antarctic sea ice within the climate system of the Southern Ocean – from today’s perspective and for future warming climate scenarios.

• DFG Programme: Independent Junior Research Groups
• International Connection: Australia, Canada, France, Switzerland, USA
• Cooperation Partners: Dr. Petra Heil; Dr. Joshua King; Dr. Glen Liston; Dr. Robert Massom; Dr. Klaus Meiners; Dr. Ghislain Picard; Dr. Martin Schneebeli