MOSAiC: Floe-scale observation and quantification of Arctic sea ice breakup and floe size during the autumn-to-summer transition (MOSAiCFSD)

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This project investigates multi-scale sea ice processes in the so-called marginal ice zone (MIZ), a region in the Arctic Ocean typically consisting of small, discrete ice floes in summer. This MIZ is very dynamic, easily affected by waves and wind, which enhances the heat and momentum exchanges between ocean and atmosphere. This dynamic MIZ has been grown during past decades, and is projected to grow to an even greater extent (almost all sea ice cover becoming the MIZ by 2080). The very inherent process within this expanding MIZ is sea ice freeze-up, deformation, spring breakup and summer melt. In autumn, open water and ice floes survived the summer melt consolidate to form a continuous sheet of winter ice that contains a mixture of multiyear ice (from last summer), first-year (grown from autumn) and newly formed ice (grown later season). This winter ice is then deformed and fractured to form leads/cracks or ridges. In spring, this winter ice breaks apart into small discrete floes, which will be further broken apart or melt in summer. We hypothesize that this seasonal evolution of ice floes is linked and should be understood to improve sea ice-ocean/climate model prediction. In this project, we aim to generate new observational data and understanding of this seasonal evolution of ice floes, at the year-long MOSAiC drifting station. For this, we will conduct small-scale (below 2 km) observation of sea ice freeze-up, deformation, spring breakup and summer melt using a combination of high-precisions GNSS buoys, drifters and airborne/satellite observations. This small-scale observational data will be combined with large-scale observation of deformation (above 2 km), ice types/features and floe size, forming a unique multi-scale data set, which will provide a comprehensive picture of the seasonal of ice floes. We will also explore the possibility to incorporate the generated data set into specific models to measure and demonstrate the impact of our process study. The data set and knowledge gained from this project will enable modelling communities to develop, calibrate and validate their new/existing model parameterisations of sea ice-ocean and climate models, thus improving climate projection in the Arctic and providing improved advice to national and international governing bodies for climate change issues.