Sea ice deformation and sea ice thickness change

Abstract

The Arctic Ocean is undergoing a major transition from a year-round sea ice cover to ice-free summers with global consequences. Sea ice thickness is at the center of the ongoing changes because the thickness regulates key processes of the Arctic climate system and in the last six decades, the mean thickness has more than halved. With the most scientific attention on the increased melting and delayed freezing of Arctic sea ice, dynamic thickness change caused by sea ice deformation has remained less studied. Dynamic thickness change alters the sea ice thickness through colliding floes that raft or form pressure ridges or floes breaking apart resulting in leads. Because sea ice grows faster in open water and under thin ice, new ice formation is enhanced in those leads compared to the surrounding ice during the growth season. Because thinner ice is easier to break and move, the ongoing thinning of Arctic sea ice may result in more ridges and leads, which, in turn, could increase ice thickness in winter. However, our limited quantitative understanding of dynamic thickness change has hampered any robust prediction if and to which extent such increased dynamic thickening in winter could mitigate summer thinning in the warming Arctic. To address this gap, we need more robust estimates of the current magnitude as well as a better understanding and representation of the different processes in state-of-the-art sea ice models. Thus, the overarching goal of this thesis is to resolve and quantify dynamic thickness change and to link it to the corresponding sea ice deformation. I focus on the freezing period addressing the following research questions: (1) How large is the dynamic contribution to the mean sea ice thickness in different dynamic regimes? (2) How is deformation shaping the ice thickness distribution? (3) How can high-resolution microwave synthetic aperture radar (SAR) satellite data be used to estimate dynamic thickness change? I answer them in two regional case studies: a unique month-long deformation event during the closing of a polynya north of Greenland and in the Transpolar Drift along the drift track of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. The combination of available high-resolution electromagnetic (EM) induction sounding ice thickness data and high-resolution deformation data offer unique research opportunities to study the highly localized and intermittent dynamic thickness changes. My results show that dynamic thickness change plays an important role in both convergent and divergent drift regimes. Studying the polynya closing event reveals that convergence can locally double the thickness of young, thin (<1 m) ice and restore the mean thickness of 2 m of the surrounding multi-year ice within one month. In more divergent regimes like the Transpolar Drift, new ice formation in leads contributes 30% to the sea ice mass balance. There are indicators that this fraction may increase in a more seasonal Arctic sea ice cover. Besides the mean changes, I show how deformation shapes the ice thickness distribution (ITD) with a particular focus on the transfer of observational results into modeling concepts. I identify the ice that participates in ridging, show that the current ridging parameterization in state-of-the-art models is not able to reproduce the observed changes in the shape of the ITD, and suggest an updated parameterization that relates the shape of the ITD proportionally to the observed deformation. Lastly, I demonstrate that SAR-derived deformation can successfully be used to describe sea ice dynamics and to estimate the dynamic contribution to the ice thickness on regional scales. In conclusion, this dissertation substantially advances our understanding of dynamic thickness change with robust and quantitative estimates. The high-resolution EM ice thickness data with simultaneously collected high-resolution deformation data provide an excellent opportunity to deepen our process understanding and to evaluate and improve the modeling of the dynamic processes shaping the ITD. With the increasing availability of SAR data in the Arctic and the presented deformation datasets and methods, new opportunities are opening up to derive dynamic thickness change on Arctic-wide scales and to study the temporal trends in dynamic thickness change over the last decade.