PhD Thesis Defense: Larson Kaidel

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Meeting ID: 997 3370 2623
Passcode: shelley

"Observations of Sea Ice Thermal Strain and Motion at Geophysically Relevant Scales"

Abstract

Ongoing and unprecedented Arctic sea ice change as a result of anthropogenic climate change impacts life in the Arctic and beyond. The sea ice cover is becoming less expansive, thinner, younger, and more dynamic. Quantifying processes and properties that differ between old versus young and thick versus thin ice is central understanding the sea ice cover, improving climate change predictions, and developing strategies to mitigate the adverse effects of sea ice loss. Therefore, we seek to better understand how a key inherent ice property, the thermal strain coefficient, changes as ice types change, and observe how sea ice motion and deformation are changing over time.

We conduct studies on the thermal strain of natural sea ice using in situ and remote sensing techniques, over km+ scales—a significant development from prior laboratory-based studies. We evaluate the thermal-strain relationship of first-year, multiyear, and freshwater ice. We find that thermal strain varies considerably from that expected in laboratory studies. We unify contradicting laboratory findings with these results explaining the combination of physical processes in situ, such as thermal gradients, surface fractures, and brine exchange. A potentially profound finding is that FYI (increasingly more common) behaves differently from MYI. Differing behavior between ice types and thicknesses are considered as they relate to Arctic sea ice decline, motion, and deformation.

Current sea ice motion-extracting tools are unable to test hypotheses about the effect of thermal fracture on basin wide motion, which would require high resolution and wide spatial coverage. Available algorithms produce high quality maps, however with resolutions too coarse to resolve much of the important ice deformation. The need for higher resolution sea ice motion analysis is widely recognized and there the field is developing many new algorithms for this purpose. Therefore, we aim to consolidate efforts by creating a "community challenge problem" that addresses a lack of validation and intercomparison between proposed methods. We release a standardized dataset that includes all necessary input imagery and a validation process using ground truth data from extensive drifting buoy networks. The provided documentation is intended to enable interdisciplinary contributions to the challenge problem.

Thesis Committee

• Christopher Polashenski (chair)
• Donald Perovich
• Benoit Cushman-Roisin
• Anrew Mahoney (University of Alaska Fairbanks)

Contact

For more information, contact Thayer Registrar at thayer.registrar@dartmouth.edu.