Investigating glacier velocities and basal friction with physics-based machine learning (KLIMAFORSK)

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This proposal seeks funding to bring Dr. Jordi Bolibar to University of Oslo's Njord Centre for a research stay of 6 weeks to initiate a project investigating glacier basal friction using machine learning. The physics that dictates glacier motion are controlled by the friction between the glacier and its bed. An improved understanding of glacier motion can lead to better hazard estimates for land terminating glaciers and better sea-level rise projects for sea terminating glaciers. Understanding the strong non-linearities that control glacier motion, friction, and the motivating factors (e.g., the sub-glacier drainage system) will require statistical modeling able to capture the nonlinearities such as deep learning. This will produce new technologies for understanding glacier evolution which is inline with the Research Council of Norway’s climate and polar portfolio. This project will produce a strong, interdisciplinary collaboration between University of Oslo and Utrecht University.