Articles | Volume 20, issue 3
https://doi.org/10.5194/tc-20-1725-2026
https://doi.org/10.5194/tc-20-1725-2026
Research article
 | 
24 Mar 2026
Research article |  | 24 Mar 2026

Outlet glacier seasonal terminus prediction using interpretable machine learning

Kevin Shionalyn, Ginny Catania, Daniel T. Trugman, Michael G. Shahin, Leigh A. Stearns, and Denis Felikson

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Latest update: 07 Nov 2026
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Short summary
The ocean-facing front of a glacier changes with the seasons. We know this cycle is controlled by the shape and speed of the glacier as well as by the climate, but we do not have a full understanding of these processes. Our study uses 20 years of data and a machine learning model to predict this pattern and identifies which factors matter most. We find that while several factors influence the seasonal cycle, the shape of the glacier plays a key role in how much a glacier changes annually.
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