The Cryosphere
The Cryosphere
TC
Articles | Volume 20, issue 6
Articles | Volume 20, issue 6
https://doi.org/10.5194/tc-20-3533-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-20-3533-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 20, issue 6
Research article
 | 
19 Jun 2026
Research article |  | 19 Jun 2026

Inferring subglacial topography using physics informed machine learning constrained by two conservation laws

Mansa Krishna, Gong Cheng, and Mathieu Morlighem

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Short summary
Estimates of the Greenland Ice Sheet’s contribution to sea level rise are affected by uncertainties in the bed topography. Traditional, physics-based methods for inferring the bed elevation are limited to fast-flowing areas of the ice sheet. We use machine learning models informed with two physical laws to infer the bed elevation for different regions in Greenland, showing that this method can be used to infer the bed elevation in slower-moving, sparsely surveyed regions of the ice sheet.
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