Articles | Volume 20, issue 9
https://doi.org/10.5194/tc-20-5041-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-20-5041-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Enabling ice sheet models to capture centennial-scale solid Earth feedback with relative ease and sufficient accuracy
Surendra Adhikari
CORRESPONDING AUTHOR
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91011, USA
Lambert Caron
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91011, USA
Erik R. Ivins
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91011, USA
Holly K. Han
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91011, USA
Luc Houriez
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91011, USA
Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA
Eric Larour
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91011, USA
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Understanding sliding at the bed of glaciers is essential to understand the future of sea-level rise and glacier-related hazards. Yet there is currently no universal law to describe this mechanism. We propose a universal glacier sliding law and a method to qualitatively constrain it. We use satellite remote sensing to create velocity maps over 6 years at Shisper Glacier, Pakistan, including its recent surge, and show that the observations corroborate the generalized theory.
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In the described study, we derive an uncertainty range for global mean sea level rise (SLR) contribution from Thwaites Glacier in a 200-year period under an extreme ocean warming scenario. We derive the spatial and vertical resolutions needed for bedrock data acquisition missions in order to limit global mean SLR contribution from Thwaites Glacier to ±2 cm in a 200-year period. We conduct sensitivity experiments in order to present the locations of critical regions in need of accurate mapping.
Kevin Bulthuis and Eric Larour
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We present and implement a stochastic solver to sample spatially and temporal varying uncertain input parameters in the Ice-sheet and Sea-level System Model, such as ice thickness or surface mass balance. We represent these sources of uncertainty using Gaussian random fields with Matérn covariance function. We generate random samples of this random field using an efficient computational approach based on solving a stochastic partial differential equation.
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Short summary
We present an efficient approach for coupling ice sheet and solid Earth models, bringing realistic gravitational and deformational processes into mainstream ice sheet modeling. Earth responses are encoded in precomputed Green’s functions and applied to modeled ice mass change through matrix multiplication. By removing a major computational and technical barrier, the approach could accelerate adoption within the Ice Sheet Model Intercomparison Project (ISMIP) to improve sea level projections.
We present an efficient approach for coupling ice sheet and solid Earth models, bringing...