Published April 2026 | Version Published
Journal Article Open

Rates of Sea-Level Rise Are Highly Sensitive to Ice Viscosity Parameters in Model Benchmarks

  • 1. ROR icon Lawrence Berkeley National Laboratory
  • 2. ROR icon University of Michigan–Ann Arbor
  • 3. ROR icon University of Bristol
  • 4. ROR icon Colorado School of Mines
  • 5. ROR icon Massachusetts Institute of Technology
  • 6. ROR icon California Institute of Technology

Abstract

Glacier flow plays a major role in current and future rates of globally averaged sea-level rise. The viscosity of glacial ice, controlling the rate of flow, decreases as stress increases and is highly sensitive to the value of the stress exponent, n, in the constitutive equation for viscous flow. Glaciologists and climate modelers almost exclusively assume n = 3 when modeling ice flow and projecting sea-level rise through forward modeling. However, recent work suggests that n ≈ 4 better fits observations, prompting the question: How sensitive are projections of sea-level rise to the value of n? We use an established community ice flow model and standard benchmark experiments designed as an idealized representation of Pine Island Glacier, West Antarctica. While initializing an n = 3 model to match observations of an n = 4 ice sheet is possible, we find that incorrectly assuming n = 3 when in fact n = 4 dramatically underestimates rates of sea-level rise. The scale of this error grows nonlinearly with the magnitude of the climate forcing, acting to increase projection uncertainties. Additionally, we find that models often account for this stress-dependent rheology mismatch during model initialization in a way that masks this rheological effect in the short term while leaving model outputs vulnerable to larger biases in longer-term projections. Initializations to observations of Pine Island Glacier display similar rheology-mismatch fingerprints to our idealized example.

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Acknowledgement

Miigwech is the word for thanks in Ojibwe. We thank Benjamin Getraer and an anonymous reviewer for their thoughtful and constructive feedback, which have substantially improved the quality and clarity of this work. We also thank a wide range of colleagues for many fruitful discussions on this and other topics. Financial support for this study was provided through the Scientific Discovery through Advanced Computing (SciDAC) program funded by the U.S. Department of Energy (DOE), Office of Science, Biological and Environmental Research and Advanced Scientific Computing Research programs, as a part of the ProSPect SciDAC Partnership. Work at Berkeley Lab was supported by the Director, Office of Science, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory, operated under Contract No. DE-AC02-05CH11231 using NERSC award ASCR-ERCAPm1041. SBK was funded by DoE Grant C3710, Framework for Antarctic System Science in E3SM and by the DOMINOS project, a component of the International Thwaites Glacier Collaboration (ITGC). Support from National Science Foundation (NSF: Grant 1738896) and Natural Environment Research Council (NERC: Grant NE/S006605/1). Support for BMM was also provided through funding from the Grantham Foundation. MT and SLC were supported by the Natural Environment Research Council on the ISOTIPIC project (NERC Grant NE/Y503320/1). BM is a co-founder of Arête Glacier Initiative (areteglaciers.org), where he maintains an affiliation through his allowance for outside professional activities provided by Caltech (current affiliation) and MIT (past affiliation). Arête is a non-profit organization (currently a fiscally sponsored project of the 401(c) 3 Digital Harbor Foundation) founded in 2024 to provide funding for glaciological research focused on sea-level rise. No funding was provided by Arête for this work.

Data Availability

All code and relevant data and input files for this work are freely available. The numerical experiments in this work were conducted using the BISICLES open-source ice sheet model (https://bisicles.lbl.gov), which in turn is built upon the Chombo open-source software framework (https://chombo.lbl.gov) (Adams et al., 2001–2021).

Downloading Chombo and BISICLES requires free registration at https://anag-repo.lbl.gov, and then can be downloaded using svn. For Chombo (this work uses svn revision 23947): svn-username username co https://anag-repo.lbl.gov/svn/Chombo/release/3.2 Chombo

For BISICLES (this work uses svn revision 4414): svn-username username co https://anag-repo.lbl.gov/svn/BISICLES/public/trunk BISICLES.

We have placed the relevant data in a repository at the National Energy Research Scientific Computing Center (NERSC): https://portal.nersc.gov/cfs/m1041/dmartin/n4RheologyData.

In this location are tarfiles containing the input and data files used in this work, along with a set of README files with instructions on how to reproduce these results. For convenience, we also include the specific versions of Chombo and BISICLES used in this work.

Supplemental Material

Supporting Information S1

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Original Version of Manuscript

Peer Review History

Author Response to Peer Review Comments

Author Response to Peer Review Comments

First Revision of Manuscript

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Additional details

Related works

Is new version of
Discussion Paper: 10.22541/essoar.177160684.41774554/v1 (DOI)

Funding

United States Department of Energy
DE-AC02-05CH11231
National Energy Research Scientific Computing Center
ASCR‐ERCAPm1041
United States Department of Energy
C3710
National Science Foundation
1738896
Natural Environment Research Council
NE/S006605/1
Grantham Foundation
Natural Environment Research Council
NE/Y503320/1

Dates

Submitted
2025-07-02
Accepted
2026-02-13
Available
2026-03-04
Version of record online

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