Articles | Volume 16, issue 1
https://doi.org/10.5194/tc-16-179-2022
© Author(s) 2022. 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-16-179-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Jan 2022
Research article |
| 20 Jan 2022
| 20 Jan 2022
A new vertically integrated MOno-Layer Higher-Order (MOLHO) ice flow model
Thiago Dias dos Santos
CORRESPONDING AUTHOR
Escola Politécnica, University of São Paulo, São Paulo, Brazil
Department of Earth System Science, University of California, Irvine, CA, USA
Centro Polar e Climático, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
Mathieu Morlighem
Department of Earth System Science, University of California, Irvine, CA, USA
Department of Earth Sciences, Dartmouth College, Hanover, NH, USA
Douglas Brinkerhoff
Department of Computer Science, University of Montana, Missoula, MT, USA
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Cited
17 citations as recorded by crossref.
- A hybrid deep neural operator/finite element method for ice-sheet modeling Q. He et al. https://doi.org/10.1016/j.jcp.2023.112428
- A comparison between three-dimensional, transient, thermomechanically coupled first-order and Stokes ice flow models Z. Yan et al. https://doi.org/10.1017/jog.2022.77
- A Python library for solving ice sheet modeling problems using physics-informed neural networks, PINNICLE v1.0 G. Cheng et al. https://doi.org/10.5194/gmd-18-5311-2025
- Ubiquitous acceleration in Greenland Ice Sheet calving from 1985 to 2022 C. Greene et al. https://doi.org/10.1038/s41586-023-06863-2
- Multifidelity uncertainty quantification for ice sheet simulations N. Aretz et al. https://doi.org/10.1007/s10596-024-10329-3
- Multifidelity deep operator networks for data-driven and physics-informed problems A. Howard et al. https://doi.org/10.1016/j.jcp.2023.112462
- Evolution of the Antarctic Ice Sheet from 2000–2300 and beyond: model sensitivity and uncertainty analysis using MPAS-Albany Land Ice T. Hillebrand et al. https://doi.org/10.5194/tc-20-4061-2026
- Inferring subglacial topography using physics informed machine learning constrained by two conservation laws M. Krishna et al. https://doi.org/10.5194/tc-20-3533-2026
- An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change J. Jakeman et al. https://doi.org/10.5194/esd-16-513-2025
- Ice sheet model simulations reveal that polythermal ice conditions existed across the northeastern USA during the Last Glacial Maximum J. Cuzzone et al. https://doi.org/10.5194/tc-19-1559-2025
- Optimally Balancing Exploration and Exploitation to Automate Multifidelity Statistical Estimation T. Dixon et al. https://doi.org/10.1137/25M1761744
- New perspectives on ice forcing in continental arc magma plumbing systems B. Singer et al. https://doi.org/10.1016/j.jvolgeores.2024.108187
- Modeling the timing of Patagonian Ice Sheet retreat in the Chilean Lake District from 22–10 ka J. Cuzzone et al. https://doi.org/10.5194/tc-18-1381-2024
- Precipitation drives western Patagonian glacier variability and may curb future ice mass loss M. Troch et al. https://doi.org/10.1038/s41598-024-77486-4
- The demise of the world's largest piedmont glacier: a probabilistic forecast D. Brinkerhoff et al. https://doi.org/10.5194/tc-19-2321-2025
- Seasonal variability in ice velocity driven by subglacial hydrology of Drang Drung Glacier, Western Himalayas V. Thota et al. https://doi.org/10.1017/jog.2026.10150
- The Stochastic Ice-Sheet and Sea-Level System Model v1.0 (StISSM v1.0) V. Verjans et al. https://doi.org/10.5194/gmd-15-8269-2022
17 citations as recorded by crossref.
- A hybrid deep neural operator/finite element method for ice-sheet modeling Q. He et al. https://doi.org/10.1016/j.jcp.2023.112428
- A comparison between three-dimensional, transient, thermomechanically coupled first-order and Stokes ice flow models Z. Yan et al. https://doi.org/10.1017/jog.2022.77
- A Python library for solving ice sheet modeling problems using physics-informed neural networks, PINNICLE v1.0 G. Cheng et al. https://doi.org/10.5194/gmd-18-5311-2025
- Ubiquitous acceleration in Greenland Ice Sheet calving from 1985 to 2022 C. Greene et al. https://doi.org/10.1038/s41586-023-06863-2
- Multifidelity uncertainty quantification for ice sheet simulations N. Aretz et al. https://doi.org/10.1007/s10596-024-10329-3
- Multifidelity deep operator networks for data-driven and physics-informed problems A. Howard et al. https://doi.org/10.1016/j.jcp.2023.112462
- Evolution of the Antarctic Ice Sheet from 2000–2300 and beyond: model sensitivity and uncertainty analysis using MPAS-Albany Land Ice T. Hillebrand et al. https://doi.org/10.5194/tc-20-4061-2026
- Inferring subglacial topography using physics informed machine learning constrained by two conservation laws M. Krishna et al. https://doi.org/10.5194/tc-20-3533-2026
- An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change J. Jakeman et al. https://doi.org/10.5194/esd-16-513-2025
- Ice sheet model simulations reveal that polythermal ice conditions existed across the northeastern USA during the Last Glacial Maximum J. Cuzzone et al. https://doi.org/10.5194/tc-19-1559-2025
- Optimally Balancing Exploration and Exploitation to Automate Multifidelity Statistical Estimation T. Dixon et al. https://doi.org/10.1137/25M1761744
- New perspectives on ice forcing in continental arc magma plumbing systems B. Singer et al. https://doi.org/10.1016/j.jvolgeores.2024.108187
- Modeling the timing of Patagonian Ice Sheet retreat in the Chilean Lake District from 22–10 ka J. Cuzzone et al. https://doi.org/10.5194/tc-18-1381-2024
- Precipitation drives western Patagonian glacier variability and may curb future ice mass loss M. Troch et al. https://doi.org/10.1038/s41598-024-77486-4
- The demise of the world's largest piedmont glacier: a probabilistic forecast D. Brinkerhoff et al. https://doi.org/10.5194/tc-19-2321-2025
- Seasonal variability in ice velocity driven by subglacial hydrology of Drang Drung Glacier, Western Himalayas V. Thota et al. https://doi.org/10.1017/jog.2026.10150
- The Stochastic Ice-Sheet and Sea-Level System Model v1.0 (StISSM v1.0) V. Verjans et al. https://doi.org/10.5194/gmd-15-8269-2022
Saved (final revised paper)
Latest update: 05 Sep 2026
Short summary
Projecting the future evolution of Greenland and Antarctica and their potential contribution to sea level rise often relies on computer simulations carried out by numerical ice sheet models. Here we present a new vertically integrated ice sheet model and assess its performance using different benchmarks. The new model shows results comparable to a three-dimensional model at relatively lower computational cost, suggesting that it is an excellent alternative for long-term simulations.
Projecting the future evolution of Greenland and Antarctica and their potential contribution to...
