An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change

<p>This study investigated the computational benefits of using multi-fidelity statistical estimation (MFSE) algorithms to quantify uncertainty in the mass change of Humboldt Glacier, Greenland, between 2007 and 2100 using a single climate change scenario. The goal of this study was to determin...

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Main Authors: J. D. Jakeman, M. Perego, D. T. Seidl, T. A. Hartland, T. R. Hillebrand, M. J. Hoffman, S. F. Price
Format: Article
Language:English
Published: Copernicus Publications 2025-04-01
Series:Earth System Dynamics
Online Access:https://esd.copernicus.org/articles/16/513/2025/esd-16-513-2025.pdf
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author J. D. Jakeman
M. Perego
D. T. Seidl
T. A. Hartland
T. R. Hillebrand
M. J. Hoffman
S. F. Price
author_facet J. D. Jakeman
M. Perego
D. T. Seidl
T. A. Hartland
T. R. Hillebrand
M. J. Hoffman
S. F. Price
author_sort J. D. Jakeman
collection DOAJ
description <p>This study investigated the computational benefits of using multi-fidelity statistical estimation (MFSE) algorithms to quantify uncertainty in the mass change of Humboldt Glacier, Greenland, between 2007 and 2100 using a single climate change scenario. The goal of this study was to determine whether MFSE can use multiple models of varying cost and accuracy to reduce the computational cost of estimating the mean and variance of the projected mass change of a glacier. The problem size and complexity were chosen to reflect the challenges posed by future continental-scale studies while still facilitating a computationally feasible investigation of MFSE methods. When quantifying uncertainty introduced by a high-dimensional parameterization of the basal friction field, MFSE was able to reduce the mean-squared error in the estimates of the statistics by well over an order of magnitude when compared to a single-fidelity approach that only used the highest-fidelity model. This significant reduction in computational cost was achieved despite the low-fidelity models used being incapable of capturing the local features of the ice-flow fields predicted by the high-fidelity model. The MFSE algorithms were able to effectively leverage the high correlation between each model's predictions of mass change, which all responded similarly to perturbations in the model inputs. Consequently, our results suggest that MFSE could be highly useful for reducing the cost of computing continental-scale probabilistic projections of sea-level rise due to ice-sheet mass change.</p>
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spelling doaj-art-0a70e6fe8f6d4da3a4cb2214244f32782025-08-20T03:04:29ZengCopernicus PublicationsEarth System Dynamics2190-49792190-49872025-04-011651354410.5194/esd-16-513-2025An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass changeJ. D. Jakeman0M. Perego1D. T. Seidl2T. A. Hartland3T. R. Hillebrand4M. J. Hoffman5S. F. Price6Optimization and Uncertainty Quantification, Sandia National Laboratories, Albuquerque, NM 87123, USAScientific Machine Learning, Sandia National Laboratories, Albuquerque, NM 87123, USAScientific Machine Learning, Sandia National Laboratories, Albuquerque, NM 87123, USACenter for Applied Scientific Computing, Lawrence Livermore National Laboratory, Livermore, CA 94550, USAFluid Dynamics and Solid Mechanics Group, Los Alamos National Laboratory, Los Alamos, NM 87544, USAFluid Dynamics and Solid Mechanics Group, Los Alamos National Laboratory, Los Alamos, NM 87544, USAFluid Dynamics and Solid Mechanics Group, Los Alamos National Laboratory, Los Alamos, NM 87544, USA<p>This study investigated the computational benefits of using multi-fidelity statistical estimation (MFSE) algorithms to quantify uncertainty in the mass change of Humboldt Glacier, Greenland, between 2007 and 2100 using a single climate change scenario. The goal of this study was to determine whether MFSE can use multiple models of varying cost and accuracy to reduce the computational cost of estimating the mean and variance of the projected mass change of a glacier. The problem size and complexity were chosen to reflect the challenges posed by future continental-scale studies while still facilitating a computationally feasible investigation of MFSE methods. When quantifying uncertainty introduced by a high-dimensional parameterization of the basal friction field, MFSE was able to reduce the mean-squared error in the estimates of the statistics by well over an order of magnitude when compared to a single-fidelity approach that only used the highest-fidelity model. This significant reduction in computational cost was achieved despite the low-fidelity models used being incapable of capturing the local features of the ice-flow fields predicted by the high-fidelity model. The MFSE algorithms were able to effectively leverage the high correlation between each model's predictions of mass change, which all responded similarly to perturbations in the model inputs. Consequently, our results suggest that MFSE could be highly useful for reducing the cost of computing continental-scale probabilistic projections of sea-level rise due to ice-sheet mass change.</p>https://esd.copernicus.org/articles/16/513/2025/esd-16-513-2025.pdf
spellingShingle J. D. Jakeman
M. Perego
D. T. Seidl
T. A. Hartland
T. R. Hillebrand
M. J. Hoffman
S. F. Price
An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change
Earth System Dynamics
title An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change
title_full An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change
title_fullStr An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change
title_full_unstemmed An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change
title_short An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change
title_sort evaluation of multi fidelity methods for quantifying uncertainty in projections of ice sheet mass change
url https://esd.copernicus.org/articles/16/513/2025/esd-16-513-2025.pdf
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