Articles | Volume 16, issue 2
https://doi.org/10.5194/esd-16-513-2025
https://doi.org/10.5194/esd-16-513-2025
Research article
 | 
03 Apr 2025
Research article |  | 03 Apr 2025

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

John D. Jakeman, Mauro Perego, D. Thomas Seidl, Tucker A. Hartland, Trevor R. Hillebrand, Matthew J. Hoffman, and Stephen F. Price

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Cited articles

Adalgeirsdottir, G., Aschwanden, A., Khroulev, C., Boberg, F., Mottram, R., Lucas-Picher, P., and Christensen, J.: Role of model initialization for projections of 21st-century Greenland ice sheet mass loss, J. Glaciol., 60, 782–794, https://doi.org/10.3189/2014JoG13J202, 2014. a
Åkesson, H., Morlighem, M., O'Regan, M., and Jakobsson, M.: Future projections of Petermann Glacier under ocean warming depend strongly on friction law, J. Geophys. Res.-Earth, 126, e2020JF005921, https://doi.org/10.1029/2020JF005921, 2021. a
Alnæs, M., Blechta, J., Hake, J., Johansson, A., Kehlet, B., Logg, A., Richardson, C., Ring, J., Rognes, M. E., and Wells, G. N.: The FEniCS project version 1.5, Archive of Numerical Software, 3, https://doi.org/10.11588/ans.2015.100.20553, 2015. a, b
Aschwanden, A. and Brinkerhoff, D. J.: Calibrated Mass Loss Predictions for the Greenland Ice Sheet, Geophys. Res. Lett., 49, e2022GL099058, https://doi.org/10.1029/2022GL099058, 2022. a, b
Bakker, A. M. R., Wong, T. E., Ruckert, K. L., and Keller, K.: Sea-level projections representing the deeply uncertain contribution of the West Antarctic ice sheet, Scientific Reports, 7, 3880, https://doi.org/10.1038/s41598-017-04134-5, 2017. a
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This study investigated the computational benefits of using multiple models of varying cost and accuracy to quantify uncertainty in the mass change of Humboldt Glacier, Greenland, between 2007 and 2100 using a single climate change scenario. Despite some models being incapable of capturing the local features of the ice-flow fields, using multiple models reduced the error in the estimated statistics by over an order of magnitude when compared to an approach that only used a single accurate model.
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