Reconstructing the Antarctic ice-sheet shape at the Last Glacial Maximum using ice-core data

Turner, Fiona E.; Buck, Caitlin E.; Jones, Julie M.; Sime, Louise C. ORCID: https://orcid.org/0000-0002-9093-7926; Vallet, Irene M.; Wilkinson, Richard D.. 2023 Reconstructing the Antarctic ice-sheet shape at the Last Glacial Maximum using ice-core data. Journal of the Royal Statistical Society: Series C, 72 (5), qlad078. 1493-1511. https://doi.org/10.1093/jrsssc/qlad078

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Abstract/Summary

The Antarctic ice sheet (AIS) is the Earth’s largest store of frozen water; understanding how it changed in the past allows us to improve projections of how it, and sea levels, may change. Here, we use previous AIS reconstructions, water isotope ratios from ice cores, and simulator predictions of the relationship between the ice-sheet shape and isotope ratios to create a model of the AIS at the Last Glacial Maximum. We develop a prior distribution that captures expert opinion about the AIS, generate a designed ensemble of potential shapes, run these through the climate model HadCM3, and train a Gaussian process emulator of the link between ice-sheet shape and isotope ratios. To make the analysis computationally tractable, we develop a preferential principal component method that allows us to reduce the dimension of the problem in a way that accounts for the differing importance we place in reconstructions, allowing us to create a basis that reflects prior uncertainty. We use Markov chain Monte Carlo to sample from the posterior distribution, finding shapes for which HadCM3 predicts isotope ratios closely matching observations from ice cores. The posterior distribution allows us to quantify the uncertainty in the reconstructed shape, a feature missing in other analyses.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1093/jrsssc/qlad078
ISSN:	0035-9254
Additional Keywords:	Antarctic ice sheet, Bayesian calibration, Gaussian process emulation, palaeo-climatology
Date made live:	21 Sep 2023 08:35 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/533229

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