Simulation-based inference of surface accumulation and basal melt rates of an Antarctic ice shelf from isochronal layers
The ice shelves buttressing the Antarctic ice sheet determine the rate of ice-discharge into the surrounding oceans. Their geometry and buttressing strength are influenced by the local surface accumulation and basal melt rates, governed by atmospheric and oceanic conditions. Contemporary methods qua...
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Cambridge University Press
2025-01-01
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| Series: | Journal of Glaciology |
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| Online Access: | https://www.cambridge.org/core/product/identifier/S0022143025000139/type/journal_article |
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| author | Guy Moss Vjeran Višnjević Olaf Eisen Falk M. Oraschewski Cornelius Schröder Jakob H. Macke Reinhard Drews |
| author_facet | Guy Moss Vjeran Višnjević Olaf Eisen Falk M. Oraschewski Cornelius Schröder Jakob H. Macke Reinhard Drews |
| author_sort | Guy Moss |
| collection | DOAJ |
| description | The ice shelves buttressing the Antarctic ice sheet determine the rate of ice-discharge into the surrounding oceans. Their geometry and buttressing strength are influenced by the local surface accumulation and basal melt rates, governed by atmospheric and oceanic conditions. Contemporary methods quantify one of these rates, but typically not both. Moreover, information about these rates is only available for recent time periods, reaching at most a few decades back since measurements are available. We present a new method to simultaneously infer the surface accumulation and basal melt rates averaged over decadal and centennial timescales. We infer the spatial dependence of these rates along flow line transects using internal stratigraphy observed by radars, using a kinematic forward model of internal stratigraphy. We solve the inverse problem using simulation-based inference (SBI). SBI performs Bayesian inference by training neural networks on simulations of the forward model to approximate the posterior distribution, therefore also quantifying uncertainties over the inferred parameters. We validate our method on a synthetic example, and apply it to Ekström Ice Shelf, Antarctica, for which independent validation data are available. We obtain posterior distributions of surface accumulation and basal melt averaging over up to 200 years before 2022. |
| format | Article |
| id | doaj-art-202a3cfca46546549889998ec8ef2f2f |
| institution | OA Journals |
| issn | 0022-1430 1727-5652 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Journal of Glaciology |
| spelling | doaj-art-202a3cfca46546549889998ec8ef2f2f2025-08-20T02:14:00ZengCambridge University PressJournal of Glaciology0022-14301727-56522025-01-017110.1017/jog.2025.13Simulation-based inference of surface accumulation and basal melt rates of an Antarctic ice shelf from isochronal layersGuy Moss0https://orcid.org/0000-0002-5504-0523Vjeran Višnjević1https://orcid.org/0000-0003-3613-0539Olaf Eisen2https://orcid.org/0000-0002-6380-962XFalk M. Oraschewski3https://orcid.org/0000-0001-7287-2965Cornelius Schröder4https://orcid.org/0000-0001-5643-2097Jakob H. Macke5https://orcid.org/0000-0001-5154-8912Reinhard Drews6https://orcid.org/0000-0002-2328-294XMachine Learning in Science, University of Tübingen and Tübingen AI Center, Tübingen, GermanyDepartment of Geosciences, University of Tübingen, Tübingen, GermanyAlfred-Wegener-Institut, Helmholtz-Zentrum für Polar und Meeresforschung, Bremerhaven, Germany Faculty of Geosciences, University of Bremen, Bremen, GermanyDepartment of Geosciences, University of Tübingen, Tübingen, GermanyMachine Learning in Science, University of Tübingen and Tübingen AI Center, Tübingen, GermanyMachine Learning in Science, University of Tübingen and Tübingen AI Center, Tübingen, Germany Max Planck Institute for Intelligent Systems, Tübingen, GermanyDepartment of Geosciences, University of Tübingen, Tübingen, GermanyThe ice shelves buttressing the Antarctic ice sheet determine the rate of ice-discharge into the surrounding oceans. Their geometry and buttressing strength are influenced by the local surface accumulation and basal melt rates, governed by atmospheric and oceanic conditions. Contemporary methods quantify one of these rates, but typically not both. Moreover, information about these rates is only available for recent time periods, reaching at most a few decades back since measurements are available. We present a new method to simultaneously infer the surface accumulation and basal melt rates averaged over decadal and centennial timescales. We infer the spatial dependence of these rates along flow line transects using internal stratigraphy observed by radars, using a kinematic forward model of internal stratigraphy. We solve the inverse problem using simulation-based inference (SBI). SBI performs Bayesian inference by training neural networks on simulations of the forward model to approximate the posterior distribution, therefore also quantifying uncertainties over the inferred parameters. We validate our method on a synthetic example, and apply it to Ekström Ice Shelf, Antarctica, for which independent validation data are available. We obtain posterior distributions of surface accumulation and basal melt averaging over up to 200 years before 2022.https://www.cambridge.org/core/product/identifier/S0022143025000139/type/journal_articleBayesian inferenceIce shelvesMelt - basalMass-balance reconstructionMachine learningSimulation-based inference |
| spellingShingle | Guy Moss Vjeran Višnjević Olaf Eisen Falk M. Oraschewski Cornelius Schröder Jakob H. Macke Reinhard Drews Simulation-based inference of surface accumulation and basal melt rates of an Antarctic ice shelf from isochronal layers Journal of Glaciology Bayesian inference Ice shelves Melt - basal Mass-balance reconstruction Machine learning Simulation-based inference |
| title | Simulation-based inference of surface accumulation and basal melt rates of an Antarctic ice shelf from isochronal layers |
| title_full | Simulation-based inference of surface accumulation and basal melt rates of an Antarctic ice shelf from isochronal layers |
| title_fullStr | Simulation-based inference of surface accumulation and basal melt rates of an Antarctic ice shelf from isochronal layers |
| title_full_unstemmed | Simulation-based inference of surface accumulation and basal melt rates of an Antarctic ice shelf from isochronal layers |
| title_short | Simulation-based inference of surface accumulation and basal melt rates of an Antarctic ice shelf from isochronal layers |
| title_sort | simulation based inference of surface accumulation and basal melt rates of an antarctic ice shelf from isochronal layers |
| topic | Bayesian inference Ice shelves Melt - basal Mass-balance reconstruction Machine learning Simulation-based inference |
| url | https://www.cambridge.org/core/product/identifier/S0022143025000139/type/journal_article |
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