Ice volume and thickness of all Scandinavian glaciers and ice caps

Abstract We present a new map of bed topography and ice thickness together with a corresponding ice volume estimate representative of the years ~2010 for all Scandinavian ice caps and glaciers. Starting from surface observations, we invert for ice thickness by iteratively running an innovative ice d...

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Published in:Journal of Glaciology
Main Authors: Frank, Thomas, van Pelt, Ward Jan Jacobus
Other Authors: Vetenskapsrådet, Swedish National Space Agency
Format: Article in Journal/Newspaper
Language:English
Published: Cambridge University Press (CUP) 2024
Subjects:
Online Access:http://dx.doi.org/10.1017/jog.2024.25
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S002214302400025X
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spelling crcambridgeupr:10.1017/jog.2024.25 2024-05-19T07:40:47+00:00 Ice volume and thickness of all Scandinavian glaciers and ice caps Frank, Thomas van Pelt, Ward Jan Jacobus Vetenskapsrådet Vetenskapsrådet Swedish National Space Agency 2024 http://dx.doi.org/10.1017/jog.2024.25 https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S002214302400025X en eng Cambridge University Press (CUP) http://creativecommons.org/licenses/by/4.0/ Journal of Glaciology page 1-14 ISSN 0022-1430 1727-5652 journal-article 2024 crcambridgeupr https://doi.org/10.1017/jog.2024.25 2024-05-02T06:50:44Z Abstract We present a new map of bed topography and ice thickness together with a corresponding ice volume estimate representative of the years ~2010 for all Scandinavian ice caps and glaciers. Starting from surface observations, we invert for ice thickness by iteratively running an innovative ice dynamics model on a distributed grid and updating bed topography until modelled and observed glacier dynamics as represented by their rate of surface elevation change (d h /d t ) fields align. The ice flow model used is the instructed glacier model (Jouvet and Cordonnier, 2023, Journal of Glaciology 1–15), a generic physics-informed deep-learning emulator that models higher-order ice flow with high-computational efficiency. We calibrate the modelled thicknesses against >11 000 ice thickness observations, resulting in a final ice volume estimate of 302.7 km 3 for Norway, 18.4 km 3 for Sweden and 321.1 km 3 for the whole of Scandinavia with an error estimate of ~ $\pm 11\%$ . The validation statistics computed indicate good agreement between modelled and observed thicknesses (RMSE = 55 m, Pearson's r = 0.87, bias = 0.8 m), outperforming all other ice thickness maps available for the region. The modelled bed shapes thus provide unprecedented detail in the subglacial topography, especially for ice caps where we produce the first maps that show ice-dynamically realistic flow features. Article in Journal/Newspaper glacier Journal of Glaciology Cambridge University Press Journal of Glaciology 1 14
institution Open Polar
collection Cambridge University Press
op_collection_id crcambridgeupr
language English
description Abstract We present a new map of bed topography and ice thickness together with a corresponding ice volume estimate representative of the years ~2010 for all Scandinavian ice caps and glaciers. Starting from surface observations, we invert for ice thickness by iteratively running an innovative ice dynamics model on a distributed grid and updating bed topography until modelled and observed glacier dynamics as represented by their rate of surface elevation change (d h /d t ) fields align. The ice flow model used is the instructed glacier model (Jouvet and Cordonnier, 2023, Journal of Glaciology 1–15), a generic physics-informed deep-learning emulator that models higher-order ice flow with high-computational efficiency. We calibrate the modelled thicknesses against >11 000 ice thickness observations, resulting in a final ice volume estimate of 302.7 km 3 for Norway, 18.4 km 3 for Sweden and 321.1 km 3 for the whole of Scandinavia with an error estimate of ~ $\pm 11\%$ . The validation statistics computed indicate good agreement between modelled and observed thicknesses (RMSE = 55 m, Pearson's r = 0.87, bias = 0.8 m), outperforming all other ice thickness maps available for the region. The modelled bed shapes thus provide unprecedented detail in the subglacial topography, especially for ice caps where we produce the first maps that show ice-dynamically realistic flow features.
author2 Vetenskapsrådet
Vetenskapsrådet
Swedish National Space Agency
format Article in Journal/Newspaper
author Frank, Thomas
van Pelt, Ward Jan Jacobus
spellingShingle Frank, Thomas
van Pelt, Ward Jan Jacobus
Ice volume and thickness of all Scandinavian glaciers and ice caps
author_facet Frank, Thomas
van Pelt, Ward Jan Jacobus
author_sort Frank, Thomas
title Ice volume and thickness of all Scandinavian glaciers and ice caps
title_short Ice volume and thickness of all Scandinavian glaciers and ice caps
title_full Ice volume and thickness of all Scandinavian glaciers and ice caps
title_fullStr Ice volume and thickness of all Scandinavian glaciers and ice caps
title_full_unstemmed Ice volume and thickness of all Scandinavian glaciers and ice caps
title_sort ice volume and thickness of all scandinavian glaciers and ice caps
publisher Cambridge University Press (CUP)
publishDate 2024
url http://dx.doi.org/10.1017/jog.2024.25
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S002214302400025X
genre glacier
Journal of Glaciology
genre_facet glacier
Journal of Glaciology
op_source Journal of Glaciology
page 1-14
ISSN 0022-1430 1727-5652
op_rights http://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.1017/jog.2024.25
container_title Journal of Glaciology
container_start_page 1
op_container_end_page 14
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