Ice-flow perturbation analysis: a method to estimate ice-sheet bed topography and conditions from surface datasets

Abstract One of the largest contributors to uncertainty in predictions of sea-level rise from ice-sheet models is a lack of knowledge about the bed topography beneath ice sheets. Bed topography maps are normally made by interpolating between linear radar surveys using methods that include kriging, m...

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Bibliographic Details
Published in:Journal of Glaciology
Main Authors: Ockenden, Helen, Bingham, Robert G, Curtis, Andrew, Goldberg, Daniel
Other Authors: Natural Environment Research Council, National Science Foundation
Format: Article in Journal/Newspaper
Language:English
Published: Cambridge University Press (CUP) 2023
Subjects:
Online Access:http://dx.doi.org/10.1017/jog.2023.50
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143023000503
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Summary:Abstract One of the largest contributors to uncertainty in predictions of sea-level rise from ice-sheet models is a lack of knowledge about the bed topography beneath ice sheets. Bed topography maps are normally made by interpolating between linear radar surveys using methods that include kriging, mass conservation and flowline diffusion, all of which may miss influential mesoscale (2–30 km) bedforms. Previous works have explored an Ice-Flow Perturbation Analysis (IFPA) approach for estimating bed topography using the surface expression of these mesoscale bedforms. Using regions of Pine Island Glacier that have been intensively surveyed by ice-penetrating radar as test sites, and a refined IFPA methodology, we find that IFPA detects bedforms capable of influencing ice flow which are not represented in Bedmachine Antarctica and other interpolated bed products. We further explore the ability of IFPA to estimate relative bed slipperiness, finding higher slipperiness in the main trunk and tributaries. Alongside other methods which estimate ice thickness, bed topography maps from IFPA have the potential to constrain projections of future sea-level rise, especially where radar data are sparse.