Articles | Volume 16, issue 9
https://doi.org/10.5194/tc-16-3867-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-3867-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Sep 2022
Research article |
| 29 Sep 2022
| 29 Sep 2022
Inverting ice surface elevation and velocity for bed topography and slipperiness beneath Thwaites Glacier
School of GeoSciences, University of Edinburgh, Drummond St., Edinburgh, EH8 9XP, UK
Robert G. Bingham
School of GeoSciences, University of Edinburgh, Drummond St., Edinburgh, EH8 9XP, UK
Andrew Curtis
School of GeoSciences, University of Edinburgh, Drummond St., Edinburgh, EH8 9XP, UK
Daniel Goldberg
School of GeoSciences, University of Edinburgh, Drummond St., Edinburgh, EH8 9XP, UK
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This preprint is open for discussion and under review for The Cryosphere (TC).
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Patrick Schmitt, Fabien Maussion, Daniel N. Goldberg, and Philipp Gregor
Geosci. Model Dev., 19, 1301–1319, https://doi.org/10.5194/gmd-19-1301-2026, https://doi.org/10.5194/gmd-19-1301-2026, 2026
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Jowan M. Barnes, G. Hilmar Gudmundsson, Daniel N. Goldberg, and Sainan Sun
The Cryosphere, 20, 777–790, https://doi.org/10.5194/tc-20-777-2026, https://doi.org/10.5194/tc-20-777-2026, 2026
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Hamish D. Pritchard, Edward C. King, David J. Goodger, Douglas Boyle, Daniel N. Goldberg, Beatriz Recinos, Andrew Orr, and Dhananjay Regmi
Earth Syst. Sci. Data, 18, 199–217, https://doi.org/10.5194/essd-18-199-2026, https://doi.org/10.5194/essd-18-199-2026, 2026
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EGUsphere, https://doi.org/10.5194/egusphere-2025-4670, https://doi.org/10.5194/egusphere-2025-4670, 2025
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Robert G. Bingham, Julien A. Bodart, Marie G. P. Cavitte, Ailsa Chung, Rebecca J. Sanderson, Johannes C. R. Sutter, Olaf Eisen, Nanna B. Karlsson, Joseph A. MacGregor, Neil Ross, Duncan A. Young, David W. Ashmore, Andreas Born, Winnie Chu, Xiangbin Cui, Reinhard Drews, Steven Franke, Vikram Goel, John W. Goodge, A. Clara J. Henry, Antoine Hermant, Benjamin H. Hills, Nicholas Holschuh, Michelle R. Koutnik, Gwendolyn J.-M. C. Leysinger Vieli, Emma J. MacKie, Elisa Mantelli, Carlos Martín, Felix S. L. Ng, Falk M. Oraschewski, Felipe Napoleoni, Frédéric Parrenin, Sergey V. Popov, Therese Rieckh, Rebecca Schlegel, Dustin M. Schroeder, Martin J. Siegert, Xueyuan Tang, Thomas O. Teisberg, Kate Winter, Shuai Yan, Harry Davis, Christine F. Dow, Tyler J. Fudge, Tom A. Jordan, Bernd Kulessa, Kenichi Matsuoka, Clara J. Nyqvist, Maryam Rahnemoonfar, Matthew R. Siegfried, Shivangini Singh, Vjeran Višnjević, Rodrigo Zamora, and Alexandra Zuhr
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Laure Moinat, Florian Franziskakis, Christian Vérard, Daniel N. Goldberg, and Maura Brunetti
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Rebecca J. Sanderson, Kate Winter, S. Louise Callard, Felipe Napoleoni, Neil Ross, Tom A. Jordan, and Robert G. Bingham
The Cryosphere, 17, 4853–4871, https://doi.org/10.5194/tc-17-4853-2023, https://doi.org/10.5194/tc-17-4853-2023, 2023
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Ice-penetrating radar allows us to explore the internal structure of glaciers and ice sheets to constrain past and present ice-flow conditions. In this paper, we examine englacial layers within the Lambert Glacier in East Antarctica using a quantitative layer tracing tool. Analysis reveals that the ice flow here has been relatively stable, but evidence for former fast flow along a tributary suggests that changes have occurred in the past and could change again in the future.
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Ice sheet models generate forecasts of ice sheet mass loss, a significant contributor to sea level rise; thus, capturing the complete range of possible projections of mass loss is of critical societal importance. Here we add to data assimilation techniques commonly used in ice sheet modelling (a Bayesian inference approach) and fully characterize calibration uncertainty. We successfully propagate this type of error onto sea level rise projections of three ice streams in West Antarctica.
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Earth Syst. Sci. Data, 15, 2695–2710, https://doi.org/10.5194/essd-15-2695-2023, https://doi.org/10.5194/essd-15-2695-2023, 2023
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This paper presents the release of over 60 years of ice thickness, bed elevation, and surface elevation data acquired over Antarctica by the international community. These data are a crucial component of the Antarctic Bedmap initiative which aims to produce a new map and datasets of Antarctic ice thickness and bed topography for the international glaciology and geophysical community.
Julien A. Bodart, Robert G. Bingham, Duncan A. Young, Joseph A. MacGregor, David W. Ashmore, Enrica Quartini, Andrew S. Hein, David G. Vaughan, and Donald D. Blankenship
The Cryosphere, 17, 1497–1512, https://doi.org/10.5194/tc-17-1497-2023, https://doi.org/10.5194/tc-17-1497-2023, 2023
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Estimating how West Antarctica will change in response to future climatic change depends on our understanding of past ice processes. Here, we use a reflector widely visible on airborne radar data across West Antarctica to estimate accumulation rates over the past 4700 years. By comparing our estimates with current atmospheric data, we find that accumulation rates were 18 % greater than modern rates. This has implications for our understanding of past ice processes in the region.
Tancrède P. M. Leger, Andrew S. Hein, Ángel Rodés, Robert G. Bingham, Irene Schimmelpfennig, Derek Fabel, Pablo Tapia, and ASTER Team
Clim. Past, 19, 35–59, https://doi.org/10.5194/cp-19-35-2023, https://doi.org/10.5194/cp-19-35-2023, 2023
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Over the past 800 thousand years, variations in the Earth’s orbit and tilt have caused antiphased solar insolation intensity in the Northern and Southern Hemispheres. Paradoxically, glacial records suggest that global ice sheets have responded synchronously to major cold glacial and warm interglacial episodes. To address this puzzle, we present a new detailed glacier chronology that estimates the timing of multiple Patagonian ice-sheet waxing and waning cycles over the past 300 thousand years.
Alice C. Frémand, Julien A. Bodart, Tom A. Jordan, Fausto Ferraccioli, Carl Robinson, Hugh F. J. Corr, Helen J. Peat, Robert G. Bingham, and David G. Vaughan
Earth Syst. Sci. Data, 14, 3379–3410, https://doi.org/10.5194/essd-14-3379-2022, https://doi.org/10.5194/essd-14-3379-2022, 2022
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This paper presents the release of large swaths of airborne geophysical data (including gravity, magnetics, and radar) acquired between 1994 and 2020 over Antarctica by the British Antarctic Survey. These include a total of 64 datasets from 24 different surveys, amounting to >30 % of coverage over the Antarctic Ice Sheet. This paper discusses how these data were acquired and processed and presents the methods used to standardize and publish the data in an interactive and reproducible manner.
Alexander Robinson, Daniel Goldberg, and William H. Lipscomb
The Cryosphere, 16, 689–709, https://doi.org/10.5194/tc-16-689-2022, https://doi.org/10.5194/tc-16-689-2022, 2022
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Here we investigate the numerical stability of several commonly used methods in order to determine which of them are capable of resolving the complex physics of the ice flow and are also computationally efficient. We find that the so-called DIVA solver outperforms the others. Its representation of the physics is consistent with more complex methods, while it remains computationally efficient at high resolution.
Conrad P. Koziol, Joe A. Todd, Daniel N. Goldberg, and James R. Maddison
Geosci. Model Dev., 14, 5843–5861, https://doi.org/10.5194/gmd-14-5843-2021, https://doi.org/10.5194/gmd-14-5843-2021, 2021
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Sea level change due to the loss of ice sheets presents great risk for coastal communities. Models are used to forecast ice loss, but their evolution depends strongly on properties which are hidden from observation and must be inferred from satellite observations. Common methods for doing so do not allow for quantification of the uncertainty inherent or how it will affect forecasts. We provide a framework for quantifying how this
initialization uncertaintyaffects ice loss forecasts.
Jowan M. Barnes, Thiago Dias dos Santos, Daniel Goldberg, G. Hilmar Gudmundsson, Mathieu Morlighem, and Jan De Rydt
The Cryosphere, 15, 1975–2000, https://doi.org/10.5194/tc-15-1975-2021, https://doi.org/10.5194/tc-15-1975-2021, 2021
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Some properties of ice flow models must be initialised using observed data before they can be used to produce reliable predictions of the future. Different models have different ways of doing this, and the process is generally seen as being specific to an individual model. We compare the methods used by three different models and show that they produce similar outputs. We also demonstrate that the outputs from one model can be used in other models without introducing large uncertainties.
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Short summary
Hills and valleys hidden under the ice of Thwaites Glacier have an impact on ice flow and future ice loss, but there are not many three-dimensional observations of their location or size. We apply a mathematical theory to new high-resolution observations of the ice surface to predict the bed topography beneath the ice. There is a good correlation with ice-penetrating radar observations. The method may be useful in areas with few direct observations or as a further constraint for other methods.
Hills and valleys hidden under the ice of Thwaites Glacier have an impact on ice flow and future...
