Articles | Volume 14, issue 11
https://doi.org/10.5194/tc-14-3687-2020
© Author(s) 2020. 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-14-3687-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
DeepBedMap: a deep neural network for resolving the bed topography of Antarctica
Antarctic Research Centre, Victoria University of Wellington, Wellington, New Zealand
Antarctic Research Centre, Victoria University of Wellington, Wellington, New Zealand
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Francesca Baldacchino, Nicholas R. Golledge, Huw Horgan, Mathieu Morlighem, Alanna V. Alevropoulos-Borrill, Alena Malyarenko, Alexandra Gossart, Daniel P. Lowry, and Laurine van Haastrecht
EGUsphere, https://doi.org/10.5194/egusphere-2023-2793, https://doi.org/10.5194/egusphere-2023-2793, 2023
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Understanding how the Ross Ice Shelf flow is changing in a warming world is important for monitoring mass changes. The flow displays an intra-annual variation; however, it is unclear what mechanisms drive this variability. Sensitivity maps are modelled showing areas of the ice shelf where changes in basal melt most influence the ice flow. We suggest that basal melting partly drives the flow variability along the calving front of the ice shelf and will continue to do so in a warming world.
Francesca Baldacchino, Mathieu Morlighem, Nicholas R. Golledge, Huw Horgan, and Alena Malyarenko
The Cryosphere, 16, 3723–3738, https://doi.org/10.5194/tc-16-3723-2022, https://doi.org/10.5194/tc-16-3723-2022, 2022
Short summary
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Understanding how the Ross Ice Shelf will evolve in a warming world is important to the future stability of Antarctica. It remains unclear what changes could drive the largest mass loss in the future and where places are most likely to trigger larger mass losses. Sensitivity maps are modelled showing that the RIS is sensitive to changes in environmental and glaciological controls at regions which are currently experiencing changes. These regions need to be monitored in a warming world.
Molly O. Patterson, Richard H. Levy, Denise K. Kulhanek, Tina van de Flierdt, Huw Horgan, Gavin B. Dunbar, Timothy R. Naish, Jeanine Ash, Alex Pyne, Darcy Mandeno, Paul Winberry, David M. Harwood, Fabio Florindo, Francisco J. Jimenez-Espejo, Andreas Läufer, Kyu-Cheul Yoo, Osamu Seki, Paolo Stocchi, Johann P. Klages, Jae Il Lee, Florence Colleoni, Yusuke Suganuma, Edward Gasson, Christian Ohneiser, José-Abel Flores, David Try, Rachel Kirkman, Daleen Koch, and the SWAIS 2C Science Team
Sci. Dril., 30, 101–112, https://doi.org/10.5194/sd-30-101-2022, https://doi.org/10.5194/sd-30-101-2022, 2022
Short summary
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How much of the West Antarctic Ice Sheet will melt and how quickly it will happen when average global temperatures exceed 2 °C is currently unknown. Given the far-reaching and international consequences of Antarctica’s future contribution to global sea level rise, the SWAIS 2C Project was developed in order to better forecast the size and timing of future changes.
Huw J. Horgan, Laurine van Haastrecht, Richard B. Alley, Sridhar Anandakrishnan, Lucas H. Beem, Knut Christianson, Atsuhiro Muto, and Matthew R. Siegfried
The Cryosphere, 15, 1863–1880, https://doi.org/10.5194/tc-15-1863-2021, https://doi.org/10.5194/tc-15-1863-2021, 2021
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The grounding zone marks the transition from a grounded ice sheet to a floating ice shelf. Like Earth's coastlines, the grounding zone is home to interactions between the ocean, fresh water, and geology but also has added complexity and importance due to the overriding ice. Here we use seismic surveying – sending sound waves down through the ice – to image the grounding zone of Whillans Ice Stream in West Antarctica and learn more about the nature of this important transition zone.
Related subject area
Discipline: Ice sheets | Subject: Data Assimilation
Impact of time-dependent data assimilation on ice flow model initialization and projections: a case study of Kjer Glacier, Greenland
A framework for time-dependent ice sheet uncertainty quantification, applied to three West Antarctic ice streams
Assimilation of surface observations in a transient marine ice sheet model using an ensemble Kalman filter
Youngmin Choi, Helene Seroussi, Mathieu Morlighem, Nicole-Jeanne Schlegel, and Alex Gardner
The Cryosphere, 17, 5499–5517, https://doi.org/10.5194/tc-17-5499-2023, https://doi.org/10.5194/tc-17-5499-2023, 2023
Short summary
Short summary
Ice sheet models are often initialized using snapshot observations of present-day conditions, but this approach has limitations in capturing the transient evolution of the system. To more accurately represent the accelerating changes in glaciers, we employed time-dependent data assimilation. We found that models calibrated with the transient data better capture past trends and more accurately reproduce changes after the calibration period, even with limited observations.
Beatriz Recinos, Daniel Goldberg, James R. Maddison, and Joe Todd
The Cryosphere, 17, 4241–4266, https://doi.org/10.5194/tc-17-4241-2023, https://doi.org/10.5194/tc-17-4241-2023, 2023
Short summary
Short summary
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.
Fabien Gillet-Chaulet
The Cryosphere, 14, 811–832, https://doi.org/10.5194/tc-14-811-2020, https://doi.org/10.5194/tc-14-811-2020, 2020
Short summary
Short summary
Marine-based sectors of the Antarctic Ice Sheet are increasingly contributing to sea-level rise. The basal conditions exert an important control on the ice dynamics. For obvious reasons of inaccessibility, they are an important source of uncertainties in numerical ice flow models used for sea-level projections. Here we assess the performance of an ensemble Kalman filter for the assimilation of transient observations of surface elevation and velocities in a marine ice sheet model.
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Short summary
A machine learning technique similar to the one used to enhance everyday photographs is applied to the problem of getting a better picture of Antarctica's bed – the part which is hidden beneath the ice. By taking hints from what satellites can observe at the ice surface, the novel method learns to generate a rougher bed topography that complements existing approaches, with a result that is able to be used by scientists running fine-scale ice sheet models relevant to predicting future sea levels.
A machine learning technique similar to the one used to enhance everyday photographs is applied...