Articles | Volume 15, issue 12
https://doi.org/10.5194/tc-15-5639-2021
https://doi.org/10.5194/tc-15-5639-2021
Research article
 | 
13 Dec 2021
Research article |  | 13 Dec 2021

Improving surface melt estimation over the Antarctic Ice Sheet using deep learning: a proof of concept over the Larsen Ice Shelf

Zhongyang Hu, Peter Kuipers Munneke, Stef Lhermitte, Maaike Izeboud, and Michiel van den Broeke

Related authors

IMAU Antarctic automatic weather station data, including surface radiation balance (1995–2022)
Maurice van Tiggelen, Paul C. J. P. Smeets, Carleen H. Reijmer, Peter Kuipers Munneke, and Michiel R. van den Broeke
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-88,https://doi.org/10.5194/essd-2025-88, 2025
Revised manuscript accepted for ESSD
Short summary
Ocean-Induced Weakening of George VI Ice Shelf
Ann-Sofie P. Zinck, Bert Wouters, Franka Jesse, and Stef Lhermitte
EGUsphere, https://doi.org/10.5194/egusphere-2025-573,https://doi.org/10.5194/egusphere-2025-573, 2025
Short summary
On the accuracy of the measured and modelled surface latent and sensible heat flux in the interior of the Greenland Ice Sheet
Ida Haven, Hans Christian Steen-Larsen, Laura J. Dietrich, Sonja Wahl, Jason E. Box, Michiel R. Van den Broeke, Alun Hubbard, Stephan T. Kral, Joachim Reuder, and Maurice Van Tiggelen
EGUsphere, https://doi.org/10.5194/egusphere-2025-711,https://doi.org/10.5194/egusphere-2025-711, 2025
Short summary
Seasonal and interannual variability of freshwater sources for Greenland's fjords
Anneke Louise Vries, Willem Jan van de Berg, Brice Noël, Lorenz Meire, and Michiel R. van den Broeke
EGUsphere, https://doi.org/10.5194/egusphere-2024-3735,https://doi.org/10.5194/egusphere-2024-3735, 2025
Short summary
Assessing the effect of forest management on above-ground carbon stock by remote sensing
Sofie Van Winckel, Jonas Simons, Stef Lhermitte, and Bart Muys
EGUsphere, https://doi.org/10.5194/egusphere-2024-4094,https://doi.org/10.5194/egusphere-2024-4094, 2025
Short summary

Related subject area

Discipline: Ice sheets | Subject: Antarctic
Bathymetry-constrained warm-mode melt estimates derived from analysing oceanic gateways in Antarctica
Lena Nicola, Ronja Reese, Moritz Kreuzer, Torsten Albrecht, and Ricarda Winkelmann
The Cryosphere, 19, 2263–2287, https://doi.org/10.5194/tc-19-2263-2025,https://doi.org/10.5194/tc-19-2263-2025, 2025
Short summary
Satellite data reveal details of glacial isostatic adjustment in the Amundsen Sea Embayment, West Antarctica
Matthias O. Willen, Bert Wouters, Taco Broerse, Eric Buchta, and Veit Helm
The Cryosphere, 19, 2213–2227, https://doi.org/10.5194/tc-19-2213-2025,https://doi.org/10.5194/tc-19-2213-2025, 2025
Short summary
Review article: Feature tracing in radio-echo sounding products of terrestrial ice sheets and planetary bodies
Hameed Moqadam and Olaf Eisen
The Cryosphere, 19, 2159–2196, https://doi.org/10.5194/tc-19-2159-2025,https://doi.org/10.5194/tc-19-2159-2025, 2025
Short summary
Viscoelastic mechanics of tidally induced lake drainage in the grounding zone
Hanwen Zhang, Richard F. Katz, and Laura A. Stevens
The Cryosphere, 19, 2087–2103, https://doi.org/10.5194/tc-19-2087-2025,https://doi.org/10.5194/tc-19-2087-2025, 2025
Short summary
A facet-based numerical model to retrieve ice sheet topography from Sentinel-3 altimetry
Jérémie Aublanc, François Boy, Franck Borde, and Pierre Féménias
The Cryosphere, 19, 1937–1954, https://doi.org/10.5194/tc-19-1937-2025,https://doi.org/10.5194/tc-19-1937-2025, 2025
Short summary

Cited articles

Arthur, J. F., Stokes, C., Jamieson, S. S., Carr, J. R., and Leeson, A. A.: Recent understanding of Antarctic supraglacial lakes using satellite remote sensing, Prog. Phys. Geogr., 44, 837–869, 2020. a
Bindschadler, R., Choi, H., Wichlacz, A., Bingham, R., Bohlander, J., Brunt, K., Corr, H., Drews, R., Fricker, H., Hall, M., Hindmarsh, R., Kohler, J., Padman, L., Rack, W., Rotschky, G., Urbini, S., Vornberger, P., and Young, N.: Getting around Antarctica: new high-resolution mappings of the grounded and freely-floating boundaries of the Antarctic ice sheet created for the International Polar Year, The Cryosphere, 5, 569–588, https://doi.org/10.5194/tc-5-569-2011, 2011. a
Breiman, L.: Random forests, Mach. Learn., 45, 5–32, 2001. a
Cape, M., Vernet, M., Skvarca, P., Marinsek, S., Scambos, T., and Domack, E.: Foehn winds link climate-driven warming to ice shelf evolution in Antarctica, J. Geophys. Res.-Atmos., 120, 11–037, 2015. a
Chen, T. and Guestrin, C.: Xgboost: A scalable tree boosting system, in: Proceedings of the 22nd acm sigkdd international conference on knowledge discovery and data mining, 13–17 August 2016, San Francisco, California, USA, 785–794, 2016. a
Download
Short summary
Antarctica is shrinking, and part of the mass loss is caused by higher temperatures leading to more snowmelt. We use computer models to estimate the amount of melt, but this can be inaccurate – specifically in the areas with the most melt. This is because the model cannot account for small, darker areas like rocks or darker ice. Thus, we trained a computer using artificial intelligence and satellite images that showed these darker areas. The model computed an improved estimate of melt.
Share