Articles | Volume 19, issue 16
https://doi.org/10.5194/gmd-19-7979-2026
https://doi.org/10.5194/gmd-19-7979-2026
Model description paper
 | 
27 Aug 2026
Model description paper |  | 27 Aug 2026

DeepMelt-GL v1: a neural network emulator of sub-shelf melt rates for the unrepresented regions of ice-shelf cavities in ocean models

Helen Ockenden, Clara Burgard, Pierre Mathiot, Christoph Kittel, Achille Gellens, Cécile Agosta, and Nicolas C. Jourdain

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The Cryosphere, 16, 3867–3887, https://doi.org/10.5194/tc-16-3867-2022,https://doi.org/10.5194/tc-16-3867-2022, 2022
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Cited articles

Asay-Davis, X. S., Cornford, S. L., Durand, G., Galton-Fenzi, B. K., Gladstone, R. M., Gudmundsson, G. H., Hattermann, T., Holland, D. M., Holland, D., Holland, P. R., Martin, D. F., Mathiot, P., Pattyn, F., and Seroussi, H.: Experimental design for three interrelated marine ice sheet and ocean model intercomparison projects: MISMIP v. 3 (MISMIP +), ISOMIP v. 2 (ISOMIP +) and MISOMIP v. 1 (MISOMIP1), Geosci. Model Dev., 9, 2471–2497, https://doi.org/10.5194/gmd-9-2471-2016, 2016. a
Beckmann, A., Hellmer, H. H., and Timmermann, R.: A numerical model of the Weddell Sea: Large-scale circulation and water mass distribution, J. Geophys. Res.-Oceans, 104, 23375–23391, https://doi.org/10.1029/1999JC900194, 1999. a
Beckmann, J., Reese, R., McCormack, F. S., Cook, S., Bird, L., Gwyther, D., Richards, D., Scheiter, M., Wang, Y., Seroussi, H., Abe‐Ouchi, A., Albrecht, T., Alvarez‐Solas, J., Asay‐Davis, X. S., Barre, J., Berends, C. J., Bernales, J., Blasco, J., Caillet, J., Chandler, D. M., Coulon, V., Cullather, R., Dumas, C., Galton‐Fenzi, B. K., Garbe, J., Gillet‐Chaulet, F., Gladstone, R., Goelzer, H., Golledge, N. R., Greve, R., Gudmundsson, G. H., Han, H. K., Hillebrand, T. R., Hoffman, M. J., Huybrechts, P., Jourdain, N. C., Klose, A. K., Langebroek, P. M., Leguy, G. R., Lipscomb, W. H., Lowry, D. P., Mathiot, P., Montoya, M., Morlighem, M., Nowicki, S., Pattyn, F., Payne, A. J., Pelle, T., Quiquet, A., Robinson, A., Saraste, L., Simon, E. G., Sun, S., Twarog, J. P., Trusel, L. D., Urruty, B., Van Breedam, J., van de Wal, R. S. W., Zhao, C., and Zwinger, T.: Disentangling uncertainty in ISMIP6 Antarctic sub-shelf melting and 2300 sea level rise projections, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-4069, 2025. a
Begeman, C. B., Tulaczyk, S., Padman, L., King, M., Siegfried, M. R., Hodson, T. O., and Fricker, H. A.: Tidal pressurization of the ocean cavity near an Antarctic ice shelf grounding line, J. Geophys. Res.-Oceans, 125, e2019JC015562, https://doi.org/10.1029/2019JC015562, 2020. a
Bett, D. T., Bradley, A. T., Williams, C. R., Holland, P. R., Arthern, R. J., and Goldberg, D. N.: Coupled ice–ocean interactions during future retreat of West Antarctic ice streams in the Amundsen Sea sector, The Cryosphere, 18, 2653–2675, https://doi.org/10.5194/tc-18-2653-2024, 2024. a
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Since numerical computing is expensive, climate models must decide between having a high spatial resolution or running for long time periods. Here, we develop a simple neural network to emulate small-scale processes occurring beneath Antarctic ice shelves, which allows sub-shelf melt and ice–ocean interactions to be included in global ocean models which can run for multiple centuries. This neural network will help us to understand how ocean circulation may change in the future.
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