EGU26-9225, updated on 14 Mar 2026
https://doi.org/10.5194/egusphere-egu26-9225
EGU General Assembly 2026
© Author(s) 2026. This work is distributed under the Creative Commons Attribution 4.0 License.
A machine-learning-based super-resolution approach for dynamical ice-sheet modeling
1,2,3,3- 1Wegener Center for Climate and Global Change, University of Graz, Austria
- 2Geophysical Institute, University of Alaska, Fairbanks, United States
- 3Department of Geography and Regional Science, University of Graz, Austria
- 4Know Center Research GmbH, Graz, Austria
How to cite: Scher, S., Aschwanden, A., Schalamon, F., Trügler, A., and Abermann, J.: A machine-learning-based super-resolution approach for dynamical ice-sheet modeling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9225, https://doi.org/10.5194/egusphere-egu26-9225, 2026.