- 1University of St Andrews, School of Geography and Sustainable Development, Lower Largo, United Kingdom of Great Britain (dib2@st-andrews.ac.uk)
- 2Environmental Science, University of Stirling, Stirling, FK9 4LA, UK
- 3CSC-IT Center for Science, Espoo, Finland
- 4Department of Geography, Swansea University, Swansea, UK
- 5Department Geographie und Geowissenschaften, Friedrich-Alexander-Universität, Erlangen-Nürnberg, Germany
- 6Institute for Marine and Antarctic Studies, Hobart, Australia
- 7Department of Physical Geography, University of Utrecht, Utrecht, Netherlands
The importance of calving losses from marine-terminating ice margins in a warming world has highlighted the need for reliable representation of calving in predictive ice-sheet models. However, there is currently no consensus regarding the most appropriate form for calving functions (so-called 'calving laws'), and the calving problem remains open. We advocate an integrated approach, in which observations, theory and high-fidelity modelling are used to develop and calibrate optimal, general calving functions for continuum ice-sheet models. Our work has demonstrated that calving is a stochastic process that gives rise to self-organising behaviour at a range of scales, including calving-size distributions, waiting times, and ice-front fluctuations. Individual calving events occur in response to critical and/or sub-critical crack propagation under tensile, shear or mixed stress regimes. We have used these insights to develop a position-based stochastic calving function, in which calving probabilities are scaled to the state of stress in the ice. When implemented in the full-stress continuum model Elmer/Ice, the calving function exhibits a wide range of realistic self-organising behaviour, and successfully reproduces observed ice-front fluctuations of Jakobshavn Isbrae and Store Glacier without the need for site-specific tuning. A calving algorithm suitable for vertically integrated ice-sheet models is in development.
How to cite: Benn, D., Wheel, I., Åström, J., Luckman, A., Cook, S., Christoffersen, P., Spicer, W., and Nick, F.: Progress in understanding and modelling calving, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4251, https://doi.org/10.5194/egusphere-egu26-4251, 2026.