Articles | Volume 15, issue 22
Geosci. Model Dev., 15, 8269–8293, 2022
https://doi.org/10.5194/gmd-15-8269-2022
Geosci. Model Dev., 15, 8269–8293, 2022
https://doi.org/10.5194/gmd-15-8269-2022
Model description paper
18 Nov 2022
Model description paper | 18 Nov 2022

The Stochastic Ice-Sheet and Sea-Level System Model v1.0 (StISSM v1.0)

Vincent Verjans et al.

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Cited articles

Albrecht, T. and Levermann, A.: Fracture-induced softening for large-scale ice dynamics, The Cryosphere, 8, 587–605, https://doi.org/10.5194/tc-8-587-2014, 2014. a
Amaral, T., Bartholomaus, T. C., and Enderlin, E. M.: Evaluation of Iceberg Calving Models Against Observations From Greenland Outlet Glaciers, J. Geophys. Res.-Earth, 125, 1–29, https://doi.org/10.1029/2019JF005444, 2020. a
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Aschwanden, A., Fahnestock, M. A., Truffer, M., Brinkerhoff, D. J., Hock, R., Khroulev, C., Mottram, R., and Khan, S. A.: Contribution of the Greenland Ice Sheet to sea level over the next millennium, Sci. Adv., 5, 6, https://doi.org/10.1126/sciadv.aav9396, 2019. a, b, c
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Short summary
We describe the development of the first large-scale ice sheet model that accounts for stochasticity in a range of processes. Stochasticity allows the impacts of inherently uncertain processes on ice sheets to be represented. This includes climatic uncertainty, as the climate is inherently chaotic. Furthermore, stochastic capabilities also encompass poorly constrained glaciological processes that display strong variability at fine spatiotemporal scales. We present the model and test experiments.