Articles | Volume 16, issue 2
The Cryosphere, 16, 689–709, 2022
https://doi.org/10.5194/tc-16-689-2022
The Cryosphere, 16, 689–709, 2022
https://doi.org/10.5194/tc-16-689-2022
Research article
25 Feb 2022
Research article | 25 Feb 2022

A comparison of the stability and performance of depth-integrated ice-dynamics solvers

Alexander Robinson et al.

Related authors

Simulating the Laurentide ice sheet of the Last Glacial Maximum
Daniel Moreno, Jorge Alvarez-Solas, Javier Blasco, Marisa Montoya, and Alexander Robinson
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-215,https://doi.org/10.5194/tc-2022-215, 2022
Preprint under review for TC
Short summary
The Earth system model CLIMBER-X v1.0 – Part 1: Climate model description and validation​​​​​​​​​​​​​​
Matteo Willeit, Andrey Ganopolski, Alexander Robinson, and Neil R. Edwards
Geosci. Model Dev., 15, 5905–5948, https://doi.org/10.5194/gmd-15-5905-2022,https://doi.org/10.5194/gmd-15-5905-2022, 2022
Short summary
On the periodicity of free oscillations for a finite ice column
Daniel Moreno, Alexander Robinson, Marisa Montoya, and Jorge Alvarez-Solas
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-97,https://doi.org/10.5194/tc-2022-97, 2022
Revised manuscript under review for TC
Short summary
Modeling the Greenland englacial stratigraphy
Andreas Born and Alexander Robinson
The Cryosphere, 15, 4539–4556, https://doi.org/10.5194/tc-15-4539-2021,https://doi.org/10.5194/tc-15-4539-2021, 2021
Short summary
Exploring the impact of atmospheric forcing and basal drag on the Antarctic Ice Sheet under Last Glacial Maximum conditions
Javier Blasco, Jorge Alvarez-Solas, Alexander Robinson, and Marisa Montoya
The Cryosphere, 15, 215–231, https://doi.org/10.5194/tc-15-215-2021,https://doi.org/10.5194/tc-15-215-2021, 2021
Short summary

Related subject area

Discipline: Ice sheets | Subject: Numerical Modelling
Geothermal heat flux is the dominant source of uncertainty in englacial-temperature-based dating of ice rise formation
Aleksandr Montelli and Jonathan Kingslake
The Cryosphere, 17, 195–210, https://doi.org/10.5194/tc-17-195-2023,https://doi.org/10.5194/tc-17-195-2023, 2023
Short summary
Improving interpretation of sea-level projections through a machine-learning-based local explanation approach
Jeremy Rohmer, Remi Thieblemont, Goneri Le Cozannet, Heiko Goelzer, and Gael Durand
The Cryosphere, 16, 4637–4657, https://doi.org/10.5194/tc-16-4637-2022,https://doi.org/10.5194/tc-16-4637-2022, 2022
Short summary
Subglacial hydrology modulates basal sliding response of the Antarctic ice sheet to climate forcing
Elise Kazmierczak, Sainan Sun, Violaine Coulon, and Frank Pattyn
The Cryosphere, 16, 4537–4552, https://doi.org/10.5194/tc-16-4537-2022,https://doi.org/10.5194/tc-16-4537-2022, 2022
Short summary
The predictive power of ice sheet models and the regional sensitivity of ice loss to basal sliding parameterisations: a case study of Pine Island and Thwaites glaciers, West Antarctica
Jowan M. Barnes and G. Hilmar Gudmundsson
The Cryosphere, 16, 4291–4304, https://doi.org/10.5194/tc-16-4291-2022,https://doi.org/10.5194/tc-16-4291-2022, 2022
Short summary
Simulations of firn processes over the Greenland and Antarctic ice sheets: 1980–2021
Brooke Medley, Thomas A. Neumann, H. Jay Zwally, Benjamin E. Smith, and C. Max Stevens
The Cryosphere, 16, 3971–4011, https://doi.org/10.5194/tc-16-3971-2022,https://doi.org/10.5194/tc-16-3971-2022, 2022
Short summary

Cited articles

Arthern, R. J. and Williams, C. R.: The sensitivity of West Antarctica to the submarine melting feedback, Geophys. Res. Lett., 44, 2352–2359, https://doi.org/10.1002/2017GL072514, 2017. a
Arthern, R. J., Hindmarsh, R. C. A., and Williams, C. R.: Flow speed within the Antarctic ice sheet and its controls inferred from satellite observations, J. Geophys. Res.-Earth, 120, 1171–1188, https://doi.org/10.1002/2014JF003239, 2015. a, b
Blatter, H.: Velocity and stress fields in grounded glaciers – a simple algorithm for including deviatoric stress gradients, J. Glaciol., 41, 333–344, 1995. a
Bueler, E.: Lectures at Karthaus: Numerical modelling of ice sheets and ice shelves, https://glaciers.gi.alaska.edu/sites/default/files/Notes_icesheetmod_Bueler2014.pdf (last access: 23 February 2022), 2009. a
Bueler, E. and Brown, J.: Shallow shelf approximation as a “sliding law” in a thermodynamically coupled ice sheet model, J. Geophys. Res., 114, F03008, https://doi.org/10.1029/2008JF001179, 2009. a
Download
Short summary
Here we investigate the numerical stability of several commonly used methods in order to determine which of them are capable of resolving the complex physics of the ice flow and are also computationally efficient. We find that the so-called DIVA solver outperforms the others. Its representation of the physics is consistent with more complex methods, while it remains computationally efficient at high resolution.