Articles | Volume 16, issue 2
The Cryosphere, 16, 533–557, 2022
https://doi.org/10.5194/tc-16-533-2022
The Cryosphere, 16, 533–557, 2022
https://doi.org/10.5194/tc-16-533-2022
Research article
15 Feb 2022
Research article | 15 Feb 2022

A new state-dependent parameterization for the free drift of sea ice

Charles Brunette et al.

Related authors

Smoothed Particle Hydrodynamics Implementation of the Standard Viscous-Plastic Sea-Ice Model and Validation in Simple Idealized Experiments
Oreste Marquis, Bruno Tremblay, Jean-François Lemieux, and Mohammed Islam
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-163,https://doi.org/10.5194/tc-2022-163, 2022
Preprint under review for TC
Short summary
A generalized stress correction scheme for the Maxwell elasto-brittle rheology: impact on the fracture angles and deformations
Mathieu Plante and L. Bruno Tremblay
The Cryosphere, 15, 5623–5638, https://doi.org/10.5194/tc-15-5623-2021,https://doi.org/10.5194/tc-15-5623-2021, 2021
Short summary
Non-normal flow rules affect fracture angles in sea ice viscous–plastic rheologies
Damien Ringeisen, L. Bruno Tremblay, and Martin Losch
The Cryosphere, 15, 2873–2888, https://doi.org/10.5194/tc-15-2873-2021,https://doi.org/10.5194/tc-15-2873-2021, 2021
Short summary
A fully coupled Arctic sea-ice–ocean–atmosphere model (ArcIOAM v1.0) based on C-Coupler2: model description and preliminary results
Shihe Ren, Xi Liang, Qizhen Sun, Hao Yu, L. Bruno Tremblay, Bo Lin, Xiaoping Mai, Fu Zhao, Ming Li, Na Liu, Zhikun Chen, and Yunfei Zhang
Geosci. Model Dev., 14, 1101–1124, https://doi.org/10.5194/gmd-14-1101-2021,https://doi.org/10.5194/gmd-14-1101-2021, 2021
Short summary
Toward a method for downscaling sea ice pressure for navigation purposes
Jean-François Lemieux, L. Bruno Tremblay, and Mathieu Plante
The Cryosphere, 14, 3465–3478, https://doi.org/10.5194/tc-14-3465-2020,https://doi.org/10.5194/tc-14-3465-2020, 2020
Short summary

Related subject area

Discipline: Sea ice | Subject: Sea Ice
Probabilistic spatiotemporal seasonal sea ice presence forecasting using sequence-to-sequence learning and ERA5 data in the Hudson Bay region
Nazanin Asadi, Philippe Lamontagne, Matthew King, Martin Richard, and K. Andrea Scott
The Cryosphere, 16, 3753–3773, https://doi.org/10.5194/tc-16-3753-2022,https://doi.org/10.5194/tc-16-3753-2022, 2022
Short summary
Predictability of Arctic sea ice drift in coupled climate models
Simon Felix Reifenberg and Helge Friedrich Goessling
The Cryosphere, 16, 2927–2946, https://doi.org/10.5194/tc-16-2927-2022,https://doi.org/10.5194/tc-16-2927-2022, 2022
Short summary
Recovering and monitoring the thickness, density, and elastic properties of sea ice from seismic noise recorded in Svalbard
Agathe Serripierri, Ludovic Moreau, Pierre Boue, Jérôme Weiss, and Philippe Roux
The Cryosphere, 16, 2527–2543, https://doi.org/10.5194/tc-16-2527-2022,https://doi.org/10.5194/tc-16-2527-2022, 2022
Short summary
Influences of changing sea ice and snow thicknesses on simulated Arctic winter heat fluxes
Laura L. Landrum and Marika M. Holland
The Cryosphere, 16, 1483–1495, https://doi.org/10.5194/tc-16-1483-2022,https://doi.org/10.5194/tc-16-1483-2022, 2022
Short summary
Reassessing seasonal sea ice predictability of the Pacific-Arctic sector using a Markov model
Yunhe Wang, Xiaojun Yuan, Haibo Bi, Mitchell Bushuk, Yu Liang, Cuihua Li, and Haijun Huang
The Cryosphere, 16, 1141–1156, https://doi.org/10.5194/tc-16-1141-2022,https://doi.org/10.5194/tc-16-1141-2022, 2022
Short summary

Cited articles

Andersen, S., Tonboe, R., Kaleschke, L., Heygster, G., and Pedersen, L. T.: Intercomparison of passive microwave sea ice concentration retrievals over the high-concentration Arctic sea ice, J. Geophys. Res.-Oceans, 112, C8, https://doi.org/10.1029/2006JC003543, 2007. a
Aporta, C.: Life on the ice: understanding the codes of a changing environment, Polar Rec., 38, 341–354, https://doi.org/10.1017/S0032247400018039, 2002. a
Armitage, T. W. K., Bacon, S., Ridout, A. L., Petty, A. A., Wolbach, S., and Tsamados, M.: Arctic Ocean surface geostrophic circulation 2003–2014, The Cryosphere, 11, 1767–1780, https://doi.org/10.5194/tc-11-1767-2017, 2017a. a, b, c, d, e, f
Armitage, T. W. K., Bacon, S., Ridout, A. L., Petty, A. A., Wolbach, S., and Tsamados, M.: Arctic Ocean surface geostrophic circulation 2003–2014, The Cryosphere, 11, 1767–1780, https://doi.org/10.5194/tc-11-1767-2017, 2017b (data available at: http://www.cpom.ucl.ac.uk/dynamic_topography). a
Armitage, T. W., Manucharyan, G. E., Petty, A. A., Kwok, R., and Thompson, A. F.: Enhanced eddy activity in the Beaufort Gyre in response to sea ice loss, Nat. Commun., 11, 1–8, https://doi.org/10.1038/s41467-020-14449-z, 2020. a
Download
Short summary
Sea ice motion is a versatile parameter for monitoring the Arctic climate system. In this contribution, we use data from drifting buoys, winds, and ice thickness to parameterize the motion of sea ice in a free drift regime – i.e., flowing freely in response to the forcing from the winds and ocean currents. We show that including a dependence on sea ice thickness and taking into account a climatology of the surface ocean circulation significantly improves the accuracy of sea ice motion estimates.