Articles | Volume 15, issue 6
https://doi.org/10.5194/tc-15-2873-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-15-2873-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Jun 2021
Research article |
| 24 Jun 2021
| 24 Jun 2021
Non-normal flow rules affect fracture angles in sea ice viscous–plastic rheologies
Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany
MARUM – Center for Marine Environmental Sciences, Leobener Str. 8, 28359, Bremen, Germany
L. Bruno Tremblay
Department of Atmospheric and Oceanic Sciences, McGill University, Montréal, Canada
Martin Losch
Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany
Related authors
Mathieu Plante, Jean-François Lemieux, L. Bruno Tremblay, Amélie Bouchat, Damien Ringeisen, Philippe Blain, Stephen Howell, Mike Brady, Alexander S. Komarov, Béatrice Duval, and Lekima Yakuden
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-227, https://doi.org/10.5194/essd-2024-227, 2024
Preprint under review for ESSD
Short summary
Short summary
Sea ice forms a thin boundary between the ocean and the atmosphere, with a complex crust-like dynamics and ever-changing networks of sea ice leads and ridges. Statistics of these dynamical features are often used to evaluate sea ice models. Here, we present a new pan-Arctic dataset of sea ice deformations derived from satellite imagery, from 01 September 2017 to 31 August 2023. We discuss the dataset coverage and some limitations associated with uncertainties in the computed values.
Damien Ringeisen, Nils Hutter, and Luisa von Albedyll
The Cryosphere, 17, 4047–4061, https://doi.org/10.5194/tc-17-4047-2023, https://doi.org/10.5194/tc-17-4047-2023, 2023
Short summary
Short summary
When sea ice is put into motion by wind and ocean currents, it deforms following narrow lines. Our two datasets at different locations and resolutions show that the intersection angle between these lines is often acute and rarely obtuse. We use the orientation of narrow lines to gain indications about the mechanical properties of sea ice and to constrain how to design sea-ice mechanical models for high-resolution simulation of the Arctic and improve regional predictions of sea-ice motion.
Damien Ringeisen, Martin Losch, L. Bruno Tremblay, and Nils Hutter
The Cryosphere, 13, 1167–1186, https://doi.org/10.5194/tc-13-1167-2019, https://doi.org/10.5194/tc-13-1167-2019, 2019
Short summary
Short summary
We study the creation of fracture in sea ice plastic models. To do this, we compress an ideal piece of ice of 8 km by 25 km. We use two different mathematical expressions defining the resistance of ice. We find that the most common one is unable to model the fracture correctly, while the other gives better results but brings instabilities. The results are often in opposition with ice granular nature (e.g., sand) and call for changes in ice modeling.
Mathieu Plante, Jean-François Lemieux, L. Bruno Tremblay, Amélie Bouchat, Damien Ringeisen, Philippe Blain, Stephen Howell, Mike Brady, Alexander S. Komarov, Béatrice Duval, and Lekima Yakuden
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-227, https://doi.org/10.5194/essd-2024-227, 2024
Preprint under review for ESSD
Short summary
Short summary
Sea ice forms a thin boundary between the ocean and the atmosphere, with a complex crust-like dynamics and ever-changing networks of sea ice leads and ridges. Statistics of these dynamical features are often used to evaluate sea ice models. Here, we present a new pan-Arctic dataset of sea ice deformations derived from satellite imagery, from 01 September 2017 to 31 August 2023. We discuss the dataset coverage and some limitations associated with uncertainties in the computed values.
Antoine Savard and Bruno Tremblay
The Cryosphere, 18, 2017–2034, https://doi.org/10.5194/tc-18-2017-2024, https://doi.org/10.5194/tc-18-2017-2024, 2024
Short summary
Short summary
We include a suitable plastic damage parametrization in the standard viscous–plastic (VP) sea ice model to disentangle its effect from resolved model physics (visco-plastic with and without damage) on its ability to reproduce observed scaling laws of deformation. This study shows that including a damage parametrization in the VP model improves its performance in simulating the statistical behavior of fracture patterns. Therefore, a damage parametrization is a powerful tuning knob.
Mathieu Plante, Jean-François Lemieux, L. Bruno Tremblay, Adrienne Tivy, Joey Angnatok, François Roy, Gregory Smith, Frédéric Dupont, and Adrian K. Turner
The Cryosphere, 18, 1685–1708, https://doi.org/10.5194/tc-18-1685-2024, https://doi.org/10.5194/tc-18-1685-2024, 2024
Short summary
Short summary
We use a sea ice model to reproduce ice growth observations from two buoys deployed on coastal sea ice and analyze the improvements brought by new physics that represent the presence of saline liquid water in the ice interior. We find that the new physics with default parameters degrade the model performance, with overly rapid ice growth and overly early snow flooding on top of the ice. The performance is largely improved by simple modifications to the ice growth and snow-flooding algorithms.
Oreste Marquis, Bruno Tremblay, Jean-François Lemieux, and Mohammed Islam
The Cryosphere, 18, 1013–1032, https://doi.org/10.5194/tc-18-1013-2024, https://doi.org/10.5194/tc-18-1013-2024, 2024
Short summary
Short summary
We developed a standard viscous–plastic sea-ice model based on the numerical framework called smoothed particle hydrodynamics. The model conforms to the theory within an error of 1 % in an idealized ridging experiment, and it is able to simulate stable ice arches. However, the method creates a dispersive plastic wave speed. The framework is efficient to simulate fractures and can take full advantage of parallelization, making it a good candidate to investigate sea-ice material properties.
Damien Ringeisen, Nils Hutter, and Luisa von Albedyll
The Cryosphere, 17, 4047–4061, https://doi.org/10.5194/tc-17-4047-2023, https://doi.org/10.5194/tc-17-4047-2023, 2023
Short summary
Short summary
When sea ice is put into motion by wind and ocean currents, it deforms following narrow lines. Our two datasets at different locations and resolutions show that the intersection angle between these lines is often acute and rarely obtuse. We use the orientation of narrow lines to gain indications about the mechanical properties of sea ice and to constrain how to design sea-ice mechanical models for high-resolution simulation of the Arctic and improve regional predictions of sea-ice motion.
Charles Brunette, L. Bruno Tremblay, and Robert Newton
The Cryosphere, 16, 533–557, https://doi.org/10.5194/tc-16-533-2022, https://doi.org/10.5194/tc-16-533-2022, 2022
Short summary
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.
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
Short summary
We propose a generalized form for the damage parameterization such that super-critical stresses can return to the yield with different final sub-critical stress states. In uniaxial compression simulations, the generalization improves the orientation of sea ice fractures and reduces the growth of numerical errors. Shear and convergence deformations however remain predominant along the fractures, contrary to observations, and this calls for modification of the post-fracture viscosity formulation.
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
Short summary
Sea ice plays a crucial role in global energy and water budgets. To get a better simulation of sea ice, we coupled a sea ice model with an atmospheric and ocean model to form a fully coupled system. The sea ice simulation results of this coupled system demonstrated that a two-way coupled model has better performance in terms of sea ice, especially in summer. This indicates that sea-ice–ocean–atmosphere interaction plays a crucial role in controlling Arctic summertime sea ice distribution.
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
Short summary
Sea ice pressure poses great risk for navigation; it can lead to ship besetting and damages. Sea ice forecasting systems can predict the evolution of pressure. However, these systems have low spatial resolution (a few km) compared to the dimensions of ships. We study the downscaling of pressure from the km-scale to scales relevant for navigation. We find that the pressure applied on a ship beset in heavy ice conditions can be markedly larger than the pressure predicted by the forecasting system.
Mathieu Plante, Bruno Tremblay, Martin Losch, and Jean-François Lemieux
The Cryosphere, 14, 2137–2157, https://doi.org/10.5194/tc-14-2137-2020, https://doi.org/10.5194/tc-14-2137-2020, 2020
Short summary
Short summary
We study the formation of ice arches between two islands using a model that resolves crack initiation and propagation. This model uses a damage parameter to parameterize the presence or absence of cracks in the ice. We find that the damage parameter allows for cracks to propagate in the ice but in a different orientation than predicted by theory. The results call for improvement in how stress relaxation associated with this damage is parameterized.
Angela Cheng, Barbara Casati, Adrienne Tivy, Tom Zagon, Jean-François Lemieux, and L. Bruno Tremblay
The Cryosphere, 14, 1289–1310, https://doi.org/10.5194/tc-14-1289-2020, https://doi.org/10.5194/tc-14-1289-2020, 2020
Short summary
Short summary
Sea ice charts by the Canadian Ice Service (CIS) contain visually estimated ice concentration produced by analysts. The accuracy of manually derived ice concentrations is not well understood. The subsequent uncertainty of ice charts results in downstream uncertainties for ice charts users, such as models and climatology studies, and when used as a verification source for automated sea ice classifiers. This study quantifies the level of accuracy and inter-analyst agreement for ice charts by CIS.
Nils Hutter and Martin Losch
The Cryosphere, 14, 93–113, https://doi.org/10.5194/tc-14-93-2020, https://doi.org/10.5194/tc-14-93-2020, 2020
Short summary
Short summary
Sea ice is composed of a multitude of floes that constantly deform due to wind and ocean currents and thereby form leads and pressure ridges. These features are visible in the ice as stripes of open-ocean or high-piled ice. High-resolution sea ice models start to resolve these deformation features. In this paper we present two simulations that agree with satellite data according to a new evaluation metric that detects deformation features and compares their spatial and temporal characteristics.
Svetlana N. Losa, Stephanie Dutkiewicz, Martin Losch, Julia Oelker, Mariana A. Soppa, Scarlett Trimborn, Hongyan Xi, and Astrid Bracher
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-289, https://doi.org/10.5194/bg-2019-289, 2019
Manuscript not accepted for further review
Short summary
Short summary
This study highlights recent advances and challenges of applying coupled physical-biogeochemical modeling for investigating the distribution of the key phytoplankton groups in the Southern Ocean. By leveraging satellite and in situ observations we define numerical ecological model requirements in the phytoplankton trait specification and level of physiological and morphological differentiation for capturing and explaining the observed biogeography of diatoms, coccolithophores and Phaeocystis.
Damien Ringeisen, Martin Losch, L. Bruno Tremblay, and Nils Hutter
The Cryosphere, 13, 1167–1186, https://doi.org/10.5194/tc-13-1167-2019, https://doi.org/10.5194/tc-13-1167-2019, 2019
Short summary
Short summary
We study the creation of fracture in sea ice plastic models. To do this, we compress an ideal piece of ice of 8 km by 25 km. We use two different mathematical expressions defining the resistance of ice. We find that the most common one is unable to model the fracture correctly, while the other gives better results but brings instabilities. The results are often in opposition with ice granular nature (e.g., sand) and call for changes in ice modeling.
Nils Hutter, Lorenzo Zampieri, and Martin Losch
The Cryosphere, 13, 627–645, https://doi.org/10.5194/tc-13-627-2019, https://doi.org/10.5194/tc-13-627-2019, 2019
Short summary
Short summary
Arctic sea ice is an aggregate of ice floes with various sizes. The different sizes result from constant deformation of the ice pack. If a floe breaks, open ocean is exposed in a lead. Collision of floes forms pressure ridges. Here, we present algorithms that detect and track these deformation features in satellite observations and model output. The tracked features are used to provide a comprehensive description of localized deformation of sea ice and help to understand its material properties.
Andrea Klus, Matthias Prange, Vidya Varma, Louis Bruno Tremblay, and Michael Schulz
Clim. Past, 14, 1165–1178, https://doi.org/10.5194/cp-14-1165-2018, https://doi.org/10.5194/cp-14-1165-2018, 2018
Short summary
Short summary
Numerous proxy records from the northern North Atlantic suggest substantial climate variability including the occurrence of multi-decadal-to-centennial cold events during the Holocene. We analyzed two abrupt cold events in a Holocene simulation using a comprehensive climate model. It is shown that the events were ultimately triggered by prolonged phases of positive North Atlantic Oscillation causing changes in ocean circulation followed by severe cooling, freshening, and expansion of sea ice.
Paul J. Kushner, Lawrence R. Mudryk, William Merryfield, Jaison T. Ambadan, Aaron Berg, Adéline Bichet, Ross Brown, Chris Derksen, Stephen J. Déry, Arlan Dirkson, Greg Flato, Christopher G. Fletcher, John C. Fyfe, Nathan Gillett, Christian Haas, Stephen Howell, Frédéric Laliberté, Kelly McCusker, Michael Sigmond, Reinel Sospedra-Alfonso, Neil F. Tandon, Chad Thackeray, Bruno Tremblay, and Francis W. Zwiers
The Cryosphere, 12, 1137–1156, https://doi.org/10.5194/tc-12-1137-2018, https://doi.org/10.5194/tc-12-1137-2018, 2018
Short summary
Short summary
Here, the Canadian research network CanSISE uses state-of-the-art observations of snow and sea ice to assess how Canada's climate model and climate prediction systems capture variability in snow, sea ice, and related climate parameters. We find that the system performs well, accounting for observational uncertainty (especially for snow), model uncertainty, and chaotic climate variability. Even for variables like sea ice, where improvement is needed, useful prediction tools can be developed.
Vincent Le Fouest, Atsushi Matsuoka, Manfredi Manizza, Mona Shernetsky, Bruno Tremblay, and Marcel Babin
Biogeosciences, 15, 1335–1346, https://doi.org/10.5194/bg-15-1335-2018, https://doi.org/10.5194/bg-15-1335-2018, 2018
Short summary
Short summary
Climate warming could enhance the load of terrigenous dissolved organic carbon (tDOC) of Arctic rivers. We show that tDOC concentrations simulated by an ocean–biogeochemical model in the Canadian Beaufort Sea compare favorably with their satellite counterparts. Over spring–summer, riverine tDOC contributes to 35 % of primary production and an equivalent of ~ 10 % of tDOC is exported westwards with the potential for fueling the biological production of the eastern Alaskan nearshore waters.
Dirk Notz, Alexandra Jahn, Marika Holland, Elizabeth Hunke, François Massonnet, Julienne Stroeve, Bruno Tremblay, and Martin Vancoppenolle
Geosci. Model Dev., 9, 3427–3446, https://doi.org/10.5194/gmd-9-3427-2016, https://doi.org/10.5194/gmd-9-3427-2016, 2016
Short summary
Short summary
The large-scale evolution of sea ice is both an indicator and a driver of climate changes. Hence, a realistic simulation of sea ice is key for a realistic simulation of the climate system of our planet. To assess and to improve the realism of sea-ice simulations, we present here a new protocol for climate-model output that allows for an in-depth analysis of the simulated evolution of sea ice.
Qinghua Yang, Martin Losch, Svetlana N. Losa, Thomas Jung, Lars Nerger, and Thomas Lavergne
The Cryosphere, 10, 761–774, https://doi.org/10.5194/tc-10-761-2016, https://doi.org/10.5194/tc-10-761-2016, 2016
Short summary
Short summary
We assimilate the summer SICCI sea ice concentration data with an ensemble-based Kalman Filter. Comparing with the approach using a constant data uncertainty, the sea ice concentration estimates are further improved when the SICCI-provided uncertainty are taken into account, but the sea ice thickness cannot be improved. We find the data assimilation system cannot give a reasonable ensemble spread of sea ice concentration and thickness if the provided uncertainty are directly used.
T. Kurahashi-Nakamura, M. Losch, and A. Paul
Geosci. Model Dev., 7, 419–432, https://doi.org/10.5194/gmd-7-419-2014, https://doi.org/10.5194/gmd-7-419-2014, 2014
Related subject area
Discipline: Sea ice | Subject: Rheology
Multivariate state and parameter estimation with data assimilation applied to sea-ice models using a Maxwell elasto-brittle rheology
On the sensitivity of sea ice deformation statistics to plastic damage
Behavior of saline ice under cyclic flexural loading
Parameter optimization in sea ice models with elastic–viscoplastic rheology
Landfast sea ice material properties derived from ice bridge simulations using the Maxwell elasto-brittle rheology
Yumeng Chen, Polly Smith, Alberto Carrassi, Ivo Pasmans, Laurent Bertino, Marc Bocquet, Tobias Sebastian Finn, Pierre Rampal, and Véronique Dansereau
The Cryosphere, 18, 2381–2406, https://doi.org/10.5194/tc-18-2381-2024, https://doi.org/10.5194/tc-18-2381-2024, 2024
Short summary
Short summary
We explore multivariate state and parameter estimation using a data assimilation approach through idealised simulations in a dynamics-only sea-ice model based on novel rheology. We identify various potential issues that can arise in complex operational sea-ice models when model parameters are estimated. Even though further investigation will be needed for such complex sea-ice models, we show possibilities of improving the observed and the unobserved model state forecast and parameter accuracy.
Antoine Savard and Bruno Tremblay
The Cryosphere, 18, 2017–2034, https://doi.org/10.5194/tc-18-2017-2024, https://doi.org/10.5194/tc-18-2017-2024, 2024
Short summary
Short summary
We include a suitable plastic damage parametrization in the standard viscous–plastic (VP) sea ice model to disentangle its effect from resolved model physics (visco-plastic with and without damage) on its ability to reproduce observed scaling laws of deformation. This study shows that including a damage parametrization in the VP model improves its performance in simulating the statistical behavior of fracture patterns. Therefore, a damage parametrization is a powerful tuning knob.
Andrii Murdza, Erland M. Schulson, and Carl E. Renshaw
The Cryosphere, 15, 2415–2428, https://doi.org/10.5194/tc-15-2415-2021, https://doi.org/10.5194/tc-15-2415-2021, 2021
Short summary
Short summary
It has been suggested that the observed sudden breakup of Arctic and Antarctic floating ice covers may be due to fatigue failure associated with cyclic loading from ocean swells that can penetrate deeply into an ice pack. To investigate this possibility, we measured the flexural strength of saline ice after cyclic loading. Contrary to expectations, we find that the flexural strength of saline ice increases upon cycling, similar to the behavior of laboratory-grown ice and natural lake ice.
Gleb Panteleev, Max Yaremchuk, Jacob N. Stroh, Oceana P. Francis, and Richard Allard
The Cryosphere, 14, 4427–4451, https://doi.org/10.5194/tc-14-4427-2020, https://doi.org/10.5194/tc-14-4427-2020, 2020
Short summary
Short summary
In the CICE6 community model, rheology and landfast grounding/arching effects are simulated by functions of sea ice thickness and concentration with a set of fixed parameters empirically adjusted to optimize model performance. In this study we consider a spatially variable extension for representing these parameters in the two-dimensional elastic–viscoplastic (EVP) sea ice model and analyze the feasibility of the optimization of these parameters through the 4D-Var data assimilation approach.
Mathieu Plante, Bruno Tremblay, Martin Losch, and Jean-François Lemieux
The Cryosphere, 14, 2137–2157, https://doi.org/10.5194/tc-14-2137-2020, https://doi.org/10.5194/tc-14-2137-2020, 2020
Short summary
Short summary
We study the formation of ice arches between two islands using a model that resolves crack initiation and propagation. This model uses a damage parameter to parameterize the presence or absence of cracks in the ice. We find that the damage parameter allows for cracks to propagate in the ice but in a different orientation than predicted by theory. The results call for improvement in how stress relaxation associated with this damage is parameterized.
Cited articles
Aksenov, Y. and Hibler, W. D.: Failure Propagation Effects in an Anisotropic Sea Ice Dynamics Model, in: IUTAM Symposium on Scaling Laws in Ice Mechanics and Ice Dynamics, edited by: Dempsey, J. P. and Shen, H. H., Solid Mechanics and Its Applications, 363–372, Springer, the Netherlands, 2001. a
Alshibli, K. A. and Sture, S.: Shear Band Formation in Plane Strain Experiments of Sand, J. Geotech. Geoenviron., 126, 495–503, https://doi.org/10.1061/(ASCE)1090-0241(2000)126:6(495), 2000. a, b
Anderson, E. M.: The dynamics of faulting and dyke formation with applications to Britain, Oliver and Boyd, 1942. a
Arthur, J. R. F., Dunstan, T., Al-Ani, Q. a. J. L., and Assadi, A.: Plastic deformation and failure in granular media, Géotechnique, 27, 53–74, https://doi.org/10.1680/geot.1977.27.1.53, 1977. a
Badgley, F. I.: Heat balance at the surface of the Arctic Ocean, in: Proceedings of the 29th Annual Western Snow Conference, Western Snow Conference, Spokane, Washington, available at: https://westernsnowconference.org/node/1205 (last access: 3 June 2021), 1961. a
Balendran, B. and Nemat-Nasser, S.: Double sliding model for cyclic deformation of granular materials, including dilatancy effects, J. Mech. Phys. Solids, 41, 573–612, https://doi.org/10.1016/0022-5096(93)90049-L, 1993. a, b, c, d
Bolton, M. D.: The strength and dilatancy of sands, ICE Publishing, Géotechnique, 36, 65–78, https://doi.org/10.1680/geot.1986.36.1.65, 1986. a
Bouchat, A. and Tremblay, B.: Using sea-ice deformation fields to constrain the mechanical strength parameters of geophysical sea ice, J. Geophys. Res.-Oceans, 122, 5802–5825, https://doi.org/10.1002/2017JC013020, 2017. a, b, c, d
Buiter, S. J. H., Babeyko, A. Y., Ellis, S., Gerya, T. V., Kaus, B. J. P., Kellner, A., Schreurs, G., and Yamada, Y.: The numerical sandbox: comparison of model results for a shortening and an extension experiment, Analogue and Numerical Sandbox Models, Geol. Soc. Sp., 253, 29–64, https://doi.org/10.1144/GSL.SP.2006.253.01.02, 2006. a
Campin, J.-M., Heimbach, P., Losch, M., Forget, G., Adcroft, A., Dussin, R., et al.: MITgcm/MITgcm: checkpoint67z (Version checkpoint67z), Zenodo, https://doi.org/10.5281/zenodo.4968496, 2021. a
Coon, M., Kwok, R., Levy, G., Pruis, M., Schreyer, H., and Sulsky, D.: Arctic Ice Dynamics Joint Experiment (AIDJEX) assumptions revisited and found inadequate, J. Geophys. Res.-Oceans, 112, C11S90, https://doi.org/10.1029/2005JC003393, 2007. a
Coon, M. D., Maykut, A., G., Pritchard, R. S., Rothrock, D. A., and Thorndike, A. S.: Modeling The Pack Ice as an Elastic-Plastic Material, AIDJEX Bulletin, 24, 1–106, 1974. a
Cunningham, G., Kwok, R., and Banfield, J.: Ice lead orientation characteristics in the winter Beaufort Sea, in: Proceedings of IGARSS '94 – 1994 IEEE International Geoscience and Remote Sensing Symposium, 3, 1747–1749, https://doi.org/10.1109/IGARSS.1994.399553, 1994. a, b, c
Dansereau, V., Weiss, J., Saramito, P., and Lattes, P.: A Maxwell elasto-brittle rheology for sea ice modelling, The Cryosphere, 10, 1339–1359, https://doi.org/10.5194/tc-10-1339-2016, 2016. a, b, c
Dethloff, K., Rex, M., and Shupe, M.: Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), EGU General Assembly Conference Abstracts, 18, https://ui.adsabs.harvard.edu/#abs/2016EGUGA..18.3064D/abstract, 2016. a
Drucker, D. C. and Prager, W.: Soil mechanics and plastic analysis or limit design, Q. Appl. Math., 10, 157–165, 1952. a
Dumont, D., Gratton, Y., and Arbetter, T. E.: Modeling the Dynamics of the North Water Polynya Ice Bridge, J. Phys. Oceanogr., 39, 1448–1461, https://doi.org/10.1175/2008JPO3965.1, 2009. a
Girard, L., Bouillon, S., Weiss, J., Amitrano, D., Fichefet, T., and Legat, V.: A new modeling framework for sea-ice mechanics based on elasto-brittle rheology, Ann. Glaciol., 52, 123–132, https://doi.org/10.3189/172756411795931499, 2011. a
Golding, N., Schulson, E. M., and Renshaw, C. E.: Shear faulting and localized heating in ice: The influence of confinement, Acta Mater., 58, 5043–5056, https://doi.org/10.1016/j.actamat.2010.05.040, 2010. a
Han, C. and Drescher, A.: Shear Bands in Biaxial Tests on Dry Coarse Sand, Soil and Foundations, 33, 118–132, https://doi.org/10.3208/sandf1972.33.118, 1993. a, b
Handin, J.: On the Coulomb–Mohr failure criterion, Journal of Geophysical Research (1896–1977), 74, 5343–5348, https://doi.org/10.1029/JB074i022p05343, 1969. a
Heorton, H. D. B. S., Feltham, D. L., and Tsamados, M.: Stress and deformation characteristics of sea ice in a high-resolution, anisotropic sea ice model, Philos. T. R. Soc. A, 376, 20170 349, https://doi.org/10.1098/rsta.2017.0349, 2018. a, b
Hibler, W. D.: A viscous sea ice law as a stochastic average of plasticity, J. Geophys. Res., 82, 3932–3938, https://doi.org/10.1029/JC082i027p03932, 1977. a, b, c, d
Hopkins, M. A.: On the ridging of intact lead ice, J. Geophys. Res.-Oceans, 99, 16351–16360, https://doi.org/10.1029/94JC00996, 1994. a
Horvat, C. and Tziperman, E.: The evolution of scaling laws in the sea ice floe size distribution, J. Geophys. Res.-Oceans, 122, 7630–7650, https://doi.org/10.1002/2016JC012573, 2017. a, b
Hutchings, J. K., Heil, P., and Hibler, W. D.: Modeling Linear Kinematic Features in Sea Ice, Mon. Weather Rev., 133, 3481–3497, https://doi.org/10.1175/MWR3045.1, 2005. a, b, c, d
Hutter, N. and Losch, M.: Feature-based comparison of sea ice deformation in lead-permitting sea ice simulations, The Cryosphere, 14, 93–113, https://doi.org/10.5194/tc-14-93-2020, 2020. a, b
Hutter, N., Martin, L., and Dimitris, M.: Scaling Properties of Arctic Sea Ice Deformation in a High-Resolution Viscous-Plastic Sea Ice Model and in Satellite Observations, J. Geophys. Res.-Oceans, 123, 672–687, https://doi.org/10.1002/2017JC013119, 2018. a, b, c, d
Hutter, N., Zampieri, L., and Losch, M.: Leads and ridges in Arctic sea ice from RGPS data and a new tracking algorithm, The Cryosphere, 13, 627–645, https://doi.org/10.5194/tc-13-627-2019, 2019. a, b, c
Ip, C. F.: Numerical investigation of different rheologies on sea-ice dynamics, PhD thesis, Dartmouth College, New Hampshire, United States, 1993. a
Itkin, P., Losch, M., and Gerdes, R.: Landfast ice affects the stability of the Arctic halocline: Evidence from a numerical model, J. Geophys. Res.-Oceans, 120, 2622–2635, https://doi.org/10.1002/2014JC010353, 2015. a
Kaus, B. J. P.: Factors that control the angle of shear bands in geodynamic numerical models of brittle deformation, Tectonophysics, 484, 36–47, https://doi.org/10.1016/j.tecto.2009.08.042, 2010. a
Koldunov, N. V., Danilov, S., Sidorenko, D., Hutter, N., Losch, M., Goessling, H., Rakowsky, N., Scholz, P., Sein, D., Wang, Q., and Jung, T.: Fast EVP Solutions in a High-Resolution Sea Ice Model, J. Adv. Model. Earth Sy., 11, 1269–1284, https://doi.org/10.1029/2018MS001485, 2019. a
Kwok, R.: Deformation of the Arctic Ocean Sea Ice Cover between November 1996 and April 1997: A Qualitative Survey, in: IUTAM Symposium on Scaling Laws in Ice Mechanics and Ice Dynamics, edited by Dempsey, J. P. and Shen, H. H., Solid Mechanics and Its Applications, 315–322, Springer, the Netherlands, Dordrecht, https://doi.org/10.1007/978-94-015-9735-7, 2001. a
König Beatty, C. and Holland, D. M.: Modeling Landfast Sea Ice by Adding Tensile Strength, J. Phys. Oceanogr., 40, 185–198, https://doi.org/10.1175/2009JPO4105.1, 2010. a
Lemieux, J.-F. and Tremblay, B.: Numerical convergence of viscous–plastic sea ice models, J. Geophys. Res.-Oceans, 114, C05009, https://doi.org/10.1029/2008JC005017, 2009. a
Losch, M., Menemenlis, D., Campin, J.-M., Heimbach, P., and Hill, C.: On the formulation of sea-ice models. Part 1: Effects of different solver implementations and parameterizations, Ocean Model., 33, 129–144, https://doi.org/10.1016/j.ocemod.2009.12.008, 2010. a
Losch, M., Fuchs, A., Lemieux, J.-F., and Vanselow, A.: A parallel Jacobian-free Newton–Krylov solver for a coupled sea ice-ocean model, J. Comput. Phys., 257, 901–911, https://doi.org/10.1016/j.jcp.2013.09.026, 2014. a, b
Mancktelow, N. S.: How ductile are ductile shear zones?, GeoScienceWorld, Geology, 34, 345–348, https://doi.org/10.1130/G22260.1, 2006. a
Marko, J. R. and Thomson, R. E.: Rectilinear leads and internal motions in the ice pack of the western Arctic Ocean, J. Geophys. Res., 82, 979–987, https://doi.org/10.1029/JC082i006p00979, 1977. a, b, c
Marshall, J., Adcroft, A., Hill, C., Perelman, L., and Heisey, C.:
A finite-volume, incompressible Navier Stokes model for studies of the ocean on parallel computers, J. Geophys. Res.-Oceans,
102, 5753–5766,
https://doi.org/10.1029/96JC02775, 1997. a
Mohr, O.: Welche Umstände bedingen die Elastizitätsgrenze und den Bruch eines Materials, Zeitschrift des Vereins Deutscher Ingenieure, 46, 1572–1577, 1900. a
Mánica, M. A., Gens, A., Vaunat, J., and Ruiz, D. F.: Nonlocal plasticity modelling of strain localisation in stiff clays, Comput. Geotech., 103, 138–150, https://doi.org/10.1016/j.compgeo.2018.07.008, 2018. a
Nguyen, A. T., Menemenlis, D., and Kwok, R.: Arctic ice-ocean simulation with optimized model parameters: Approach and assessment, J. Geophys. Res.-Oceans, 116, C04 025, https://doi.org/10.1029/2010JC006573, 2011. a
Nguyen, A. T., Kwok, R., and Menemenlis, D.: Source and Pathway of the Western Arctic Upper Halocline in a Data-Constrained Coupled Ocean and Sea Ice Model, American Meteorological Society, J. Phys. Oceanogr., 42, 802–823, https://doi.org/10.1175/JPO-D-11-040.1, 2012. a
Overland, J. E., McNutt, S. L., Salo, S., Groves, J., and Li, S.: Arctic sea ice as a granular plastic, J. Geophys. Res., 103, 21845–21868, https://doi.org/10.1029/98JC01263, 1998. a, b
Plante, M., Tremblay, B., Losch, M., and Lemieux, J.-F.: Landfast sea ice material properties derived from ice bridge simulations using the Maxwell elasto-brittle rheology, The Cryosphere, 14, 2137–2157, https://doi.org/10.5194/tc-14-2137-2020, 2020. a
Rampal, P., Bouillon, S., Ólason, E., and Morlighem, M.: neXtSIM: a new Lagrangian sea ice model, The Cryosphere, 10, 1055–1073, https://doi.org/10.5194/tc-10-1055-2016, 2016. a
Rampal, P., Dansereau, V., Olason, E., Bouillon, S., Williams, T., Korosov, A., and Samaké, A.: On the multi-fractal scaling properties of sea ice deformation, The Cryosphere, 13, 2457–2474, https://doi.org/10.5194/tc-13-2457-2019, 2019. a
Ringeisen, D., Losch, M., Tremblay, L. B., and Hutter, N.: Simulating intersection angles between conjugate faults in sea ice with different viscous–plastic rheologies, The Cryosphere, 13, 1167–1186, https://doi.org/10.5194/tc-13-1167-2019, 2019. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w
Roach, L. A., Horvat, C., Dean, S. M., and Bitz, C. M.: An Emergent Sea Ice Floe Size Distribution in a Global Coupled Ocean-Sea Ice Model, J. Geophys. Res.-Oceans, 123, 4322–4337, https://doi.org/10.1029/2017JC013692, 2018. a
Rothrock, D. A.: The energetics of the plastic deformation of pack ice by ridging, J. Geophys. Res., 80, 4514–4519, https://doi.org/10.1029/JC080i033p04514, 1975. a
Rothrock, D. A. and Thorndike, A. S.: Measuring the sea ice floe size distribution, J. Geophys. Res.-Oceans, 89, 6477–6486, https://doi.org/10.1029/JC089iC04p06477, 1984. a
Schall, P. and van Hecke, M.: Shear Bands in Matter with Granularity, Annu. Rev. Fluid Mech., 42, 67–88, https://doi.org/10.1146/annurev-fluid-121108-145544, 2010. a
Schulson, E. M.: Fracture of Ice on Scales Large and Small, in: IUTAM Symposium on Scaling Laws in Ice Mechanics and Ice Dynamics, edited by: Dempsey, J. P. and Shen, H. H., Solid Mechanics and Its Applications, 161–170, Springer, the Netherlands, 2001. a
Schulson, E. M.: Brittle Failure of Ice, GeoScienceWorld, Rev. Mineral. Geochem., 51, 201–252, https://doi.org/10.2138/gsrmg.51.1.201, 2002. a, b, c
Schulson, E. M. and Hibler, W. D.: Fracture of the winter sea ice cover on the Arctic ocean, C. R. Phys., 5, 753–767, https://doi.org/10.1016/j.crhy.2004.06.001, 2004. a
Schulson, E. M., Fortt, A. L., Iliescu, D., and Renshaw, C. E.: Failure envelope of first-year Arctic sea ice: The role of friction in compressive fracture, John Wiley & Sons, Ltd., J. Geophys. Res.-Oceans, 111, C11S25, https://doi.org/10.1029/2005JC003235, 2006a. a
Schulson, E. M., Fortt, A. L., Iliescu, D., and Renshaw, C. E.: On the role of frictional sliding in the compressive fracture of ice and granite: Terminal vs. post-terminal failure, Acta Mater., 54, 3923–3932, https://doi.org/10.1016/j.actamat.2006.04.024, 2006b. a
Spreen, G., Kwok, R., Menemenlis, D., and Nguyen, A. T.: Sea-ice deformation in a coupled ocean–sea-ice model and in satellite remote sensing data, The Cryosphere, 11, 1553–1573, https://doi.org/10.5194/tc-11-1553-2017, 2017. a
Stern, H. L., Rothrock, D. A., and Kwok, R.: Open water production in Arctic sea ice: Satellite measurements and model parameterizations, John Wiley & Sons, Ltd., J. Geophys. Res.-Oceans, 100, 20601–20612, https://doi.org/10.1029/95JC02306, 1995. a, b, c, d
Stroeve, J., Barrett, A., Serreze, M., and Schweiger, A.: Using records from submarine, aircraft and satellites to evaluate climate model simulations of Arctic sea ice thickness, The Cryosphere, 8, 1839–1854, https://doi.org/10.5194/tc-8-1839-2014, 2014. a
Tsamados, M., Feltham, D. L., and Wilchinsky, A. V.: Impact of a new anisotropic rheology on simulations of Arctic sea ice, J. Geophys. Res.-Oceans, 118, 91–107, https://doi.org/10.1029/2012JC007990, 2013. a, b
Vardoulakis, I.: Shear band inclination and shear modulus of sand in biaxial tests, Int. J. Numer. Anal. Met., 4, 103–119, https://doi.org/10.1002/nag.1610040202, 1980. a
Vardoulakis, I. and Graf, B.: Calibration of constitutive models for granular materials using data from biaxial experiments, ICE Publishing, Géotechnique, 35, 299–317, https://doi.org/10.1680/geot.1985.35.3.299, 1985. a
Vermeer, P. A.: The orientation of shear bands in biaxial tests, Géotechnique, 40, 223–236, https://doi.org/10.1680/geot.1990.40.2.223, 1990. a, b
Wang, K.: Pack ice as a two-dimensional granular plastic: a new constitutive law, Ann. Glaciol., 44, 317–320, https://doi.org/10.3189/172756406781811358, 2006. a
Wang, K.: Observing the yield curve of compacted pack ice, J. Geophys. Res.-Oceans, 112, C05015, https://doi.org/10.1029/2006JC003610, 2007. a
Weiss, J. and Schulson, E. M.: Coulombic faulting from the grain scale to the geophysical scale: lessons from ice, J. Phys. D Appl. Phys., 42, 214 017, https://doi.org/10.1088/0022-3727/42/21/214017, 2009. a, b
Weiss, J., Schulson, E. M., and Stern, H. L.: Sea ice rheology from in-situ, satellite and laboratory observations: Fracture and friction, Earth Planet. Sci. Lett., 255, 1–8, https://doi.org/10.1016/j.epsl.2006.11.033, 2007. a, b
Wilchinsky, A. V., Feltham, D. L., and Hopkins, M. A.: Effect of shear rupture on aggregate scale formation in sea ice, J. Geophys. Res.-Oceans, 115, C10 002, https://doi.org/10.1029/2009JC006043, 2010. a
Williams, J., Tremblay, L. B., and Lemieux, J.-F.: The effects of plastic waves on the numerical convergence of the viscous–plastic and elastic–viscous–plastic sea-ice models, J. Comput. Phys., 340, 519–533, https://doi.org/10.1016/j.jcp.2017.03.048, 2017. a
Zhang, J. and Hibler, W. D.: On an efficient numerical method for modeling sea ice dynamics, J. Geophys. Res.-Oceans, 102, 8691–8702, https://doi.org/10.1029/96JC03744, 1997. a
Zhang, J. and Rothrock, D. A.: Effect of sea ice rheology in numerical investigations of climate, J. Geophys. Res.-Oceans, 110, C08 014, https://doi.org/10.1029/2004JC002599, 2005. a, b, c
Download
The requested paper has a corresponding corrigendum published. Please read the corrigendum first before downloading the article.
- Article
(2000 KB) - Full-text XML
Short summary
Deformations in the Arctic sea ice cover take the shape of narrow lines. High-resolution sea ice models recreate these deformation lines. Recent studies have shown that the most widely used sea ice model creates fracture lines with intersection angles larger than those observed and cannot create smaller angles. In our work, we change the way sea ice deforms post-fracture. This change allows us to understand the link between the sea ice model and intersection angles and create more acute angles.
Deformations in the Arctic sea ice cover take the shape of narrow lines. High-resolution sea ice...
