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
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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
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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...
