Articles | Volume 11, issue 5
https://doi.org/10.5194/tc-11-2117-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/tc-11-2117-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Wave–ice interactions in the neXtSIM sea-ice model
Timothy D. Williams
CORRESPONDING AUTHOR
Nansen Environmental and Remote Sensing Center, Thormøhlensgate 47, N5006, Bergen, Norway and the Bjerknes Center for Climate Research, Bergen, Norway
Pierre Rampal
Nansen Environmental and Remote Sensing Center, Thormøhlensgate 47, N5006, Bergen, Norway and the Bjerknes Center for Climate Research, Bergen, Norway
Sylvain Bouillon
Nansen Environmental and Remote Sensing Center, Thormøhlensgate 47, N5006, Bergen, Norway and the Bjerknes Center for Climate Research, Bergen, Norway
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Fabien Salmon, Pierre Rampal, Stéphanie Leroux, Timothy Williams, Einar Ólason, and Nicolas Barral
EGUsphere, https://doi.org/10.5194/egusphere-2026-1869, https://doi.org/10.5194/egusphere-2026-1869, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Accurate modeling of sea ice dynamics is a major challenge for forecasting its future evolution and assessing its impact on climate change. This paper presents the parallelisation of state-of-the art sea-ice dynamics model NeXtSIM. The code was interfaced with a new parallel version of the remeshing library MMG. Validation and performance of the code are discussed. Simulations with a uniform 1km spatial resolution are run, which is unprecedented with this kind of lagrangian sea-ice models.
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This paper introduces a new version of the neXtSIM sea-ice model. NeXtSIM is unique among sea-ice models in how it represents sea-ice dynamics, focusing on features such as cracks and ridges and how these impact interactions between the atmosphere and ocean where sea ice is present. The new version introduces some physical parameterisations and model options detailed and explained in the paper. Following the paper's publication, the neXtSIM code will be released publicly for the first time.
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It is possible to compute sea ice motion from satellite observations and detect areas where ice converges (moves together), forms ice ridges or diverges (moves apart) and opens leads. However, it is difficult to predict the exact motion of sea ice and position of ice ridges or leads using numerical models. We propose a new method to initialise a numerical model from satellite observations to improve the accuracy of the forecasted position of leads and ridges for safer navigation.
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The Cryosphere, 15, 3207–3227, https://doi.org/10.5194/tc-15-3207-2021, https://doi.org/10.5194/tc-15-3207-2021, 2021
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neXtSIM (neXt-generation Sea Ice Model) includes a novel and extremely realistic way of modelling sea ice dynamics – i.e. how the sea ice moves and deforms in response to the drag from winds and ocean currents. It has been developed over the last few years for a variety of applications, but this paper represents its first demonstration in a forecast context. We present results for the time period from November 2018 to June 2020 and show that it agrees well with satellite observations.
Fabien Salmon, Pierre Rampal, Stéphanie Leroux, Timothy Williams, Einar Ólason, and Nicolas Barral
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Accurate modeling of sea ice dynamics is a major challenge for forecasting its future evolution and assessing its impact on climate change. This paper presents the parallelisation of state-of-the art sea-ice dynamics model NeXtSIM. The code was interfaced with a new parallel version of the remeshing library MMG. Validation and performance of the code are discussed. Simulations with a uniform 1km spatial resolution are run, which is unprecedented with this kind of lagrangian sea-ice models.
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EGUsphere, https://doi.org/10.5194/egusphere-2025-6379, https://doi.org/10.5194/egusphere-2025-6379, 2026
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We examine how uncertainty in the initial position of sea ice features (leads, ridges), affects daily-to-weekly winter sea-ice forecasts. Using ensemble simulations with a sea ice–ocean model, we compare two formulations of sea ice mechanics. We show that pack-ice dynamics are highly sensitive to this choice: one formulation strongly amplifies small initial errors, while the other damps them. Our results highlight the need for ensemble forecasts to capture uncertainty and risks in the Arctic.
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EGUsphere, https://doi.org/10.5194/egusphere-2024-3521, https://doi.org/10.5194/egusphere-2024-3521, 2025
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This paper introduces a new version of the neXtSIM sea-ice model. NeXtSIM is unique among sea-ice models in how it represents sea-ice dynamics, focusing on features such as cracks and ridges and how these impact interactions between the atmosphere and ocean where sea ice is present. The new version introduces some physical parameterisations and model options detailed and explained in the paper. Following the paper's publication, the neXtSIM code will be released publicly for the first time.
Rémy Lapere, Louis Marelle, Pierre Rampal, Laurent Brodeau, Christian Melsheimer, Gunnar Spreen, and Jennie L. Thomas
Atmos. Chem. Phys., 24, 12107–12132, https://doi.org/10.5194/acp-24-12107-2024, https://doi.org/10.5194/acp-24-12107-2024, 2024
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Elongated open-water areas in sea ice, called leads, can release marine aerosols into the atmosphere. In the Arctic, this source of atmospheric particles could play an important role for climate. However, the amount, seasonality and spatial distribution of such emissions are all mostly unknown. Here, we propose a first parameterization for sea spray aerosols emitted through leads in sea ice and quantify their impact on aerosol populations in the high Arctic.
Laurent Brodeau, Pierre Rampal, Einar Ólason, and Véronique Dansereau
Geosci. Model Dev., 17, 6051–6082, https://doi.org/10.5194/gmd-17-6051-2024, https://doi.org/10.5194/gmd-17-6051-2024, 2024
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A new brittle sea ice rheology, BBM, has been implemented into the sea ice component of NEMO. We describe how a new spatial discretization framework was introduced to achieve this. A set of idealized and realistic ocean and sea ice simulations of the Arctic have been performed using BBM and the standard viscous–plastic rheology of NEMO. When compared to satellite data, our simulations show that our implementation of BBM leads to a fairly good representation of sea ice deformations.
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
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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.
Anton Korosov, Pierre Rampal, Yue Ying, Einar Ólason, and Timothy Williams
The Cryosphere, 17, 4223–4240, https://doi.org/10.5194/tc-17-4223-2023, https://doi.org/10.5194/tc-17-4223-2023, 2023
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It is possible to compute sea ice motion from satellite observations and detect areas where ice converges (moves together), forms ice ridges or diverges (moves apart) and opens leads. However, it is difficult to predict the exact motion of sea ice and position of ice ridges or leads using numerical models. We propose a new method to initialise a numerical model from satellite observations to improve the accuracy of the forecasted position of leads and ridges for safer navigation.
Heather Regan, Pierre Rampal, Einar Ólason, Guillaume Boutin, and Anton Korosov
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Multiyear ice (MYI), sea ice that survives the summer, is more resistant to changes than younger ice in the Arctic, so it is a good indicator of sea ice resilience. We use a model with a new way of tracking MYI to assess the contribution of different processes affecting MYI. We find two important years for MYI decline: 2007, when dynamics are important, and 2012, when melt is important. These affect MYI volume and area in different ways, which is important for the interpretation of observations.
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This work studies a novel application of combining a Lagrangian sea ice model, neXtSIM, and data assimilation. It uses a deterministic ensemble Kalman filter to incorporate satellite-observed ice concentration and thickness in simulations. The neXtSIM Lagrangian nature is handled using a remapping strategy on a common homogeneous mesh. The ensemble is formed by perturbing air–ocean boundary conditions and ice cohesion. Thanks to data assimilation, winter Arctic sea ice forecasting is enhanced.
Guillaume Boutin, Einar Ólason, Pierre Rampal, Heather Regan, Camille Lique, Claude Talandier, Laurent Brodeau, and Robert Ricker
The Cryosphere, 17, 617–638, https://doi.org/10.5194/tc-17-617-2023, https://doi.org/10.5194/tc-17-617-2023, 2023
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Sea ice cover in the Arctic is full of cracks, which we call leads. We suspect that these leads play a role for atmosphere–ocean interactions in polar regions, but their importance remains challenging to estimate. We use a new ocean–sea ice model with an original way of representing sea ice dynamics to estimate their impact on winter sea ice production. This model successfully represents sea ice evolution from 2000 to 2018, and we find that about 30 % of ice production takes place in leads.
Timothy Williams, Anton Korosov, Pierre Rampal, and Einar Ólason
The Cryosphere, 15, 3207–3227, https://doi.org/10.5194/tc-15-3207-2021, https://doi.org/10.5194/tc-15-3207-2021, 2021
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neXtSIM (neXt-generation Sea Ice Model) includes a novel and extremely realistic way of modelling sea ice dynamics – i.e. how the sea ice moves and deforms in response to the drag from winds and ocean currents. It has been developed over the last few years for a variety of applications, but this paper represents its first demonstration in a forecast context. We present results for the time period from November 2018 to June 2020 and show that it agrees well with satellite observations.
Marcel Kleinherenbrink, Anton Korosov, Thomas Newman, Andreas Theodosiou, Alexander S. Komarov, Yuanhao Li, Gert Mulder, Pierre Rampal, Julienne Stroeve, and Paco Lopez-Dekker
The Cryosphere, 15, 3101–3118, https://doi.org/10.5194/tc-15-3101-2021, https://doi.org/10.5194/tc-15-3101-2021, 2021
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Harmony is one of the Earth Explorer 10 candidates that has the chance of being selected for launch in 2028. The mission consists of two satellites that fly in formation with Sentinel-1D, which carries a side-looking radar system. By receiving Sentinel-1's signals reflected from the surface, Harmony is able to observe instantaneous elevation and two-dimensional velocity at the surface. As such, Harmony's data allow the retrieval of sea-ice drift and wave spectra in sea-ice-covered regions.
Cited articles
Ardhuin, F., Sutherland, P., Doble, M., and Wadhams, P.: Ocean waves across the Arctic: Attenuation due to dissipation dominates over scattering for periods longer than 19s., Geophys. Res. Lett., 43, 5775–5783, https://doi.org/10.1002/2016GL068204, 2016.
Ardhuin, F., Stopa, J., Chapron, B., Collard, F., Smith, M., Thomson, J., Doble, M., Blomquist, B., Persson, O., Collins, III, C. O., and Wadhams, P.: Measuring ocean waves in sea ice using SAR imagery: A quasi-deterministic approach evaluated with Sentinel-1 and in situ data, Remote Sens. Environ., 189, 211–222, https://doi.org/10.1016/j.rse.2016.11.024, 2017.
Bagnold, R. A.: Experiments on a gravity-free dispersion of large solid spheres in a newtonian fluid under shear, Proc. R. Soc. A, 225, 49–63, https://doi.org/10.1098/rspa.1954.0186, 1954.
Bennetts, L. G. and Squire, V. A.: On the calculation of an attenuation coefficient for transects of ice-covered ocean, Proc. Roy. Soc. Lond. A, 468, 136–162, https://doi.org/10.1098/rspa.2011.0155, 2012.
Bennetts, L. G., O'Farrell, S., and Uotila, P.: Brief communication: Impacts of ocean-wave-induced breakup of Antarctic sea ice via thermodynamics in a stand-alone version of the CICE sea-ice model, The Cryosphere, 11, 1035–1040, https://doi.org/10.5194/tc-11-1035-2017, 2017.
Bouillon, S. and Rampal, P.: Presentation of the dynamical core of neXtSIM, a new sea ice model, Ocean Model., 91, 23–37, https://doi.org/10.1016/j.ocemod.2015.04.005, 2015a.
Bouillon, S. and Rampal, P.: On producing sea ice deformation data sets from SAR-derived sea ice motion, The Cryosphere, 9, 663–673, https://doi.org/10.5194/tc-9-663-2015, 2015b.
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.
Doble, M. J. and Bidlot, J.-R.: Wavebuoy measurements at the Antarctic sea ice edge compared with an enhanced ECMWF WAM: progress towards global waves-in-ice modeling, Ocean Model., 70, 166–173, https://doi.org/10.1016/j.ocemod.2013.05.012, 2013.
Dumont, D., Kohout, A. L., and Bertino, L.: A wave-based model for the marginal ice zone including a floe breaking parameterization, J. Geophys. Res., 116, 1–12, https://doi.org/10.1029/2010JC006682, 2011.
Feltham, D. L.: Granular flow in the marginal ice zone, Philos. T. R. Soc. A, 363, 1677–1700, 2005.
Frederking, R. M. W. and Svec, O. J.: Stress-relieving techniques for cantilever beam tests in an ice cover, Cold Reg. Sci. Technol., 11, 247–255, 1985.
Fung, Y.: Foundations of Solid Mechanics, Prentice-Hall Inc, Englewood Cliffs, New Jersey, 1965.
Guo, T. and Campbell, C. S.: An experimental study of the elastic theory for granular flows, Phys. Fluids, 28, 083303, https://doi.org/10.1063/1.4961096, 2016.
Herman, A.: Sea-ice floe-size distribution in the context of spontaneous scaling emergence in stochastic systems, Phys. Rev. E, 81, 066123, https://doi.org/10.1103/PhysRevE.81.066123, 2010.
Herman, A.: Influence of ice concentration and floe-size distribution on cluster formation in sea-ice floes, Cent. Eur. J. Phys., 10, 715–722, https://doi.org/10.2478/s11534-012-0071-6, 2012.
Herman, A.: Shear-Jamming in two-dimensional granular materials with power-law grain-size distribution, Entropy, 15, 4802–4821, https://doi.org/10.3390/e15114802, 2013.
Herman, A.: Discrete-Element bonded-particle Sea Ice model DESIgn, version 1.3a – model description and implementation, Geosci. Model Dev., 9, 1219–1241, https://doi.org/10.5194/gmd-9-1219-2016, 2016.
Hibler, III, W. D. and Leppäranta, M.: MIZEX 83 mesoscale sea ice dynamics: initial analysis, in: MIZEX: Bull. IV, U.S. Army Cold Reg. Res. and Eng. Lab., 1984.
Horvat, C. and Tziperman, E.: A prognostic model of the sea-ice floe size and thickness distribution, The Cryosphere, 9, 2119–2134, https://doi.org/10.5194/tc-9-2119-2015, 2015.
Horvat, C., Tziperman, E., and Campin, J.-M.: Interaction of sea ice floe size, ocean eddies, and sea ice melting, Geophys. Res. Lett., 43, 8083–8090, https://doi.org/10.1002/2016GL069742, 2016.
Karulina, M., Karulin, E., and Marchenko, A. V.: Field investigations of first year ice mechanical properties in north-west Barents Sea, in: Proceedings of the 22nd International Conference on Port and Ocean Engineering under Arctic Conditions, June 9–13, 2013, Espoo, Finland, 2013.
Kohout, A. L. and Meylan, M. H.: An elastic plate model for wave attenuation and ice floe breaking in the marginal ice zone, J. Geophys. Res., 113, C09016, https://doi.org/10.1029/2007JC004434, 2008.
Kohout, A. L., Williams, M. J. M., Dean, S. M., and Meylan, M. H.: Storm-induced sea-ice breakup and the implications for ice extent, Nature, 509, 604–607, https://doi.org/10.1038/nature13262, 2014.
Kwok, R.: Deformation of the Arctic Ocean sea ice cover: November 1996 through April 1997, in: Scaling Laws in Ice Mechanics and Dynamics, edited by: Dempsey, J. and Shen, H. H., Kluwer Academic Publishers, 315–323, 2001.
Langhorne, P. J., Squire, V. A., Fox, C., and Haskell, T. G.: Break-up of sea ice by ocean waves, Ann. Glaciol., 27, 438–442, 1998.
Langhorne, P. J., Squire, V. A., Fox, C., and Haskell, T. G.: Lifetime estimation for a land-fast ice sheet subjected to ocean swell, Ann. Glaciol., 33, 333–338, 2001.
Li, J., Kohout, A. L., and Shen, H. H.: Comparison of wave propagation through ice covers in calm and storm conditions, Geophys. Res. Lett., 42, 5935–5941, https://doi.org/10.1002/2015GL064715, 2015.
Marchenko, A. V., Morozov, E. G., and Muzylev, S. V.: Measurements of sea ice bending stiffness by pressure characteristics of flexural-gravity waves, Ann. Glaciol., 54, 51–60, 2013.
Marchenko, A. V., Karulin, E., Chistyakov, P., Sodhi, D., Karulina, M., and Sakharov, A.: Three Dimensional Fracture Effects in Tests with Cantilever and Fixed Ends Beams, in: 22nd IAHR International Symposium on Ice, Singapore, 249–256, 2014.
Marchenko, A. V., Karulina, M., Karulin, E., Chistyakov, P., and Sakharov, A.: Flexural strength of ice reconstructed from field tests with cantilever beams and laboratory tests with beams and disks, in: Proceedings of the 24th International Conference on Port and Ocean Engineering under Arctic Conditions, Busan, Korea, 2017.
Masson, D. and LeBlond, P. H.: Spectral Evolution of Wind-Generated Surface Gravity Waves in a Dispersed Ice Field, J. Fluid Mech., 202, 111–136, 1989.
Meier, W. N.: Losing Arctic sea ice: Observations of the recent decline and the long-term context, in: Sea Ice, edited by: Thomas, D. N., John Wiley & Sons, 3 edn., chap. 11, 290–303, 2017.
Meylan, M., Squire, V., and Fox, C.: Toward realism in modelling ocean wave behaviour in marginal ice zones, J. Geophys. Res.-Oceans, 102, 22981–22991, 1997.
Meylan, M. H., Bennetts, L. G., and Kohout, A. L.: In-situ measurements and analysis of ocean waves in the Antarctic marginal ice zone, Geophys. Res. Lett., 41, 5046–5051, 2014.
Perrie, W. and Hu, Y.: Air–Ice–Ocean Momentum Exchange. Part 1: Energy Transfer between Waves and Ice Floes, J. of Phys. Ocean., 26, 1705–1720, 1996.
Phillips, O. M.: The Dynamics of the Upper Ocean, Cambridge University Press, New York, 2nd edn., 1977.
Rabatel, M., Labbé, S., and Weiss, J.: Dynamics of an assembly of rigid ice floes, J. Geophys. Res.-Oceans, 120, 5887–5909, https://doi.org/10.1002/2015JC010909, 2015.
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.
Robinson, N. J. and Palmer, S. C.: A Modal Analysis of a Rectangular Plate Floating on an Incompressible Fluid, J. Sound Vib., 142, 453–460, 1990.
Rynders, S., Aksenov, Y., Feltham, D. L., Nurser, A. J. G., and Naveira Garabato, A. C.: Modelling MIZ dynamics in a global model, in: EGU General Assembly Conference Abstracts, vol. 18, p. 1004, April, 2016.
Schulson, E. M.: Fracture of Ice and other Coulombic Materials, in: Mechanics of Natural Solids, edited by: Kolymbas, D. and Viggiani, G., Springer-Verlag Berlin Heidelberg, 177–202, 2009.
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, J. Geophys. Res.-Oceans: Oceans, 111, c11S25, https://doi.org/10.1029/2005JC003235, 2006.
Shen, H. H., Hibler, W. D., and Leppäranta, M.: On Applying Granular Flow Theory to a Deforming Broken Ice Field, Acta Mech., 63, 143–160, 1986.
Shen, H. H., Hibler, W. D., and Leppäranta, M.: The role of floe collisions in sea ice rheology, J. Geophys. Res., 92, 7085–7096, 1987.
Steele, M.: Sea Ice Melting and Floe Geometry in a Simple Ice-Ocean Model, J. Geophys. Res., 97, 17729–17738, 1992.
Stephenson, S. R., Smith, L. C., and Agnew, J. A.: Divergent long-term trajectories of human access to the Arctic, Nature Climate Change, 1, 156–160, https://doi.org/10.1038/NCLIMATE1120, 2011.
Suzuki, N. and Fox-Kemper, B.: Understanding Stokes forces in the wave-averaged equations, J. Geophys. Res.-Oceans, 121, 3579–3596, https://doi.org/10.1002/2015JC011566, 2016.
Suzuki, N., Fox-Kemper, B., Hamlington, P. E., and Van Roekel, L. P.: Surface waves affect frontogenesis, J. Geophys. Res.-Oceans, 121, 3597–3624, https://doi.org/10.1002/2015JC011563, 2016.
Thomson, J. and Rogers, W. E.: Swell and sea in the emerging Arctic Ocean, Geophys. Res. Lett., 41, 3136–3140, https://doi.org/10.1002/2014GL059983, 2014.
Thorndike, A. S., Rothrock, D. A., Maykut, G. A., and Colony, R.: The thickness distribution of sea ice, J. Geophys. Res., 80, 4501–4513, https://doi.org/10.1029/JC080i033p04501, 1975.
Timco, G. W. and Weeks, W. F.: A review of the engineering properties of sea ice, Cold Reg. Sci. Technol., 60, 107–129, 2010.
Tolman, H. L. and the WAVEWATCH III Development Group: User manual and system documentation of WAVEWATCH III version 5.16, Tech. Rep. 329, Environmental Modeling Center, Marine Modeling and Analysis Branch, 2016.
Toyota, T., Haas, C., and Tamura, T.: Size distribution and shape properties of relatively small sea-ice floes in the Antarctic marginal ice zone in late winter, Deep-Sea Res. Pt. II, 58, 1182–1193, 2011.
Wadhams, P.: Attenuation of Swell by Sea Ice, J. Geophys. Res., 78, 3552–3563, 1973.
Wang, R. and Shen, H. H.: Gravity waves propagating into an ice-covered ocean: A viscoelastic model, J. Geophys. Res., 115, C06024, https://doi.org/10.1029/2009JC005591, 2010.
Weiss, J.: Drift, Deformation and Fracture of Sea Ice – A perspective across scales, Springer, 2013.
Weiss, J., Schulson, E. M., and Stern, H.: Sea ice rheology from in-situ, satellite and laboratory observations: Fracture and friction, Earth Planet. Sc. Lett., 255, 1–8, https://doi.org/10.1016/j.epsl.2006.11.033, 2007.
Williams, T. D., Bennetts, L. G., Squire, V. A., Dumont, D., and Bertino, L.: Wave-ice interactions in the marginal ice zone. Part 1: Theoretical foundations, Ocean Model., 71, 81–91, https://doi.org/10.1016/j.ocemod.2013.05.010, 2013a.
Williams, T. D., Bennetts, L. G., Squire, V. A., Dumont, D., and Bertino, L.: Wave-ice interactions in the marginal ice zone. Part 2: Numerical implementation and sensitivity studies along 1D transects of the ocean surface, Ocean Model., 71, 92–101, https://doi.org/10.1016/j.ocemod.2013.05.011, 2013b.
Zhang, J., Stern, H., Hwang, B., Schweiger, A., and Steele, M.: Modeling the seasonal evolution of the Arctic sea ice floe size distribution., Elem. Sci. Anth., 4, https://doi.org/10.12952/journal.elementa.000126, 2016.
Zhao, X. and Shen, H.: A diffusion approximation for ocean wave scatterings by randomly distributed ice floes, Ocean Model., 107, 21–27, https://doi.org/10.1016/j.ocemod.2016.09.014, 2016.
Short summary
As the Arctic sea ice extent drops, more ship traffic seeks to take advantage of this, and a need for better wave and sea ice forecasts arises. One aspect of this is the location of the sea ice edge. The waves here can be quite large, but they die away as they travel into the ice. This causes momentum to be transferred from the waves to the ice, causing ice drift. However, our study found that the effect of the wind drag had more impact on the ice edge position than the waves.
As the Arctic sea ice extent drops, more ship traffic seeks to take advantage of this, and a...