The elastic–viscous–plastic method revisited

Bouillon, Sylvain; Fichefet, Thierry; Legat, Vincent; Madec, Gurvan

doi:10.1016/j.ocemod.2013.05.013

Cited by 99 publications

(108 citation statements)

References 30 publications

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“…LIM3 mostly differs from other multicategory models in terms of parameterizations and implementation details. The new features of LIM3 are mainly multiple ice categories to represent the sub-grid-scale ice thickness distribution (Thorndike et al, 1975), multi-layer halothermodynamics including brine dynamics and their impact on thermal properties and ice-ocean salt exchanges ( Vancoppenolle et al, 2009b) and a C-grid formulation (Bouillon et al, 2009) for ice dynamics using the modified elasticviscous-plastic (EVP) rheology (Bouillon et al, 2013), instead of the more computationally expensive VP rheology (Hibler III, 1979).…”

Section: Model Descriptionmentioning

confidence: 99%

“…The external stress terms are multiplied by concentration to satisfy free drift at low concentration (Connolley et al, 2004). The stress tensor σ is computed using the C-grid EVP formulation of Bouillon et al (2009Bouillon et al ( , 2013. EVP (Hunke and Dukowicz, 1997) regularises the original VP approach (Hibler III, 1979).…”

Section: Momentum Equationmentioning

confidence: 99%

“…By introducing artificial damped elastic waves and a time-dependence to the stress tensor, the EVP method enables an explicit resolution of the momentum equation with a reasonable number of sub-time steps (∼ 100) and easy implementation on parallel architectures. However, EVP has to be used carefully since even the modified EVP of Bouillon et al (2013) hardly converges to the VP solution unless a very large number (> 500) of iterations is used (Kimmritz et al, 2015).…”

Section: Momentum Equationmentioning

confidence: 99%

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The Louvain-La-Neuve sea ice model LIM3.6: global and regional capabilities

et al. 2015

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Abstract. The new 3.6 version of the Louvain-la-Neuve sea ice model (LIM) is presented, as integrated in the most recent stable release of Nucleus for European Modelling of the Ocean (NEMO) (3.6). The release will be used for the next Climate Model Inter-comparison Project (CMIP6). Developments focussed around three axes: improvements of robustness, versatility and sophistication of the code, which involved numerous changes. Robustness was improved by enforcing exact conservation through the inspection of the different processes driving the air-ice-ocean exchanges of heat, mass and salt. Versatility was enhanced by implementing lateral boundary conditions for sea ice and more flexible ice thickness categories. The latter includes a more practical computation of category boundaries, parameterizations to use LIM3.6 with a single ice category and a flux redistributor for coupling with atmospheric models that cannot handle multiple sub-grid fluxes. Sophistication was upgraded by including the effect of ice and snow weight on the sea surface. We illustrate some of the new capabilities of the code in two standard simulations. One is an ORCA2-LIM3 global simulation at a nominal 2 • resolution, forced by reference atmospheric climatologies. The other one is a regional simulation at 2 km resolution around the Svalbard Archipelago in the Arctic Ocean, with open boundaries and tides. We show that the LIM3.6 forms a solid and flexible base for future scientific studies and model developments.

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Section: Model Descriptionmentioning

confidence: 99%

Section: Momentum Equationmentioning

confidence: 99%

Section: Momentum Equationmentioning

confidence: 99%

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The Louvain-La-Neuve sea ice model LIM3.6: global and regional capabilities

et al. 2015

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“…It features a single sea-ice category and open water represented using ice concentration; the Semtner (1976) three-layer thermodynamics with a virtual reservoir of shortwave radiation heat, which parameterises brine inclusions, the revisited C-grid elastic-viscous-plastic rheology of Bouillon et al (2013) and the second-order moment-conserving advection scheme of Prather (1986), plus a few extra parameterisations. LIM2 implements the snow-ice formation by infiltration and freezing of seawater into snow when deep enough.…”

Section: Nemo Sea-ice Components Lim2 and Lim3mentioning

confidence: 99%

Comparing sea ice, hydrography and circulation between NEMO3.6 LIM3 and LIM2

et al. 2017

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Abstract. A set of hindcast simulations with the new version 3.6 of the Nucleus for European Modelling of the Ocean (NEMO) ocean-ice model in the ORCA1 configuration and forced by the DRAKKAR Forcing Set version 5.2 (DFS5.2) atmospheric data was performed from 1958 to 2012. Simulations differed in their sea-ice component: the old standard version Louvain-la-Neuve Sea Ice Model (LIM2) and its successor LIM3. Main differences between these sea-ice models are the parameterisations of sub-grid-scale sea-ice thickness distribution, ice deformation, thermodynamic processes, and sea-ice salinity. Our main objective was to analyse the response of the ocean-ice system sensitivity to the change in sea-ice physics. Additional sensitivity simulations were carried out for the attribution of observed differences between the two main simulations.In the Arctic, NEMO-LIM3 compares better with observations by realistically reproducing the sea-ice extent decline during the last few decades due to its multi-category sea-ice thickness. In the Antarctic, NEMO-LIM3 more realistically simulates the seasonal evolution of sea-ice extent than NEMO-LIM2. In terms of oceanic properties, improvements are not as evident, although NEMO-LIM3 reproduces a more realistic hydrography in the Labrador Sea and in the Arctic Ocean, including a reduced cold temperature bias of the Arctic Intermediate Water at 250 m. In the extra-polar regions, the oceanographic conditions of the two NEMO-LIM versions remain relatively similar, although they slowly drift apart over decades. This drift is probably due to a stronger deep water formation around Antarctica in LIM3.

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“…Interior sectors exhibit errors in ice drift (speed and direction) that are not simply linked to model-reanalysis or inter-model wind differences. The sea ice cover is packed there and undergoes large mechanical produce different sea ice dynamic responses to a forcing on a daily timescale (Hunke and Dukowicz, 1997;Hunke and Zhang, 1999;Bouillon et al, 2013). Therefore, the sea ice motion in response to the wind forcing in these regions is affected by the rheologies used for sea ice and expectedly displays more complex 450 drift error patterns than just those potentially induced by winds.…”

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confidence: 99%

Impact of surface wind biases on the Antarctic sea ice concentration budget in climate models

et al. 2016

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Highlights• The ice concentration budget (ICB) is applied to several forced and coupled models.• Ice drift and 10 m wind vectors are evaluated against observations and reanalyses.• Biases in winds are largely responsible for biases in the ICB in free drift regions.• Errors in winds and sea ice model physics are equally important closer to the coast.• The method provides a new tool for climate model intercomparisons. AbstractWe derive the terms in the Antarctic sea ice concentration budget from the output of three models, and compare them to observations of the same terms. Those models include two climate models from the 5th Coupled Model Intercomparison Project (CMIP5) and one ocean-sea ice coupled model with prescribed atmospheric forcing. Sea ice drift and wind fields from those models, in average over April-October 1992-2005, all exhibit large differences with the available observational or reanalysis datasets. However, the discrepancies between the two distinct ice drift products or the two wind reanalyses used here are sometimes even greater than those differences. Two major findings stand out from the analysis. Firstly, large biases in sea ice drift speed and direction in exterior sectors of the sea ice covered region tend to be systematic and consistent with those in winds. This suggests that sea ice errors in these areas are most likely wind-driven, so as errors in the simulated ice motion vectors. The systematic nature of these biases is less prominent in interior sectors, nearer the coast, where sea ice is mechanically constrained and its motion in response to the wind forcing more depending on the model rheology. Second, the intimate relationship between winds, sea ice drift and the sea ice concentration budget gives insight on ways to categorize models with regard to errors in their ice dynamics. In exterior regions, models with seemingly too weak winds and slow ice drift consistently yield a lack of ice velocity divergence and hence a wrong wintertime sea ice growth rate. In interior sectors, too slow ice drift, presumably originating from issues in the physical representation of sea ice dynamics as much as from errors in surface winds, leads to wrong timing of the late winter ice retreat. Those results illustrate that the applied methodology provides a valuable tool for prioritizing model improvements based on the ice concentration budget-ice * Corresponding author

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The elastic–viscous–plastic method revisited

Cited by 99 publications

References 30 publications

The Louvain-La-Neuve sea ice model LIM3.6: global and regional capabilities

The Louvain-La-Neuve sea ice model LIM3.6: global and regional capabilities

Comparing sea ice, hydrography and circulation between NEMO3.6 LIM3 and LIM2

Impact of surface wind biases on the Antarctic sea ice concentration budget in climate models

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