Impact of a new anisotropic rheology on simulations of Arctic sea ice

Tsamados, Michel; Feltham, D. L.; Wilchinsky, Alexander V.

doi:10.1029/2012jc007990

Cited by 105 publications

(83 citation statements)

References 49 publications

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“…Additionally, promising advances in the parametrization of form drag (Tsamados et al, 2014) of air-ice, sea-ice and rheology (Tsamados et al, 2013) need to be implemented and tested, although for the latter it is not clear how beneficial this new rheology can be at high resolution -which is true of any existing rheology for that matter. The two latter advances are already available in CICE5 (Turner and Hunke, 2015).…”

Section: Discussionmentioning

confidence: 99%

A high-resolution ocean and sea-ice modelling system for the Arctic and North Atlantic oceans

et al. 2015

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Abstract. As part of the CONCEPTS (Canadian Operational Network of Coupled Environmental PredicTion Systems) initiative, a high-resolution (1/12 • ) ice-ocean regional model is developed covering the North Atlantic and the Arctic oceans. The long-term objective is to provide Canada with short-term ice-ocean predictions and hazard warnings in ice-infested regions. To evaluate the modelling component (as opposed to the analysis -or data-assimilation -component, which is not covered in this contribution), a series of hindcasts for the period 2003-2009 is carried out, forced at the surface by the Canadian GDPS reforecasts (Smith et al., 2014). These hindcasts test how the model represents upper ocean characteristics and ice cover. Each hindcast implements a new aspect of the modelling or the ice-ocean coupling. Notably, the coupling to the multi-category ice model CICE is tested. The hindcast solutions are then assessed using a verification package under development, including in situ and satellite ice and ocean observations. The conclusions are as follows: (1) the model reproduces reasonably well the time mean, variance and skewness of sea surface height; (2) the model biases in temperature and salinity show that while the mean properties follow expectations, the Pacific Water signature in the Beaufort Sea is weaker than observed; (3) the modelled freshwater content of the Arctic agrees well with observational estimates; (4) the distribution and volume of the sea ice are shown to be improved in the latest hindcast due to modifications to the drag coefficients and to some degree to the ice thickness distribution available in CICE; (5) nonetheless, the model still overestimates the ice drift and ice thickness in the Beaufort Gyre.

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Section: Discussionmentioning

confidence: 99%

A high-resolution ocean and sea-ice modelling system for the Arctic and North Atlantic oceans

et al. 2015

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“…Lemieux et al, 2010;Kimmritz et al, 2015), different rheologies (e.g. Tremblay and Mysak, 1997;Hopkins, 2004;Schreyer et al, 2006;Wilchinsky and Feltham, 2006;Sulsky et al, 2007;Girard et al, 2011;Tsamados et al, 2013;Herman, 2016;Rabatel et al, 2015;Dansereau et al, 2016), and wind and/or ocean drag parameterisations (e.g. Lu et al, 2011;Lüpkes et al, 2012;Tsamados et al, 2014).…”

Section: P Rampal Et Al: Nextsim: a New Lagrangian Sea Ice Modelmentioning

confidence: 99%

neXtSIM: a new Lagrangian sea ice model

et al. 2016

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Abstract. The Arctic sea ice cover has changed drastically over the last decades. Associated with these changes is a shift in dynamical regime seen by an increase of extreme fracturing events and an acceleration of sea ice drift. The highly non-linear dynamical response of sea ice to external forcing makes modelling these changes and the future evolution of Arctic sea ice a challenge for current models. It is, however, increasingly important that this challenge be better met, both because of the important role of sea ice in the climate system and because of the steady increase of industrial operations in the Arctic. In this paper we present a new dynamical/thermodynamical sea ice model called neXtSIM that is designed to address this challenge. neXtSIM is a continuous and fully Lagrangian model, whose momentum equation is discretised with the finite-element method. In this model, sea ice physics are driven by the combination of two core components: a model for sea ice dynamics built on a mechanical framework using an elasto-brittle rheology, and a model for sea ice thermodynamics providing damage healing for the mechanical framework. The evaluation of the model performance for the Arctic is presented for the period September 2007 to October 2008 and shows that observed multiscale statistical properties of sea ice drift and deformation are well captured as well as the seasonal cycles of ice volume, area, and extent. These results show that neXtSIM is an appropriate tool for simulating sea ice over a wide range of spatial and temporal scales.

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“…In all model runs, we choose the elastic-anisotropic-plastic rheology described in Tsamados et al [31]. This rheology is the default choice in our developmental branch of CICE and was shown to result in large regional differences in ice thickness with respect to the default elastic-viscousplastic rheology of Hunke & Dukowicz [32].…”

Section: Processes Controlling Ice Melt In a Sea Ice Model (A) Choicementioning

confidence: 99%

Processes controlling surface, bottom and lateral melt of Arctic sea ice in a state of the art sea ice model

Feltham

Petty

Schröder

et al. 2015

Phil. Trans. R. Soc. A.

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We present a modelling study of processes controlling the summer melt of the Arctic sea ice cover. We perform a sensitivity study and focus our interest on the thermodynamics at the ice-atmosphere and iceocean interfaces. We use the Los Alamos community sea ice model CICE, and additionally implement and test three new parametrization schemes: (i) a prognostic mixed layer; (ii) a three equation boundary condition for the salt and heat flux at the ice-ocean interface; and (iii) a new lateral melt parametrization. Recent additions to the CICE model are also tested, including explicit melt ponds, a form drag parametrization and a halodynamic brine drainage scheme. The various sea ice parametrizations tested in this sensitivity study introduce a wide spread in the simulated sea ice characteristics. For each simulation, the total melt is decomposed into its surface, bottom and lateral melt components to assess the processes driving melt and how this varies regionally and temporally. Because this study quantifies the relative importance of several processes in driving the summer melt of sea ice, this work can serve as a guide for future research priorities.

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Impact of a new anisotropic rheology on simulations of Arctic sea ice

Cited by 105 publications

References 49 publications

A high-resolution ocean and sea-ice modelling system for the Arctic and North Atlantic oceans

A high-resolution ocean and sea-ice modelling system for the Arctic and North Atlantic oceans

neXtSIM: a new Lagrangian sea ice model

Processes controlling surface, bottom and lateral melt of Arctic sea ice in a state of the art sea ice model

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