Elastic‐decohesive constitutive model for sea ice

Abstract

[1] One of the dominant characteristics of Arctic ice is the development and persistence of leads. Leads are critically important for climate modeling since they are a source for new ice and an avenue for heat exchange between the atmosphere and ocean. Therefore a specific representation for leads in a constitutive model for pack ice is considered essential. Presented here is an elastic-decohesive constitutive model whose purpose is to specifically indicate when a lead is initiated, to provide the orientation of the lead, to give the mode of failure, and to allow for the numerical determination of the width of leads. Both laboratory and in situ data of sea ice provide the motivation for the basic structure of the model. Sample paths in stress and strain space are used to illustrate how the model can simulate failure. The model can predict multiple failure planes, a feature that is necessary to simulate crack branching. Preexisting planes of weakness such as those formed from previous leads can also be accommodated.

neXtSIM: a new Lagrangian sea ice model

“…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).…”

Atomistic simulations of friction at an ice-ice interface

“…Examples include fracture of the Arctic sea ice cover [2][3][4][5][6][7][8][9][10][11][12], brittle compressive failure during interactions between natural ice features and engineered structures [13,14], and tectonic activity of ice-encrusted bodies within the outer solar system [15][16][17][18][19][20][21][22][23][24]. For most of these systems, it is the friction of ice sliding upon itself that dominates the mechanics and heat generated at the interface.…”

Physically-based data assimilation

“…The sea-ice simulations we perform to demonstrate our scheme use an elastic-decohesive constitutive model for the sea ice (Schreyer et al, 2006). The model was developed for predicting the initiation and opening of leads in the Arctic ice.…”

“…The control and experimental simulations are of ice behavior in a 831.600 km 2 Model parameters include the elastic moduli, ice density, Coriolis parameter, drag coefcients and the parameters in the decohesive model that set the failure strength of ice in tension τ nf and shear τ sf , the length scale over which decohesion occurs u 0 , and two parameters that describe the shape of the failure surface in stress space, κ and τ sm (Schreyer et al, 2006, and Appendix A). Values of the parameters used for the simulations are given in Table 1.…”

“…The underlying principle for our assimilation algorithm is to use data to precondition model variables or material properties that allow internal model physics to generate future model states that agree better with observed data. The new scheme is tested with a sea ice model (Schreyer et al, 2006;described in Sect. 2.3 and Appendix A) and RADARSAT Geophysical Processor System (RGPS; Kwok, 1998) data, in a physically-based nudging context for one assimilation cycle.…”