Description: Sea ice deformation localizes along Linear Kinematic Features (LKFs) that are relevant for the air/ocean/sea-ice interaction and for shipping andmarine operations. At high resolution (〈 5km) viscous-plastic sea ice models start to resolve LKFs. Here, we study the short-range (up to 10 days) potential predictability of LKFs in Arctic sea ice using ensemble simulations of an ocean/sea-ice model with a grid point separation of 4.5 km. We analyze the sensitivity of predictability to idealized initial perturbations, mimicking the uncertainties in sea ice analyses, and to growing uncertainty of the atmospheric forcing caused by the chaotic nature of the atmosphere. The similarity between pairs of ensemble members is quantified by Pearson correlation and Modified Hausdorff Distance (MHD). In our perfect model experiments, the potential predictability of LKFs, based on the MHD, drops below 0.6 after 4 days in winter. We find that forcing uncertainty (due to limited atmospheric predictability) largely determines LKF predictability on the 10-day time scale, while uncertainties in the initial state impact the potential predictability only within the first 4 days.

Description: Sea ice dynamics determine the drift and deformation of sea ice. Nonlinear physics, usually expressed in a viscous‐plastic rheology, makes the sea ice momentum equations notoriously difficult to solve. At increasing sea ice model resolution the nonlinearities become stronger as linear kinematic features (leads) appear in the solutions. Even the standard elastic‐viscous‐plastic (EVP) solver for sea ice dynamics, which was introduced for computational efficiency, becomes computationally very expensive, when accurate solutions are required, because the numerical stability requires very short, and hence more, subcycling time steps at high resolution. Simple modifications to the EVP solver have been shown to remove the influence of the number of subcycles on the numerical stability. At low resolution appropriate solutions can be obtained with only partial convergence based on a significantly reduced number of subcycles as long as the numerical procedure is kept stable. This previous result is extended to high resolution where linear kinematic features start to appear. The computational cost can be strongly reduced in Arctic Ocean simulations with a grid spacing of 4.5 km by using modified and adaptive EVP versions because fewer subcycles are required to simulate sea ice fields with the same characteristics as with the standard EVP.

Description: The sea ice modeling community is progressing towards pan-Arctic simulations that explicitly resolve leads in the simulated sea ice cover. Evaluating these simulations against observations poses new challenges. A new feature-based evaluation of simulated deformation fields is introduced, and the results are compared to a scaling analysis of sea ice deformation. Leads and pressure ridges – here combined into linear kinematic features (LKFs) – are detected and tracked automatically from deformation and drift data. LKFs in two pan-Arctic sea ice simulations with a horizontal grid spacing of 2 km are compared with an LKF dataset derived from the RADARSAT Geophysical Processor System (RGPS). One simulation uses a five-class ice thickness distribution (ITD). The simulated sea ice deformation follows a multi-fractal spatial and temporal scaling, as observed from RGPS. The heavy-tailed distribution of LKF lengths and the scale invariance of LKF curvature, which points to the self-similar nature of sea ice deformation fields, are reproduced by the model. Interannual and seasonal variations in the number of LKFs, LKF densities, and LKF orientations in the ITD simulation are found to be consistent with RGPS observations. The lifetimes and growth rates follow a distribution with an exponential tail. The model overestimates the intersection angle of LKFs, which is attributed to the model's viscous-plastic rheology with an elliptical yield curve. In conclusion, the new feature-based analysis of LKF statistics is found to be useful for a comprehensive evaluation of simulated deformation features, which is required before the simulated features can be used with confidence in the context of climate studies. As such, it complements the commonly used scaling analysis and provides new useful information for comparing deformation statistics. The ITD simulation is shown to reproduce LKFs sufficiently well for it to be used for studying the effect of directly resolved leads in climate simulations. The feature-based analysis of LKFs also identifies specific model deficits that may be addressed by specific parameterizations, for example, a damage parameter, a grounding scheme, and a Mohr–Coulombic yield curve.

Description: Sea-ice observations and models show zones of high deformation typical of granular medium (linear kinematic features (LKFs)). Recent high-resolution simulations feature fractures that mimic the observed pattern but with wider intersection angles. Motivated by this, we investigate the dependence between conjugate faults intersection angles and different viscous–plastic rheologies. Using an idealized uniaxial setting, the ice fracture is modeled with different confinement ratios and two different VP rheologies: one with an elliptical yield curve and a normal flow rule, and one with a Coulombic yield curve and a normal flow rule that applies only to the elliptical cap. Modeling fracture angles smaller than 30° is not possible with an elliptical yield curve in a pure compression setting. Further several modeled behaviors are inconsistent with the granular nature of sea ice : (1) the fracture angle increases with ice shear strength; (2) the divergence along the fracture lines (or LKFs) is uniquely defined by the shear strength of the material with divergence for high shear strength and convergence follow shear strength; (3) the angle of fracture depends on the confining pressure with more convergence as the confining pressure increases. With Mohr’s circle, this behavior is shown to be linked to the convexity of the yield curve. The Coulombic yield curve is able to model smaller angles but the solution is unstable because of non-differentiable corners between the straight limbs of the Coulombic yield curve and the elliptical cap. The results show that, although the fracture patterns at first appear realistic, the yield curve should be revised to take into account the nature of sea ice as a pressure-sensitive and dilatant granular material.

Description: Recent high resolution pan-Arctic sea ice simulations show fracture patterns that are typical of granular materials but with intersection (fracture) angles wider than those observed from high-resolution satellite images (with a modal value of θ = 20º). In this work, we investigate the mechanism of formation and parameter dependencies of ice fracture in simple numerical uni-axial test on a 8 km x 25 km ice floe at an unprecedented resolution of 25 m for two different Visco-Plastic (VP) yield curves: an elliptical (standard in sea ice models) and a coulombic yield curve both with normal flow rule. In the standard VP model, the simulated angle of fracture is θ=33.9º. The dependence of the angle of fracture on the ice shear strength is also contrary to that of typical granular materials with larger angle of fracture for higher shear strength. In this model, the divergence along the fracture lines (or LKFs) is entirely dictated by the ice shear strength with high shear strength resulting in convergence along LKFs and low shear strength resulting in divergence along LKFs. This is again contrary to typical granular materials. Moreover, the angle of fracture depends on the confining pressure in the uni-axial test with more convergence as the confining pressure increases, again contrary to granular material. In the Coulombic model, the angle of fracture is smaller (θ=23.5º), but the solution is unstable because of the discontinuity between the straight limbs of the yield curve and the elliptical capping. Our results show that while the VP model gives angles of fracture that are visually correct, the bias in the magnitude of the angle of fracture and the physical dependencies of the angle of fracture on mechanical strength parameters and stress fields couple the sea ice mechanical strength parameters, the sea-ice drift, sea-ice deformation (strain-rate) field in an inconsistent way. We consider this evidence to move away from the elliptical yield curve and associative (normal) flow rule.

Description: Many climate models use a rheology of the viscous-plastic type to simulate sea ice dynamics. With this rheology, large scale velocity and thickness fields can be realistically simulated, but the representation of small scale deformation rates and Linear Kinematic Features (LKF) is thought to be inadequate. However, at high resolution (〈 5 km) the rheology starts to produce lines of localised deformation rates. In this study we use results from a 1-km Pan-Arctic model to investigate the influence of these deformation features on the scaling properties of sea ice deformation. For evaluation the EGPS satellite data set of small-scale sea ice kinematics for the Central Arctic (successor of RGPS) is used. The modelled sea ice deformation shows multi-fractal spatial scaling and, in this sense, agrees with the satellite data. In addition, the temporal coupling of the spatial scaling is reproduced as well. Furthermore, we examine the regional and seasonal variations of spatial scaling properties and its dependence on the ice condition, i.e. sea ice concentration and thickness, which are in agreement with previous RGPS studies.

Description: Many climate models use a rheology of the viscous-plastic type to simulate sea ice dynamics. With this rheology, large scale velocity and thickness fields can be realistically simulated, but the representation of small scale deformation rates and Linear Kinematic Features (LKF) is thought to be inadequate. However, at high resolution (〈 5 km) the rheology starts to produce lines of localised deformation rates. In this study we use results from a 1-km Pan-Arctic model to investigate the influence of these deformation features on the scaling properties of sea ice deformation. For evaluation the EGPS satellite data set of small-scale sea ice kinematics for the Central Arctic (successor of RGPS) is used. The modelled sea ice deformation shows multi-fractal spatial scaling and, in this sense, agrees with the satellite data. In addition, the temporal coupling of the spatial scaling is reproduced as well. Furthermore, we examine the regional and seasonal variations of spatial scaling properties and its dependence on the ice condition, i.e. sea ice concentration and thickness, which are in agreement with previous RGPS studies.

Description: Many climate models use a rheology of the viscous-plastic type to simulate sea ice dynamics. With this rheology, large scale velocity and thickness fields can be realistically simulated, but the representation of small scale deformation rates and Linear Kinematic Features (LKF) is thought to be inadequate. However, at high resolution (〈 5 km) the rheology starts to produce lines of localised deformation rates. In this study we use results from a 1-km Pan-Arctic model to investigate the influence of these deformation features on the scaling properties of sea ice deformation. For evaluation the EGPS satellite data set of small-scale sea ice kinematics for the Central Arctic (successor of RGPS) is used. The modelled sea ice deformation shows multi-fractal spatial scaling and, in this sense, agrees with the satellite data. In addition, the temporal coupling of the spatial scaling is reproduced as well. Furthermore, we examine the regional and seasonal variations of spatial scaling properties and its dependence on the ice condition, i.e. sea ice concentration and thickness, which are in agreement with previous RGPS studies.