Using buoy data from the International Arctic Buoy Program, we found that the sea ice mean speed has substantially increased over the last 29 years (+17% per decade for winter and +8.5% for summer). A strong seasonal dependence of the mean speed is also revealed, with a maximum in October and a minimum in April. The sea ice mean strain rate also increased significantly over the period (+51% per decade for winter and +52% for summer). We check that these increases in both sea ice mean speed and deformation rate are unlikely to be consequences of a stronger atmospheric forcing. Instead, they suggest that sea ice kinematics play a fundamental role in the albedo feedback loop and sea ice decline: increasing deformation means stronger fracturing, hence more lead opening, and therefore a decreasing albedo. This accelerates sea ice thinning in summer and delays refreezing in early winter, therefore decreasing the mechanical strength of the cover and allowing even more fracturing, larger drifting speed and deformation, and possibly a faster export of sea ice through the Fram Strait. The September minimum sea ice extent of 2007 might be a good illustration of this interplay between sea ice deformation and sea ice shrinking, as we found that for both winter 2007 and summer 2007 exceptionally large deformation rates affected the Arctic sea ice cover.

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 multi-scale 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.

Sea ice volume has decreased in the last decades, evoked by changes in sea ice area and thickness. Estimates of sea ice area and thickness rely on a number of geophysical parameters which introduce large uncertainties. To quantify these uncertainties we use freeboard retrievals from ICESat and investigate different assumptions about snow depth, sea ice density and area. We find that uncertainties in ice area are of minor importance for the estimates of sea ice volume during the cold season in the Arctic basin. The choice of mean ice density used when converting sea ice freeboard into thickness mainly influences the resulting mean sea ice thickness, while snow depth on top of the ice is the main driver for the year-to-year variability, particularly in late winter. The absolute uncertainty in the mean sea ice thickness is 0.28 m in February/March and 0.21 m in October/November. The uncertainty in snow depth contributes up to 70% of the total uncertainty and the ice density 30–35%, with higher values in October/November. We find large uncertainties in the total sea ice volume and trend. The mean total sea ice volume is 10 120 ± 1280 km3 in October/November and 13 250 ± 1860 km3 in February/March for the time period 2005–2007. Based on these uncertainties we obtain trends in sea ice volume of −1450 ± 530 km3 a−1 in October/November and −880 ± 260 km3 a−1 in February/March over the ICESat period (2003–2008). Our results indicate that, taking into account the uncertainties, the decline in sea ice volume in the Arctic between the ICESat (2003–2008) and CryoSat-2 (2010–2012) periods may have been less dramatic than reported in previous studies. However, more work and validation is required to quantify these changes and analyse possible unresolved biases in the freeboard retrievals.

In this paper, we evaluate the neXtSIM sea ice model with respect to the observed scaling invariance properties of sea ice deformation in the spatial and temporal domains. Using an Arctic setup with realistic initial conditions, state-of-the-art atmospheric reanalysis forcing and geostrophic currents retrieved from satellite data, we show that the model is able to reproduce the observed properties of this scaling in both the spatial and temporal domains over a wide range of scales, as well as their multi-fractality. The variability of these properties during the winter season is also captured by the model. We also show that the simulated scaling exhibits a space–time coupling, a suggested property of brittle deformation at geophysical scales. The ability to reproduce the multi-fractality of this scaling is crucial in the context of downscaling model simulation outputs to infer sea ice variables at the sub-grid scale and also has implications for modeling the statistical properties of deformation-related quantities, such as lead fractions and heat and salt fluxes.