Classical sea-ice models in climate model resolution do not resolve the small-scale physics of sea ice. New methods to address this problem include modifications to established viscous-plastic (VP) rheology models, sub-gridscale parameterizations or new rheologies such as the Maxwell elasto-brittle (MEB) rheology. Here, we investigate differences in gridscale dynamics simulated by the VP and MEB models, their dependency on tunable model parameters and their response to added stochastic perturbations of material parameters in a new implementation in the Massachusetts Institute of Technology general circulation model. Idealized simulations are used to demonstrate that material parameters can be tuned so that both VP and MEB rheologies lead to similar cohesive stress states, arching behaviour and heterogeneity in the deformation fields. As expected, simulations with MEB rheology generally show more heterogeneity than the VP model as measured by the number of simulated linear kinematic features (LKFs). For both rheologies, the cohesion determines the emergence of LKFs. Introducing gridscale heterogeneity by random model parameter perturbation, however, leads to a larger increase of LKF numbers in the VP simulations than in the MEB simulations and similar heterogeneity between VP and MEB models.

Evaluating CMIP6 model performance helps to improve the prediction of future changes in Arctic sea ice. We analyze the seasonal cycles, distribution, and evolution of sea ice in different regions from 1979 to 2014. We compare the output from selected CMIP6 models with reference data for sea ice motion. We also discuss the correlations between sea ice motion(SIM) and sea ice thickness (SIT) in reference data, and how CMIP6 models explain them. We select EC-Earth3, ACCESS-CM2, BCC-CSM2-MR, MPI-ESM1-2-HR, and NorESM2-LM for CMIP6 study. We compare outputs with reference data: Sea ice extent (SIE) from NSIDC; SIT from PIOMAS; and SIM from the IABP buoy data. Analytical techniques include Theil-Sen and Ordinary least squares (OLS) regression. Most selected CMIP6 models have seasonal cycles of SIM lagging behind IABP observations by 1-2 month and overestimate central Arctic SIM magnitude, with MPI-ESM1-2-HR having the highest discrepancy and NorESM2-LM lowest. The models show better simulation of SIM in the ice melting season than in the growing season. Models perform worse at capturing regional differences in SIM evolution and are overly conservative when simulating the increasing trend in ice motion, especially in coastal Arctic seas during summer. There is significant negative correlation between SIT and SIM in October.

Understanding sea-ice dynamics at the floe scale is crucial to comprehend polar climate systems. While continuum models are commonly used to simulate large-scale sea-ice dynamics, they have limitations in accurately representing sea-ice behaviour at small scales. DEMs, on the other hand, are well-suited for modelling the behaviour of individual ice floes but face limitations due to computational constraints. To address the limitations of both approaches while combining their strengths, we explored the feasibility of using a DEM within a continuum model, where the latter provides boundary conditions for a rectangular high-resolution DEM domain. This paper presents a feasibility study where a discrete model of a 100 × 100 km2 icefield was created using high-resolution optical satellite imagery. Sea-ice dynamics were simulated in the DEM considering environmental forces and integrating large-scale ice-drift velocities as boundary conditions. Model predictions were compared with satellite observations for ice drift and deformation parameters. This numerical approach showed potential for offering accurate, high-resolution predictions of sea ice, particularly in coastal areas and near islands, and may find applications in ice navigation and climate studies. However, further development of the DEM, along with upgrades to the coupled ocean models providing data for the ice component, may be necessary. Additionally, challenges remain to develop a two-way coupling between the DEM and a continuum model, which may be needed to improve the accuracy of large-scale simulations.

Processes driving changes in sea-ice seasonality and sea-ice thickness were explored for a ‘warm-shelf’ region along the West Antarctic Peninsula using vertically coupled sea-ice-ocean thermodynamic simulations, with and without assimilated satellite sea-ice observations and moored ocean temperature observations. Simulations with assimilated sea-ice observations permitted investigation of surface [thermodynamic and dynamic (e.g., wind-driven)] processes affecting sea-ice thickness and seasonality. Assimilation of quasi-weekly variability in the depth and temperature of the deep warm pycnocline permitted examination of subsurface processes affecting sea-ice. Simulations using assimilated sea-ice observations (and implied motion) always produced greater surface heat fluxes and overall thinner sea ice. Assimilating seasonal and quasi-weekly variability in the depth and temperature of the pycnocline modified the start of the sea-ice season by −23 to +1 d, and also modified the sea ice thickness/seasonality to be thinner/shorter or thicker/longer at sub-seasonal and seasonal timescales, highlighting a mechanism where a shoaling pycnocline enhanced upward deep-water heat fluxes as transient surface-induced turbulence had a greater effect on a reduced mixed layer volume. The observed interplay of surface, subsurface, and sea-ice modulation of ocean-atmosphere heat transfer underscores the importance of representing the interaction between sea-ice concentration and upper ocean variability in climate projections.

Using operational sea-ice maps, we provide first insight into the seasonal evolution of fast ice in the East Siberian Sea for the period between 1999 and 2021. The fast ice season tends to start later by 4.7 d per decade and to end earlier by 9.7 d per decade. As a result, there is a trend towards a shorter length of fast ice season by 2 weeks per decade. The analysis of air temperatures indicates that onset and end of the fast ice season are largely driven by thermodynamic processes. Two spatial modes (large, L-mode and small, S-mode) of East Siberian fast ice cover which have significant areal differences were distinguished. The occurrence of L- and S-modes was linked to the polarity of the Arctic Oscillation (AO) index. Negative AO phase leads to increased sea-ice convergence in the region, which in turn favours sea-ice grounding and promotes the development of large fast ice extent (L-mode). Lower deformation rates in the region during positive AO phase does not allow the formation of grounded features which results in small fast ice extent (S-mode). An analysis of sea-ice divergence confirms that L-mode seasons are characterised by higher on-shore convergence compared with S-mode seasons.

In situ observations of wave attenuation by sea ice are required to develop and validate wave–ice interaction parameterizations in coupled wave models. To estimate ice-induced wave attenuation in the field, the wave field is typically assumed to be stationary. In this study we investigate the validity of this assumption by creating a synthetic wave field in sea ice for different attenuation rates. We observe that errors in estimates of the wave attenuation rates are largest when attenuation rates are small or temporal averaging periods are short. Moreover, the adoption of the wave stationarity assumption can lead to negative estimates of the instantaneous wave attenuation rate. These apparent negative values should therefore not be attributed to wave growth or erroneous measurements a priori. Surprisingly, we observe that the validity of the wave stationarity assumption is irrelevant to the accuracy of estimates of wave attenuation rates as long as the temporal averaging period is taken sufficiently long. This may provide opportunities in using satellite-derived products to estimate wave attenuation rates in sea ice at global scales.

Sea-ice drift in the Antarctic marginal ice zone (MIZ) is discussed using data from a 4-month-long drift of a buoy deployed on a pancake ice floe during the winter sea-ice expansion. We demonstrate increased meandering and drift speeds, and changes in the dynamical regimes of the absolute dispersion during cyclone activity, together with high correlations between drift velocities and wind from atmospheric reanalyses. This indicates a dominant physical control of wind forcing on ice drift and the persistence of free-drift conditions. These conditions occurred despite the buoy remaining largely in >80% ice concentrations and at distances >200 km from the estimated ice edge. The drift is additionally characterised by a strong inertial signature at 13.47 h, which appears initiated by passing cyclones. A wavelet analysis of the buoy's velocity confirms that the momentum transfer from winds at the multi-day frequencies is due to atmospheric forcing, while the initiation of inertial oscillations of sea ice has been identified as the secondary effect. Propagating storm-generated waves may initiate inertial oscillations by increasing the mobility of floes and enhance the drag of the inertial current. This analysis indicates that the Antarctic MIZ in the Indian Ocean sector remains much wider and mobile, during austral winter-to-spring, than defined by sea-ice concentration.

Geophysical systems are often assumed to follow Gaussian probability density functions; however, deviations from Gaussian behaviour can shed light on the underlying dynamics. For the large-scale motion of the Arctic sea ice, such deviations have been interpreted as signatures of structure in dynamic flow fields. In this study, we use higher-order moments (skewness and kurtosis) to identify spatiotemporal changes in the Beaufort Gyre (BG) and the Transpolar Drift (TPD) sea-ice drift patterns. Higher-order moments of satellite-derived ice drift speeds are examined over the winter period of 2006–2017 to describe the persistence of features like the BG and TPD, and their variation over time. Index patterns indicate that the periphery of the BG can be identified by a combination of high positive skewness and high kurtosis in the ice drift time series on an annual basis.

Quantifying the rate of wave attenuation in sea ice is key to understanding trends in the Antarctic marginal ice zone extent. However, a paucity of observations of waves in sea ice limits progress on this front. We deployed 14 waves-in-ice observation systems (WIIOS) on Antarctic sea ice during the Polynyas, Ice Production, and seasonal Evolution in the Ross Sea expedition (PIPERS) in 2017. The WIIOS provide in situ measurement of surface wave characteristics. Two experiments were conducted, one while the ship was inbound and one outbound. The sea ice throughout the experiments generally consisted of pancake and young ice <0.5 m thick. The WIIOS survived a minimum of 4 d and a maximum of 6 weeks. Several large-wave events were captured, with the largest recorded significant wave height over 9 m. We find that the total wave energy measured by the WIIOS generally decays exponentially in the ice and the rate of decay depends on ice concentration.

The role of synoptic-scale cyclones in the trends and variability of Arctic sea ice conditions has remained uncertain. In recognition, we conduct a systematic investigation of how sea-ice concentration (SIC) changes with cyclone passage, including all individual storms that pass over any part of the region's ice pack. For all seasons, especially summer and autumn, we find a pattern of higher ice concentration after a region is influenced by a cyclone compared to when it is not, primarily due to thermodynamic effects. During warm months, cyclones appear to slow the general day-to-day decline in concentration; in cold months, cyclones augment the day-to-day increase. These relationships are changing over time, with cyclone-associated concentration changes becoming less distinct from overall changes. Cyclone effects on ice divergence are spatially variable; computed fields are noisy. In summer, these dynamic effects of cyclone passage generally decrease SIC, but are outweighed by the thermodynamic effects (e.g., reductions in air temperature, shortwave radiation). In autumn, cyclone-associated concentration changes are not as easily explained by observed cyclone conditions. Key questions remain regarding the extent to which our findings are influenced by artifacts of surface melt and weather effects on the passive microwave retrievals.

In the marginal ice zone, surface waves drive motion of sea ice floes. The motion of floes relative to each other can cause periodic collisions, and drives the formation of pancake sea ice. Additionally, the motion of floes relative to the water results in turbulence generation at the interface between the ice and ocean below. These are important processes for the formation and growth of pancakes, and likely contribute to wave energy loss. Models and laboratory studies have been used to describe these motions, but there have been no in situ observations of relative ice velocities in a natural wave field. Here, we use shipboard stereo video to measure wave motion and relative motion of pancake floes simultaneously. The relative velocities of pancake floes are typically small compared to wave orbital motion (i.e. floes mostly follow the wave orbits). We find that relative velocities are well-captured by existing phase-resolved models, and are only somewhat over-estimated by using bulk wave parameters. Under the conditions observed, estimates of wave energy loss from ice–ocean turbulence are much larger than from pancake collisions. Increased relative pancake floe velocities in steeper wave fields may then result in more wave attenuation by increasing ice–ocean shear.

The permeability of sea ice can strongly affect the dissipation of wave energy into the ice pack. Sea-ice permeability is known to be impacted by the brine volume fraction and the blockage of flow pathways by the freezing of infiltrating lower salinity water. Here we investigate another process impacting sea-ice permeability, namely, inelastic deformation. We report the results of a first-of-its-kind field-scale deformation experiment to investigate the impact of compressive loading on sea-ice permeability. We observed that deformation decreased permeability by four orders of magnitude or more in some locations, while elsewhere permeability was unaffected or possibly increased. We show that the observed changes in permeability are consistent with expected changes in stress state and, as a result, in the mechanisms of deformation.

The presence of leads with open water or thin ice is an important feature of the Arctic sea ice cover. Leads regulate the heat, gas and moisture fluxes between the ocean and atmosphere and are areas of high ice growth rates during periods of freezing conditions. Here, an algorithm providing an automatic lead detection based on synthetic aperture radar images is described that can be applied to a wide range of Sentinel-1 scenes. By using both the HH and the HV channels instead of single co-polarised observations the algorithm is able to classify more leads correctly. The lead classification algorithm is based on polarimetric features and textural features derived from the grey-level co-occurrence matrix. The Random Forest classifier is used to investigate the importance of the individual features for lead detection. The precision–recall curve representing the quality of the classification is used to define threshold for a binary lead/sea ice classification. The algorithm is able to produce a lead classification with more that 90% precision with 60% of all leads classified. The precision can be increased by the cost of the amount of leads detected. Results are evaluated based on comparisons with Sentinel-2 optical satellite data.

We present sea-ice surface roughness estimates, i.e. the standard deviation of relative surface elevation, in the Arctic regions of Fram Strait and the Nansen Basin north of Svalbard acquired by an airborne laser scanner and a single-beam laser altimeter in 2010. We compare the scanner to the altimeter and compare the differences between the two survey regions. We estimate and correct sensor roll from the scanner data using the hyperbolic response of the scanner over a flat surface. Measurement surveys had to be longer than 5 km north of Svalbard and longer than 15 km in Fram Strait before the statistical distribution in surface roughness from the scanner and altimeter became similar. The shape of the surface roughness probability distributions agrees with those of airborne electromagnetic induction measurements of ice thickness. The ice in Fram Strait had a greater mean surface roughness, 0.16 m vs 0.09 m, and a wider distribution in roughness values than the ice in the Nansen Basin. An increase in surface roughness with increasing ice thickness was observed over fast ice found in Fram Strait near the coast of Greenland but not for the drift ice.

Data from the Seasonal Ice Zone Observing Network (SIZONet) acquired near Barrow, Alaska, during the 2009/10 ice season allow novel comparisons between measurements of ice thickness and velocity. An airborne electromagnetic survey that passed over a moored Ice Profiling Sonar (IPS) provided coincident independent measurements of total ice and snow thickness and ice draft at a scale of 10 km. Once differences in sampling footprint size are accounted for, we reconcile the respective probability distributions and estimate the thickness of level sea ice at 1.48 ± 0.1 m, with a snow depth of 0.12 ± 0.07 m. We also complete what we believe is the first independent validation of radar-derived ice velocities by comparing measurements from a coastal radar with those from an under-ice acoustic Doppler current profiler (ADCP). After applying a median filter to reduce high-frequency scatter in the radar-derived data, we find good agreement with the ADCP bottom-tracked ice velocities. With increasing regulatory and operational needs for sea-ice data, including the number and thickness of pressure ridges, coordinated observing networks such as SIZONet can provide the means of reducing uncertainties inherent in individual datasets.

In this paper we investigate the effect on sea-ice movement of changes in the synoptic atmospheric conditions in late boreal summer 2010. Our study area is the western Fram Strait, a crucial passage for the transport of ice out of the Arctic basin. Ice dynamics here affect the movement of ice in the East Greenland Current, the transpolar drift and ice extent in the Arctic Ocean. In contrast to other times of the year, when the Fram Strait wind field is characterized by strong, persistent northerlies, we show that the weaker, more variable winds typical during late summer for the Fram Strait can slow movement of ice floes out of the area, thus slowing the export of ice from the Arctic Ocean at the end of summer, a time crucial for ice export. The Arctic Ocean could lose even more of the ice that survives the summer if this was not the case. This would leave the Arctic Ocean in an even more vulnerable position with regard to the amount of multi-year ice remaining the following summer.

During summer 2007, perennial sea ice in the Beaufort Sea, Arctic Ocean, experienced an unprecedented amount of basal melt. It has previously been shown that this basal melt was linked to an increase in open-water fraction, increasing absorption of solar radiation into the ocean. GPS ice drifters, deployed around the site where the unprecedented basal melt was observed, provide a coincident observation of local divergence. This divergence is used to drive a multi-thickness category thermodynamic sea-ice model. We demonstrate that ∼ 75% of the observed open-water fraction by midsummer 2007 can be attributed to ice pack divergence during the growth season, preconditioning the ice pack for early melt in summer. Divergence during the melt season explains the remaining 25% of open water. Enhanced ice pack divergence in spring and summer 2007, in response to the increased transport of ice out of the Beaufort Sea, was sufficient to explain the melt observed in summer 2007 and the heat stored in the upper ocean at the end of summer.

Central to an understanding of evolution in sea-ice characteristics in response to climate change is an understanding of sea-ice dynamics. In this study, we investigate regional differences in ice dynamics in the Beaufort Sea and High Arctic using high-frequency ice buoy (beacon) data deployed during the SEDNA and IPY-CFL field campaigns from spring 2007 to winter 2008. Examined in particular are scaling laws determined from absolute dispersion statistics. We create temporal scaling maps to determine whether distinct dynamical regimes can be identified with differing scaling properties. The results from this analysis provide an alternative characterization to changes in sea ice based on dynamics rather than concentration and thickness, and thus insight into, and improved understanding of, the connections between sea-ice drift and morphology.

A new numerical implementation is proposed for a wave-ice interaction model. It is applied to an idealized transect geometry. Wave attenuation due to ice floes and wave-induced ice fracture are both included in the model. The new method alleviates the need for subgrid spatial or temporal discretizations, thereby facilitating future integration of wave-ice interactions into large-scale coupled models.

During the 30th Chinese Antarctic Expedition in 2013/14, the Chinese icebreaker RV Xuelong answered a rescue call from the Russian RV Akademik Shokalskiy. While assisting the repatriation of personnel from the Russian vessel to the Australian RV Aurora Australis, RV Xuelong itself became entrapped within the compacted ice in the Adélie Depression region. Analysis of MODIS and SAR imagery provides a detailed description of the regional sea-ice conditions which led to the 6 day long besetment of RV Xuelong. The remotely sensed imagery revealed four stages of sea-ice characteristics during the entrapment: the gathering, compaction, dispersion and calving stages. Four factors characterizing the local sea-ice conditions during late December 2013 and early January 2014 were identified: surface component of the coastal current; near-surface wind; ocean tides; and surface air temperature. This study demonstrates that shipping activity in ice-invested waters should be underpinned by general knowledge of the ice situation. In addition, during such activity high spatiotemporal resolution remotely sensed data should be acquired regularly to monitor local and regional sea-ice changes with a view to avoiding the besetment of vessels.