A parameterization of the impact of internal waves on momentum transfer at the sea-ice–ocean interface based on previous work by McPhee has been implemented in a sea-ice model for the first time. The ice–ocean drag from internal waves is relevant for shallow mixed layer depth and the presence of a density jump at the pycnocline and is also a function of the strength of the stratification beneath the ocean mixed layer and geometry of the ice interface. We present results from a coupled sea-ice–ocean model where the parameterization of internal wave drag has been implemented. We conducted simulations spanning the years from 2000 to 2017. We find a deceleration of ice drift by 5–8% in both winter and summer, but with significant spatial and temporal variation reaching seasonal average values of ~10%. The spatial variation of ice transport leads to local impacts on deformed ice of magnitude ~0.05 m (2–5%), and reductions in ocean-to-ice heat fluxes of ~1 W m−2, and a decrease in bottom melt of ~0.02–0.04 cm d−1. There is an increase of up to 15% in thickness and ice concentration in the Canadian Arctic and a 10% overall impact on the total sea-ice volume.

The changing conditions in which sea ice forms and exists are likely to affect the properties of sea ice itself, and potential climate feedbacks need to be identified and understood to improve future projections. Here we perform a set of idealised laboratory experiments that model sea-ice growth under a range of freezing conditions. The results confirm existing theories; sea-ice growth rate is largest for cooler freezing temperatures, fresher ambient salinities and cases with bottom cooling. Our primary metric of interest is the brine fraction (the volume ratio of brine inclusions to the total sea ice), which we quantify and determine its sensitivity with respect to the ambient salinity, freezing temperature and, for the first time, the freezing direction. We find that the brine fraction of our model sea ice is most sensitive to freezing temperature, and increases 2.5% per 1$^\circ$C increase of freezing temperature.

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.

Brash ice formation and accumulation occur at a faster rate in ship channels, harbours and turning areas compared to the surrounding level ice. Accurate prediction of brash ice thickness plays an important role in addressing operational challenges and optimisation of ice management strategies. This study enhances existing brash ice growth models by considering the effects of snow and accounting for brash ice expulsion towards the sides of ship channels at each passage. To validate the influence of these critical factors on brash ice thickness, three distinct ship channels located in the Bay of Bothnia, Luleå, Sweden, were investigated. For two test channels formed for study purposes, the slower growth rate of brash ice caused by snow insulation was more prominent than the brash ice growth acceleration caused by the snow–slush–snow ice transformation. In the third channel characterised by frequent navigation, the transformation of slush into snow ice played a more substantial role than snow insulation. In both test channels, the brash ice growth model performed optimally, assuming a 10% expulsion of brash ice sideways at each vessel passage. In the third, wider and more frequently navigated channel, a 1.2% brash ice expelling coefficient predicted well the measured brash ice thicknesses.

Brash ice forms in harbours and ship channels from frequent ship passages and the resulting freezing–breaking cycles create a unique ice formation. The brash ice accumulation over the winter season is a result of meteorological, thermodynamical and mechanical processes. A reliable brash ice growth model is an important asset when determining navigation routes through ice conditions and when establishing port ice management solutions. This review aims to describe the brash ice development and its modelling as well as the key parameters that influence the brash ice growth and its estimation. This paper summarises the brash ice growth models and the fundamental theories of level ice growth upon which these models are based, and outlines the main knowledge gaps. The results highlight the importance of porosity and piece size distribution and their effect on the consolidation process. The inclusion of the brash ice lateral movement and the side ridge formation would improve the accuracy of forecast models. Furthermore, the findings of the study identify the effect of omitting meteorological parameters such as snow and radiation, from the brash ice growth models. Their contribution to the level ice thickness suggests a significant influence on the brash ice consolidation process.

With the assimilation of satellite-based sea-ice thickness (SIT) data, the new SIT reanalysis from the Towards an Operational Prediction system for the North Atlantic European coastal Zones (TOPAZ4) was released from 2014 to 2018. Apart from assimilating sea-ice concentration and oceanic variables, TOPAZ4 further assimilates CS2SMOS SIT. In this study, the 5-year reanalysis is compared with CS2SMOS, the Pan-Arctic Ice-Ocean Modeling and Assimilating System (PIOMAS) and the Combined Model and Satellite Thickness (CMST). Moreover, we evaluate TOPAZ4 SIT with field observations from upward-looking sonar (ULS), ice mass-balance buoys, Operation IceBridge Quicklook and Sea State Ship-borne Observations. The results indicate TOPAZ4 well reproduces the spatial characteristics of the Arctic SIT distributions, with large differences with CS2SMOS/PIOMAS/CMST mainly restricted to the Atlantic Sector and to the month of September. TOPAZ4 shows thinner ice in March and April, especially to the north of the Canadian Arctic Archipelago with a mean bias of −0.30 m when compared to IceBridge. Besides, TOPAZ4 simulates thicker ice in the Beaufort Sea when compared to ULS, with a mean bias of 0.11 m all year round. The benefit from assimilating SIT data in TOPAZ4 is reflected in a 34% improvement in root mean square deviation.

Columnar sea ice grows with an interface of tiny parallel ice plates, the distance of which is known as plate spacing. While it has been proposed as a fundamental microstructure scale of sea ice, the physics behind its formation has not been fully understood. Here the problem is analysed on the basis of morphological stability theory to propose a model that results in a physically consistent prediction of the relationship between the plate spacing a0 and growth velocity V. The relationship may be divided into two regimes. In the diffusive regime, for V above ≈2 × 10−4 cm s−1 one finds a0 ~ V−2/3 to first order. In the convective regime, the extent of diffusive boundary layer is controlled by solutal convection near the interface, which leads to the proportionality a0 ~ V−1/3. From a comparison to observations it is evident that the plate spacing is predictable over 5 orders of magnitude in the growth velocity, covering the range from fast laboratory ice growth to slow accretion at the bottom of marine ice shelves. The predictability opens new paths towards concise modelling of marine and sea-ice microstructure and physical properties.

We examine the relative effect of warming events (storms) and snow cover on thermodynamic growth of Arctic sea ice in winter. We use a 1-D snow and ice thermodynamic model to perform sensitivity experiments. Observations from the winter period of the Norwegian young sea ICE (N-ICE2015) campaign north of Svalbard are used to initiate and force the model. The N-ICE2015 winter was characterized by frequent storm events that brought pulses of heat and moisture, and a thick snow cover atop the sea ice (0.3–0.5 m). By the end of the winter, sea-ice bottom growth was negligible. We show that the thermodynamic effect of storms to the winter sea-ice growth is controlled by the amount of snow on sea ice. For 1.3 m initial ice thickness, the decrease in ice growth caused by the warming events ranged from −1.4% (for 0.5 m of snow) to −7.5% (for snow-free conditions). The decrease in sea-ice growth caused by the thick snow (0.5 m) was more important, ranging from −17% (with storms) to −23% (without storms). The results showcase the critical role of snow on winter Arctic sea-ice growth.

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.

Increasing ship traffic and human activity in the Arctic has led to a growing demand for accurate Arctic weather forecast. High-quality forecasts obtained by models are dependent on accurate initial states achieved by assimilation of observations. In this study, a multi-variate nudging (MVN) method for assimilation of sea-ice variables is introduced. The MVN assimilation method includes procedures for multivariate update of sea-ice volume and concentration, and for extrapolation of observational information spatially. The MVN assimilation scheme is compared with the Ensemble Kalman Filter (EnKF) using the Los Alamos Sea Ice Model. Two multi-variate experiments are conducted: in the first experiment, sea-ice thickness from the European Space Agency's Soil Moisture and Ocean Salinity mission is assimilated, and in the second experiment, sea-ice concentration from the ocean and Sea Ice Satellite Application Facility is assimilated. The multivariate effects are cross-validated by comparing the model with non-assimilated observations. It is found that the simple and computationally cheap MVN method shows comparable skills to the more complicated and expensive EnKF method for multivariate update. In addition, we show that when few observations are available, the MVN method is a significant model improvement compared to the version based on one-dimensional sea-ice concentration assimilation.

The seasonal cycle of fast ice thickness in Prydz Bay, East Antarctica, was observed between March and December 2012. In March, we observed a 0.16 m thickness gain of 0.22 m-thick first-year ice (FYI), while 1.16 m-thick second-year ice (SYI) nearby simultaneously ablated by 0.59 m. A 1-D thermodynamic sea-ice model was applied to identify the factors that led to the simultaneous growth of FYI and melt of SYI. The different evolutions were explained by the difference in the conductive heat flux between the FYI and SYI. As the FYI was thin, there was a large temperature gradient between the ice base and the colder ice surface. This generated an upward conductive heat flux, which was larger than the heat flux from the ocean to the ice base, yielding basal growth of ice. In the case of the thicker SYI the temperature gradient and, hence, the conductive heat flux were smaller, and not sufficient to balance the oceanic heat flux at the ice base, yielding basal ablation. Penetration of solar radiation affected the conductive heat flux in both cases, and the model results were sensitive to the initial ice temperature profile and the uncertainty of the oceanic heat flux.

The decrease in summer sea-ice extent in the Arctic Ocean opens shipping routes and creates potential for many marine operations. For these activities accurate predictions of sea-ice conditions are required to maintain marine safety. In an attempt at Arctic sea-ice prediction, the summer of 2010 is selected to implement an Arctic sea-ice data assimilation (DA) study. The DA system is based on a regional Arctic configuration of the Massachusetts Institute of Technology general circulation model (MITgcm) and a local singular evolutive interpolated Kalman (LSEIK) filter to assimilate Special Sensor Microwave Imager/Sounder (SSMIS) sea-ice concentration operational products from the US National Snow and Ice Data Center (NSIDC). Based on comparisons with both the assimilated NSIDC SSMIS concentration and concentration data from the Ocean and Sea Ice Satellite Application Facility, the forecasted sea-ice edge and concentration improve upon simulations without data assimilation. By the nature of the assimilation algorithm with multivariate covariance between ice concentration and thickness, sea-ice thickness fields are also updated, and the evaluation with in situ observation shows some improvement compared to the forecast without data assimilation.

We estimate the sea-ice extent and basal melt of Antarctic ice shelves at the Last Glacial Maximum (LGM) using a coupled ice-shelf-sea-ice-ocean model. The shape of Antarctic ice shelves, ocean conditions and atmospheric surface conditions at the LGM are different from those in the present day; these are derived from an ice-shelf-ice-sheet model, a sea-ice-ocean model and a climate model for glacial simulations, respectively. The winter sea ice in the LGM is shown to extend up to ∼7° of latitude further equatorward than in the present day. For the LGM summer, the model shows extensive sea-ice cover in the Atlantic sector and little sea ice in the other sectors. These modelled sea-ice features are consistent with those reconstructed from sea-floor sedimentary records. Total basal melt of Antarctic ice shelves in the LGM was ∼2147 Gt a–1, which is much larger than the present-day value. More warm waters originating from Circumpolar Deep Water could be easily transported into ice-shelf cavities during the LGM because the full glacial grounding line extended to shelf break regions and ice shelves overhung continental slopes. This increased transport of warm water masses underneath an ice shelf and into their basal cavities led to the high basal melt of ice shelves in the LGM.

We examine the melting of sea ice versus freshwater ice in laboratory experiments and with one-dimensional model simulations. Our primary aim is to investigate the vertical partitioning of heat between thinning and internal phase changes. In agreement with our general understanding of the two ice types, we find that freshwater ice quickly starts thinning and then keeps a constant melt rate for constant external heat input. In contrast, sea ice starts thinning later but then thins faster than freshwater ice. This temporal evolution is caused by the substantial amount of heat that is used for internal phase changes in sea ice. Those internal phase changes give rise to a nonlinear temperature profile in the sea ice during the entire melting period, whereas freshwater ice quickly reaches its melting temperature throughout its entire thickness. Infrared imagery provides additional insights into the surface temperature of both ice types during melting. We find that, during melting, sea ice can have a mean surface temperature several tenths of a degree above 0°C because of meltwater-filled millimetre-scale dimples at the ice surface.

A theoretical model and an experimental model of surge motions of an ice floe due to regular waves are presented. The theoretical model is a modified version of Morrison’s equation, valid for small floating bodies. The experimental model is implemented in a wave basin at a scale 1:100, using a thin plastic disc to model the floe. The processed experimental data display a regime change in surge amplitude when the incident wavelength is approximately twice the floe diameter. It is shown that the theoretical model is accurate in the high-wavelength regime, but highly inaccurate in the low-wavelength regime.

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.

In this paper we explore simulated responses of electromagnetic (EM) signals relative to in situ field surveys and quantify the effects that different values of conductivity in sea ice have on the EM fields. We compute EM responses of ice types with a three-dimensional (3-D) finite-volume discretization of Maxwell’s equations and present 2-D sliced visualizations of their associated EM fields at discrete frequencies. Several interesting observations result: First, since the simulator computes the fields everywhere, each gridcell acts as a receiver within the model volume, and captures the complete, coupled interactions between air, snow, sea ice and sea water as a function of their conductivity; second, visualizations demonstrate how 1-D approximations near deformed ice features are violated. But the most important new finding is that changes in conductivity affect EM field response by modifying the magnitude and spatial patterns (i.e. footprint size and shape) of current density and magnetic fields. These effects are demonstrated through a visual feature we define as ‘null lines’. Null line shape is affected by changes in conductivity near material boundaries as well as transmitter location. Our results encourage the use of null lines as a planning tool for better ground-truth field measurements near deformed ice types.

A new modelling framework using Lagrangian particle tracking has been developed to assess dynamic and thermodynamic effects of underwater frazil ice. This frazil-ice model treats a Lagrangian particle as a bulk cluster of many frazil crystals, and calculates the thermodynamic growth of each particle and the corresponding budget of latent heat and fresh water. The effective density and viscosity of sea water depend on the mass fraction of underwater frazil ice, and hence affect ocean convection. An idealized experiment using our model successfully reproduces the formation of underwater frazil ice and its transition to grease ice at the surface. Because underwater frazil ice does not reduce the atmosphere/ocean heat exchange, surface heat flux and net sea-ice production in the experiment with frazil ice are relatively high compared with the experiment where surface cooling directly leads to columnar growth of a solid ice cover which effectively insulates the heat flux. These results suggest that large-scale sea-ice models which do not take account of the effects of frazil ice might underestimate atmosphere/ocean heat exchange, particularly at times of active new ice formation.

Antarctic coastal sea ice often grows in water that has been supercooled by interaction with an ice shelf. In these situations, ice crystals can form at depth, rise and deposit under the sea-ice cover to form a porous layer that eventually consolidates near the base of the existing sea ice. The least consolidated portion is called the sub-ice platelet layer. Congelation growth eventually causes the sub-ice platelet layer to become frozen into the sea-ice cover as incorporated platelet ice. In this study, we simulate these processes in three dimensions using Voronoi dynamics to govern crystal growth kinetics. Platelet deposition, in situ growth and incorporation into the sea-ice cover are integrated into the model. Heat and mass transfer are controlled by diffusion. We extract and compare spatial-temporal distributions of porosity, salinity, temperature and crystallographic c-axes with observations from McMurdo Sound, Antarctica. The model captures the crystallographic structure of incorporated platelet ice as well as the topology of the sub-ice platelet layer. The solid fraction, which has previously been poorly constrained, is simulated to be ∼0.22, in good agreement with an earlier estimate of 0.25 ± 0.06. This property of the sub-ice platelet layer is important for biological processes, and for the freeboard-thickness relationship around Antarctica.

During late winter 2007, coincident measurements of sea ice were collected using various sensors at an ice camp in the Beaufort Sea, Canadian Arctic. Analysis of the archived data provides new insight into sea-ice isostasy and its related R-factor through case studies at three scales using different combinations of snow and ice thickness components. At the smallest scale (<1 m; point scale), isostasy is not expected, so we calculate a residual and define this as Ж (‘zjey’) to describe vertical displacement due to deformation. From 1 to 10 m length scales, we explore traditional isostasy and identify a specific sequence of thickness calculations which minimize freeboard and elevation uncertainty. An effective solution exists when the R-factor is allowed to vary: ranging from 2 to 12, with mean of 5.17, mode of 5.88 and skewed distribution. At regional scales, underwater, airborne and spaceborne platforms are always missing thickness variables from either above or below sea level. For such situations, realistic agreement is found by applying small-scale skewed ranges for the R-factor. These findings encourage a broader isostasy solution as a function of potential energy and length scale. Overall, results add insight to data collection strategies and metadata characteristics of different thickness products.