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.

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.

Snow ice (SI) forms from freezing wet snow, known as slush, and contributes to the thickness of level and brash ice. However, the mechanism of snow-slush-snow ice transformation has not been extensively investigated to date, despite the difference in the freezing rate of slush in comparison with water is important for estimating the ice thickness. In this study, we examined the growth of initial congelation ice (CI) and snow ice (SI) in a fresh water tank exposed to outdoor weather conditions in Luleå, northern Sweden. The tank of size 1.8 × 0.65 × 1.2 m in length, width and height was divided into two compartments to facilitate the simultaneous growth of CI and SI. A total of 12 experiments were conducted in the years 2021 and 2022. The transformation from slush to snow ice was achieved by submerging various amounts of snow in the compartments. It was observed that approximately 35% of the initial snow transformed into SI. Snow ice grew 4 mm°C−0.5 d−0.5 faster than congelation ice. The CI growth under SI was 1 mm°C−0.5 d−0.5 slower than the CI growth under CI. This study provides valuable insights for modelling snow-slush-snow ice transformation and designing future laboratory-scale experiments.

The seasonal ice-free period in the Hudson Bay Complex (HBC) has grown longer in recent decades in response to warming, both from progressively earlier sea-ice retreat in summer and later sea-ice advance in fall. Such changes disrupt the HBC ecosystem and ice-based human activities. In this study, we compare 102 simulations from 37 models participating in phase 6 of the Coupled Model Intercomparison Project to the satellite passive microwave record and atmospheric reanalyses. We show that, throughout the HBC, models simulate an ice-free period that averages 30 d longer than in satellite observations. This occurs because seasonal sea-ice advance is unrealistically late and seasonal sea-ice retreat is unrealistically early. We find that much of the ice-season bias can be linked to a warm bias in the atmosphere that is associated with a southerly wind bias, especially in summer. Many models also exhibit an easterly wind bias during winter and spring, which reduces sea-ice convergence on the east side of Hudson Bay and impacts the spatial patterns of summer sea-ice retreat. These results suggest that, for many models, more realistic simulation of atmospheric circulation would improve their simulation of HBC sea ice.

This study presents the first dataset of physical and textural properties of sea ice collected in the South Atlantic and Indian Ocean sector of the Antarctic marginal ice zone (MIZ). Observations of sea ice from this region in the austral spring 2019, including sea-ice core temperature, salinity, crystal size, texture, oxygen isotopes and stratigraphy, were used in conjunction with a Lagrangian back-tracking algorithm and atmospheric reanalyses. This method relates the reconstructed synoptic conditions to sea-ice growth along the transect. A significant difference was found between the stratigraphy of consolidated pack ice samples collected at the same latitude and spanning over 550 km eastwards. The eastward group was found to have more disturbances in their stratigraphy which is attributed to the highly variable atmospheric and sea-ice conditions together with varying wave penetration through the sea-ice pack, notably during the passage of an intense polar cyclone, while the westward group showed no signs of disturbance or deformation. These results indicate that consolidated Antarctic sea-ice floes of similar thickness and from the same latitude in the MIZ have distinct stratigraphic properties, which will influence their physical and biogeochemical features.

Sample collection and field studies of sea ice take place under harsh conditions which, combined with the logistical difficulties and high cost of voyages to the polar regions, limits the abilities of researchers to determine its properties. Observations of laboratory-grown sea ice can help quantify important sea-ice properties and incorporate them into numerical models. The growth of laboratory sea ice requires experimental set-ups that consider the complexity of sea-ice growth. Regulation and monitoring of environmental variables allow for growth and melt conditions to be controlled, manipulated and reproduced. Facilities thus vary widely because of differing research objectives. This paper presents a summary of some of the published sea-ice laboratories that study the physical properties of sea ice and an overview of their major design considerations, such as tank size, freezing method and instrumentation. It also discusses how these design considerations were implemented in the set-up of the new sea-ice growth laboratory at the Marine and Antarctic Research for Innovation and Sustainability. This paper should guide others in designing their facilities as well as in their understanding of other facilities for results comparison.

A precise knowledge of landfast sea-ice (fast-ice) thickness is relevant to many different disciplines. Sea Ice Monitoring Stations (SIMS) are used to measure time series of fast-ice thickness at a location. SIMS measure ice and ocean temperature via thermistor strings with many different methods for extracting sea-ice thickness from temperature existing. This study investigates: if thickness results from temperature recorded by SIMS of different designs, and analysed with different methods are comparable; which methods are recommended for their robustness, precision and accuracy and how they compare to independent thickness measurements; how otherwise unuseable data can be salvaged through specific SIMS designs. We present an analysis of fast-ice thickness calculated from SIMS deployed in McMurdo Sound, Antarctica and in the Chukchi Sea near Utqiaġvik, Alaska, over two decades. We find that median thicknesses derived by different methods agree within 1 ± 1.5 cm for McMurdo Sound and 2 ± 3 cm for Utqiaġvik. Thus, it is possible to confidently compare data collected from different stations and analysed with different methods. The vertical gradient of sea-ice temperature gives the best results for fast-ice thickness during the growth season and including standard resistors in a thermistor string can reduce potential data loss due to noise.

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.

We analysed the three-dimensional microstructure of sea ice by means of X-ray-micro computed tomography. Microscopic (brine- and air- pore sizes, numbers and connectivity) and macroscopic (salinity, density, porosity) properties of young Arctic sea ice were analysed. The analysis is based on ice cores obtained during spring 2016. Centrifuging of brine prior to CT imaging has allowed us to derive confident relationships between the open, vertically connected and total porosity of young sea ice at relatively high temperatures. We analysed the dependence of the microscopic properties on vertical position and total brine porosity. Most bulk properties (salinity, density) and pore space properties (pore sizes and their distribution) show a strong dependence on total brine porosity, but did not change significantly over the course of the field work. However, significant changes were observed for pore numbers (decreasing over time) and pore connectivity (increasing over time). CT-based salinity determinations are subject to larger than standard uncertainties (from conductivity), while the CT method yields important information about the salinity contributions from closed and open pores. We also performed a comparison of CT-based air porosity with calculations based on density from hydrostatic weighing. The consistency is encouraging and gives confidence to our CT-based results.

The inaugural data from the first systematic program of sea-ice observations in Kotzebue Sound, Alaska, in 2018 coincided with the first winter in living memory when the Sound was not choked with ice. The following winter of 2018–19 was even warmer and characterized by even less ice. Here we discuss the mass balance of landfast ice near Kotzebue (Qikiqtaġruk) during these two anomalously warm winters. We use in situ observations and a 1-D thermodynamic model to address three research questions developed in partnership with an Indigenous Advisory Council. In doing so, we improve our understanding of connections between landfast ice mass balance, marine mammals and subsistence hunting. Specifically, we show: (i) ice growth stopped unusually early due to strong vertical ocean heat flux, which also likely contributed to early start to bearded seal hunting; (ii) unusually thin ice contributed to widespread surface flooding. The associated snow ice formation partly offset the reduced ice growth, but the flooding likely had a negative impact on ringed seal habitat; (iii) sea ice near Kotzebue during the winters of 2017–18 and 2018–19 was likely the thinnest since at least 1945, driven by a combination of warm air temperatures and a persistent ocean heat flux.

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.

The Arctic sea-ice cover has undergone a significant decline in recent decades. The melt season is starting earlier, ice is thinner and seasonal ice dominates. Here we examine the effects of these changes on the solar heat input to the upper ocean in ice-covered Arctic waters from 1985 to 2014. Satellite observations of ice concentration, onset dates of melt and freeze-up and ice age, are combined with ice thicknesses from the PIOMAS model and incident solar irradiance from reanalysis products to calculate the contributions of open ocean and ice to the solar heat input in the upper ocean. Of the total, 86% of the area has positive trends for solar heat input to the ocean through leads due to decreases in ice concentration. Only 62% of the area shows positive trends of solar heat input to the ocean explicitly through the ice. Positive trends are due to thinning ice, while negative trends occur in regions where the ice-free season has lengthened. The annual total solar heat input to the ocean exhibits positive trends in 82% of the area. The spatial pattern of the cumulative annual total solar heat input is similar to the pattern of solar heat input directly to leads.

Clouds play an important role in the Arctic surface radiative budget, impacting the seasonal evolution of Arctic sea-ice cover. We explore the large-scale impacts of springtime and early summer (March through July) cloud and radiative fluxes on sea ice by comparing these fluxes to seasonal ice volume losses over the central Arctic basin, calculated for available observational years 2004–2007 (ICESat) and 2011–2017 (CryoSat-2). We also supplement observation data with sea-ice volume computed from the Pan-Arctic Ice–Ocean Modeling and Assimilation System (PIOMAS) during summer months. We find that the volume of sea ice lost over the melt season is most closely related to observed downwelling longwave radiation in March and early summer (June and July) longwave cloud radiative forcing, which together explain a large fraction of interannual variability in seasonal sea-ice volume loss (R2 = 0.71, p = 0.007). We show that downwelling longwave fluxes likely impact the timing of melt onset near the sea-ice edge, and can limit the magnitude of ice thickening from March to April. Radiative fluxes in June and July are likely critical to seasonal volume loss because modeled data show the greatest ice volume reductions occur during these months.

The widespread occurrence of snow-ice formation on the pack ice plays a critical role in the mass balance of Antarctic sea ice. The stable isotope composition, ice texture and salinity of eight ice cores, obtained from the Amundsen Sea during the Oden Southern Ocean 2010/11 expedition from late December 2010 to January 2011, were investigated to illustrate the snow-ice growth process and its contribution to sea-ice development. Most previous research has utilized δ18O as an index tracer to determine the percentages of core length that contain meteoric water, i.e. snow ice. However, this standard practice of snow-ice identification might be biased due to normally low-resolution isotopic measurements and mixing/diffusion processes between the snow ice and underlying ice layers. Snow-ice contributions in these ice cores based instead on an updated isotope mixing model are also presented. Depth profiles of ice texture and salinity are described to serve as representations of the structures of these ice cores. Our isotope mixing model produced an average of 15.9% snow-ice contribution for pack ice in the Amundsen Sea, and meteoric water occupying 40% of snow-ice mass for all ice stations. These results are compared to previous investigations of snow-ice occurrence around Antarctica.

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 Ross Sea is known for showing the greatest sea-ice increase, as observed globally, particularly from 1979 to 2015. However, corresponding changes in sea-ice thickness and production in the Ross Sea are not known, nor how these changes have impacted water masses, carbon fluxes, biogeochemical processes and availability of micronutrients. The PIPERS project sought to address these questions during an autumn ship campaign in 2017 and two spring airborne campaigns in 2016 and 2017. PIPERS used a multidisciplinary approach of manned and autonomous platforms to study the coupled air/ice/ocean/biogeochemical interactions during autumn and related those to spring conditions. Unexpectedly, the Ross Sea experienced record low sea ice in spring 2016 and autumn 2017. The delayed ice advance in 2017 contributed to (1) increased ice production and export in coastal polynyas, (2) thinner snow and ice cover in the central pack, (3) lower sea-ice Chl-a burdens and differences in sympagic communities, (4) sustained ocean heat flux delaying ice thickening and (5) a melting, anomalously southward ice edge persisting into winter. Despite these impacts, airborne observations in spring 2017 suggest that winter ice production over the continental shelf was likely not anomalous.

The surface flooding of Antarctic sea ice in summer covers 50% or more of the sea-ice area in the major summer ice packs, the western Weddell and the Bellingshausen-Amundsen Seas. Two CRREL ice mass-balance buoys were deployed on the Amundsen Sea pack in late December 2010 from the icebreaker Oden, bridging the summer period (January–February 2011). Temperature records from thermistors embedded vertically in the snow and ice showed progressive increases in the depth of the flooded layer (up to 0.3–0.35 m) on the ice cover during January and February. While the snow depth was relatively unchanged from accumulation (<10 cm), ice thickness decreased by up to a meter from bottom melting during this period. Contemporaneous with the high bottom melting, under-ice water temperatures up to 1°C above the freezing point were found. The high temperature arises from solar heating of the upper mixed layer which can occur when ice concentration in the local area falls and lower albedo ocean water is exposed to radiative heating. The higher proportion of snow ice found in the Amundsen Sea pack ice therefore results from both winter snowfall and summer ice bottom melt found here that can lead to extensive surface flooding.

Results examining variations in the ice extent along the Norwegian coastline based on the analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) images from 2001 to 2019, February through May, are presented. A total of 386 fjords and coastal areas were outlined and grouped into ten regions to assess seasonal and long-term trends in ice extent. In addition, three fjords were examined to investigate how ice extent may vary over short distances (<100 km). Of the 386 outlined, 47 fjords/coastal areas held >5 km2 of ice at least once between 2001 and 2019. Over this span of time, no statistically significant trend in ice extent is found for all ten regions; however, variations between regions and years are evident. Ice extent is assessed through comparison to three weather variables – freezing degree days (FDD), daily new snowfall and daily freshwater supply from rainfall plus snowmelt. Six out of ten regions are significantly positively correlated (p < 0.05) to FDD. In addition, ice in two regions is significantly positively correlated to daily new snowfall, and in one region negatively correlated to rainfall plus snowmelt. The importance of fjord geometry and bathymetry as well as other weather variables including wind is discussed.

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 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.