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Based on ice maps of the Sea of Azov for 1993–2023 routinely compiled at the Hydrometcenter of Russia, nine winters with the most challenging ice conditions have been selected. For each of the winters, the features of ice formation, changes in ice characteristics, and possible reasons for the formation of challenging ice conditions are described. Data on the maximum thickness of fast ice in the winters under consideration from four hydrometeorological stations are presented, and a method for computing the spatial distribution of drifting ice thickness is proposed. By the example of the winter of 2016/2017, a change in ice thickness over time on the shipping route from the Taganrog Bay to the Kerch Strait is studied.

A Fast Ice Prediction System (FIPS) was constructed and is the first regional land-fast sea-ice forecasting system for the Antarctic. FIPS had two components: (1) near-real-time information on the ice-covered area from MODIS and SAR imagery that revealed, tidal cracks, ridged and rafted ice regions; (2) a high-resolution 1-D thermodynamic snow and ice model (HIGHTSI) that was extended to perform a 2-D simulation on snow and ice evolution using atmospheric forcing from ECMWF: either using ERA-Interim reanalysis (in hindcast mode) or HERS operational 10-day predictions (in forecast mode). A hindcast experiment for the 2015 season was in good agreement with field observations, with a mean bias of 0.14 ± 0.07 m and a correlation coefficient of 0.98 for modeled ice thickness. The errors are largely caused by a cold bias in the atmospheric forcing. The thick snow cover during the 2015 season led to modeled formation of extensive snow ice and superimposed ice. The first FIPS operational service was performed during the 2017/18 season. The system predicted a realistic ice thickness and onset of snow surface melt as well as the area of internal ice melt. The model results on the snow and ice properties were considered by the captain of R/V Xuelong when optimizing a low-risk route for on-ice transportation through fast ice to the coastal Zhongshan Station.

Based on satellite remote sensing, several polynyas have been found in Prydz Bay, East Antarctica. Compared with the Mackenzie Bay Polynya, the only polynya in the west, the polynyas in eastern Prydz Bay have a larger area and higher ice production, but have never been studied individually. In this study, four recurrent polynyas were identified in eastern Prydz Bay from sea ice concentration data during 2002–2011. Their areas generally exhibit synchronous temporal variations and have good correlation with wind speed, which indicates that they are primarily wind-driven polynyas that need at least one stationary ice barrier to block the inflow of drifting sea ice. The components of the ice barriers of these four polynyas were identified through comparison of satellite remote sensing visible images and synthetic aperture radar images. All types of fast ice, including landfast ice, offshore fast ice and ice fingers serving as ice barriers for these polynyas are anchored by an assemblage of small icebergs and have an approximately year-round period of variations that also regulates the variability of polynyas. The movement and grounding of giant icebergs near the polynyas significantly affects the development of the polynyas. The results of this study illustrate the important impact of icebergs on Antarctic wind-driven polynyas and the formation of dense shelf water.

The White Sea is a unique marine environment combining features of temperate and Arctic seas. The composition and abundance of photosynthetic picoeukaryotes (PPEs) were investigated in the land-fast ice of the White Sea, Russia, in March 2013 and 2014. High-throughput tag sequencing (Illumina MiSeq system) of the V4 region of the 18S rRNA gene was used to reveal the diversity of PPE ice community. The integrated PPE abundance varied from 11 × 10⁶ cells/m² to 364 × 10⁶ cells/m²; the integrated biomass ranged from 0.02 to 0.26 mg C/m². The composition of seaice PPEs was represented by 16 algae genera belonging to eight classes and three super-groups. Chlorophyta, especially Mamiellophyceae, dominated among ice PPEs. The detailed analysis revealed the latent diversity of Micromonas and Mantoniella. Micromonas clade E2 revealed in the subarctic White Sea ice indicates that the area of distribution of this species is wider than previously thought. We suppose there exists a new Micromonas clade F. Micromonas clade C and Minutocellulus polymorphus were first discovered in the ice and extend the modern concept of sympagic communities’ diversity generally and highlights the importance of further targeting subarctic sea ice for microbial study.

Compact Polarimetric (CP) Synthetic Aperture Radar (SAR) is expected to gain more and more ground for Earth observation applications in the coming years. This comes in light of the recently launched RADARSAT Constellation Mission (RCM), which uniquely provides CP SAR imagery in operational mode. In this study, we present observations about the sensitivity of CP SAR imagery to thickness of thermodynamically-grown fast sea ice during early ice growth (September–December 2017) in the Resolute Bay area, Canadian Central Arctic. Fast ice is most suitable to use for this preliminary study since it exhibits only thermodynamic growth in absence of ice mobility and deformation. Results reveal that ice thickness up to 30 cm can be retrieved using several CP parameters from the tested set. This ice thickness corresponds to the thickness of young ice. We found the surface scattering mechanism to be dominant during the early ice growth, exposing an increasing tendency up to 30 cm thickness with a correlation coefficient with the thickness equal to 0.86. The degree of polarization was found to be the parameter with the highest correlation up to 0.95. While thickness retrieval within the same range is also possible using parameters from Full Polarimetric (FP) SAR parameters as shown in previous studies, the advantage of using CP SAR mode is the much larger swath coverage, which is an operational requirement.

Basal melt of ice shelves is not only an important part of Antarctica's ice sheet mass budget, but it is also the origin of platelet ice, one of the most distinctive types of sea ice. In many coastal Antarctic regions, ice crystals form and grow in supercooled plumes of Ice Shelf Water. They usually rise towards the surface, becoming trapped under an ice shelf as marine ice or forming a semi-consolidated layer, known as the sub-ice platelet layer, below an overlying sea ice cover. In the latter, sea ice growth consolidates loose crystals to form incorporated platelet ice. These phenomena have numerous and profound impacts on the physical properties, biological processes and biogeochemical cycles associated with Antarctic fast ice: platelet ice contributes to sea ice mass balance and may indicate the extent of ice-shelf basal melting. It can also host a highly productive and uniquely adapted ecosystem. This paper clarifies the terminology and reviews platelet ice formation, observational methods as well as the geographical and seasonal occurrence of this ice type. The physical properties and ecological implications are presented in a way understandable for physicists and biologists alike, thereby providing the background for much needed interdisciplinary research on this topic.

In late March 2011, landfast sea ice (hereafter, “fast ice”) formed in the northern Larsen B embayment and persisted continuously as multi-year fast ice until January 2022. In the 11 years of fast-ice presence, the northern Larsen B glaciers slowed significantly, thickened in their lower reaches, and developed extensive mélange areas, leading to the formation of ice tongues that extended up to 16 km from the 2011 ice fronts. In situ measurements of ice speed on adjacent ice shelf areas spanning 2011 to 2017 show that the fast ice provided significant resistive stress to ice flow. Fast-ice breakout began in late January 2022 and was closely followed by retreat and breakup of both the fast-ice mélange and the glacier ice tongues. We investigate the probable triggers for the loss of fast ice and document the initial upstream glacier responses. The fast-ice breakup is linked to the arrival of a strong ocean swell event (>1.5 m amplitude; wave period waves >5 s) originating from the northeast. Wave propagation to the ice front was facilitated by a 12-year low in sea ice concentration in the northwestern Weddell Sea, creating a near-ice-free corridor to the open ocean. Remote sensing data in the months following the fast-ice breakout reveals an initial ice flow speed increase (>2-fold), elevation loss (9 to 11 m), and rapid calving of floating and grounded ice for the three main embayment glaciers Crane (11 km), Hektoria (25 km), and Green (18 km).

Creating accurate predictive models for drift and pack ice is crucial for a wide array of applications, from improving maritime operations to improving weather prediction and climate simulations. Traditional large‐scale sea ice dynamics models rely on phenomenological ice rheology to simulate ice movements. These models are efficient on large scales but struggle to depict smaller‐scale ice features. In our study, we use a new version of the HiDEM discrete element model software to examine the formation of drift and pack ice under various stress conditions. Our findings show that high‐resolution size distributions of ice floes are universal and multimodal, and that compression ridges form three distinct zones. Reproducing complex characteristics of this nature in a standard rheology model is challenging, suggesting that a combination of models may be necessary for more precise predictions of sea ice dynamics. We propose a potential hybrid algorithm that integrates these approaches. Plain Language Summary Sea ice forms in cold climates and is susceptible to being easily fragmented by wind and currents, resulting in a dynamic landscape comprising solid fast ice, drift ice and pack ice. Pack ice, in particular, can pose challenges such as hindering shipping, causing damage to offshore structures, and complicating traditional fishing and hunting activities. Operational models for sea ice dynamics are currently utilized to optimize ship routes and the deployment of icebreakers. Although existing rheology‐based models perform well on large scales, they encounter difficulties in capturing the finer details that are often crucial. In this study, we utilize a high‐resolution Discrete Element Model computer code that is capable of simulating detailed sea ice dynamics at scales ranging from meters to kilometers. Our simulation results reveal insights that are not readily obtained from conventional large‐scale models, and we explore the potential for integrating these two approaches to create a hybrid model. Key Points Ultra high‐definition simulation (0.5 m elements) of sea ice fragmentation on a square kilometer scale The HiDEM model captures in fine detail the formations of leads, pressure ridge networks, and floe‐size distributions The model reveals features that cannot be reproduced by rheological models, suggesting a hybrid method for prediction

Ice loss from the world’s glaciers and ice sheets contributes to sea level rise, influences ocean circulation, and affects ecosystem productivity. Ongoing changes in glaciers and ice sheets are driven by submarine melting and iceberg calving from tidewater glacier margins. However, predictions of glacier change largely rest on unconstrained theory for submarine melting. Here, we use repeat multibeam sonar surveys to image a subsurface tidewater glacier face and document a time-variable, three-dimensional geometry linked to melting and calving patterns. Submarine melt rates are high across the entire ice face over both seasons surveyed and increase from spring to summer. The observed melt rates are up to two orders of magnitude greater than predicted by theory, challenging current simulations of ice loss from tidewater glaciers.

Antifreeze proteins (AFPs) are a unique class of proteins that bind to growing ice crystal surfaces and arrest further ice growth. AFPs have gained a large interest for their use in antifreeze formulations for water-based materials, such as foods, waterborne paints, and organ transplants. Instead of commonly used colligative antifreezes such as salts and alcohols, the advantage of using AFPs as an additive is that they do not alter the physicochemical properties of the water-based material. Here, we report the first comprehensive evaluation of thermal hysteresis (TH) and ice recrystallization inhibition (IRI) activity of all major classes of AFPs using cryoscopy, sonocrystallization, and recrystallization assays. The results show that TH activities determined by cryoscopy and sonocrystallization differ markedly, and that TH and IRI activities are not correlated. The absence of a distinct correlation in antifreeze activity points to a mechanistic difference in ice growth inhibition by the different classes of AFPs: blocking fast ice growth requires rapid nonbasal plane adsorption, whereas basal plane adsorption is only relevant at long annealing times and at small undercooling. These findings clearly demonstrate that biomimetic analogs of antifreeze (glyco)proteins should be tailored to the specific requirements of the targeted application.