Search Results (801)

Ice accretion from marine icing events accumulating on structures poses a significant hazard to ship and offshore operations in cold regions, being relevant for offshore activities like oil explorations, offshore wind, and shipping in arctic regions. The adhesion strength of such ice is a critical factor in predicting the build-up of ice loads on structures. While the adhesion strength of freshwater ice has been extensively studied, knowledge about sea spray ice adhesion remains limited. This study intends to bridge this gap by investigating the adhesion strength of sea spray icing under controlled laboratory conditions. In this study, we built a new in situ ice adhesion test setup and grew ice at −7 °C to −15 °C on quadratic aluminium samples of 3 cm to 12 cm edge length. The results reveal that sea spray ice adhesion strength is in a significantly lower range—5 kPa to 100 kPa—compared to fresh water ice adhesion and shows a low dependency on the temperature during the spray event, but a notable size effect and influence of the brine layer thickness on the adhesion strength. These findings provide critical insights into sea spray icing, enhancing the ability to predict and manage ice loads in marine environments. Full article

The Arctic Ocean is turning blue. Abrupt Arctic warming and amplification is driving rapid sea ice decline and irreversible deglaciation of Greenland. The already emerging, substantial consequences for the planet and society are intensifying and yet, model-based projections lack validatory consensus. To date, we cannot anticipate how a blue Arctic will respond to and amplify an increasingly warmer future climate, nor how it will impact the wider planet and society. Climate projections are inconclusive as we critically lack key Arctic geological archives that preserved the answers. This “Arctic Challenge” of global significance can only be addressed by investigating the processes, consequences, and impacts of past “greenhouse” (warmer-than-present) climate states. To address this challenge, the ERC Synergy Grant project Into the Blue (i2B) is undertaking a program of research focused on retrieving new Arctic geological archives of past warmth and key breakthroughs in climate model performance to deliver a ground-breaking, synergistic framework to answer the central question: “Why and what were the global ramifications of a “blue” (ice-free) Arctic during past warmer-than-present climates?” Here, we present the proposed research plan that will be conducted as part of this program. Into the Blue will quantify cryosphere (sea ice and land ice) change in a warmer world that will form the scientific basis for understanding the dynamics of Arctic cryosphere and ocean changes to enable the quantitative assessment of the impact of Arctic change on ocean biosphere, climate extremes, and society that will underpin future cryosphere-inclusive IPCC assessments. Full article

This study evaluates machine learning-based methods for retrieving thin Arctic sea ice thickness (SIT) from L-band radiometry, using data from the European Space Agency’s (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite. In addition to the operational ESA product, three alternative approaches are assessed: a Random Forest (RF) algorithm, a Convolutional Neural Network (CNN) that incorporates spatial coherence, and a Long Short-Term Memory (LSTM) neural network designed to capture temporal coherence. Validation against in situ data from the Beaufort Gyre Exploration Project (BGEP) moorings and the ESA SMOSice campaign demonstrates that the RF algorithm achieves robust performance comparable to the ESA product, despite its simplicity and lack of explicit spatial or temporal modeling. The CNN exhibits a tendency to overestimate SIT and shows higher dispersion, suggesting limited added value when spatial coherence is already present in the input data. The LSTM approach does not improve retrieval accuracy, likely due to the mismatch between satellite resolution and the temporal variability of sea ice conditions. These results highlight the importance of L-band sea ice emission modeling over increasing algorithm complexity and suggest that simpler, adaptable methods such as RF offer a promising foundation for future SIT retrieval efforts. The findings are relevant for refining current methods used with SMOS and for developing upcoming satellite missions, such as ESA’s Copernicus Imaging Microwave Radiometer (CIMR). Full article

This review provides the recent advancements in nonlinear sea ice modeling for hydroelastic analysis of ice-covered channels and their interaction with floating structures. It surveys theoretical, experimental, and numerical methodologies used to analyze complex coupled sea ice–structure interactions. The paper discusses governing fluid domain solutions, fluid–ice interaction mechanisms, and ice–structure (ship) contact models, alongside experimental techniques and various numerical models. While significant progress has been made, particularly with coupled approaches validated by experimental data, challenges remain in full-scale validation and accurately representing ice properties and dynamic interactions. Findings highlight the increasing importance of understanding sea ice interactions, particularly in the context of climate change, Arctic transportation, and the development of very large floating structures. This review serves as a crucial resource for advancing safe and sustainable Arctic and offshore engineering. Full article

The presence of sea ice threatens low ice-class vessels’ navigation safety in the Arctic, and traditional Navigation Risk Assessment Models based on sea ice parameters have been widely used to guide safe passages for ships operating in ice regions. However, these models mainly rely on empirical coefficients, and the accuracy of these models in identifying sea ice navigation risk remains insufficiently validated. Therefore, under the binary classification framework, this study used Automatic Identification System (AIS) data along the Northeast Passage (NEP) as positive samples, manual interpretation non-navigable data as negative samples, a total of 10 machine learning (ML) models were employed to capture the complex relationships between ice conditions and navigation risk for Polar Class (PC) 6 and Open Water (OW) vessels. The results showed that compared to traditional Navigation Risk Assessment Models, most of the 10 ML models exhibited significantly improved classification accuracy, which was especially pronounced when classifying samples of PC6 vessel. This study also revealed that the navigability of the East Siberian Sea (ESS) and the Vilkitsky Strait along the NEP is relatively poor, particularly during the month when sea ice melts and reforms, requiring special attention. The navigation risk output by ML models is strongly determined by sea ice thickness. These findings offer valuable insights for enhancing the safety and efficiency of Arctic maritime transport. Full article

Underwater explosion ice-breaking technology is critical for Arctic development and ice disaster prevention due to its high efficiency, yet it faces challenges in understanding the coupled dynamics of shock waves, pulsating bubbles, and heterogeneous ice fracture. This review synthesizes theoretical models, experimental studies, and numerical simulations investigating damage mechanisms. Key findings establish that shock waves initiate brittle fracture via stress superposition while bubble pulsation drives crack propagation through pressure oscillation; optimal ice fragmentation depends critically on charge weight, standoff distance, and ice thickness. However, significant limitations persist in modeling sea ice heterogeneity, experimental replication of polar conditions, and computational efficiency. Future advancements require multiscale fluid–structure interaction models integrating brine migration effects, enhanced experimental diagnostics for transient processes, and optimized numerical algorithms to enable reliable predictions for engineering applications. Full article

With the natural evolution of the Arctic route and advancements in related technologies, the development of new green ice-class ships is becoming a key technological breakthrough for the global shipbuilding industry. As a special vessel form that must perform icebreaking operations and undertake long-distance ocean voyages, an ice-class ship requires sufficient icebreaking capacity to navigate ice-covered water areas. However, since such ships operate for most of their time under open water conditions, it is also crucial to consider their resistance characteristics in these environments. Firstly, this paper employs linear interpolation to extract wind, wave, and sea ice data along the route and calculates the proportion of ice-covered and open water area in the overall voyage. This provides data support for hull form optimization based on real sea state conditions. Then, a resistance optimization platform for ice-class ships is established by integrating hull surface mixed deformation control within a scenario analysis framework. Based on the optimization results, comparative analysis is conducted between the parent hull and the optimized hull under various environmental resistance scenarios. Finally, the optimization results are evaluated in terms of energy consumption using a fuel consumption model of the ship’s main engine. The optimized hull achieves a 16.921% reduction in total resistance, with calm water resistance and wave-added resistance reduced by 5.92% and 27.6%, respectively. Additionally, the optimized hull shows significant resistance reductions under multiple wave and floating ice conditions. At the design speed, calm water power and hourly fuel consumption are reduced by 7.1% and 7.02%, respectively. The experimental results show that the hull form optimization process in this paper can take into account both ice-region navigation and ice-free navigation. The design ideas and solution methods can provide a reference for the design of ice-class ships. Full article

The observations of atmospheric, oceanic, and sea ice data from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition were used to analyze the influence of snow redistribution and melt-pond processes on the evolution of sea ice thickness (SIT) in 2019 and 2020. To mitigate the effect of missing atmospheric observations from the time of the expedition, we used ERA5 atmospheric reanalysis along the MOSAiC drift trajectory to force the single-column sea ice model Icepack. SIT simulations from six combinations of two melt-pond schemes and three snow-redistribution configurations of Icepack were compared with observations and analyzed to investigate the sources of model–observation discrepancies. The three snow-redistribution configurations are the bulk scheme, the snwITDrdg scheme, and one simulation conducted without snow redistribution. The bulk scheme describes snow loss from level ice to leads and open water, and snwITDrdg describes wind-driven snow redistribution and compaction. The two melt-pond schemes are the TOPO scheme and the LVL scheme, which differ in the distribution of melt water. The results show that Icepack without snow redistribution simulates excessive snow–ice formation, resulting in an SIT thicker than that observed in spring. Applying snow-redistribution schemes in Icepack reduces snow–ice formation while enhancing the congelation rate. The bulk snow-redistribution scheme improves the SIT simulation for winter and spring, while the bias is large in simulations using the snwITDrdg scheme. During the summer, Icepack underestimates the sea ice surface albedo, resulting in an underestimation of SIT at the end of simulation. The simulations using the TOPO scheme are characterized by a more realistic melt-pond evolution compared to those using the LVL scheme, resulting in a smaller bias in SIT simulation. Full article

Ice wedges, which are ubiquitous in permafrost areas, play a significant role in the evolution of permafrost landscapes, influencing the topography and hydrology of these regions. In this paper, we combine a detailed multi-generational, interdisciplinary, and international literature review along with our own field experiences to explore the development of low-centered ice-wedge polygons and their orthogonal networks. Low-centered polygons, a type of ice-wedge polygonal ground characterized by elevated rims and lowered wet central basins, are critical indicators of permafrost conditions. The formation of these features has been subject to numerous inconsistencies and debates since their initial description in the 1800s. The development of elevated rims is attributed to different processes, such as soil bulging due to ice-wedge growth, differential frost heave, and the accumulation of vegetation and peat. The transition of low-centered polygons to flat-centered, driven by processes like peat accumulation, aggradational ice formation, and frost heave in polygon centers, has been generally overlooked. Low-centered polygons occur in deltas, on floodplains, and in drained-lake basins. There, they are often arranged in orthogonal networks that comprise a complex system. The prevailing explanation of their formation does not match with several field studies that practically remain unnoticed or ignored. By analyzing controversial subjects, such as the degradational or aggradational nature of low-centered polygons and the formation of orthogonal ice-wedge networks, this paper aims to clarify misconceptions and present a cohesive overview of lowland terrain ice-wedge dynamics. The findings emphasize the critical role of ice wedges in shaping Arctic permafrost landscapes and their vulnerability to ongoing climatic and landscape changes. Full article

At present, sea ice remains a critical factor affecting the safety of vessel operations along the Northern Sea Route (NSR). However, inconsistencies between the navigability outcomes derived from the criteria for the admission of ships in the area of the Northern Sea Route (NSR criteria) and the polar operational limit assessment risk indexing system (POLARIS) methodology present challenges for navigational decision-making. This study aims to conduct a systematic comparison of the POLARIS methodology and the NSR criteria in evaluating the navigability of independently operating vessels classified as Arc4 to Arc9. Through comparative calculations of navigability and the navigability rates for six ice-class vessels across 27 districts using the two methods, this study reveals the consistencies and discrepancies in their navigability outcomes. Firstly, using the POLARIS methodology, the risk index outcome (RIO) is calculated for six ice-class vessels across 27 districts. For these districts, the navigability threshold is defined when 95% or more of the area exhibits an RIO greater than or equal to zero. Secondly, using the NSR criteria, navigability ratios for six ice-class vessels under varying ice conditions are evaluated. A navigability threshold is defined when 95% or more of the ice conditions in a district are classified as navigable. Finally, a quantitative comparison of the weekly navigability ratios obtained by the two methods is conducted to reveal the consistencies and discrepancies in the navigability outcomes of each ice-class vessel across different NSR districts. The results indicate that the consistency between the navigability outcomes of the two methods decreases with lower vessel ice classes, particularly in September and March. In general, the consistency of performance between the two methods in terms of navigability outcomes deteriorates as the vessel ice class decreases and ice conditions become more complex. This study provides a scientific foundation and data-based support for route planning and real-time decision-making in polar waters. Full article

There are very few data linking recent climatic changes to changes in biological communities in the Russian Arctic, and no palaeoecological data are available from the Novaya Zemlya archipelago (NZ). We studied chironomid, cladoceran, and diatom communities from a 165-year-old sediment core from a lake on Southern Island, NZ. Sixteen diatom and four cladoceran species new to NZ were found in the lake. Significant changes occurred in biological communities; species turnover was highest for diatoms (2.533 SD), followed by chironomids (1.781 SD) and cladocerans (0.614 SD). Biological communities showed a correlation with meteorologically recorded climate parameters. For chironomids, the strongest relationships were found for T_June, T_July, and T_ann. Both planktonic proxies, diatoms, and cladocerans showed a relationship with summer and annual air temperature and precipitation. The largest shifts in communities can be linked to recent climatic events, including the onset of steady warming following the variable conditions at the end of the LIA (ca. 1905), the cooling associated with the highest precipitation on record between 1950 and 1970, and, probably, the anthropogenic influence specific to Novaya Zemlya at this time. The new data provide a valuable basis for future ecological studies in one of the least explored and remote Arctic regions. Full article

The Arctic ice layer serves as an excellent cover for strategic nuclear submarine forces, but it also poses significant challenges when submarines surface. This paper proposes a method for breaking through the ice layer and surfacing in polar environments based on the principle of resonance. This method eliminates the need for direct contact between the submarine and the ice layer, solving the current issues with submarine ice-breaking methods that demand high strength from the submarine and pose risks to both the submarine and its crew. Through theoretical analysis, numerical simulation and experimental verification, the vibration characteristics and fracture mechanism of the ice layer under the action of excitation loads were studied. Experiments showed that when the excitation frequency matched the fundamental eigenfrequency Ω1 of the ice layer, obvious resonance occurred and cracks appeared in the ice layer. A dynamic model of the ice layer was established using Abaqus software, and modal extraction and stress analysis were carried out. The error between the Ω1 obtained by numerical simulation and the experimental results was only 0.53%, verifying the reliability of the model. After applying the excitation load with a frequency of Ω1, the stress in the ice layer gradually expanded to the strength limit of the ice, achieving an ice-breaking effect consistent with the experimental results. Experimental and simulation results showed that the use of Ω1 for resonance ice-breaking had the best effect. When the ice layer resonated, the stress increased first and then stabilized, and cracks occurred before the stress stabilized to achieve the ice-breaking effect. Full article

Ubiquitous and accelerating mass loss from the Greenland Ice Sheet (GrIS) has been widely reported in recent scientific studies, implying rapid changes in the Arctic cryosphere. However, while numerous studies provide accounts of glacial mass loss and consequent sea level change, a qualitative assessment of the implications is conspicuously absent. This scoping review addresses that gap by synthesizing the recent scientific literature related to cryospheric change in Greenland and its implications for key species and ecological processes; and highlights the necessity of understanding the bigger picture of how multiple ecological processes, abiotic-biotic assemblages, and cryosphere-human interactions with the environment are rapidly changing and pushing the Arctic into a possible no-analog scenario in recent geological times. It is also argued that this situation presents a novel challenge for planetary sustainability and warrants the identification of new research priorities that can generate a holistic understanding of the complexity of the Arctic cryosphere, interactions between biotic and abiotic components, and local lifeworlds—all of which are related to the well-being of the Earth itself. Full article

In this paper, the time-series model is used to predict whether an ocean buoy is about to be inside a vortex. Marine buoys are an important tool for collecting ocean data and studying ocean dynamics, climate change, and ecosystem health. A vortex is an important ocean dynamic process. If we can predict that a buoy is about to enter a vortex, we can automatically adjust the buoy’s sampling frequency to better observe the vortex’s structure and development. To address this requirement, based on the profile data, including latitude and longitude, temperature, and salinity, collected by 56 buoys in the Arctic Ocean from 2014 to 2023, this paper uses the TSMixer time-series model to predict whether an ocean buoy is about to be inside a vortex. The TSMixer model effectively captures the spatio-temporal characteristics of multivariate time series through time-mixing and feature-mixing mechanisms, and the accuracy of the model reaches 84.6%. The proposed model is computationally efficient and has a low memory footprint, which is suitable for real-time applications and provides accurate prediction support for marine monitoring. Full article

Due to global warming, ozone depletion and their ramifications on the Arctic and Antarctic snowscapes, there has been an incentivized drive towards net zero-carbon emission policies by several countries. These policies extend to several sectors, including several manufacturing and processing industries and transportation, which are a few of their notable stakeholders. In the transportation sector, this journey towards net zero-carbon emissions is aided by the adoption of battery electric vehicles (BEVs) due to their zero-carbon emissions during operation. However, they might have zero running emissions, but they do have emissions when charging through conventional sources. This research paper looks at the carbon emissions produced by both electric vehicles (EVs) and internal combustion engine (ICE) vehicles during their operational stages and compares them based on a 200,000 km driving range, battery manufacturing emissions and different power production alternatives to draw up some very important recommendations. The analysis presented in this paper helps in drawing conclusions and proposes ideas which, when included in transport policies, will help curb global warming and eventually lead to the sustainable development of the transport sector. The analysis in this study shows that the emissions needed to produce a single battery unit have increased by approximately 258.7% with the change in battery production locations. Furthermore, charging EVs with a fossil-fuel-dominated grid has shown an increase in emissions of 17.98% compared to the least emissive ICE car considered in the study. Finally, policy update recommendations which are essential for the sustainable development of the transport sector are discussed. Full article