Ice Types Research Articles

A Spatio-Temporal Deep Learning Model for Automatic Arctic Sea Ice Classification with Sentinel-1 SAR Imagery

Arctic sea ice has a significant effect on global climate change, ship navigation, Arctic ecosystems, and human activities. Therefore, it is essential to produce high-resolution sea ice maps that accurately represent the geographical distribution of various sea ice types. Based on deep learning technology, many automatic sea ice classification algorithms have been developed using synthetic aperture radar (SAR) imagery over the last decade. However, sea ice classification faces two vital challenges: (1) it is difficult to distinguish sea ice types with close developmental stages solely from SAR images and (2) an imbalanced sea ice dataset has a significantly negative effect on ice classification model performance. In this article, a spatio-temporal deep learning model—the Dynamic Multi-Layer Perceptron (MLP)—is utilized to classify 10 sea ice types automatically. It consists of a SAR image branch and a spatio-temporal branch, which extracts SAR image features and spatio-temporal distribution characteristics of sea ice, respectively. By projecting similar image features to different positions in the spatio-temporal feature space dynamically, the Dynamic MLP model effectively distinguishes between similar sea ice types. Furthermore, to reduce the impact of data imbalance on model performance, the dynamic curriculum learning (DCL) method is used to train the Dynamic MLP model. Experimental results demonstrate that our proposed method outperforms the long short-term memory (LSTM) network approach in distinguishing between sea ice types with similar developmental stages. Moreover, the DCL training method can also effectively improve model performance in identifying minority ice types.

Microplastics in Southern Ocean sea ice: a pan-Antarctic perspective

Microplastic (MP; plastic particles < 5 mm) pollution is pervasive in the marine environment, including remote polar environments. This study provides the first pan-Antarctic survey of MP pollution in Southern Ocean sea ice by analyzing sea ice cores from several diverse Antarctic regions. Abundance, chemical composition, and particle size data were obtained from 19 archived ice core samples. The cores were melted, filtered, and chemically analyzed using Fourier-transform infrared spectroscopy and 4,090 MP particles were identified. Nineteen polymer types were found across all samples, with an average concentration of 44.8 (± 50.9) particles·L-1. Abundance and composition varied with ice type and geographical location. Pack ice exhibited significantly higher particle concentrations than landfast ice, suggesting open ocean sources of pollution. Winter sea ice cores had significantly more MPs than spring and summer-drilled cores, suggesting ice formation processes play a role in particle incorporation. Smaller particles dominated across samples. Polyethylene (PE) and polypropylene (PP) were the most common polymers, mirroring those most identified across marine habitats. Higher average MP concentrations in developing sea ice during autumn and winter, contrasting lower levels observed in spring and summer, suggest turbulent conditions and faster growth rates are likely responsible for the increased incorporation of particles. Southern Ocean MP contamination likely stems from both local and distant sources. However, the circulation of deep waters and long-range transport likely contribute to the accumulation of MPs in regional gyres, coastlines, and their eventual incorporation into sea ice. Additionally, seasonal sea ice variations likely influence regional polymer compositions, reflecting the MP composition of the underlying waters.

NUMERICAL MODELING OF WAVE-ICE INTERACTION WITH A SINGLE SUPPORT

The change in the joint wave-ice load acting on a freestanding hydraulic structure under conditions of ice freezing to the support is considered. The existing scientific works on this problem were analyzed and the appropriate research method was chosen. The topic of the article is relevant in the light of active development of the Arctic part of Russia and construction of new hydraulic structures, which require more accurate methods of determining ice and wave loads. The novelty of the work lies in the analysis of the joint impact of the wave and ice floe on the structure. Numerical modeling in LS-DYNA program and analytical methods presented in normative documents were used for the study. Verification of the model by loads was performed by comparing numerical data with the results of analytical calculation. Changes in the horizontal forces of wave and ice floe pressure on the structure, as well as the wave impact on the ice floe were obtained. Dependences of changes in these forces and their ratios on the ice floe length were plotted. In the course of analyzing the results it was determined that the ice floe pressure force on the structure changes most significantly. The cyclic character of changes in the wave and ice forces was also revealed. Presumably, this is due to the dynamic nature of ice breakup and the effect of "ice floe surfacing-submergence". In further research, it is recommended to apply the developed model for different scenarios involving other types of ice and types of structures. The results of the paper can be used to develop more accurate methods for analytical calculation of the impact of waves and ice on structures.

A review of photothermal and superhydrophobic polymer nanocomposites as anti‐icing nanocoatings

AbstractFreezing and ice formation at low temperatures have always caused numerous challenges in variant crafts such as aeronautical, transportation, power lines, oil platforms, etc. Anti‐icing and de‐icing approaches have been employed to reduce the contrary results of icing on surfaces. Due to the disadvantages of de‐icing methods, anti‐icing techniques are noteworthy, and extensive research has been done in this field. Anti‐icing techniques have been used to prevent ice accumulation or simplify separating once the ice has formed. Superhydrophobicity has the property that can neglect to ice or delay icing on the surface. Nowadays, nanocomposites, one of the most extremely used advanced substances, are used in various industries and usages. In the meantime, polymer nanocomposites as a nanocoating offer innovative solutions for the icing phenomenon by bridging the areas of polymer composite technology, nanoscience, and superhydrophobicity. Additionally, photothermal polymer nanocomposites are based on conventional superhydrophobic materials with high solar absorption rates and have unique anti‐icing properties. In this review, the types of ice were examined in terms of their appearance, formation order, and crystal structure. Also, various theories of wettability and freezing mechanisms were studied. Moreover, various methods of making surface superhydrophobic such as top‐down, and bottom‐top procedures were mentioned. Finally, superhydrophobic and photothermal polymer nanocomposite coatings were explained in‐depth.Highlights Types of ice and its structure were investigated. Kinds of wettability theories and freezing mechanisms were studied. Methods of ice formation prevention were summarized. Superhydrophobic and photothermal polymer nanocomposites were explained.

Development and validation of a global thin ice thickness algorithm for SMMR

Abstract Thin ice thickness algorithms using satellite passive microwave radiometers are frequently used to quantify sea ice production in coastal polynyas. The objective of this paper is to develop and validate a thin ice thickness algorithm using only low-frequency (LF) data (19 and 37 GHz channels), applicable back to 1978 when the Scanning Multichannel Microwave Radiometer (SMMR) observations started. We compared several recent satellite observations for 22 cases of typical polynya events in the Southern Ocean and developed a new method to discriminate three types of thin ice (active frazil, thin solid ice, and a mixture of the two) using only LF data. Combined with ice type discrimination, the obtained LF ice thickness (20 cm or less) has a bias of less than 1 cm and an RMSD of about 5 cm, as shown by validation data from 24 cases of typical polynya events that occurred prior to 1992 in the Southern Ocean and the Bering Sea. Although the error in ice type discrimination with LF data is relatively large in comparison with previous studies, these results still suggest that the LF ice thickness could be a continuous global data since 1978. We also developed a false thin ice detection algorithm using only LF data and created daily false thin ice masks from 1978 to the present, which are also essential for estimating global sea ice production. The use of our new LF algorithm will allow quantification of the global sea ice production over nearly half a century since 1978.

Experimental and theoretical studies of sea ice effects on internal solitary waves

Internal solitary waves in polar regions have attracted much interest recently. It is important to understand how sea ice affects them as this may have a profound influence on human activities and the environment. In this study, experiments on internal solitary waves with and without two types of sea ice (ice sheet and ice keel) are presented, as well as corresponding simulations using the Korteweg-de Vries (KdV) equation, the Benjamin-Ono (BO) equation, and the variable-coefficient Korteweg-de Vries (vKdV) equation, which is a derivation of the KdV equation. Comparison between experiments without sea ice and simulations using the KdV and BO equations proves the suitability of the former over the latter for this study. The experiments with sea ice and theoretical simulations using the vKdV equation provide evidence for wave deformation, oscillation occurring in the rear of the wave, and a decrease in amplitude. The latter suggests possibilities of energy dissipation or the emission of small amplitude linear waves. The sharp vertices of the ice result in occasional inconsistency with the vKdV predictions. Nonetheless, the vKdV equation is still suitable for modeling internal solitary waves under sea ice, giving generally accurate results that can assist further studies. This is the first time the vKdV equation has been applied to investigate the impacts of sea ice on internal solitary waves.

Angular variation of SAR polarimetric parameters over multiyear ice

ABSTRACT Backscatter and derived parameters from Synthetic Aperture Radar (SAR) may vary across the swath as the incident angle increases from the near to the far range, especially in the ScanSAR mode. Previous studies characterize this angular variation in the form of linear regression for commonly used ice types, namely first-year (FYI) and multi-year (MYI). The present study took advantage of the appearance of three grounded multi-year ice floes, viewed at different radar incidence angles, in a series of 22 RADARSAT-2 fully-polarimetric images, acquired over the Resolute Passage in the Canadian Arctic, during the period from 21 October to 28 December 2017. The ice properties remained invariant during the observation period; hence, variation of radar parameters of MYI can be attributed to change of incidence angle only. Quantification of angular variation of the selected SAR parameters was performed. They include conventional orthogonal backscatter coefficients, derived parameters from the incoherent decomposition of Cloude-Pottier, Yamaguchi, and Touzi, as well as a set of parameters from the compact polarimetry mode. Results specify the parameters that reveal variation with incidence angle and present the linear regressions equations. The explanation for the behaviour of each parameter, in terms of showing or not showing an angular trend, is offered. Results will be useful when using the polarimetric parameters in the sea ice classification scheme.

Incidence angle dependency and seasonal evolution of L and C-band SAR backscatter over landfast sea ice

Abstract We estimate sea-ice type specific incidence angle (IA) dependencies for dual polarized (HH/HV) L and C-band synthetic aperture radar (SAR) for the winter, melt onset and advanced melt seasons for level and deformed ice, using time-series of Advanced Land Observing Satellite-2 (ALOS-2) and Sentinel-1 imagery off the north-east coast of Greenland. The IA dependencies are used to radiometrically correct the L and C-band backscatter time-series, which enables analysis of their seasonal evolution. From this, we observe that the L-band backscatter intensity increases for both ice types at the transition from winter to melt onset. We use these results to estimate ice type separability and to train an IA aware Bayesian classifier at both frequencies. These results show that while both frequencies are capable of distinguishing level and deformed ice during the winter, only L-band SAR can reliably make this separation during the melt onset season. During the advanced melt season, the overall classification accuracies are similarly low for L and C-band. This study demonstrates the potential of L-band SAR for sea-ice mapping, which is highly relevant in the light of several upcoming L-band SAR missions.

1 h МҰЗ ТҮРІНІҢ (110-210) К ТЕМПЕРАТУРА МЕН (20-1350)∙106 ПА ҚЫСЫМ АРАЛЫҒЫНДАҒЫ КӨЛЕМІНІҢ ӨЗГЕРІСІН ЗЕРТТЕУ ӘДІСІ

The article examines the temperature-pressure dependence of the relative volume, Young's modulus and shear of the type of ice that crystallizes at normal pressure at temperatures below 273 K. Currently, there is a practical need to study the elastic properties of ice. The anomalous properties of water have their own benefits and harms. An increase in the volume of water when it enters the ice can destroy structures whose openings contain water in the fall. In addition, water, as a gas, liquid and solid, has a large number of minerals in the atmosphere, on the surface and in the interior of the Earth, so it has a great influence on our ecology, weather and the growth of living organisms.

Research on icing model and calculation methods

Aircraft icing seriously threatens flight safety. This paper describes a modified shallow-water icing thermodynamic model that is applicable to unstructured grids and considers the effects of changes in water physical parameters and sublimation on icing. An icing calculation method enables the automatic determination of whether freezing occurs and the type of icing. An autonomous icing calculation program is developed to extract the geometric coordinates and mesh information of the icing surface and combine this information with the multiphase flow field of air-supercooled water droplets. The icing equations in the Godnov format are discretized to produce a large-scale sparse matrix that is solved iteratively using the biconjugate gradient stabilized method. The output includes parameter distributions for the ice thickness, water film thickness, and equilibrium temperature. Taking the National Advisory Committee for Aeronautic 0012 airfoil as the study object, the results of icing simulations are compared with experimental data from an ice wind tunnel and the ice shapes calculated by the FENSAP-ICE software. The results are found to be in good agreement with the experimental data, and the ice height errors at stagnation points are less than 15%. In the case of rime ice, single-horned ice shapes are simulated for both conventional and large supercooled droplets. For mixed ice and glaze ice, double-horned ice shapes are simulated for both droplet conditions. FENSAP-ICE fails to simulate the ice horns and produces large errors in ice thickness and ice range.

Anti-icing performance and influencing factors of super-lubricated surface in simulated glaze icing

Abstract The icing of the overhead aluminum conductor has caused the conductor load to be too heavy or uneven, which results in huge accidents. The super-lubricated surface (SLIPS) shows great potential in anti-icing. Glaze ice is a common type of icing, and its damage to transmission lines is the most serious. However, the properties and influencing factors of anti-icing lubricated surfaces at glaze ice surroundings are rarely reported. In this study, the super-lubricated surface was prepared by the anodic oxidation method, and the anti-icing properties and influencing factors of surfaces were investigated in glaze ice surroundings. The results demonstrate that the SLIPS can decrease the icing amount, which is only 41% of the original aluminum surface. SLIPS exhibits excellent anti-icing performance in different environments temperatures and rainfalls. This study provides experimental guidance for the practice application of SLIPS in anti-icing aluminum conductors.

High strain-rate behavior of polycrystalline and granular ice: An experimental and numerical study

We study the stress–strain response of two different types of ice, viz. polycrystalline ice and granular ice, between −1° – 0 °C over a strain-rate range of 100s−1 to 300s−1 employing the split Hopkinson pressure bar (SHPB). Polycrystalline ice samples, prepared by freezing water in plastic moulds, exhibit a compressive strength ranging from 7 to 10 MPa within the considered strain-rate range. The strain at peak stress remains below 0.2%, indicating brittle behavior. The stress-strain curve of polycrystalline ice displays a prolonged tail, suggesting that the damaged ice specimen retains some strength. High-speed imaging during tests reveals the damage mechanism in ice is fragmentation and axial splitting. A user subroutine based on the Johnson–Holmquist II (JH-2) model is implemented in the commercial finite element (FE) software ABAQUS to predict ice's response at high strain-rates, which captures the softening present in the experimental stress–strain curve. Intact strength parameters and strain-rate sensitivity constants in the JH-2 model are determined from our experimental data and literature results, ensuring alignment with experimental peak stress. Fractured strength and damage evolution parameters are determined by matching post-peak responses from simulations to experiments. Temporal damage evolution from FE simulations aligns well with high-speed images from experiments, providing additional validation. Extending the study to granular ice, samples are prepared by crushing polycrystalline ice and refreezing it. The compressive strength of granular ice at a nominal strain-rate of 200±50s−1 is found to be 4±0.7 MPa. The granular ice, which is a mixture of polycrystalline ice and voids, is homogenized using rule-of-mixture to obtain the elastic properties. The FE simulation results utilizing the JH-2 parameters that we determine matches well with the experimental data, demonstrating that the JH-2 model is well suited to predict the high strain-rate behavior of both types of ice.

Modelling climate change impacts on lake ice and snow demonstrates breeding habitat decline of the endangered Saimaa ringed seal

Snowdrifts on lake ice provide vital breeding habitats for the endangered Saimaa ringed seal. In this study, a lake ice model of Watershed Simulation and Forecasting System (WSFS-Ice) was developed for improved estimation of ice and snow conditions in Lake Saimaa during the pupping season of the Saimaa ringed seal. The WSFS-Ice model is based on energy balance, enabling reliable estimation of the ice cover evolution in current and future climate. In addition, a simple snowdrift model was used to simulate formation of snowdrifts, which are essential for the seals breeding success in Lake Saimaa. The model was calibrated against ice thickness, ice type and snow depth measurements. According to our results based on climate scenarios with intermediate representative concentration pathway (RCP4.5), the breeding habitat of the Saimaa ringed seal is significantly deteriorating during the twenty-first century. The mean depth of the snowdrifts is projected to decrease approximately to half from the 1981–2010 to 2070–99 period and at the same time the ice-covered period is reduced by one and a half months. During the mildest winters the ice cover is projected to melt even before the pupping season has ended. The results highlight the importance of climate change mitigation and active conservation measures to enhance seal population growth, enabling it to survive in a changing climate.

Hardware-in-the-Loop experiments in model ice for analysis of ice-induced vibrations of offshore structures

The study investigated the use of a Hardware-in-the-Loop (HiL) technique applied in model ice experiments to enable the analysis of offshore structures with low natural frequencies under dynamic ice loading. Traditional approaches were limited by facility capacities and ineffective downscaling of the geometry of the offshore structures. The goal of the present study was to overcome these challenges and to enhance the understanding and explore the applicability of a hybrid testing technique in model ice experiments. To achieve the objective, 204 Hardware-in-the-Loop simulations in model Ice (HiLI) were analyzed. Results showed robust behavior and good performance of the HiLI due to minimal variation in measured delay, normalized root mean square error, and peak tracking error and low magnitudes of such parameters despite alterations in factors such as the choice of the numerical structural model, physical prototype, measurement system, and ice type. Notably, the performance of the HiLI was affected when testing with warm model ice or scaling for harsh ice conditions, attributed to a reduced signal-to-noise ratio and instability of the system, respectively. Experimental identification of the critical delay, along with the application of an analytical stability criterion, revealed that the instability observed, was likely induced by reducing the structural stiffness of the numerical structural model to fulfil the scaling requirements when testing for harsh ice conditions. Additionally, the study showed improved HiLI performance when the physical prototype was in contact with the model ice. This observation was further analyzed and is assumed to be caused by the coupling between the ice and physical prototype, causing a coupled and thus increased eigenfrequency of the physical prototype-ice system.

River ice breakup classification using dual- (HH&HV) or compact-polarization RADARSAT Constellation Mission data

Ice jams and associated flooding during river ice breakup are seasonal hazards for many northern communities. Synthetic Aperture Radar (SAR) data enable timely monitoring of river ice conditions in inclement weather. River ice types and open water are discriminated during breakup using dual-polarized (HH&HV; DPH) and compact polarimetric (CP) C-band SAR imagery from the RADARSAT Constellation Mission (RCM). Study areas comprise nineteen locations on rivers in northern Ontario, the Northwest Territories, and Alberta, Canada. Rubble ice, sheet ice, and open water areas are sampled in RCM imagery using corroborating evidence from shoreline cameras and oblique airborne photography. Samples are obtained in the incidence angle range 19° to 48°, for open water with various wind speeds and flow conditions, and for rubble ice and sheet ice with varying surface roughness, snow cover, and wetness. Discrimination relies on a primary classification of rubble ice, sheet ice, and open water, and a secondary classification of ice roughness. The primary classification model development uses a recursive-partitioning machine-learning technique. Overall accuracies for the best DPH models are 83.8% to 89.6%, depending on image noise floor. DPH models use both HH and HV polarizations for low noise floor image modes, whereas only HH is used for higher noise floor image modes. The best CP model accuracy is 90.2%, using the RL, RR, and RVRH parameters. Secondary classification associates increasing ice roughness with increasing HH backscatter for DPH data, and with increasing RH backscatter for CP data. The angular dependencies of rubble ice or sheet ice are used to normalize backscatter, which is then divided into roughness categories. The DPH and CP classification models are named IceBC-DP and IceBC-CP, respectively. Qualitative analysis illustrates good overall ice type and open water classification. Confounding situations are mixed pixel issues, whitewater and wind roughening of water, moist snow microwave absorption, and superficial water on sheet ice. The development of robust methods for monitoring ice jam formation with RCM is an operational concern for departments within the Government of Canada and within Provincial and Territorial Governments.

Mechanistic investigation of nucleation kinetics in heterogeneous ice crystallization: the role of cooling rate, surface energy, surface nanostructure, and wetting state

The mechanism of nucleation in heterogeneous ice crystallization is important but remains unclear in spite of decades-long research. This study aims at investigating the nucleation kinetics in heterogeneous ice crystallization through molecular dynamics simulations, and comprehensively elucidating the effect of cooling rate, surface energy, surface nanostructure, and wetting state on the nucleation behaviours. More than 300 cases were simulated using monatomic water (mW) model based on a modified Stillinger-Weber (SW) potential. The dynamic nucleation and crystallization behaviours, along with the evolution of the largest ice nucleus, total ice clusters, kinetic energy, and interaction energy between nanodroplet and substrate, were investigated. Increasing the cooling rate and higher surface energy could promote the ice nucleation, but may lead to a tendency to transform into metastable interfacial ice and 4-coordinated molecule types, and create ice-free layer near the substrate due to the strong interaction strength. What's more, the effect of size match between the accessible width and ice lattice constant depends on the wetting states. In Cassie-Baxter state, the size match effect could promote the ice nucleation, while in Wenzel state it is not pronounced and decreasing the contact area by increasing the nanogroove width would inhibit the nucleation process. This work will be valuable in understanding the mechanism of nucleation kinetics in heterogeneous ice crystallization and provide guidance in promoting or inhibiting ice formation.

Sea ice concentration inversion based on different Arctic sea ice types

Sea ice concentration inversion based on different Arctic sea ice types

Dilute concentrations of maritime fuel can modify sediment reworking activity of high-latitude marine invertebrates.

Multiple expressions of climate change, in particular warming-induced reductions in the type, extent and thickness of sea ice, are opening access and providing new viable development opportunities in high-latitude regions. Coastal margins are facing these challenges, but the vulnerability of species and ecosystems to the effects of fuel contamination associated with increased maritime traffic is largely unknown. Here, we show that low concentrations of the water-accommodated fraction of marine fuel oil, representative of a dilute fuel oil spill, can alter functionally important aspects of the behaviour of sediment-dwelling invertebrates. We find that the response to contamination is species specific, but that the range in response among individuals is modified by increasing fuel concentrations. Our study provides evidence that species responses to novel and/or unprecedented levels of anthropogenic activity associated with the opening up of high-latitude regions can have substantive ecological effects, even when human impacts are at, or below, commonly accepted safe thresholds. These secondary responses are often overlooked in broad-scale environmental assessments and marine planning yet, critically, they may act as an early warning signal for impending and more pronounced ecological transitions.

Parametric investigation of aerodynamic performance degradation due to icing on a symmetrical airfoil

Ice accretion on lifting surfaces induces an aerodynamic penalty in lift and drag on an aircraft. This performance degradation depends on the geometric features, type, and surface characteristics of the accreted ice on the airfoil. In the present work, we propose a set of two-parameter, low-order models to represent some of the typical ice topologies: glaze, rime, and horn. The parametric space is swept for all types of ice to isolate the aerodynamic changes causing performance degradation on a canonical symmetrical airfoil, which is the representative airfoil used by the National Research Council of Canada's platform for ice accretion and coatings tests with ultrasonic readings platform for in-flight icing tests. The three ice topologies show a self-similar trend between the stall angle of attack and the ice thickness, with the horn-type of ice imparting the greatest drag and lift penalty due to strong boundary layer separation. The relative effect of ice roughness plays a secondary role in performance degradation, and in some cases, the roughness causes a thicker and more resilient boundary layer, which can, under very specific icing conditions, enhance the aerodynamic performance.

Photosynthetic processes in Antarctic sea ice during the spring melt

AbstractHigh‐latitude oceans experience strong seasonality where low light limits photosynthetic activity most of the year. This limitation is pronounced for algae within and underlying sea ice, and these algae are uniquely acclimated to low light levels. During spring melt, however, light intensity and daylength increase drastically, triggering blooms of ice algae that play important roles in carbon cycling and ecosystem productivity. How the algae acclimate to this dynamic and heterogeneous environment is poorly understood. Here, we measured 14C‐carbon fixation rates, photophysiology, and ribulose 1,5‐bisphosphate carboxylase oxygenase (Rubisco) content of sea‐ice algae in coastal waters near the western Antarctic Peninsula during spring, ranging from a low‐light‐acclimated, bottom community to a light‐saturated bloom. Carbon fixation rates by sea‐ice algae were similar to other Antarctic sea‐ice measurements (2–49 mg C m−2 d−1), and there was little phytoplankton biomass in the underlying water at the time of sampling. Net‐to‐gross ratios of carbon fixation were generally high and showed no relationship with ice type. We found algal photophysiology and Rubisco concentrations varied in relation to the different types of ice, altering the balance between the photochemical and biochemical processes that constrain carbon fixation rates. For algae inhabiting the bottom layers of sea ice, rates of carbon fixation were largely constrained by light availability whereas in surface seawater, interior and rotten/brash ice, carbon fixation rates could be calculated with reasonable accuracy from measurements of Rubisco concentrations. This work provides additional insight and means to evaluate carbon fixation rates as sea ice continues to change in future.