Thin First-year Ice Research Articles

Possibilities of investigating ice development of the Kara sea based on CryoSat-2 and SMOS data

Sea ice age is a proxy for thickness, which can be obtained through the use of satellite data. The paper presents the results of comparison of CryoSat-2, SMOS and CryoSat-2 & SMOS fusion data with detailed ice charts (October–April, 2010–2018). The AARI ice charts were chosen as references for comparison because they integrate knowledge and data from various sources, including expert analysis of operational satellite information, in-situ measurements at coastal stations, data on ice conditions from ships of the Northern Sea Route (NSR). The division of satellite data elements into classes (stages of development) was performed according to the maximum likelihood classifier. The recognition result for each stage of development was evaluated by means of three criteria, in accordance with the class value of Mode, Median and Mean. The effectiveness of satellite data in determining the Kara Sea ice thickness varies depending on the sea ice stage of development and winter season time. Four stages of development (old ice, thick first-year ice, medium first-year ice, nilas) showed the best recognition results. Although the CryoSat-2 mission was designed primarily to detect climate-dependent variations of the thickness of floating ice, in terms of statistical recognition of the Kara Sea ice stages of development, CryoSat-2 data can also be used to retrieve the thickness of thick first-year ice (January–April) and the thickness of medium first-year ice (January–February). For the remaining stages within the study area, the altimetry method shows a significant uncertainty, which can be resolved for nilas, thin first-year ice and medium first-year ice (March) by using SMOS data and CryoSat-2 & SMOS fusion data. In general, altimetric data, radiometric data and combination thereof can be applied in the complex analysis of all available information to ensure hydrometeorological and navigation support. Also, it is proposed to use the data of the ICESat-2 laser altimeter and to make a general comparison with in-situ measurements.

Wintertime Emissivities of the Arctic Sea Ice Types at the AMSR2 Frequencies

The surface effective emissivities of Arctic sea ice are calculated using Advanced Microwave Scanning Radiometer 2 (AMSR2) measurements. These emissivities are analyzed for stable winter conditions during the months of January–May and November and December of 2020 for several main sea ice types defined with the sea ice maps of the Arctic and Antarctic Research Institute (AARI). The sea ice emissivities are derived from the AMSR2 data using the radiation transfer model for a non-scattering atmosphere and ERA5 reanalysis data. The emissivities are analyzed only for areas of totally consolidated sea ice of definite types. Probability distribution functions are built for the emissivities and their functions for such sea ice types as nilas, young ice, thin first-year (FY) ice, medium FY ice, thick FY ice and multi-year ice. The emissivity variations with frequency are estimated for each of the considered sea ice type for all seven months. The variations are calculated both for the emissivities and for their gradients at the AMSR2 channel frequencies. Obtained emissivities turned out to be generally lower than reported previously in scientific studies, whereas the emissivity variability values proved to be much larger than was known before. For all FY ice types, at all the frequencies, an increase in the emissivity at the beginning of winter and its decrease by the end of May are observed. The emissivity gradients demonstrate noticeable decreases with sea ice age, and their values may be used in sea ice classification algorithms based on the AMSR2 data.

Lightweight Structural Concepts in Bearing Quasi-Static Ice Hull Interaction Loads

Lightweight ice-class vessels offer the possibility of increasing the payload capacity while making them comparable in energy consumption with non-ice-class vessels during ice-free periods. We approach the development of a lightweight hull by dividing ice–hull interactions into quasi-static loading and impact loading phases. Then, investigative outcomes of lightweight concepts for each loading phase may be combined to develop a lightweight ice-going hull. In this study, we focus on the quasi-static loading phase characteristic of thin first-year ice in inland waterways. We investigate metal grillages, sandwich structures and stiffened sandwich structures parametrically using the finite element method. The model is validated using previous experimental studies. In total over 2000 cases are investigated for strength and stiffness with respect to mass. The stiffened sandwich was found to be the most favorable concept that offered both a light weight as well as high gross tonnage. Further, significant parameters and their interactions and material differences for the three structural concepts were investigated and their trends discussed. The outcomes result in the creation of a viable pool of lightweight variants that fulfill the quasi-static loading phase. Together with outcomes from the impact loading phase, a lightweight ice-going hull may be developed.

An Improved Sea Ice Classification Algorithm with Gaofen-3 Dual-Polarization SAR Data Based on Deep Convolutional Neural Networks

The distribution of sea ice is one of the major safety hazards for sea navigation. As human activities in polar regions become more frequent, monitoring and forecasting of sea ice are of great significance. In this paper, we use SAR data from the C-band synthetic aperture radar (SAR) Gaofen-3 satellite in the dual-polarization (VV, VH) fine strip II (FSII) mode of operation to study the Arctic sea ice classification in winter. SAR data we use were taken in the western Arctic Ocean from January to February 2020. We classify the sea ice into four categories, namely new ice (NI), thin first-year ice (tI), thick first-year ice (TI), and old ice (OI), by referring to the ice maps provided by the Canadian Ice Service (CIS). Then, we use the deep learning model MobileNetV3 as the backbone network, input samples of different sizes, and combine the backbone network with multiscale feature fusion methods to build a deep learning model called Multiscale MobileNet (MSMN). Dual-polarization SAR data are used to synthesize pseudocolor images and produce samples of sizes 16 × 16 × 3, 32 × 32 × 3, and 64 × 64 × 3 as input. Ultimately, MSMN can reach over 95% classification accuracy on testing SAR sea ice images. The classification results using only VV polarization or VH polarization data are tested, and it is found that using dual-polarization data could improve the classification accuracy by 10.05% and 9.35%, respectively. When other classification models are trained using the training data from this paper for comparison, the accuracy of MSMN is 4.86% and 1.84% higher on average than that of the model built using convolutional neural networks (CNNs) and ResNet18 model, respectively.

Turbulent heat exchange characterisics in sea ice ridges areas

The studies of the features of turbulent heat exchange were carried out for the first time in domestic practice near ice ridge areas of sea ice using an unmanned aerial vehicle (UAV) as part of the expedition "Transarktika-2019" onboard the R/V “Akademik Tryoshnikov”. An original measuring complex designed in AARI, was used to assess the characteristics of the ice surface (ice ridges, flat areas of ice). This made it possible to obtain comparative estimates of the albedo and surface temperature of different morphometric structures of the sections of the ice field, where the expedition's ice camp was organized. Measurements of air temperature and wind velocity were carried in the atmospheric surface layer on flat snow-covered areas of sea ice out from the windward and leeward sides of the ridge in parallel with the UAV flights. As a result of the experiments, it was found that the ice ridges areas have a lower albedo and surface temperature compared to neighboring areas of flat sea ice on average. Turbulent heat fluxes from the windward side of the hummock ridge exceed similar values recorded from the leeward side under conditions of unstable stratification in the atmospheric surface layer and exceed the fluxes calculated for conditions of flat ice on the sections with absence of hummocks, on average. In total, the nature and intensity of turbulent heat conduction in the ice ridges area differs from the analogous values observed on the flat sea ice cover. It is possible that the assessment of heat conduction with the atmosphere requires a certain revision, against the background (within the conditions) of thin first-year ice increasing which is more prone to hummocking than multi-year ice.

Vertical Distribution of Brine and Volume Structure of Thin Annual Ice in Amursky Bay Based on the Methods of Nuclear Magnetic Resonance and Magnetic Resonance Imaging

Spatial distribution of the liquid and solid phases in the pores of first-year sea ice in Amursky Bay was studied using the method of nuclear magnetic resonance and magnetic resonance imaging in the period from 2013 to 2016. We describe the influence of snow cover on the brine content in the pores of sea ice, on the bulk structure of crystalline formations, and on the formation of its individual layers. The difference in vertical profiles of temperature and salinity in the winter and spring periods is shown. The characteristic features of the bulk crystal structure and liquid phase in thin first-year ice are compared with the thick ice of the polar regions. A new empirical relationship is given for the calculation of the entire thickness and separate ice layers as applied to thin young ice.

Analysis of the interannual variability of ice conditions along the route "Sabetta – Murmansk» for the period 1997-2018

«Вестник Санкт-Петербургского университета. Науки о Земле» — научно-теоретический рецензируемый журнал, обобщающий результаты исследований в области геологии, гидрогеологии и геохимии, петрологии и экологии, ландшафтного планирования и геоморфологии, экономической и социальной географии.

RRNA and rDNA based assessment of sea ice protist biodiversity from the central Arctic Ocean

Sea ice is a large and diverse ecosystem contributing significantly to primary production in ice-covered regions. In the Arctic Ocean, sea ice consists of mixed multi-year ice (MYI), often several metres thick, and thinner first-year ice (FYI). Current global warming is most severe in Arctic regions; as a consequence, summer sea ice cover is decreasing and MYI is disappearing at an alarming rate. Despite its apparent hostility, sea ice is inhabited by a diverse microbial community of bacteria and protists, many of which are photosynthetic. Here we present an assessment of eukaryotic biodiversity in MYI and FYI from the central Arctic Ocean using high-throughput 454 sequencing of 18S rRNA and rDNA amplicons. We compared the rDNA-based ‘total’ biodiversity with the ‘active’ biodiversity from rRNA amplicons and found differences between them including an over-representation of Ciliophora, Bicosoecida and Bacillariophyceae operational taxonomic units (OTUs) in the active part of the community. Differences between the two libraries are more pronounced at the lower taxonomic level: certain genera, such as Melosira, are more abundant in the rRNA library, indicating activity of these genera. Furthermore, we found that one FYI station showed a higher activity of potential grazers which was probably due to the advanced stage of melt evident by higher ice temperatures and highly porous ice compared with the other stations.

Full-depth desalination of warm sea ice

[1] The large-scale Arctic sea-ice retreat induces a gradual replacement of thick, multi-year sea ice by thinner first-year ice. The latter has distinctive physical properties and is in particular substantially saltier. It is generally thought that while salt rejection occurs primarily during ice formation in winter, most of the remaining brine is flushed out of the ice by the percolating surface melt water in summer. Here, it is argued that a substantial part of this residual desalination of first-year sea ice can occur well before summer melt, due to brine convection over the full thickness of the ice, once the ice temperature is higher than a threshold that depends on bulk salinity and thickness. This critical temperature is substantially higher than the permeability threshold. The argument stems from a theoretical analysis of the porous Rayleigh number depicting the propensity for convection in the mushy-layer theory. It is supported by simulations performed with a state-of-the-art 1-D sea-ice model. The study was initially motivated by observations collected in March 2007 in Storfjorden, Svalbard. Those are indirect, however, and are thus presented here as a possible example. Two sporadic anomalies of seawater salinity were recorded close to the base of 40 cm thick ice in temperature conditions that are incompatible with ice formation. Analyses and simulations forced with observed atmospheric conditions suggest that the second peak is caused by flushing of meltwater, while the first and most intense peak is likely associated with an episode of brine convection over the full depth of the ice, yielding significant desalination.

The changing Arctic Ocean

The vast frozen surface of the Arctic Ocean, often referred to as the polar ice cap, separates the atmosphere from the underlying ocean, reflects incoming radiation from the sun back out to space, and provides a unique habitat for creatures ranging in size from microbes to 1500 pound (680 kg) polar bears. While the amount of Arctic sea ice has waxed and waned with the seasons for all of recorded human history, a large fraction would always persist throughout the year. This old, multiyear sea ice reached thicknesses of several meters and resisted melting, even in the polar summer (Eicken et al., 1995). As temperatures have increased in recent decades, much of this old ice has disappeared and been replaced by thinner first-year ice that melts earlier in spring (Maslanik et al., 2011). Earlier melt has allowed the surface ocean to absorb more solar radiation, delaying the onset of freeze-up in the fall. As a result, a positive feedback has developed in which rising Arctic Ocean temperatures have been accompanied by a markedly thinner and less extensive sea ice cover and an ever-lengthening open water season, which allows the ocean to absorb more radiation, further increasing the temperature (Perovich, 2011). Estimates suggest that the volume of sea ice in the Arctic today is only 20% of that present just a few decades ago (Laxon et al., 2013). Scientists are no longer debating if the Arctic Ocean will eventually become ice-free in summer—they are debating when, with estimates ranging from 20 to 50 years from now (Wang and Overland, 2009). For some, the loss of Arctic sea ice is a unique opportunity. Improved access to ice-free Arctic waters has sparked interest in the development of a viable Arctic commercial fishery. It has also fuelled interest from energy companies wishing to explore the shallow continental shelves for fossil hydrocarbons. Already, a more predictably ice-free Northwest Passage (Smith and Stephenson, 2013), a northern gateway between the Atlantic and Pacific oceans, has resulted in increased commercial ship traffic in Arctic waters. As all of these activities ramp up, it is essential that strategies are developed and implemented to minimize environmental degradation (Pew, 2013). For others, the loss of Arctic sea ice looks to be a disaster in the making, particularly for indigenous populations that rely on the ocean for their food. Access to the interior ice pack for hunting is hampered as shore-fast ice diminishes and pack ice retreats further from shore. Subsistence whaling is becoming more difficult as the sea ice historically used as a reliable hunting platform disappears (Struzik, 2012). Newly ice-free waters are encouraging the northward migration of non-native animals, such as killer whales, that compete with native species and indigenous humans for food (Higdon, Hauser and Ferguson, 2012). And coastal populations are rapidly losing valuable land to erosion (Solomon, 2005; Kittel et al., 2011) caused by intense wave action from frequent and stronger storms (Hakkinen, Proshutinsky and Ashik, 2008) with more intense storm surges (Vermaire et al., 2013) in increasingly ice-free waters. Yet the consequences of Arctic sea ice loss extend far beyond the subsistence and commercial activities of humans there will be profound ecological implications as well. Some of these are already apparent, such as habitat reduction for large mammals like ringed seals and polar bears that require stable sea ice in spring/ summer for reproduction and feeding (Stirling and Derocher, 2012). But most consequences are still playing out and our ability to either understand or predict them is limited. This is particularly true for the smallest Arctic inhabitants on which the rest of the marine ecosystem relies.

Thickness and surface‐properties of different sea‐ice regimes within the Arctic Trans Polar Drift: Data from summers 2001, 2004 and 2007

Large‐scale sea‐ice thickness and surface property data were obtained in three summers and in three different sea‐ice regimes in the Arctic Trans‐Polar Drift (TPD) by means of helicopter electromagnetic sounding. Distribution functions P of sea‐ice thickness and of the height, spacing, and density of sails were analyzed to characterize ice regimes of different ages and deformations. Results suggest that modal ice thickness is affected by the age of a sea‐ice regime and that the degree of deformation is represented by the shape of P. Mean thickness changes with both age and deformation. Standard error calculations showed that representative mean and modal thickness could be obtained with transect lengths of 15 km and 50 km, respectively, in less deformed ice regimes such as those around the North Pole. In heavier deformed ice regimes closer to Greenland, 100 km transects were necessary for mean thickness determination and a representative modal thickness could not be obtained at all. Mean sail height did not differ between ice regimes, whereas sail density increased with the degree of deformation. Furthermore, the fraction of level ice, open melt ponds, and open water along the transects were determined. Although overall ice thickness in the central TPD was 50% thinner in 2007 than in 2001, first‐year ice (FYI) was not significantly thinner in 2007 than FYI in 2001, with a decrease of only 0.3 m. Thinner FYI in 2007 only occurred close to the sea‐ice edge, where open water covered more than 10% of the surface. Melt pond coverage retrieved from laser measurements was 15% in both the 2004 MYI regime and the 2007 FYI regime.

Observations of sea ice thickness, surface roughness and ice motion in Amundsen Gulf

Ice thickness and surface roughness measurements of first‐year (FY) sea ice were collected with a fix‐mounted helicopter‐borne electromagnetic (HEM) ‐laser system in Amundsen Gulf in April to May 2004. The modal ice thickness values are in good qualitative agreement with different ice types identified in synthetic aperture radar (SAR) imagery and shown on ice charts produced by the Canadian Ice Service. Modal ice thickness values which generally represent level ice thicknesses were about 2.0 m over landfast ice. A large range of modal ice thicknesses was observed in the mobile ice region, with values of about 0.2 m (young ice) in leads (where there was high radar backscatter), 0.6 m (thin FY ice) in the polynya (where there was medium to high backscatter), and about 1.1–1.9 m (thick FY ice) elsewhere. High surface roughnesses are strongly associated with high radar backscatter in SAR imagery, and are observed in areas of large shear. The ratio of the standard deviations of ice draft and averaged roughness in an area of landfast ice is in good agreement with the ratio of the standard deviations of ice draft and ice‐equivalent roughness expected from isostasy, with constant level ice and snow thickness. However, the standard deviation of ice‐equivalent roughness may be significantly underestimated, due to differences in snow thickness between level and deformed ice, and limitations of the laser processing method. Modal ice (plus snow) thicknesses measured with the HEM system are within the range of historical values measured at Cape Parry.

Protist entrapment in newly formed sea ice in the Coastal Arctic Ocean

Protist abundance and taxonomic composition were determined in four development stages of newly formed sea ice (new ice, nilas, young ice and thin first-year ice) and in the underlying surface waters of the Canadian Beaufort Sea from 30 September to 19 November 2003. Pico- and nanoalgae were counted by flow cytometry whereas photosynthetic and heterotrophic protists ≥ 4 µm were identified and counted by inverted microscopy. Protists were always present in sea ice and surface water samples throughout the study period. The most abundant protists in sea ice and surface waters were cells < 4 µm. They were less abundant in sea ice (418–3051 × 10 3 cells L − 1 ) than in surface waters (1393–5373 × 10 3 cells L − 1 ). In contrast, larger protists (≥ 4 µm) were more abundant in sea ice (59–821 × 10 3 cells L − 1 ) than in surface waters (22–256 × 10 3 cells L − 1 ). These results suggest a selective incorporation of larger cells into sea ice. The ≥ 4 µm protist assemblage was composed of a total number of 73 taxa, including 12 centric diatom species, 7 pennate diatoms, 11 dinoflagellates and 16 flagellates. The taxonomic composition in the early stage of ice formation (i.e., new ice) was very similar to that observed in surface waters and was composed of a mixed population of nanoflagellates (Prasinophyceae and Prymnesiophyceae), diatoms (mainly Chaetoceros species) and dinoflagellates. In older stages of sea ice (i.e., young ice and thin first-year ice), the taxonomic composition became markedly different from that of the surface waters. These older ice samples contained relatively fewer Prasinophyceae and more unidentified nanoflagellates than the younger ice. Diatom resting spores and dinoflagellate cysts were generally more abundant in sea ice than in surface waters. However, further studies are needed to determine the importance of this winter survival strategy in Arctic sea ice. This study clearly shows the selective incorporation of large cells (≥ 4 µm) in newly formed sea ice and the change in the taxonomic composition of protists between sea ice and surface waters as the fall season progresses.

Characteristics of Sea-ice thickness and Snow-depth distributions of the Summer landfast ice in Lützow-Holm Bay, East Antarctica

AbstractSea-ice observations have been conducted on board icebreakershiraseas a part of the Scientific programs of the Japanese Antarctic Research Expedition. We Summarize these to investigate Spatial and interannual variability of ice thickness and Snow depth of the Summer landfast ice in Lützow-Holm Bay, East Antarctica. Electromagnetic–inductive observations, which have been conducted Since 2000, provide total thickness distributions with high Spatial resolution. A clear discontinuity, which Separates thin first-year ice from thick multi-year ice, was observed in the total thickness distributions in two voyages. Comparison with Satellite images revealed that Such phenomena reflected the past breakup of the landfast ice. Within 20–30km from the Shore, total thickness as well as Snow depth decrease toward the Shore. This is due to the Snowdrift by the Strong northeasterly wind. Video observations of Sea-ice thickness and Snow depth were conducted on 11 voyages Since December 1987. Probability density functions derived from total thickness distributions in each year are categorized into three types: a thin-ice, thick-ice and intermediate type. Such interannual variability primarily depends on the extent and duration of the Successive break-up events.

Observation and inversion of seismo-acoustic waves in a complex arctic ice environment

The propagation of low-frequency seismoacoustic waves in the arctic ice canopy is examined through the analysis of data collected during the 1987 PRUDEX ice camp. Study of the geophone time series generated by under-ice detonations reveals not only the expected longitudinal and flexural waves in the ice plate, but also unexpected horizontally polarized transverse (SH) waves. The travel paths of all three wave types are found to be refracted in the horizontal plane along a known ridge line locally separating the ice canopy into two distinct half-plates of thin first-year ice and thicker multi-year ice. The need to determine both the origin of the SH wave and location of each detonation from the received time series highlights the dramatic superiority of geophones over hydrophones in this aplication. Inversion of the geophone data for the ice sheet’s low-frequency elastic parameters is conducted initially by modeling the ice as a single homogeneous isotropic plate using SAFARI. A modified stationary phase approach is then used to extend SAFARI modeling to invert for the parameters of the two ice half-plates simultaneously. The estimated compressional/shear bulk wave speeds are comparable to previously obtained values; however, the compression/shear attenuation values are up to four times greater than earlier estimates.

Four years of low-altitude sea ice broad-band backscatter measurements

The ability to use radar to discriminate Arctic Sea ice types has been investigated using surface-based and helicopter-borne scatterometer systems. The surface-based FM/CW radar operated at 1.5 GHz and at multiple frequencies in the 8-18-GHz region. Measurements were made at angles of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">10\deg</tex> to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">70\deg</tex> from nadir. The helicopter-based radar operated at the 8-18-GHz frequencies with incidence angles of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0\deg</tex> to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">60\deg</tex> . Extensive surface-truth measurements were made at or near the time of backscattar measurement to describe the physical and electrical properties of the polar scene. Measurements in the 8-18-GHz region verify the ability to discriminate multiyear, thick first-year, thin first-year, and pressure-ridged sea ice and lake ice. The lowest frequency, 9 GHz, was found to provide the greatest contrast between these ice categories, with significant levels of separation existing between angles from <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">15\deg</tex> to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">70\deg</tex> . The radar cross sections for like antenna polarizations, VV and HH, were very similar in absolute level and angular response. Cross-polarization, VH and HV, provided the greatest contrast between ice types, The 1.5-GHz measurements showed that thick first-year, thin first-year, and multiyear sea ice cannot be distinguished at <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">10\deg</tex> to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">60\deg</tex> incidence angles with like polarization, VV, by backscatter alone; but that undeformed sea ice can be discriminated from pressure-ridged ice and lake ice. The effect of snow cover on the backscatter from thick first-year ice was also investigated. It contributes on the order of 0 to 4 dB, depending on frequency and incidence angle; the contribution of the snow layer increased with increasing frequency. Snow cover on smooth lake ice was found to be a major backscatter mechanism. Summer measurements demonstrate the inability to extend the knowledge of the backscatter from sea ice under spring conditions to all seasons.