Ice Texture Research Articles

An initial study of interference coloration for quantifying the texture and fabric of ice

The manual application of universal (Rigsby) stage techniques is commonly used to determine the fabric of thin sections of ice viewed with crossed-polarized light. This process can require hours of focus in cold conditions to identify the c-axis of each grain in a thin section. Automated ice texture and fabric methods of several forms exist but are rarely implemented beyond the field of glaciology. The present study introduces a method based on the theory of interference coloration for automated ice texture and quarter fabric analysis by using in-plane conventional photography of an ice thin section as input. The method is compatible with universal stages and polariscopes, and is not restricted by the planar-face dimensions of the thin section, allowing for thin section analysis of any size when sufficient digital camera resolution is available. Light source color temperature and chromatic adaptation are considered in the interference coloration theory, and ice fabrics are simulated for reference in identifying ice types. Sample thin section texture and quarter fabric analyses from freshwater lake and laboratory-grown ice are presented to demonstrate the applications of the method. The method is compared with the Rigsby stage technique, which yielded mean (standard deviation of) azimuth and inclination errors of 2.9 (1.0) and 11.5 (8.0) degrees, respectively, thereby demonstrating accuracy sufficient for quantifying quarter fabrics when considering a mean standard deviation in inclination of 5.4 degrees with the Rigsby stage technique.

Remote sensing sea ice classification based on DenseNet and heterogeneous data fusion

Most remote sensing sea ice classification methods use single-source remote sensing data, such as synthetic aperture radar (SAR) data and optical remote sensing data. SAR data contain rich sea ice texture information, but the data are relatively single, making it difficult to distinguish detailed sea ice categories. Optical data include abundant spatial-spectral information, but they are often affected by clouds, fog, and severe weather. Hence, given the limitations of single-source data, the remote sensing sea ice classification accuracy cannot be further improved. A sea ice classification method based on deep learning and multisource remote sensing data fusion is proposed utilizing an improved densely connected convolutional neural network (DenseNet) to mine and fuse the multilevel features of sea ice. According to the characteristics of SAR data and optical data, a dual-branch network structure based on an improved DenseNet is employed for feature extraction, and a squeeze-and-excitation attention mechanism is introduced to weight the fusion features to further enhance the feature weights that can effectively distinguish different types of sea ice. The fully connected network is used to perform the deep fusion of features and classify sea ice. To verify the effectiveness of the proposed method, two sets of sea ice data are utilized for sea ice classification. The experimental results show that the proposed method fully excavates and fuses the multilevel characteristics of heterogeneous data using the improved dual-branch network structure, leverages the complementary characteristics of SAR data and optical data, significantly increases the sea ice classification accuracy, and effectively improves the influence of cloud cover on the sea ice classification accuracy. Compared with the typical single-source data classification method and other heterogeneous data fusion classification methods, the proposed method achieves superior overall classification accuracy (98.49% and 98.58%).

Genetic Identification Of Ground Ice By Petrographic Method

The advantages and limitations of the petrography method and the relevance of its use for the study of natural ice are reviewed in the present work. The petrographic method of ground ice study is often used for solving paleogeographic issues. The petrofabric analysis of ground ice is not only useful for descriptive purposes but, like the study of cryostructures, helps to infer growth processes and conditions. Different types of natural ice have specific features that can help us to determine ice genesis. Surface ice, such as glacier ice is often presented by foliation formed by large crystals (50-60 mm); lake ice is characterised by the upper zone of small (6 mm x 3 mm) dendritic and equigranular crystals, which change with increasing depth to large (may exceed 200 mm) columnar and prismatic crystals; segregated ice is composed by crystals forming foliation. Ground ice, such as ice wedge is presented by vertical-band appearance and small crystals (2-2.5 mm); closed-cavity ice is often distinguished by radial-ray appearance produced by elongated ice crystals; injection ice is composed by anhedral crystals, showing the movement of water; snowbank ice is presented by a high concentration of circular bubbles and small (0.1-1 mm) equigranular crystals; icing is described by foliation and mostly columnar crystals. Identification of the origin of ground ice is a complicated task for geocryology because it is difficult to distinguish different types of ground ice based on only visual explorations. The simplest way to get an ice texture pattern is by using polarized light. Distinctions between genetic types of ground ice are not always made in studies, and that can produce erroneous inferences. Petrography studies of an ice object are helpful to clarify the data interpretation, e.g., of isotopic analyses. It is particularly relevant for heterogeneous ice wedges’ study.

Freezing and Thawing of D2O/Sand Mixtures Investigated by Neutron Diffraction

Evolution ice diffraction patterns in mixtures of D2O with quartz sand of three different grain coarseness (100–600, 300–800 and 600–1200 μm) were studied under various temperature regimes by means of neutron diffraction method. The studied structural parameters and characteristics involved the phase composition of specimens, Ih D2O ice lattice parameters, and crystallographic texture of the present phases. Variations in the ice crystallographic texture during the repeated freezing and thawing were observed for all tested sample types, showing an intermittent enhancement of ice and quartz texture indices accompanying the start of specimens cooling. Formation of radial internal stresses is demonstrated by the observed split of (002) and (100) diffraction maxima of ice. Estimated mean internal radial stress values are calculated.

Texture characterization of some large hailstones with an automated technique

AbstractHailstone structures have been studied for over a century, but so far mainly by manual optical means. This paper presents new texture and microstructure data (i.e. crystal lattice orientations, grain sizes and shapes) measured with an Automatic Ice Texture Analyzer, which gives access to high spatial and angular resolutions. The hailstones show two main characteristics: (1) they are structured with several concentric layers composed of alternating fine equiaxed grains and coarse elongated and radially oriented grains, and (2) they show two texture types with c-axes oriented either parallel or perpendicular to the radial direction. Such textures are compared with the ones observed in lake S1 and S2 ices, respectively. The S1 texture type (with c-axes parallel to the columnar crystals that grew in the radial direction) may result from epitaxial growth from a polycrystalline embryo, while the S2 texture (c-axes in the plane perpendicular to the column direction) may result from the growth from an embryo made of a few crystals with mainly one crystallographic orientation. Our novel high-resolution maps and measurements of both microstructure and texture may help to shed new light on the long-term discussion on the growth mechanisms of large hailstones.

Investigation of a cold-based ice apron on a high-mountain permafrost rock wall using ice texture analysis and micro-14C dating: a case study of the Triangle du Tacul ice apron (Mont Blanc massif, France)

AbstractThe current paper studies the dynamics and age of the Triangle du Tacul (TDT) ice apron, a massive ice volume lying on a steep high-mountain rock wall in the French side of the Mont-Blanc massif at an altitude close to 3640 m a.s.l. Three 60 cm long ice cores were drilled to bedrock (i.e. the rock wall) in 2018 and 2019 at the TDT ice apron. Texture (microstructure and lattice-preferred orientation, LPO) analyses were performed on one core. The two remaining cores were used for radiocarbon dating of the particulate organic carbon fraction (three samples in total). Microstructure and LPO do not substantially vary with along the axis of the ice core. Throughout the core, irregularly shaped grains, associated with strain-induced grain boundary migration and strong single maximum LPO, were observed. Measurements indicate that at the TDT ice deforms under a low strain-rate simple shear regime, with a shear plane parallel to the surface slope of the ice apron. Dynamic recrystallization stands out as the major mechanism for grain growth. Micro-radiocarbon dating indicates that the TDT ice becomes older with depth perpendicular to the ice surface. We observed ice ages older than 600 year BP and at the base of the lowest 30 cm older than 3000 years.

Influence of Porosity on Ice Dynamic Tensile Behavior as Assessed by Spalling Tests

The impact of ice on structures is a strong concern, in particular for aeronautical or space crafts that are strongly damaged by the impact of atmospheric ice, and more specifically by hailstones during hailstorms. During the impact, the hailstone is submitted to a complex loading including a strong dynamic tensile component that is responsible for its fragmentation and influences the mechanical loading transmitted to the impacted structure. However, up to now, very limited work were conducted on the tensile strength of ice under dynamic loading and the microstructure influence was out the scope of most studies. In particular the presence of porosity in ice as observed in hailstones is thought to significantly affect the ice mechanical response. The aim of this paper is to investigate the role of porosity on the tensile behavior of polycrystalline ice at high strain rates. To do so, spalling tests with a Hopkinson bar apparatus were conducted on microstructures characterized by porosities with two different pore size distributions. The dynamic tensile strength was computed by the use of the so-called Novikov formula and several indicators were used to assess the quality of each test. A whole set of high porosity samples was tested and additional tests were performed on low porosity ice, expanding the existing results in the literature. The fragmentation processes occuring during the spalling tests were observed by means of an ultra high speed camera and the influence of porosity on the main fracture planes was investigated by analysing post-spalling samples with an automatic ice texture analyser and X-ray tomography. Tensile strength is shown to increase with strain rate over the range \(24\,\hbox {s}^{-1}\) to \(120\,\hbox {s}^{-1}\) and to decrease with increasing porosity. The presence of large porosities in the high porosity samples appear to contribute preferentially to this strength decrease. Relevant observations concerning the detected cracks, the tortuosity of crack paths and the presence of porosities on the crack surfaces seem to validate the hypothesis of porosities playing a key role for crack initiation and propagation during ice fragmentation.

Concentration and isotopic composition of bromine and chlorine in Antarctic sea ice

This work presents the results from the first investigation of Br and Cl isotopic partitioning in Southern Ocean sea ice. The sea ice samples were collected during the Australian-led Sea Ice Physics and Ecosystem eXperiment-2 (SIPEX-2) marine voyage in austral spring of 2012 (26 Sept – 10 Nov), within the area bounded by 115–125°E and 62–66oS off the East Antarctic coast. Multicollector inductively coupled plasma mass spectrometry was used to provide isotopic data for bromine and chlorine. Bromine concentrations ranged from 710 ± 20 μg L−1 to 31440 ± 570 μg L−1 and chlorine concentrations ranged from 218 ± 12 mg L−1 to 7945 ± 351 mg L−1. Bromine and chlorine concentrations were positively correlated with a slope of 0.0038, consistent with the seawater Br/Cl ratio of 0.0035. Bromine isotopic compositions (denoted δ81Br with respect to SMOB isotopic reference) varied from −0.64 to 0.10‰ with a mean of −0.16‰ and standard deviation of 0.04‰. Chlorine isotopic compositions (denoted δ37Cl with respect to SMOC isotopic reference) varied from −1.10‰ to 0.43‰ with a mean of −0.26‰ and standard deviation of 0.10‰. Despite their strong concentration correlation, there was a much less consistent relation between Br and Cl isotopic compositions and great variability within individual sea ice cores. The samples showing the largest degree of fractionation in their Br and Cl isotopic compositions were found deepest in the sea ice samples. Multiple parameters may influence isotopic fractionation processes in sea ice, including ice texture, age, salt content, and algal biomass content (represented by chlorophyll-a concentrations), although no single factor was found to consistently correlate with the bromine or chlorine isotopic signature. We consider the possibility of isotopic fractionation resulting from brine rejection and desalinization processes.

Snow-ice contribution to the structure of sea ice in the Amundsen Sea, Antarctica

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

Hyperspectral Sea Ice Image Classification Based on the Spectral-Spatial-Joint Feature with Deep Learning

Sea ice is one of the causes of marine disasters. The classification of sea ice images is an important part of sea ice detection. The labeled samples in hyperspectral sea ice image classification are difficult to acquire, which causes minor sample problems. In addition, most of the current sea ice classification methods mainly use spectral features for shallow learning, which also limits further improvement of the sea ice classification accuracy. Therefore, this paper proposes a hyperspectral sea ice image classification method based on the spectral-spatial-joint feature with deep learning. The proposed method first extracts sea ice texture information by the gray-level co-occurrence matrix (GLCM). Then, it performs dimensionality reduction and a correlation analysis of the spectral information and spatial information of the unlabeled samples, respectively. It eliminates redundant information by extracting the spectral-spatial information of the neighboring unlabeled samples of the labeled sample and integrating the information with the spectral and texture data of the labeled sample to further enhance the quality of the labeled sample. Lastly, the three-dimensional convolutional neural network (3D-CNN) model is designed to extract the deep spectral-spatial features of sea ice. The proposed method combines relevant textural features and performs spectral-spatial feature extraction based on the 3D-CNN model by using a large amount of unlabeled sample information. In order to verify the effectiveness of the proposed method, sea ice classification experiments are carried out on two hyperspectral data sets: Baffin Bay and Bohai Bay. Compared with the CNN algorithm based on a single feature (spectral or spatial) and other CNN algorithms based on spectral-spatial features, the experimental results show that the proposed method achieves better sea ice classification (98.52% and 97.91%) with small samples. Therefore, it is more suitable for classifying hyperspectral sea ice images.

Recrystallization processes, microstructure and crystallographic preferred orientation evolution in polycrystalline ice during high-temperature simple shear

Abstract. Torsion experiments were performed in polycrystalline ice at high temperature (0.97 Tm) to reproduce the simple shear kinematics that are believed to dominate in ice streams and at the base of fast-flowing glaciers. As clearly documented more than 30 years ago, under simple shear ice develops a two-maxima c axis crystallographic preferred orientation (CPO), which evolves rapidly into a single cluster CPO with a c axis perpendicular to the shear plane. Dynamic recrystallization mechanisms that occur in both laboratory conditions and naturally deformed ice are likely candidates to explain the observed CPO evolution. In this study, we use electron backscatter diffraction (EBSD) and automatic ice texture analyzer (AITA) to characterize the mechanisms accommodating deformation, the stress and strain heterogeneities that form under torsion of an initially isotropic polycrystalline ice sample at high temperature, and the role of dynamic recrystallization in accommodating these heterogeneities. These analyses highlight an interlocking microstructure, which results from heterogeneity-driven serrated grain boundary migration, and sub-grain boundaries composed of dislocations with a [c]-component Burgers vector, indicating that strong local stress heterogeneity develops, in particular, close to grain boundaries, even at high temperature and high finite shear strain. Based on these observations, we propose that nucleation by bulging, assisted by sub-grain boundary formation and followed by grain growth, is a very likely candidate to explain the progressive disappearance of the c axis CPO cluster at low angle to the shear plane and the stability of the one normal to it. We therefore strongly support the development of new polycrystal plasticity models limiting dislocation slip on non-basal slip systems and allowing for efficient accommodation of strain incompatibilities by an association of bulging and formation of sub-grain boundaries with a significant [c] component.

The Impact of Ice Texture on Coefficient of Friction for Stainless Steel with Different Surface Roughness

Winter forces people to adapt to snow and ice conditions and understand the regularities in nature in the cold regions. The understanding of ice and snow regularities can help to improve the safety of moving over ice. The objective of this work was to investigate the impact of ice texture on the static coefficient of friction for stainless steel samples with different surface roughness under laboratory conditions. The ice was prepared flatted, scratched and glazed to represent the various ice textures which might appear in real-life situations. The samples were prepared as rectangular stainless steel blocks with different surface roughness. Contact area between the sample and the ice was considered as the most influential factor. A larger contact area resulted in a higher static coefficient of friction. This outcome provides useful information for working in surroundings with ice.

Stable Isotope Clues to the Formation and Evolution of Refrozen Melt Ponds on Arctic Sea Ice

AbstractSea ice is one of the determining parameters of the climate system. The presence of melt ponds on the surface of Arctic sea ice plays a critical role in the mass balance of sea ice. A total of nine cores was collected from multiyear ice refrozen melt ponds and adjacent hummocks during the 2015 Arctic Sea State research cruise. The depth profiles of water isotopes, salinity, and ice texture for these sea ice cores were examined to provide information about the development of refrozen melt ponds and water balance generation processes, which are otherwise difficult to acquire. The presence of meteoric water with low oxygen isotope values as relatively thin layers indicates melt pond water stability and little mixing during formation and refreezing. The hydrochemical characteristics of refrozen melt pond and seawater depth profiles indicate little snowmelt enters the upper ocean during melt pond refreezing. Due to the seasonal characters of deuterium excess for Arctic precipitation, water balance calculations utilizing two isotopic tracers (oxygen isotope and deuterium excess) suggest that besides the melt of snow cover, the precipitation input in the melt season may also play a role in the evolution of melt ponds. The dual‐isotope mixing model developed here may become more valuable in a future scenario of increasing Arctic precipitation. The layers of meteoric origin were found at different depths in the refrozen melt pond ice cores. Surface topography information collected at several core sites was examined for possible explanations of different structures of refrozen melt ponds.

The Influence of Ice Texture on Sliding Over Ice

Abstract Winter brings snow and ice to Northern Europe and with it the need to move safely over ice. It has been customary to select an appropriate material surface for movement over ice, but another way to influence the interaction with ice is to appropriately prepare the ice surface. The objective of the research is to investigate the influence of ice texture on initiating movement over ice and on sliding velocity over ice in the laboratory and field conditions. The ice has been prepared smooth, scratched and glazed similar to the one found in real life situations. The static coefficient of friction and the sliding speed have been measured at the laboratory, but the sliding speed quantified on a skeleton –at the skeleton push-start facility. The scratched ice surface has increased the resistance to movement, thus resulting in the lowest sliding speed under laboratory conditions. Sliding is better on the smooth ice and glazed ice. The contact surfaces have been measured to determine the effect of contact area on sliding properties. Field experiments with heavier loads have flattened the ice surface irregularities for more constant sliding conditions over time. This outcome provides a useful indicator for pedestrians and road traffic related to the safety of movement over different ice surfaces as well as a reference for those involved in winter sports.

Evolution of climate, glaciation and subglacial environments of Antarctica from the deep ice core and Lake Vostok water sample studies (Key results of implementation of the Russian Science Foundation project, 2014–2016)

Work on the project focused on the following five areas: 1) field works in Antarctica at Vostok and Concordia stations; 2) experimental and theoretical studies in the field of ice core and paleoclimate research; 3) experimental and theoretical works related to the exploration of subglacial Lake Vostok; 4) development of technology and drilling equipment for deep ice coring and exploration of subglacial lakes; 5) upgrading the analytical instrumentation in the Climate and Environmental Research Laboratory (CERL) of the Arctic and Antarctic Research Institute. The main achievements in the field of ice core and paleoclimate research include 1) further elaboration of a new method of ice core dating, which is based on the link between air content of ice and local insolation, 2) investigation of the possible applications of the 17O-excess measurements in ice core to the paleoclimate research, 3) a better understanding of the mechanisms of the formation of relief-related variations in the isotopic content of an ice core drilled in the area of Antarctic megadunes, and 4) obtaining the first reliable data set on the variations of the 17O-excess in the Vostok core corresponding to marine isotope stage 11. As part of our studies of subglacial Lake Vostok, we have obtained a large body of new experimental data from the new ice core recovered from the 5G-3 borehole to the surface of the subglacial lake. Stacked profiles of isotopic composition, gas content and the size and orientation of the ice crystals in the lake ice have been composed from the data of three replicate cores from boreholes 5G-1, 5G-2 and 5G-3. The study reveals that the concentration of gases in the lake water beneath Vostok is unexpectedly low. A clear signature of the melt water in the surface layer of the lake, which is subject to refreezing on the icy ceiling of Lake Vostok, has been discerned in the three different properties of the accreted ice (the ice texture, the isotopic and gas content of the ice). These sets of data indicate in concert that poor mixing of the melt (and hydrothermal) water with the resident lake water and pronounced spatial and/or temporal variability of local hydrological conditions are likely to be the characteristics of the southern end of the lake. A considerable part of the funding allocated by the RSF to this project was used for upgrading the analytical instrumentation for ice core studies in the CERL of AARI. Using this grant, we purchased and started working with the Picarro L-2140i, a new-generation laser mass analyzer, and set the upgraded mass spectrometer Delta V Plus into operation. The new equipment was used to carry out research planned as part of the project, including the setting up and carrying out of new measurements of 17О in ice cores.

Texture and structure of the Late Holocene ground ice in the Northern West Siberia

The Late Holocene ground ices are occurred due to freeze cracking, slope, thermocast, thermoerosion pro‑ cesses. New formation ice within may intervene to the Pleistocene, lower Holocene ground ice and perma‑ frost and can really complicate their structure. Relationship between seasonal and perennial new formation of ice with massive ice and permafrost was studied in cross section of the North Western Siberia. The features of texture and structure of ice formed in the thawing cavities, some cracks were determined. The differences in structure of the late Holocene ground ices and ground ices of the early Holocene and late Pleistocene were defined. The differences in ground ice texture and structure depend to the cavity configuration of the freezing and cracks and freezing temperature conditions. The quantitative parameters of the crystal structure can be used to identify closed‑cavity ice and crack ice in the composition of massive ice and determine mechanisms and conditions of formation before the Holocene ice wedges.

The layered evolution of fabric and microstructure of snow at Point Barnola, Central East Antarctica

Snow fabric, defined as the distribution of the c-axis orientations of the ice crystals in snow, is poorly known. So far, only one study exits that measured snow fabric based on a statistically representative technique. This recent study has revealed the impact of temperature gradient metamorphism on the evolution of fabric in natural snow, based on cold laboratory experiments. On polar ice sheets, snow properties are currently investigated regarding their strong variability in time and space, notably because of their potential influence on firn processes and consequently on ice core analysis. Here, we present measurements of fabric and microstructure of snow from Point Barnola, East Antarctica (close to Dome C). We analyzed a snow profile from 0 to 3 m depth, where temperature gradients occur. The main contributions of the paper are (1) a detailed characterization of snow in the upper meters of the ice sheet, especially by providing data on snow fabric, and (2) the study of a fundamental snow process, never observed up to now in a natural snowpack, namely the role of temperature gradient metamorphism on the evolution of the snow fabric. Snow samples were scanned by micro-tomography to measure continuous profiles of microstructural properties (density, specific surface area and pore thickness). Fabric analysis was performed using an automatic ice texture analyzer on 77 representative thin sections cut out from the samples. Different types of snow fabric could be identified and persist at depth. Snow fabric is significantly correlated with snow microstructure, pointing to the simultaneous influence of temperature gradient metamorphism on both properties. We propose a mechanism based on preferential grain growth to explain the fabric evolution under temperature gradients. Our work opens the question of how such a layered profile of fabric and microstructure evolves at depth and further influences the physical and mechanical properties of snow and firn. More generally, it opens the way to further studies on the influence of the snow fabric in snow processes related to anisotropic properties of ice such as grain growth, mechanical response, electromagnetic behavior.

Critical investigation of calculation methods for the elastic velocities in anisotropic ice polycrystals

Abstract. Crystallographic texture (or fabric) evolution with depth along ice cores can be evaluated using borehole sonic logging measurements. These measurements provide the velocities of elastic waves that depend on the ice polycrystal anisotropy, and they can further be related to the ice texture. To do so, elastic velocities need to be inverted from a modeling approach that relate elastic velocities to ice texture. So far, two different approaches can be found. A classical model is based on the effective medium theory; the velocities are derived from elastic wave propagation in a homogeneous medium characterized by an average elasticity tensor. Alternatively, a velocity averaging approach was used in the glaciology community that averages the velocities from a given population of single crystals with different orientations. In this paper, we show that the velocity averaging method is erroneous in the present context. This is demonstrated for the case of waves propagating along the clustering direction of a highly textured polycrystal, characterized by crystallographic c axes oriented along a single maximum (cluster). In this case, two different shear wave velocities are obtained while a unique velocity is theoretically expected. While making use of this velocity averaging method, reference work by Bennett (1968) does not end with such an unphysical result. We show that this is due to the use of erroneous expressions for the shear wave velocities in a single crystal, as the starting point of the averaging process. Because of the weak elastic anisotropy of ice single crystal, the inversion of the measured velocities requires accurate modeling approaches. We demonstrate here that the inversion method based on the effective medium theory provides physically based results and should therefore be favored.

Imaging air volume fraction in sea ice using non-destructive X-ray tomography

Abstract. Although the presence of a gas phase in sea ice creates the potential for gas exchange with the atmosphere, the distribution of gas bubbles and transport of gases within the sea ice are still poorly understood. Currently no straightforward technique exists to measure the vertical distribution of air volume fraction in sea ice. Here, we present a new fast and non-destructive X-ray computed tomography technique to quantify the air volume fraction and produce separate images of air volume inclusions in sea ice. The technique was performed on relatively thin (4–22 cm) sea ice collected from an experimental ice tank. While most of the internal layers showed air volume fractions < 2 %, the ice–air interface (top 2 cm) systematically showed values up to 5 %. We suggest that the air volume fraction is a function of both the bulk ice gas saturation factor and the brine volume fraction. We differentiate micro bubbles (Ø < 1 mm), large bubbles (1 mm < Ø < 5 mm) and macro bubbles (Ø > 5 mm). While micro bubbles were the most abundant type of gas bubbles, most of the air porosity observed resulted from the presence of large and macro bubbles. The ice texture (granular and columnar) as well as the permeability state of ice are important factors controlling the air volume fraction. The technique developed is suited for studies related to gas transport and bubble migration.

Numerical validation of the conjecture of a subglacial lake at Amundsenisen, Svalbard

The likelihood of a subglacial lake beneath Amundsenisen Plateau at Southern Spitzbergen, Svalbard, pointed out by the flat signal within the Ground Penetrating Radar (GPR) remote survey of the area, is justified, here, via numerical simulation.This investigation has been developed under the assumption that the icefield thickness does not change on average, as it is confirmed by recently published physical measurements taken over the past 40 years. As a consequence, we have considered admissible to assume the temperature and density in-depth profiles, snow and firn layers included, to be stationary. The upper icefield surface and the rocky bed surface are known in detail.The mathematical numerical model is based on an unsteady Stokes formulation of the ice flow and on a Large Eddy Simulation formulation of the lake water flow. Following the numerical sensitivity results that we presented on a recent issue of this journal, we have, here, upgraded the model by improving the description of critical aspects of icefield thermo-mechanics, such as the local water release within temperate ice as a strain heating effect and ice sliding on the bedrock. The first issue impacts on ice texture, i.e. its constitutive equation, while the second one drives icefield surging. Actually, we have obtained 13% enhancement of the numerical value of the ice top surface velocity versus measured one, and physically consistent numerical ice sliding velocity values at the rocky bottom.Adopting a new physically sound initial subglacial lake water temperature and velocity fields, we present the numerical simulation of the whole system, icefield and conjectured subglacial lake, within a time slot of 20,000d (physical time), when its evolution trend was clearly captured. By then, although the maximum value of water temperature keeps rather low, metastability appears to be overcome on more than half of the conjectured basin, with a progressive trend in time in support to the subglacial lake existence. We stress that the numerical subglacial lake surface converges to the GPR flat signal spot with tolerance equal to the GPR measuring error.Finally, we observe that the numerical simulation results meet quantitatively and qualitatively the fundamental aspects of the conjecture, so that further on-site investigations on the subglacial lake (e.g. drilling operations) appear fully justified.