Salt is often present in the snow overlying seasonal sea ice, and has profound thermodynamic and electromagnetic effects. However, its provenance and behaviour within the snow remain uncertain. We describe two investigations tracing upward brine movement in snow: one conducted in the laboratory and one in the field. The laboratory experiments involved the addition of dyed brine to the base of terrestrial snow samples, with subsequent wicking being measured. Our field experiment involved dye being added directly (without brine) to bare sea-ice and lake ice surfaces, with snow then accumulating on top over several days. On the sea ice, the dye migrated upwards into the snow by up to 5 cm as the snow's basal layer became more salty, whereas no migration occurred in our control experiment over non-saline lake ice. This occurred in relatively dry snowpacks where brine took up $< 6\%$ of the snow's calculated pore volume, suggesting pore saturation is not required for upward salt transport. Our results highlight the potential role of microstructural parameters beyond those currently retrievable with penetrometry, and the potential value of longitudinal, process-based field studies of young snowpacks.

Brash ice formation and accumulation occur at a faster rate in ship channels, harbours and turning areas compared to the surrounding level ice. Accurate prediction of brash ice thickness plays an important role in addressing operational challenges and optimisation of ice management strategies. This study enhances existing brash ice growth models by considering the effects of snow and accounting for brash ice expulsion towards the sides of ship channels at each passage. To validate the influence of these critical factors on brash ice thickness, three distinct ship channels located in the Bay of Bothnia, Luleå, Sweden, were investigated. For two test channels formed for study purposes, the slower growth rate of brash ice caused by snow insulation was more prominent than the brash ice growth acceleration caused by the snow–slush–snow ice transformation. In the third channel characterised by frequent navigation, the transformation of slush into snow ice played a more substantial role than snow insulation. In both test channels, the brash ice growth model performed optimally, assuming a 10% expulsion of brash ice sideways at each vessel passage. In the third, wider and more frequently navigated channel, a 1.2% brash ice expelling coefficient predicted well the measured brash ice thicknesses.

The relationship between the behavior of water in snow and its microstructure is crucial to improve the prediction of wet snow disasters. X-ray computed tomography (X-ray CT) is frequently used to observe snow microscopically. However, distinguishing between ice and water in the X-ray images is difficult because ice exhibits an X-ray absorption coefficient similar to that of water. In contrast, magnetic resonance imaging (MRI) acquires nuclear magnetic resonance (NMR) signals of protons in a liquid and visualizes the NMR signal intensity, enabling discrimination between water and ice signals. However, snow grains and pore spaces cannot be distinguished in MRI images because they do not generate NMR signals.

To investigate the relationship between the microstructure of snow and the distribution of liquids in snow, we developed a novel method that combines X-ray CT and MRI images to compensate for the disadvantages associated with each method. Using this method, we successfully visualized where liquid (C12H24) occupied pore spaces. We also showed the possibility of using C12H24 instead of water to obtain water retention curve of snow cover, which is a fundamental aspect of hydraulic properties. Although there is room for improvement in the visualization of water in snow, such as shortening the imaging time to escape snow metamorphosis and image superimposition methods, this method is expected to effectively elucidate the behavior of water in snow and clarify the characteristics of wet snow.

Liquid water at the ground–snow interface is thought to play a crucial role in the release of glide-snow avalanches, which can be massive and threaten infrastructure in alpine regions. Several mechanisms have been postulated to explain the formation of this interfacial water. However, these mechanisms remain poorly understood, in part because suitable measurement techniques are lacking. Here, we demonstrate the use of neutron radiography for imaging water transport in soil–snow systems. Columns of sand, gravel and snow were used to simulate the capillary forces of the soil–vegetation–snow layering found in nature. The columns were connected to a water reservoir to maintain a constant-pressure boundary condition and placed in a climatic chamber within the neutron beam. We show that neutron radiography is capable of measuring changes in the optical density distribution (related to liquid water content) within all three layers of the model system. Results suggest that a porous interface between the sand and snow may induce the formation of a water layer in the basal snowpack. Improved understanding of the water transport in soil–snow systems should lead to better prediction of glide-snow avalanche release and could also benefit other fields such as snow hydrology.

Snow ice (SI) forms from freezing wet snow, known as slush, and contributes to the thickness of level and brash ice. However, the mechanism of snow-slush-snow ice transformation has not been extensively investigated to date, despite the difference in the freezing rate of slush in comparison with water is important for estimating the ice thickness. In this study, we examined the growth of initial congelation ice (CI) and snow ice (SI) in a fresh water tank exposed to outdoor weather conditions in Luleå, northern Sweden. The tank of size 1.8 × 0.65 × 1.2 m in length, width and height was divided into two compartments to facilitate the simultaneous growth of CI and SI. A total of 12 experiments were conducted in the years 2021 and 2022. The transformation from slush to snow ice was achieved by submerging various amounts of snow in the compartments. It was observed that approximately 35% of the initial snow transformed into SI. Snow ice grew 4 mm°C−0.5 d−0.5 faster than congelation ice. The CI growth under SI was 1 mm°C−0.5 d−0.5 slower than the CI growth under CI. This study provides valuable insights for modelling snow-slush-snow ice transformation and designing future laboratory-scale experiments.

Antarctic firn presents an exotic seismological environment in which the behaviors of propagating waves can be significantly at odds with those in other Earth media. We present a condensed view of the nascent field of ambient noise seismology in Antarctic firn-covered media, and highlight multiple unusual and information-rich observations framed through the lens of the firn's important role as a buffer for air temperature anomalies and a complex contributor to ice mass balance. We summarize key results from several recent papers depicting novel wind-excited firn resonances and point to the plethora of ways these observations could facilitate imaging and monitoring of glacial systems at single, isolated seismometers. Finally, we propose significant instrumental and computational objectives necessary to constrain resonance excitation mechanisms and broadly apply these observations as useful monitoring tools in Antarctica.

Once fallen, snow settles due to the combined effects of metamorphism and deformation of the ice matrix under gravity. To understand how these coupled processes affect snow evolution, we performed oedometric compression tests and continuously monitored the snow microstructure with X-ray tomography. Centimetric samples with an initial density between 200 and 300 kg m−3 were followed during an initial sintering phase and under two different loads of 2.1 and 4.7 kPa at $-8^\circ$C for ~1 week. The microstructure captured at a voxel size of 8.5 μm was characterized by density, specific surface area (SSA) and two metrics related to bond network, namely the Euler characteristic and the minimum cut surface. Load-induced creep of the ice matrix was observed only for sufficiently low values of initial density (<290 kg m−3 in our tests), and was shown to be associated to a significant increase of the number of bonds. Application of the load, however, did not affect the individual bond size nor the SSA, which appeared to be mainly controlled by isothermal metamorphism. The uniaxial compression did not induce any creation of anisotropy on the microstructural characteristics. Overall, our results show that, for the considered conditions, the deformation of the ice matrix mainly leads to a reduction of the pore space and an increase of the coordination number, while metamorphism mainly affects the grain and bond sizes.

Heated needle probes provide the most convenient method to measure snow thermal conductivity. Recent studies have suggested that this method underestimates snow thermal conductivity; however the reasons for this discrepancy have not been elucidated. We show that it originates from the fact that, while the theory behind the method assumes that the measurements reach a logarithmic regime, this regime is not reached within the standard measurement procedure. Using the needle probe without this logarithmic regime leads to thermal conductivity underestimations of tens of percents. Moreover, we show that the poor thermal contact between the probe and the snow due to insertion damages results in a further underestimation. Thus, we encourage the use of fixed needle probes, set up before the snow season and buried under snowfalls, rather than hand-inserted probes. Finally, we propose a method to correct the measurements performed with such fixed needle probes buried in snow. This correction is based on a lookup table, derived specifically for the Hukseflux TP02 needle probe model, frequently used in snow studies. Comparison between corrected measurements and independent estimations of snow thermal conductivity obtained with numerical simulations shows an overall improvement of the needle probe values after application of the correction.

This paper presents a physics-based macroscale model for the densification of dry snow which provides for a smooth transition between densification by grain-boundary sliding (stage 1) and densification by power-law creep (stage 2). The model uses established values of the stage 1 and 2 densification rates away from the transition zone and two transition parameters with a simple physical basis: the transition density and the half-width of the transition zone. It has been calibrated using density profiles from the SUMup database and physically based expressions for the transition parameters have been derived. The transition model produces better predictions of the depth of the nominal bubble close-off horizon than the Herron and Langway model, both in its classical form and in a recent version with re-optimised densification rates.

Casting snow is necessary to prevent metamorphism and deformation prior to X-ray micro-computed tomography (μCT) imaging. Current methods are insufficient for large-scale field sampling of snow due to safety considerations associated with the casting medium and/or lengthy sample preparation times. Here, a casting method using contrast-enhanced diethylphthalate (DEP) for μCT of snow is presented. The X-ray contrast of DEP is enhanced with barium titanate nanoparticles (BaTiO3) and iodine (I2). A partially unsupervised, three-phase segmentation method utilizing traditional Gaussian smoothing followed by a three-step process to address transition voxels is also presented. Synthetic images derived from real snow samples are used to evaluate the segmentation method with various configurations of trapped air bubbles. Real snow samples spanning a range of specific surface areas (SSAs) (8–28 m2 kg−1) and densities (135–463 kg m−3) are used to assess the performance of the segmentation method on real, cast samples. The method yields SSA, density and correlation length errors of less than 10% for synthetic images with air bubble surface areas less than 333 m−1 per sample volume for eight of the nine snow samples. For eight of the nine cast samples, the method yields errors of less than 10% for all three parameters.

Measurements of elastic wave velocities enable non-destructive estimation of the mechanical properties, elastic moduli and density of snow and firn. The variation of elastic moduli with porosity in dry snow and firn is modeled using a differential effective medium scheme modified to account for the critical porosity above which the bulk and shear moduli of the ice frame vanish. A comparison of predicted and measured elastic moduli indicates that the shear modulus of ice in snow is lower than that computed from single crystal elastic stiffnesses of ice. This may indicate that the bonds between snow particles are more deformable under shear than under compression. A partial alignment of ice crystals also may contribute. Good agreement between elastic stiffnesses of the ice frame obtained from elastic wave velocity measurements and the predictions of the theory is observed. The approach is simple and compact, and does not require the use of empirical fits to the data. Owing to its simplicity, this model may prove useful in a variety of potential applications such as construction on snow, interpretation of seismic measurements to monitor and locate avalanches and estimation of density within compacting snow deposited on glaciers and ice sheets.

Ice-sheet mass-balance estimates derived from repeat satellite-altimetry observations require accurate calculation of spatiotemporal variability in firn-air content (FAC). However, firn-compaction models remain a large source of uncertainty within mass-balance estimates. In this study, we investigate one process that is neglected in FAC estimates derived from firn-compaction models: enhanced layer thinning due to horizontal divergence. We incorporate a layer-thinning scheme into the Community Firn Model. At every time step, firn layers first densify according to a firn-compaction model and then thin further due to an imposed horizontal divergence rate without additional density changes. We find that horizontal divergence on Thwaites (THW) and Pine Island Glaciers can reduce local FAC by up to 41% and 18%, respectively. We also assess the impact of temporal variability of horizontal divergence on FAC. We find a 15% decrease in FAC between 2007 and 2016 due to horizontal divergence at a location that is characteristic of lower THW. This decrease accounts for 16% of the observed surface lowering, whereas climate variability alone causes negligible changes in FAC at this location. Omitting transient horizontal divergence in estimates of FAC leads to an overestimation of ice loss via satellite-altimetry methods in regions of dynamic ice flow.

The Antarctic Impulsive Transient Antenna (ANITA) balloon experiment was designed to detect radio signals initiated by high-energy neutrinos and cosmic ray (CR) air showers. These signals are typically discriminated by the polarization and phase inversions of the radio signal. The reflected signal from CRs suffer phase inversion compared to a direct ‘tau neutrino’ event. In this paper, we study subsurface reflection, which can occur without phase inversion, in the context of the two anomalous up-going events reported by ANITA. It is found that subsurface layers and firn density inversions may plausibly account for the events, while ice fabric layers and wind ablation crusts could also play a role. This hypothesis can be tested with radar surveying of the Antarctic region in the vicinity of the anomalous ANITA events. Future experiments should not use phase inversion as a sole criterion to discriminate between down-going and up-going events, unless the subsurface reflection properties are well understood.

The response of snowpack to a +2°C global warming relative to the present climate was estimated in Hokkaido, Japan, using a physical snowpack model driven by dynamically downscaled (DDS) data, after model evaluation. The evaluation revealed that the snowpack model successfully reproduced the height of snow cover (HS), snow water equivalent (SWE) and snow-covered days (SCDs), but had a moderate bias in the thickness ratios of melt form (MF) and hoar category (HC). The DDS-forced simulation predicted that the seasonal-maximum HS and SWE would decrease by 30–40% in the southwestern and eastern parts of Hokkaido due to a large decrease in snowfall during the accumulation period, and that the HS and SWE in the north would decrease, albeit not significantly due to uncertain atmospheric forcing. The number of SCDs in Hokkaido was predicted to decline by ~30 d. Additionally, ~50% of snowpack thickness during a season would be MF in most areas, whereas HC would be <50% all over Hokkaido.

Full snow-pit observations were performed on a monthly basis over ten winter seasons from 1995 to 2004, at 15 study plots spaced at 100 m elevation intervals (1300–2700 m a.s.l.) in the mountainous forest of the Japanese Central Alps. We observed 514 pits with an average depth of 1.12 m. Density measurements were taken in 2610 snow layers in total. Monthly trends indicate that snow depth has a strong linear correlation with elevation and that the mean density of snow cover has a moderate linear correlation with elevation in midwinter. Snow water equivalent can increase as a quadratic function of elevation in January and February. For this reason, the influence of overburden load and wind packing is elevation-dependent from January to February, a period when a facet-prominent snowpack existed on account of low snow and air temperatures. The density of depth hoar is greater at higher elevations than it is for rounded grains in midwinter due to densification. On forested slopes, with increasing elevation, snowfall frequency and the impact of wind upon snow increases while air temperature decreases, causing elevational variance in grain shapes.

Snow properties relevant to the fracture processes involved in dry-snow slab avalanche release include weak layer specific fracture energy, slab elastic modulus and density. Various techniques exist to determine these snow mechanical properties, but it is presently unclear how values determined with different methods compare. In the laboratory, the 3-D microstructure of cm-sized snow samples is reconstructed by micro-computed tomography (μCT) so that density and elastic modulus can be computed. In the field, fracture energy and modulus are estimated based on particle tracking velocimetry (PTV) of the displacement field observed during propagation saw tests. Snow stratigraphy is measured with the snow micro-penetrometer (SMP) in either, field or laboratory. We compared SMP-derived properties to corresponding μCT- and PTV-derived values. Values of snow density related well to μCT results and so were SMP-derived elastic moduli related to PTV-derived values. By taking into account snow anisotropy a good relation between SMP- and μCT-derived moduli resulted suggesting the SMP-derived modulus characterizes the components of the modulus perpendicular to the axis of penetration. SMP- and PTV-derived values of fracture energy were correlated. The SMP can provide a bridge between scales and techniques, yet further improvements in signal interpretation are still needed.

Up to now, snow cover on Antarctic sea ice and its impact on radar backscatter, particularly after the onset of freeze/thaw processes, are not well understood. Here we present a combined analysis of in situ observations of snow properties from the landfast sea ice in Atka Bay, Antarctica, and high-resolution TerraSAR-X backscatter data, for the transition from austral spring (November 2012) to summer (January 2013). The physical changes in the seasonal snow cover during that time are reflected in the evolution of TerraSAR-X backscatter. We are able to explain 76-93% of the spatio-temporal variability of the TerraSAR-X backscatter signal with up to four snowpack parameters with a root-mean-squared error of 0.87-1.62 dB, using a simple multiple linear model. Over the complete study, and especially after the onset of early-melt processes and freeze/thaw cycles, the majority of variability in the backscatter is influenced by changes in snow/ice interface temperature, snow depth and top-layer grain size. This suggests it may be possible to retrieve snow physical properties over Antarctic sea ice from X-band SAR backscatter.

Spectral albedos of open water, nilas, nilas with frost flowers, slush, and first-year ice with both thin and thick snow cover were measured in the East Antarctic sea-ice zone during the Sea Ice Physics and Ecosystems eXperiment II (SIPEX II) from September to November 2012, near 65°S, 120°E. Albedo was measured across the ultraviolet (UV), visible and near-infrared (nIR) wavelengths, augmenting a dataset from prior Antarctic expeditions with spectral coverage extended to longer wavelengths, and with measurement of slush and frost flowers, which had not been encountered on the prior expeditions. At visible and UV wavelengths, the albedo depends on the thickness of snow or ice; in the nIR the albedo is determined by the specific surface area. The growth of frost flowers causes the nilas albedo to increase by 0.2–0.3 in the UV and visible wavelengths. The spectral albedos are integrated over wavelength to obtain broadband albedos for wavelength bands commonly used in climate models. The albedo spectrum for deep snow on first-year sea ice shows no evidence of light-absorbing particulate impurities (LAI), such as black carbon (BC) or organics, which is consistent with the extremely small quantities of LAI found by filtering snow meltwater. Estimated BC mixing ratios were in the range 0.1–0.5 ng of carbon per gram of snow.

Snow metamorphism and settlement change the microstructure of a snowpack simultaneously. Past experiments investigated snow deformation under isothermal conditions. In nature, temperature gradient metamorphism and settlement often occur together. We investigated snow settlement in the first days after the onset of temperature-gradient metamorphism in laboratory experiments by means of in-situ time-lapse micro-computed tomography. We imposed temperature gradients of up to 95 K m−1 on samples of rounded snow with a density of ~230 kg m−3 and induced settlement by applying 1.7 kPa stress with a passive load on the samples simultaneously. We found that snow settled about half as fast when a temperature gradient was present, compared with isothermal conditions. The change in specific surface area after 4 days caused by temperature-gradient metamorphism was only a few percent. The viscosity evolution correlated with the amount of the temperature gradient. Finite element simulations of the snow samples revealed that stress-bearing chains had developed in the snow structure, causing the large increase in viscosity. We could show that a small change in microstructure caused a large change in the mechanical properties. This explains the difficulty of predicting snow mechanical properties in applications such as firn compaction or snow avalanche formation.

The microstructure and stratigraphy of a snowpack determine its physical behaviour. Weak layers or weak interfaces buried under a slab are prerequisites for the formation of dry-snow slab avalanches, and a precise characterization of weak layers or interfaces is essential to assess stability. Yet their exact geometry and micromechanical properties are poorly known. We cast weak layers and their adjacent layers in the field during two winters and reconstructed their three-dimensional microstructure using X-ray microcomputer tomography. The high resolution of 10–20 μm allowed us to study snow stratigraphy at the microstructural scale. We quantified the microstructural variability for 32 centimetre-sized layered samples and we calculated Young’s modulus and Poisson’s ratio by tomography-based finite-element simulations. Layers in a sample could therefore be differentiated not only by a change in morphology or microstructure, but also by a change in mechanical properties. We found a logarithmic correlation of Young’s modulus with density for two different density ranges, consistent with previous studies. By calculating the relative microstructural changes within our samples, we showed that a large change could indicate a potential weak layer, but only when the weak layer and both adjacent layers, i.e. the sandwich, were considered.