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.

Snow appears as a granular material in most engineering applications. We examined the role of grain shape and cohesion in angle of repose experiments, which are a common means for the characterization of granular materials. The role of shape was examined by investigating diverse snow types with discernable shape and spherical ice beads. Two geometrical shape parameters were calculated from X-ray micro-computed-tomography images after a particle segmentation was performed with a watershed algorithm. Cohesion was examined by conducting experiments at six different temperatures between −40 and −2°C, assuming sintering as its cause, which accelerates with increasing temperature. As a cohesionless reference, experiments with glass beads were performed. We found that both shape and cohesion exerted about equally strong influence on the angle of repose. We utilized our results for an empirical model that describes the influence of shape and cohesion as additive corrections of the angle of repose of cohesionless spheres and explains all experiments with a correlation coefficient r2 = 0.95. With temperature and the chosen shape parameter as fitting variables, previous experiments with another snow type could be consistently included. The experiments highlight the relevance of these parameters in granular snow mechanics and can be used for model calibration.

A new in situ sensor for the simultaneous measurement of snow water equivalent, snow density and liquid-water content is presented in this paper. The system consists of radio frequency transmission lines of up to 25 m length cast in a flat PVC band, which can be set up either horizontally to monitor single snow-layer properties or sloping from a mast to the soil surface to determine vertical snowpack properties. The dielectric coefficient along the flat-band cable is measured with a time-domain reflectometer at high frequencies, and with a low-frequency impedance analyzer. The performance of the sensor system was tested during two winter seasons (2001–03) at the high-alpine test site Weissfluhjoch, Davos, Switzerland. The cable suspension and set-up of the sloping cable was shown to be critical with regard to stability and the formation of unwanted air gaps along the cable. Overall, the sensing system proved quite robust and produced results in agreement with manual snowpack observations.

The mechanisms leading to dry-snow slab release are influenced by the three-dimensional variability of the snow cover. We measured 113 profiles of penetration resistance with a snow micropenetrometer on an alpine snow slope. Seven distinct layers were visually identified in all snow micropenetrometer profiles. The penetration resistance of adjacent layers did not change abruptly, but gradually across layer boundaries that were typically 2 mm thick. In two layers, penetration resistance varied around 200% over the grid, possibly due to wind effects during or after layer deposition. Penetration resistance varied around 25%in five layers. Statistically significant slope-scale linear trends were found for all layers. The semivariogram was used to describe the spatial variation. Penetration resistance was autocorrelated, but the scale of variation was layer-specific. A buried layer of surface hoar was the most critical weak layer. It had little spatial variation. The layers in the slab above had higher spatial variation. The penetration resistance of each snow layer had distinct geostatistical properties, caused by the depositional processes.

We investigated a buried surface-hoar layer using the SnowMicroPen (SMP), an instrument designed to measure detailed snowpack profiles.We collected data from two adjacent parts of a slope 6 days apart. In addition, one manual snowpack profile was sampled each day, as well as 50 quantified loaded column tests (QLCTs) which provided an index of shear strength. For the SMP data, a 900 m2 area was sampled on both days in a grid with points 3 mapart, with some sub-areas of more closely spaced measurements. We collected 86 SMP profiles on the first day and 129 on the second day. Our analyses involved manually locating layer boundaries and calculating statistics for the force signal through the surface-hoar layer. The shear strength index increased by 40% between the two sampling days, but the SMP data show no statistical difference in layer thickness, and the mean, minimum, median, and a variety of percentile measures of the SMP force signal through the layer also do not change. Interestingly, the maximum hardness, and the variance and coefficient of variation of the SMP signal, increased. Since the small SMP tip might only break one or a couple of bonds as it passes through the weak layer, we interpret these changes as being indicative of increasing bond strength. Though we cannot specifically tie the increasing maximum hardness of the SMP signal to our QLCT results, our work suggests that the maximum SMP signal within buried surface-hoar layers may be useful for tracking increases in the shear strength of those layers.

Snow-cover models are used in many applications in today’s snow and ice research. Descriptions of changes in size and shape are a major problem in modelling the snow cover. Empirical models for kinetic growth under temperature gradients have been developed, as well as more complicated models based upon microstructure. In this work a simple; physically based model is derived which depends on one adjustable geometric factor only Snow texture is described as a body-centred cubic lattice containing source and sink grains. The latter grow as plates due to water-vapour transport in the layer as well as between the layers. The model was implemented in a research version of the one-dimensional snow-cover model SNOWPACK. Model outputs are compared to experiments done in the cold laboratory where sieved snow is subjected to temperature gradients. Disaggregated snow samples are analyzed by digital image processing, by sieving and by visual characterization. In order to determine grain-size as objectively as possible, these various methods are evaluated for compatibility. The new model simulates very well kinetic grain growth for densities of 100–200 kg m−3 and temperature gradients up to –200 Km−1. The model will be incorporated in the operational version of SNOWPACK.

The mechanical properties of snow depend on its microstructure. The fabric of snow was reconstructed in three dimensions using serial sections or X-ray microtomography. A voxel-based finite-element model, with the elements based on the microstructure and ice as the material, was used to calculate the stress distribution in the snow. A small elastic deformation was simulated and the bulk elastic moduli of these samples were determined. The simulated elastic modulus was 3–10 times or 10–100 times larger than previously published measurements. The deviation is possibly caused by the relatively slow deformation rates of the usual tests. This strain-rate effect is well known for pure ice. Locations of stress concentrations can be extracted and compared to the micro-structural location of bonds. By this method we are able to determine mechanical properties of thin or extremely brittle snow layers which are otherwise difficult or impossible to measure.

The thermal conductivity of snow determines, to a large extent, ground heat flux and snow metamorphism. One common method of measuring the thermal conductivity of snow is with a needle probe. We measured the microstructural changes in the snow around a typical needle using micro- computed tomography. The insertion of the needle probe caused structural changes up to a radial distance of 0.5-1 mm. Using a commercial needle probe with short (30 s) heating time, we measured thermal conductivity values in snow that were 50% lower than the conductivity measured using a calibrated guarded hot-plate apparatus. Numerically simulated time-temperature curves with an introduced air gap that simulated the needle damage reproduced the observed needle-probe results well, confirming that poor contact resistance between the needle and the snow will lead to measurement discrepancies and a large bias. While most measurements in snow have been done using a long heating time and are not subject to this error, the thermal conductivity of snow measured with needle probes with short measurement times should be avoided. This same effect is probably observed in other brittle and highly porous materials, a condition that may not be widely appreciated.

Information on snow-cover stability is important for predicting avalanche danger. Traditionally, stability evaluation is based on manual observations of snow stratigraphy and stability tests, which are time-consuming. The SnowMicroPen (SMP) is a high-resolution, constant-speed penetrometer to measure penetration resistance. We have analysed the resistance signal to derive snow stability. The proposed stability algorithm was developed by comparing 68 SMP force–distance profiles with the corresponding manual profiles, including stability tests. The algorithm identifies a set of four potentially weak layers by taking into account changes in structure and rupture strength of microstructural elements that make up snow layers as derived from the SMP signal. In 90% of the cases, one of the four potentially weak layers proposed by the algorithm coincided with the failure layer observed in the stability test. To select the critical layer from the four potential weaknesses was more difficult. With fully automatic picking of the critical layer, agreement with the failure layer observed in the stability test was reached in 60% of the cases. To derive a stability classification, we analysed weak-layer as well as slab properties. These predictor variables allow the SMP signal to be classified into two stability classes, poor and fair-to-good, with an accuracy of ∼75% when compared with observed stability. The SMP, in combination with the proposed algorithm, shows high potential for providing snow-cover stability information at high resolution in time and space.

The specific surface area (SSA) is considered an essential microstructural parameter for the characterization of snow. Photography in the near-infrared (NIR) spectrum is sensitive to the SSA. We calculated the snow reflectance from calibrated NIR images of snow-pit walls and measured the SSA of samples obtained at the same locations. This new method is used to map the snow stratigraphy. The correlation between reflectance and SSA was found to be 90%. Calibrated NIR photography allows quantitative determination of SSA and its spatial variation in a snow profile in two dimensions within an uncertainty of 15%. In an image covering 0.5–1.0 m2, even layers of 1mm thickness can be documented and measured. Spatial maps of SSA are an important tool in initializing and validating physical and chemical models of the snowpack.

Visualization and quantification of snow structures at a scale of a few millimetres is important in understanding the mechanical, thermal and electromagnetic properties of snow. Surface sections and, to an even greater degree, three-dimensional (3-D) reconstructions of cast snow samples are difficult to prepare, and automatic image processing is notoriously difficult and often requires manual evaluation. Here, we present a new method to measure the 3-D structure of cast snow samples. Snow samples cast with diethyl phthalate (DEP) and frozen are cut to a sample size a few centimetres in diameter and up to 10 cm in height. The ice of these samples is then sublimated in high vacuum and the remaining negative structure (replica) is imaged using X-ray microtomography (micro-CT). The accuracy of the method is demonstrated by comparing micro-CT scans of the original snow structure and the replica. The method described here allows easy transportation of samples, requires little manual interaction, has a very high spatial resolution of up to 10 μm and is environmentally friendly.

A tomography-based methodology for the mass transport characterization of snow is presented. Five samples, characteristic for a wide range of seasonal snow, are considered. Their three-dimensional (3-D) geometrical representations are obtained by micro-computed tomography and used in direct pore-level simulations to numerically solve the governing mass and momentum conservation equations, allowing for the determination of their effective permeability and Dupuit–Forchheimer coefficient. The extension to the Dupuit–coefficient is useful near the snow surface, where Reynolds numbers higher than unity can appear. Simplified semi-empirical models of porous media are also examined. The methodology presented allows for the determination of snow’s effective mass transport properties, which are strongly dependent on the snow microstructure and morphology. These effective properties can, in turn, readily be used in snowpack volume-averaged (continuum) models such as strongly layered samples with macroscopically anisotropic properties.

Time series of observed microwave brightness temperatures at Dome C, East Antarctic plateau, were modeled over 27 months with a multilayer microwave emission model based on dense-medium radiative transfer theory. The modeled time series of brightness temperature at 18.7 and 36.5 GHz were compared with Advanced Microwave Scanning Radiometer–EOS observations. The model uses in situ high-resolution vertical profiles of temperature, snow density and grain size. The snow grain-size profile was derived from near-infrared (NIR) reflectance photography of a snow pit wall in the range 850–1100 nm. To establish the snow grain-size profile, from the NIR reflectance and the specific surface area of snow, two empirical relationships and a theoretical relationship were considered. In all cases, the modeled brightness temperatures were overestimated, and the grain-size profile had to be scaled to increase the scattering by snow grains. Using a scaling factor and a constant snow grain size below 3 m depth (i.e. below the image-derived snow pit grain-size profile), brightness temperatures were explained with a root-mean-square error close to 1 K. Most of this error is due to an overestimation of the predicted brightness temperature in summer at 36.5 GHz.

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.

The physical properties of snow are tied to its microstructure. Especially for the slow, plastic deformation of snow and firn, the crystal orientation is an important factor in addition to the geometry of the ice matrix. While micro-computed tomography measures the snow microstructure precisely, it gives no information about the orientation of the ice crystals. In this study, we applied a temperature gradient of 50 K m−1 to large blocks of undisturbed decomposed snow and sieved snow during 3 months. The mean temperature of the snow samples during the temperature gradient experiment was −20°C. Two closely spaced snow samples were taken before the experiment, then every week during the first month and afterwards every month. From each sampling, one sample was analyzed by micro-computed tomography and the other was used for thin sections. The orientation of the c-axis was measured in the thin sections using an automatic ice texture analyzer. Initial density was 30% higher in the sieved snow sample. Density and specific surface area evolved alike, while the fabric showed a different evolution between the two samples. The undisturbed snow evolved from a weak single-maximum fabric towards a weak girdle fabric, while the sieved sample showed no evolution. The undisturbed snow sample converged toward the sieved sample fabric after 6 weeks, but continued its evolution thereafter. We suggest that the main factor causing this different behavior is the difference in density and in pore size.

Understanding physical processes in near-zero accumulation areas can help us to better understand polar ice-core records, particularly during periods when accumulation rates were lower than today. We report measurements from a 5 m firn core from the Allan Hills, Antarctica, which include physical properties using computer tomography, stable isotope ratios δD and δ18O, and 210Pb activity. The core shows a highly metamorphosed firn with homogeneous and stable structure, but with discrete layers near the surface. The observed firn structure is caused by a combination of unique depositional and post-depositional processes. The irregular δD and δ18O signal does not follow the stratigraphic sequence and implies post-depositional modification caused by microscopic pressure gradients in the firn that can result from either forced ventilation over rough surfaces in the presence of wind or alternating temperature-gradients between the firn and the atmosphere. Our results also indicate impact snow deposition under high winds and with a high initial density and air exchange between the atmosphere and the snowpack.210Pb activity below 0.3 m falls below the detection limit, implying that most of the core is more than 100 years old. We conclude that the Allan Hills record provides a unique opportunity to investigate important processes that would have affected ice-core records from glacial periods.

We present an improved machine to produce nature-identical snow in a cold laboratory for reproducible experiments. The machine is based on the common supersaturation principle of blowing cold air over a heated water basin. The moist airstream is directed into a chamber, where it cools and the nucleation of ice crystals is promoted on stretched nylon wires. Snow crystals grow on the wires and are harvested regularly by a new automatic brush rack. Depending on the settings, different snow crystals can be produced, which are shown to be consistent with the Nakaya diagram. The main snow types are dendrites and needles. We prepared specimens from the snow produced by the snowmaker and analyzed them using microcomputer tomography. For dendrites we show that there are natural snow samples that have the same crystal shape and similar microstructural parameters, namely density and specific surface area. The machine can produce suitable amounts of snow for laboratory experiments in an efficient way. As an advantage over previous designs, uniform and reproducible snow samples can be generated under well-defined conditions.

The instrumented sample holder Snowbreeder 5 is used to investigate the simultaneous influence of settlement on temperature-gradient snow metamorphism in time-lapse micro-computed tomography experiments. So far, experiments have only been done on temperature-gradient snow metamorphism without settlement or settlement under isothermal conditions. With the new device we can impose a constant temperature gradient on a snow sample and induce settlement by placing a passive load on top of the snow sample. The weight of the load can be varied, simulating various snow heights on top of the snow sample. Snow-temperature measurements on the passive load are possible due to wireless data transfer via Bluetooth. The temperature gradient is set by controlling the air temperature inside the computer tomograph and by a Peltier element at the bottom of the snow sample. First experiments under isothermal conditions and a constant temperature gradient of 43 K m−1 showed that the settlement was reduced to almost half as soon as a temperature gradient was applied under otherwise almost equal snow conditions. The compactive viscosity in the isothermal experiment was in the range of literature values.

Time-domain reflectometry (TDR) is widely used in soil physics to determine water content. Existing equipment and methods ran be adapted to measurements of snow wetness. The main advantages compared to other methods are flexibility in constructing sensors, minimal influence on snow cover during measurements and sensors can be multiplexed. We developed sensors suitable for continuous and non-continuous measurements of snow wetness and density, measured the apparent permittivity in different snow densities and snow types, and compared the measurements to existing mixing formulas for mixtures of snow and air. In dry snow, density was measured from 110 to 470 kg m−3. The residual error is 14 kg m −3 and the 95% confidence interval of our model is 3 kg m−3. To measure snow density and wetness continuously suitable sensors have been constructed. Their small size and high surface area to weight ratio minimizes their movement in the snowpack, except when they are exposed to intense solar radiation. Results show that changes in dry-snow density of less than 5 kgm−3 can be detected. Infiltration of even small amounts of water clearly shows up in the permittivity. At the surface of the snowpack, problems occur due to the formation of air pockets around the sensors during long-term measurements.