Of critical importance for avalanche forecasting, is the ability to draw meaningful conclusions from only a handful of field observations. To that end, it is common for avalanche forecasters to not only have to rely on sparse data, but also on their own intuitive understanding of how their field-based observations may be correlated to complex physical processes responsible for structural instability within a snowpack. One such well-documented basis for mechanical instability to increase within a snowpack is that caused by the presence of a buried ice lens or ice crust. Although such icy layers are naturally formed and frequently encountered in seasonal snowpacks, very little is known about the microstructural evolution of these layers and how they contribute towards weak layer development. Furthermore, in terms of assessing the structural integrity of the snowpack, there is at the present time no consistent treatment for identifying these layers a priori as problematic or benign. To address this issue, we have created an idealized laboratory scenario in which we can study how an artificially created ice lens may affect the thermophysical and microstructural state of the interface between the ice lens and adjacent layers of snow while under a controlled temperature gradient of primarily-100 K m-1. Utilizing in situ micro-thermocouple measurements, our findings show that a super-temperature gradient exists within only a millimeter of the ice

Effective snow grain radius (re) is mapped at high resolution using near-infrared hyperspectral imaging (NIR-HSI). The NIR-HSI method can be used to quantify re spatial variability, change in re due to metamorphism, and visualize water percolation in the snowpack. Results are presented for three different laboratory-prepared snow samples (homogeneous, ice lens, fine grains over coarse grains), the sidewalls of which were imaged before and after melt induced by a solar lamp. The spectral reflectance in each ~3 mm pixel was inverted for re using the scaled band area of the ice absorption feature centered at 1030 nm, producing re maps consisting of 54 740 pixels. All snow samples exhibited grain coarsening post-melt as the result of wet snow metamorphism, which is quantified by the change in re distributions from pre- and post-melt images. The NIR-HSI method was compared to re retrievals from a field spectrometer and X-ray computed microtomography (micro-CT), resulting in the spectrometer having the same mean re and micro-CT having 23.9% higher mean re than the hyperspectral imager. As compact hyperspectral imagers become more widely available, this method may be a valuable tool for assessing re spatial variability and snow metamorphism in field and laboratory settings.

One of the challenges that limit the amount of information that can be inferred from radar measurements of ice and mixed-phase precipitating clouds is the variability in ice mass within hydrometeors. The variable amount of ice mass within particles of a given size drives further variability in single-scattering properties that results in uncertainties of forward-modeled remote sensing quantities. Nonspherical ice-phase hydrometeors are often approximated as spheroids to simplify the calculation of single-scattering properties, yet offline calculations remain necessary to quantify these radiative properties as a function of size in discrete increments. In this paper, a simple scaling of the Clausius–Mossotti factor is used that allows for an approximation of the scattering and extinction cross sections for an arbitrary mass–dimensional power-law relationship of a nonspherical particle given a single T-matrix calculation. Using data collected by the University of Wyoming King Air in snow clouds over the Colorado Park Range, the uncertainty in forward-modeled radar reflectivity to assumptions regarding mass–dimensional relationships is examined. This is accomplished by taking advantage of independently measured condensed mass and particle size distributions to estimate the variability of the prefactor in the mass–dimensional power law. Then, calculating the partial derivative of the radar backscatter cross sections using the scaling relationships, an estimate is made of the statistical uncertainty in forward-modeled radar reflectivity. Uncertainties on the order of 4 dB are found in this term for the dataset considered.

The Earth's large continental ice sheets contain a variety of naturally occurring impurities, both soluble and insoluble. Understanding how these impurities affect the rheology, intrinsic thermodynamic properties, and fate of these ice sheets is not well understood. To investigate the effects that trace amounts of H2SO4 have on the flow and ductility of polycrystalline ice, a series of mechanical tests were conducted at −6, −10, −12.5, and −20°C using laboratory‐prepared specimens of polycrystalline ice doped with 1–15 ppm of H2SO4. Parallel tests were performed on identical but undoped specimens of polycrystalline ice. Mechanical testing included constant‐load tensile creep tests at an initial stress of 0.75 MPa and compression tests at constant displacement rates with initial strain rates ranging from 1 × 10−6 to 1 × 10−4 s−1. It was found that H2SO4‐doped specimens of ice exhibited faster creep rates in tension and significantly lower peak stresses in compression, when compared to the undoped ice. Postmortem microstructural analyses were performed using cross‐polarized light thin section imaging, X‐ray computed microtomography, Raman spectroscopy, and electron backscatter diffraction. These analyses showed that H2SO4‐doped specimens had a larger grain size at strains ≤15%, and an earlier onset of microcracking at lower strain rates than the undoped ice. Strain‐induced grain boundary migration was found to be the predominant mechanism of recrystallization in both doped and undoped specimens. Further, an aqueous phase of H2SO4 was found to exist at the grain boundaries and triple junctions of the doped ice, which is thought to have significantly contributed toward its reduced viscosity.