Abstract
Abstract. We carried out a study to monitor the time evolution of microstructural and physical properties of snow during temperature gradient metamorphism: a snow slab was subjected to a constant temperature gradient in the vertical direction for 3 weeks in a cold room, and regularly sampled in order to obtain a series of three-dimensional (3-D) images using X-ray microtomography. A large set of properties was then computed from this series of 3-D images: density, specific surface area, correlation lengths, mean and Gaussian curvature distributions, air and ice tortuosities, effective thermal conductivity, and intrinsic permeability. Whenever possible, specific attention was paid to assess these properties along the vertical and horizontal directions, and an anisotropy coefficient defined as the ratio of the vertical over the horizontal values was deduced. The time evolution of these properties, as well as their anisotropy coefficients, was investigated, showing the development of a strong anisotropic behavior during the experiment. Most of the computed physical properties of snow were then compared with two analytical estimates (self-consistent estimates and dilute beds of spheroids) based on the snow density, and the size and anisotropy of the microstructure through the correlation lengths. These models, which require only basic microstructural information, offer rather good estimates of the properties and anisotropy coefficients for our experiment without any fitting parameters. Our results highlight the interplay between the microstructure and physical properties, showing that the physical properties of snow subjected to a temperature gradient cannot be described accurately using only isotropic parameters such as the density and require more refined information. Furthermore, this study constitutes a detailed database on the evolution of snow properties under a temperature gradient, which can be used as a guideline and a validation tool for snow metamorphism models at the micro- or macroscale.
Highlights
Natural snowpacks are frequently subjected to temperature gradients induced by their environment
Löwe et al (2013) proposed a refined parameterization of the effective thermal conductivity tensor of snow based on anisotropic second-order bounds. Their results show the importance of taking into account the microstructural anisotropy for the estimation of the effective thermal conductivity during temperature gradient (TG) metamorphism. We propose addressing these issues by studying the evolution of snow morphology together with several physical properties during a typical experiment of TG metamorphism
As the non-diagonal terms of the tensors τ i, τ a, k and K are negligible compared to the diagonal terms, we only focus on the latter ones
Summary
Natural snowpacks are frequently subjected to temperature gradients induced by their environment. Due to temperature differences in the snowpack, the morphology of snow at the microscale, i.e., the snow microstructure, quickly evolves with time. This metamorphism, called temperature gradient (TG) metamorphism, is mainly characterized by the reorganization of ice along the gradient direction by sublimation of the warmest parts of the grains, water vapor transport across the air pores, and its deposition on the coldest zones of the ice matrix (Yosida et al, 1955; de Quervain, 1973; Colbeck, 1997; Flin and Brzoska, 2008).
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