Project

Discipline

Mass transport; Recrystallization

Lead
Lay summary
Using in-situ micro-tomography of representative snow samples, an experimental system will be developed for investigating the snow metamorphism under airflow. In-situ time-lapse experimental runs will be first conducted using micro computer tomography (μCT) on quasi-isothermal snow, and then extended on snow under a temperature gradient. The 3D digital representations of snow samples will be obtained by μCT and applied in direct pore-level simulations (DPLS) to numerically solve the governing mass, momentum, and energy conservation equations, allowing for the determination of the snow’s effective transport properties. Finally, phase-field modeling will simulate the observed evolution of the microstructure. Of special focus is the accurate determination of the effective permeability and thermal conductivity. Vapor mass flux and recrystallization rate will be determined using an adapted version of particle image velocimetry based on time-lapse images. A functional understanding of snow metamorphism combined with airflow will give more in-depth understanding of the snow structure observed in polar and alpine regions.  The research proposed has crucial significance to a wide range of environmental processes, including evolution of the snowpack in arctic regions, and flux mechanism of trace gases exchanged between the ground and atmospheric air. This project will enable the determination of more accurate effective transport properties, which in turn can be incorporated in forecasting models of late-stage alpine snowpack responsible for large-scale avalanches.

Direct link to Lay Summary

Last update: 21.02.2013

Active participation

Number	Title	Start	Funding scheme

Using in-situ micro-tomography of representative snow samples, we plan to develop an experimental system where metamorphism under airflow can be quantified. In-situ time-lapse experimental runs will be first conducted in micro computer tomography (µCT) on quasi-isothermal snow, and then extended on snow under a temperature gradient. A new sample holder will be designed for these experiments. Effective heat and mass transport properties, as well as diffusion and advection processes at the pore level, will be determined by direct pore-level numerical simulations and validated with direct measurements. Finally, phase-field modeling will simulate the observed evolution of the microstructure.The 3D geometrical representations of snow samples will be obtained by µCT and used in direct pore-level simulations (DPLS) to numerically solve the governing mass, momentum, and energy conservation equations, allowing for the determination of the snow’s effective transport properties. Of special focus is the accurate determination of the effective permeability and thermal conductivity. Vapor mass flux and recrystallization rate will be determined using an adapted version of particle image velocimetry based on time-lapse images. We will examine the coupling between recrystallization rate and permeability for experiments with an imposed temperature gradient under advective conditions.A functional understanding of snow metamorphism combined with airflow will give more in-depth understanding of the snow structure observed in polar and alpine regions. The research proposed has crucial significance to a wide range of environmental processes, as the results of our experiments and simulations can be used for improving models of firn compaction and evolution, for understanding evolution of the snowpack in arctic regions, for elucidating the flux mechanism of trace gases exchanged between the ground and atmospheric air, and for providing more accurate effective transport properties to forecasting models of late-stage alpine snowpack responsible for large scale avalanches.