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Snow physical properties determine its impact on climate and atmospheric chemistry. Essentially, snow physical properties are determined by the sizes of snow grains, their shapes, their spacing and the strength of their interconnections. These aspects will determine measureable variables such as :
- Density. This is the mass of snow per unit volume, usually expressed in kg m-3 (sometimes still in g cm-3). Density is readily measured and is the most widely used snow variable. Many attempts have been made to relate other physical variables to density.
- Specific surface area (SSA). This is the surface area per unit mass, usually expressed in m2 kg-1, although cm2 g-1 was often used in the recent past. If snow grains are assumed to me spheres, then SSA=3.27x106/r, where r is the sphere diameter in µm, and SSA is then in m2 kg-1. The SSA of seasonal snow ranges from 2 m2 kg-1 for melt-freeze crusts to 150 m2 kg-1 for fresh dendritic snow.
- Albedo and e-folding depth. Albedo is the fraction of downwelling radiation that is reflected upward. Both the albedo at a given wavelength and the albedo integrated over the solar spectrum can be considered. Since solar radiation penetrates inside the snow pack, one can be interested in how deep down radiation goes. The e-folding depth is the snow depth over which the actinic flux in the snow decreases by a factor e.
- Heat conductivity. This variable relates the heat flow to the temperature gradient. Heat transfer through snow is the result of several processes, and what is often measured is an effective heat conductivity, keff, such that q=-keff dT/dz, where q is the heat flux and dT/dz is the temperature gradient .
- Shear resistance and other mechanical properties. This is of great interest for avalanche forecasting, but unfortunately it is not within my field of research. Why don't you visit SLF in Davos ?
Our research has focused on the specific surface area (SSA) and more recently on the thermal conductivity of snow. Our activities have included :
- Developing methods to measure snow SSA. Our initial method has been to use methane adsorption at 77 K, a very successful method which has been exported internationally. At present, we are developing a new and faster method based on IR reflectance.
- Performing field and laboratory experiments to quantify the rate of decrease of snow SSA, as a function of temperature and of the temperature gradient in the snowpack.
- Testing models of evolution of particles with given size distributions and test whether theories such as Ostwald ripening could be applied to snow (Short answer : no)
- Producing empirical equations to predict the rate of decrease of snow SSA as a function of environmental variables.
- Since snow albedo is in part determined by snow grain size, i.e. snow SSA, we have speculated on how changes in climate will affect chnages in snow SSA and albedo, and on how this would feed back on climate.
- Performing laboratory experiments to quantify the rate of decrease of the effective heat conductivity of snow, keff, as a function of temperature and of the temperature gradient in the snowpack.
- Performing field measurements of the heat conductivity of snow, and relating the values to environmental variables.
- Integrating both points above to speculate on how climate change will affect , and how changes in will in turn affect environmental processes such as sea ice growth and permafrost disappearance.
Please see our publications for details.