Determining snow specific surface area from near-infrared reflectance measurements: Numerical study of the influence of grain shape
Abstract
Determining the specific surface area of snow from reflectance measurements in the near infrared domain represents a promising technique to rapidly and quantitatively acquire snow stratigraphic profiles in the field. In this paper, we develop a ray tracing model that simulates the albedo of snowpacks composed of geometric crystals (spheres, cubes, cylinders, etc) and model simulations are exploited to study the influence of the grain shape on the SSA-albedo relationship. The results clearly show that the relationship depends on the grain shape at 1310 nm: Cubic (resp. cylindrical) grains reflect about 40% (resp. 20%) more than spherical grains at equal SSA. Depth-hoar modeled as a collection of hollow cubes is found to reflect exactly as much as cubes. None of the tested shapes (including concave and hollow shapes) reflects more than cubes. These results suggest that determining SSA from albedo measurement is uncertain when the snow grain shape is unknown. This uncertainty reaches ± 20% considering that spherical and cubic grains are the two extreme cases in terms of reflexion. This large value is probably over-pessimistic for practical applications as only perfect crystals are considered in this theoretical study and natural snow is always a mixture of curved and plane faces. Therefore, further experimental studies should focus on jointly measuring SSA and albedo in order to assess the influence of the grain shape (or snow type) on the SSA-albedo relationship in natural snows.