Articles | Volume 10, issue 1
Research article
15 Feb 2016
Research article |  | 15 Feb 2016

Intercomparison of snow density measurements: bias, precision, and vertical resolution

Martin Proksch, Nick Rutter, Charles Fierz, and Martin Schneebeli

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Cited articles

Adams, E. and Sato, A.: Model of effective thermal conductivity of a dry snow cover composed of uniform spheres, Ann. Glaciol., 18, 300–304, 1993.
Albert, M.: Modeling heat, mass, and species transport in polar firn, Ann. Glaciol., 23, 138–143, 1996.
Brun, E., Martin, E., Simon, V., Gendre, C., and Coleou, C.: An energy and mass model of snow cover suitable for operational avalanche forecasting, J. Glaciol., 35, 333–342, 1989.
Calonne, N., Flin, F., Morin, S., Lesaffre, B., Rolland du Roscoat, S., and Geindreau, C.: Numerical and experimental investigations of the effective thermal conductivity of snow, Geophys. Res. Lett., 38, L23501,, 2011.
Calonne, N., Geindreau, C., Flin, F., Morin, S., Lesaffre, B., Rolland du Roscoat, S., and Charrier, P.: 3-D image-based numerical computations of snow permeability: links to specific surface area, density, and microstructural anisotropy, The Cryosphere, 6, 939–951,, 2012.
Short summary
Density is a fundamental property of porous media such as snow. During the MicroSnow Davos 2014 workshop, different approaches (box-, wedge- and cylinder-type density cutters, micro-computed tomography) to measure snow density were applied in a controlled laboratory environment and in the field. In general, results suggest that snow densities measured by different methods agree within 9 %. However, the density profiles resolved by the measurement methods differed considerably.