A parameterization of the specific surface area of seasonal snow for field use and for models of snowpack evolution

• Published in: Journal of Geophysical Research
• Main Authors: Domine, Florent, Taillandier, Anne-Sophie, Simpson, William R.
• Other Authors: Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Geophysical Institute Fairbanks, University of Alaska Fairbanks (UAF), Department of Chemistry and Biochemistry Fairbanks
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2007
• Subjects: [SDU.STU.GL]Sciences of the Universe [physics]/Earth Sciences/Glaciology; taiga; Tundra
• Online Access: https://hal-insu.archives-ouvertes.fr/insu-00376230; https://hal-insu.archives-ouvertes.fr/insu-00376230/document; https://hal-insu.archives-ouvertes.fr/insu-00376230/file/2006JF000512.pdf; https://doi.org/10.1029/2006JF000512

International audience The specific surface area (SSA) of snow is needed to model air-snow exchange of chemical species. SSA is related to many snow physical properties, such as albedo and permeability. However, it is not described in models of snowpack evolution, in part because it is difficult to measure. Snowpack models often predict snow grain shape and snow density, and the goal of this paper is to propose parameterizations of snow SSA, based on snow density and grain shape. SSA values of 345 snow samples from snowpacks of the Alpine, maritime, tundra and taiga types are presented. Samples are regrouped into three main types: fresh (F), recent (R), and aged (A) snows, with several subtypes referring to grain shapes. Overall, there is a clear inverse correlation between SSA and density, d. Empirical equations of the form SSA = A ln(d) + B are proposed for the F and R types. For aged snows, separate correlations are proposed for subtypes A1 (rounded grains), A2 (faceted crystals), A3 (depth hoar), and A4 (lightly melted snow). Within subtypes A1, A2, and A3, more elaborate classifications are made by considering the snowpack type (Alpine, taiga, or tundra). For A1, A2, and A3 types, different trends are related to different intensities of wind action, which increases in the order taiga, Alpine, and tundra. We finally propose three parameterizations of snow SSA with increasing sophistication, by correlating SSA to snow type, then to snow type and density, and finally to snow type, density, and snowpack type.