Linking the effective thermal conductivity of snow to its shear strength and density

• Published in: Journal of Geophysical Research
• Main Authors: Domine, Florent, Bock, Josué, Morin, Samuel, Giraud, Gérald
• 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), Takuvik International Research Laboratory, Université Laval Québec (ULaval)-Centre National de la Recherche Scientifique (CNRS), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2011
• Subjects: [SDU]Sciences of the Universe [physics]; [SDU.STU]Sciences of the Universe [physics]/Earth Sciences; Arctic; North Pole; Svalbard; Alaska
• Online Access: https://insu.hal.science/insu-03622588; https://insu.hal.science/insu-03622588/document; https://insu.hal.science/insu-03622588/file/Journal%20of%20Geophysical%20Research%20Earth%20Surface%20-%202011%20-%20Domine%20-%20Linking%20the%20effective%20thermal%20conductivity%20of%20snow%20to%20its.pdf; https://doi.org/10.1029/2011JF002000

International audience The effective thermal conductivity of snow, k eff , is a crucial climatic and environmental variable. Here, we test the intuition that k eff is linked to microstructural and mechanical properties by attempting to relate k eff to density ρ snow , and to shear strength σ measured with a handheld shear vane. We performed 106 combined measurements of k eff , ρ snow and σ in the Alps, Svalbard, Arctic Alaska, and near the North Pole, covering essentially all snow types. We find a good correlation between k eff and ρ snow which is not significantly different from that of Sturm et al. (1997). The correlation between k eff and a combination of σ and ρ snow is stronger than with density alone. We propose an equation linking k eff , (W m -1 K -1 ) ρ snow (kg m -3 ) and σ (Pa): k eff = 7.114 10 -5 ρ snow σ 0.333 + 2.367 10 -2 . This equation places constraints on the calculation of k eff , ρ snow and σ in avalanche warning models where σ is a key variable. For our samples, we calculate σ from measured values of k eff and ρ snow using our equation and compare the value to that predicted by the French MEPRA avalanche warning model, which uses density and grain type as input data. MEPRA and the prediction of σ based on k eff and ρ snow agree within 8%. MEPRA agrees with observations within 11%. Calculating σ from density only yields values 55% lower than measured, showing the interest of using additional data to predict σ.