Articles | Volume 20, issue 4
https://doi.org/10.5194/tc-20-2439-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-20-2439-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
27 Apr 2026
Research article |
| 27 Apr 2026
| 27 Apr 2026
Simulating the effect of natural convection in a tundra snow cover
CRYOS, School of Architecture, Civil and Environmental Engineering, EPFL, Lausanne, Switzerland
Michael Lehning
CRYOS, School of Architecture, Civil and Environmental Engineering, EPFL, Lausanne, Switzerland
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
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Cited articles
Armstrong, R. L. and Brun, E.: Snow and Climate: Physical Processes, Surface Energy Exchange and Modeling, Cambridge University Press, ISBN-13 978-0521130653, 2009. a
Bartelt, P. and Lehning, M.: A physical SNOWPACK model for the Swiss avalanche warning: Part I: numerical model, Cold Reg. Sci. Technol., 35, 123–145, https://doi.org/10.1016/S0165-232X(02)00074-5, 2002. a, b, c
Bear, J.: On the tensor form of dispersion in porous media, J. Geophys. Res., 66, 1185–1197, 1961. a
Bear, J.: Dynamics of fluids in porous media, Courier Corporation, 1988. a
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, https://doi.org/10.5194/tc-6-939-2012, 2012. a, b
Calonne, N., Geindreau, C., and Flin, F.: Macroscopic modeling of heat and water vapor transfer with phase change in dry snow based on an upscaling method: Influence of air convection, J. Geophys. Res.-Earth, 120, 2476–2497, https://doi.org/10.1002/2015JF003605, 2015. a
Delgado, J.: Longitudinal and transverse dispersion in porous media, Chem. Eng. Res. Des., 85, 1245–1252, 2007. a
Derksen, C., Silis, A., Sturm, M., Holmgren, J., Liston, G. E., Huntington, H., and Solie, D.: Northwest Territories and Nunavut snow characteristics from a subarctic traverse: Implications for passive microwave remote sensing, J. Hydrometeorol., 10, 448–463, 2009. a
Domine, F., Barrere, M., Sarrazin, D., Morin, S., and Arnaud, L.: Automatic monitoring of the effective thermal conductivity of snow in a low-Arctic shrub tundra, The Cryosphere, 9, 1265–1276, https://doi.org/10.5194/tc-9-1265-2015, 2015. a
Domine, F., Barrere, M., and Sarrazin, D.: Seasonal evolution of the effective thermal conductivity of the snow and the soil in high Arctic herb tundra at Bylot Island, Canada, The Cryosphere, 10, 2573–2588, https://doi.org/10.5194/tc-10-2573-2016, 2016. a, b, c, d
Domine, F., Belke-Brea, M., Sarrazin, D., Arnaud, L., Barrere, M., and Poirier, M.: Soil moisture, wind speed and depth hoar formation in the Arctic snowpack, J. Glaciol., 64, 990–1002, https://doi.org/10.1017/jog.2018.89, 2018. a, b
Domine, F., Lackner, G., Sarrazin, D., Poirier, M., and Belke-Brea, M.: Meteorological, snow and soil data (2013–2019) from a herb tundra permafrost site at Bylot Island, Canadian high Arctic, for driving and testing snow and land surface models, Earth Syst. Sci. Data, 13, 4331–4348, https://doi.org/10.5194/essd-13-4331-2021, 2021. a, b, c
Duchesne, D., Gauthier, G., and Berteaux, D.: Habitat selection, reproduction and predation of wintering lemmings in the Arctic, Oecologia, 167, 967–980, https://doi.org/10.1007/s00442-011-2045-6, 2011. a
Fahs, M., Graf, T., Tran, T. V., Ataie-Ashtiani, B., Simmons, C. T., and Younes, A.: Study of the effect of thermal dispersion on internal natural convection in porous media using Fourier series, Transport Porous Med., 131, 537–568, 2020. a
Gouttevin, I., Langer, M., Löwe, H., Boike, J., Proksch, M., and Schneebeli, M.: Observation and modelling of snow at a polygonal tundra permafrost site: spatial variability and thermal implications, The Cryosphere, 12, 3693–3717, https://doi.org/10.5194/tc-12-3693-2018, 2018. a
Hansen, A. C. and Foslien, W. E.: A macroscale mixture theory analysis of deposition and sublimation rates during heat and mass transfer in dry snow, The Cryosphere, 9, 1857–1878, https://doi.org/10.5194/tc-9-1857-2015, 2015. a
Jafari, M.: Water vapor transport in snowpacks, EPFL, PhD thesis, p. 154, https://doi.org/10.5075/epfl-thesis-9659, 2022. a
Jafari, M.: cryos-snowBedFoam/SNOWPACKFoam: SNOWPACKFoam v1.0.0 (paper snapshot for egusphere-2025-3035) (v1.0.0), Zenodo [software], https://doi.org/10.5281/zenodo.18788998, 2026. a
Jafari, M. and Lehning, M.: snowpackBuoyantPimpleFoam: an OpenFOAM Eulerian–Eulerian two-phase solver for modelling convection of water vapor in snowpacks, EnviDat [data set], https://doi.org/10.16904/envidat.265, 2021. a
Jafari, M. and Lehning, M.: Convection of snow: when and why does it happen?, Front. Earth Sci., 11, https://doi.org/10.3389/feart.2023.1167760, 2023a. a
Jafari, M. and Lehning, M.: Convection of snow: when and why does it happen?, Front. Earth Sci., 11, https://doi.org/10.3389/feart.2023.1167760, 2023b. a
Jafari, M., Gouttevin, I., Couttet, M., Wever, N., Michel, A., Sharma, V., Rossmann, L., Maass, N., Nicolaus, M., and Lehning, M.: The Impact of Diffusive Water Vapor Transport on Snow Profiles in Deep and Shallow Snow Covers and on Sea Ice, Front. Earth Sci., 8, 249, https://doi.org/10.3389/feart.2020.00249, 2020. a, b, c, d, e
Keenan, E., Wever, N., Dattler, M., Lenaerts, J. T. M., Medley, B., Kuipers Munneke, P., and Reijmer, C.: Physics-based SNOWPACK model improves representation of near-surface Antarctic snow and firn density, The Cryosphere, 15, 1065–1085, https://doi.org/10.5194/tc-15-1065-2021, 2021. a, b, c
Kvernvold, O. and Tyvand, P. A.: Dispersion effects on thermal convection in porous media, J. Fluid Mech., 99, 673–686, https://doi.org/10.1017/S0022112080000821, 1980. a
Lehning, M., Bartelt, P., Brown, B., Russi, T., Stöckli, U., and Zimmerli, M.: SNOWPACK model calculations for avalanche warning based upon a network of weather and snow stations, Cold Reg. Sci. Technol., 30, 145–157, https://doi.org/10.1016/S0165-232X(99)00022-1, 1999. a, b, c
Lehning, M., Bartelt, P., Brown, B., and Fierz, C.: A physical SNOWPACK model for the Swiss avalanche warning Part III: Meteorological forcing, thin layer formation and evaluation, Cold Reg. Sci. Technol., 35, 169–184, https://doi.org/10.1016/S0165-232X(02)00072-1, 2002a. a, b, c
Moukalled, F., Mangani, L., and Darwish, M.: The finite volume method in computational fluid dynamics, vol. 6, Springer, https://doi.org/10.1007/978-3-319-16874-6, 2016. a
Poirier, M., Fauteux, D., Gauthier, G., Domine, F., and Lamarre, J.-F.: Snow hardness impacts intranivean locomotion of arctic small mammals, Ecosphere, 12, e03835, https://doi.org/10.1002/ecs2.3835, 2021. a
Reid, D. G., Bilodeau, F., Krebs, C. J., Gauthier, G., Kenney, A., Gilbert, B., Leung, M., Duchesne, D., and Hofer, E.: Lemming winter habitat choice: a snow-fencing experiment, Behav. Ecol., 22, 1056–1062, https://doi.org/10.1093/beheco/arr086, 2011. a
Sommer, C. G., Wever, N., Fierz, C., and Lehning, M.: Investigation of a wind-packing event in Queen Maud Land, Antarctica, The Cryosphere, 12, 2923–2939, https://doi.org/10.5194/tc-12-2923-2018, 2018. a
Sturm, M. and Benson, I. C. S.: Vapor transport, grain growth and depth-hoar development in the subarctic snow, J. Glaciol., 43, https://doi.org/10.3189/S0022143000002793, 1997. a, b, c
Sturm, M. and Johnson, J. B.: Natural convection in the subarctic snow cover, J. Geophys. Res.-Sol. Ea., 96, 11657–11671, https://doi.org/10.1029/91JB00895, 1991. a, b, c, d
Taillandier, A.-S., Domine, F., Simpson, W. R., Sturm, M., Douglas, T. A., and Severin, K.: Evolution of the snow area index of the subarctic snowpack in central Alaska over a whole season. Consequences for the air to snow transfer of pollutants, Environ. Sci. Technol., 40, 7521–7527, 2006. a
Vikhamar-Schuler, D., Hanssen-Bauer, I., Schuler, T. V., Mathiesen, S. D., and Lehning, M.: Use of a multilayer snow model to assess grazing conditions for reindeer, Ann. Glaciol., 54, 214–226, https://doi.org/10.3189/2013AoG62A306, 2013. a
Wen, B., Chang, K. W., and Hesse, M. A.: Rayleigh-Darcy convection with hydrodynamic dispersion, Physical Review Fluids, 3, 123801, https://doi.org/10.1103/PhysRevFluids.3.123801, 2018. a
Wever, N., Keenan, E., Amory, C., Lehning, M., Sigmund, A., Huwald, H., and Lenaerts, J. T. M.: Observations and simulations of new snow density in the drifting snow-dominated environment of Antarctica, J. Glaciol., 69, 823–840, https://doi.org/10.1017/jog.2022.102, 2023. a, b, c
Short summary
We studied how air moves within snow in Arctic regions and how this affects the snow's structure. Using a new method that links two computer models, we found that cold weather can trigger air movement inside the snow, creating vertical channels and changing the snow's density and temperature. These changes are not captured by traditional models, so our work helps improve how snow and climate processes are simulated in cold environments.
We studied how air moves within snow in Arctic regions and how this affects the snow's...
