Articles | Volume 16, issue 8
https://doi.org/10.5194/tc-16-3357-2022
https://doi.org/10.5194/tc-16-3357-2022
Research article
 | 
25 Aug 2022
Research article |  | 25 Aug 2022

Snow properties at the forest–tundra ecotone: predominance of water vapor fluxes even in deep, moderately cold snowpacks

Georg Lackner, Florent Domine, Daniel F. Nadeau, Matthieu Lafaysse, and Marie Dumont

Related authors

Meteorological, snow and soil data, CO2, water and energy fluxes from a low-Arctic valley of Northern Quebec
Florent Domine, Denis Sarrazin, Daniel F. Nadeau, Georg Lackner, and Maria Belke-Brea
Earth Syst. Sci. Data, 16, 1523–1541, https://doi.org/10.5194/essd-16-1523-2024,https://doi.org/10.5194/essd-16-1523-2024, 2024
Short summary
On the energy budget of a low-Arctic snowpack
Georg Lackner, Florent Domine, Daniel F. Nadeau, Annie-Claude Parent, François Anctil, Matthieu Lafaysse, and Marie Dumont
The Cryosphere, 16, 127–142, https://doi.org/10.5194/tc-16-127-2022,https://doi.org/10.5194/tc-16-127-2022, 2022
Short summary
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
Florent Domine, Georg Lackner, Denis Sarrazin, Mathilde Poirier, and Maria Belke-Brea
Earth Syst. Sci. Data, 13, 4331–4348, https://doi.org/10.5194/essd-13-4331-2021,https://doi.org/10.5194/essd-13-4331-2021, 2021
Short summary

Related subject area

Discipline: Snow | Subject: Arctic (e.g. Greenland)
Assessment of Arctic seasonal snow cover rates of change
Chris Derksen and Lawrence Mudryk
The Cryosphere, 17, 1431–1443, https://doi.org/10.5194/tc-17-1431-2023,https://doi.org/10.5194/tc-17-1431-2023, 2023
Short summary
Observed and predicted trends in Icelandic snow conditions for the period 1930–2100
Darri Eythorsson, Sigurdur M. Gardarsson, Andri Gunnarsson, and Oli Gretar Blondal Sveinsson
The Cryosphere, 17, 51–62, https://doi.org/10.5194/tc-17-51-2023,https://doi.org/10.5194/tc-17-51-2023, 2023
Short summary
Spatial patterns of snow distribution in the sub-Arctic
Katrina E. Bennett, Greta Miller, Robert Busey, Min Chen, Emma R. Lathrop, Julian B. Dann, Mara Nutt, Ryan Crumley, Shannon L. Dillard, Baptiste Dafflon, Jitendra Kumar, W. Robert Bolton, Cathy J. Wilson, Colleen M. Iversen, and Stan D. Wullschleger
The Cryosphere, 16, 3269–3293, https://doi.org/10.5194/tc-16-3269-2022,https://doi.org/10.5194/tc-16-3269-2022, 2022
Short summary
Snowfall and snow accumulation during the MOSAiC winter and spring seasons
David N. Wagner, Matthew D. Shupe, Christopher Cox, Ola G. Persson, Taneil Uttal, Markus M. Frey, Amélie Kirchgaessner, Martin Schneebeli, Matthias Jaggi, Amy R. Macfarlane, Polona Itkin, Stefanie Arndt, Stefan Hendricks, Daniela Krampe, Marcel Nicolaus, Robert Ricker, Julia Regnery, Nikolai Kolabutin, Egor Shimanshuck, Marc Oggier, Ian Raphael, Julienne Stroeve, and Michael Lehning
The Cryosphere, 16, 2373–2402, https://doi.org/10.5194/tc-16-2373-2022,https://doi.org/10.5194/tc-16-2373-2022, 2022
Short summary
Inter-comparison of snow depth over Arctic sea ice from reanalysis reconstructions and satellite retrieval
Lu Zhou, Julienne Stroeve, Shiming Xu, Alek Petty, Rachel Tilling, Mai Winstrup, Philip Rostosky, Isobel R. Lawrence, Glen E. Liston, Andy Ridout, Michel Tsamados, and Vishnu Nandan
The Cryosphere, 15, 345–367, https://doi.org/10.5194/tc-15-345-2021,https://doi.org/10.5194/tc-15-345-2021, 2021
Short summary

Cited articles

Anderson, E. A.: A point energy and mass balance model of a snow cover, https://repository.library.noaa.gov/view/noaa/6392 (last access: 20 January 2022), 1976. a, b
Barrere, M., Domine, F., Decharme, B., Morin, S., Vionnet, V., and Lafaysse, M.: Evaluating the performance of coupled snow–soil models in SURFEXv8 to simulate the permafrost thermal regime at a high Arctic site, Geosci. Model Dev., 10, 3461–3479, https://doi.org/10.5194/gmd-10-3461-2017, 2017. a, b, c, d, e, f, g
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
Bartlett, P. A., MacKay, M. D., and Verseghy, D. L.: Modified snow algorithms in the Canadian land surface scheme: Model runs and sensitivity analysis at three boreal forest stands, Atmos. Ocean, 44, 207–222, https://doi.org/10.3137/ao.440301, 2006. a
Belke-Brea, M., Domine, F., Boudreau, S., Picard, G., Barrere, M., Arnaud, L., and Paradis, M.: New allometric equations for Arctic shrubs and their application for calculating the albedo of surfaces with snow and protruding branches, J. Hydrometeorol., 21, 1–49, https://doi.org/10.1175/JHM-D-20-0012.1, 2020. a, b
Download
Short summary
We compared the snowpack at two sites separated by less than 1 km, one in shrub tundra and the other one within the boreal forest. Even though the snowpack was twice as thick at the forested site, we found evidence that the vertical transport of water vapor from the bottom of the snowpack to its surface was important at both sites. The snow model Crocus simulates no water vapor fluxes and consequently failed to correctly simulate the observed density profiles.