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Volume 10, issue 3
The Cryosphere, 10, 1201–1215, 2016
https://doi.org/10.5194/tc-10-1201-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: The evolution of permafrost in mountain regions

The Cryosphere, 10, 1201–1215, 2016
https://doi.org/10.5194/tc-10-1201-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 03 Jun 2016

Research article | 03 Jun 2016

Small-scale variation of snow in a regional permafrost model

Kjersti Gisnås1, Sebastian Westermann1, Thomas Vikhamar Schuler1, Kjetil Melvold2, and Bernd Etzelmüller1 Kjersti Gisnås et al.
  • 1Department of Geosciences, University of Oslo, Oslo, Norway
  • 2Norwegian Water Resources and Energy Directorate, Oslo, Norway

Abstract. The strong winds prevalent in high altitude and arctic environments heavily redistribute the snow cover, causing a small-scale pattern of highly variable snow depths. This has profound implications for the ground thermal regime, resulting in highly variable near-surface ground temperatures on the metre scale. Due to asymmetric snow distributions combined with the nonlinear insulating effect of snow, the spatial average ground temperature in a 1 km2 area cannot be determined based on the average snow cover for that area. Land surface or permafrost models employing a coarsely classified average snow depth will therefore not yield a realistic representation of ground temperatures. In this study we employ statistically derived snow distributions within 1 km2 grid cells as input to a regional permafrost model in order to represent sub-grid variability of ground temperatures. This improves the representation of both the average and the total range of ground temperatures. The model reproduces observed sub-grid ground temperature variations of up to 6 °C, and 98 % of borehole observations match the modelled temperature range. The mean modelled temperature of the grid cell reproduces the observations with an accuracy of 1.5 °C or better. The observed sub-grid variations in ground surface temperatures from two field sites are very well reproduced, with estimated fractions of sub-zero mean annual ground surface temperatures within ±10 %. We also find that snow distributions within areas of 1 km2 in Norwegian mountain environments are closer to a gamma than to a lognormal theoretical distribution. The modelled permafrost distribution seems to be more sensitive to the choice of distribution function than to the fine-tuning of the coefficient of variation. When incorporating the small-scale variation of snow, the modelled total permafrost area of mainland Norway is nearly twice as large compared to the area obtained with grid-cell average snow depths without a sub-grid approach.

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In wind exposed areas snow redistribution results in large spatial variability in ground temperatures. In these areas, the ground temperature of a grid cell must be determined based on the distribution, and not the average, of snow depths. We employ distribution functions of snow in a regional permafrost model, showing highly improved representation of ground temperatures. By including snow distributions, we find the permafrost area to be nearly twice as large as what is modelled without.
In wind exposed areas snow redistribution results in large spatial variability in ground...
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