Small-scale variation of snow in a regional permafrost model
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 me...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2016-06-01
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| Series: | The Cryosphere |
| Online Access: | http://www.the-cryosphere.net/10/1201/2016/tc-10-1201-2016.pdf |
| Summary: | 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 km<sup>2</sup> 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 km<sup>2</sup> 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 km<sup>2</sup> 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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| ISSN: | 1994-0416 1994-0424 |