A statistical approach to represent small-scale variability of permafrost temperatures due to snow cover

• Published in: The Cryosphere
• Main Authors: Gisnås, K., Westermann, S., Schuler, T. V., Litherland, T., Isaksen, K., Boike, J., Etzelmüller, B.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2014
• Subjects: article; Verlagsveröffentlichung; Norway; permafrost; The Cryosphere
• Online Access: https://doi.org/10.5194/tc-8-2063-2014; https://noa.gwlb.de/receive/cop_mods_00018436; https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00018391/tc-8-2063-2014.pdf; https://tc.copernicus.org/articles/8/2063/2014/tc-8-2063-2014.pdf

In permafrost environments exposed to strong winds, drifting snow can create a small-scale pattern of strongly variable snow heights, which has profound implications for the thermal regime of the ground. Arrays of 26 to more than 100 temperature loggers were installed to record the distribution of ground surface temperatures within three study areas across a climatic gradient from continuous to sporadic permafrost in Norway. A variability of the mean annual ground surface temperature of up to 6°C was documented within areas of 0.5 km2. The observed variation can, to a large degree, be explained by variation in snow height. Permafrost models, employing averages of snow height for grid cells of, e.g., 1 km2, are not capable of representing such sub-grid variability. We propose a statistical representation of the sub-grid variability of ground surface temperatures and demonstrate that a simple equilibrium permafrost model can reproduce the temperature distribution within a grid cell based on the distribution of snow heights.