dc.date.accessioned | 2016-08-03T12:40:28Z | |
dc.date.available | 2016-08-03T12:40:28Z | |
dc.date.issued | 2016 | |
dc.identifier.uri | http://hdl.handle.net/10852/51039 | |
dc.description.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. | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Kjersti Gisnås (2016) Permafrost modelling over different scales in arctic and high-mountain environments. Doctoral thesis. http://urn.nb.no/URN:NBN:no-54520 | |
dc.relation.uri | http://urn.nb.no/URN:NBN:no-54520 | |
dc.rights | Attribution 3.0 Unported | |
dc.rights.uri | https://creativecommons.org/licenses/by/3.0/ | |
dc.title | Small-scale variation of snow in a regional permafrost model | en_US |
dc.type | Journal article | en_US |
dc.creator.author | Gisnås, Kjersti | |
dc.creator.author | Westermann, Sebastian | |
dc.creator.author | Schuler, Thomas Vikhamar | |
dc.creator.author | Melvold, Kjetil | |
dc.creator.author | Etzelmüller, Bernd | |
dc.identifier.jtitle | The Cryosphere | |
dc.identifier.volume | 10 | |
dc.identifier.startpage | 1201 | |
dc.identifier.endpage | 1215 | |
dc.identifier.doi | 10.5194/tcd-9-6661-2015 | |
dc.identifier.urn | URN:NBN:no-54522 | |
dc.type.document | Tidsskriftartikkel | en_US |
dc.type.peerreviewed | Peer reviewed | |
dc.identifier.fulltext | Fulltext https://www.duo.uio.no/bitstream/handle/10852/51039/1/tc-10-1201-2016.pdf | |
dc.type.version | PublishedVersion | |