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| Titel |
Regional scale distribution of permafrost in Norway based on two equilibrium models. |
| VerfasserIn |
Kjersti Gisnås, Herman Farbrot, Bernd Etzelmüller, Thomas Vikhamar Schuler |
| Konferenz |
EGU General Assembly 2011
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 13 (2011) |
| Datensatznummer |
250046461
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| Zusammenfassung |
| Previous regional permafrost mapping in Norway has exclusively been based on mean annual
air temperature (MAAT). While MAAT is important when considering the climatic
limitations and thus macro-scale distribution of permafrost, many other factors such as the
timing and thickness of the snow cover, vegetation and thermal properties in the active layer
are of decisive importance when considering regional/discontinuous (meso-scale) permafrost
presence. Two established equilibrium models are used to determine the permafrost
distribution in mainland Norway: (1) the empirically based TTOP-model (temperature at top
of permafrost), by Smith & Riseborough (1996), and (2) the Kudryavtsev approach,
implemented in the GIPL-model (Geophysical Institute Permafrost Laboratory, University of
Alaska, Fairbanks, Sazonova & Romanovsky (2003)). While both models define the top of
permafrost from air temperatures, the TTOP-model includes seasonal n-factors derived from
vegetation and snow cover distribution, and the conductivity ratio between frozen and thawed
states in the active layer. Correspondingly, the Kudryavtsev approach utilizes a
physical parameterization of snow- and vegetation cover and the soil in the active
layer.
Block fields are known to represent a negative thermal anomaly. While these features are
widespread in Norway, currently available digital sediment maps do not accurately represent
observed block-field distribution. Therefore, block fields have been identified from Landsat
images and have been considered in the models presented above. Petrophysical data such as
bedrock density and thermal conductivity have been kindly provided by the Norwegian
Geological Survey. Both models are implemented at 1km resolution for mainland Norway,
and forced with operationally gridded temperature and snowdepth data from the period
1960-2010, provided by Norwegian Meteorological Institute and Norwegian Water and
Energy Directorate.
The model results are validated against: (1) ground surface temperature from 140
miniature temperature data loggers distributed throughout Norway; (2) vertical temperature
profiles measured in 20 boreholes; and (3) maps of palsa- and rock glacier distribution. The
modelled permafrost distribution agrees relatively well with observations, and reproduces
regional permafrost patterns. Compared to estimates based solely on MAAT, both the TTOP-
and GIPL-models present a more accurate representation of the observed east-west gradient
due to the consideration of snowdepth . Sporadic permafrost, which was not represented in
previous regional modelling, is now reproduced, due to the incorporation of sediment
conductivity data. Despite these improvements, topographic variation introduces challenges
related to snow distribution and ground thermal properties. The largest sources of error in the
TTOP-model relate to the freezing factors (nf) for snow and the thermal regime
in block field areas which is controlled by both convective and conductive heat
transfer.
Sazonova, T and Romanovsky, V. 2003. A model for regional scale estimation of
temporal and spatial variability of active layer thickness and mean annual ground
temperatures. Permafrost and Periglacial Processes 14, 125-139.
Smith, M., & Riseborough, D. 1996. Permafrost Monitoring and Climate Change.
Permafrost and Periglacial Processes (7). 301-307. |
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