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| Titel |
Scale-dependent measurement and analysis of ground surface temperature variability in alpine terrain |
| VerfasserIn |
S. Gubler, J. Fiddes, M. Keller, S. Gruber |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1994-0416
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| Digitales Dokument |
URL |
| Erschienen |
In: The Cryosphere ; 5, no. 2 ; Nr. 5, no. 2 (2011-05-25), S.431-443 |
| Datensatznummer |
250002434
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| Publikation (Nr.) |
 copernicus.org/tc-5-431-2011.pdf |
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| Zusammenfassung |
Measurements of environmental variables are often used to validate and
calibrate physically-based models. Depending on their application,
the models are used at different scales, ranging from few meters to tens
of kilometers. Environmental variables can vary strongly within the
grid cells of these models. Validating a model with a single
measurement is therefore delicate and susceptible to induce bias in
further model applications.
To address the question of uncertainty associated with scale in
permafrost models, we present data of 390 spatially-distributed ground
surface temperature measurements recorded in terrain of high
topographic variability in the Swiss Alps. We illustrate a way to
program, deploy and refind a large number of measurement devices
efficiently, and present a strategy to reduce data loss reported in
earlier studies. Data after the first year of deployment is presented.
The measurements represent the variability of ground surface
temperatures at two different scales ranging from few meters to some
kilometers. On the coarser scale, the dependence of mean annual ground
surface temperature on elevation, slope, aspect and ground cover type
is modelled with a multiple linear regression model. Sampled mean annual ground
surface temperatures vary from −4 °C to 5 °C
within an area of approximately 16 km2 subject to elevational differences of
approximately 1000 m. The measurements also indicate that
mean annual ground surface temperatures vary up to 6 °C
(i.e., from −2 °C to 4 °C) even within an
elevational band of 300 m. Furthermore, fine-scale variations can be high (up
to 2.5 °C) at distances of less than 14 m in homogeneous
terrain. The effect of this high variability of an environmental
variable on model validation and applications in alpine regions is
discussed. |
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