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| Titel |
Active-layer thermal monitoring on the Fildes Peninsula, King George Island, maritime Antarctica |
| VerfasserIn |
R. F. M. Michel, C. E. G. R. Schaefer, F. M. B. Simas, M. R. Francelino, E. I. Fernandes-Filho, G. B. Lyra, J. G. Bockheim |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1869-9510
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| Digitales Dokument |
URL |
| Erschienen |
In: Solid Earth ; 5, no. 2 ; Nr. 5, no. 2 (2014-12-21), S.1361-1374 |
| Datensatznummer |
250115363
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| Publikation (Nr.) |
 copernicus.org/se-5-1361-2014.pdf |
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| Zusammenfassung |
| International attention to climate change phenomena has grown in the last
decade; the active layer and permafrost are of great importance in
understanding processes and future trends due to their role in energy flux
regulation. The objective of this paper is to present active-layer
temperature data for one Circumpolar Active Layer Monitoring South hemisphere (CALM-S) site located on the Fildes Peninsula, King George
Island, maritime Antarctica over an 57-month period (2008–2012).
The monitoring site was installed during the summer of 2008 and consists of
thermistors (accuracy of ±0.2 °C), arranged vertically with
probes at different depths, recording data at hourly intervals in a high-capacity data logger. A series of statistical analyses was performed to
describe the soil temperature time series, including a linear fit in order to
identify global trends, and a series of autoregressive integrated moving
average (ARIMA) models was tested in order to define the best fit for the
data. The affects of weather on the thermal regime of the active layer have
been identified, providing insights into the influence of climate change
on permafrost. The active-layer thermal regime in the studied period
was typical of periglacial environments, with extreme variation in surface
during the summer resulting in frequent freeze and thaw cycles. The active-layer
thickness (ALT) over the studied period shows a degree of variability related
to different annual weather conditions, reaching a maximum of 117.5 cm in
2009. The ARIMA model could describe the data adequately and is an important
tool for more conclusive analysis and predictions when longer data sets are
available. Despite the variability when comparing temperature readings and
ACT over the studied period, no trend can be identified. |
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