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Titel |
Unlocking annual firn layer water equivalents from ground-penetrating radar data on an Alpine glacier |
VerfasserIn |
L. Sold, M. Huss, A. Eichler , M. Schwikowski, M. Hoelzle |
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 ; 9, no. 3 ; Nr. 9, no. 3 (2015-05-21), S.1075-1087 |
Datensatznummer |
250116802
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Publikation (Nr.) |
copernicus.org/tc-9-1075-2015.pdf |
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Zusammenfassung |
The spatial representation of accumulation measurements is a major
limitation for current glacier mass balance monitoring
approaches. Here, we present a method for estimating annual
accumulation rates on a temperate Alpine glacier based on the
interpretation of internal reflection horizons (IRHs) in
helicopter-borne ground-penetrating radar (GPR) data. For each
individual GPR measurement, the signal travel time is combined with
a simple model for firn densification and refreezing of meltwater. The
model is calibrated at locations where GPR repeat measurements are available in two
subsequent years and the densification can be tracked over time. Two
10.5 m long firn cores provide a reference for the density and
chronology of firn layers. Thereby, IRHs correspond to density maxima,
but not exclusively to former summer glacier surfaces.
Along GPR profile sections from
across the accumulation area we obtain the water
equivalent (w.e.) of several annual firn layers. Because deeper IRHs could be tracked over shorter
distances, the total length of analysed profile sections varies from 7.3 km for the
uppermost accumulation layer (2011) to 0.1 km for the deepest (i.e. oldest) layer (2006).
According to model results, refreezing accounts for
10% of the density increase over time and depth, and for
2% of the water equivalent. The
strongest limitation to our method is the dependence on layer
chronology assumptions. We show that GPR can be used not only to complement
existing mass balance monitoring programmes on temperate
glaciers but also to retrospectively extend newly initiated time
series. |
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