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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 Link zu Wikipedia, M. Schwikowski, M. Hoelzle
Medientyp Artikel
Sprache Englisch
ISSN 1994-0416
Digitales Dokument URL
Erschienen In: The Cryosphere ; 9, no. 3 ; Nr. 9, no. 3 (2015-05-21), S.1075-1087
Datensatznummer 250116802
Publikation (Nr.) Volltext-Dokument vorhandencopernicus.org/tc-9-1075-2015.pdf
 
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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