Using airborne Ku-band altimeter waveforms to investigate winter accumulation and glacier facies on Austfonna, Svalbard

Winter balance is an important metric for assessing the change on glaciers and ice caps, yet measuring it using ground-based techniques can be challenging. We use the European Space Agency prototype Airborne SAR/Interferometric Radar Altimeter System (ASIRAS) to extract snow depths from the received...

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Bibliographic Details
Published in:Journal of Glaciology
Main Authors: HAWLEY, Robert L., BRANDT, Ola, DUNSE, Thorben, HAGEN, Jon Ove, Helm, Veit, KOHLER, Jack, LANGLEY, Kirsty, MALNES, Eirik, HØGDA, Kjell-Arild
Format: Article in Journal/Newspaper
Language:unknown
Published: 2013
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Online Access:https://epic.awi.de/id/eprint/33671/
https://doi.org/10.3189/2013JoG13J051
https://hdl.handle.net/10013/epic.42037
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Summary:Winter balance is an important metric for assessing the change on glaciers and ice caps, yet measuring it using ground-based techniques can be challenging. We use the European Space Agency prototype Airborne SAR/Interferometric Radar Altimeter System (ASIRAS) to extract snow depths from the received altimeter waveforms over Austfonna ice cap, Svalbard. Additionally, we attempt to distinguish the long-term firn area from other glacier facies. We validate our results using snow depth and glacier facies characterizations determined from ground-based radar profiles, snow pits and a multi- look satellite synthetic aperture radar image. We show that the depth of the winter snowpack can be extracted from the altimeter data over most of the accumulation zone, comprising wet snow zone and a superimposed ice zone. The method struggles at lower elevations where internal reflections within the winter snowpack are strong and the winter snow depth is less than 1m. We use the abruptness of the reflection from the last summer surface (LSS) to attempt to distinguish glacier facies. While there is a general correlation between LSS abruptness and glacier facies, we do not find a relationship that warrants a distinct classification based on ASIRAS waveforms alone.