Snow accumulation variability derived from radar and firn core data along a 600 km transect in Adelie Land, East Antarctic plateau

• Published in: The cryosphere 2012-11, Vol.6 (6), p.1345-1358
• Main Authors: Verfaillie, D, Fily, M, Le Meur, E, Magand, O, Jourdain, B, Arnaud, L, Favier, V
• Format: Article
• Language: English
• Subjects: Analysis; Arctic research; Earth Sciences; Ice sheets; Marine; Radar; Sciences of the Universe
• ISSN: 1994-0424; 1994-0416; 1994-0424; 1994-0416
• DOI: 10.5194/tc-6-1345-2012

The mass balance of ice sheets is an intensively studied topic in the context of global change and sea-level rise. However – particularly in Antarctica – obtaining mass balance estimates remains difficult due to various logistical problems. In the framework of the TASTE-IDEA (Trans-Antarctic Scientific Traverses Expeditions – Ice Divide of East Antarctica) program, an International Polar Year project, continuous ground penetrating radar (GPR) measurements were carried out during a traverse in Adelie Land (East Antarctica) during the 2008–2009 austral summer between the Italian–French Dome C (DC) polar plateau site and French Dumont D'Urville (DdU) coastal station. The aim of this study was to process and interpret GPR data in terms of snow accumulation, to analyse its spatial and temporal variability and compare it with historical data and modelling. The focus was on the last 300 yr, from the pre-industrial period to recent times. Beta-radioactivity counting and gamma spectrometry were applied to cores at the LGGE laboratory, providing a depth–age calibration for radar measurements. Over the 600 km of usable GPR data, depth and snow accumulation were determined with the help of three distinct layers visible on the radargrams (≈ 1730, 1799 and 1941 AD). Preliminary results reveal a gradual increase in accumulation towards the coast (from ≈ 3 cm w.e. a−1 at Dome C to ≈ 17 cm w.e. a−1 at the end of the transect) and previously undocumented undulating structures between 300 and 600 km from DC. Results agree fairly well with data from previous studies and modelling. Drawing final conclusions on temporal variations is difficult because of the margin of error introduced by density estimation. This study should have various applications, including model validation.