Detailed quantification of glacier elevation and mass changes in South Georgia
Farias-Barahona, David
University of Erlangen Nuremberg
Sommer, Christian
University of Erlangen Nuremberg
Sauter, Tobias
University of Erlangen Nuremberg
Bannister, Daniel
UK Research & Innovation (UKRI)
Seehaus, Thorsten C.
University of Erlangen Nuremberg
Malz, Philipp
University of Erlangen Nuremberg
Mayewski, Paul A.
University of Maine System
Turton, Jenny
University of Erlangen Nuremberg
Braun, Matthias H.
University of Erlangen Nuremberg
Journal
environmental research letters
ISSN
1748-9326
Open Access
gold
Volume
15
Most glaciers in South America and on the Antarctic Peninsula are retreating and thinning. They are considered strong contributors to global sea level rise. However, there is a lack of glacier mass balance studies in other areas of the Southern Hemisphere, such as the surrounding Antarctic Islands. Here, we present a detailed quantification of the 21st century glacier elevation and mass changes for the entire South Georgia Island using bi-static synthetic aperture radar interferometry between 2000 and 2013. The results suggest a significant mass loss since the beginning of the present century. We calculate an average glacier mass balance of -1.04 0.09 m w.e.a(-1) and a mass loss rate of 2.28 0.19 Gt a(-1) (2000-2013), contributing 0.006 0.001 mm a(-1) to sea-level rise. Additionally, we calculate a subaqueous mass loss of 0.77 0.04 Gt a(-1) (2003-2016), with an area change at the marine and lake-terminating glacier fronts of -6.58 0.33 km(2) a(-1), corresponding to similar to 4% of the total glacier area. Overall, we observe negative mass balance rates in South Georgia, with the highest thinning and retreat rates at the large outlet glaciers located at the north-east coast. Although the spaceborne remote sensing dataset analysed in this research is a key contribution to better understanding of the glacier changes in South Georgia, more detailed field measurements, glacier dynamics studies or further long-term analysis with high-resolution regional climate models are required to precisely identify the forcing factors.