Quantifying uncertainty in using multiple datasets to determine spatiotemporal ice mass loss over 101 years at kårsaglaciären, sub‐arctic sweden

Abstract

Glacier mass balance and mass balance gradient are fundamentally affected by changes in glacier 3D geometry. Few studies have quantified changing mountain glacier 3D geometry, not least because of a dearth of suitable spatiotemporally distributed topographical information. Additionally, there can be significant uncertainty in georeferencing of historical data and subsequent calculations of the difference between successive surveys. This study presents multiple 3D glacier reconstructions and the associated mass balance response of Kårsaglaciären, which is a 0.89 ± 0.01 km² mountain glacier in sub‐arctic Sweden. Reconstructions spanning 101 years were enabled by historical map digitisation and contemporary elevation and thickness surveys. By considering displacements between digitised maps via the identification of common tie‐points, uncertainty in both vertical and horizontal planes were estimated. Results demonstrate a long‐term trend of negative mass balance with an increase in mean elevation, total glacier retreat (1909–2008) of 1311 ± 12 m, and for the period 1926–2010 a volume decrease of 1.0 ± 0.3 × 10^–3 km³ yr^–1. Synthesising measurements of the glaciers’ past 3D geometry and ice thickness with theoretically calculated basal stress profiles explains the present thermal regime. The glacier is identified as being disproportionately fast in its rate of mass loss and relative to area, is the fastest retreating glacier in Sweden. Our long‐term dataset of glacier 3D geometry changes will be useful for testing models of the evolution of glacier characteristics and behaviour, and ultimately for improving predictions of meltwater production with climate change.

Key words:

• mountain glacier
• mass balance
• glacier reconstruction
• glacier geometry

Acknowledgements

C. Williams was supported by a NERC PhD studentship whilst at the University of Leeds. Fieldwork was supported by INTERACT grants obtained by J. Carrivick and D. Rippin. The AWS was funded by the University of Leeds and installed with help from L. Brown and D. Hannah. D. Carrivick and A. O'Leary are thanked for their extensive help in the field. P. Holmlund and P. Jansson are thanked for their support in providing original data as well as for their expert local knowledge. The staff at the Abisko Naturvetenskapliga Station (ANS) are thanked for all of their help with logistics and access to meteorological data records for the Abisko region.

Notes

1. GLIMS, and National Snow and Ice Data Center, 2005, updated 2012. GLIMS Glacier Database, version 1. National Snow and Ice Data Center, Boulder, Colorado USA. http://dx.doi.org/10.7265/N5V98602

[Correction added on 17 March 2016 after initial online publication on 16 March 2016: Figures have been changed to color online.]

Additional information

Notes on contributors

Christopher N. Williams

Christopher N. Williams, Bristol Glaciology Group, University of Bristol, Bristol BS8 1SS, UK Email: [email protected]

Jonathan L. Carrivick

Jonathan L. Carrivick, Andrew J. Evans, School of Geography, University of Leeds, Leeds LS2 9JT, UK Email: [email protected], [email protected]

David M. Rippin

David M. Rippin, Environment Department, University of York, York YO10 5DD, UK Email: [email protected]