The Cryosphere
The Cryosphere
TC
Articles | Volume 17, issue 6
Articles | Volume 17, issue 6
https://doi.org/10.5194/tc-17-2285-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-2285-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 6
Research article
 | 
08 Jun 2023
Research article |  | 08 Jun 2023

Constraining regional glacier reconstructions using past ice thickness of deglaciating areas – a case study in the European Alps

Christian Sommer, Johannes J. Fürst, Matthias Huss, and Matthias H. Braun

Supplement

https://doi.org/10.5194/tc-17-2285-2023-supplement

Data sets

Surface elevation changes of glaciers in the European Alps between 2000 and 2014 Christian Sommer, Philipp Malz, Thorsten Seehaus, Stefan Lippl, Michael Zemp, and Matthias Braun https://doi.org/10.1594/PANGAEA.914118

Randolph Glacier Inventory - A Dataset of Global Glacier Outlines, Version 6 RGI Consortium https://doi.org/10.7265/4m1f-gd79

The Austrian glacier inventory GI 1, 1969, in ArcGIS (shapefile) format Gernot Patzelt https://doi.org/10.1594/PANGAEA.844983

The Austrian Glacier Inventory GI 4 (2015) in ArcGis (shapefile) format Johannes Buckel and Jan-Christoph Otto https://doi.org/10.1594/PANGAEA.887415

Swiss Glacier Thickness - Release 2020 Melchior Grab https://doi.org/10.3929/ethz-b-000434697

Glacier Thickness Database 3.1.0 GlaThiDa Consortium https://doi.org/10.5904/wgms-glathida-2020-10

Model code and software

Application of a two-step approach for mapping ice thickness to various glacier types on Svalbard (https://github.com/FAU-glacier-systems/ElmerIce_Thickness_Reconstruction) J. J. Fürst, F. Gillet-Chaulet, T. J. Benham, J. A. Dowdeswell, M. Grabiec, F. Navarro, R. Pettersson, G. Moholdt, C. Nuth, B. Sass, K. Aas, X. Fettweis, C. Lang, T. Seehaus, and M. Braun https://doi.org/10.5194/tc-11-2003-2017

The Ice-Free Topography of Svalbard (https://github.com/FAU-glacier-systems/ElmerIce_Thickness_Reconstruction) J. J. Fürst, F. Navarro, F. Gillet-Chaulet, M. Huss, G. Moholdt, X. Fettweis, C. Lang, T. Seehaus, S. Ai, T. J. Benham, D. I. Benn, H. Björnsson, J. A. Dowdeswell, M. Grabiec, J. Kohler, I. Lavrentiev, K. Lindbäck, K. Melvold, R. Pettersson, D. Rippin, A. Saintenoy, P. Sánchez-Gámez, T. V. Schuler, H. Sevestre, E. Vasilenko, and M. H. Braun https://doi.org/10.1029/2018GL079734

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Short summary
Knowledge on the volume of glaciers is important to project future runoff. Here, we present a novel approach to reconstruct the regional ice thickness distribution from easily available remote-sensing data. We show that past ice thickness, derived from spaceborne glacier area and elevation datasets, can constrain the estimated ice thickness. Based on the unique glaciological database of the European Alps, the approach will be most beneficial in regions without direct thickness measurements.
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