Observing glacier elevation changes from spaceborne optical and radar sensors – an inter-comparison experiment using ASTER and TanDEM-X data

• Main Authors: Piermattei, Livia, Zemp, Michael, Sommer, Christian, Brun, Fanny, Braun, Matthias, Andreassen, Liss M., Belart, Joaquín M. C., Berthier, Etienne, Bhattacharya, Atanu, Boehm Vock, Laura, Bolch, Tobias, Dehecq, Amaury, Dussaillant, Ines, Falaschi, Daniel, Florentine, Caitlyn, Floricioiu, Dana, Ginzler, Christian, Guillet, Gregoire, Hugonnet, Romain, Huss, Matthias, Kääb, Andreas, King, Owen, Klug, Christoph, Knuth, Friedrich, Krieger, Lukas, La Frenierre, Jeff, McNabb, Robert, McNeil, Christopher, Prinz, Rainer, Sass, Louis, Seehaus, Thorsten, Shean, David, Treichler, Désirée, Wendt, Anja, Yang, Ruitang
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2024
• Subjects: SAR-Signalverarbeitung; The Cryosphere; The Cryosphere Discussions
• Online Access: https://elib.dlr.de/199477/; https://elib.dlr.de/199477/1/egusphere-2023-2309.pdf; https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2309/

Observations of glacier mass changes are key to understanding the response of glaciers to climate change and related impacts, such as regional runoff, ecosystem changes, and global sea-level rise. Spaceborne optical and radar sensors make it possible to quantify glacier elevation changes, and thus multi-annual mass changes, on a regional and global scale. However, estimates from a growing number of studies show a wide range of results with differences often beyond uncertainty bounds. Here, we present the outcome of a community-based inter-comparison experiment using spaceborne optical stereo (ASTER) and synthetic aperture radar interferometry (TanDEM-X) data to estimate elevation changes for defined glaciers and target periods that pose different assessment challenges. Using provided or self-processed digital elevation models (DEMs) for five test sites, 12 research groups provided a total of 97 spaceborne elevation-change datasets using various processing strategies. Validation with airborne data showed that using an ensemble estimate is promising to reduce random errors from different instruments and processing methods, but still requires a more comprehensive investigation and correction of systematic errors. We found that scene selection, DEM processing, and co-registration have the biggest impact on the results. Other processing steps, such as treating spatial data voids, differences in survey periods, or radar penetration, can still be important for individual cases. Future research should focus on testing different implementations of individual processing steps (e.g. co-registration) and addressing issues related to temporal corrections, radar penetration, glacier area changes, and density conversion. Finally, there is a clear need for our community to develop best practices, use open, reproducible software, and assess overall uncertainty in order to enhance inter-comparison and empower physical process insights across glacier elevation-change studies.