Surge dynamics of Shisper Glacier revealed by time-series correlation of optical satellite images and their utility to substantiate a generalized sliding law

Understanding fast ice flow is key to assessing the future of glaciers. Fast ice flow is controlled by sliding at the bed, yet that sliding is poorly understood. A growing number of studies show the relationship between sliding and basal shear stress transitions from an initially rate-strengthening...

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Bibliographic Details
Published in:The Cryosphere
Main Authors: Beaud, Flavien, Aati, Saif, Delaney, Ian, Adhikari, Surendra, Avouac, Jean-Philippe
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2022
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Online Access:https://doi.org/10.5194/tc-16-3123-2022
https://noa.gwlb.de/receive/cop_mods_00062099
https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00061431/tc-16-3123-2022.pdf
https://tc.copernicus.org/articles/16/3123/2022/tc-16-3123-2022.pdf
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Summary:Understanding fast ice flow is key to assessing the future of glaciers. Fast ice flow is controlled by sliding at the bed, yet that sliding is poorly understood. A growing number of studies show the relationship between sliding and basal shear stress transitions from an initially rate-strengthening behavior to a rate-independent or rate-weakening behavior. Studies that have tested a glacier sliding law with data remain rare. Surging glaciers, as we show in this study, can be used as a natural laboratory to inform sliding laws because a single glacier shows extreme velocity variations at a subannual timescale. The present study has two main goals: (1) we introduce a new workflow to produce velocity maps with a high spatiotemporal resolution from remote-sensing data, combining Sentinel-2 (S2) and Landsat 8 (L8) and using the results to describe the recent surge of Shisper Glacier, and (2) we present a generalized sliding law and substantiate the sliding-law behavior using the remote sensing dataset. The quality and spatiotemporal resolution of the velocity time series allow us to identify a gradual amplification of spring speed-up velocities in the 2 years leading up to the surge that started in November 2017. We also find that surface velocity patterns during the surge can be decomposed into three main phases, and each phase appears to be associated with hydraulic changes. Using this dataset, we are able to highlight the rate-independent and rate-weakening relationships between resistive stress and sliding during the surge. We then discuss the importance of the generalized sliding relationship to reconcile observations of fast ice flow, and in particular, different surge behaviors. The approach used in this study remains qualitative, but if coupled with better bed-elevation data and numerical modeling could lead to the widespread quantification of sliding-law parameters.