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

Flavien Beaud, Saif Aati, Ian Delaney, Surendra Adhikari, Jean-Philippe Avouac

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Abstract

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.
Original languageEnglish
Pages (from-to)3123-3148
Number of pages26
JournalThe Cryosphere
Volume16
Issue number8
DOIs
Publication statusPublished - 3 Aug 2022

Bibliographical note

This research has been supported by the Caltech-JPL President’s and Director’s Fund program and the Resnick Sustainability Institute, and the Swiss National Science Fund Mobility Postdoc Fellowships (grant no. P2SKP2_171755; 2017–2019 and P400P2_191105; 2020–2021).

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