Preprints
https://doi.org/10.5194/egusphere-2023-1340
https://doi.org/10.5194/egusphere-2023-1340
20 Jul 2023
 | 20 Jul 2023

Towards the systematic reconnaissance of seismic signals from glaciers and ice sheets – Part A: Event detection for cryoseismology

Rebecca B. Latto, Ross J. Turner, Anya M. Reading, and J. Paul Winberry

Abstract. Cryoseismology is a powerful toolset for progressing the understanding of the structure and dynamics of glaciers and ice sheets. It can enable the detection of hidden processes such as brittle fracture, basal sliding, transient hydrological processes, and calving. Due to the diversity and often low signal-to-noise levels of glacier processes, the automated detection of seismic events caused by such processes can pose a challenge. We present a novel approach for the automated detection of events in glacier environments, the multi-STA/LTA algorithm, with a focus on capturing the many signal types recorded on ice sheet margins. This develops the use of approaches that use the ratio between short and long time averages (sta,lta) of signal amplitude as the means of event detection. Implemented in the open source and widely used ObsPy python package, the algorithm constructs a hybrid characteristic function from a set of sta, lta pairs. We apply the multi-STA/LTA algorithm to data from a seismic array deployed on the Whillans Ice Stream (WIS) in West Antarctica (austral summer 2010–2011), to form an event catalogue. The new algorithm compares favorably with standard approaches, yielding a diversity of seismic events, including all previously identified stick-slip events (Pratt et al., 2014), teleseisms, and other noise-type signals. We investigate a partial association of seismicity with the tidal cycle, and a slight association with ice temperature changes of the Antarctic summer. The new algorithm and workflow has the potential to yield systematic catalogues for further cryoseismology studies: conventional glacier seismology, and those tailored to pattern recognition by machine learning.

Rebecca B. Latto, Ross J. Turner, Anya M. Reading, and J. Paul Winberry

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1340', Anonymous Referee #1, 07 Aug 2023
    • AC1: 'Reply on RC1', Rebecca Latto, 08 Sep 2023
  • RC2: 'Comment on egusphere-2023-1340', Anonymous Referee #2, 07 Aug 2023
    • AC2: 'Reply on RC2', Rebecca Latto, 08 Sep 2023
Rebecca B. Latto, Ross J. Turner, Anya M. Reading, and J. Paul Winberry

Data sets

Electronic Supplement Rebecca B. Latto and Ross J. Turner and Anya M. Reading https://github.com/beccalatto/multi_sta_lta

Model code and software

An ObsPy library for event detection and seismic attribute calculation: preparing waveforms for automated analysis Ross J. Turner and Rebecca B. Latto and Anya M. Reading http://doi.org/10.5334/jors.365

Rebecca B. Latto, Ross J. Turner, Anya M. Reading, and J. Paul Winberry

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Short summary
The study of icequakes allows for investigation of many glacier processes that are unseen by typical reconnaissance methods. However, detection of such seismic signals is challenging because of low signal-to-noise levels and diverse source mechanisms. Here, we present a novel algorithm that is optimized to detect signals from a glacier environment. We apply the algorithm to seismic data recorded in the 2010–2011 austral summer from Whillans Ice Stream then evaluate the resulting event catalogue.