Seismic noise interferometry and Distributed Acoustic Sensing (DAS): Inverting for the firn layer S-velocity structure on Rutford Ice Stream, Antarctica

Zhou, Wen; Butcher, Antony; Brisbourne, Alex ORCID: https://orcid.org/0000-0002-9887-7120; Kufner, Sofia-Katerina ORCID: https://orcid.org/0000-0002-9687-5455; Kendall, J-Michael; Stork, Anna. 2022 Seismic noise interferometry and Distributed Acoustic Sensing (DAS): Inverting for the firn layer S-velocity structure on Rutford Ice Stream, Antarctica. Journal of Geophysical Research: Earth Surface, 127 (12), e2022JF006917. 17, pp. https://doi.org/10.1029/2022JF006917

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Abstract/Summary

Firn densification profiles are an important parameter for ice-sheet mass balance and palaeoclimate studies. One conventional method of investigating firn profiles is using seismic refraction surveys, but these are difficult to upscale to large-area measurements. Distributed acoustic sensing (DAS) presents an opportunity for large-scale seismic measurements of firn with dense spatial sampling and easy deployment, especially when seismic noise is used. We study the feasibility of seismic noise interferometry on DAS data for characterizing the firn layer at the Rutford Ice Stream, West Antarctica. Dominant seismic energy appears to come from anthropogenic noise and shear-margin crevasses. The DAS cross-correlation interferometry yields noisy Rayleigh wave signals. To overcome this, we present two strategies for cross-correlations: (1) hybrid instruments – correlating a geophone with DAS, and (2) stacking of selected cross-correlation panels picked in the tau-p domain. These approaches are validated with results derived from an active survey. Using the retrieved Rayleigh wave dispersion curve, we inverted for a high-resolution 1D S-wave velocity profile down to a depth of 100 m. The profile shows a ‘kink’ (velocity gradient inflection) at ∼12 m depth, resulting from a change of compaction mechanism. A triangular DAS array is used to investigate directional variation in velocity, which shows no evident variations thus suggesting a lack of azimuthal anisotropy in the firn. Our results demonstrate the potential of using DAS and seismic noise interferometry to image the near-surface and present a new approach to derive S-velocity profiles from surface wave inversion in firn studies.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1029/2022JF006917
Additional Keywords:	Distributed Acoustic Sensing, noise interferometry, firn, near-surface imaging, glacier, S velocity model
Date made live:	16 Dec 2022 15:08 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/531891

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