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Distributed Acoustic Sensing Recordings of Cryoseismicity Enable Seismic Imaging of Permafrost in Remote Arctic Regions

Distributed Acoustic Sensing Recordings of Cryoseismicity Enable Seismic Imaging of Permafrost in Remote Arctic Regions

This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.

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Authors

Ahmad Tourei , Eileen Martin, Gabriel Fernando Rocha dos Santos, Tieyuan Zhu, Nikhil Punithan, Ming Xiao

Abstract

Permafrost can be highly heterogeneous, and variability in its subsurface structure under climate warming remains poorly understood despite the critical role of permafrost in Arctic hydrology, ecosystems, and infrastructure stability. Distributed acoustic sensing (DAS) provides a long-term method for dense seismic array monitoring in remote regions with passively recorded seismic activities. We deployed a 2 km fiber-optic DAS array across disturbed and undisturbed tundra near Utqiagvik, Alaska. It recorded naturally occurring cryoseismic events generated by shallow thermal contraction cracking. These events fill data gaps and provide seismic energy for imaging subsurface permafrost structure. We assessed the effects of gauge length and wave-propagation direction on the extracted dispersion characteristics and evaluated the stability and uncertainty of the resulting shear-wave velocity (Vs) inversions. The resulting Vs models reveal deep ice-rich layers interpreted as massive ground ice. This demonstrates a new, scalable technique for permafrost characterization using cryoseismic energy, which may have potential for time-lapse monitoring of permafrost dynamics and supporting infrastructure resilience in remote regions.

DOI

https://doi.org/10.31223/X56492

Subjects

Geophysics and Seismology, Geotechnical Engineering, Glaciology

Keywords

Arctic Region, Cryoseismology, Permafrost, Distributed Acoustic Sensing

Dates

Published: 2026-07-29 15:56

Last Updated: 2026-07-30 10:54

License

CC BY Attribution 4.0 International

Additional Metadata

Data Availability:
The das-anomaly Python package (Tourei, 2026a) was used for cryoseismic event detection. DASCore (Chambers et al., 2024) was used for DAS dispersion analysis, along with hvsrpy (Vantassel, 2025) and SWinvert (Vantassel & Cox, 2021) packages for post-processing of the dispersion images. MasavesPy library (Olafsdottir et al., 2024) was used for MC inversion, and IntelligentMASW(Liu etal., 2020) was used for NLLS inversion of the Vs profiles. The DAS data are on Arctic Data Center (Tourei, 2026b) and A21K data are reported through EARTHSCOPE DMC and were accessed using ObsPy IRIS client (Beyreuther et al., 2010).

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