Improved moving window cross‐spectral analysis for resolving large temporal seismic velocity changes in permafrost

• Published in: Geophysical research letters Vol. 44; no. 9; pp. 4018 - 4026
• Main Authors: James, S. R., Knox, H. A., Abbott, R. E., Screaton, E. J.
• Format: Journal Article
• Language: English
• Published: Washington John Wiley & Sons, Inc 16.05.2017; American Geophysical Union
• Subjects: Ambient noise; ambient seismic noise; cycle‐skipping; GEOSCIENCES; Ice; Interferometry; Monitoring; Noise; Noise monitoring; Permafrost; Seismic activity; Seismology; Soil dynamics; Spectra; Spectral analysis; Velocity; Alaska; Arctic; United States > US; Arctic region; USA, Alaska
• ISSN: 0094-8276; 1944-8007
• DOI: 10.1002/2016GL072468

Cross correlations of seismic noise can potentially record large changes in subsurface velocity due to permafrost dynamics and be valuable for long‐term Arctic monitoring. We applied seismic interferometry, using moving window cross‐spectral analysis (MWCS), to 2 years of ambient noise data recorded in central Alaska to investigate whether seismic noise could be used to quantify relative velocity changes due to seasonal active‐layer dynamics. The large velocity changes (>75%) between frozen and thawed soil caused prevalent cycle‐skipping which made the method unusable in this setting. We developed an improved MWCS procedure which uses a moving reference to measure daily velocity variations that are then accumulated to recover the full seasonal change. This approach reduced cycle‐skipping and recovered a seasonal trend that corresponded well with the timing of active‐layer freeze and thaw. This improvement opens the possibility of measuring large velocity changes by using MWCS and permafrost monitoring by using ambient noise. Key Points Cycle‐skipping prevents use of moving window cross‐spectral analysis to track large seismic velocity changes in the permafrost active‐layer Using a moving reference greatly reduces cycle‐skipping in moving window cross‐spectral analysis Seismic interferometry can potentially provide valuable spatiotemporal monitoring in permafrost