Improved moving window cross-spectral analysis for resolving large temporal seismic velocity changes in permafrost
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...
| Published in: | Geophysical Research Letters |
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| Main Authors: | , , , |
| Language: | unknown |
| Published: |
2022
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| Subjects: | |
| Online Access: | http://www.osti.gov/servlets/purl/1374826 https://www.osti.gov/biblio/1374826 https://doi.org/10.1002/2016GL072468 |
| Summary: | 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. Lastly, this improvement opens the possibility of measuring large velocity changes by using MWCS and permafrost monitoring by using ambient noise. |
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