Seismic velocity changes concentrated at the shallow structure as inferred from correlation analyses of ambient noise during volcano deformation at Izu‐Oshima, Japan

Abstract

We investigate the stress sensitivity of velocity changes at Izu‐Oshima in Japan using seismic interferometry method. We calculate cross correlation functions (CCFs) of ambient noises recorded by four seismic stations on the active volcano from 1 January 2012 to 31 December 2015 at 0.5–1 Hz, 1–2 Hz, and 2–4 Hz. Applying moving time windows to calculate cross spectrum between daily CCFs and reference CCF, which is the average for the all observation period, we compute daily velocity changes. The obtained velocity changes vary from −1% to 3% with a dominant period of about 1 year. We calculate areal strains by using Global Navigation Satellite Systems data at the volcano. It is evident that the velocity changes are well correlated with the areal strain changes whose linear trend is removed. The stress sensitivity of velocity changes, which are obtained from the observed velocity changes and areal strains, is lower at 0.5–1 Hz than that at higher frequencies: (7.1 ± 1.3) × 10−8 Pa−1 at 0.5–1 Hz, (1.4 ± 0.1) × 10−7 Pa−1 at 1–2 Hz, and (1.3 ± 0.1) × 10−7 Pa−1 at 2–4 Hz. Modeling the velocity changes of Rayleigh wave propagating in layered structures, we find that the observed velocity changes are concentrated in the upper 1 km of the structure. Since similar frequency dependency is recognized among the stress sensitivity of velocity changes reported in previous studies, we conclude that the velocity changes are localized in the shallow depth because of the increase of confining pressure.

Sensitivity of Seismic Velocity Changes to the Tidal Strain at Different Lapse Times: Data Analyses of a Small Seismic Array at Izu‐Oshima Volcano

“…The time window of 5 s is the same as that for which we analyzed the lapse time‐dependent characteristics of the strain sensitivity in section . Overall, apparent velocities for all station pairs are about 1 km/s around the direct wave part of CCFs, which is consistent with the group velocity of Rayleigh wave at 1–4 Hz (Takano et al, ). The sensitivity kernel of fundamental Rayleigh waves at the frequency of 3 Hz shows that the depth distribution of strain sensitivity values is shallower than the depth of 0.4 km.…”

“…This is contrary to the results obtained from the present study that uses tidal strain. The seismic velocity changes caused by the tidal strain show the lapse time dependence, although Takano et al () indicate that the velocity changes in response to the volcano deformation do not vary with the lapse time. There are three possible causes of differences between the velocity changes in response to the tidal strain and the volcanic pressure source.…”

“…We also analyze the strain sensitivity of seismic velocity changes at 0.5-1 Hz band, but the error of seismic velocity changes is too large to discuss the strain sensitivity of seismic velocity changes. Takano et al (2017) compared the seismic velocity changes with the volcano deformation caused by the volcanic pressure source at Izu-Ohsima with the noise correlation method. They estimated the strain sensitivity of velocity changes at 1-2 and 2-4 Hz by fitting a regression line between the seismic velocity changes and areal strain changes which are calculated by displacements of Global Navigation Satellite Systems stations.…”

“…Strain changes cause preexisting cracks to close and open, and consequently the seismic velocities decrease and increase in regions of dilatation and contraction of the structure, respectively (e.g., Nur, ; Walsh, ). For example, seismic velocity changes caused by volcano deformations (Donaldson et al, ; Nagaoka et al, ; Ratdomopurbo & Poupinet, ; Rivet et al, ; Takano et al, ), thermoelastic strains (Hillers et al, ; Richter et al, ; Tsai, ), and the Earth tide (Hillers et al, ; Reasenberg & Aki, ; Takano et al, ; Yamamura et al, ), which are not accompanied by strong ground motions, have been observed.…”

Towards the Processing of Large Data Volumes with Phase Cross‐Correlation

“…The preprocessing of the raw data may include instrument response correction, anomalous signal rejection, spectral whitening, and time-domain normalization (Bensen et al, 2007), and once the correlations are computed, weighted stacking and denoising (Baig et al, 2009;Schimmel et al, 2011;Cheng et al, 2015;Moreau et al, 2017). Finally, subsequent measurements of group and phase velocity dispersion are done in surface-wave tomography applications (e.g., Haned et al, 2016;Obermann et al, 2016;Schippkus et al, 2018), of velocity and structure variations in monitoring (e.g., Hadziioannou et al, 2011;D'Hour et al, 2016;Takano et al, 2017;Sánchez-Pastor et al, 2018), or of travel times of body waves from ambient noise or earthquake coda in Earth's deep interior studies (e.g., Nishida, 2013;Boué et al, 2014;Phạm et al, 2018;Tkalčić and Phạm, 2018).…”