Single‐station monitoring of volcanoes using seismic ambient noise

Abstract

Seismic ambient noise cross correlation is increasingly used to monitor volcanic activity. However, this method is usually limited to volcanoes equipped with large and dense networks of broadband stations. The single‐station approach may provide a powerful and reliable alternative to the classical “cross‐station” approach when measuring variation of seismic velocities. We implemented it on the Piton de la Fournaise in Reunion Island, a very active volcano with a remarkable multidisciplinary continuous monitoring. Over the past decade, this volcano has been increasingly studied using the traditional cross‐correlation technique and therefore represents a unique laboratory to validate our approach. Our results, tested on stations located up to 3.5 km from the eruptive site, performed as well as the classical approach to detect the volcanic eruption in the 1–2 Hz frequency band. This opens new perspectives to successfully forecast volcanic activity at volcanoes equipped with a single three‐component seismometer.

Volcanic, Coseismic, and Seasonal Changes Detected at White Island (Whakaari) Volcano, New Zealand, Using Seismic Ambient Noise

“…These are larger for auto-correlations (Figure 2a), with measurements made using the cross-components found to be more stable through time (Figure 2b). This is consistent with previous studies, where the reduced stability of auto-correlations is thought to result from the inability to apply spectral whitening (e.g., De Plaen et al, 2016;Hobiger et al, 2014). Spectral properties of velocity changes at WIZ do not reveal a clear systematic pattern to short-term changes (Figures 2c and 2d), as might be expected if influenced by the 14-day tidal stress cycle.…”

“…Only one of these (WIZ) has been active throughout recent activity (Table S2), handicapping station-pair correlation approaches. One alternative is to cross-correlate the different components of individual seismic stations, with recent work (Bennington et al, 2018;De Plaen et al, 2016) showing encouraging similarities when compared to velocity changes measured using the traditional two station approach. We therefore apply this technique at White Island, with its sparse seismic coverage providing an excellent test case for single-station monitoring.…”

Temporal Changes of Seismic Velocity Caused by Volcanic Activity at Mt. Etna Revealed by the Autocorrelation of Ambient Seismic Noise

“…Seismic velocity changes were measured from seismic noise cross-correlation, following a workflow similar to Lecocq et al (2014) andDe Plaen et al (2016). Seismic records for all components were pre-processed by carefully checking for their timing and gaps.…”

“…Cross-correlation functions, used to perform interferometry, are typically reconstructed from the signals acquired by pairs of stations, allowing to continuously and accurately monitor the temporal changes in seismic velocity (Hadziioannou et al, 2009). More recently, implementations of this technique used passive recordings at individual stations to detect changes of seismic velocity in the crust by cross-correlating each component of each individual station with itself, or autocorrelation (e.g., Hobiger et al, 2014;De Plaen et al, 2016;Yukutake et al, 2016).…”

Complex Near‐Surface Rheology Inferred From the Response of Greater Tokyo to Strong Ground Motions

“…Without necessarily interpreting the phases in the cross correlograms, one can also monitor the temporal evolution of the wave arrival times. AC and SC functions have been used to detect seismic velocity changes during earthquakes (Gassenmeier et al, 2016;Hobiger et al, 2012Hobiger et al, , 2014Hobiger et al, , 2016Richter et al, 2014;Wegler & Sens-Schönfelder, 2007) and volcanic eruptions (De Plaen et al, 2016). However, these studies focused on velocity changes of coda waves at relatively low frequencies (∼0.1 to 4 Hz), making the measurements sensitive to variations occurring within a few kilometers of depth.…”