High‐Broadband Seismoacoustic Signature of Vulcanian Explosions at Popocatépetl Volcano, Mexico

Matoza, Robin S.; Arciniega-Ceballos, A.; Sanderson, R. W.; Mendo‐Pérez, Gerardo; Rosado‐Fuentes, Alejandro; Chouet, Bernard

doi:10.1029/2018gl080802

Cited by 24 publications

(14 citation statements)

References 47 publications

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“…This enables signal beamforming for the discrimination of different activities at multiple vents. It also helps distinguish volcanic signals from uncorrelated noise or infrasound from non-volcanic sources (Ripepe and Marchetti 2002;Johnson and Ripepe 2011;Yamakawa et al 2018;Matoza et al 2019). However, the construction and maintenance of arrays in volcanic regions is not easy, and only a few volcanoes are equipped with permanent infrasound arrays.…”

Section: Introductionmentioning

confidence: 99%

Reconstructing surface eruptive sequence of 2018 small phreatic eruption of Iwo-yama volcano, Kirishima Volcanic Complex, Japan, by infrasound cross-correlation analysis

Muramatsu

Matsushima

Ichihara

2021

Earth Planets Space

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The Iwo-yama volcano of the Kirishima Volcanic Complex in Japan had a small phreatic eruption in April 2018, which newly formed multiple vents. The activity was recorded by two infrasound sensors and two monitoring cameras, which had been installed within 1 km of the vents. This study identified infrasonic signals from the multiple vents by a cross-correlation analysis between the two infrasound sensors. The analysis successfully revealed the signals from two main eruption craters and constrained the infrasound onsets at the individual vents in the two craters. We combined the infrasound results with the images from the cameras and reconstructed the sequence of the small phreatic eruption of Iwo-yama. At each of the two craters, the intense eruption, which was depicted by the evident infrasound signals, occurred several hours after the eruption onset. This study provides a sequence of the activities of the multiple vents in a phreatic eruption, which will be useful for understanding the phreatic eruption and hazard assessments.

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Section: Introductionmentioning

confidence: 99%

Reconstructing surface eruptive sequence of 2018 small phreatic eruption of Iwo-yama volcano, Kirishima Volcanic Complex, Japan, by infrasound cross-correlation analysis

Muramatsu

Matsushima

Ichihara

2021

Earth Planets Space

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“…These algorithms are very sensitive, give low false alarm rate but have the disadvantage of being able to detect only signals which are very similar to the template waveform, which in turn needs to be well known (Withers et al, 1999;Gibbons et al, 2007). In volcano acoustics, similar techniques (e.g., Cannata et al, 2013a;Cannata et al,2013b;Thompson, 2015;Hotovec-Ellis and Jeffrines, 2016;Matoza et al, 2019a;Senobari et al, 2019), or methods making use of advanced signal processing techniques (Bueno et al, 2019), are implemented to identify and extract amplitude transients from the real-time streaming of signals, that characterize explosive or degassing activity. In particular, energy detectors, such as STA/LTA, are efficient algorithms when multiple infrasound sources are active (as at multi-vent volcanoes) and exhibit space-time variations, while correlation detectors are a powerful tool when we want to identify amplitude transients produced by a single and/or stable infrasound source in order to study its physical properties (Montalto et al, 2010;Sciotto et al, 2013;Cannata et al, 2013a;Hotovec-Ellis and Jeffrines, 2016;Yokoo et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Application of Subspace-Based Detection Algorithm to Infrasound Signals in Volcanic Areas

Sciotto¹,

Montalto²

2021

Front. Earth Sci.

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Infrasonic signals investigation plays a fundamental role for both volcano monitoring purpose and the study of the explosion dynamics. Proper and reliable detection of weak signals is a critical issue in active volcano monitoring. In particular, in volcanic acoustics, it has direct consequences in pinpointing the real number of generated events (amplitude transients), especially when they exhibit low amplitude, are close in time to each other, and/or multiple sources exist. To accomplish this task, several algorithms have been proposed in literature; in particular, to overcome limitations of classical approaches such as short-time average/long-time average and cross-correlation detector, in this paper a subspace-based detection technique has been implemented. Results obtained by applying subspace detector on real infrasound data highlight that this method allows sensitive detection of lower energy events. This method is based on a projection of a sliding window of signal buffer onto a signal subspace that spans a collection of reference signals, representing similar waveforms from a particular infrasound source. A critical point is related to subspace design. Here, an empirical procedure has been applied to build the signal subspace from a set of reference waveforms (templates). In addition, in order to determine detectors parameters, such as subspace dimension and detection threshold, even in presence of overlapped noise such as infrasonic tremor, a statistical analysis of noise has been carried out. Finally, the subspace detector reliability and performance, have been assessed by performing a comparison among subspace approach, cross-correlation detector and short-time average/long-time average detector. The obtained confusion matrix and extrapolated performance indices have demonstrated the potentiality, the advantages and drawbacks of the subspace method in tracking volcanic activity producing infrasound events. This method revealed to be a good compromise in detecting low-energy and very close in time events recorded during Strombolian activity.

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“…Therefore, it is recorded not only by infrasound sensors but also by seismic sensors. Such signals in seismometer data are called 'ground-coupled air waves' in recent papers in volcanology [e.g., Johnson and Malone, 2007;De Angelis et al, 2012;Fee et al, 2016;Smith et al, 2016;McKee et al, 2018;Matoza et al, 2019]. However, the term 'ground-coupled airwaves' was originally used to indicate the pressure oscillation generated by propagating seismic waves [Donn and Posmentier, 1964].…”

Section: Introductionmentioning

confidence: 99%

A simple method to evaluate the seismic/infrasonic energy partitioning during an eruption using data contaminated by air-to-ground signals

Ichihara

Yamakawa

Muramatsu

2021

Preprint

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A volcanic eruption transmits both seismic waves and infrasound signals. The seismo-acoustic power ratio is widely used to investigate the eruption behaviors and the source dynamics. It is often the case that seismic data during an eruption are significantly contaminated or even dominated by ground shaking due to infrasound (air-to-ground signals). To evaluate the contribution of infrasound-originated power in the seismic data, we need a response function of the seismic station to infrasound. It is rare to obtain a seismo-acoustic data-set containing only infrasound signals, though it is ideal for calculating the response function. This study proposes a simple way to calculate the response function using seismo-acoustic data containing infrasound and independent seismic waves. The method requires data recorded at a single station and mainly uses the cross-correlation function between the infrasound data and the Hilbert transform of the seismic data. It is tested with data recorded by a station at Kirishima volcano, Japan, of which response function has been constrained. It is shown that the method calculates a proper response function even when the seismic data contain more significant seismic power (or noise) than the air-to-ground signals. The proposed method will be useful in monitoring and understanding eruption behaviors using seismo-acoustic observations.

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High‐Broadband Seismoacoustic Signature of Vulcanian Explosions at Popocatépetl Volcano, Mexico

Cited by 24 publications

References 47 publications

Reconstructing surface eruptive sequence of 2018 small phreatic eruption of Iwo-yama volcano, Kirishima Volcanic Complex, Japan, by infrasound cross-correlation analysis

Reconstructing surface eruptive sequence of 2018 small phreatic eruption of Iwo-yama volcano, Kirishima Volcanic Complex, Japan, by infrasound cross-correlation analysis

Application of Subspace-Based Detection Algorithm to Infrasound Signals in Volcanic Areas

A simple method to evaluate the seismic/infrasonic energy partitioning during an eruption using data contaminated by air-to-ground signals

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