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• W2772286403 abstract "Systematic mining and reanalysis of large volcano-seismic waveform datasets Robin S. Matoza* 1 , Peter M. Shearer 1 , Paul G. Okubo 2 , Bernard Chouet 3 , Phil Dawson 3 , and Seth Moran 4 Institute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, UC San Diego US Geological Survey, Hawaiian Volcano Observatory US Geological Survey, Menlo Park US Geological Survey, Cascades Volcano Observatory Summary The analysis and interpretation of seismicity from mantle depths to the surface plays a key role in understanding how volcanoes work. We are developing and applying methods for the systematic reanalysis of waveforms from volcano- seismic networks, including high-precision earthquake relocation, spectral event classification, and source mechanism and stress drop estimates. Our datasets include 23 years of tectonic, volcano-tectonic, and long-period (LP, 0.5–5 Hz) seismicity from the ~50-station permanent network of the USGS Hawaiian Volcano Observatory (HVO), and millions of LP seismic events recorded on ~35 stations during the 2004–2008 eruption of Mount St. Helens, WA. Introduction at several other volcanoes (e.g., Lees et al., 2008; Power and Lalla, 2014; Firstov and Shakirova, 2014). Method We have been developing a modular set of codes for the mining and analysis of large waveform datasets from volcanoes, based on previous work analyzing large event- based regional seismic datasets from Southern California (Shearer, 1997; Shearer et al., 2005; Lin et al., 2007). The processing steps include automated network-based template-matching detection to build an event database, analyses of the evolutionary dynamics of event metrics, waveform cross-correlation and high-precision relocations, and full-waveform inversions using representative stacks of similar events. Our combined cluster analysis and relative relocation method is described in more detail by Matoza et al. (2013, 2014). Volcanoes generate seismicity by a full spectrum of fluid and solid processes. Long-period seismicity (LP, 0.5–5 Hz) is a class of volcano-seismic signal that is of particular interest. LP seismicity includes individual transient LP events and more continuous volcanic tremor. These signals are used routinely by volcano monitoring scientists to forecast volcanic eruptions despite an incomplete understanding of their origin (e.g., Chouet et al., 1994; McNutt, 1996). LP events often consist of a brief broadband onset, followed by a coda of decaying harmonic oscillations containing pronounced spectral peaks that are independent of azimuth and distance to the source. This is commonly interpreted as a broadband, time-localized pressure excitation mechanism (or trigger mechanism), followed by the volumetric response of a fluid-filled resonator (e.g., Chouet and Matoza, 2013). LP seismicity has been recorded for decades in the summit region of Kilauea Volcano, Hawaii, and is postulated as linked with the magma transport and shallow hydrothermal systems. The 2004–2008 eruption of Mount St. Helens produced millions of LP events, only a small fraction of which have been analyzed or modeled in detail. Many of the LP events during this eruption occurred with such precise regularity that they were termed “drumbeats” (Moran et al., 2008), a phenomenon that has been observed Figure 1: High-precision relocations of seismicity in the summit region of Kilauea Volcano, Hawaii from 1986 to 2009 (Matoza et al. 2013, 2014). Blue dots are events we automatically classify as LP and red dots are non-LP. We produce a dramatic sharpening of earthquake locations along faults and magmatic features compared to standard earthquake catalog locations." @default.
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• W2772286403 date "2015-01-01" @default.
• W2772286403 modified "2023-09-26" @default.
• W2772286403 title "Near-Surface Asia Pacific Conference" @default.
• W2772286403 hasPublicationYear "2015" @default.
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