Towards a Comprehensive Catalog of Volcanic Seismicity

Monday, 15 December 2014
Glenn Thompson, University of South Florida Tampa, Tampa, FL, United States
Catalogs of earthquakes located using differential travel-time techniques are a core product of volcano observatories, and while vital, they represent an incomplete perspective of volcanic seismicity. Many (often most) earthquakes are too small to locate accurately, and are omitted from available catalogs. Low frequency events, tremor and signals related to rockfalls, pyroclastic flows and lahars are not systematically catalogued, and yet from a hazard management perspective are exceedingly important. Because STA/LTA detection schemes break down in the presence of high amplitude tremor, swarms or dome collapses, catalogs may suggest low seismicity when seismicity peaks.

We propose to develop a workflow and underlying software toolbox that can be applied to near-real-time and offline waveform data to produce comprehensive catalogs of volcanic seismicity. Existing tools to detect and locate phaseless signals will be adapted to fit within this framework. For this proof of concept the toolbox will be developed in MATLAB, extending the existing GISMO toolbox (an object-oriented MATLAB toolbox for seismic data analysis). Existing database schemas such as the CSS 3.0 will need to be extended to describe this wider range of volcano-seismic signals. WOVOdat may already incorporate many of the additional tables needed. Thus our framework may act as an interface between volcano observatories (or campaign-style research projects) and WOVOdat.

We aim to take the further step of reducing volcano-seismic catalogs to sets of continuous metrics that are useful for recognizing data trends, and for feeding alarm systems and forecasting techniques. Previous experience has shown that frequency index, peak frequency, mean frequency, mean event rate, median event rate, and cumulative magnitude (or energy) are potentially useful metrics to generate for all catalogs at a 1-minute sample rate (directly comparable with RSAM and similar metrics derived from continuous data). Our framework includes tools to plot these metrics in a consistent manner. We work with data from unrest at Redoubt volcano and Soufriere Hills volcano to develop our framework.