Volcanic earthquake catalog enhancement using integrated detection, matched-filtering, and relocation tools

نویسندگان

چکیده

Volcanic earthquake catalogs are an essential data product used to interpret subsurface volcanic activity and forecast eruptions. Advances in detection techniques (e.g., matched-filtering, machine learning) relative relocation tools have improved catalog completeness refined event locations. However, most volcano observatories yet incorporate these into their catalog-building workflows. This is due part complexities operationalizing, automating, calibrating a satisfactory way for disparate networks varied seismicity. In effort streamline the integration of catalog-enhancing at Alaska Volcano Observatory (AVO), we integrated four popular open-source tools: REDPy, EQcorrscan, HypoDD, GrowClust. The combination offers capability adding seismic detections relocating events single workflow. workflow relies on standard triggering cross-correlation clustering (REDPy) consolidate representative templates matched-filtering (EQcorrscan). then relocated using differential time methods provided by HypoDD and/or Our also provides codes campaign appropriate junctures, calculate magnitude frequency index valid events. We apply this three datasets: 2012–2013 swarm sequence Mammoth Mountain (California), 2009 eruption Redoubt (Alaska), 2006 Augustine (Alaska); compare our results with previous studies each volcano. general, significant increase number locations, relate clusters temporal progressions relevant activity. discuss implementation best practices, particularly applying sparse networks. envision that datasets presented here will be useful detailed analyses monitoring research efforts.

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ژورنال

عنوان ژورنال: Frontiers in Earth Science

سال: 2023

ISSN: ['2296-6463']

DOI: https://doi.org/10.3389/feart.2023.1158442