Options
Lamb, Oliver
Loading...
2 results
Now showing 1 - 2 of 2
- PublicationOpen AccessVINEDA—Volcanic INfrasound Explosions Detector Algorithm(2019-12-13)
; ; ; ; ; ; ; ; ; ; ; ; ; Infrasound is an increasingly popular tool for volcano monitoring, providing insights of the unrest by detecting and characterizing acoustic waves produced by volcanic processes, such as explosions, degassing, rockfalls, and lahars. Efficient event detection from large infrasound databases gathered in volcanic settings relies on the availability of robust and automated workflows. While numerous triggering algorithms for event detection have been proposed in the past, they mostly focus on applications to seismological data. Analyses of acoustic infrasound for signal detection is often performed manually or by application of the traditional short-term average/long-term average (STA/LTA) algorithms, which have shown limitations when applied in volcanic environments, or more generally to signals with poor signal-to-noise ratios. Here, we present a new algorithm specifically designed for automated detection of volcanic explosions from acoustic infrasound data streams. The algorithm is based on the characterization of the shape of the explosion signals, their duration, and frequency content. The algorithm combines noise reduction techniques with automatic feature extraction in order to allow confident detection of signals affected by non-stationary noise. We have benchmarked the performances of the new detector by comparison with both the STA/LTA algorithm and human analysts, with encouraging results. In this manuscript, we present our algorithm and make its software implementation available to other potential users. This algorithm has potential to either be implemented in near real-time monitoring workflows or to catalog pre-existing databases.325 17 - PublicationOpen AccessVolume Flow Rate Estimation for Small Explosions at Mt. Etna, Italy, From Acoustic Waveform InversionRapid assessment of the volume and the rate at which gas and pyroclasts are injected into the atmosphere during volcanic explosions is key to effective eruption hazard mitigation. Here, we use data from a dense infrasound network deployed in 2017 on Mt. Etna, Italy, to estimate eruptive volume flow rates (VFRs) during small gas-and-ash explosions. We use a finite-difference time-domain approximation to compute the acoustic Green's functions and perform a full waveform inversion for a multipole source, combining monopole and horizontal dipole terms. The inversion produces realistic estimates of VFR, on the order of 4 × 104 m3/s and well-defined patterns of source directivity. This is the first application of acoustic waveform inversion at Mt. Etna. Our results demonstrate that acoustic waveform inversion is a mature and robust tool for assessment of source parameters and holds potential as a tool to provide rapid estimates of VFR in near real time.
311 16