Performance of the radial semblance method for the location of very long period volcanic signals
Links
- More information: Publisher Index Page (via DOI)
- Download citation as: RIS | Dublin Core
Abstract
We investigate the performance of a source location method that combines multichannel semblance and particle motions and is being increasingly used to obtain estimates of the source locations of very long period (VLP) seismic signals recorded on volcanoes. The method makes use of the radial particle motions and large wavelengths that characterize the VLP events. To assess the capabilities of this radial semblance method, and to better understand its limitations, we quantify the effects of window length, noise contents of the signal, inaccurate velocity models, receiver coverage, and orientation errors in the horizontal components of the receivers. Our results show that the semblance method performs best when (1) the noise level is low enough to allow a good characterization of the waveforms, (2) the sources are located at distances between one half of the average receiver spacing and about two times the network aperture, and (3) the orientations of the horizontal components of the seismometers are known with relative accuracy. When these requirements are met, the radial semblance method constitutes an adequate tool to obtain preliminary locations of VLP volcanic signals recorded by broadband networks. Moreover, we provide a formula to determine the radial semblance level that should be used to define error regions associated to the estimated source locations.
Publication type | Article |
---|---|
Publication Subtype | Journal Article |
Title | Performance of the radial semblance method for the location of very long period volcanic signals |
Series title | Bulletin of the Seismological Society of America |
DOI | 10.1785/0120020143 |
Volume | 93 |
Issue | 5 |
Year Published | 2003 |
Language | English |
Publisher | Seismological Society of America |
Description | 14 p. |
First page | 1890 |
Last page | 1903 |
Google Analytic Metrics | Metrics page |