Long Period Rayleigh Wave Focal Spot Imaging Applied to USArray Data

Author:

Tsarsitalidou C.1ORCID,Hillers G.1ORCID,Giammarinaro B.12ORCID,Boué P.3ORCID,Stehly L.3,Campillo M.3ORCID

Affiliation:

1. Institute of Seismology Department of Geosciences and Geography University of Helsinki Helsinki Finland

2. Now at LabTAU INSERM Centre Léon Bérard Université Claude Bernard Lyon 1 Lyon France

3. Institut des Sciences de la Terre Université Grenoble Alpes Grenoble France

Abstract

AbstractWe demonstrate the effectiveness of seismic dense array surface wave focal spot imaging using USArray data from the western‐central United States. We study dispersion in the 60–310 s period range and assess the image quality of fundamental mode Rayleigh wave phase velocity maps. We apply isotropic spatial autocorrelation models to the time domain zero lag noise correlation wavefield data at distances of about one wavelength. Local estimates of the phase velocity, its uncertainty, and the regression quality imply overall better ZZ relative to ZR or RZ results. The extension of the depth resolution compared to passive surface wave tomography is demonstrated by the inversion of three clustered dispersion curves from different tectonic units. We observe anisotropic surface wave energy flux and the influence of body wave energy, but sensitivity tests at 60 s targeting the data range, correlation component, and processing choices show that the ZZ focal spots yield consistent high‐quality images compared to regional tomography results in the 60–150 s period range. In contrast, at 200–300 s the comparatively small scales of the imaged structures and the imperfect agreement with low‐resolution global tomography results highlight the persistent challenge to reconcile imaging results based on different data sources, theories, and techniques. Our study shows that surface wave focal spot imaging is an accurate, robust, local imaging approach. Better control over clean autocorrelation fields can further improve applications of this seismic imaging tool for increased resolution of the elastic structure below dense seismic arrays.

Funder

Research Council of Finland

Helsingin Yliopisto

Publisher

American Geophysical Union (AGU)

Reference96 articles.

1. Albuquerque Seismological Laboratory (ASL)/USGS. (1990).United States National Seismic Network [Dataset].FDSN. Retrieved fromhttps://www.fdsn.org/networks/detail/US/

2. How ocean waves rock the Earth: Two mechanisms explain microseisms with periods 3 to 300 s

3. Nonlinear Regression

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