Comprehensive global dataset of 300,000 uniformly processed shear-wave splitting measurements with regular updates

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Authors

Jonathan Wolf , Thorsten W. Becker , Ed Garnero, Kelly H Liu, John D. West

Abstract

Seismic anisotropy can inform us about convective flow in the mantle. Shear waves traveling through azimuthally anisotropic regions split into fast and slow pulses, and measuring the resulting shear-wave splitting provides some of the most direct insights into Earth’s interior dynamics. Shear-wave splitting is a constraint for path-averaged azimuthal anisotropy and is often studied regionally, and global compilations of these measurements exist. Such compilations include measurements obtained using different data processing methodologies (e.g., filtering), which do not necessarily yield identical results, and reproducing a number of studies can be challenging given that not all provide the required information, e.g., about the source location. Here, we automatically determine SKS, SKKS and PKS shear-wave splitting parameters from a global dataset. This dataset includes all earthquakes with magnitudes ≥ 5.9 from 2000 to the present, collected from 24 data centers, totaling over 4,700 events and 16 million three-component seismograms. We obtain approximately 90,000 robust measurements for “fast azimuth”, ϕ, and delay time, δt, and 210,000 robust null measurements. Results generally agree with previous work but our measurements allow us to identify hundreds of “null stations” below which the mantle appears effectively isotropic with respect to azimuthal anisotropy, which are important for some splitting techniques. We make all measurements publicly available as a data product, along with detailed metadata. This serves two purposes: ensuring full reproducibility of results and providing all necessary information for future systematic use of our measurements, in tomography applications or comparisons with geodynamic flow predictions.

DOI

https://doi.org/10.31223/X54Q5S

Subjects

Physical Sciences and Mathematics

Keywords

Dates

Published: 2024-12-06 01:24

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License

CC-By Attribution-NonCommercial-NoDerivatives 4.0 International