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Shear-wave splitting measurements are commonly used to resolve seismic anisotropy in both the upper and lowermost mantle. Typically, such techniques are applied to SmKS phases that have reflected (m-1) times off the underside of the core-mantle boundary before being recorded. Practical constraints for shear-wave splitting studies include the limited number of suitable phases as well as the large fraction of available data discarded because of poor signal-to-noise ratios (SNRs) or large measurement uncertainties. Array techniques such as beamforming are commonly used in observational seismology to enhance SNRs, but have not been applied before to improve SmKS signal strength and coherency for shear wave splitting studies. Here, we investigate how a beamforming methodology, based on slowness and backazimuth vespagrams to determine the most coherent incoming wave direction, can improve shear-wave splitting measurement confidence intervals. Through the analysis of real and synthetic seismograms, we show that (a) the splitting measurements obtained from the beamformed seismograms (beams) reflect an average of the single-station splitting parameters that contribute to the beam; (b) the beams have (on average) more than twice as large SNRs than the single-station seismograms that contribute to the beam; (c) the increased SNRs allow the reliable measurement of shear wave splitting parameters from beams down to average single-station SNRs of 1.3. Beamforming may thus be helpful to more reliably measure splitting due to upper mantle anisotropy. Moreover, we show that beamforming holds potential to greatly improve detection of lowermost mantle anisotropy by demonstrating differential SKS– SKKS splitting analysis using beamformed USArray data.
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The expression of mantle seismic anisotropy in the global seismic wavefield
SUMMARY The dependence of seismic wave speeds on propagation or polarization direction, called seismic anisotropy, is a relatively direct indicator of mantle deformation and flow. Mantle seismic anisotropy is often inferred from measurements of shear-wave splitting. A number of standard techniques to measure shear-wave splitting have been applied globally; for example, *KS splitting is often used to measure upper mantle anisotropy. In order to obtain robust constraints on anisotropic geometry, it is necessary to sample seismic anisotropy from different directions, ideally using different seismic phases with different incidence angles. However, many standard analysis techniques can only be applied for certain epicentral distances and source–receiver geometries. To search for new ways to detect mantle anisotropy, instead of focusing on the sensitivity of individual phases, we investigate the wavefield as a whole: we apply a ‘wavefield differencing’ approach to (systematically) understand what parts of the seismic wavefield are most affected by splitting due to seismic anisotropy in the mantle. We analyze differences between synthetic global wavefields calculated for isotropic and anisotropic input models, incorporating seismic anisotropy at different depths. Our results confirm that the seismic phases that are commonly used in splitting techniques are indeed strongly influenced by mantle anisotropy. However, we also identify less commonly used phases whose waveforms reflect the effects of anisotropy. For example, PS is strongly affected by splitting due to seismic anisotropy in the upper mantle. We show that PS can be used to fill in gaps in global coverage in shear-wave splitting data sets (for example, beneath ocean basins). We find that PcS is also a promising phase, and present a proof-of-concept example of PcS splitting analysis across the contiguous United States using an array processing approach. Because PcS is recorded at much shorter distances than *KS phases, PcS splitting can therefore fill in gaps in backazimuthal coverage. Our wavefield differencing results further hint at additional potential novel methods to detect and characterize splitting due to mantle seismic anisotropy.
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- Award ID(s):
- 2026917
- PAR ID:
- 10564807
- Publisher / Repository:
- Royal Astronomical Society
- Date Published:
- Journal Name:
- Geophysical Journal International
- Volume:
- 238
- Issue:
- 1
- ISSN:
- 0956-540X
- Page Range / eLocation ID:
- 346 to 363
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Shear‐wave splitting measurements are commonly used to resolve seismic anisotropy in both the upper and lowermost mantle. Typically, such techniques are applied to SmKS phases that have reflected (m‐1) times off the underside of the core‐mantle boundary before being recorded. Practical constraints for shear‐wave splitting studies include the limited number of suitable phases as well as the large fraction of available data discarded because of poor signal‐to‐noise ratios (SNRs) or large measurement uncertainties. Array techniques such as beamforming are commonly used in observational seismology to enhance SNRs, but have not been applied before to improve SmKS signal strength and coherency for shear wave splitting studies. Here, we investigate how a beamforming methodology, based on slowness and backazimuth vespagrams to determine the most coherent incoming wave direction, can improve shear‐wave splitting measurement confidence intervals. Through the analysis of real and synthetic seismograms, we show that (a) the splitting measurements obtained from the beamformed seismograms (beams) reflect an average of the single‐station splitting parameters that contribute to the beam; (b) the beams have (on average) more than twice as large SNRs than the single‐station seismograms that contribute to the beam; (c) the increased SNRs allow the reliable measurement of shear wave splitting parameters from beams down to average single‐station SNRs of 1.3. Beamforming may thus be helpful to more reliably measure splitting due to upper mantle anisotropy. Moreover, we show that beamforming holds potential to greatly improve detection of lowermost mantle anisotropy by demonstrating differential SKS–SKKS splitting analysis using beamformed USArray data.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1093/gji/ggae164
