Stacking of Rayleigh Waves in Multi-Component Ambient Noise Cross-Correlations: Application to Central California

Avinash Nayak, & Clifford H. Thurber

In Preparation November 23, 2109, SCEC Contribution #9990

Ambient seismic noise cross-correlation with three-component sensors yields a nine-component empirical Green’s tensor, in which four components of the radial-vertical plane contain Rayleigh waves. We exploit the retrograde elliptical nature of particle motion of the fundamental mode Rayleigh wave to correct the phase of the four radial-vertical components and stack them to obtain an average fundamental mode Rayleigh-wave time-series. This technique can suppress incoherent noise and wave packets that do not follow the targeted elliptical particle motion. The same technique can be used to isolate the first higher mode Rayleigh wave that follows prograde elliptical particle motion. We first demonstrate the effectiveness of the method on synthetic waveforms and then apply it on noise cross-correlations computed in Central California. The waveforms stacked assuming retrograde particle motion return at least ~20% more group velocity dispersion measurements satisfying a minimum signal-to-noise ratio criteria than the individual components for periods ~4-18 s. For equivalent group velocity measurements, signal-to-noise ratio for the stacked estimate of the fundamental mode Rayleigh wave is on average 40% greater than that measured on the individual components at periods less than 10 s. Using this method, we isolate 1st higher mode Rayleigh waves on noise cross-correlations in the Great Valley, California, which provides new phase velocity constraints for estimating velocity structure in the sedimentary basin. The technique also provides an easy way to detect large errors in sensor orientation.

Citation
Nayak, A., & Thurber, C. H. (2109). Stacking of Rayleigh Waves in Multi-Component Ambient Noise Cross-Correlations: Application to Central California. Geophysical Journal International, (in preparation).