Denoising Surface Waves Extracted From Ambient Noise Recorded by 1-D Linear Array Using Three-Station Interferometry of Direct Waves

We develop an automatic workflow for enhancing surface wave signals in ambient noise cross correlations (ANCs) calculated for a one-dimensional (1-D) linear array. The proposed array-based method is applied to a 1.6 km-long dense linear nodal array crossing surface traces of the San Jacinto fault near Anza, California. Fundamental and higher modes of surface waves are observed in ANCs of the nodal array. After attenuating the surface wave overtones by applying a frequency-dependent tapering window to the ANCs, signals dominated by the fundamental mode surface wave are then enhanced through a denoising process based on three-station interferometry of direct waves. The signal-to-noise ratio is significantly increased at high frequencies (>2 Hz) after denoising. Phase travel times are extracted reliably in the frequency domain for the period ranges of 0.3-1.2 s and 0.3-1.6 s for Rayleigh and Love waves, respectively. The corresponding period-dependent phase velocity profiles derived from the eikonal equation reveal high-resolution details of fault zone internal structures beneath the array. A broad (500-1,000 m) low-velocity zone that narrows with increasing period is observed, illuminating a flower-shaped structure of the San Jacinto fault damage zone.

Automated summary

An automatic workflow for enhancing surface wave signals in ambient noise cross correlations was developed for a 1-D linear array, demonstrating significant improvement in signal-to-noise ratio at high frequencies (>2 Hz). Reliable extraction of phase travel times in the frequency domain for Rayleigh and Love waves was achieved, revealing detailed internal structures of fault zones beneath the array. The method illuminated a flower-shaped structure of the San Jacinto fault damage zone, with a broad low-velocity zone narrowing with increasing period.