Abstract
Stacks of ambient noise cross-correlations are more and more routinely
used to extract empirical Green's functions between station pairs.
The success of the cross-correlations is due to waves which are recorded
by both stations and that constructively sum at lag times which equal
their propagation time between the station pair. Stacking cross-correlograms
corresponding to different time spans improves the azimuthal noise
coverage and further enhances the signals. Here we show how the instantaneous
phase coherence can be used for a more efficient signal extraction
from ambient noise cross-correlations. The instantaneous phase coherence
is obtained by analytic signal processing and can be employed through
the phase cross-correlation and/or through the time-frequency domain
phase-weighted stack. The phase cross-correlation is more sensitive
to waveform similarity but less sensitive to strong amplitude features
than the conventional cross-correlation. The time-frequency domain
phase-weighted stack cleans the ambient noise cross-correlograms
by attenuating incoherent noise and permits an improved signal identification.
We show that both approaches are powerful tools in the recovery of
signals from ambient noise data and show examples where they improve
the extraction of P and Rayleigh waves by considering local and global
scale applications.
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