Characterizing waveform uncertainty due to ambient noise for the Global Seismic Network

Abstract:

Ambient seismic noise is the vibration present on seismograms not due by any earthquake or discrete source. It can be caused by trees swaying in the wind or trucks rumbling on the freeway, but the main source of noise is the microseism caused by ocean waves. The frequency content and amplitude of seismic noise varies due to weather, season, and the location of a station, among other factors. Because noise affects recordings of earthquake waveforms, better understanding it could improve the detection of small earthquakes, reduce false positives in earthquake early warning, and quantify uncertainty in waveform-based studies

In this study, we used two years of 3-component accelerograms from stations in the GSN. We eliminate days with major earthquakes, aggregate analysis by month, and calculate the mean power spectrum for each component and the transfer function between components. For each power spectrum, we determine the dominant frequency and amplitude of the primary (PM) and secondary (SM) microseisms which appear at periods of ~14s and ~7s, as well as any other prominent peaks. The cross-component terms show that noise recorded on different components cannot be treated as independent. Trends in coherence and phase delay suggest directionality in the noise and information about in which modes it propagates.

Preliminary results show that the noise on island stations exhibits less monthly variability, and its PM peaks tend to be much weaker than the SM peaks. The continental stations show much less consistent behavior, with higher variability in the PM peaks between stations and higher frequency content during winter months. Stations that are further inland have smaller SM peaks compared to coastal stations, which are more similar to island stations. Using these spectra and cross-component results, we develop a method for generating realistic 3-component seismic noise and covariance matrices, which can be used across various seismic applications.