[S-SS07] Environmental Seismology: from deep earth to surface process

[SSS07-P01] Reconstruction of the autocorrelation function of stationary stochastic signals and its application to the Earth's seismic hum

Dubois-Dognon Balthazar², *Kiwamu Nishida¹ (1.Earthquake Research Institute, University of Tokyo, 2.Research school of Earth Sciences, ANU)

Keywords:Earth's normal mode, Seismic hum of the Earth, Time series analysis

In the mHz band, the detection of multi-orbit seismic waves by auto-correlating background seismic data requires the utilisation of substantial noise-free data over several days. To overcome this data gap problem, this study proposes a new method to estimate the autocorrelation function (ACF). The ACF of a signal is represented as the summation of the cross terms of sub-segments of arbitrary length. To successfully remove undesired transients in the data, a correction for the amplitude bias associated with the removal of sub-segments, based on the comparison between the expected stationary signal and the measured signal, is introduced. The method reconstructs and accesses later lag times, greater frequency resolution, obtains a better signal-to-noise ratio (SNR) and allows for using segmented records in the context of noisy data sets. As an application, a high SNR and resolution spectrum of Earth's seismic hum on the vertical component is successfully retrieved and compared with synthetic autocorrelation for spatially isotropic and homogeneous excitation by random shear traction at the ocean bottom and pressure at the Earth's surface. Shear traction is know to dominate the source spectrum of seismic hum beyond 5 mHz. Using the high resolution spectrum, an inversion of the source spectra of the two mechanisms indicates that random pressure source also contributes the spectrum below 5 mHz. Reconstruction of the ACF can be used as a single-station approach in the context of extraterrestrial seismology.