Group B, Poster #026, Seismology

Earthquake Source Spectra Estimates Obtained from S-Wave Maximum Amplitudes: Application to the 2019 Ridgecrest Sequence

Ian Vandevert, Peter M. Shearer, & Wenyuan Fan
Poster Image: 

Poster Presentation

2022 SCEC Annual Meeting, Poster #026, SCEC Contribution #12160 VIEW PDF
Earthquakes radiate a wide spectrum of seismic energy, from which properties like seismic moment and stress drop can be estimated. A common approach to large data sets of local earthquakes with many sources and receivers is spectral decomposition, which first separates event terms from station and other path terms and then solves for a best-fitting source model. A common problem in spectral decomposition is a poor signal-to-noise ratio for smaller earthquakes at low frequencies, which prevents setting the lower frequency limit low enough to accurately measure the moments and corner frequencies of the largest earthquakes. Here we experiment with a new method for amplitude decomposition, whic...h measures the maximum shear wave amplitude of bandpass filtered seismograms as a function of event-dependent effects, station-dependent effects, and path effects. We produce spectra by filtering at different bands and assembling the decomposed results in the frequency domain. The main benefit of this method is that spectra appear reliable at frequencies about an order of magnitude lower than with P-wave spectral decomposition applied to the same events. We apply this method to seismic data generated during the 2019 Ridgecrest earthquake sequence, compare the results to previous spectral decomposition studies, and explore any implications for source-scaling issues.