9:45 AM - 10:00 AM
[SSS04-04] Complexities in Earthquake Source Spectra Revealed by the Multiple Spectral Ratio Analyses
Keywords:Earthquake, Earthquake Source Spectra, Complexities in Earthquake Source Processes
Earthquake source spectra are simple representations of the earthquake rupture process. The standard spectral model is the omega-square model (e.g., Aki, 1967; Brune, 1970; Boatwright, 1978). Recent developments in seismic observations and seismic data analyses made it possible to study more details in earthquake source spectra. For example, spectral models with two corner frequencies have been proposed by Denolle and Shearer (2016) and Ji and Archuleta (2020). The multiple spectral ratio method (Uchide and Imanishi, 2016) is a powerful tool to redetect complexities in source spectra by stacking the residual of spectral ratio analyses using many empirical Green’s function events. Wu et al. (2019) studied the source complexities in an induced earthquake in Oklahoma. Quantification of the source complexity will be a clue to understanding the physics of earthquake source processes and the characteristic of source regions.
This study investigated 3351 M3-4 earthquakes that occurred in 2002-2020 in Japan by the multiple spectral ratio method. The stacked residuals are indicators of the source complexity. I compared them by taking peak-to-peak ratios as residual amplitudes. I chose high seismicity areas and made histograms in those areas. The histograms varied in a certain range, but I did not see distinct features among them.
I also adopted a different reference model for the multiple spectral ratio analysis. Analyses with the Brune and Boatwright models produced similar shapes in stacked residual spectra. Complex events detected using the Brune model were recognized as complex ones by the Boatwright model. However, the estimated source spectra, as the reference model plus the stacked residual, were different. This suggests that the stacked residual spectra are model-dependent, though they are still usable as indicators of the source complexity.
Acknowledgment
This study used seismic data from NIED Hi-net, JMA, Hokkaido University, Hirosaki University, Tohoku University, ERI (the University of Tokyo), Nagoya University, DPRI (Kyoto University), Kochi University, Kyushu University, and Kagoshima University. This study also uses the JMA Unified Earthquake Catalog and NIED F-net Moment Tensor Catalog. This research was supported by JSPS KAKENHI Grant Number JP21H05205 in Grant-in-Aid for Transformative Research Areas (A) “Science of Slow-to-Fast Earthquakes.”
This study investigated 3351 M3-4 earthquakes that occurred in 2002-2020 in Japan by the multiple spectral ratio method. The stacked residuals are indicators of the source complexity. I compared them by taking peak-to-peak ratios as residual amplitudes. I chose high seismicity areas and made histograms in those areas. The histograms varied in a certain range, but I did not see distinct features among them.
I also adopted a different reference model for the multiple spectral ratio analysis. Analyses with the Brune and Boatwright models produced similar shapes in stacked residual spectra. Complex events detected using the Brune model were recognized as complex ones by the Boatwright model. However, the estimated source spectra, as the reference model plus the stacked residual, were different. This suggests that the stacked residual spectra are model-dependent, though they are still usable as indicators of the source complexity.
Acknowledgment
This study used seismic data from NIED Hi-net, JMA, Hokkaido University, Hirosaki University, Tohoku University, ERI (the University of Tokyo), Nagoya University, DPRI (Kyoto University), Kochi University, Kyushu University, and Kagoshima University. This study also uses the JMA Unified Earthquake Catalog and NIED F-net Moment Tensor Catalog. This research was supported by JSPS KAKENHI Grant Number JP21H05205 in Grant-in-Aid for Transformative Research Areas (A) “Science of Slow-to-Fast Earthquakes.”