ABSTRACT
ABSTRACT: We utilized statistical Green’s functions extracted from strong motion data of K-NET, KiK-net and the JMA Shindo-kei network in Japan to predict strong motions for a large subduction-zone earthquake. The spectrum and envelope information were needed to generate statistical Green’s functions. About 16,000 records of Fourier spectra were separated into source, path and site factors. We also determined parameters of the Boore’s envelope function for all the accelerograms and separate them into source, path and site factors. Then the Irikura-Kamae method was used to sum up statistical Green’s functions for a moderate size earthquake (M5.5) and synthesize them to predict strong motions due to the expected Tonankai earthquake of M8.1. The resultant strong motions show similar PGA values of empirical relations, and the calculated seismic intensities show similar values as observed in the previous two events.
