Early Forecast of Long-Period Ground Motions via Data Assimilation of Observed Ground Motions and Wave Propagation Simulations

Abstract

We propose an efficient approach for the early forecast of long-period (> 3–10 s) ground motions generated in sedimentary basins by large earthquakes based on the data assimilation of observed ground motions and finite-difference method simulations of seismic wave propagation in a 3-D heterogeneous structure. This approach uses the dense K-NET and KiK-net nationwide networks in Japan and a high-performance supercomputer to perform forecasts using the assimilated wavefields at speeds much faster than the actual wave propagation speed. Therefore, an early alert can be issued prior to the occurrence of strong motions in basins due to large, distant earthquakes. We validated the effectiveness of this data-assimilation-based forecast approach via numerical tests for the early forecast of long-period ground motions in central Tokyo using the observed waveform data from the Mw6.6 2007 Off Niigata and Mw9.0 2011 Off Tohoku earthquakes.