We propose a tsunami forecasting method based on a data assimilation technique designed for dense tsunameter networks. Rather than using seismic source parameters or initial sea surface height as the initial condition of for a tsunami forecasting, it estimates the current tsunami wavefield (tsunami height and tsunami velocity) in real time by repeatedly assimilating dense tsunami data into a numerical simulation. Numerical experiments were performed using a simple 1‐D station array and the 2‐D layout of the new S‐net tsunameter network around the Japan Trench. Treating a synthetic tsunami calculated by the finite‐difference method as observed data, the data assimilation reproduced the assumed tsunami wavefield before the tsunami struck the coastline. Because the method estimates the full tsunami wavefield, including velocity, these wavefields can be used as initial conditions for other tsunami simulations to calculate inundation or runup for real‐time forecasting.
National Research Institute for Earth Science and Disaster Resilience (NIED) integrated the land observation networks established since the 1995 Kobe earthquake with the seafloor observation networks established since the 2011 Tohoku earthquake and tsunami as MOWLAS (Monitoring of Waves on Land and Seafloor) in November 2017. The purpose of MOWLAS is to provide comprehensive, accurate, and rapid observation and monitoring of earthquake, tsunami, and volcano events throughout Japan and its offshore areas. MOWLAS data are widely utilized for long-term earthquake forecasting, the monitoring of current seismic activity, seismic and tsunami hazard assessments, earthquake early warning, tsunami warning, and earthquake engineering, as well as earthquake science. Ocean bottom observations provide an extension of observations to areas where no people are living and have the advantage of increasing lead time of earthquake early warning and tsunami warning. The application of recent technology advancements to real-time observations as well as the processing of MOWLAS data has contributed to the direct disaster mitigation of ongoing earthquakes. These observations are fundamental for both science and disaster resilience, and thus it is necessary to continue ceaseless operation and maintenance.
We present high-resolution three-dimensional tomographic images of the crust beneath the entire Kyushu arc, and particularly the western portion. Our results reveal a velocity anomaly that correlates well with an upper crustal gravity anomaly. Signi cant low-velocity anomalies exist beneath the Miyazaki plane and along the Beppu-Shimabara Graben. Another extensive low-velocity region near the bottom of the crust is located just below the volcanic front and between active volcanoes. The low-velocity anomalies exhibit low V p and V p /V s characteristics, and the spatial relationship between these anomalies, the Bouguer gravity anomaly, and the Moho suggests that low-density material at the base of the crust is responsible for both the seismic and gravity signatures. We interpret this material to constitute a relict ridge subducting below the Kyushu Mountains.
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