摘要：To continuously monitor crustal behavior associated with earthquakes, magmatic activities and other environmental effects (e.g., tides and rain precipitation), we have developed a continuous monitoring system of seismic velocity of the Japanese Islands. The system includes four main processing procedures to obtain spatio-temporal velocity changes: (1) preparing ambient-noise data; (2) creating virtual seismograms between pairs of seismometer stations by applying seismic interferometry; (3) estimating temporal velocity variations from virtual seismograms by stretching interpolation approach, and (4) mapping spatio-temporal velocity variations. We developed a data-processing scheme that removes unstable stretching interpolation results by using the median absolute deviation technique and a median filter. To map velocity changes with high stability and high temporal resolution during long-term (i.e., longer-term monitoring), we proposed the “sliding reference method”. We also developed evaluation method to select the optimum parameters related to stability and temporal resolution. To reduce computation time for continuous monitoring, we applied parallel computation methods, such as shared memory and hybrid distributed memory parallelization. Using our efficient and stable monitoring system, we succeeded to continuously monitor the spatio-temporal velocity variation of the whole Japanese Islands using ambient-noise data from 767 seismometers. Finally, we developed a web application that displays spatio-temporal velocity changes. In the monitoring results that we open through the website, we identified velocity variation (e.g., pore pressure variation) that could be related to earthquake, aftershock, magmatic activities and environmental effects in a stable manner.
关键词：Crustal monitoring; Seismic velocity; Parallel and high-performance computing; Big data; Seismic interferometry; Ambient noise
