Resumen de Performance of the GFZ decentralized on‐site earthquake early warning software (GFZ‐Sentry): application to k‐net and kik‐net recordings, Japan
S. Parolai, A. Oth, Tobias Boxberger
In this article, we report on the application of GFZ‐Sentry software for decentralized on‐site earthquake early warnings to a large data set of recordings collected by the Japanese K‐NET and KiK‐net seismic networks. The data set is composed of 3,225 three‐component recordings from 24 seismic events. The magnitudes of the selected earthquakes fall into a range of MJMAMJMA 6.0–7.3 ( MwMw 5.7–6.9) and cover hypocentral (epicentral) distances between 5 and 107 km (2 and 103 km, respectively). The data have been coordinated in real time with velocity and displacement; in this manner, the peak ground displacement (Pd) within the first few seconds (to a maximum of 3 s) after the P‐wave arrival in the vertical component is determined. This value is used to estimate the peak ground velocity (the median, along with the associated 16% and 84% confidence intervals) on the horizontal components using empirical relationships. Based on these values, the traffic light status (green, orange, red) is then determined following the methodology introduced by Parolai et al. (2015), which uses three matrices to show the relationship between the expected ground motion and the possible damage (in terms of seismic intensity) that may arise. The performance of the software was evaluated without making ad hoc calibrations for the area or the selected thresholds and was found to be quite reliable.
For example, in 90% of cases, assignment of the “red” status is followed by shaking that leads to a seismic intensity equal to or greater than V (very light potential damage). Additionally, all of the recordings leading to an intensity greater than VII (moderate to heavy damage) were correctly classified by a red status. Similarly, when considering all the declared green statuses, it is remarkable that only in 10% of cases was there a “missed alarm” (i.e., a green status is determined, but due to the level of observed shaking, it is later seen that the status should have been red).
