Japan Geoscience Union Meeting 2018

Presentation information

[JJ] Poster

S (Solid Earth Sciences) » S-CG Complex & General

[S-CG65] Reducing risks from earthquakes, tsunamis & volcanoes: new applications of realtime geophysical data

Wed. May 23, 2018 3:30 PM - 5:00 PM Poster Hall (International Exhibition Hall7, Makuhari Messe)

convener:Mitsuyuki Hoshiba(Meteorological Research Institute), Satoshi Kawamoto(Geospatial Information Authority of Japan), Naotaka YAMAMOTO CHIKASADA(防災科学技術研究所, 共同), Masashi Ogiso(Meteorological Research Institute, Japan Meteorological Agency)

[SCG65-P03] A feasibility study on the PLUM method with a dense observation network: An application to MeSO-net stations

*Yuki Kodera1, Shin'ichi Sakai2 (1.Meteorological Research Institute, Japan Meteorological Agency, 2.Earthquake Research Institute,The University of Tokyo)

Keywords:Earthquake early warning, Ground motion prediction, PLUM method, MeSO-net

The PLUM method is an earthquake early warning (EEW) algorithm that predicts a seismic intensity at a target site directly from observed intensities within 30 km from the site (Kodera et al., 2018). Although the prediction procedure is very simple, the PLUM method outperforms conventional point source algorithms, which are implemented into many EEW systems, in terms of robust ground motion prediction for large earthquakes with complex rupture behavior and intense seismic activities. On the other hand, the PLUM method has a shortcoming in that long warning times are not available, which resulted from the limited use of observed intensities only within 30 km. A rough estimate of the maximum warning time is 10 s, assuming the S-wave velocity of 3 km/s and no system delay.

In this study, we investigated the feasibility of the PLUM method with a dense observation network, using Metropolitan Seismic Observation network (MeSO-net) stations, deployed around the Tokyo metropolitan area with a several-km interval. The use of a dense network would enhance the timeliness of the PLUM method; multiple stations can immediately detect earthquakes that occur beneath the network. In addition, the dense network may allow to estimate detailed characteristics of ongoing wavefields such as propagation direction and apparent velocity. Incorporating such wavefield features would improve the prediction procedure of the PLUM method.

As the first step, we simulated the original PLUM method using waveform records of MeSO-net stations and evaluated the prediction accuracies and available lead times. Site corrections used in the PLUM method were obtained by comparing observed intensities at target sites to an interpolated intensity distribution based on seismic intensity data reported by the Japan Meteorological Agency (JMA). When applied to 81 M>=5 earthquakes that occurred around the network from 2009 to 2016 except earthquakes in March 2011, the PLUM method provided predicted intensities with an error of less than 0.4 unit on the JMA instrumental intensity scale in average for sites with observed intensities of 3.5 or more. The average of available lead times was 3.6 s for a seismic intensity threshold of 3.5. Compared to simulation results using KiK-net stations (Kodera, 2018), several-second additional lead times were provided in this simulation for seismic intensity thresholds of 2.5, 3.0, and 3.5; however, the prediction errors were ~0.2–0.6 units larger, and the overpredictions were apparent especially for sites with relatively low intensities (<= ~3). Although the PLUM method exhibited acceptable performance for sites with high seismic intensities, the prediction procedure may need to be improved for more accurate predictions for sites with low intensities.

Acknowledgments: Waveform records at MeSO-net stations were used in the analysis. This study is partially supported by JSPS KAKENHI Grant Number 17K13001.