JpGU-AGU Joint Meeting 2020

Presentation information

[J] Oral

S (Solid Earth Sciences ) » S-SS Seismology

[S-SS13] Seismicity

convener:Yasuhiro Yoshida(Meteorological College, Japan Meteorological Agency)

[SSS13-03] Difference of foreshock characteristics between real data and synthetic space-time ETAS catalogs:
Through the application of an earthquake forecasting method by supposing swarm-like activity to be possible foreshocks

*Fuyuki Hirose1, Koji Tamaribuchi1, Kenji Maeda2 (1.Seismology and Tsunami Research Department, Meteorological Research Institute, 2.Seismology and Volcanology Department, Japan Meteorological Agency)

Keywords:Earthquake forecast model, Foreshocks, Space-time ETAS model, Izu islands

It is pointed out that there is no effective earthquake forecast model than ETAS model [Ogata, 1988, JASA] because earthquakes are probabilistic phenomena driven by seismically cascading process represented by a superposition of background activity and epidemic-type aftershock sequence [e.g., Felzer et al., 2004, BSSA; 2015, NatureGeo]. On the other hand, it is also pointed out that the information of foreshock characteristics could be an effective clue of earthquake forecast because foreshocks are a part of the nucleation process, including precursory slips, which ETAS model cannot represent [e.g., Lippiello et al., 2012, SciRep; Bouchon et al., 2013, NatureGeo].

We investigated the reproducibility of real data by ETAS model as follows.
1. We estimated 8 parameters of stationary space-time ETAS model [Ogata & Zhuang, 2006, Tectonophys] by applying R package ‘ETAS’ [Jalilian, 2019, https://github.com/jalilian/ETAS] to real data in Izu islands.
2. We produced 1000 synthetic earthquake catalogs (hereafter ETAS catalogs) based on ETAS parameters obtained in step 1 and frequency-magnitude distribution of real data.
3. We investigated the efficiency of the forecast by applying an earthquake forecasting method by supposing swarm-like activity to be possible foreshocks (hereafter Maeda’s method) [Maeda, 1996, BSSA] to both real data and ETAS catalogs.
4. We compared time series of stacking cumulative numbers before mainshocks for both real data and ETAS catalogs.

Our investigation resulted in that real data yielded higher scores than ETAS catalogs when Maeda’s method was applied to those. Also, temporal acceleration of foreshocks of real data was larger than that of ETAS catalogs. In other words, it is hard for ETAS model to reproduce foreshock characteristics, indicating the earthquake forecast model based on foreshock characteristics is more efficient rather than ETAS model.