Japan Geoscience Union Meeting 2021

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[E] Oral

M (Multidisciplinary and Interdisciplinary) » M-IS Intersection

[M-IS08] Interdisciplinary studies on pre-earthquake processes

Sun. Jun 6, 2021 10:45 AM - 12:15 PM Ch.22 (Zoom Room 22)

convener:Katsumi Hattori(Department of Earth Sciences, Graduate School of Science, Chiba University), Dimitar Ouzounov(Center of Excellence in Earth Systems Modeling & Observations (CEESMO) , Schmid College of Science & Technology Chapman University, Orange, California, USA), Jann-Yenq LIU(Department of Space Science and Engineering, National Central University, Taiwan), Qinghua Huang(Peking University), Chairperson:Katsumi Hattori(Department of Earth Sciences, Graduate School of Science, Chiba University), Dimitar Ouzounov(Center of Excellence in Earth Systems Modeling & Observations (CEESMO) , Schmid College of Science & Technology Chapman University, Orange, California, USA)

11:50 AM - 12:10 PM

[MIS08-05] Assessing the potential earthquake precursory information in ULF magnetic data recorded in Kanto, Japan during 2000 – 2010: distance and magnitude dependences

★Invited Papers

*Peng Han1, Jiancang Zhuang2, Katsumi Hattori3, Chieh-Hung Chen4, Febty Febriani5, Hongyan Chen1 (1.Southern University of Science and Technology, Shenzhen, China, 2.The Institute of Statistical Mathematics, Tokyo, Japan, 3.Graduate School of Science, Chiba University, Chiba, Japan, 4.Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China, 5.Research Center for Physics, Indonesian Institute of Sciences, Tangerang, Banten, Indonesia)

Keywords:ULF magnetic data, earthquake precursory information, Molchan’s error diagram, Kanto, Japan

In order to clarify the ULF seismo-magnetic phenomena, a sensitive geomagnetic network has been installed in Kanto, Japan since 2000. In previous studies, we have verified the correlation between ULF magnetic anomalies and local sizeable earthquakes. In this paper, we use Molchan’s error diagram to evaluate the potential earthquake precursory information in the magnetic data recorded in Kanto, Japan during 2000 – 2010. We introduce the probability gain (PG') and the probability difference (D') to quantify the forecasting performance and to explore the optimal prediction parameters for a given ULF magnetic station. The results show that the earthquake predictions based on magnetic anomalies are significantly better than random guesses, indicating the magnetic data contain potential useful precursory information. Further investigations suggest that the prediction performance depends on the choices of the distance (R) and size of the target earthquake events (Es). Optimal R and Es are about (100 km, 108.75) and (180 km, 108.75) for Seikoshi (SKS) station in Izu and Kiyosumi (KYS) station in Boso, respectively.