JpGU-AGU Joint Meeting 2017

講演情報

[EE] 口頭発表

セッション記号 M (領域外・複数領域) » M-IS ジョイント

[M-IS04] [EE] Interdisciplinary studies on pre-earthquake processes

2017年5月24日(水) 09:00 〜 10:30 102 (国際会議場 1F)

コンビーナ:服部 克巳(千葉大学大学院理学研究科)、劉 正彦(国立中央大学太空科学研究所)、Ouzounov Dimitar(Center of Excellence in Earth Systems Modeling & Observations (CEESMO) , Schmid College of Science & Technology Chapman University, Orange, California, USA)、Qinghua Huang(Peking University)、座長:Ouzounov Dimitar(Center of Excellence in Earth Systems Modeling & Observations (CEESMO) , Schmid College of Science & Technology Chapman University, Orange, California, USA)、座長:服部 克巳(千葉大学大学院理学研究科)

09:45 〜 10:00

[MIS04-04] Assessing the potential earthquake precursory information in ULF magnetic data recorded in Kanto, Japan during 2000 – 2010

*韓 鵬1庄 建倉1服部 克巳2 (1.統計数理研究所、2.千葉大学)

キーワード: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.