HR: 11:50h
AN: NG22A-07 INVITED     [Abstracts]
TI: Pattern informatics and its application for forecasting large earthquakes in Japan
AU: * Nanjo, K Z
EM: nanjo@cse.ucdavis.edu
AF: Center for Computational Science and Engineering, c/o Department of Physics, University of California at Davis, One Shields Avenue, Davis, CA 95616 United States
AU: Rundle, J B
EM: jbrundle@ucdavis.edu
AF: Center for Computational Science and Engineering, c/o Department of Physics, University of California at Davis, One Shields Avenue, Davis, CA 95616 United States
AU: Holliday, J R
EM: holliday@cse.ucdavis.edu
AF: Center for Computational Science and Engineering, c/o Department of Physics, University of California at Davis, One Shields Avenue, Davis, CA 95616 United States
AB: The 17 January 1995 Kobe, Japan, earthquake was only a magnitude 7.2 event and yet produced an estimated \$200 billion loss. The magnitude of potential loss of life and property is so great that reliable earthquake forecasting should be at the forefront of research goals, especially in Japan. An approach to earthquake forecasting is Pattern Informatics (PI). The PI technique can be used to detect precursory seismic activation or quiescence and make earthquake forecasts. Application to earthquake data from southern California shows that this method is a powerful technique for forecasting large events. Here, we attempt to forecast Japan earthquakes using the PI method. To insure the completeness of earthquake catalog maintained by Japan Meteorological Agency, events in 1955-1994 around the epicenter of the Kobe event are used for our analyses. This is done for forecasting the occurrence of large future events that are the earthquakes of magnitude greater than 5 for the time period 1995-present, including the Kobe event. Optimizing parameters of the PI method needs to be performed. We also change the extent of our study area to determine the optimal application of the method. Our results show that the method has skill for forecasting the spatial and temporal distribution of the large future earthquakes. Specifically, we find that the occurrence of the Kobe event can correspond to a seismically anomalous region. We further use two statistical tests to evaluate the accuracy for forecasting the large future events. The results of these tests also support that the method has some forecast skill.
DE: 7223 Seismic hazard assessment and prediction
DE: 7260 Theory and modeling
DE: 7294 Instruments and techniques
DE: 3220 Nonlinear dynamics
DE: 3230 Numerical solutions
SC: Nonlinear Geophysics [NG]
MN: 2004 AGU Fall Meeting