HR: 14:25h
AN: S43D-04    [Abstracts]
TI: Earthquake forecasting using the pattern informatics (PI) index
AU: * Tiampo, K F
EM: ktiampo@uwo.ca
AF: Department of Earth Sciences, University of Western Ontario, London, ON N6A 5B7 Canada
AU: Rundle, J B
EM: rundle@cse.ucdavis.edu
AF: Center for Computational Science and Engineering, University of California, Davis, CA 95616 United States
AU: Holliday, J
EM: holliday@cse.ucdavis.edu
AF: Center for Computational Science and Engineering, University of California, Davis, CA 95616 United States
AU: Nanjo, K Z
EM: nanjo@ism.ac.jp
AF: The Institute of Statistical Mathematics, Minato-ku, Tokyo, 106-8569 Japan
AU: Chen, C
EM: s123@sal.gep.ncu.edu.tw
AF: Department of Earth Sciences and Graduate Institute of Geophysics, National Central University, Jhongli, Taoyuan, 320, ROC Taiwan
AU: Turcotte, D L
EM: turcotte@geology.ucdavis.edu
AF: Department of Geology, University of California, Davis, 095616 United States
AU: Jimenez, A
EM: ajlloret@ual.es
AF: Department of Applied Physics, University of Almeria, Almeria, 04120 Spain
AU: Levin, S
EM: slevin2@uwo.ca
AF: Center for Computational Science and Engineering, University of California, Davis, CA 95616 United States
AB: Recent large earthquakes include the M ~ 7.4 event that struck Izmit, Turkey in August of 1999, the M ~ 7.6 Taiwan earthquake which occurred in September of 1999, the M ~ 7.1 Hector Mine, California earthquake of October 1999, and the M ~ 9 Indonesian earthquake of December 2005. Many similar examples have been documented over the course of time, yet, until recently, no reliable precursors have been detected with any repeatability. The most successful recent geophysical research associated with earthquakes forecasting has centered on investigating the spatial and temporal patterns in seismicity data. In the past we have employed a pattern informatics analysis technique, formulated based on the physical and theoretical understanding of complex, nonlinear fault systems, to isolate emergent regions of coherent, correlated seismicity prior to their occurrence in southern California (Tiampo et al., 2002). This new technique, the PI index, identifies the characteristic patterns associated with the shifting of small earthquakes from one location to another through time prior to the occurrence of large earthquakes. These identify regions of increased probability of a future large earthquake, on an intermediate length time scale. Examples of the application of this technique to other regions, such as Turkey, Spain, Japan, and the Caribbean, will be discussed, and the current extent of its ability to forecast the magnitude of the upcoming event.
DE: 3238 Prediction (3245, 4263)
DE: 3245 Probabilistic forecasting (3238)
DE: 4460 Pattern formation
DE: 7209 Earthquake dynamics (1242)
DE: 7223 Earthquake interaction, forecasting, and prediction (1217, 1242)
SC: Seismology [S]
MN: Fall Meeting 2005