HR: 17:45h
AN: S44A-07    [Abstracts]
TI: Data Fusion Concepts for Tsunami Warning
AU: Hebenstreit, G T
EM: gerald.t.hebenstreit@saic.com
AF: SAIC, 1710 SAIC Dr M/S 1-11-15, Mclean, VA 22102, United States
AU: * Salzberg, D H
EM: david.h.salzberg@saic.com
AF: SAIC, 1710 SAIC Dr M/S 1-11-15, Mclean, VA 22102, United States
AB: The tsunami source region for subduction zone earthquakes is near the base of the acreationary wedge. In that region the material properties are weak, and are unable to store significant elastic energy. Therefore, the tsunamigenic rupture is nearly aseismic. Instead, the seismic energy primarily radiates from deeper within the fault; thus resolving or imaging this shallow rupture is extremely difficult, particularly when factoring in the real time requirements of tsunami warning. In the current U.S. Tsunami warning systems, the operational paradigm is to initially determine the most probable source parameters in a maximum likelihood sense, then establish alert level based, and wait for sea level measurements (DART or tide gauge) to validate or cancel the alert. This approach results in numerous false alarms, with some missed tsunamis based on the initial alert. In fact, the maximum likelihood approach works well for typical events; however, the tsunamigenic events are outliers; in the last 30 years, there have been about 130 events of size and location that would warrant a expanding warning. Of those events, 43 were associated with tsunamis of greater than 1 m; however, most of those were local, with only 13 events having significant far field tsunamis. So, even for large events, tsunamigenic earthquakes are statistical outliers. To address this issue, we have conceptualized a data fusion based approach to tsunami warning that will incorporate multiple data types simultaneously to provide better, rapid estimates of tsunami source, partially by identifying "statistical outliers" and partially by running multiple hypothesis of tsunami sources. For example, we can test to see the error bias of the preliminary magnitude estimate; that is, is the system more likely underestimating or overestimating the magnitude. In addition, incorporating non-seismic data, such as hydroactoustic (T-phase) and GPS data may improve the ability to image the shallow rupture. The approach also allows for the incorporation of evidence for slumping/landslides, including anomalous long period Rayleigh waves (e.g., Eksrom, 2006) and hydroacoustic signals. In summary, a fusion approach to tsunami warning should provide for lower false alarm rates while increasing the probability of detection of the events in time period prior to sea level measurements.
DE: 4564 Tsunamis and storm surges
DE: 7215 Earthquake source observations (1240)
SC: Seismology [S]
MN: 2007 Fall Meeting