IMPROVING REGIONAL SEISMIC EVENT LOCATION THROUGH CALIBRATION OF THE INTERNATIONAL MONITORING SYSTEM

At Lawrence Livermore National Laboratory (LLNL), we are working to help calibrate the 170 seismic stations that are part of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) monitoring network, in order to enhance the network's ability to locate small seismic events. These low magnitude events are likely to be recorded by only the closest of seismic stations, ranging from local to near teleseismic distances. At these distance ranges, calibration statistics become highly nonstationary, challenging us to develop more general statistical models for proper calibration. To meet the goals outlined above, we are developing a general nonstationary framework to accurately calibrate seismic travel-time predictions over the full distance range, from local, to regional, to teleseismic distances. The objective of this framework is to develop valid region-specific corrections for the Middle East, North Africa, and portions of the Soviet Union, to assess our progress towards meeting calibration goals, and to perform cost- benefit analysis for future calibrations. The framework integrates six core components essential to accurate calibration. First, is the compilation and statistical characterization of well located reference events, including aftershock sequences, mining explosions and rockbursts, calibration explosions, and teleseismically constrained events (Harris et al., SSA 1999; Hanley et al., SSA 1999). Second, is the development of generalized velocity models based on these reference events (McNamara et al., SSA 1998; Pasyanos, SSA 1999). Third, is the development of nonstationary spatial corrections (nonstationary Bayesian kriging) that refine the base velocity models (Schultz et al., SSA 1998). The fourth component is the development of a detection model on a station- by-station basis. The fifth component is the cross-validation of calibration results to ensure internal consistency along with the continual benchmarking of our nonstationary model where event locations are accurately known (Myers and Schultz., SSA 1999). Finally, the sixth component is the development of location uncertainty maps, demonstrating how calibration is helping to improve location accuracy across both seismically active and aseismic regions. Together, these components help us to ensure the accurate location of events, and just as important, help to ensure the accurate representation of bias uncertainty and random uncertainty in the predicted error ellipses.