Synthetic testing of the Pacific Northwest earthquake early warning system

Abstract:

The Cascadia subduction zone poses one of the greatest risks for a megaquake in the continental United States and, because of this, the Pacific Northwest Seismic Network (PNSN) at the University of Washington is building a joint seismic and geodetic earthquake early warning system. Our two-stage approach to earthquake early warning includes: (1) detection and initial characterization using strong-motion and broadband data from the PNSN with the ElarmS package, and (2) geodetic modeling modules using GPS data from the Pacific Northwest Geodetic Array (PANGA) and combined seismogeodetic (GPS + strong-motion) data. Because of Cascadia’s relatively low seismicity rate and the paucity of data from plate boundary earthquakes, we have prioritized the development of a test system and the creation of several large simulated events. The test system permits us to: (1) replay segments of actual seismic waveform data recorded from the PNSN and neighboring networks to represent both earthquakes and noise conditions, and (2) broadcast synthetic data into the system to simulate signals we anticipate from earthquakes for which we have no actual ground motion recordings. The test system lets us also simulate various error conditions (latent and/or out-of-sequence data, telemetry drop-outs, etc.) and to explore how best to mitigate them. Here, we report on the performance of the joint early warning system and the geodetic modeling modules in a simulated real-time mode using simulated 5-Hz displacements from plausible Cascadian earthquake scenarios. The simulations are created using the FK integration method for hypothetical source models for a wide array of possible faulting types and magnitudes. The results show that the geodetic modeling modules are able to properly characterize the simulated events, and we discuss the limitations with respect to latency, network architecture, and earthquake location throughout the Pacific Northwest.