Development of a Geodetic Component for the U.S. West Coast Earthquake Early Warning System

• DOI: 10.1785/0220180162
• Publication Date: 2018-10-03T18:25:06Z
• Authors: J. R. Murray; B. W. Crowell; R. Grapenthin; K. Hodgkinson; J. O. Langbein; T. Melbourne; D. Melgar; S. E. Minson; D. A. Schmidt
• Keywords: Washington; seismic waves; body waves; early warning systems; S-waves; algorithms; 01 natural sciences; California; global navigation satellite systems; Oregon; geodetic networks; warning systems; 0103 physical sciences; ShakeAlert; earthquakes; elastic waves; faults; Geomorphology; United States; natural hazards; waveforms; geologic hazards; displacements; Geophysics and Seismology; P-waves; Tectonics and Structure

An earthquake early warning (EEW) system, ShakeAlert, is under development for the West Coast of the United States. This system currently uses the first few seconds of waveforms recorded by seismic instrumentation to rapidly characterize earthquake magnitude, location, and origin time; ShakeAlert recently added a seismic line source algorithm. For large to great earthquakes, magnitudes estimated from the earliest seismic data alone generally saturate. Realâ€time Global Navigation Satellite System (GNSS) data can directly measure large displacements, enabling accurate magnitude estimates for Mw7+ events, possibly before rupture termination. GNSSâ€measured displacements also track evolving slip and, alone or in combination with seismic data, constrain finiteâ€fault models. Particularly for largeâ€magnitude, longâ€rupture events, GNSSâ€based magnitude and rupture extent estimates can improve updates to predicted shaking and thus alert accuracy. GNSS data processing centers at ShakeAlert partner institutions provide realâ€time streams to the EEW system, and three geodetic EEW algorithms have been developed through the ShakeAlert collaboration. These algorithms will undergo initial testing within ShakeAlert’s computational architecture using a suite of input data that includes simulated realâ€time displacements from synthetic earthquakes and GNSS recordings from recent earthquakes worldwide. Performance will be evaluated using metrics and standards consistent with those adopted for ShakeAlert overall. This initial assessment will guide method refinement and synthesis of the most successful features into a candidate geodetic algorithm for the ShakeAlert production system. In parallel, improvements to geodetic networks and streamlining approaches to data processing and exchange will ensure robust geodetic data availability in the event of an earthquake.