Internal Code: MAS3820
Earthquake early warning (EEW) is the rapid detection of an earthquake underway, and prediction of the expected ground shaking within seconds so that a warning can be broadcast to those in harm’s way. Currently, such systems are implemented in Mexico [Espinosa‐Aranda et al., 2011] and Japan [Doi, 2011], and are being tested in other parts of the Americas, Asia and Europe [see Allen et al., 2009a, and references therein]. One of the challenges for EEW development is to ensure that the system functions appropriately for the largest and least frequent earthquakes. Many of the EEW methodologies use just a few seconds of the P‐wave to estimate the magnitude of an event, and it remains controversial how accurate this approach is for larger earthquakes [Olson and Allen, 2005; Rydelek and Horiuchi, 2006; Lewis and Ben‐Zion, 2008; Brown et al., 2009]. In March 11, 2011, M9 Tohoku‐oki earthquake the JMA warning system issued an alert, but the seismically based magnitude for the warning system peaked at M8.1 [Sagiya et al., 2011]. The now available real‐time GPS data streams have the potential to contribute to EEW system for these larger events [e.g., Crowell et al., 2009]. New techniques to rapidly characterize large magnitude events will also benefit all rapid earthquake information systems used by the emergency response and scientific response communities. In this paper, we present a practical application of a simple method for extraction of real‐time constraints on earthquake magnitude. We apply the method to real‐time 1Hz GPS total displacement waveforms generated from California Real Time Network (CRTN) data as described by Bock et al.  during the April 4, 2010, Mw 7.2 El Mayor‐Cucapah earthquake, which straddled the California‐Mexico border. We use these data to compare the GPS and seismic wave-forms, explore what constraints the GPS data can provide, determine the timeline when the GPS constraints are available, and illustrate how the GPS could be incorporated into existing seismic EEW methodologies. While the algorithm development and application was obviously done after the fact, it is fully causal and the algorithm/code has been written
in such a way that it could be running in real‐time. The focus here is on how displacement time series could be used for EEW, whereas issues related to the different processing approaches to generate the displacement time series are beyond the scope of the present study. We assess the utility of GPS‐based real‐time earthquakes information in the context of the existing ElarmS EEW methodology that is currently operating in California [Allen and Kanamori, 2003; Allen et al., 2009b; Brown et al., 2011].
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