Application of real‐time GPS to earthquake early warning in subduction and strike‐slip environments

Abstract

[1] We explore the application of GPS data to earthquake early warning and investigate whether the coseismic ground deformation can be used to provide fast and reliable magnitude estimations and ground shaking predictions. We use an algorithm to extract the permanent static offset from GPS displacement time series and invert for the slip distribution on the fault plane, which is discretized into a small number of rectangular patches. We developed a completely "self-adapting" strategy in which the initial fault plane model is built based on a quick, approximate magnitude estimation and is then allowed to increase in size based on the evolutionary magnitude estimation resulting from the slip inversion. Two main early warning outputs are delivered in real-time: magnitude and the along-strike extent of the rupture area. These are finally used to predict the expected ground shaking due to the finite source. We tested the proposed strategy by simulating real-time environments for three earthquakes. For the M w 9.0, 2011 Tohoku-Oki earthquake, our algorithm provides the first magnitude estimate of 8.2 at 39 s after the origin time and then gradually increases to 8.9 at 120 s. The estimated rupture length remains constant from the outset at~360 km. For the M w 8.3, 2003 Tokachi-Oki earthquake, the initial magnitude estimate is 8.5 at 24 s and drops to 8.2 at 40 s with a rupture length of 290 km. Finally, for the M w 7.2, 2010 El Mayor-Cucapah earthquake, the magnitude estimate is 7.0 from the outset with a rupture length of 140 km. The accuracy of the ground shaking prediction using the GPS-based magnitude and finite extent is significantly better than existing seismology-based point source approaches. This approach would also facilitate more rapid tsunami warnings.Citation: Colombelli, S., R. M. Allen, and A. Zollo (2013), Application of real-time GPS to earthquake early warning in subduction and strike-slip environments,

Application of Seismic Array Processing to Earthquake Early Warning

“…Based on the measurement of the static field, the GPS-based approaches (Allen and Ziv, 2011;Colombelli et al, 2013) can potentially provide valid slip estimate upon the arrival of S waves. However, with limited spatial resolution and the smoothing regularization applied in the inversion, the boundary of the actual slip area can be only roughly defined.…”

“…Among the ongoing efforts to determine the finite-fault extent in real time, Global Positioning System (GPS) approaches provide more reliable static displacements, and thus a static slip model, than seismic methods (Hudnut et al, 2002;Allen and Ziv, 2011;Colombelli et al, 2013). The FinDer approach is also proposed to determine linear fault geometry based on the difference in near/far-field seismic waveforms, provided dense station coverage (Böse et al, 2012).…”

Assessment of GNSS-based height data of multiple ships for measuring and forecasting great tsunamis

“…Real-time GNSS data with high sampling (e.g., 1 Hz) possibly enable us to rapidly estimate the earthquake size and its expansion (i.e., coseismic fault model) that can more directly relate to the generated tsunami than the conventional point source estimation based on seismic wave analysis alone (Blewitt et al 2006;Ohta et al 2012;Wright et al 2012;Colombelli et al 2013). For the case of near-coast great tsunamigenic earthquakes, these GNSS analyses possibly work well to obtain a reliable fault model within about 10 min.…”

Real-time seismic intensity prediction using frequency-dependent site amplification factors

“…For the first issue, the 2011 Tohoku earthquake (M9.0) showed that rapid estimation of source parameters is hampered by very large focal areas and the simultaneous occurrence of aftershocks (Hoshiba et al 2011;Hoshiba and Ozaki 2013). Attempts to solve the problem of large focal areas have included analysis of real-time GNSS data (e.g., Colombelli et al 2013;Grapenthin et al 2014) and direct estimation of focal area and rupture direction directly from observed seismograms (Böse et al 2012). Other ingenious methods have been proposed to distinguish simultaneous multiple earthquakes (e.g., Tamaribuchi et al 2014;Wu et al 2014).…”