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arXiv · 1901.11124

Quantifying the Value of Real-time Geodetic Constraints for Earthquake Early Warning using a Global Seismic and Geodetic Dataset

C. J. Ruhl·D. Melgar·A. I. Chung·R. Grapenthin·R. M. Allen
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Abstract

Geodetic earthquake early warning (EEW) algorithms complement point-source seismic systems by estimating fault-finiteness and unsaturated moment magnitude for the largest, most damaging earthquakes. Because such earthquakes are rare, it has been difficult to demonstrate that geodetic warnings improve ground motion estimation significantly. Here, we quantify and compare timeliness and accuracy of magnitude and ground motion estimates in simulated real time from seismic and geodetic observations for a suite of globally-distributed, large earthquakes. Magnitude solutions saturate for the seismic EEW algorithm (we use ElarmS) while the ElarmS-triggered Geodetic Alarm System (G-larmS) reduces the error even for its first solutions. Shaking intensity (MMI) time series calculated for each station and each event are assessed based on MMI-threshold crossings, allowing us to accurately characterize warning times per-station. We classify alerts and find that MMI 4 thresholds result in only 12.3% true positive (TP) alerts with a median warning time of 16.3 +- 20.9 s for ElarmS, but 44.4% TP alerts with a longer median warning time of 50.2 +- 49.8 s for G-larmS. The geodetic EEW system reduces the number of missed alerts for thresholds of MMI 3 and 4 by over 30%. If G-larmS was triggered instantaneously at the earthquake origin time, the performance statistics are similar, with slightly longer warning times and slightly more accurate magnitudes. By quantifying increased accuracy in magnitude, ground motion estimation, and alert timeliness; we demonstrate that geodetic algorithms add significant value, including better cost savings performance, to EEW systems.

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BibTeXRIS

C. J. Ruhl, D. Melgar, A. I. Chung, R. Grapenthin, R. M. Allen. 2019-01-30. Quantifying the Value of Real-time Geodetic Constraints for Earthquake Early Warning using a Global Seismic and Geodetic Dataset. https://doi.org/10.1029/2018jb016935

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