Woods Hole Oceanographic Institution

Woods Hole MA 02543, USA

Princeton University

Princeton NJ 08544, USA

Woods Hole Oceanographic Institution

Woods Hole MA 02543, USA

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## Earthquake Early Warning (EEW) algorithms estimate the magnitude of an underway rupture from the first few seconds of the P-wave to allow hazard assessment and mitigation before the S-wave arrival. Many large subduction-zone earthquakes initiate 50-150 km offshore, potentially allowing seafloor instruments sufficient time to identify large ruptures before the S-waves reach land. We tested an EEW algorithm using accelerograms recorded offshore Hokkaido in the region of the 2003 Mw 8.1 Tokachi-Oki earthquake and its aftershocks. A wavelet transform of the first 4 seconds of the P-wave concentrates information about earthquake magnitude from both waveform amplitude and frequency content. We find that wavelets with support of a few seconds provide discriminants for EEW that are both accurate enough to be useful and superior to peak acceleration or peak velocity. Additionally, we observe a scaling of wavelet coefficient magnitude above Mw 6.0 indicating that, at least for the mainshock and largest aftershock (Mw 7.1), the final size of a rupture could have be estimated in a stochastic sense from the initial portion of the seismogram.

- Figure 01
Representative waveforms
*(not included in paper)*

- Figure 02
Representative waveforms and wavelet analysis

- Figure 03
Which is better: wavelets, peak velocity or acceleration?

- Figure 04
Wavelet correlates with magnitude as the Sato-Hirasawa model

Frederik Simons Last modified: Wed Apr 12 23:06:25 EDT 2023