National Oceanic and
Atmospheric Administration
United States Department of Commerce


FY 2020

Toward near-field tsunami forecasting along the Cascadia subduction zone using rapid GNSS source models

Williamson, A.L., D. Melgar, B.W. Crowell, D. Arcas, T.I. Melbourne, Y. Wei, and K. Kwong

J. Geophys. Res., 125(8), e2020JB019636, doi: 10.1029/2020JB019636 (2020)

Over the past 15 years and through multiple large and devastating earthquakes, tsunami warning systems have grown considerably in their efficacy in providing timely and accurate forecasts to affected communities. However, one part of tsunami warning that still needs improvement is forecasts catered to local, near‐field communities in the time after an earthquake rupture but before coastal inundation. In this study, we test a rapid, Global Navigation Satellite Systems (GNSS)‐driven earthquake characterization model using a large data set of synthetic megathrust ruptures for its near‐field tsunami forecasting potential. We also provide a framework for tsunami forecasting that focuses on the likelihood of exceedance of user‐defined coastal amplitudes that may be of use in the first 15 min following an earthquake. Specifically, we can estimate the earthquake magnitude, without saturation, for 82% of tested ruptures. We can also identify test ruptures as dominantly thrust events, without analyst guidance for 92% of tested thrust ruptures. Finally, modeling the tsunami component of our rapidly estimated fault rupture leads to greater than 80% accuracy in identifying tsunami impact at key coastal amplitude thresholds. This is promising for near‐field warning when the time prior to inundation is limited to tens of minutes. We focus this study on large megathrust ruptures along the quiescent Cascadia subduction zone where there is already a dense GNSS network.

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