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Tsunamis generated by seafloor displacements accompanying large submarine earthquakes provide sensitivity to absolute slip position and distribution for offshore faulting analogous to that of geodetic observations for landward faulting. Tsunami recordings at deep‐water and near‐shore ocean bottom pressure sensors and tide gauges, along with runup and inundation measurements, can now be reliably modeled using detailed bathymetric structures and robust numerical codes. As a result, tsunami observations now play an important role in quantifying coseismic slip distributions for large submarine earthquakes in subduction zones and other tectonic environments. Applications of joint modeling or inversion of seismic, geodetic and tsunami observations for recent major earthquakes are described, highlighting the specific contributions of the tsunami observations to source model resolution. Tsunami observations provide unique information on the up‐dip extent of earthquake coseismic slip on subduction zone megathrust faults and occurrence of near‐trench slip, which are usually not well constrained by seismic and land‐based geodetic signals. Tsunami signals also help to detect offshore slow slip that is not evident in seismic or land‐based geodetic data and to balance geophysical constraints on ruptures that extend from on‐shore to off‐shore. Tsunami runup measurements and stratigraphic deposits further provide unique constraints on large earthquake ruptures that occurred prior to modern geophysical instrumentation.
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Real‐Time Prediction of Alongshore Near‐Field Tsunami Runup Distribution From Heterogeneous Earthquake Slip Distribution
Abstract Real‐time tsunami prediction is necessary for tsunami forecasting. Although tsunami forecasting based on a precomputed tsunami simulation database is fast, it is difficult to respond to earthquakes that are not in the database. As the computation speed increases, various alternatives based on physics‐based models have been proposed. However, physics‐based models still require several minutes to simulate tsunamis and can have numerical stability issues that potentially make them unreliable for use in forecasting—particularly in the case of near‐field tsunamis. This paper presents a data‐driven model called the tsunami runup response function for finite faults (TRRF‐FF) model that can predict alongshore near‐field tsunami runup distribution from heterogeneous earthquake slip distribution in less than a second. Once the TRRF‐FF model is trained and calibrated based on a discrete set of tsunami simulations, the TRRF‐FF model can predict alongshore tsunami runup distribution from any combination of finite fault parameters. The TRRF‐FF model treats the leading‐order contribution and the residual part of the alongshore tsunami runup distribution separately. The interaction between finite faults is modeled based on the leading‐order alongshore tsunami runup distribution. We validated the TRRF‐FF modeling approach with more than 200 synthetic tsunami scenarios in eastern Japan. We further explored the performance of the TRRF‐FF model by applying it to the 2011 Tohoku (Japan) tsunami event. The results show that the TRRF‐FF model is more flexible, occupies much less storage space than a precomputed tsunami simulation database, and is more rapid and reliable than real‐time physics‐based numerical simulation.
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- PAR ID:
- 10392942
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Oceans
- Volume:
- 128
- Issue:
- 1
- ISSN:
- 2169-9275
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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