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Numerical Procedure to Forecast the Tsunami Parameters from a Database of Pre-Simulated Seismic Unit Sources

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Abstract

We have implemented a numerical procedure to forecast the parameters of a tsunami, such as the arrival time of the front of the first wave and the maximum wave height in real and virtual tidal stations along the Peruvian coast, with this purpose a database of pre-computed synthetic tsunami waveforms (or Green functions) was obtained from numerical simulation of seismic unit sources (dimension: 50 × 50 km2) for subduction zones from southern Chile to northern Mexico. A bathymetry resolution of 30 arc-sec (approximately 927 m) was used. The resulting tsunami waveform is obtained from the superposition of synthetic waveforms corresponding to several seismic unit sources contained within the tsunami source geometry. The numerical procedure was applied to the Chilean tsunami of April 1, 2014. The results show a very good correlation for stations with wave amplitude greater than 1 m, in the case of the Arica tide station an error (from the maximum height of the observed and simulated waveform) of 3.5% was obtained, for Callao station the error was 12% and the largest error was in Chimbote with 53.5%, however, due to the low amplitude of the Chimbote wave (<1 m), the overestimated error, in this case, is not important for evacuation purposes. The aim of the present research is tsunami early warning, where speed is required rather than accuracy, so the results should be taken as preliminary.

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Acknowledgements

This research was sponsored in part by the Vice-rectorate for Research and Postgraduate from “Universidad Nacional Mayor de San Marcos” (Group Research Project 2017) and by the “Direccion de Hidrografia y Navegacion” from Peruvian Navy. In addition, we acknowledge the anonymous reviewers.

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Correspondence to César Jiménez.

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Jiménez, C., Carbonel, C. & Rojas, J. Numerical Procedure to Forecast the Tsunami Parameters from a Database of Pre-Simulated Seismic Unit Sources. Pure Appl. Geophys. 175, 1473–1483 (2018). https://doi.org/10.1007/s00024-017-1660-5

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  • DOI: https://doi.org/10.1007/s00024-017-1660-5

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