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IUGG XXIV General Assembly July 2-13, 2007 Perugia, Italy<br />

(S) - <strong>IASPEI</strong> - International Association of Seismology and Physics of the Earth's<br />

Interior<br />

JSS002 Oral Presentation 1736<br />

A Comparison Study of Two Numerical Tsunami Forecasting Systems<br />

Dr. Diana Greenslade<br />

Bureau of Meteorology Research Centre Australian Bureau of Meteorology <strong>IASPEI</strong><br />

Vasily Titov<br />

Recent tsunami events, e.g. Sumatra 2004 and Java 2006 have demonstrated the need for providing<br />

accurate and timely tsunami warnings. Improvements in the availability of sea-level observations and<br />

advances in numerical modelling techniques are increasing the potential for tsunami warnings to be<br />

based on numerical model forecasts. Numerical tsunami propagation and inundation models are well<br />

developed, but they present a challenge to run in real-time; partly due to computational limitations and<br />

also due to lack of detailed knowledge on the earthquake rupture details. For these reasons, current<br />

tsunami forecast systems are based on pre-computed tsunami scenarios. A tsunami scenario is a single<br />

tsunami model run that is calculated ahead of time with the initial conditions carefully selected so that<br />

they are likely to represent an actual tsunamigenic earthquake. This paper will present a comparison of<br />

two tsunami scenario databases: the NOAA/PMEL system, currently being implemented at NOAA<br />

Tsunami Warning Centers and the Bureau of Meteorology system, which is being developed for the<br />

Australian Tsunami Warning System. Both scenario databases are based on the MOST numerical model,<br />

but there are some differences in the way the scenarios are constructed. The databases will be<br />

described, and a comparison of results for the Tonga event (May 3, 2006) will be presented. The<br />

tsunami forecasts will be compared to each other and to available observations, including those from<br />

two DART buoys located near Hawaii.<br />

Keywords: tsunami, forecast, modelling

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