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A tsunami is a series of water waves caused by many
factors like earthquakes, volcanic eruptions, landslides and
meteorite impacts. This study involves the identification of
tsunami waves using partial data before it reaches the shoreline
that can be applied as a forecasting tool. The results of the
study were based 01'1 a discrete-event simulation of a prototype
tsunami wave in Deep Ocean and real data of a tsunami event
in 2003. Fast Fourier Transform (FFT) was the mathematical
tool, which was used in the study. Truncation error occurred
when a limited portion of the prototype wave was observed. The
exponential function tapered window played a major role in
reducing this truncation error. The results showed that when
25% of the prototype tsunami wave started to emerge, it is
possible to identify that the wave was of tsunami type and when
37% of the wave starts to emerge it can be verified that the wave
is a tsunami wave. The validity of this result was checked by
real data of a tsunami event occurred on 17 November 2003. It
showed that when nearly 25% of the wave was generated, it
could be identified that the wave was of tsunami type. Finally, a
tsunami wave superposed with a ship wave in Deep Ocean
showed that they have similar patterns and it was not difficult to
interpret that the superposed wave was tsunami. The results
obtained from this study can be used to forecast whether a
tsunami wave is generated. Henceforth, the responsible
authorities can take necessary actions to evacuate the residents
to safe areas and to reduce the number of false alerts.
