Rat Islands Tsunami
Observation data from the expanding tsunami observation network will continue to provide more data for model verification. NOAA's National Geophysical Data Center (http://www.ngdc.noaa.gov/seg/hazard/tsu.shtml), NOAA's Tsunami Warning Centers (http://wcatwc.arh.noaa.gov/), and NOAA's Center for Tsunami Research websites provide updated information on the latest tsunami data. Here, we present the data used for the first real-time model forecast test as an example of data use for model verification.
The magnitude earthquake was located on the shelf near
Rat Islands, Alaska, on 17 November 2003 and generated a tsunami.
This tsunami provided good data for testing operational models,
since the tsunami was detected by three tsunameters located along
the Aleutian Trench and was recorded at many coastal locations
(Titov et al., 2005). This was the first real-time tsunami
detection by the newly developed tsunameter system (DART). In
addition, for the first time, tsunami model predictions were
obtained during the tsunami propagation, before the waves had
reached many coastlines. Here, the combined use of tsunami
propagation and inundation models is required for simulation of
tsunami dynamics from generation to inundation. The test requires
matching the propagation model data with the DART recording to
constrain the tsunami source model (Fig. 1). If a
finite-difference method on a structured grid is used, several
nested numerical grids would allow ``telescoping'' from a
coarse-resolution propagation model into a high-resolution
inundation model with a model grid of at least 50 m resolution. If
an unstructured grid method is used, a single grid may include
enough resolution near the coast. The data-constrained propagation
model should drive the high-resolution inundation model of Hilo
Harbor. The inundation model is to reproduce the tide gage record at
Hilo (Fig. 2). Since this benchmarking is required
for the forecasting models, it is essential to model 4 hr of Hilo
Harbor tsunami dynamics in 10 min of computational time.
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