Abstract
We present a method of tsunami data assimilation using a linear dispersive model in order to provide an accurate tsunami early warning. To speed up the assimilation process, we use the Green’s function-based tsunami data assimilation, in which the Green’s functions are calculated in advance with linear dispersive tsunami propagation models. We demonstrate a test case in the Nankai Trough off southwest Japan, with a source model similar to the main shock of the 2004 off the Kii Peninsula earthquake (M7.4) which generated tsunamis with dispersive characteristics. We show that assimilation of existing ocean bottom pressure gauge data can rapidly forecast the tsunami arrival time and the maximum height of the first tsunami peak along the coast of Shikoku and Kyushu Islands. Both the linear long-wave model and the linear dispersive model can accurately forecast the tsunami height, but the linear dispersive model can predict the tsunami arrival time more accurately for the tested earthquake.
Highlights
Tsunami data assimilation is a promising approach for tsunami forecasting
An optimum interpolation method (Kalnay 2003) is adopted in data assimilation to compute the tsunami wavefield and to forecast the tsunami arrival time and maximum amplitude along the coast. This method has been successfully applied to observed tsunami waveforms of the 2012 Haida Gwaii Earthquake (Gusman et al 2016) using bottom pressure gauge array data in the Cascadia subduction zone and a hypothetic tsunami in the Tohoku region (Maeda et al 2015) using synthetic data based on the Seafloor Observation Network for Earthquakes and Tsunamis (S-net)
The accuracy of the forecasted maximum amplitude and arrival time depends on the length of the assimilation time window
Summary
Tsunami data assimilation is a promising approach for tsunami forecasting It predicts the tsunami waveform by assimilating offshore observed data into a numerical simulation, without calculating the initial sea surface height at the source (Maeda et al 2015). An optimum interpolation method (Kalnay 2003) is adopted in data assimilation to compute the tsunami wavefield and to forecast the tsunami arrival time and maximum amplitude along the coast. This method has been successfully applied to observed tsunami waveforms of the 2012 Haida Gwaii Earthquake (Gusman et al 2016) using bottom pressure gauge array data in the Cascadia subduction zone and a hypothetic tsunami in the Tohoku region (Maeda et al 2015) using synthetic data based on the Seafloor Observation Network for Earthquakes and Tsunamis (S-net). We compare the forecasted results of arrival time and maximum height by assimilation using the LLW and DSP models
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