The use of such parameters may bias the estimation of tsunami sources, which is undesirable for tsunami forecasts in the cases of tsunami earthquakes.
This simulation mimicked the problem of calculating the Green's function for purposes of tsunami forecasting and/or inversion of the initial sea-surface height of large earthquakes (e.g., Tsushima et al. 2009; Baba and Cummins 2005; Takagawa and Tomita 2014).
For this study, we have retrospectively applied an algorithm of tsunami forecasting to the data that were available in real time (Figs. 1(b) and 1(c)).
Because tsunamis can be detected at offshore stations earlier than at the coast, several methods of tsunami forecasting based on offshore tsunami data have been proposed for near-field tsunamis (e.g., Baba et al., 2004; Takayama, 2008; Tatsumi and Tomita, 2009; Tsushima, 2009; Tsushima et al., 2009; Hayashi, 2010), as well as for far-field tsunamis (Titov et al., 2005).
In the present study, we examine usefulness of the PPP ship height for great tsunami forecasting.
In their method, the tsunami wavefield including offshore tsunami height and velocity will be available as initial conditions for other tsunami forecasting methods such as tFISH (Tsushima et al. 2009), NearTIF (Gusman et al. 2014) to calculate the inundation or run-up for real-time forecasting.
We prefer to use information that strongly reflects the tsunami rather than earthquake for robust and reliable tsunami forecasting.
Pseudo observation data (d) are made for the tsunami forecast test.
Here, the PPP noise was added to the tsunami simulation data used for the tsunami forecast test.
The Tokai-Tonankai-Nankai great earthquake tsunami scenario with M w 8.7 (Central Disaster Prevention Council 2003) is considered for the tsunami forecast test (Fig. 2).
