DATA ASSIMILATION TSUNAMI FORECASTING USING RADIAL FLOW VELOCITY DISTRIBUTION WITH OCEAN RADAR

Abstract

 We proposed a coastal tsunami forecasting method based on data assimilation using radial flow velocity distribution obtained with an ocean HF radar. The optimal interpolation method was adopted considering light calculation load. After confirming the effectiveness of the method using a simple uniform depth model with the linear long wave theory, we examined the effectiveness using a real topography model near Kashiwazaki Kariwa Nuclear Power Station with nonlinear long wave theory. Comparing tsunami waveform at the plant by the assumed tsunami source and the data assimilation tsunami forecasting, it was shown that the tsunami waveform can be predicted with high accuracy. And we confirmed that it can predict about 30 minutes later by several data assimilation.