Korean East Coast wave predictions by means of ensemble Kalman filter data assimilation

Abstract

To respond to the need for preventing offshore and coastal accidents, damage and flooding, a state-of-the-art coastal wave forecast system for the East Coast of Korea waters is being developed. Given that the quality of the input wind has been identified as the main factor influencing the quality of the wave results, the effectiveness of adjusting the wind fields by means of data assimilation using the ensemble Kalman filter technique has been explored. In this article the model setup, the data assimilation parameters and the validation of the predictions during stormy periods is described. The validation shows that the model is able to provide predictions of coastal waves fulfilling available benchmarks; especially, the data assimilation analysis and forecast predictions are judged to be of high quality.