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

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.     

Development of the Operational Oceanographic System of Korea

Ocean Science Journal - The Korea Operational Oceanographic System (KOOS) was developed at the Korea Institute of Ocean Science and Technology (KIOST) to produce real-time forecasting and...     

Wave Data Assimilation to Modify Wind Forcing Using an Ensemble Kalman Filter

In order to improve the predictability of winter storm waves in the East Sea, this article explores the use of the ensemble Kalman filter technique for dat