Ocean Dynamics

, Volume 68, Issue 11, pp 1571–1592 | Cite as

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

  • Sofia Caires
  • Jinah Kim
  • Jacco Groeneweg
Part of the following topical collections:
  1. Topical Collection on the 15th International Workshop on Wave Hindcasting and Forecasting in Liverpool, UK, September 10-15, 2017


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.


EnKF SWAN Wave modelling East Coast of Korea 



We are thankful to ECMWF, KMA, KHOA and the KOOS project of KIOST for the having been able to access and use their data.

Funding information

We are, furthermore, grateful to the Korean Government for funding. This research was part of a project entitled “Construction of Ocean Research Station and their Application Studies” which was funded by the Ministry of Oceans and Fisheries, South Korea.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.DeltaresDelftNetherlands
  2. 2.Korea Institute of Ocean Science and Technology (KIOST)AnsanSouth Korea

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