4.2 Article

Data assimilation with the ensemble Kalman filter in a high-resolution wave forecasting model for coastal areas

期刊

JOURNAL OF OPERATIONAL OCEANOGRAPHY
卷 9, 期 2, 页码 103-114

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/1755876X.2016.1244232

关键词

Data assimilation; Kalman filter; wave forecast; wave modelling; SWAN

资金

  1. Portuguese Foundation for Science and Technology [PTDC/ECM-HID/1896/2012]
  2. Portuguese Foundation for Science and Technology under post-doctoral grant [SFRH/BPD/65553/2009]

向作者/读者索取更多资源

The present work describes a post-processing implementation of the ensemble Kalman filter (EnKF) that is used to improve the wave predictions in a high-resolution Simulating Waves Nearshore computational domain implemented in the Portuguese continental nearshore. The approach consists in applying the EnKF algorithm directly to the parameter to be predicted, replacing the observation at the forecast time by the analysis previously obtained. This technique has already led previously to good results when applied to the significant wave height, and an improved algorithm is used now to increase the accuracy both of the predicted significant wave height and mean wave period. The results of this new approach indicate a visible enhancement of the wave predictions reliability. It can be thus concluded that the work continues the effort to find a better post-processing algorithm in order to improve the results of the numerical wave models near the harbour areas by means of data assimilation methods.

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