Data assimilation with the ensemble Kalman filter in a high-resolution wave forecasting model for coastal areas. Issue 2 (2nd July 2016)

• Record Type: Journal Article
• Authors: Almeida, Sofia; Rusu, Liliana; Guedes Soares, Carlos
• Is Part Of: Journal of operational oceanography. Volume 9:Issue 2(2016)
• Page Start: 103
• Page End: 114
• Publication Date: 2016-07-02
• Subjects: Data assimilation -- Kalman filter -- wave forecast -- wave modelling -- SWAN; Oceanography -- Periodicals; Climatology -- Periodicals; Periodicals; 551.4605
• DOI: 10.1080/1755876X.2016.1244232
• Languages: English
• ISSNs: 1755-876X

Abstract

ABSTRACT: 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.