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

被引:17
|
作者
Almeida, Sofia [1 ]
Rusu, Liliana [1 ]
Soares, Carlos Guedes [1 ]
机构
[1] Univ Lisbon, Ctr Marine Technol & Ocean Engn CENTEC, Inst Super Tecn, Lisbon, Portugal
关键词
Data assimilation; Kalman filter; wave forecast; wave modelling; SWAN; SYSTEM;
D O I
10.1080/1755876X.2016.1244232
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
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.
引用
收藏
页码:103 / 114
页数:12
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