Wave data assimilation using a hybrid approach in the Persian Gulf

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Title Wave data assimilation using a hybrid approach in the Persian Gulf
Author Moeini, Mohammad Hadi; Etemad Shahidi, Amir Farshad; Chegini, Vahid; Rahmani, Iraj
Journal Name Ocean Dynamics
Year Published 2012
Place of publication Germany
Publisher Springer
Abstract The main goal of this study is to develop an efficient approach for the assimilation of the hindcasted wave parameters in the Persian Gulf. Hence, the third generation SWAN model was employed for wave modeling forced by the 6-h ECMWF wind data with a resolution of 0.5°. In situ wave measurements at two stations were utilized to evaluate the assimilation approaches. It was found that since the model errors are not the same for wave height and period, adaptation of model parameter does not result in simultaneous and comprehensive improvement of them. Therefore, an approach based on the error prediction and updating of output variables was employed to modify wave height and period. In this approach, artificial neural networks (ANNs) were used to estimate the deviations between the simulated and measured wave parameters. The results showed that updating of output variables leads to significant improvement in a wide range of the predicted wave characteristics. It was revealed that the best input parameters for error prediction networks are mean wind speed, mean wind direction, wind duration, and the wave parameters. In addition, combination of the ANN estimated error with numerically modeled wave parameters leads to further improvement in the predicted wave parameters in contrast to direct estimation of the parameters by ANN.
Peer Reviewed Yes
Published Yes
Alternative URI http://dx.doi.org/10.1007/s10236-012-0529-5
Copyright Statement Copyright 2012 Springer Berlin / Heidelberg. This is an electronic version of an article published in Ocean Dynamics, May 2012, Volume 62, Issue 5, pp 785-797. Ocean Dynamics is available online at: http://www.springerlink.com/ with the open URL of your article.
Volume 62
Issue Number 5
Page from 785
Page to 797
ISSN 1616-7341
Date Accessioned 2012-05-18
Language en_US
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Geology
URI http://hdl.handle.net/10072/46756
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

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