Error distribution and correction of the predicted wave characteristics over the Persian Gulf

OCEAN ENGINEERING

卷:75

Article

Moeini, Mohammad Hadi¹  Etemad-Shahidi, Amir²  Chegini, Vahid³  Rahmani, Iraj⁴  Moghaddam, Mona⁴ 

[1] Iran Univ Sci & Technol, Sch Civil Engn, Tehran, Iran

[2] Griffith Univ, Griffith Sch Engn, Gold Caost, Qld 4222, Australia

[3] Iranian Natl Inst Oceanog, Tehran, Iran

[4] Transportat Res Inst, Tehran, Iran

关键词: Persian Gulf;    Wave hindcasting;    SWAN;    Error distribution;    Wave modeling;   

DOI  :  10.1016/j.oceaneng.2013.11.012

来源: Elsevier

【 摘 要 】

Wind-waves are the most important environmental parameter for the design of coastal and offshore structures, sediment transport, coastal erosion etc. Therefore, an accurate evaluation of the wave climate is of great importance. Due to the lack of long term measurements, nowadays numerically modeled wave data are widely used for determining the wave climate. The numerically simulated wave data are continuous in time and space, but generally inaccurate in enclosed and semi-enclosed basins mainly due to the inaccurate wind input data. The main goal of this study is to develop a new and efficient approach to improve the hindcasted wave parameters in the Persian Gulf. Hence, the third generation SWAN model was employed for the wave modeling forced by the 6-hourly ECMWF wind data with a resolution of 0.5. A new methodology was introduced for the distribution of wave prediction errors from discrete observation points to the other points of interest. It was found that the proposed method which considers the wave generation physics, leads to a significant improvement in the predicted wave parameters. In addition, it was revealed that the improvements in prediction of waves with higher wave heights and longer periods are more than those of others. This was shown to be due to the higher correlation between high values of output parameters which contain larger errors. The influence radius in the error distribution procedure was found to be near 2 (similar to 200 km). (C) 2013 Elsevier Ltd. All rights reserved.

【 授权许可】

Free