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Qian Liu, Xiaofeng Zhao, Jing Zou, Yunzhou Li, Zhijin Qiu, Tong Hu, Bo Wang and Zhiqian Li
The Coupled Ocean?Atmosphere?Wave?Sediment Transport (COAWST) model serves as the foundation for creating a forecast model to detect lower atmospheric ducts in this study. A set of prediction tests with different forecasting times focusing on the South C...
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Jiao Shi, Tianyun Su, Xinfang Li, Fuwei Wang, Jingjing Cui, Zhendong Liu and Jie Wang
Significant wave height (SWH) is a key parameter for monitoring the state of waves. Accurate and long-term SWH forecasting is significant to maritime shipping and coastal engineering. This study proposes a transformer model based on an attention mechanis...
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Min Roh, Sang-Myeong Oh, Pil-Hun Chang, Hyun-Suk Kang and Hyung-Suk Kim
A regional wave forecasting system in East Asia, including the Korean Peninsula, was built based on WAVEWATCH III using offshore wind forecast data from the Global Data Assimilation Prediction System. The numerical simulations were performed on the sensi...
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Chenghan Luo, Shaoping Shang, Yanshuang Xie, Zhigang He, Guomei Wei, Feng Zhang, Lei Wang and Xueding Li
The terrain, such as Taiwan Island, have been shown to have complex effects on typhoons and the associated typhoon waves. Terrain effects change with typhoon tracks. In this study, three types of typhoon tracks (northern, middle and southern) were define...
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Lingxiao Zhao, Zhiyang Li, Junsheng Zhang and Bin Teng
In recent years, wave energy has gained attention for its sustainability and cleanliness. As one of the most important parameters of wave energy, significant wave height (SWH) is difficult to accurately predict due to complex ocean conditions and the ubi...
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Montserrat Sacie, Matilde Santos, Rafael López and Ravi Pandit
One of the most promising solutions that stands out to mitigate climate change is floating offshore wind turbines (FOWTs). Although they are very efficient in producing clean energy, the harsh environmental conditions they are subjected to, mainly strong...
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Hengyu Hu, Zhengwei He, Yanfang Ling, Junmin Li, Lu Sun, Bo Li, Junliang Liu and Wuyang Chen
In this paper, a calibration algorithm for forecasting the significant wave height (SWH) in nearshore areas is proposed, based on artificial neural networks. The algorithm has two features: first, it is based on SOM-BRFnn (self-organizing map?radial basi...
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Lei Han, Qiyan Ji, Xiaoyan Jia, Yu Liu, Guoqing Han and Xiayan Lin
Deep learning methods have excellent prospects for application in wave forecasting research. This study employed the convolutional LSTM (ConvLSTM) algorithm to predict the South China Sea (SCS) significant wave height (SWH). Three prediction models were ...
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Caleb T. Lodge and Robert J. Weaver
Efficiency in storm surge modeling is crucial for forecasting coastal hazards in real-time. While computation cost may not be the main concern for organizations with ample resources, the robustness of forecasts generated by most parties are restricted by...
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Shuyi Zhou, Brandon J. Bethel, Wenjin Sun, Yang Zhao, Wenhong Xie and Changming Dong
Wave forecasts, though integral to ocean engineering activities, are often conducted using computationally expensive and time-consuming numerical models with accuracies that are blunted by numerical-model-inherent limitations. Additionally, artificial ne...
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