首页|Regional Storm Surge Forecast Method Based on a Neural Network and the Coupled ADCIRC-SWAN Model
Regional Storm Surge Forecast Method Based on a Neural Network and the Coupled ADCIRC-SWAN Model
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
万方数据
维普
Timely and accurate forecasting of storm surges can effectively prevent typhoon storm surges from causing large economic losses and casualties in coastal areas.At present,numerical model forecasting consumes too many resources and takes too long to compute,while neural network forecasting lacks regional data to train regional forecasting models.In this study,we used the DUAL wind model to build typhoon wind fields,and constructed a typhoon database of 75 processes in the northern South China Sea using the coupled Advanced Circulation-Simulating Waves Nearshore(ADCIRC-SWAN)model.Then,a neural network with a Res-U-Net structure was trained using the typhoon database to forecast the typhoon processes in the validation dataset,and an excellent storm surge forecasting effect was achieved in the Pearl River Estuary region.The storm surge forecasting effect of stronger typhoons was improved by adding a branch structure and transfer learning.
Laboratory of Ocean Observation and Forecasting and Key Laboratory of Ocean Circulation and Waves,Institute of Oceanology,Chinese Academy of Sciences,Qingdao 266071,China
Laboratory for Ocean Dynamics and Climate,Qingdao Marine Science and Technology Center,Qingdao 266237,China
University of Chinese Academy of Sciences,Beijing 100049,China
Center for Ocean Mega-Science,Chinese Academy of Sciences,Qingdao 266071,China
万方数据
维普
