Prediction of Sea Surface Wind Speed in China's Offshore Areas Based on Weighted Loss Function
QU Hongyu
HU Haichuan
QIAN Chuanhai
HUANG Bin
Abstract：Sea surface wind speed forecasts based on numerical models often exhibit deviations.Although statistical models based on numerical models can reduce the deviation to a certain extent,their performance in predicting strong winds remains suboptimal due to the scarcity of strong wind samples.This study systematically evaluated the 24-hour sea surface wind speed forecasts from the European Centre for Medium-Range Weather Forecasts(ECMWF)and employed the XGBoost model to develop a correction model tailored for China's offshore areas.This model not only demonstrated good overall forecasting accuracy,but also significantly enhanced the prediction of strong winds through the use of a weighted loss function during training.The model was independently tested using observational data from 14 buoys in China's offshore waters from January 2022 to January 2023.The average error and root mean squared error of the model were 0.11 m s-1 and 1.75 m s-1,respectively.The forecast accuracy of the model for wind speeds classified as levels 7 to 9 was significantly improved compared to that of the ECMWF,with root mean squared errors reduced by 15%,25%,and 24%,respectively.Furthermore,when applied to grid points not included in the training,the model continued to provide more accurate forecasts than the ECMWF.This model is easy to operate and use and can provide reference information for sea surface wind speed forecasting,especially strong wind forecasting,in China's coastal waters.
Keywords：sea surface wind speedforecast correctionweighted loss function
Publication Date：2024-12-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：12( 931-942 )