Accurate forecasts of surface winds plays an important role in offshore wind energy development.This study uses the ERA5 reanalysis data during 2019‒2021 to evaluate the EC fine-grid 10 m winds forecasts in Jiangsu offshore area.It is found that the EC fine-grid 10 m wind speed forecasts perform best in accuracy for wind scale 4,with a 24 hour(48 hour)forecasting RMSE of 2.28 m/s(2.34 m/s).As wind scale increases,the wind speed forecasting accuracy decreases significantly,and the 24 hour(48 hour)forecasting RMSE for wind scales 5～11 increases from 2.39 m/s(2.58 m/s)to 8.67 m/s(8.51 m/s).In addition,significant spatial differentiation exists in the 10 m wind speed forecast errors,and the errors grow along with the increase of offshore distance.Based on the Resnet50 model,a correction method for surface wind forecasts in Jiangsu offshore area is constructed.The independence test using the forecasting data in 2022 shows that the correction method significantly improves the accuracy of the EC 24-hour and 48-hour 10 m wind speed forecasts,with a 24 hour(48 hour)forecasting RMSE of 1.48 m/s(1.65 m/s),which is 45%(40%)lower than the original EC forecasts.For wind scales 3～10,the 24-hour and 48-hour corrected forecasting RMSE are 1.13 m/s to 6.67 m/s and 1.21 m/s to 5.68 m/s,which is also significantly lower than the original EC forecasts(2.33 m/s to 7.65 m/s and 2.58 m/s to 9.97 m/s).
关键词
深度学习/海面风场/订正/Resnet50
Key words
deep learning/sea surface winds/correction/Resnet50
维普
万方数据