AUTHOR=Pang Cong , Song Tao , Sun Handan , Li Xin , Xu Danya 

TITLE=A deep learning method for bias correction of wind field in the South China Sea

JOURNAL=Frontiers in Marine Science

VOLUME=Volume 11 - 2024

YEAR=2025

URL=https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2024.1429057

DOI=10.3389/fmars.2024.1429057

ISSN=2296-7745

ABSTRACT=To address the systematic bias in the Global Forecast System (GFS) wind field forecasts, we utilize deep learning techniques. The developed MU - Diffusion framework, based on a diffusion model and MultiUnet (a multitasking Unet model), establishes a nonlinear relationship between GFS and the fifth-generation EC atmospheric reanalysis (ERA5) data. Focusing on the South China Sea region, this method corrects both wind speed and direction simultaneously. Using 2022 GFS data, we achieved average enhancements of 42% in wind speed and 38.3% in wind direction compared to the initial GFS data. Tests in typhoon conditions also confirm the excellent performance of this architecture.