Fusion and Test of Wind Data from a China–France Oceanography Satellite Scatterometer

Single-sea-surface wind data have problems such as observation scarcity, uneven distribution, and difficulty covering the earth. Multisource wind data are fused to achieve grid continuity, effectively covering the sea surface and improving operational accuracy. In order to promote the improvement of the fusion effect of multi-source sea surface wind field data mainly based on China’s independently controllable scatterometer wind field data, four types of sea surface wind data were collected herein: buoy, ship report, ASCAT (Advanced Scatterometer), and CSCAT (China–France Oceanography satellite scatterometer) wind data, and relevant fusion experiments and verifications were conducted. The quality of the CSCAT wind data was compared and verified, and then the time–space weighted interpolation and optimal interpolation methods were used. Using CSCAT data as the core and supplementing it with other wind data, daily average global wind data fusion and three-hour regional wind data fusion were performed. Then, the quality of the fusion wind was inspected. The results show that the accuracy and stability of the CSCAT data are slightly lower than those of the ASCAT data. After fusing the two data types, the wind field can meet certain operational accuracy requirements. The optimal interpolation method is more suitable for the Pacific Ocean, while the spatio-temporal weighted interpolation method is more suitable for the Indian Ocean. In the Atlantic Ocean, the effects of both methods are similar. The 3-hour regional wind field quality obtained through the integrated spatio-temporal weighted and optimal interpolation methods is higher than that of the daily averaged global wind field. This method is simple to implement, and the fusion data are reliable. In particular, in sparsely observed areas, they can provide a reference for quickly obtaining the high-resolution standardized gridded wind fields over the sea.