Abstract: In order to enhance the application of 10 m wind field data from the CMA Land Data Assimilation System (CLDAS) in Fujian region, this article analyzes the spatiotemporal distribution characteristics of errors between CLDAS wind field data and measured winds at corresponding stations using wind field data from 1713 automatic stations in Fujian Province from 2022 to 2023 and CLDAS wind field data. The results show that:The average correlation between the U and V components of CLDAS data is 0.96 and 0.97, respectively, which are weaker than observations.The errors in the CLDAS wind field are mainly caused by higher wind speeds, followed by larger errors in areas with complex terrain, land-sea boundaries, and offshore stations.In the hourly error distribution, significant systematic errors are prone to occur at 01:00 and 16:00.When the wind speed of the V component is 15–20 m/s during strong wind processes, there are a large number of underestimated samples, resulting in low wind speeds in the CLDAS wind field during strong wind processes. The CLDAS wind field data can better reflect the measured wind speeds of most stations in Fujian Province, but there is still room for correction for special terrains and strong wind processes.