EOF‐Based Bias Correction of Near‐Surface Wind Speed Over China Reveals Stronger Future Trends and Variability

Abstract As near‐surface wind speed (NSWS) largely controls wind power generation, robust projection is vital to wind energy planning and broader sustainability goals. However, the predictive skill of climate models for NSWS remains uncertain. Analysis of Coupled Model Intercomparison Project Phase 6 simulations shows that the models reproduce the mean NSWS over China reasonably well but substantially underestimate the observed long‐term trend and variability. Given these large biases, bias correction is essential for obtaining more reliable NSWS projections. We correct this bias using an Empirical Orthogonal Function approach to isolate the dominant spatial modes of NSWS variability. The corrected projections exhibit amplified future trends and increased variability of NSWS over China compared with the original model output, with the strongest changes emerging under higher greenhouse gas emissions. Our results indicated that unadjusted models may understate the magnitude of future NSWS changes. This study provides a more reliable reference for future evolution of NSWS.