Global-ABLWind: a global atmospheric boundary layer wind speed profile dataset derived from Aeolus and surface ancillary information

Abstract. Accurate wind speed profiles within the atmospheric boundary layer (ABL) are essential for understanding atmospheric processes, climate change, and wind energy assessment. However, existing global ABL wind products lack either sufficient vertical resolution or accuracy, limiting their ability to resolve wind structures throughout the ABL. Here, we propose a physics-constrained machine learning framework designed to reconstruct continuous ABL wind speed profiles by integrating physically interpretable bias-correction mechanisms with dynamical constraints from Aeolus L2C observations. The proposed method enables the reconstruction of high-accuracy wind speed profiles at a vertical resolution of 100 m across the full ABL (0–2 km), overcoming the trade-off between accuracy and vertical resolution that characterizes existing products. Independent validation against RS observations demonstrates that the proposed method achieves high accuracy across all ABL heights. It has an overall correlation coefficient (R) of 0.92 and a root mean square error (RMSE) of 1.94 m s^-1, outperforming the original Aeolus L2C product (R = 0.90, RMSE = 2.23 m s^-1). Further comparisons at 100 m vertical resolution with the fifth generation ECMWF reanalysis (ERA5) and the power law method confirm the superior accuracy of XGB-Wind, especially in the near-surface layer (0–500 m). Applying the proposed framework to the full Aeolus mission period (from July 2020 to April 2023), we generate a global high-resolution ABL wind speed profile dataset, termed Global-ABLWind. This dataset provides 100 m vertical resolution wind profiles with enhanced accuracy, continuous ABL coverage, and reduced data gaps on a global scale. The dataset is freely available at https://doi.org/10.5281/zenodo.18286457 (Tong et al., 2026) and represents a valuable remote sensing resource for boundary-layer wind studies and wind-related environmental applications.