Low-level atmospheric turbulence dataset in China generated by combining radar wind profiler and radiosonde observations

Abstract. Low-level atmospheric turbulence plays a critical role in cloud dynamics and aviation safety. Nevertheless, height-resolved turbulence profiles remain scarce, largely owing to observational challenges. By leveraging collocated radar wind profiler (RWP) and radiosonde observations from 29 stations across China during 2023, a high-resolution dataset of low-level turbulence-related parameters are generated based on spectral width method. This dataset includes squared Brunt–Vaisala frequency (N²), turbulent dissipation rate (ε), and vertical eddy diffusivity (κ), inner scale (l₀), and buoyancy length scale (L_B), which are provided twice daily at 00 and 12 UTC with a vertical resolution of 120 m, covering altitudes from 0.12 km to 3.0 km above ground level. Spatial analysis reveals significant regional disparities in turbulence-related parameters across China, where ε, κ and L_B are higher in northwest and north China compared to south China, while N² and l₀ display an inverse spatial pattern. This contrasting geographical distributions suggest distinct atmospheric instability across China. In terms of seasonality, turbulence-related variables showed maxima during spring and summer. Vertical profiles characteristics show distinct altitudinal dependencies, ε, L_B and κ exhibit progressive attenuation with altitude, while N² and l₀ increase with height. Statistical analysis indicates that ε and κ follow log-normal distributions, whereas l₀ and L_B align with Gamma distributions. This dataset is publicly accessible https://doi.org/10.5281/zenodo.14959025 (Meng and Guo, 2025), which provides crucial insights into the fine-scale structural evolution of low-level turbulence. The preliminary findings based on the dataset have great implications for improving our understanding of pre-storm environment and conducting scientific planning and guiding of low-level flight routes in the emerging low-altitude economy in China.