This dataset supports the research article “Entrainment in Sheared Convective Boundary Layers: The Depth Dependence”, which employs a series of LES experiments to systematically examine the evolution of entrainment and related parameters under different boundary layer depths, geostrophic wind speeds, and free-atmosphere stratification. The dataset includes high-resolution LES experiment outputs (stored in the dataset folder) and the MATLAB plotting scripts (stored in the matfile folder). By updating the data paths in the MATLAB scripts, users can reproduce all figures presented in the article “Entrainment in Sheared Convective Boundary Layers: The Depth Dependence”. The experiment data include:(1) 15 simulations with zonal geostrophic wind Ug = 0, 5, 10, 20, and 30 m/s, with surface sensible heat flux Qs = 0.24 K m s⁻¹ and free-atmospheric capping inversion strength dθ/dz = 0.009 K m⁻¹ under different initial CBL depths (1000, 2000, and 3500 m).(2) 6 simulations with different initial CBL depths (1000, 2000, and 3500 m), constant surface heating Qs = 0.24 K m s⁻¹, and two free-atmospheric stratifications dθ/dz = 0.003 and 0.009 K m⁻¹. Content of each folder: · \dataset\statics: Mean and standard-deviation profiles of potential temperature (θ), u-wind, v-wind, w-wind, geopotential height (z), turbulent kinetic energy (TKE), and the spatial correlation coefficient between w and θ (wthr) for all experiments. · \dataset\statics_flux: Profiles of sensible heat flux (resolved + subgrid-scale). · \dataset\statics_fine: Profiles of the mean and count of positive and negative vertical velocity (w). · \dataset\entrainment: Statistical parameters describing the entrainment process. The meaning of each row can be referenced in the MATLAB scripts and in the article “Entrainment in Sheared Convective Boundary Layers: The Depth Dependence”. Users may refer to the article “Entrainment in Sheared Convective Boundary Layers: The Depth Dependence” as well as the MATLAB scripts provided in this dataset when analyzing or plotting the data.For any questions, please feel free to contact: zhanghl@idm.cn.