Characterizing multilevel wind interactions via transfer entropy analysis: Evidence from vertical and horizontal components

Abstract Understanding how wind information propagates across atmospheric layers is fundamental to characterizing boundary‐layer turbulence and improving wind modeling. This study introduces transfer entropy (TE) to quantify the directional and scale‐dependent causal interactions between wind components across multi‐heights. The analysis reveals a consistent directional asymmetry, with stronger TE from lower to higher levels, indicating upward propagation of dynamical influence driven by surface‐generated turbulence. TE magnitudes were found to decrease with increasing vertical separation and temporal scale, reflecting the distance‐ and scale‐dependent attenuation of information flow. The horizontal component exhibits more pronounced coupling near the surface, whereas the vertical component shows enhanced interactions aloft, highlighting distinct shear‐ and buoyancy‐controlled mechanisms. In addition, diurnal variations further indicate intensified causal connectivity during daytime convective periods and suppression under nocturnal stability. Overall, these results demonstrate that TE provides a robust diagnostic framework for quantifying multilevel wind interactions and information transfer within the atmospheric boundary layer.