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March 18, 2026Quarterly Journal of the Royal Meteorological Society0 citations

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

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ZSZ. R. ShuHDH. C. DengYYY. L. Yang

Key Points

  • This study aims to quantify how wind information transfers between different atmospheric layers using transfer entropy.
  • Introduced transfer entropy to analyze directional interactions between wind components.
  • Performed analysis at multiple heights to capture layer-dependent relationships.
  • Investigated the effects of temporal scale and vertical separation on information flow.
  • Found stronger transfer entropy from lower to higher levels, indicating upward influence from surface turbulence.
  • Determined that transfer entropy decreases with greater vertical separation and longer time scales.
  • Observed pronounced coupling in horizontal components near the surface and increased vertical interactions aloft.

Abstract

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.

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Cite This Study

Shu et al. (2026) studied this question.

synapsesocial.com/papers/69ba44654e9516ffd37a612chttps://doi.org/10.1002/qj.70146
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