Nonlinear Causal Evidence for Turbulence–Particle Growth Coupling: Insights from a Subtropical Freezing Rain Event

Understanding and estimating the impact of atmospheric turbulence on the growth of precipitation particles in freezing weather can help improve the prediction of freezing rain precipitation. In this study, the turbulent kinetic energy dissipation rate (ε) during a freezing weather event was retrieved using the power spectral analysis method, based on observational data from a Ka-band millimeter-wave cloud radar, radiosondes, and ground automatic weather stations, and the influence of atmospheric turbulence on the growth of freezing rain precipitation particles was investigated using nonlinear causal methods such as transfer entropy (TE), convergent cross-mapping (CCM), the phase-randomized surrogate test, and partial CCM. Causality tests confirmed a significant bidirectional causal relationship between ε and Ze, with the information transfer from ε to Ze systematically dominating throughout the entire height range of precipitation particles. The bidirectional original ρ was far higher than the 99% quantile of the surrogate distribution, and the coupling was enhanced after removing the influence of temperature and humidity, indicating that it was independent of the thermodynamic covariant background. The causal intensity in the ice crystal growth zone above 6 km was approximately 3 times the average in the liquid zone, indicating that atmospheric turbulence is one of the key factors driving the growth of precipitation particles in freezing weather and that the effect is concentrated in the dominant layer of ice crystals. This finding provides a practical basis for improving the parameterization scheme and numerical prediction of the precipitation particle microphysical processes in freezing weather.