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<p>Atmospheric boundary layer (ABL) turbulence is often characterized by large time-scale fluctuations, such as diurnal and seasonal variations, which may affect the estimation of the statistical properties of wind fields and related quantities. Superstatistical approaches exploit the scale separation between slow and fast dynamical processes to model the resulting velocity fluctuations. All the results support the validity of a log-normal superstatistical description of near ground ABL turbulence, reproducing both intermittency features and the main scaling properties observed in the data, in a range of temporal scales enclosed in the interval 15 minutes up to 1 day. The probability density functions of wind velocity fluctuations are found to be in good agreement with the predictions of the superstatistical model, consistently with results reported for laboratory flows and microscale atmospheric turbulence. Overall, the combination of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise, and superstatistics offers a robust framework for investigating multiscale and non-stationary wind fluctuations in the atmospheric boundary layer.</p>

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Scale-dependent dynamics and intermittency of atmospheric boundary-layer wind fluctuations

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月22日

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  • Christian N. Gencarelli,
  • Francesco Carbone

摘要

Atmospheric boundary layer (ABL) turbulence is often characterized by large time-scale fluctuations, such as diurnal and seasonal variations, which may affect the estimation of the statistical properties of wind fields and related quantities. Superstatistical approaches exploit the scale separation between slow and fast dynamical processes to model the resulting velocity fluctuations. All the results support the validity of a log-normal superstatistical description of near ground ABL turbulence, reproducing both intermittency features and the main scaling properties observed in the data, in a range of temporal scales enclosed in the interval 15 minutes up to 1 day. The probability density functions of wind velocity fluctuations are found to be in good agreement with the predictions of the superstatistical model, consistently with results reported for laboratory flows and microscale atmospheric turbulence. Overall, the combination of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise, and superstatistics offers a robust framework for investigating multiscale and non-stationary wind fluctuations in the atmospheric boundary layer.