Probability law of turbulent kinetic energy in the atmospheric surface layer

Mohammad Allouche, Gabriel G. Katul, Jose D. Fuentes, Elie Bou-Zeid

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

The probability density function p(k) of the turbulent kinetic energy k is investigated for diabatic atmospheric surface layer (ASL) flows. When the velocity components are near-Gaussian and their squared amplitudes are nearly independent, the resulting p(k) is shown to be γ-distributed with exponents that vary from 0.8 to 1.8. A nonlinear Langevin equation that preserves a γ-distributed p(k), but allows linear relaxation of k to its mean state, is proposed and tested using multiple ASL data sets. The three parameters needed to describe the drift and nonlinear diffusion terms can be determined from the ground shear stress and the mean velocity at height z. Using these model parameters, the Langevin equation reproduces the measured p(k) with minimal Kullback-Leibler divergence.

Original languageEnglish (US)
Article number074601
JournalPhysical Review Fluids
Volume6
Issue number7
DOIs
StatePublished - Jul 2021
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Computational Mechanics
  • Modeling and Simulation
  • Fluid Flow and Transfer Processes

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