@article{8a08f4f954444e1ebf4f3aef5e5442b6,

title = "Probability law of turbulent kinetic energy in the atmospheric surface layer",

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.",

author = "Mohammad Allouche and Katul, {Gabriel G.} and Fuentes, {Jose D.} and Elie Bou-Zeid",

note = "Funding Information: M.A. and E.B.Z. are supported by the Cooperative Institute for Modeling the Earth System at Princeton University under Award No. NA18OAR4320123 from the National Oceanic and Atmospheric Administration, and by the Andlinger Center for Energy and the Environment at Princeton University. G.K. acknowledges support from the U.S. National Science Foundation (Grants No. NSF-AGS-1644382, NSF-AGS-2028633 and No. NSF-IOS-1754893), as well as Princeton University{\textquoteright}s Metropolis Project for partial support during a sabbatical leave at Princeton in 2020. J.D.F. acknowledges the support provided by the National Science Foundation to complete the PHOXMELT field studies (Grant No. PLR-1417914) to collect the data. We thank K. Pratt, P. Shepson, Sham Thanekar, and J.Ruiz-Plancart for their contributions to obtaining the turbulence data set at Utqiagvik, Alaska during
2016 field campaign. Publisher Copyright: {\textcopyright} 2021 American Physical Society.",

year = "2021",

month = jul,

doi = "10.1103/PhysRevFluids.6.074601",

language = "English (US)",

volume = "6",

journal = "Physical Review Fluids",

issn = "2469-990X",

publisher = "American Physical Society",

number = "7",

}