Spectra and correlation functions of surface layer atmospheric turbulence in unstable thermal stratification

Kader, B. A.; Yaglom, A. M.

doi:10.1007/978-94-015-7904-9_24

Cited by 72 publications

(90 citation statements)

References 5 publications

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“…Note that for Kh Ͼ 2, an approximate Ϫ7/3 power law (regression slope ϭ Ϫ2.08), typically observed in the inertial subrange (fine scales) of surface layer turbulence, is present for nearly three decades. For Kh Ͻ 1, an approximate Ϫ1 power law is apparent at z ϭ h, which is in agreement with many surface layer experiments (Kader and Yaglom 1991). The transition in power laws from Ϫ1 to Ϫ7/3 occurs at about Kh ϭ 2, which is also the ''active'' scale for scalar and momentum transport, as evidenced by the energy cospectra in Fig.…”

Section: Fluxessupporting

confidence: 89%

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Active Turbulence and Scalar Transport near the Forest–Atmosphere Interface

Katul¹,

Geron²,

Hsieh³

et al. 1998

J. Appl. Meteor.

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Turbulent velocity, temperature, water vapor concentration, and other scalars were measured at the canopyatmosphere interface of a 13-14-m-tall uniform pine forest and a 33-m-tall nonuniform hardwood forest. These measurements were used to investigate whether the mixing layer (ML) analogy of Raupach et al. predicts eddy sizes and flow characteristics responsible for much of the turbulent stresses and vertical scalar fluxes. For this purpose, wavelet spectra and cospectra were derived and analyzed. It was found that the ML analogy predicts well vertical velocity variances and integral timescales. However, at low wavenumbers, inactive eddy motion signatures were present in horizontal velocity wavelet spectra, suggesting that ML may not be suitable for scaling horizontal velocity perturbations. Momentum and scalar wavelet cospectra of turbulent stresses and scalar fluxes demonstrated that active eddy motion, which was shown by Raupach et al. to be the main energy contributor to vertical velocity (w) spectral energy (E w ), is also the main scalar flux-transporting eddy motion. Predictions using ML of the peak E w frequency are in excellent agreement with measured wavelet cospectral peaks of vertical fluxes (Kh ϭ 1.5, where K is wavenumber and h is canopy height). Using Lorentz wavelet thresholding of vertical velocity time series, wavelet coefficients associated with active turbulence were identified. It was demonstrated that detection frequency of organized structures, as predicted from Lorentz wavelet filtering, relate to the arrival frequency ͗U͘/h and integral timescale, where ͗U ͘ is the mean horizontal velocity at height z ϭ h. The newly proposed wavelet thresholding approach, which relies on a ''global'' wavelet threshold formulation for the energy in w, provides simultaneous energy-covariance-preserving characterization of ''active'' turbulence at the canopy-atmosphere interface.

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Section: Fluxessupporting

confidence: 89%

“…Evidence of the Ϫ1 power law in the scalar time series in Fig. 4c also suggests that inactive eddy motion contributes to scalar variance (see Kader and Yaglom 1991).…”

Section: ) Wavelet Energy and Power Spectramentioning

confidence: 79%

Active Turbulence and Scalar Transport near the Forest–Atmosphere Interface

Katul¹,

Geron²,

Hsieh³

et al. 1998

J. Appl. Meteor.

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“…264) and Kader and Yaglom (1991), the occurrence of the -1 power law at the production scales can be derived from dimensional arguments by noting that the spectrum of velocity for the small wavenumber range has units of (m s-1 )2 m. Therefore, the spectrum of the vertical velocity E33(K) for large scales, based on Monin-Obukhov (1954) similarity theory with velocity and length dimensions scaled by u. and z, results in --…”

Section: C(3)k-5/3 a 33)mentioning

confidence: 99%

“…A recent study by Kader and Yaglom (1991) based on the work of Zilitinkevich (1971), Betchov and Yaglom (1971), and Kader and Yaglom (1984) suggests that the ASL is comprised of three sublayers that have a self preserving turbulence structure. These sublayers are 1) forced convective or dynamic sublayer, 2) dynamic convective, and 3) free convective.…”

Section: Introductionmentioning

confidence: 99%

“…The dynamic convective sublayer occurs at moderate values of ( = -z/L and all three dimensional variables are important. The distinction between these sublayers allows for separate universal formulation of the Fourier power spectrum and co-spectrum (Eij) of the velocity components (i = 1,2, 3; j = 1,2, 3) for wavenumbers (K) that are dynamically important and much smaller than the Kolmogorov dissipation scales (Kader and Yaglom, 1991). For the vertical velocity fluctuations w r (i = 3, j = 3), the Fourier power spectrum E33(K) within the various sublayers has a universal power-law behavior given by (Kader and Yaglom, 1991): t~(1) 1 (-5/3 E33( 1[ ~) : "~33 .,1 for b~ ) < 1( <[ a~13 ) For z << L, (2) ,o, 331"2(1)/i"-111 for d~13 ) < I6 < b~13 ) /~33(i(]----C~i)t( -5/3 forb~ 2) < I~" < a~ 2) ~(2) ~,,--5/3…”

Section: Introductionmentioning

confidence: 99%

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The spatial structure of turbulence at production wavenumbers using orthonormal wavelets

Katul

Parlange

1995

Boundary-Layer Meteorol

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Abstract. Orthonormal wavelet expansions are applied to surface-layer measurements of vertical wind speed under various atmospheric stability conditions. The orthonormal wavelet transform allows for the unfolding of these measurements into space and scale simultaneously to reveal the large intermittent behavior in space for the turbulent production wavenumbers. Both Fourier and wavelet power spectra indicated the existence of a -1 power law for the vertical velocity measurements at the production wavenumbers. The -1 power law in the turbulent production range was derived from surface-layer similarity theory. A dimensionless skewness structure function is applied to the wavelet decomposed vertical velocity field to trace the destruction of the shear-or buoyancy-induced anisotropy under various stability conditions. The structure skewness function revealed shear-or buoyancy-induced eddy asymmetry dependence on stability at each scale within the -1 power-law wavenumber range with more isotropy during propagation from smaller to larger wavenumbers. The asymmetry of these events at the turbulent production wavenumbers appeared very localized in space, as well as in scale, and could be described with a simple eddy-overturning model. It is demonstrated that the wavelet transform is suitable for such analysis.

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Effect of Migrating Bed Topography on Flow Turbulence: Implications for Modelling Sediment Transport

Singh

Foufoula‐Georgiou

2013

Coherent Flow Structures at Earth's Surface

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Spectra and correlation functions of surface layer atmospheric turbulence in unstable thermal stratification

Cited by 72 publications

References 5 publications

Active Turbulence and Scalar Transport near the Forest–Atmosphere Interface

Active Turbulence and Scalar Transport near the Forest–Atmosphere Interface

The spatial structure of turbulence at production wavenumbers using orthonormal wavelets

Effect of Migrating Bed Topography on Flow Turbulence: Implications for Modelling Sediment Transport

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