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Active Turbulence and Scalar Transport near the Forest–Atmosphere Interface

Gabriel G. KatulSchool of the Environment and Center for Hydrologic Science, Duke University, Durham, North Carolina

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Chris D. GeronUnited States Environmental Protection Agency, Research Triangle Park, North Carolina

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Cheng-I. HsiehSchool of the Environment, Duke University, Durham, North Carolina

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Brani VidakovicInstitute of Statistics and Decision Sciences, Duke University, Durham, North Carolina

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Alex B. GuentherAtmospheric Chemistry Division, National Center for Atmospheric Research, Boulder, Colorado

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Print Publication:
01 Dec 1998
DOI:
https://doi.org/10.1175/1520-0450(1998)037<1533:ATASTN>2.0.CO;2
Page(s):
1533–1546
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Abstract

Turbulent velocity, temperature, water vapor concentration, and other scalars were measured at the canopy–atmosphere 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 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 to be the main energy contributor to vertical velocity (w) spectral energy (Ew), is also the main scalar flux–transporting eddy motion. Predictions using ML of the peak Ew frequency are in excellent agreement with measured wavelet cospectral peaks of vertical fluxes (Kh = 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 〈U〉/h and integral timescale, where 〈U〉 is the mean horizontal velocity at height z = 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.

Corresponding author address: Gabriel G. Katul, School of the Environment, Box 902328, Duke University, Durham, NC 27708-0328.

gaby@duke.edu

Abstract

Turbulent velocity, temperature, water vapor concentration, and other scalars were measured at the canopy–atmosphere 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 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 to be the main energy contributor to vertical velocity (w) spectral energy (Ew), is also the main scalar flux–transporting eddy motion. Predictions using ML of the peak Ew frequency are in excellent agreement with measured wavelet cospectral peaks of vertical fluxes (Kh = 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 〈U〉/h and integral timescale, where 〈U〉 is the mean horizontal velocity at height z = 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.

Corresponding author address: Gabriel G. Katul, School of the Environment, Box 902328, Duke University, Durham, NC 27708-0328.

gaby@duke.edu

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