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Latent and sensible heat flux predictions from a uniform pine forest using surface renewal and flux variance methods

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Abstract

A surface renewal model that links organized eddy motion to the latent and sensible heat fluxes is tested with eddy correlation measurements carried out in a 13m tall uniform Loblolly pine plantation in Duke Forest, Durham, North Carolina. The surface renewal model is based on the occurance of ramp-like patterns in the scalar concentration measurements. To extract such ramp-like patterns from Eulerian scalar concentration measurements, a newly proposed time-frequency filtering scheme is developed and tested. The time-domain filtering is carried out using compactly-supported orthonormal wavelets in conjunction with the “Universal Wavelet Thresholding” approach of Donoho and Johnstone, while the frequency filtering is carried out by a band-pass sine filter centered around the ramp-occurrence frequency as proposed by other studies. The method was separately tested for heat and water vapour with good agreement between eddy correlation flux measurements and model predictions. The usefulness of the flux-variance method to predict sensible and latent heat fluxes is also considered. Our measurements suggest that the simple flux-variance method reproduces the measured heat and momentum fluxes despite the fact that the variances were measured within the roughness sublayer and not in the surface layer. Central to the predictions of water vapour fluxes using the flux-variance approach is the similarity between heat and water vapour transport by the turbulent air flow. This assumption is also investigated for this uniform forest terrain.

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Authors and Affiliations

  1. School of the Environment, Duke University, 27708-0328, Durham, NC, USA

    Gabriel Katul, Cheng-I Hsieh, Ram Oren, David Ellsworth & Nathan Phillips

  2. Center for Hydrologic Sciences, Duke University, 27708, Durham, NC, USA

    Gabriel Katul

  3. Jet Propulsion Laboratory, California Institute of Technology, 91109, Pasadena, CA, USA

    Ram Oren

  4. Biosystems and Process Sciences Division, Brookhaven National Laboratory, 11973, Upton, NY, USA

    David Ellsworth

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  1. Gabriel Katul
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Katul, G., Hsieh, CI., Oren, R. et al. Latent and sensible heat flux predictions from a uniform pine forest using surface renewal and flux variance methods. Boundary-Layer Meteorol 80, 249–282 (1996). https://doi.org/10.1007/BF00119545

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