4.5 Article

A Possible Reconciliation between Eddy Covariance Fluxes and Surface Energy Balance Closure

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ATMOSPHERE
卷 13, 期 12, 页码 -

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MDPI
DOI: 10.3390/atmos13121965

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energy balance closure; eddy covariance; sensible heat flux; latent heat flux

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The surface energy balance equation, which distributes the available radiative energy between different heat fluxes, has been found to have a non-closure problem in previous measurements. This paper suggests additional terms that are based on thermodynamic considerations and could potentially explain the non-closure. Testing these corrections on observations from different sites improved the closure defect significantly.
At the surface of the earth, the available radiative energy R-n is distributed between the ground heat flux and the sensible and latent heat fluxes according to the surface energy balance (SEB) equation. In the past decades, most attempts to measure the individual terms of this equation have revealed a non-closure problem, regardless of the site of observation or period of the year. Today, no definitive answer has been provided to this question. In general, it is suspected that the sensible and latent heat fluxes (H and LvE, respectively) that are calculated with the eddy-covariance technique are underestimated. This paper suggests two additional terms that should be considered in the SEB equation, which are based on thermodynamic considerations. They are directly related to H and LvE and appear to be interesting candidates for explaining (at least in part) the non-closure of the SEB. The distribution of the correction between H and LvE varies as a function of the Bowen ratio B. The correction relative to H is dominant for values of B that are greater than 0.2 and represents more than 80% of the total correction for values greater than unity. The impact of these corrections on the SEB closure was tested on a large set of observations from 24 FLUXNET sites around the world with different vegetation types. The closure defect, which is about 17% in the original dataset, is reduced to about 3% with the proposed corrections.

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