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New Transfer Functions for Correcting Turbulent Water Vapour Fluxes

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Abstract

We address the problem of the high-frequency correction of water vapour fluxes measured by eddy covariance with a closed-path infrared gas analyser (IRGA). Different transfer functions are compared and evaluated at a forested (Vielsalm, Belgium) and an agricultural (Lonzée, Belgium) site. Classical functions, usually applied to correct CO2 fluxes (Gaussian, Lorentzian), are found to be unsuited to water vapour cospectral corrections, being characterised by too sharp a decrease at high frequency. Two other functions characterised by a lower decreasing slope are found to better fit experimental transfer functions. They were calibrated and validated on experimental transfer functions and their dependency on air humidity is parameterised. On this basis, new correction coefficients are estimated. The coefficients are found to be larger than those based on the classical functions, even when the dependency of the latter on air humidity is taken into account. The difference amounts to 10% at the forested site and to 5% larger at the crop site. The study highlights the necessity of characterising the water transfer function shape and taking it into account in the correction factor at each site equipped with a closed path IRGA.

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Abbreviations

RMSD:

Root-mean-square differences

a j :

Parameter of regression for model j

b j :

Parameter of regression for model j

C :

Cospectrum

C ref :

Cospectrum of reference

C ws :

Cospectral density of two variables w and s

\({C_{ws}^{\rm exp}}\) :

Experimental cospectral density of two variables w and s

C wT :

STF cospectral density

\({C_{wT}^{\rm exp}}\) :

Experimental STF cospectral density

c :

CO2 concentration

D s :

Vapour pressure deficit

d j :

Parameter of regression for model j

f :

Frequency

f o :

Half-power frequency

f o,s, j :

Half-power frequency for a scalar s and for model j

g j :

Parameter of regression for model j

h :

Water vapour concentration

i j :

Parameter of regression for model j

j :

Number of models

k j :

Parameter of regression for model j

L self :

Inductance

N T,exp :

Normalisation factor of the measured STF cospectrum

N s :

Normalisation factors of the cospectrum of variables w and s

N s,exp :

Normalisation factors of the measured cospectrum of variables w and s

s :

Scalar

x j :

Exponent-parameter of model j

w :

Vertical wind speed

w′:

Fluctuation of the vertical wind speed

δ s :

Transfer function of the scalar s

\({\delta_s^{\rm exp}}\) :

Experimental transfer function of the scalar s

ε s :

Correction factor for the flux of scalar s

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Authors and Affiliations

  1. Gembloux Agro-Bio Tech, University of Liege, Unité de Physique des Biosystèmes, 8 Avenue de la Faculté, 5030, Gembloux, Belgium

    A. De Ligne, B. Heinesch & M. Aubinet

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  1. A. De Ligne
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  2. B. Heinesch
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  3. M. Aubinet
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Correspondence to A. De Ligne.

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De Ligne, A., Heinesch, B. & Aubinet, M. New Transfer Functions for Correcting Turbulent Water Vapour Fluxes. Boundary-Layer Meteorol 137, 205–221 (2010). https://doi.org/10.1007/s10546-010-9525-9

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  • DOI: https://doi.org/10.1007/s10546-010-9525-9

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