The possibility ofmeasuring heat and moisture fluxes using sonic anemometer data is investigated. Theoretical relations for the temperature variance and heat flux are derived. In the first part of this paper, these relations are verified by experimental data, involving a sonic anemometer, a fast thermocouple and a Lyman-cc hygrometer. In the second part we propose two simple procedures to estimate heat flux from sonic anemometer data. The first one requires a rough estimate of the Bowen ratio; for the second one the net radiation is needed. Using the last method, a good estimate of the moisture flux is also obtained.

Temperature measurement with a sonic anemometer and its application to heat and moisture fluxes

Atmospheric measurements from several field experiments have been combined to develop a better understanding of the turbulence structure of the stable atmospheric boundary layer. Fast response wind velocity and temperature data have been recorded using 3-dimensional sonic anemometers, placed at several heights (≈ 1 m to 4.3 m) above the ground. The measurements were used to calculate the standard deviations of the three components of the wind velocity, temperature, turbulent kinetic energy (TKE) dissipation and temperature variance dissipation. These data were normalized and plotted according to Monin–Obukhov similarity theory. The non-dimensional turbulence statistics have been computed, in part, to investigate the general applicability of the concept of z-less stratification for stable conditions. From the analysis of a data set covering almost five orders of magnitude in the stability parameter ζ = z/L (from near-neutral to very stable atmospheric stability), it was found that this concept does not hold in general. It was only for the non-dimensional standard deviation of temperature and the average dissipation rate of turbulent kinetic energy that zless behaviour has been found. The other variables studied here (non-dimensional standard deviations of u, v, and w velocity components and dissipation of temperature variance) did not follow the concept of z-less stratification for the very stable atmospheric boundary layer. An imbalance between production and dissipation of TKE was found for the near-neutral limit approached from the stable regime, which matches with previous results for near-neutral stability approached from the unstable regime.

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On Monin-Obukhov similarity in the stable atmospheric boundary layer

A global network of long-term carbon and water flux measurements has existed since the late 1990s. With its representative sampling of the terrestrial biosphere's climate and ecological spaces, this network is providing background information and direct measurements on how ecosystem metabolism responds to environmental and biological forcings and how they may be changing in a warmer world with more carbon dioxide. In this review, I explore how carbon and water fluxes of the world's ecosystem are responding to a suite of covarying environmental factors, like sunlight, temperature, soil moisture, and carbon dioxide. I also report on how coupled carbon and water fluxes are modulated by biological and ecological factors such as phenology and a suite of structural and functional properties. And, I investigate whether long-term trends in carbon and water fluxes are emerging in various ecological and climate spaces and the degree to which they may be driven by physical and biological forcings. As a growing number of time series extend up to 20 years in duration, we are at the verge of capturing ecosystem scale trends in the breathing of a changing biosphere. Consequently, flux measurements need to continue to report on future conditions and responses and assess the efficacy of natural climate solutions.

How eddy covariance flux measurements have contributed to our understanding of Global Change Biology

The von Karman constant . This is, thus, the largest, most comprehensive atmospheric data set ever used to evaluate the von Karman constant.

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Evaluations of the von Kármán constant in the atmospheric surface layer

(Received 26 May 1993; accepted 8 March 1994) Orthonormal wavelet expansions are applied to atmospheric surface layer velocity and temperature measurements above a uniform bare soil ‘ surface that exhibit a long inertial subrange energy spectrum. In order to investigate intermittency effects on Kolmogorov’ s theory, a direct relation between the &h-order structure function and the wavelet coefficients is derived. This relation is used to examine deviations from the classical Kolmogorov theory for velocity and temperature in the inertial subrange. The local nature of the orthonormal wavelet transform in physical space aided the identification of events directly contributing to intermittency buildup at inertial subrange scales. These events occur at edges of large eddies and contaminate the Kolmogorov inertial subrange scaling. By suppressing these events, the statistical structure of the inertial subrange for the velocity and temperature, as described by Kolmogorov’ s theory, is recovered. The suppression of intermittency on the nth-order structure function is carried out via a conditional wavelet sampling scheme. The conditioned wavelet statistics reproduced the Kolmogorov scaling (up to n = 6) in the inertial subrange and result in a zero intermittency factor. The conditional wavelet statistics for the mixed velocity temperature structure functions are also presented. It was found that the conditional wavelet statistics for these mixed moments result in a thermal intermittency parameter consistent with other laboratory and field measurements. The relationship between Kolmogorov’ s theory and near-Gaussian statistics for velocity and temperature gradients is also considered. 1. INTRODUCTION From Kolmogorov’ theory (K41), the ensemble average of the nth order velocity difference (Auij between two points separated by spatial distance (Y), in the inertial sub- range, can be computed using (~hz#)=K,((~))~‘ ~r~‘ ~, (1) where E is the turbulent energy dissipation rate

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J C Wyngaard

Papers

Cup, Propeller, Vane, and Sonic Anemometers in Turbulence Research