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Notes: Summary We examine the notion that scalars are transported along their mean concentration gradients in the air space of the canopy. Recent observations and theory indicate that this concept is both inappropriate and misleading. Independent measurements of the fluxes and gradients of heat, water vapour and CO2 in a forest canopy show that counter-gradient fluxes are common. The intermittency of the transport processes and their large scale are seen as important reasons for this. Eddy-correlation and/or ecological techniques seem to be the only viable alternatives for measuring flux densities and source-sink strengths at present, but the logistical problems are formidable. For modelling exchange processes at leaf surfaces, hence source-sink distributions, analyses based on the gradient-diffusion concept may not be too much in error in as much as they employ essentially correct descriptions of transfer across leaf boundary-layers, if not in the canopy air space. An empirical description of transport in the latter may suffice. The utility of alternative models of scalar transport based on the nature of canopy turbulence is examined. Second-order closure models appear to have great pedagogic value in identifying the existence and relative importance of mechanisms for the production, transport and dissipation of scalar fluxes, but they are of limited use for prediction. Lagrangian models, though, appear to predict dispersion and profile development very well, provided the source distribution is known. However, the inverse problem of inferring source distributions from the concentration profiles remains a challenge.

Notes: Abstract An array of slender, vertical, cylindrical rods was used in a wind tunnel to simulate a plant canopy. Turbulence measurements were made with a cross hot wire, both inside and above the canopy. Measurements were also made inside the canopy when its top was covered by boards, leaving no space above the rods. This artificially confined canopy provided reference data. The results show an exponential wind profile and constant turbulence intensity, skewness and mixing length along the height of the (unconfined) canopy, the contribution of the eddies shed by the rods to the turbulence observed inside the canopy was small, but clearly apparent.

Notes: Abstract Fourth-order mixed moments of velocity and temperature fluctuations, measured within the atmospheric surface layer, are compared with results obtained by assuming the quasi-Gaussian approximation. Standard deviations of the products uw, uθ and wθ(u and w are the longitudinal and vertical velocity fluctuations; θ is the temperature fluctuation) are in good agreement with those obtained using the quasi-Gaussian assumption. Good agreement is also obtained between measured and Gaussian estimates of fourth-order moments including all three fluctuations u, w, θ Schwarz inequalities, commonly used in the clipping approximation in turbulence modelling, are found to provide bounds for third-order moments of w, θ that are too conservative. More reasonable, tighter, bounds for these moments are given by inequalities obtained by Lumley.

Notes: Abstract Atmospheric surface-layer measurements of terms in the equation for the streamwise heat flux confirm previous results in both laboratory and atmosphere that the temperature-pressure gradient correlation acts as a sink, approximately equal in magnitude to the production term. The measured viscous dissipation term is independent of stability and represents less than 10% of the production term over the range of experimental stability conditions. Models for the temperature-pressure gradient correlation are compared with the measurements.

Notes: Abstract Measurements of mean wind flow and turbulence parameters have been made over Cooper's Ridge, a 115 m high elongated ridge with low surface roughness. This paper describes measurements of the streamwise and vertical variations in the mean field for a variety of atmospheric stability conditions. In near-neutral conditions, the normalised speedup over the ridge compares well with measurements from Askervein (Mickleet al., 1988). The near-neutral results are also compared to an analytical flow model based on that of Huntet al. (1988a). Measured streamwise variations show less deceleration at the foot of the hill and slightly more acceleration at the crest of the hill than does the model. In non-neutral conditions, the speedup over the ridge reduces slightly in unstable conditions and increases by up to a factor of two in stable conditions. The model is modified to allow boundary-layer stability to change the upwind wind profile and the depths of the inner and middle layers. Such a modification is shown to describe the observations of speedup well in unstable and weakly stable conditions but to overestimate the speedup in moderate to strongly stable conditions. This disagreement can be traced to the model's overestimation of the upstream scaling velocity at the height of the middle layer through its use of a stable wind profile form which has greater shear than that of the observed profiles, in possible combination with the three-dimensionality of the ridge which would allow enhanced flow around, rather than over, the feature in more stable conditions.

Notes: Abstract The behaviour of odd-order structure functions of temperature in the atmospheric surface layer is consistent with the presence of a coherent structure characterised by temperature ramps. The use of a simple linear model for the ramp together with measurements of second-, third-, and fifth-order temperature structure functions yields estimates for the characteristic mean amplitude and repetition interval of ramps for stability conditions ranging from neutral to moderately unstable. Both amplitude and repetition interval compare favourably with values derived from observations of temperature traces obtained simultaneously at two heights in the surface layer.

Notes: Abstract Production, transport and dissipation terms in the temperature variance equation have been measured in the atmospheric surface layer. The transport term is, within the experimental uncertainty, negligible. The dissipation term, determined by assuming local isotropy, is approximately equal to production under near-neutral conditions. For moderately unstable conditions, the ratio of production to dissipation is 1.4. The resulting imbalance in the budget is attributed to the inequality between the three components of the dissipation term. The Kolmogorov constant for temperature is found to be about 0.8.

Notes: Abstract Production, transport and dissipation terms in the mean cube temperature equation have been evaluated from measurements in the atmospheric surface layer under moderately unstable conditions. The transport term, calculated by making use of the quasi-Gaussian approximation, is, on average, comparable with the production term. The molecular destruction or dissipation term is approximately equal to the production. Since the transport and production terms are of the same sign, the magnitude of the dissipation term is only about half that of the sum of transport and production terms. It is suggested that the imbalance is caused primarily by the assumption of isotropy in the analysis for the mean dissipation rate, 293-01, and the effects of various parameterizations for this quantity are discussed. The measured value of the inertial subrange co-spectral constant for the third moment of temperature is 1.17. It is subject to the uncertainty in the estimate of 293-02, but is unlikely to be significantly different from the spectral constant for the second moment. The ratio of dissipative time values for the thermal and velocity fields is 0.5 near neutral, reducing with increasing instability.

Notes: Abstract The relation between the turbulence Reynolds numberR λ and a Reynolds numberz* based on the friction velocity and height from the ground is established using direct measurements of the r.m.s. longitudinal velocity and turbulent energy dissipation in the atmospheric surface layer. Measurements of the relative magnitude of components of the turbulent kinetic energy budget in the stability range 0 〉z/L ≥ 0.4 indicate that local balance between production and dissipation is maintained. Approximate expressions, in terms of readily measured micrometeorological quantities, are proposed for the Taylor microscale λ and the Kolmogorov length scale η.

Notes: Abstract Turbulence data for the International Turbulence Comparison Experiment (ITCE) held at Conargo, N.S.W. (35° 18′ S., 145° 10′ E.) during October, 1976 are analysed. The standard deviation % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaaiikaiqado% hagaqbamaaCaaaleqabaGaaGOmaaaakiaacMcadaahaaWcbeqaaiaa% igdacaGGVaGaaGOmaaaaaaa!3B93!\[(s'^2 )^{1/2} \] and covariance % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWaa0aaaeaace% WG3bGbauaaceWGZbGbauaaaaaaaa!3809!\[\overline {w's'} \] measured by a number of instruments and instrument arrays have been compared to assess their field performance and calibration accuracy. Satisfactory agreement, i.e. typically 5% for % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaaiikamaana% aabaGabm4CayaafaWaaWbaaSqabeaacaaIYaaaaaaakiaacMcadaah% aaWcbeqaaiaaigdacaGGVaGaaGOmaaaaaaa!3BA4!\[(\overline {s'^2 } )^{1/2} \] (except in humidity) and of the order of 20% for % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaaiikaiqado% hagaqbamaaCaaaleqabaGaaGOmaaaakiaacMcadaahaaWcbeqaaiaa% igdacaGGVaGaaGOmaaaaaaa!3B93!\[(s'^2 )^{1/2} \], was achieved, but only after consideration of: (1) Instrumental response at high frequencies. (2) Flow distortion induced by instruments and supporting structures. (3) Spatial separation of instruments used for covariance measurements. (4) Statistical errors associated with single point measurements over a finite averaging time, and with lateral separation of two sensor arrays being compared.