Some Errors in the Measurement of Reynolds Stress

179

For the 1968 Kansas atmospheric surface-layer experiment, a supplementary analysis is made of the evaluation procedure. Available data on the ratio of wind speeds measured on separate booms show a variation with wind direction which is too large for an open mast. Actually the Kansas mast appears to have carried a bulky array of apparatus at the sonic anemometer levels. It is shown that the air flow interference caused by this obstacle can be satisfactorily estimated by way of potential flow calculations. From these it follows that the sonic anemometer measurements probably have undervalued the free-flow eddy stress by 20% to 30%, which implies that the simultaneous drag plate measurements of stress were generally correct. Also the overestimation of the mean wind speed by the Kansas cup anemometer is found to have been 6% rather than 10%. Some Kansas evaluation results are amended accordingly. The von Karma, constant is found to be 0.41 rather than 0.35, and the near-adiabatic eddy diffusivity ratio K,IK, becomes 1.0 rather than 1.3. The flux-gradient relations (Businger et al., 1971) after similar revision no longer differ significantly from those obtained elsewhere.

Section: Upflow At the Sonic Anemometer Locationmentioning

confidence: 99%

Section: Of Thementioning

confidence: 99%

A revaluation of the Kansas mast influence on measurements of stress and cup anemometer overspeeding

Wieringa

1980

179

“…The one major exception to this generality was the estimated value of the G cross-correlation for each anemometer. Such cross-correlations are known to be affected by as much as lo-12% per degree of vertical misalignment (e.g., Kaimal and Haugen, 1969;Dyer ef al., 1970), an error estimate which was confirmed by comparisons of rotated and non-rotated data in the present case. Thus rotation by the mean elevation angle to ensure that C became identically zero was carried out for all & results presented here.…”

Section: Mean Wind Speed and Directionmentioning

confidence: 99%

Structure of mean winds and turbulence in the planetary boundary layer over rural terrain

Teunissen

1980

A detailed analysis has been carried out of the temporal and spatial structure of mean winds and turbulence in the neutrally-stable planetary boundary layer over typically rural terrain. The data were obtained from a horizontal array of tower-mounted propeller anemometers (z = 11 m) during a five-hour period for which the mean wind direction was virtually perpendicular to the main span of the array. Various turbulence characteristics have been obtained for all three components of velocity and have been compared with idealized models for such a flow and with some of the other available atmospheric results.Considerable tower-to-tower and block-to-block variability has been observed in many of the measured results, particularly in those for the horizontal-component integral scales. Surface shear stress, roughness length and turbulence intensities were in good agreement with expected values for such a site. Power spectra for all components displayed significantly more energy at middle and lower frequencies than that observed by Kaimal et al. (1972) over flat, relatively featureless terrain. This is felt to be a result of the generally rougher gross features of the terrain in the present case and has led to the development of a modified version of the Kaimalspectral model which fits the observed data better than either the original Kaimal model or the von K&m&n model. It is suggested that it may in future be possible to represent power spectra over a wide range of terrain types by using such a modified spectral model.Integral scales of turbulence were calculated by three different techniques and in most cases displayed a strong dependence on the technique used. Averaged values of scale showed reasonable agreement with most of the available atmospheric data and with the values suggested by ESDU (1975). The anticipated elongation of turbulent eddies in the longitudinal direction was confirmed for all three velocity components, although it was found to be not as large as some other observations. Nomenclature ai, h k '4 KlO I:' n n, Fig Ri CAY, 7) {i (7) &j(O) Si (n) spectral equation constants -see Section 3.5 non-dimensional frequency = nz/ fi wave number = n/ 0 wave number at which peak of i-component power spectrum occurs surface drag coefficient (z = 10 m) = (u*/ ii,,)' integral scale of i-component for separation in j-direction, calculated by correlation integral technique (Section 3.7) integral scale of i-component for separation in j-direction, calculated by exponential fit technique (Section 3.7) integral scale of i-component for separation in j-direction, calculated by spectra1 fit technique (Section 3.7) frequency filter cut-off frequency (-3 dB) gradient Richardson number normalized time-delayed cross-correlation of i-components for separations in lateral direction [e.g. d, (Ay, 7) = ~/(cr,,~,)] normalized autocorrelation of i-component [e.g. g,,(7) = u(t) u(t + 7)/m:] Reynolds stress coefficient for i-and j-components [e.g. d,,(O) =G/((T,(~,)] power spectral density of i-component time Boundary-Layer Meteoro...

“…Measurement accuracy is inherently limited by the accuracy to which the lengths of the acoustic paths, the direction cosines of the path geometry, and the acoustic transit times are measured (e.g. Kaimal and Haugen 1969). Finally the sonic array, composed of the acoustic transducers and their support structure, can itself modify the flow that is being measured.…”

Section: Introductionmentioning

confidence: 99%

Correction of a Non-orthogonal, Three-Component Sonic Anemometer for Flow Distortion by Transducer Shadowing

Horst

Semmer

Maclean

2015

We propose that flow distortion within a non-orthogonal CSAT3 sonic anemometer is primarily due to transducer shadowing, which is caused by wakes in the lee of the acoustic transducers impinging on their measurement paths. The dependence of transducer shadowing on sonic path geometry, wind direction and atmospheric stability is investigated with simulations that use surface-layer data from the Horizontal Array Turbulence Study (HATS) field program and canopy roughness-sublayer data from the CHATS (Canopy HATS) field program. We demonstrate the efficacy of correcting the CSAT3 for transducer shadowing with measurements of its flow distortion in the NCAR wind tunnel, combined with 6 months of data collected in the atmospheric surface layer with adjacent CSAT3 and orthogonal ATI-K sonic anemometers at the NCAR Marshall field site. CSAT3 and ATI-K measurements of the variance of vertical velocity σ 2 w and the vertical flux of sonic temperature agree within 1 % after correction of both sonics for transducer shadowing. Both the simulations of transducer shadowing and the comparison of CSAT3 and ATI-K field data suggest a simple, approximate correction of CSAT3 surface-layer scalar fluxes with an increase on the order of 4-5 %, independent of wind direction and atmospheric stability. We also find that σ w /u * (where u * is the friction velocity) and r uw (the correlation coefficient) calculated with corrected CSAT3 data are insensitive to wind direction and agree closely with known values of these dimensionless variables for neutral stratification, which is evidence for the efficacy of the correction of the horizontal wind components for transducer shadowing as well.