The characteristics of turbulent velocity components in the surface layer under convective conditions

Panofsky, H. A.; Tennekes, H.; Lenschow, Donald H.; Wyngaard, J. C.

doi:10.1007/bf02186086

Cited by 547 publications

(358 citation statements)

References 10 publications

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“…Krishnan and Kunhikrishnan 2002;Ramana et al 2004). Panofsky et al (1977) showed that z and u * are not the appropriate scaling variables for the horizontal velocity fluctuations in the convective surface layer. Indeed, due to low-frequency thermal eddies "sweeping" the bottom of the ABL (Banta 1985;Khanna and Brasseur 1997), the boundary-layer depth h (which constrains the size of these large eddies) and the convective velocity scale w * should be two relevant scaling variables.…”

Section: Dimensionless Standard Deviations Of Wind Velocity Componentsmentioning

confidence: 99%

Similarity Scaling Over a Steep Alpine Slope

Nadeau

Pardyjak

Higgins

et al. 2012

Boundary-Layer Meteorol

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In this study, we investigate the validity of similarity scaling over a steep mountain slope (30-41 • ). The results are based on eddy-covariance data collected during the Slope Experiment near La Fouly (SELF-2010); a field campaign conducted in a narrow valley of the Swiss Alps during summer 2010. The turbulent fluxes of heat and momentum are found to vary significantly with height in the first few metres above the inclined surface. These variations exceed by an order of magnitude the well-accepted maximum 10 % required for the applicability of Monin-Obukhov similarity theory in the surface layer. This could be due to a surface layer that is too thin to be detected or to the presence of advective fluxes. It is shown that local scaling can be a useful tool in these cases when surface-layer theory breaks down. Under convective conditions and after removing the effects of self-correlation, the normalized standard deviations of slope-normal wind velocity, temperature and humidity scale relatively well with z/Λ, where z is the measurement height and Λ(z) the local Obukhov length. However, the horizontal velocity fluctuations are not correlated with z/Λ under all stability regimes. The non-dimensional gradients of wind velocity and temperature are also investigated. For those, the local scaling appears inappropriate, particularly at night when shallow drainage flows prevail and lead to negative wind-speed gradients close to the surface.

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Section: Dimensionless Standard Deviations Of Wind Velocity Componentsmentioning

confidence: 99%

Similarity Scaling Over a Steep Alpine Slope

Nadeau

Pardyjak

Higgins

et al. 2012

Boundary-Layer Meteorol

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“…Essential parts of the experimental set-up and conditions in general are discussed in detail elsewhere (Jørgensen and Mikkelsen 1993;Cionco et al 1999;Nielsen et al 2002;Mikkelsen et al 2002) so here a short summary will suffice. The temporal half-width of the aerosol backscatter Lidar's impulse response function is 10 ns, yielding an effective 1.5 m spatial resolution (−3 dB) along the beam direction, within the measured instantaneous cloud concentration.…”

Section: Observationsmentioning

confidence: 99%

“…The "Trial" experiment, also at Landskrona, Sweden (1), involved a heavy gas. Details concerning distances from the source are given in Nielsen et al (2002) and Mikkelsen et al (2002).…”

Section: Observationsmentioning

confidence: 99%

Concentration Fluctuations in Smoke Plumes Released Near the Ground

Jørgensen

Mikkelsen

Pécseli

2010

Boundary-Layer Meteorol

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Near-ground artificial cloud releases in the turbulent atmospheric boundary layer were investigated experimentally by Lidar measurement techniques. Simple scaling relations between the average concentration and the lowest order moments are suggested by simple analytical models, and the experimental results are tested against these hypotheses. We find strong evidence for a simple scaling of the standard deviation, skewness and kurtosis with the average concentrations at the downwind distances observed in our experiments. Near-ground concentration fluctuations in fixed as well as moving frames of references are investigated. The scaling is supported by data from several experimental sites and different atmospheric stability conditions. One conclusion of the study is that relatively accurate estimates for the standard deviation, skewness and kurtosis can be obtained for the concentration fluctuations, given a reliable estimate of the space-time varying average concentration field.

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“…For the horizontal component, the expression proposed by Panofsky et al (1977) given by In atmospheric turbulence which is not isotropic, the relation (18) is not exactly valid. However, we shall assume (18) as a better approximation than the assumption ) *f =*g.…”

Section: Markov Chain Modelmentioning

confidence: 99%

Numerical Simulation of Instantaneous Images of the Smoke Released from a Chimney

Shimanuki

Nomura

1991

Journal of the Meteorological Society of Japan

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Instantaneous images of the smoke released to the unstable surface boundary layer from a chimney are simulated numerically.The characteristic patterns of instantaneous images are formed by introducing spatial correlation of velocity. Trajectories correlated spatially are obtained by use of random variables correlated spatially in a Markov chain equation. In order to generate the field of random variables correlated spatially, a random number is given for each region divided by a length corresponding to the scale of turbulence.Empirical profiles of the mean and fluctuation of wind velocity are used in the Markov chain. The scale of turbulence is estimated from these profiles. Numerical simulations of the diffusion released from a source of 60 m height were carried out. Under certain atmospheric conditions, some samples of image are formed. The results with irregular patterns seem to be realistic. The spatial correlation of velocity was detected from the results of simulation, which is smaller than that of the given random variable.

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The characteristics of turbulent velocity components in the surface layer under convective conditions

Cited by 547 publications

References 10 publications

Similarity Scaling Over a Steep Alpine Slope

Similarity Scaling Over a Steep Alpine Slope

Concentration Fluctuations in Smoke Plumes Released Near the Ground

Numerical Simulation of Instantaneous Images of the Smoke Released from a Chimney

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