Horizontal coherence of wind fluctuations

The coherence for streamwise and cross-stream wind components is studied at four meteorological sites and compared with a representative wind-tunnel experiment. The coherence is approximated by a negative exponential in terms of a non-dimensional frequency, Δf and a decay parameter, a. Theoretical guidelines are developing to aid in identifying the pertinent variables affecting the decay parameters. These theoretical discussions indicate that for longitudinal separations, both the streamwise and cross-stream decay parameters are functions of roughness; the cross-stream decay parameter is a strong function of stability while the streamwise component is not. For lateral separations, it is found that both the streamwise and cross-stream decay parameters are functions of stability. Isopleths of the decay parameter are drawn on graphs with coordinates of angle and Richardson number for both the streamwise and cross-stream decay parameters of coherence. These empirical curves give an indication of the behavior of the decay parameters of coherence for a range of stabilities given by -0.9<Ri<0.08, and a range of angles between zero and ninety degrees. Department of Meteorology. Department of Aerospace Engineering.     

The structure and magnitude of concentration fluctuations

This paper is concerned with the science of turbulent diffusion and not, except incidentally, with its numerous practical applications. It discusses some recent research, particularly that by the authors and their collaborators. Among the topics considered are (i) the intermittency factor, (ii) the relationship between the mean of the concentration and its variance, and (iii) the interpretation of data. The principal aim of the paper is to draw attention to some outstanding basic questions which would seem promising targets for future research. Without progress on these questions (and others), regulatory modesl of air quality will continue-inevitably-to be unreliable and hardly worth using.     

Fractal aspects of integrated concentration fluctuations

Time series of vertically integrated concentrations (VIC) across neutrally buoyant plumes are used to study the fractal and multifractal characteristics of passive scalar fluctuations in turbulent flow fields. Here, the multifractal analysis is based on a novel definition of the singularity spectrum-F() of the time records. Approximations for quantities such as the fractal dimension and the spectral exponent are derived as functions ofF() and are compared with the experimental results. Among other things, we show that VIC records are characterized by two typical subdomains. One domain, which is related to integrated concentration fluctuations, is a subfractal process; whereas the second one, which is directly related to the concentration fluctuations, is a fractal process.     

Incorporation of internal fluctuations in a meandering plume model of concentration fluctuations

A meandering plume model that explicitly incorporates the effects of small-scale structure in the instantaneous plume has been formulated. The model requires the specification of two physically based input parameters; namely, the meander ratio,M, which is dependent on the ratio of the meandering plume dispersion to the instantaneous relative plume dispersion and, a relative in-plume fluctuation measure,k, that is related inversely to the fluctuation intensity in relative coordinates. Simple analytical expressions for crosswind profiles of the higher moments (including the important shape parameters such as fluctuation intensity, skewness, and kurtosis) and for the concentration pdf have been derived from the model. The model has been tested against some field data sets, indicating that it can reproduce many key aspects of the observed behavior of concentration fluctuations, particularly with respect to modeling the change in shape of the concentration pdf in the crosswind direction.List of Symbols C Mean concentration in absolute coordinates - C _r Mean concentration in relative coordinates - C₀ Centerline mean concentration in absolute coordinates - C _r,0 Centerline mean concentration in relative coordinates - f Probability density function of concentration in absolute coordinates - f _c Probability density function of plume centroid position - f _r Probability density function of concentration in relative coordinates - i Absolute concentration fluctuation intensity (standard deviation to mean ratio) - i _r Relative concentration fluctuation intensity (standard deviation to mean ratio) - k Relative in-plume fluctuation measure:k=1/i _r ² - K Concentration fluctuation kurtosis - M Meander ratio of meandering plume variance to relative plume variance - S Concentration fluctuation skewness - x Downwind distance from source - y Crosswind distance from mean-plume centerline - z Vertical distance above ground - Instantaneous (random) concentration - Crosswind dispersion ofnth concentration moment about zero - _ny Mean-plume crosswind (absolute) dispersion - _y Plume centroid (meandering) dispersion in crosswind direction - _y,c Instantaneous plume crosswind (relative) dispersion - Normalized mean concentration in absolute coordinates:C/C ₀ - Particular value taken on by instantaneous concentration,      

Large-sample estimates of wind fluctuations over the ocean

The best quality wind data from the Norwegian sector of the North Sea, consisting of 3662 20-min time series measured at the top of the Statfjord A drilling derrick, are analyzed. Identification of Autoregressive wind models with Akaike's AIC and Achwarz's BIC measures appears to give rather arbitrary results. Spectral estimation with FFT- and AIC-identified AR-methods give almost identical results in the mean. At the higher frequencies (% MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamOzaaaa!36D7!\[f\] > 10^–2 s^–1) the spectrum is estimated to follow the usual inertial subrange law with little variability. The small-scale turbulent intensity is estimated to be very low, even in hurricane conditions. Comparatively, the low-frequency (% MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaGaamOzaaaa!36D7!\[f\] ~ 10^–3 s^–1) fluctuations are more energetic than expected. None of the chosen low-frequency characteristica appear to be significantly linearly correlated to the available mean weather variables. However, some nonlinear relations appear to exist.     

Modelling of concentration fluctuations in canopy turbulence

The knowledge of the concentration probability density function (pdf) is of importance in a number of practical applications, and a Lagrangian stochastic (LS) pdf model has been developed to predict statistics and concentration pdf generated by continuous releases of non-reactive and reactive substances in canopy generated turbulence. Turbulent dispersion is modelled using a LS model including the effects of wind shear and along-wind turbulence. The dissipation of concentration fluctuations associated with turbulence and molecular diffusivity is simulated by an Interaction by Exchange with the Conditional Mean (IECM) micromixing model. A general procedure to obtain the micromixing time scale needed in the IECM model useful in non-homogeneous conditions and for single and multiple scalar sources has been developed. An efficient algorithm based on a nested grid approach with particle splitting, merging techniques and time averaging has been used, thus allowing the calculation for cases of practical interest. The model has been tested against wind-tunnel experiments of single line and multiple line releases in a canopy layer. The approach accounted for chemical reactions in a straightforward manner with no closure assumptions, but here the validation is limited to non-reacting scalars.     

Small-particle concentration fluctuations at a coastal site

Aerosol size spectra (d=10 nm–10 μm) were measured with an electrical aerosol spectrometer (EAS) at Mace Head on the west coast of Ireland. Several small aerosol particle (diameter 10–32 nm) concentration bursts were observed during the measurement period. Relationships between the events, air mass trajectories, tide height, and meteorological parameters are examined. Series of bursts were observed when a spectral transformation due to subsequent particle growth from 10 to 56–100 nm can be identified in an Eulerian experiment. Particle growth rates of between 1 and 3 nm/h were determined. These bursts appear in cold and comparatively clean arctic or polar air masses with temperature and relative humidity fluctuations, and do not correlate with low tide in some cases. These episodes, similar to those frequently found in the continental boundary layer, are thought to occur over a wide area and, for clear detection, require stable airflow for a few days. Elevated small-particle concentration events are more common during low tide or shortly after, and are typically associated with low wind speeds. Here, the increased shore exposure during low tide is thought to influence the nucleation and the subsequent growth of these aerosol particles. The occurrences of the bursts are found to depend on local wind direction. The highest d=10–32 nm particle concentrations appeared for wind sectors furthest from the tidal regions when the wind direction was 150–160°(south-easterly). Most of the events occurred during daytime when solar irradiation is most intense.     

The effect of line averaging on concentration fluctuations

The reduction in variance of concentration fluctuations due to line averaging is estimated assuming that the process is influenced by the integral distance scale, y _I , of ambient turbulence and the scaling width, W, of the time-averaged plume. An analytical formula is derived for the line-averaged variance for situations where the autocorrelogram is exponential and the point variance decreases exponentially with distance from plume centerline. Predictions of concentration fluctuation variance are compared with water tank and field data, with the result that the decrease of variance with averaging distance is well-simulated if the model parameters y _I and W are carefully chosen.     

Intraseasonal zonal wind fluctuations seen through Indian radiosonde observations

Summary Twice-daily radiosonde records for Calcutta, Madras, Nagpur, New Delhi, Trivandrum, and Visakhapatnam have been quality checked and analyzed for intraseasonal activity in the summer monsoon. The records for all six cities end on 30 June 1978 and are 17–27 years long.Spectra were estimated by smoothing periodograms and by using the maximum entropy method (MEM), which entails fitting an autoregressive (AR) model. We show how confidence limits can be placed on an average of MEM spectral estimates using the Central Limit Theorem and how this helps pick the orders of the AR models to be tried. We donot favor use of Akaike's Final Prediction Error in choosing the model order, because it can grossly underestimate the AR model order needed to resolve low frequency peaks.MEM spectra of zonal wind based on thirtieth order AR models have large peaks around 30 day time scales. 10–20 day activity is identifiable but is much less prominent. On average, 3–5 day time scales are part of the spectral continuum and do not have a significant spectral peak.Time-height diagrams of filtered zonal wind show that a deep layer of the troposphere acts in phase on 30–50 day time scales over India. The shortest vertical length scale is over southern India and the longest is over northern India. Vertical phase propagation is irregular except over Nagpur, where it is generally upward. Empirical orthogonal functions indicate that vertically in phase activity has more variance (kinetic energy) than the first baroclinic mode.With 10 Figures     

On characteristics of wind direction fluctuations in the surface layer

It is shown that the ratio of standard deviation of lateral velocity to the friction velocity, /u _*, and therefore wind direction fluctuations, are sensitive to mesoscale terrain properties. Under neutral conditions, /u _* is almost 40% larger in rolling terrain than over a horizontal surface. In the lee of a low mountain, the fluctuations may be 2.5 times as strong as over horizontal terrain. In contrast, vertical velocity fluctuations are little influenced by mesoscale terrain features.Now with Air Weather Service, Offutt AFB, Omaha, Nebraska.     

The vertical profile of concentration fluctuations in near-surface plumes

Field experiments on concentration fluctuations have frequently measured horizontal cross-sections of fluctuation statistics through plumes at fixed heights near the surface, but have not considered the effect of height above the ground in any detail. A set of tracer experiments designed to measure vertical profiles of concentration fluctuations in plumes, with a range of source heights, is described, and profiles of statistics are presented. Considerable variation of the statistics with both source and detector height is found. Near the surface, fluctuation intensity is a minimum and the time and length scales of the fluctuations are greatly increased. Profiles are consistent with the idea that concentration fluctuations near the surface are like those higher up at a greater distance from the source. Lowering the source height reduces the fluctuation intensity at all heights, and also alters the form of the concentration PDF. Results may be explained by the reduced length scale of sheargenerated turbulence near the surface causing enhanced small-scale mixing, which rapidly smooths out much of the fine structure with the plume.     

On estimating the return values for time series of wind speed and wind wave height

In order to estimate the return values ofthe time series ofwind speed and wind wave height, it is proposed to use the extrapolation of polynomial approximation constructed for the small part of the tail of probability function of the series considered. The method is based on the optimization of the accuracy of polynomial approximation implemented by varying the length and shift of the used part of probability function and the polynomial exponent. Optimization includes control over quality criteria for approximation that are aimed at increasing approximation accuracy. On the example of wind reanalysis data and the results of numerical simulation of wind waves in the Indian Ocean for the period of 1980-2010, the proposed method is applied to obtain the return value estimates of the mentioned parameters at several fixed points in the ocean.     

An inverse method for determining wind stress from water-level fluctuations

The hydrodynamic equations governing the water-level response of a lake to wind stress are inverted to determine wind stress from water-level fluctuations. In order to obtain a unique solution, the wind-stress field is represented in terms of a finite number of spatially dependent basis functions with time-dependent coefficients. The discretized version of the inverse equation is solved by a least-squares procedure to obtain the coefficients, and thereby the stress. The method is tested for several ideal cases with Lake Erie topography. Real water-level data is then used to determine hourly values of vector wind stress over Lake Erie for the period 5 May–31 October, 1979. Results are compared with measurements of wind speed and direction from buoys deployed in the lake. Calculated stress direction agrees with observed wind direction for wind speeds > 7.5 m s⁻¹. Under neutral conditions, calculated drag coefficients increase with the wind speed from 1.53 × 10⁻³ for 7.5−10 m s⁻¹ winds to 2.04 × 10⁻³ for 15−17.5 m s⁻¹ winds. Drag coefficients are lower for stable conditions and higher for unstable conditions.     

The exponential probability density function and concentration fluctuations in smoke plumes

Observations of 1-s average concentration fluctuations during two trials of a U.S. Army diffusion experiment are presented and compared with model predictions based on an exponential probability density function (pdf). The source is near the surface and concentration monitors are on lines about 30 to 100 m downwind of the source. The observed ratio of the standard deviation to the mean of the concentration fluctuations is about 1.3 on the mean plume axis and 4 to 5 on the mean plume edges. Plume intermittency (fraction of non-zero readings) is about 50%; on the mean plume axis and 10%; on the mean plume edges. A meandering plume model is combined with an exponential pdf assumption to produce predictions of the intermittency and the standard deviation of the concentration fluctuations that are within 20%; of the observations.     

The effects of source size on concentration fluctuations in plumes

The effects of source size on plume behaviour have been examined in a 1.2 m wind tunnel boundary layer for isokinetic sources with diameters from 3 to 35 mm at source heights of 230 mm and at ground level. Experimental measurements of mean concentration and the variance, intermittency and probability density functions of the concentration fluctuations were obtained. In addition, a fluctuating Gaussian plume model is presented which reproduces many of the observed features of the elevated emission. The mean plume width becomes independent of source size much more rapidly than the instantaneous plume width. Since it is the meandering of the instantaneous plume which generates most of the concentration fluctuations near the source, these are also dependent on source size. The flux of variance in the plume reaches a maximum, whose value is greatest for the smallest source size, close to the source and thereafter is monotonically decreasing. The intermittency factor reaches a minimum, whose value is lowest for the smallest source, and increases back towards one. Concentration fluctuations for the ground-level source are much less dependent on source size due to the effects of the surface.     

The variations of the statistics of wind,temperature and humidity fluctuations with stability

Measurements of the turbulent fluctuations of wind, temperature and humidity were made in the atmospheric surface layer. The statistics of the fluctuations were investigated in both the time and frequency domains. The vertical wind, temperature and smaller-scale horizontal wind fluctuations appear to obey the Monin-Obukhov similarity hypothesis. The humidity fluctuations were found to be governed by a humidity flux stability parameter rather than the normal Monin-Obukhov length.     

Statistics of wind direction fluctuations in the surface layer over plant canopies

Boundary-Layer Meteorology - Height dependency of statistics of horizontal and vertical wind direction fluctuations over plant canopies have been studied, using observational data in the surface...     

Seasonal variation of wind direction fluctuations vs Pasquill stabilities in complex terrain

The authors have studied the seasonal variation of Σ_θ (the standard deviation of wind direction fluctuations) vs Pasquill stabilities over complex terrain. It is found that the values of Σ_θ are quite high in the month of April in contrast with other months. Values are also high when compared with those estimated over flat terrain and at a coastal site.     

Measurements of fluctuations of vertical wind velocity,temperature and radio-refractive index above the sea

Mean spectra of vertical wind velocity, temperature, and humidity and co-spectra of vertical turbulent heat and moisture fluxes are reported, normalized in terms of the similarity theory of Monin-Obukhov. The measurements were made in April 1967 at light-house Alte Weser at a height of 30 m above the German Bight. Ten spectra measured under conditions of moderate instability (z/L –0.08) have been used for the evaluation of a mean spectral curve. The humidity fluctuations have been determined from simultaneous turbulence measurements of temperature and radiorefractive-index, which were obtained by a microwave refractometer.Similar to the BOMEX measurements discussed by Phelps and Pond (1971) our results also show a dissimilarity between the fluctuations of temperature and humidity. Accordingly, in the range of lower and higher natural frequencies, significant differences were present between the co-spectra of the vertical heat and moisture fluxes, although the mean peak frequencies of both the fluxes nearly correspond to that of the mean vertical wind-velocity spectrum (f _m 0.35).