A Wind Tunnel and Numerical Investigation of Turbulent Dispersion in Coastal Atmospheric Boundary Layers

Thermal internal boundary layers in onshore air flows have a significant influence on pollutant diffusion in coastal areas. Although several models for this diffusion problem exist, measurements for model verification are scarce. In this paper, we present a set of wind tunnel observations and examine the performance of a Lagrangian stochastic model. The good agreement between the model simulation and the tunnel measurements confirms the usefulness of the Lagrangian stochastic model for practical purposes. Sensitivity tests of the model to turbulence statistics show that uncertainty in velocity skewness to the extent of observational scatter does not seem to have a significant influence on pollutant dispersion, while uncertainties in turbulence intensity (variance) significantly influence the dispersion pattern.     

A closure to derive a three-dimensional well-mixed trajectory-model for non-Gaussian, inhomogeneous turbulence

A three-dimensional Lagrangian stochastic (LS) model to evaluate pollutant dispersion in the atmospheric boundary layer has been developed. The model satisfies the well-mixed criterion of Thomson and allows for inhomogeneous, skew turbulence. Making use of the spherical reference frame, one of the possible solutions has been obtained. A skewed joint probability density function (PDF), which reproduces the given velocity moments (means, variances, skewness and covariances), has been built-up by a linear combination of eight Gaussian PDFs. In order to verify consistency with the well-mixed criterion, the long term results have been compared with the theoretical behaviour. A comparison between our model and Thomson's published algorithms was also carried out. By comparing wind-tunnel data and numerical predictions, a further validation of our LS model has been obtained. From an analysis of the numerical results, we can state that our model is able to evaluate dispersion in the case of complex flows where the application of previous models is unsuccessful.     

Turbulence in an almond orchard: Vertical variations in turbulent statistics

Three-dimensional wind velocity components were measured above and within a uniform almond orchard. Turbulent statistics associated with the turbulent flow inside the canopy are examined in detail. Turbulence in an almond orchard is characterized by relatively high turbulent intensities and large skewness and kurtosis values. These results indicate that the frequency distribution of wind velocity components is non-Gaussian. Conditional sampling of the turbulent measurements show that large, infrequent sweeps provide the predominant mechanism for tangential momentum stress in the canopy crown. Deep inside the canopy, a secondary wind maximum and small, but positive, tangential momentum stresses are observed.     

On the Formulation of Lagrangian Stochastic Models of Scalar Dispersion Within Plant Canopies

Lagrangian stochastic models, quadratic in velocity and satisfying the well-mixed condition for two-dimensional Gaussian turbulence, are used to make predictions of scalar dispersion within a model plant canopy. The non-uniqueness associated with satisfaction of the well-mixed condition is shown to be non-trivial (i.e. different models produce different predictions for scalar dispersion). The best agreement between measured and predicted mean concentrations of scalars is shown to be obtained with a small sub-class of optimal models. This sub-class of optimal models includes Thomson's model (J. Fluid Mech. 180, 529–556, 1987), the simplest model that satisfies the well-mixed condition for Gaussian turbulence, but does not include two other models identified recently as being in optimal agreement with the measured spread of tracers in a neutral boundary layer. It is therefore demonstrated that such models are not universal, i.e. applicable to a wide range of flows without readjustment of model parameters. Predictions for scalar dispersion in the model plant canopy are also obtained using the model of Flesch and Wilson (Boundary-Layer Meteorol. 61, 349–374, 1992). It is shown that, when used with a Gaussian velocity distribution or a maximum-missing-information velocity distribution, which accounts for the measured skewness and kurtosis of velocity statistics, the agreement between predictions obtained using the model of Flesch and Wilson and measurements is as good as that obtained using Thomson's model.     

Large-Eddy Simulation of the Wind Field and Plume Dispersion Within Different Obstacle Arrays Using a Dynamic Mixing Length Subgrid-Scale Model

A novel dynamic mixing length (DML) subgrid-scale (SGS) model is proposed to improve the large-eddy simulations of the wind field and contaminant dispersion around a group of buildings. Wind field and contaminant dispersion in two kinds of building array geometries are simulated using the model, with wind-tunnel experimental data used to validate the model. The relative errors in the lateral profiles of the streamwise mean velocities behind the sixth row of the buildings of the staggered obstacle array and the aligned obstacle array at the half height of the building are 15 and 9%, respectively. The DML velocity fluctuations in the staggered and aligned obstacle arrays are in agreement with those of the experiment. The results indicate that the DML model can make a more accurate prediction of the mean velocity and velocity fluctuations. The DML model is highly suitable for the simulation of multi-scale turbulent flow in urban canyons, of high Reynolds number turbulent flow and of complex turbulent flow.     

A two-dimensional trajectory-simulation model for non-Gaussian,inhomogeneous turbulence within plant canopies

We report a two-dimensional (alongwind u, vertical w) trajectory-simulation model, consistent with Thomson's (1987) well-mixed criteria, that allows for the non-Gaussian turbulence typical of flow within a plant canopy. The effect of non-Gaussian turbulence was examined by formulating a non-Gaussian u, w joint probability density function (PDF) as the sum of two Gaussian joint-PDFs. The resultant PDF reproduced the desired means, variances, skewnesses, and kurtoses, and the correct covariance. In prediction of the location of maximum concentration downwind of a line source in homogeneous, slightly non-Gaussian turbulence, it proved advantageous to incorporate skewness and kurtosis. However, in the case of inhomogeneous, highly non-Gaussian turbulence, the addition of skewness and kurtosis in the model resulted in substantially worse agreement with measurements than the results of the model using Gaussian PDFs. This may be due to inaccuracy in our PDF formulation. Dispersion predictions from the model with Gaussian PDFs were generally not statistically different from measurements. These results indicate that a two-dimensional Gaussian trajectory-simulation approach is adequate to predict mean concentrations and fluxes resulting from sources within plant canopies.     

Turbulence structure in a deciduous forest

Three-dimensional wind velocity components were measured at two levels above and at six levels within a fully-leafed deciduous forest. Greatest shear occurs in the upper 20% of the canopy, where over 70% of the foliage is concentrated. The turbulence structure inside the canopy is characterized as non-Gaussian, intermittant and highly turbulent. This feature is supported by large turbulence intensities, skewness and kurtosis values and by the large infrequent sweeps and ejections that dominate tangential momentum transfer. Considerable day/night differences were observed in the vertical profiles of the mean streamwise wind velocity and turbulence intensities since the stability of the nocturnal boundary layer dampens turbulence above and within the canopy.     

Dispersion Moments of Fumigating Plumes – Lidar Estimates and Pdf Model Simulations

Near-instantaneous vertical scans ofpower plant plumes, sampled by a lidar over three days as part ofthe 1995 Kwinana Coastal Fumigation Study, are analysed to obtainhourly-averaged total dispersion moments up to fourth order, andalso the relative and meander spreads. Two distinct fumigationcases, termed as neutral and stable cases, are observed dependingon whether the plume transport prior to fumigation takes place ina neutral atmosphere, or in a stable region above the neutralatmosphere. Plumes in the stable case are observed to undergoslower fumigation. The mean spreads display contrasting behavioursfor the two fumigating cases, while the vertical skewness shows anegative peak value of about -1 for the neutral case and -2for the stable case in the fumigation zone. The lateral skewnessis positive with a peak value of about unity for both cases, andis attributed to wind directional shear within the thermalinternal boundary layer. The vertical kurtosis is greater than theGaussian value of 3 in the fumigation zone, while the lateralkurtosis is scattered about this value. A recently-developedskewed probability density function model with wind shear isapplied to describe the fumigation data. Overall, the modelsimulates the observed vertical and lateral statistics well up tothe fourth order, except for the lateral skewness and kurtosisvalues in the stable case, which is probably due to the lidar'srange and sensitivity constraints and an inadequate sample size.Although the lateral turbulent diffusion in the model is Gaussian(i.e., zero skewness), the inclusion of wind shear in the model ismanifested in the predicted lateral skewness being greater thanzero in the fumigation zone, and of similar magnitude to the lidardata in the neutral case.     

风廓线雷达探测大气返回信号谱的仿真模拟

利用2008年1—9月北京延庆地区对流层CFL-08风廓线雷达和2009年7—12月广东东莞地区边界层CFL-03风廓线雷达晴空大气探测资料,对大气返回信号功率谱密度分布及雷达系统噪声幅度统计特征进行分析。基于大气返回信号的谱分布符合高斯分布的统计结果,采用高斯模型对大气返回信号谱进行模拟;雷达系统噪声是白噪声,其谱线幅度的统计特征呈高斯分布,在此基础上,通过生成高斯分布随机函数对雷达探测输出信号进行信号谱分布的仿真模拟,并采用雷达探测信号的谱参数对仿真模拟进行检验,效果较好。该文应用仿真模拟的数据,对风廓线雷达信息处理方法及其处理精度进行了初步试验和分析。     

Footprints in Homogeneously and Heterogeneously Driven Boundary Layers Derived from a Lagrangian Stochastic Particle Model Embedded into Large-Eddy Simulation

A Lagrangian stochastic (LS) model, which is embedded into a parallelised large-eddy simulation (LES) model, is used for dispersion and footprint evaluations. For the first time an online coupling between LES and LS models is applied. The new model reproduces concentration patterns, which were obtained in prior studies, provided that subgrid-scale turbulence is included in the LS model. Comparisons with prior studies show that the model evaluates footprints successfully. Streamwise dispersion leads to footprint maxima that are situated less far upstream than previously reported. Negative flux footprints are detected in the convective boundary layer (CBL). The wide range of applicability of the model is shown by applying it under neutral and stable stratification. It is pointed out that the turning of the wind direction with height leads to a considerable dependency of source areas on height. First results of an application to a heterogeneously heated CBL are presented, which emphasize that footprints are severely affected by the inhomogeneity.     

海面风场订正对风暴潮数值模拟的影响

海洋模式在模拟风暴增水时对于风场的依赖性比较大,准确的风场模拟是正确模拟风暴潮的重要前提.用渤海海域4次典型的风暴潮个例,检验改良的渤海风场推算模式对风暴潮数值模拟的影响,分别用订正前后的风场驱动风暴潮数值模式得到逐时的渤海增水场,并与塘沽实测值比较表明:在4个过程中海面风场订正后风暴潮模式的模拟结果均得到了明显的改进...     

ON THE PDF MODELS FOR ATMOSPHERIC DIFFUSION IN BOUNDARY LAYER

In this paper, taking its turbulent exchange coefficient as a function of the Lagrangian timescale and standard variance of the turbulence in atmosphere, the atmospheric dispersion PDFmodels are obtained on the basis of atmospheric diffusion K-theory. In the model the statistics ofwind speed are directly used as its parameters instead of classic dispersion parameters. The bi-Gaussian PDF is derived in convective boundary layer (CBL), from the statistics of verticalvelocity in both of the downdraft and updraft regions that are investigated theoretically in the otherpart of this paper. Giving the driven parameters of the CBL (including the convective velocity scalew* and the mixing depth h_i) and the time-averaged wind speed at release level, the PDF model isable to simulate the distribution of concentration released at any levels in the CBL. The PDF'ssimulations are fairly consistent with the measurements in CONDORS experiment or the resultsbrought out by some numerical simulations.     

Evaluation of a micro-scale wind model’s performance over realistic building clusters using wind tunnel experiments

The simulation performance over complex building clusters of a wind simulation model(Wind Information Field Fast Analysis model, WIFFA) in a micro-scale air pollutant dispersion model system(Urban Microscale Air Pollution dispersion Simulation model, UMAPS) is evaluated using various wind tunnel experimental data including the CEDVAL(Compilation of Experimental Data for Validation of Micro-Scale Dispersion Models) wind tunnel experiment data and the NJU-FZ experiment data(Nanjing University-Fang Zhuang neighborhood wind tunnel experiment data). The results show that the wind model can reproduce the vortexes triggered by urban buildings well, and the flow patterns in urban street canyons and building clusters can also be represented. Due to the complex shapes of buildings and their distributions, the simulation deviations/discrepancies from the measurements are usually caused by the simplification of the building shapes and the determination of the key zone sizes. The computational efficiencies of different cases are also discussed in this paper. The model has a high computational efficiency compared to traditional numerical models that solve the Navier–Stokes equations, and can produce very high-resolution(1–5 m) wind fields of a complex neighborhood scale urban building canopy(～ 1 km ×1km) in less than 3 min when run on a personal computer.     

A Statistical Model for the Prediction of Wind-Speed Probabilities in the Atmospheric Surface Layer

Wind fields in the atmospheric surface layer (ASL) are highly three-dimensional and characterized by strong spatial and temporal variability. For various applications such as wind-comfort assessments and structural design, an understanding of potentially hazardous wind extremes is important. Statistical models are designed to facilitate conclusions about the occurrence probability of wind speeds based on the knowledge of low-order flow statistics. Being particularly interested in the upper tail regions we show that the statistical behaviour of near-surface wind speeds is adequately represented by the Beta distribution. By using the properties of the Beta probability density function in combination with a model for estimating extreme values based on readily available turbulence statistics, it is demonstrated that this novel modelling approach reliably predicts the upper margins of encountered wind speeds. The model’s basic parameter is derived from three substantially different calibrating datasets of flow in the ASL originating from boundary-layer wind-tunnel measurements and direct numerical simulation. Evaluating the model based on independent field observations of near-surface wind speeds shows a high level of agreement between the statistically modelled horizontal wind speeds and measurements. The results show that, based on knowledge of only a few simple flow statistics (mean wind speed, wind-speed fluctuations and integral time scales), the occurrence probability of velocity magnitudes at arbitrary flow locations in the ASL can be estimated with a high degree of confidence.     

High-Order Statistics of Temperature Fluctuations in an Unstable Atmospheric Surface Layer over Grassland

Skewness(S) and kurtosis(K) of temperature in the surface layer over a grassland are investigated under unstable thermal stratifications. We find that both skewness and kurtosis generally obey Monin–Obukhov similarity theory and tend to be constant values(1.5 and 5.3, respectively) when the stability parameter z/L -2. Quantitative formulas of the similarity functions are proposed. The temperature probability density function(PDF) is close to Gaussian in near neutral stratification and non-Gaussian in unstable stratification. The influence of coherent motions on the PDF behavior is analyzed using the quadrant analysis technique. It shows that PDF behaviors are controlled by ejections and sweeps. The results also indicate that the PDF type of the ejections always follows a Gaussian distribution, while the PDF of the sweeps changes with stability.     

A Homogeneous Langevin Equation Model, Part i: Simulation of Particle Trajectories in Turbulence with a Skewed Velocity Distribution

A Lagrangian stochastic model for the time evolution of the velocity of a fluid particle is presented. This model is based on a one-dimensional generalized Langevin equation, and assumes the velocity probability distribution of the turbulent fluid is skewed and spatially homogeneous. This has been shown to be an effective approach to simulating vertical dispersion in the convective boundary layer. We use a form of the Langevin equation that has a linear (in velocity) deterministic acceleration and a random acceleration that is a non-Gaussian, skewed process. For the case of homogeneous fluid velocity statistics, this 'linear-skewed' Langevin equation can be integrated explicitly, resulting in an efficient numerical simulation method. Model simulations were tested using cases for which exact, analytic statistical properties of particle velocity are known. Results of these tests show that, for homogeneous turbulence, a linear-skewed Langevin equation model can overcome the difficulties encountered in applying a Langevin equation with a skewed random acceleration. The linear-skewed Langevin equation model results are compared to results of a 'nonlinear-Gaussian' Langevin equation model, and show that the linear-skewed model is significantly more efficient.     

Turbulent velocity distributions and implied trajectory models

Well-mixed, first-order Lagrangian stochastic (LS) particle trajectory models are derived from several idealized (“toy”) turbulent velocity distributions, and their performance is compared against the observations of Project Prairie Grass, i.e., the case of a continuous point source of tracer near the ground, in the horizontally homogeneous and neutrally stratified surface layer. Although in a context of limited information a Gaussian distribution is the preferred choice, and although the Gaussian corresponds to the simplest of this set of LS models (namely, the Langevin equation), models stemming from other velocity distributions give similar, albeit distinguishable, predictions.     

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.     

WIND SHEAR IDENTIFICATION WITH THE RETRIEVED WIND OF DOPPLER WEATHER RADAR

Wind shear reflects that the wind field is not uniform, which is one of the primary factors which make the retrieval of the wind field difficult. Based on volume velocity process(VVP) wind field retrieval technique, the intensity of wind shear is identified in this paper. After analyzing the traditional techniques that rely on the difference of radial velocity to identify wind shear, a fixed difference among radial velocities that may cause false identification in a uniform wind field was found. Because of the non-uniformity in wind shear areas, the difference of retrieved results between surrounding analysis volumes can be used as a measurement to show how strong the wind shear is. According to the analysis of a severe convective weather process that occurred in Guangzhou, it can be found that the areas of wind shear appeared with the strength significantly larger than in other regions and the magnitude generally larger than4.5 m/(s·km). Besides, by comparing the variation of wind shear strength during the convection, it can be found that new cells will be more likely to generate when the strength is above 3.0 m/(s·km). Therefore, the analysis of strong wind shear's movement and development is helpful to forecasting severe convections.