Forward-in-time and Backward-in-time Dispersion in the Convective Boundary Layer: the Concentration Footprint

The turbulence field obtained using a large-eddy simulation model is used to simulate particle dispersion in the convective boundary layer with both forward-in-time and backward-in-time modes. A Lagrangian stochastic model is used to treat subgrid-scale turbulence. Results of forward dispersion match both laboratory experiments and previous numerical studies for different release heights in the convective boundary layer. Results obtained from backward dispersion show obvious asymmetry when directly compared to results from forward dispersion. However, a direct comparison of forward and backward dispersion has no apparent physical meaning and might be misleading. Results of backward dispersion can be interpreted as three-dimensional or generalized concentration footprints, which indicate that sources in the entire boundary layer, not only sources at the surface, may influence a concentration measurement at a point. Footprints at four source heights in the convective boundary layer corresponding to four receptors are derived using forward and backward dispersion methods. The agreement among footprints derived with forward and backward methods illustrates the equivalence between both approaches. The paper shows explicitly that Lagrangian simulations can yield identical footprints using forward and backward methods in horizontally homogeneous turbulence.     

A Homogeneous Langevin Equation Model, Part ii: Simulation of Dispersion in the Convective Boundary Layer

We present a Lagrangian stochastic model of vertical dispersion in the convective boundary layer (CBL). This model is based on a generalized Langevin equation that uses the simplifying assumption that the skewed vertical velocity probability distribution is spatially homogeneous. This approach has been shown to account for two key properties of CBL turbulence associated with large-scale coherent turbulent structures: skewed vertical velocity distributions and long velocity correlation time. A 'linear-skewed' form of the generalized Langevin equation is used, which has a linear (in velocity) deterministic acceleration and a skewed random acceleration. 'Reflection' boundary conditions for selecting a new velocity for a particle that encounters a boundary were investigated, including alternatives to the standard assumption that the magnitudes of the particle incident and reflected velocities are positively correlated. Model simulations were tested using cases for which exact, analytic statistical properties of particle velocity and position are known, i.e., well-mixed spatial and velocity distributions. Simulations of laboratory experiments of CBL dispersion show that (1) the homogeneous linear-skewed Langevin equation model (as well as an alternative 'nonlinear-Gaussian' Langevin equation model) can simulate the important aspects of dispersion in the CBL, and (2) a negatively-correlated-speed reflection boundary condition simulates the observed dispersion of material near the surface in the CBL significantly better than alternative reflection boundary conditions. The homogeneous linear-skewed Langevin equation model has the advantage that it is computationally more efficient than the homogeneous nonlinear-Gaussian Langevin equation model, and considerably more efficient than inhomogeneous Langevin equation models.     

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.     

Turbulent dispersion in coastal atmospheric boundary layers: An application of a Lagrangian model

A Lagrangian model is applied to simulate the dispersion of passive tracers (in particular, water vapour) in coastal atmospheric boundary layers under onshore wind conditions. When applied to convective boundary layers over uniform surfaces, the model gives results in agreement with those of similar studies. Numerical simulation of turbulent dispersion in coastal areas also reproduces the basic features known from experimental studies. Under onshore wind conditions, the humidity field is plume-shaped with the maximum vertical transport being over land downstream of the coast line. The model shows that the surface sensible heat flux over land, the static stability of the onshore air flow and the onshore wind speed are the most important factors determining the basic features of turbulent dispersion in coastal areas.     

A Lagrangian Stochastic Model for Heavy Particle Dispersion in the Atmospheric Marine Boundary Layer

The dispersion of heavy particles and pollutants is often simulated with Lagrangian stochastic (LS) models. Although these models have been employed successfully over land, the free surface at the air-sea interface complicates the implementation of traditional LS models. We present an adaptation of traditional LS models to the atmospheric marine boundary layer (MBL), where the bottom boundary is represented by a realistic wavy surface that moves and deforms. In addition, the correlation function for the turbulent flow following a particle is extended to the anisotropic, unsteady case. Our new model reproduces behaviour for Lagrangian turbulence in a stratified air flow that departs only slightly from the expected behaviour in isotropic turbulence. When solving for the trajectory of a heavy particle in the air flow, the modelled turbulent forcing on the particle also behaves remarkably well. For example, the spectrum of the turbulence at the particle location follows that of a massless particle for time scales approximately larger than the Stokes’ particle response time. We anticipate that this model will prove especially useful in the context of sea-spray dispersion and its associated momentum, sensible and latent heat, and gas fluxes between spray droplets and the atmosphere.     

Simulation of Time Series of Concentration Fluctuations in Atmospheric Dispersion Using a Correlation-distortion Technique

Short-duration fluctuations in the concentration of airborne substances can be important in a variety of atmospheric dispersion problems, especially when assessing the risks posed by harmful materials. This paper discusses a simulation technique for generating individual realisations of fluctuating concentration time series in dispersing plumes based on target probability distributions and spectral functions. The scheme uses a correlation-distortion approach to simulate these time series. Gaussian processes with modified spectral characteristics are generated and then transformed to yield non-Gaussian processes with the desired spectral characteristics. The simulation scheme is initially developed for a single receptor, and is then extended to model pairs of correlated time series at two receptors. In fact, the modelling technique can be generalised to an arbitrary number of receptors and this provides, in principal, an approach that is applicable to a wide class of similar problems (such as the modelling of instantaneous puff releases or the response of line-of-sight detection systems). The simulation technique is illustrated using observations made during recent field experiments, conducted both in the United Kingdom and in the U.S.A., investigating the short-range dispersion of a passive tracer.     

三维大气扩散粒子分裂(ADPS)模式

本文描述了基于PIC方法的三维大气扩散粒子分裂(ADPS)模式,并用解析解和1988年的广州地区现场观测资料验证了本模式.模式根据局地均匀和定常假设引入大粒子概念、烟团扩散原理和大粒子分裂技术,并运用了嵌套网格.ADPS模式用于模拟气态污染物在大气中的散布,同时也具备模拟TSP扩散的效能.     

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.     

On The Dynamical Content Of Lagrangian Stochastic Models In The Well-Mixed Class

It is shown how the correspondence between Lagrangian stochasticmodels and second-moment closures of the scalar-flux equation can be exploited to distinguishbetween Lagrangian stochastic models in the well-mixed class. It is found that physically realisticclosures of the scalar-flux equation correspond to Lagrangian stochastic models that have non-zero`spin' and so produce spiralling tracer-particle trajectories, whilst `zero-spin'models correspond to the isotropic-production model of scalar-fluxes.Lagrangian stochastic models consistent with rapid distortion theory and Speziale's transformation rule for the Reynolds stressequations in the extreme limit of two-dimensional turbulence are also shown to have non-zero spin.The residual non-uniqueness associated with satisfaction of thewell-mixed condition and the specification of mean spin is shown to be related to the helicity oftracer-particle trajectories. Investigations are also made of the influence upon turbulent dispersion oftime-dependent spin and of mean rotations of the fluctuating Lagrangian acceleration vector(i.e., second-order spin).     

基于大涡模拟评估GRAPES模式对对流边界层的模拟性能

为检验GRAPES半拉格朗日动力框架在大涡尺度上的模拟性能,为未来发展千米及其以下高分辨尺度的数值模式奠定基础,并构造GRAPES大涡模式以检验和发展边界层湍流参数化提供科学工具。通过在GRAPES模式中加入Smagorinsky-Lilly小尺度湍涡参数化,并将模式分辨率提高至50 m,构建GRAPES大涡模式(GRAPES_LES),以便分析GRAPES模式在大涡尺度上的适用性。同时利用广泛应用的已有大涡模式UCLA_LES作为参考,通过对干对流边界层湍流的模拟分析及与UCLA_LES模拟结果的对比,得出如下主要结论:GRAPES半拉格朗日动力框架能够模拟出与已有的大涡模式相似的边界层湍流特征;同时,通过分析也证明GRAPES存在由于采用半拉格朗日平流计算而带来过度耗散的问题:当使用相同的滤波尺度(Smagorinsky 常数)时,GRAPES_LES模拟出的速度场更为平滑,小尺度湍流结构过于光滑,通过对湍流能量的能谱分析更清楚地表明了这一点。进一步,对不同的Smagorinsky常数(对应不同的滤波尺度)进行了敏感性试验,表明可以通过改变滤波尺度,有效地缓解半拉格朗日框架隐含的耗散问题,得到更接近UCLA_LES所模拟的湍流特征。     

A Lagrangian Stochastic Model for Sea-Spray Evaporation in the Atmospheric Marine Boundary Layer

The dispersion of heavy particles subjected to a turbulent forcing is often simulated with Lagrangian stochastic models. Although these models have been employed successfully over land, the implementation of traditional LS models in the marine boundary layer is significantly more challenging. We present an adaptation of traditional Lagrangian stochastic models to the atmospheric marine boundary layer with a particular focus on the representation of the scalar turbulence for temperature and humidity. In this new model, the atmosphere can be stratified and the bottom boundary is represented by a realistic wavy surface that moves and deforms. Hence, the correlation function for the turbulent flow following a particle is extended to the inhomogenous, anisotropic case. The results reproduce behaviour for scalar Lagrangian turbulence in a stratified airflow that departs only slightly from the expected behaviour in isotropic turbulence. When solving for the surface temperature and the radius of evaporating heavy water droplets in the airflow, the modelled turbulent forcing on the particle also behaves remarkably well. We anticipate that this model will prove especially useful in the context of sea-spray dispersion and its associated sensible heat, latent heat, and gas fluxes between spray droplets and the atmosphere.     

A Two-Dimensional Lagrangian Stochastic Dispersion Model for Convective Boundary Layers with Wind Shear

Rotach, Gryning and Tassone constructed a two-dimensional Lagrangian stochastic model to describe the dispersion of passive tracers in turbulent boundary layers with stabilities ranging from ideally-neutral (w_* = 0) to fully-convective (u_* = 0). They found that the value of the Kolmogorov constant, C₀, as determined by optimizing model agreement with the measured spread of passive tracers, was dependent upon stability. Here, it is shown that the non-uniqueness, associated with satisfaction of the well-mixed condition, can be exploited to construct an alternative version of the model of Rotach et al. for which C₀ = 3 is universally applicable over the entire range of stabilities under consideration. This alternative model is shown to be in very close agreement with predictions, obtained in large-eddy simulations, for the dispersion of passive tracers in turbulent boundary layers with stabilities ranging from ideally-neutral to fully-convective.     

The Influence Of Vertical Wind Direction Shear On Dispersion In The Convective Boundary Layer, And Its Incorporation In Coastal Fumigation Models

The mean concentration distributionwithin a plume released from a point source in the atmosphericboundary layer can be greatly influenced by the systematic turningof wind with height (i.e. vertical wind direction shear). Such aninfluence includes a deflection of the plume centroid, with anassociated shearing of the vertical plume cross-section, and anenhancement of dispersion, in the horizontal plane. Wind directionshear is normally not accounted for in coastal fumigation models,although dispersion observations with shear acting as acontrolling parameter are not uncommon. A three-dimensionalLagrangian stochastic model is used to investigate the influenceof uniform wind direction shear on the diffusion of a point-sourceplume within the horizontally homogeneous convective boundarylayer, with the source located at the top of the boundary layer.Parameterisations are developed for the plume deflection andenhanced dispersion due to shear within the framework of aprobability density function (PDF) approach, and compared with theLagrangian model results. These parameterisations are thenincorporated into two applied coastal fumigation models: a PDFmodel, and a commonly used model that assumes uniform andinstantaneous mixing in the vertical direction. The PDF modelrepresents the vertical mixing process more realistically. A moreefficient version of the PDF model, which assumes a well-mixedconcentration distribution in the vertical at large times, isapplied to simulate sulfur dioxide data from the Kwinana CoastalFumigation Study. A comparison between the model results and thedata show that the model performs much better when the wind-sheareffects are included.     

Comparison of the Langrangian Footprint

We compare flux and concentration footprint estimates of athree-dimensional Lagrangian stochastic dispersion modelapplying backward trajectories with the results of ananalytical footprint model by Kormann and Meixner.The comparison is performed for varying stability regimesof the surface layer as well as for different measurementheights. In general, excellent correspondence is found.     

A Large-Eddy Simulation and Lagrangian Stochastic Study of Heavy Particle Dispersion in the Convective Boundary Layer

Large-eddy simulation and Lagrangian stochastic dispersion models were used to study heavy particle dispersion in the convective boundary layer (CBL). The effects of various geostrophic winds, particle diameters, and subgrid-scale (SGS) turbulence were investigated. Results showed an obvious depression in the vertical dispersion of heavy particles in the CBL and major vertical stratification in the distribution of particle concentrations, relative to the passive dispersion. Stronger geostrophic winds tended to increase the dispersion of heavy particles in the lower CBL. The SGS turbulence, particularly near the surface, markedly influenced the dispersion of heavy particles in the CBL. For reference, simulations using passive particles were also conducted; these simulation results agreed well with results from previous convective tank experiments and numerical simulations.     

半拉格朗日、半隐式欧拉方程组大气数值模式研究

介绍了一个具有较高时间积分效率的三维弹性大气数值模式。其中,控制方程为能够描述大气非静力及可压缩性的欧拉方程组,时间积分采用了高效率的“半拉格朗日、半隐式”方案。通过引用一个简化的“云物理过程”参数化方案,针对大气中深厚湿对流过程的若干问题进行了数值试验,结果表明,模式能够对该过程中的一些基本和复杂现象进行有效地模拟。试验结果还表明,动力学框架具有很好的稳定性,能够实现高效率的时间积分,它还具有较好的频散特性,保证了空间计算的精度,从而完好地描述了风暴的形态。     

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.     

Estimation of the Lagrangian Velocity Structure Function Constant C0 by Large-Eddy Simulation

The inertial subrange Kolmogorov constant C ₀, which determines the effective turbulent diffusion in velocity space, plays an important role in the Lagrangian modelling of pollutants. A wide range of values of the constant are found in the literature, most of them determined at low Reynolds number and/or under different assumptions. Here we estimate the constant C ₀ by tracking an ensemble of Lagrangian particles in a planetary boundary layer simulated with a large-eddy simulation model and analysing the Lagrangian velocity structure function in the inertial subrange. The advantage of this technique is that it easily allows Reynolds numbers to be achieved typical of convective turbulent flows. Our estimates of C ₀ is C ₀=4.3±0.3 consistent with values found in the literature