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Analytical puff modelling of light-wind dispersion in stable and unstable conditions

机译:稳定和不稳定条件下的风散的解析粉扑模型

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摘要

The puff modelling technique can describe dispersion in light winds by accounting for streamwise diffusion. A simple analytical puff model is formulated for stable as well as unstable stratification. In the stable case, the model is a slight generalisation of the Gaussian puff model of Thomson and Manning (2001), whereas in the unstable case it incorporates a probability density function approach to account for the observed skewness of the vertical turbulent velocities. An evaluation conducted using a well-known dataset collected under stable conditions suggests that the performance of the model is comparable to some of the top-performing models based on more complex techniques. However, it is apparent that some of the observed complex dispersion behaviour that arises due to the non-Gaussian characteristics of the wind direction distribution cannot be properly modelled by using the hourly-averaged meteorology. Since there are no suitable datasets for evaluation under unstable conditions, the puff model is benchmarked against a full three-dimensional Lagrangian particle model. The results show that the puff model is capable of describing most of the well-known features of convective dispersion observed under moderate winds, and that it simulates light-wind dispersion characteristics that are in good agreement with the particle model predictions. The results also highlight that the time since the start of tracer release is an important parameter in light winds. Quantitative estimates as to when the effects of streamwise diffusion in unstable flows can be neglected are also given.
机译:吹气建模技术可以通过考虑流向扩散来描述小风中的扩散。建立了一个简单的分析粉扑模型,以实现稳定以及不稳定的分层。在稳定的情况下,该模型是Thomson and Manning(2001)的高斯吹气模型的略微推广,而在不稳定的情况下,它采用了概率密度函数方法来解决垂直湍流速度的偏斜问题。使用在稳定条件下收集的众所周知的数据集进行的评估表明,该模型的性能与某些基于更复杂技术的性能最高的模型相当。但是,很明显,由于使用风向分布的非高斯特性而导致的某些观测到的复杂分散行为无法通过使用小时平均气象学来正确建模。由于没有合适的数据集在不稳定条件下进行评估,因此将粉扑模型与完整的三维拉格朗日粒子模型进行了基准比较。结果表明,吹气模型能够描述在中等风下观测到的大多数对流弥散特征,并且它模拟的风-风弥散特征与粒子模型的预测非常吻合。结果还强调,自示踪剂释放开始以来的时间是小风中的重要参数。还给出了关于何时可以忽略不稳定流中的流向扩散影响的定量估计。

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