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Comparison of conventional lagrangian stochastic footprint models against les driven footprint estimates

机译:传统拉格朗日随机足迹模型与les驱动足迹估计的比较

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摘要

In this study we introduce a comparison method for footprint model results by evaluating the performance of conventional Lagrangian stochastic (LS) footprint models that use parameterised flow field characteristics with results of a Lagrangian trajectory model embedded in a large eddy simulation (LES) framework. The two conventional models follow the particles backward and forward in time while the trajectories in LES only evolve forward in time. We assess their performance in two unstably stratified boundary layers at observation levels covering the whole depth of the atmospheric boundary layer. We present a concept for footprint model comparison that can be applied for 2-D footprints and demonstrate that comparison of only cross wind integrated footprints is not sufficient for purposes facilitating two dimensional footprint information. Because the flow field description among the three models is most realistic in LES we use those results as the reference in the comparison. We found that the agreement of the two conventional models against the LES is generally better for intermediate measurement heights and for the more unstable case, whereas the two conventional flux footprint models agree best under less unstable conditions. The model comparison in 2-D was found quite sensitive to the grid resolution.
机译:在这项研究中,我们通过评估常规拉格朗日随机(LS)足迹模型的性能来介绍足迹模型结果的比较方法,该模型使用参数化流场特征以及嵌入在大型涡流仿真(LES)框架中的拉格朗日轨迹模型的结果。两种常规模型都在时间上向后和向前跟踪粒子,而LES中的轨迹仅在时间上向前演化。我们在覆盖大气边界层整个深度的观测水平上,在两个不稳定的边界层中评估了它们的性能。我们提出了一种可用于二维足迹的足迹模型比较概念,并演示了仅交叉风集成足迹的比较不足以促进二维足迹信息。因为在LES中这三个模型之间的流场描述是最现实的,所以我们将这些结果用作比较的参考。我们发现,对于中间测量高度和更不稳定的情况,两个常规模型相对于LES的一致性通常更好,而在不那么不稳定的条件下,两个常规磁通足迹模型的一致性最佳。发现二维中的模型比较对网格分辨率非常敏感。

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