Footprint model development and validation for homogeneous and inhomogeneous terrain using high resolution large eddy simulation

使用高分辨率大涡模拟开发和验证均匀和非均匀地形的足迹模型

• 批准号: 5452157
• 负责人: Professor Dr. Thomas Foken
• 金额: --
• 依托单位: Institut für Meteorologie und Klimatologie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2005
• 资助国家: 德国
• 起止时间: 2004-12-31 至 2008-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/5452157?language=en
• 关键词: Footprint; model; development; validation; homogeneous

The project focuses on developing and validating methods to compute footprints of atmospheric constituents above thermally and aerodynamically heterogeneous surfaces. A footprint function determines the spatial context of a measurement by defining a transfer function between sources or sinks of the constituent and the sensor position. The resulting source area is an important quality assessment tool, e.g. to assess the influence of variable terrain elements on the data. Although micrometeorological research focuses increasingly on complex terrain, footprint models developed to date are restricted to idealised cases of horizontally homogeneous flow conditions, and thus cannot consider the impact of heterogeneity. In the framework of this project, one means to consider influence of heterogeneity is a highresolution large eddy simulation (LES) model that allows the explicit resolution of the turbulent transport processes. As a second, computationally less costly method, both forward and backward Lagrangian stochastic (LS) algorithms are modified to account for horizontally heterogeneous flow conditions. The LES datasets will be used both to derive the flow statistics required to run the LS models, and to evaluate their produced source areas. The applicability of the footprint estimates from both LES model and LS algorithms will finally be assessed with data from field experiments.

该项目的重点是开发和验证计算热和空气动力学异质表面上方大气成分足迹的方法。足迹函数通过定义成分的源或汇与传感器位置之间的传递函数来确定测量的空间背景。由此产生的源区域是一个重要的质量评估工具，例如评估可变地形元素对数据的影响。尽管微气象研究越来越关注复杂地形，但迄今为止开发的足迹模型仅限于水平均匀流条件的理想情况，因此无法考虑非均质性的影响。在该项目的框架中，考虑异质性影响的一种方法是高分辨率大涡模拟（LES）模型，该模型允许明确解析湍流传输过程。作为第二种计算成本较低的方法，前向和后向拉格朗日随机 (LS) 算法都经过修改，以考虑水平异质流条件。 LES 数据集将用于导出运行 LS 模型所需的流量统计数据，并评估其产生的源区域。 LES 模型和 LS 算法的足迹估计的适用性最终将通过现场实验的数据进行评估。