Exchange processes in mountainous regions; Large-eddy-simulation

在这个子项目中，将进行高分辨率大涡模拟（LES），以研究森林内部和森林与上覆大气之间的湍流交换。与bundle应用EGER （ExchanGE processes in山区）的实验子项目相比，LES提供了对三维非平稳湍流场的完整和详细的了解，并允许研究相干结构及其对垂直交换的影响以及它们如何影响湍流测量。与以往的理想化研究不同，这个子项目旨在尽可能地再现测量现场的条件。地形图将包括在LES中。森林效应将通过将LES与详细的植被模型耦合来解释，该模型计算由植被引起的动量、能量和物质通量，并将其作为LES的边界条件。随WRF进行的中尺度模拟将提供大尺度驱动力。此外，森林林隙对次生循环产生的临界大小应通过进行具有系统变化林隙大小的理想化研究来确定。将采用线性随机估计、经验正交函数（EOF）、适当正交分解（POD）和小波分析等先进方法对LES数据进行相干结构分析。此外，将对传感器位置进行虚拟涡流相关测量，并使用LES嵌入式拉格朗日粒子模型计算它们的足迹。

Within this sub-project, high-resolution large-eddy simulations (LES) will be carried out in order to study the turbulent exchange within and between the forest and the overlying atmosphere. Compared with the experimental sub-projects of the bundle application EGER (ExchanGE processes in mountainous Regions), LES offers a complete and detailed insight into the threedimensional non-stationary turbulence field and allows the investigation of coherent structures and their effect on the vertical exchange and how they effect the turbulence measurements.In contrast with previous idealized studies, this sub-project aims to reproduce the measurement site conditions as close as possible. Topography will be included in the LES. The forest effect will be accounted for by coupling the LES with a detailed vegetation model, which calculates momentum, energy, and matter fluxes caused by the vegetation and provides it as boundary conditions for the LES. Large-scale driving forces will be provided by accompanying mesoscale simulations with WRF.Additionally, the critical size of forest gaps with respect to the generation of secondary circulations shall be determined by performing idealized studies with systematically varied gap size. LES data will be analyzed for coherent structures by advanced methods like linear stochastic estimation, empirical orthogonal functions (EOF), proper orthogonal decomposition (POD), and wavelet analysis. Also, virtual eddy-correlation measurements will be done for the sensor positions and footprints will be calculated for them using an LES embedded Lagrangian particle model.