Vertical Mixing and Horizontal Transport for Weak-wind Stable Conditions

文献中的新结果极大地改变了我们对夜间稳定边界层的概念框架，也发现了我们对弱风强层化条件的理解的严重不足。相似理论是数值模式中表示湍流混合的基础，但最近对弱风非常稳定条件的分析并不支持这一理论。不在标准相似理论中的其他影响包括：a)在各种尺度上的间歇性，b)从地表逆温层上方切变产生的湍流向下输送，c)在具有强烈层结条件的弱地表非均匀上的显著水平平流，d)在某些情况下比热量输送更有效的动量输送，e)与小尺度中尺度运动，如重力波和曲折运动的耦合。PI正在评估这些影响的作用，以推广湍流通量的常用相似理论，以及相似理论的几种替代方案。这些理论正在扩展，以包括概率分布，以说明在给定的一组外部条件下，当不可预测的重力波和蜿蜒运动也存在时，湍流特征的广泛范围。在这项工作中，他将使用来自20个地点的质量控制的塔通量数据，这些数据已经为各种地表类型和气候条件积累了下来。数据集包括五个通量塔的微型网络，用于检查湍流和中尺度运动的空间结构。用一种新的更仔细的方法计算通量，对于这种弱湍流的检验是必不可少的。智能优点：改进的分析技术和涡旋相关测量网络的结合，为非常稳定的条件下湍流和中尺度曲折/重力波的时空结构及其相互作用提供了新的见解。这些分析提高了我们对湍流的间歇性及其对通量-梯度关系的影响的理解。广泛的影响：这项工作将改进大气模式中湍流混合和中尺度输送的公式，特别是在霜冻破坏和地面雾形成的风险最大的非常弱混合的情况下。这些都是模型在预测表面变量中遭受最大误差的情况。湍流混合和中尺度输送的新公式改进了在污染物浓度积聚最大的夜间弱风条件下大气污染物扩散的模拟。此外，大量的质量控制数据集正在向研究界提供。两名本科生和一名独立资助的国际研究生或博士后研究员正在与这位资深研究员合作这个项目。

New results in the literature have dramatically altered our conceptual framework for the stable nocturnal boundary layer, and also have identified serious inadequacies in our understanding for weak-wind strongly-stratified conditions. Similarity theory, which forms the basis for representation of the turbulent mixing in numerical models, is not supported by recent analyses for weak-wind very-stable conditions. Additional influences not in standard similarity theory include: a) intermittency on a variety of scales, b) downward transport of shear-generated turbulence from above the surface inversion layer, c) significant horizontal advection over even weak surface heterogeneity with strongly-stratified conditions, d) more efficient transport of momentum compared to transport of heat in some situations and e) coupling with small-scale mesoscale motions, such as gravity waves and meandering motions. The PI is evaluating the role of these influences in order to generalize commonly-used similarity theories for turbulent fluxes, and for several alternatives to similarity theory as well. These theories are being expanded to include probability distributions to account for the broad range of turbulence characteristics for a given set of external conditions when unpredictable gravity waves and meandering motions also are present. For this work he will use quality-controlled tower flux data from 20 sites that has been accumulated for a wide variety of surface types and climate regimes. The datasets include five micro-networks of flux towers for examination of the spatial structure of the turbulence and mesoscale motions. Computation of fluxes with a new more careful method is essential for this examination of weak turbulence. Intellectual Merit: The combination of improved analysis techniques and the networks of eddy-correlation measurements yields new insight into the space-time structure of turbulence and mesoscale meandering/gravity waves, and their interaction, for very stable conditions. These analyses improve our understanding of intermittency of turbulence and its influence on the flux-gradient relationship.Broader Impacts: The work will improve formulations of turbulent mixing and mesoscale transport in atmospheric models, particularly for cases of very weak mixing when risk of frost damage and ground fog formation are greatest. These are the cases where models suffer the largest errors in predicted surface variables. The new formulations of turbulent mixing and mesoscale transport improve modeling of dispersion of atmospheric contaminants in weak-wind nocturnal conditions when buildup of contaminant concentrations are greatest. In addition, the massive quality-controlled datasets are being made available to the research community. Two undergraduate students, and an international graduate student or post-doctoral researcher with separate funding, are working with this veteran researcher on this project.