Vertical Mixing and Horizontal Transport for Weak-wind Stable Conditions

弱风稳定条件下的垂直混合和水平输送

• 批准号: 0607842
• 负责人: Larry Mahrt
• 金额: $ 64.81万
• 依托单位: Oregon State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-10-01 至 2012-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0607842&HistoricalAwards=false
• 关键词: Vertical; Mixing; Horizontal; Transport; Weak

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.

文献中的新结果极大地改变了我们对稳定夜间边界层的概念框架，并且还发现我们对弱风强分层条件的理解存在严重不足。相似理论构成了数值模型中湍流混合表示的基础，但最近对弱风非常稳定条件的分析并不支持相似理论。标准相似性理论中没有的其他影响包括：a）各种尺度上的间歇性，b）从表面逆温层上方剪切产生的湍流向下传输，c）在强分层条件下，即使表面不均匀性很弱，也会出现显着的水平平流， d) 在某些情况下，与热传递相比，动量传递更有效；e) 与小尺度介尺度运动（例如重力波和蜿蜒运动）耦合。 PI 正在评估这些影响的作用，以便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法。这些理论正在扩展到包括概率分布，以解释当也存在不可预测的重力波和蜿蜒运动时给定的外部条件组的广泛湍流特征。在这项工作中，他将使用来自 20 个地点的质量控制塔通量数据，这些数据是针对各种表面类型和气候状况积累的。该数据集包括五个通量塔微网络，用于检查湍流和中尺度运动的空间结构。对于弱湍流的检查来说，采用更仔细的新方法计算通量至关重要。智力优点：改进的分析技术和涡相关测量网络的结合，可以在非常稳定的条件下对湍流和中尺度蜿蜒/重力波的时空结构及其相互作用产生新的见解。这些分析提高了我们对湍流间歇性及其对通量梯度关系的影响的理解。更广泛的影响：这项工作将改进大气模型中湍流混合和中尺度传输的公式，特别是在存在霜冻损坏风险和混合非常弱的情况下地面雾的形成最大。在这些情况下，模型的预测表面变量误差最大。湍流混合和中尺度传输的新公式改进了污染物浓度累积最大时弱风夜间条件下大气污染物扩散的建模。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开展该项目。