Turbulence Generation in Common Near-Calm Conditions

常见的近平静条件下湍流的产生

• 批准号: 1115011
• 负责人: Larry Mahrt
• 金额: $ 85.37万
• 依托单位: NorthWest Research Associates, Incorporated
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-10-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1115011&HistoricalAwards=false
• 关键词: Turbulence; Generation; Common; Near; Calm

Turbulence near the earth's surface under low wind speed conditions (which are common to nighttime and other stably stratified conditions) is primarily generated by gravity waves and other small-scale non-turbulent motions. Although such processes have received little attention and are poorly understood, the nocturnal near-calm regime is common, particularly with high-pressure systems over flat terrain and under a wider variety of synoptic conditions in small basins and valleys with weak down-valley slope. The time-averaged surface flux is then dominated by infrequent mixing events of unknown origin. Existing methods of data analysis have generally failed to identify the basic physics of generation of mixing events under such conditions. Proper attribution of the root causes of the mixing events requires more emphasis on spatial variation than provided in existing analysis strategies. This project will provide such emphasis by initially focusing on dense networks of sonic anemometers and auxiliary data to more comprehensively characterize the temporal and spatial variability of the turbulence as well as mean turbulence quantities. Obtained representations will include scale-dependent probability distributions and stochastic models with extreme-value capabilities. Such approaches require very large data sets, which have been recently acquired. Since the non-turbulent motions and event mixing can be site dependent, a more limited version of the analysis will be applied to ~20 different field programs representing a wide range of surface conditions. To obtain more even finer spatial information, the investigator plans to deploy fiber-optic cables capable of providing high density information on temperature fluctuations and video based semi-Lagrangian tracking of machine-generated fog elements, all embedded within a new network of sonic anemometers and pressure sensors. These measurements will be integrated with tower profiles of turbulence quantities and deeper profiling from sodars to examine the generation of mixing events in a quasi-three dimensional framework.The intellectual merit of this effort centers on pioneering work to understand and stochastically describe those complex flow features involving superposition of waves, microfronts and other complex non-deterministic signatures thought to be common under near-calm conditions via application of new observational tools and non-standard analysis techniques. Broader impacts will include contributions toward improved model parameterizations of surface fluxes and dispersion under weak winds conditions and improved ability to anticipate localized surface cooling associated with dense fog formation or frost damage to crops. An existing instructional video of near-surface motions based on machine-generated fog, currently used by a number of universities in boundary-layer course work, will be expanded into a set of more professional instructional videos on local atmospheric flows for broader distribution and use. A joint effort with a local high school will provide media suitable secondary school settings and public demonstrations.

在低风速条件下（常见于夜间和其他稳定分层条件），地球表面附近的湍流主要由重力波和其他小尺度非湍流运动产生。 虽然这种过程很少受到关注，也不太了解，但夜间近平静的状态很常见，特别是在平坦地形上的高压系统和在小盆地和山谷中具有弱下坡的各种天气条件下。 时间平均的表面通量，然后占主导地位的罕见的混合事件的来源不明。 现有的数据分析方法通常无法确定在这种条件下产生混合事件的基本物理过程。 正确归因混合事件的根本原因需要比现有分析策略更强调空间变化。 该项目将提供这样的重点，首先侧重于密集的声波风速计网络和辅助数据，以更全面地表征湍流的时间和空间变化以及平均湍流量。 所获得的表示将包括尺度相关的概率分布和具有极值能力的随机模型。 这些方法需要最近获得的非常大的数据集。 由于非湍流运动和事件混合可能取决于场地，因此将对代表各种表面条件的约20个不同现场项目进行更有限的分析。 为了获得更多甚至更精细的空间信息，研究人员计划部署光纤电缆，这些电缆能够提供关于温度波动的高密度信息，并基于视频对机器生成的雾元素进行半拉格朗日跟踪，所有这些都嵌入在一个新的声波风速计和压力传感器网络中。 这些测量将与湍流量的塔剖面和声雷达的更深剖面相结合，以检查准三维框架中混合事件的产生。这项工作的智力价值集中在开创性工作，以理解和随机描述那些涉及波叠加的复杂流动特征，通过应用新的观测工具和非标准分析技术，微锋和其他被认为在近平静条件下常见的复杂的非确定性特征。 更广泛的影响将包括有助于改进弱风条件下地表通量和扩散的模型参数化，以及提高预测与浓雾形成或霜冻损害作物有关的局部地表冷却的能力。 一些大学目前在边界层课程工作中使用的一个基于机器产生的雾的近地表运动的现有教学录像将扩大为一套关于当地大气流动的更专业的教学录像，以便更广泛地分发和使用。 与当地一所高中共同努力，将提供适合媒体的中学环境和公众示范。