Turbulent Collision-Coalescence of Cloud Droplets and its Impact on Warm Rain Formation

云滴的湍流碰撞聚结及其对暖雨形成的影响

• 批准号: 0527140
• 负责人: Lian-Ping Wang
• 金额: $ 52.27万
• 依托单位: University of Delaware
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-08-15 至 2010-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0527140&HistoricalAwards=false
• 关键词: Turbulent; Collision; Coalescence; Cloud; Droplets

The PIs are seeking to quantify the effects of turbulence on the collection kernel of cloud droplets and how this impacts the warm rain precipitation process. Air turbulence could affect the collection kernel through (1) enhanced relative motion due to differential acceleration and shear effects, (2) enhanced average pair density due to local clustering of droplets, and (3) enhanced collision efficiency due to turbulent fluctuations. The levels of enhancements depend, in a complex manner, on the size of droplets (which in turn determines the response time and settling velocity) and the strength of air turbulence as measured by the flow dissipation rate and Reynolds number.The first objective of this research is to parameterize the above effects of turbulence by combining a Hybrid Direct Numerical Simulation (HDNS) approach and a theoretical approach. The HDNS approach integrates an improved superposition method for the disturbance flows due to droplets into a pseudo-spectral simulation of undisturbed air turbulence. This allows for the direct incorporation of hydrodynamic interactions within DNS and computations from first principles of all statistical information related to collision-coalescence. The theoretical approach is based on a successive pair-trajectory approximation and probability distribution function modeling of pair statistics, and will be used to model Reynolds-number effects. The deliverable will be a parameterized collection kernel for different droplet-pair size combinations, flow dissipation rates, and Reynolds numbers. Realistic flow conditions from cumulus cloud observations, e.g., the Small Cumulus Microphysics Study (SCMS) and the Rain In Cumulus over the Ocean (RICO) experiment, will be used in this investigation.The second objective is to study the effects of turbulence on the broadening rate of droplet size spectrum by numerically integrating the kinetic collection equation (KCE) within cloud models, using the enhanced collection kernel developed above. In particular, we will study the time scale during which drizzle drops can be generated from initially narrow size distribution. Our approach is to combine our recently developed numerical method (Linear integral method with Gauss quadrature) for treating KCE with a warm precipitating cloud model (a rising parcel). The goal is to understand and quantify the connection between the above effects of turbulence with observations in warm precipitating clouds.Broader impacts of the research: The research intends to resolve the outstanding question of whether the air turbulence can reconcile the discrepancy between the existing model predictions and observations in cumulus clouds (the size-gap problem). Critical weather phenomena such as aircraft icing and freezing precipitation resulting from warm rain processes are known to have a significant economical impact. The research will also impact other areas of atmospheric science and engineering: such as indirect aerosol effects on weather and climate, spray combustion, powder production, and industrial emissions. The interdisciplinary team from the University of Delaware and the National Center for Atmospheric research allows new theoretical developments and advanced engineering research tools to be efficiently applied to atmospheric processes. The research offers two graduate students and one undergraduate minority student a unique educational experience as they take advantage of the resources at both institutions.

PI正在寻求量化湍流对云滴收集核心的影响，以及这如何影响暖雨降水过程。空气湍流可以通过以下方式影响收集核：（1）由于差分加速度和剪切效应而增强的相对运动，（2）由于液滴的局部聚集而增强的平均对密度，以及（3）由于湍流波动而增强的碰撞效率。增强的水平取决于，在一个复杂的方式，对液滴的大小（这反过来又决定了响应时间和沉降速度）和空气湍流的强度作为测量的流量耗散率和Reynoldsnumber.The的第一个目标，这项研究是parameterized上述湍流的影响相结合的混合直接数值模拟（HDNS）的方法和理论方法。HDNS方法集成了一个改进的叠加方法的扰动流由于液滴到一个伪谱模拟未受干扰的空气湍流。这允许直接纳入DNS内的流体动力学相互作用和计算从第一原则的所有统计信息有关的碰撞聚结。理论方法是基于连续对轨迹近似和概率分布函数建模的对统计，并将被用来建模的金数效应。可交付成果将是一个参数化的收集内核，用于不同的液滴对尺寸组合、流量耗散率和雷诺数。来自积云观测的真实流动条件，例如，小积云微物理学研究（SCMS）和海洋积云降雨（RICO）试验的第二个目标是通过数值积分云模式中的动力学收集方程（KCE），利用上述发展的增强收集核，研究湍流对雾滴谱展宽率的影响。特别是，我们将研究的时间尺度，在此期间，毛毛雨滴可以产生从最初狭窄的尺寸分布。我们的方法是联合收割机我们最近开发的数值方法（线性积分法与高斯求积）处理KCE与暖降水云模式（上升的包裹）。其目的是了解和量化上述湍流效应与暖降水云观测之间的联系。研究的更广泛影响：研究旨在解决空气湍流是否可以调和现有模式预测与积云观测之间的差异（尺寸差距问题）这一悬而未决的问题。已知诸如飞机结冰和暖雨过程导致的冰冻降水等关键天气现象具有显著的经济影响。该研究还将影响大气科学和工程的其他领域：例如气溶胶对天气和气候的间接影响，喷雾燃烧，粉末生产和工业排放。来自特拉华州大学和国家大气研究中心的跨学科团队允许新的理论发展和先进的工程研究工具有效地应用于大气过程。这项研究为两名研究生和一名本科少数民族学生提供了独特的教育体验，因为他们利用了这两个机构的资源。