Effects of Turbulence on the Collision-Coalescence Growth of Cloud Droplets

雨的形成机制之一是云滴的碰撞和聚合。 这通常被称为暖雨机制，以区别于扩散增长的过程，扩散增长对于包含冰晶和过冷水滴混合物的低于0摄氏度的云中降水的形成很重要。 长期以来，人们一直推测湍流的空气运动可能会增加水滴碰撞的速度，从而加速降水的形成。 两种效应归因于将倾向于增加液滴碰撞速率的湍流：（1）惯性效应，其中碰撞是由于液滴不能随着气流移出接近的较大液滴的路径而引起的;（2）累积效应，其中湍流中的持续涡流产生较高液滴浓度的区域，其中碰撞速率将增加。 该项目通过直接数值模拟（DNS）计算湍流空气中的水滴运动来分析这些影响。 一个目标是量化和参数化湍流、液滴惯性和重力沉降对液滴碰撞核的组合效应，该量描述了较大液滴在单位时间内超过较小液滴并与之碰撞的概率，假定它们都以单位浓度存在。 另一个目标是应用新的参数化求解随机聚结方程，它描述了液滴光谱的演变，因为液滴相互作用和相互碰撞，以确定湍流缩短沉淀大小的液滴（约0.1毫米）形成的时间的程度。 该项目需要一位计算流体动力学专家和一位云物理学家的合作。 基本上，它带来了承担云物理技术，已开发的多相流分析在工程中。 其结果将是一个更准确的参数化的雨形成的暖雨过程，这可能有助于解释之间的差异，似乎存在目前的理论（其中不包括湍流）和观测到的时间降水形成。

One of the mechanisms by which rain is formed is the collision and coalescence of cloud droplets. This is usually called the warm rain mechanism, to distinguish it from the process of diffusional growth, which is important for the formation of precipitation in clouds colder than 0 degrees C containing a mixture of ice crystals and supercooled water droplets. It has long been speculated that turbulent air motions may increase the rate of droplet collisions and hence speed up the formation of precipitation. Two effects are attributed to turbulence that would tend to increase the rate of droplet collisions: (1) an inertial effect whereby collisions are caused by the inability of a drop to move with the airflow out of the path of an approaching larger drop; (2) an accumulation effect, whereby persistent vortices in the turbulent flow create regions of higher drop concentration, in which the rate of collisions will be increased. This project analyzes these effects by computing the movement of drops in turbulent air by direct numerical simulation (DNS). One objective is to quantify and parameterize the combined effects of turbulence, droplet inertia, and gravitational settling on the droplet collision kernel, a quantity that describes the probability that a larger drop will overtake and collide with a smaller drop in unit time, given that they are both present in unit concentration. Another objective is to apply the new parameterization in solving the stochastic coalescence equation, which describes the evolution of a droplet spectrum as the drops interact and collide with each other, to determine the extent to which turbulence shortens the time for precipitation-sized drops (about 0.1 mm) to form. The project requires the collaboration of a specialist in computational fluid dynamics and a cloud physicist. Basically, it brings to bear on cloud physics techniques that have been developed for the analysis of multiphase flows in engineering. The result will be a more accurate parameterization of rain formation by the warm rain process, which could help to explain discrepancies that seem to exist between current theory (which does not include turbulence) and the observed times for precipitation formation.