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

雨形成的机制之一是云滴的碰撞和合并。这通常被称为暖雨机制，以区别于扩散生长过程，扩散生长过程对于在含有冰晶和过冷水滴混合物的低于0摄氏度的云中形成降水很重要。长期以来，人们一直推测湍流空气运动可能会增加液滴碰撞的速率，从而加速降水的形成。两种效应归因于湍流，它们倾向于增加液滴的碰撞率：(1)惯性效应，即由于液滴无法随气流移动出接近的更大液滴的路径而引起的碰撞；(2)积累效应，即湍流中持续的涡旋产生了更高的液滴浓度区域，在该区域，碰撞率将增加。本项目通过直接数值模拟（DNS）计算液滴在湍流空气中的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综合影响，一个描述单位时间内较大液滴超过并碰撞较小液滴的概率的量，假设它们都以单位浓度存在。另一个目标是将新的参数化应用于求解随机聚结方程，该方程描述了液滴相互作用和碰撞时液滴光谱的演变，以确定湍流缩短降水大小的液滴（约0.1 mm）形成时间的程度。该项目需要计算流体动力学专家和云物理学家的合作。基本上，它带来了云物理技术，已经发展为工程中多相流的分析。结果将是一个更准确的暖雨过程降雨形成的参数化，这将有助于解释当前理论（不包括湍流）与观测到的降水形成时间之间似乎存在的差异。

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.