Hydrodynamic Behavior and Growth Processes of Large Ice Particles in Clouds

准确了解大冰水凝物的降落行为和生长过程对于理解雷暴过程和数值模拟是必要的。它们对云物理学的研究也具有根本的重要性。这些过程包括雹、<$云的边缘生长、雹、<$云与冰晶的碰撞以及雪花的聚集。它们发生在深对流云中，由于其热力和动力作用，影响了深对流云的进一步发展。冰晶和<$球的碰撞被认为与雷雨云的带电有关。冰雹每年给农业和财产造成数十亿美元的损失。在风暴中，雪的聚集体主导着铁砧过程。这些过程的定量知识是准确的天气和气候预测所必需的，但到目前为止，这是知之甚少。智力上的优点：本项目将进行数值研究，以调查各种冰粒类型、形状和大小的大冰粒（、冰雹、有边晶体和雪聚集体）的下落行为和扩散以及碰撞生长。将开发数值模型来模拟这些大冰粒的下落行为，因为它们在改变形状的同时吸积其他粒子。碰撞增长模型也将被发展来研究由于过冷液滴或冰粒的吸积而导致的它们的碰撞增长率。前者涉及数值求解相关的Navier-Stokes方程，以获得下落粒子的流场，这些粒子可能执行复杂的运动，例如平移、振动、旋转等。将求解过冷液滴或冰粒围绕下落冰粒的运动方程，以确定轨迹，从而确定碰撞效率。 本文将计算下落冰粒的通风系数，并求解冰粒周围水汽的对流扩散方程，以确定冰粒的扩散增长率。研究结果将填补云物理学这一基础领域的一个重要空白，并为这些过程如何在云中运行提供必要的定量信息。这些信息可用于云解析模型设计更好的冰增长参数化，以更好地了解对流云动力学。 它们也可以用于更大尺度的天气/气候模式，以改善其参数化，以尽量减少预测的不确定性。 更广泛的影响：研究结果将对我们的社会有直接的影响，因为它们将适用于通过使用中尺度云解析模式和更大尺度的数值天气/气候预测模式来提高我们的天气和气候预测能力。这项研究活动将有助于培养研究生和青年科学家，他们将为大气科学研究作出贡献。研究成果将在科学期刊、会议和公开讲座中传播，以便更广泛的受众了解它们。

Accurate knowledge of the fall behavior and the growth of large ice hydrometeors are necessary for understanding the thunderstorm processes and the numerical modeling of them. They are also of fundamental importance to the study of cloud physics. These processes include the riming growth of graupel and hail, collision between graupel/hail and ice crystals, and the aggregation of snowflakes. They occur in deep convective clouds and it influences the further development of such clouds due to its thermodynamic and dynamic effects. The ice crystal-graupel collision is known to be connected with the electrification of thunderclouds. Hail damage costs billions of dollars annually to agriculture and properties. Snow aggregates dominate the anvil process in storms. Quantitative knowledge of these processes is necessary for accurate weather and climate predictions, but so far this is poorly understood.Intellectual Merit:This project will perform a numerical study to investigate the fall behavior and diffusion and collisional growth of large ice particles (graupel, hail, rimed crystals and snow aggregates) for a wide variety of ice particle types, shapes and sizes. Numerical models will be developed to simulate the fall behavior of these large ice particles as they accrete other particles while changing their shapes. Collision growth models will also developed to study the collision growth rates of them due to accretion of supercooled droplets or ice particles. The former involves solving numerically the relevant Navier-Stokes equations to obtain the flow field of the falling particle that may perform complex motions such as translation, vibration, rotation, etc. The equation of motion of the supercooled droplets or ice particles around the falling ice particle will be solved so as to determine the trajectory and hence the collision efficiency. The computation of the ventilation coefficient of the falling ice particle will be conducted and the convective diffusion equation of water vapor around the ice particles will be solved to determine their diffusion growth rates.The results from the study will fill a major gap in this fundamental area of cloud physics and provide necessary quantitative information on how these processes operate in clouds.Such information can be used by a cloud resolving model to design better ice growth parameterizations to understand better the convective cloud dynamics. They can also be used by larger scale weather/climate models to improve their parameterizations to minimize the prediction uncertainties. Better models will allow forecasters to make better forecasts on severe storms.Broader Impacts:The results of the study will have direct impact to our society as they will be applicable to enhance our capability of weather and climate predictions through the use of mesoscale cloud resolving models and larger scale numerical weather/climate prediction models. The research activity will help training graduate students and young scientists who will contribute to atmospheric science research. The research results will be disseminated in scientific journals, meetings, and public lectures so that wider audience becomes aware of them.