A Numerical Study of the Growth of Large Ice Hydrometeors

大冰水凝物增长的数值研究

• 批准号: 1219586
• 负责人: Pao-Kuan Wang
• 金额: $ 38万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1219586&HistoricalAwards=false
• 关键词: Numerical; Study; Growth; Large; Ice

The growth of large ice hydrometeors is a central problem in cloud physics and one that potentially has great impacts on a wide variety of atmospheric processes, particularly in the context of deep convective (thunderstorm-type) clouds. These impacts include the rate and location of riming growth of graupel and hail and the aggregation of snowflakes, which in-turn influence cloud development and ensuing production of precipitation ultimately reaching the ground. The growth of graupel is known to be connected with the electrification of thunderclouds, while costs of hail damage to property and agriculture runs into billions of dollars annually. Snow-related processes impact thunderstorm anvil structures, which have important downstream radiative impacts. Quantitative knowledge of all of these processes and their interactions are required for accurate weather and climate predictions, yet understanding of these processes on the scale of individual particles and their interactions remains limited.This investigator will utilize a commercially available computational fluid dynamics package to solve the Navier-Stokes equation for flow around a target ice particles whose surfaces are defined by an analytical expression, and thereby gain improved descriptions of the collisional growth of large ice particles (in particular graupel and snow aggregates). Numerical models of the fall behavior of these large ice particles as they are accreting other particles (either supercooled droplets or another ice particle) and hence changing their shapes will be developed, as will collisional-growth rate models. Complex combinations of various modes of particle motion including as translation, vibration, and rotation will be explicitly represented so as to more accurately characterize particle trajectories, ventilation coefficients and associated collision efficiencies applicable to real clouds. The intellectual merit of this work centers on an improved understanding of cloud microphysical interactions applicable to convective clouds. Broader impacts will include student education and, ultimately, the potential for improved interpretation of cloud observations through a variety of operational and anticipated research-mode measurements including storm-penetrating aircraft.

大型冰水凝物的增长是云物理学中的一个核心问题，并且可能对各种各样的大气过程产生巨大影响，特别是在深对流（雷暴型）云的背景下。 这些影响包括<$雨和冰雹的速度和位置以及雪花的聚集，这反过来又影响云的发展和随后产生的最终到达地面的降水。 据了解，雹的增长与雷暴云的带电有关，而冰雹对财产和农业造成的损失每年高达数十亿美元。 与雪有关的过程影响雷暴砧结构，这有重要的下游辐射影响。 准确的天气和气候预测需要所有这些过程及其相互作用的定量知识，但在单个粒子及其相互作用的尺度上对这些过程的理解仍然有限。本研究员将利用商业上可获得的计算流体动力学软件包来求解围绕目标冰粒的流动的Navier-Stokes方程，其表面由解析表达式定义，并由此获得对大冰粒（特别是霰和雪聚集体）的碰撞生长的改进描述。 这些大冰粒的下落行为的数值模型，因为它们是吸积其他粒子（无论是过冷液滴或另一个冰粒），从而改变它们的形状将被开发，将碰撞增长率模型。 粒子运动的各种模式的复杂组合，包括平移，振动和旋转将被明确表示，以便更准确地表征粒子轨迹，通风系数和相关的碰撞效率适用于真实的云。 这项工作的智力价值集中在改进适用于对流云的云微物理相互作用的理解。 更广泛的影响将包括学生教育，并最终通过各种业务和预期的研究模式测量，包括风暴穿透飞机，改进云观测的解释的潜力。