Collaborative Research: Integrating Models and Observations to Assess Effects of Turbulence on Warm Rain Initiation

虽然人们认为“暖雨”过程--在这一过程中，冰相微物理对降水大小的粒子的发展几乎没有作用--占所有热带降水的三分之一，但其确切机制仍然存在一些不确定因素。特别是，经典的凝聚增长和碰撞-合并伴随着重力沉降的理论无法解释经常观察到的云中雨的快速发展，这些云的温度限制在0摄氏度以下。人们逐渐认识到，湍流可能在加速这一过程中发挥关键作用，但由于缺乏定量研究方法，很难实现可实现的预测。最近在理论和计算能力方面的进展使得能够更定量地评估湍流对碰撞-合并速率的影响，并且已经发展了几个初步的湍流收集参数。这项研究的目标是：(A)将真实的湍流驱动的收集(即液滴增长)的表示纳入使用bin微物理方案的云行为的大涡模拟(LES)模式中，并随后(B)使用现有的真实云的现场观测来评估结果预报，以确定这种新表示的过程在哪些条件下影响和改进模式预报。由于海洋层积云的生命周期很长，而且有大量高质量的观测数据可供进行真实世界模式的比较，因此将重点介绍海洋层积云。将使用混合直接数值模拟(DNS)方法来开发低到中等平均流耗散率条件下的湍流碰撞-合并的更准确的参数化，并将探索将这种参数化纳入大涡模拟框架的统计方法。这一方法将得到雷诺数对气流影响的现象学模拟的补充，在这样做的过程中，LES模型将得到改进，以考虑不同的云卷吸混合情景。这项研究的学术价值将集中在更准确和系统地演变湍流对现实层积条件的影响，并改进对我们目前以预测模式定量表示此类影响的能力的评估。这项工作的更广泛影响将包括发展最终应适用于其他类型云(例如，更活跃的积云)的研究结果，改进更粗粒度的数值天气预报和气候模式中暖雨发展的定量表示，以及通过加强云微物理和计算科学之间的协作。这一环境将为两所相关院校的本科生和研究生提供一个充满活力和多方面的教育和培训场所。

While the "warm rain" process--in which ice-phase microphysics play little or no role in development of precipitation-size particles--is thought to account for as much as one-third of all tropical precipitation, yet a number of uncertainties remain regarding its exact mechanisms. In particular, the classic theory of condensational growth followed by collision-coalescence accompanying gravitational settling is unable to explain the oft-observed rapid development of rain in clouds confined to temperatures warmer than 0 degC. It has gradually become recognized that turbulence could play a critical role in accelerating this process, but realizable predictions have been difficult to achieve because quantitative research approaches are lacking. Recent advances in theory and computational capacity have enabled more quantitative assessment of turbulence effects on the collision-coalescence rate, and several preliminary parameterizations of turbulent collection have been developed. The goals of this research are to (a) incorporate representation of realistic turbulence-driven collection (i.e. droplet growth) in a large-eddy simulation (LES) model of cloud behavior using a bin microphysical scheme, and subsequently (b) to evaluate resulting predictions using existing in situ observations of real clouds to identify those conditions under which this newly-represented process affects and improves model predictions. Owing to their long lifecycle and a large amount of high-quality observational data available to facilitate real world-model comparisons, marine stratocumulus clouds will be emphasized. A hybrid direct numerical simulation (DNS) approach will be used to develop more accurate parameterization of turbulent collision-coalescence in conditions of low-to-intermediate mean flow dissipation rates, and statistical methods to incorporate such a parameterization into the LES framework will be explored. This approach will be complemented by phenomenological modeling of Reynolds number effects on airflow, and in so doing the LES model will be improved to allow for differing cloud entrainment mixing scenarios. The intellectual merit of this study will center on a more accurate and systematic evolution of the effects of turbulence on realistic stratocumulus conditions and improved assessment of our current ability to represent such effects quantitatively in a predictive mode. Broader Impacts of the effort will include development of findings that should ultimately be applicable to other types of clouds (e.g., more vigorous cumulus) and improved quantitative representation for warm-rain development in more coarse-grained numerical weather prediction and climate models, as well as through enhanced collaboration across the cloud microphysics and computational sciences. This setting will provide a vibrant and multifaceted education and training ground for a mix of undergraduate and graduate students at the two involved institutions.