Dynamical Processes of Orographic Cumuli II

地形积云 II 的动力学过程

• 批准号: 0849225
• 负责人: Bart Geerts
• 金额: $ 47.6万
• 依托单位: University of Wyoming
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-10-01 至 2013-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0849225&HistoricalAwards=false
• 关键词: Dynamical; Processes; Orographic; Cumuli; II

In the summer of 2006 a field campaign focused on orographic cumulus convection and boundary-layer circulations was conducted. The field campaign was called CuPIDO (Cumulus Photogrammetric, In-situ and Doppler Observations). This campaign deployed a unique combination of instruments, including an airborne cloud radar, atmospheric soundings, a surface mesonet, and stereo-photogrammetry. The present project involves further analysis of the CuPIDO dataset and builds on research completed in the initial two years following the field campaign.The main objective of the new research is to describe the observed fine-scale vertical and horizontal structure of the radar-observed cloud circulations and reflectivity fields within orographic cumuli congesti, and to use this in combination with flight-level measurements and other CuPIDO data to test the following key hypotheses: 1) Toroidal circulations surround the buoyant cores of growing cumuli. Significant entrainment occurs due to fine-scale instabilities at the updraft interface, and the mixed air is efficiently transferred to the cumulus core by the toroidal circulation, and 2) In places where a cumulus grows in the detritus of older clouds, its growth is enhanced, in particular at levels where the environment is dry (moisture-convection feedback hypothesis). The second objective is to use a high-resolution cloud-resolving model to statistically compare observed vs. modeled cumulus properties and patterns of entrainment and detrainment, and to use the continuous and dynamically consistent model output to assist in the interpretation of the observations, in particular regarding cumulus-environment interactions. The model will be used also in a more idealized way to assess the impact of ambient conditions (wind, wind shear, stable or dry layers) on the evolution of orographic (locked-source) convection.Intellectual Merit. In the past half-century several field studies of cumulus dynamics have been conducted by means of ground-based precipitation radars and aircraft making in situ measurements. The CuPIDO experiment places flight-level observations, collected while penetrating a cumulus, in the context of the radar-derived echo and velocity field, at a resolution of 40 m or better, in both vertical and horizontal planes. This combination constitutes a powerful tool for the study of fundamental cumulus dynamics. In particular, cloud radar data reveal entrainment events at various scales, and close-proximity aircraft data allow assessment of the thermodynamic and cloud microphysical characteristics of these events. The combination of the rich CuPIDO dataset with numerical modeling of orographic convection at resolutions matching that of the cloud radar will improve our understanding of characteristic cumulus properties and evolutions, the patterns and scales of entrainment, and mechanisms of cumulus-environment interaction. Broader impacts. Most warm-season precipitation results from deep convection. Cumulus convection operates over a range of horizontal and vertical scales, both over mountains and elsewhere. Not all scales can be resolved by operational numerical weather prediction models, now or in the foreseeable future. Parameterization of the effect of these unresolved cloud circulations on the larger-scale resolved circulations remains one of the greatest uncertainties in these models and also in climate models. Our analyses and numerical simulations of the fine-scale structure and evolution of cumuli, and of the interaction of cumuli with their environment, should lead to more accurate parameterization of the effects of cumulus convection on the resolved scales of these models.

在2006年夏季进行了一次以地形积云对流和边界层环流为重点的野外活动。这次野外活动被称为CuPIDO（积云摄影测量、原位和多普勒观测）。这次行动部署了独特的仪器组合，包括机载云雷达、大气探测、地面中网和立体摄影测量。目前的项目涉及对CuPIDO数据集的进一步分析，并以实地活动后最初两年完成的研究为基础。这项新研究的主要目的是描述雷达观测到的地形积雨团云层环流和反射率场的精细尺度垂直和水平结构，并将其与飞行水平测量和其他CuPIDO数据相结合，以验证以下关键假设：1)围绕增长积雨团浮力核心的环形环流。明显的夹带是由于上升气流界面的精细尺度不稳定性，混合空气通过环形环流有效地转移到积云核心。2)积云在旧云碎屑中生长的地方，其生长增强，特别是在环境干燥的水平（水分对流反馈假设）。第二个目标是使用一个高分辨率的云分辨模型来统计比较观测到的和模拟的积云的特性以及夹带和夹带的模式，并使用连续和动态一致的模型输出来帮助解释观测结果，特别是关于积云与环境的相互作用。该模式还将以更理想的方式用于评估环境条件（风、风切变、稳定层或干层）对地形（锁定源）对流演变的影响。知识价值。在过去的半个世纪里，通过地面降水雷达和飞机的现场测量，对积云动力学进行了几次实地研究。CuPIDO实验将穿透积云时收集的飞行水平观测数据放在雷达回波和速度场的背景下，在垂直和水平平面上的分辨率为40米或更高。这种组合构成了研究基本积云动力学的有力工具。特别是，云雷达数据揭示了各种尺度的夹带事件，近距离飞机数据允许评估这些事件的热力学和云微物理特征。将丰富的CuPIDO数据集与与云雷达分辨率相匹配的地形对流数值模拟相结合，将提高我们对特征积云特性和演变、夹带的模式和规模以及积云与环境相互作用机制的理解。更广泛的影响。大多数暖季降水是由深层对流引起的。积云对流在水平和垂直尺度范围内发生作用，在山脉和其他地方都有。不是所有的尺度都可以用现在或可预见的将来的数值天气预报模式来解决。这些未解决的云环流对大尺度已解决环流的影响的参数化仍然是这些模式和气候模式中最大的不确定性之一。我们对积云的精细尺度结构和演化，以及积云与环境的相互作用的分析和数值模拟，将有助于在这些模式的分辨尺度上更精确地参数化积云对流的影响。