Observations and Modeling of Orographic Cumulus Development Using Data Collected During CuPIDO 2006

在美国国家科学基金会的支持下，PI进行了积云摄影测量、原位和多普勒观测（CuPIDO）的现场阶段，并对收集到的数据进行了初步分析。项目中使用的观测设备包括数码相机、自动地面中网站、基于GPS的气球探测系统和搭载95 GHz机载多普勒雷达的怀俄明州国王航空研究飞机。CuPIDO所基于的基本假设是，地形对流的发生是由于山上边界层和局地地表热通量的辐合，导致局地边界层加深到自由对流的水平，而对流和雷暴的发展是由积云和环境的相互作用控制的。特别是，我们认为，剖面的润湿和/或通过浅对流的作用去除稳定层为深对流提供了有利的环境。干空气对热气流的侵蚀在西南沙漠地区可能更为明显，但对流作为组织对流的一种手段对环境的调节通常可能是重要的。在这项研究中，首席研究员将改进和自动化分割和立体分析技术，并利用这些技术来分析在CuPIDO期间收集的数据。对地表强迫、中尺度上坡流的开始、对流的触发和随后的深部对流的发展进行了描述。通过结合现场、多普勒和摄影测量数据以及云分辨模式的模拟，将提供对流单体结构的详细发展和周围环境的演变。智力优势：目标是通过研究积云夹带/夹带的机制，从浅对流到深对流的过渡时间，以及在不同的切变、稳定性和湿度剖面下积云与环境的相互作用，扩展对积云发展的基本方面的理解。通过自动从图像中提取定量信息，首席研究员将能够处理大量案例，并扩展和概括该主题先前工作的结果。特别是，他将专注于改进由实验室模拟和高分辨率数值模拟产生的经典概念模型。更广泛的影响：除了扩展对积云对流基本原理的理解之外，这些信息将对西南部沙漠的预报员有用。在高架地形上对流边界层的演变在很大程度上是未知的。不同环境条件下对流发展的汇编将使预报员能够将山谷的条件与风暴触发地区的条件联系起来。本项目收集的数据将有助于设计和调整数值天气预报、中尺度和云解析过程模式研究以及大尺度、一般环流和气候模式的云参数化。该项目还依赖于学科之间的协同作用，因为计算机科学和图像处理是分析的重要部分。

Under prior NSF support, the PI conducted the field phase of the Cumulus Photogrammetric, In-situ and Doppler Observations (CuPIDO) and performed preliminary analysis of the collected data. Observational assets employed during the project included digital cameras, automated surface mesonet stations, GPS based balloon sounding systems and the Wyoming King Air research aircraft with 95 GHz airborne Doppler radar. The fundamental hypotheses around which CuPIDO is based are that the onset of orographic convection results from the convergence of boundary layer over the mountain and local surface heat fluxes, leading to local boundary-layer deepening to the level of free convection and that subsequent development of the convection and thunderstorm development is governed by mutual interaction of cumulus and the environment. In particular, it is believed that moistening of the profile and/or that removal of stable layers though the action of shallow convection provides a favorable environment for deep convection. The erosion of thermals by dry air may be more pronounced in the desert southwest, but the conditioning of the environment by convection as a means of organizing convection may be important in general. In this research, the Principal Investigator will refine and automate segmentation and stereo analysis techniques and utilize these to analyze data collected during CuPIDO. A description of the surface forcing, onset of the mesoscale upslope flow, triggering of the convection and subsequent development of deep convection will be obtained. Detailed development of the structure of convective cells and the evolution of the surrounding environment will be provided through the combination of in-situ, Doppler and photogrammetric data along with simulations from a cloud resolving model. Intellectual Merit: The goal is to extend understanding of fundamental aspects of cumulus development by examining the mechanics of cumulus entrainment/detrainment, timing of the transition from shallow to deep convection and interaction of cumulus with the environment under varying shear, stability and moisture profiles. By extracting quantitative information from the images automatically, the Principal Investigator will be able to process large numbers of cases and extend and generalize the results of previous work on this subject. In particular, he will focus on refining classical conceptual models resulting from laboratory analogs and those emerging from high resolution numerical simulations. Broader Impact: In addition to extending understanding of the fundamentals of cumulus convection, this information will be of use to operational forecasters in the desert southwest. The evolution of the convective boundary layer over the elevated terrain is largely unexplored. A compilation of convective development under different environmental conditions will allow forecasters to relate conditions in the valley to those in the regions where the storms are triggered. The data collected during this project will be useful in designing and tuning cloud parameterizations for numerical weather prediction, meso- and cloud resolving process model studies and large-scale, general circulation and climate models. This project also relies on a synergy between disciplines, as computer science and image processing are essential parts of the analysis.