EAGER: Collaborative Analysis of Doppler Lidar Data from Canopy Horizontal Array Turbulence Study (CHATS)

与大气边界层结构和运动的许多遥感测量来源一样，多普勒激光雷达数据由于其庞大和高度详细的性质以及可能受到干扰信号(例如从地球下表面和/或植物冠层返回的信号)的污染，对分析构成了巨大的挑战。这一严格范围的研究工作将支持一位精通激光雷达测量的首席研究员和美国国家科学基金会国家大气研究中心的一位冠层诱导湍流专家之间的合作，以寻求改进的技术，以精确而经济有效的手段，更自动地处理先前在2007年冠层水平阵列湍流研究(CHATS)期间在NSF支持下收集的激光雷达数据。这项工作的智力优势集中在开发和应用预期相干结构(如滚涡和其他在大涡模拟中明显存在的现象和通过其他手段)的理想化模型，以提供一个节省劳动力的框架，在该框架中，径向速度测量可能被更智能地处理和解释。这将反过来支持提取植物冠层上方负责与行星边界层交换动量和痕量气体(如二氧化碳)的相干结构的改进表示。在聊天期间获得的冠层内串联高分辨率湍流通量测量的可用性，以评估这一以前未经证实的分析方法，代表了一种潜在的高回报研究方法。这一努力的更广泛影响包括改善下游关于生物地球化学循环和低层大气湍流来源的知识，以及加强首席研究人员的课堂教育工作。

Like many sources of remotely-sensed measurements of atmospheric boundary layer structure and motions, Doppler lidar data present a formidable analysis challenge both owing to their voluminous and highly detailed nature and potential for contamination by interfering signals such as those returned from the earth's underlying surface and/or plant canopies. This tightly-scoped research effort will support collaborations between a principal investigator who is well versed in lidar measurements and a canopy-induced turbulence expert at NSF's National Center for Atmospheric Research to pursue improved techniques for accurate yet cost-effective means for more automated processing of lidar data previously collected with NSF support during the Canopy Horizontal Array Turbulence Study (CHATS) in 2007.The intellectual merit of this effort centers on development and application of idealized models of expected coherent structures (such as roll vortices and other phenomena evident in large-eddy simulations and via other means) to provide a labor-saving framework in which raw radial velocity measurements may be more intelligently processed and interpreted. This will in-turn support extraction of improved representations of coherent structures above plant canopies that are responsible for exchange of momentum and trace gases (such as CO2) with the planetary boundary layer. The availability of tandem in-canopy, high-resolution turbulent flux measurements obtained during CHATS to evaluate this previously unproven analysis approach represents a potentially high-payoff research approach. Broader impacts of this effort include improved downstream knowledge of biogeochemical cycles and sources of low-level atmospheric turbulence, as well as enhancements to the lead investigator's classroom education efforts.