Horizontal Vector Wind Field Measurement with Eye-Safe Elastic Lidar

使用人眼安全弹性激光雷达进行水平矢量风场测量

• 批准号: 0924407
• 负责人: Shane Mayor
• 金额: $ 55.46万
• 依托单位: Chico State Enterprises
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0924407&HistoricalAwards=false
• 关键词: Horizontal; Vector; Wind; Field; Measurement

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).The ability of a scanning eye-safe aerosol lidar to measure the horizontal vector wind field in the atmospheric surface layer will be quantitatively evaluated. This will be done by calculating spatial correlation functions from elastic backscatter lidar scan images displaced in time. This method capitalizes on the wind-induced motion of aerosol features in the lidar?s scan imagery. The primary hypothesis is that the correlation technique will perform well during periods of sufficient turbulence intensity and may fail during periods of strong stability. The hypothesis will be tested by comparing how well the wind vectors from the lidar and in situ anemometers located within the scanned region agree as a function of turbulence intensity and stability as measured by the instrumentation on a tower within the scanned region.In addition to testing the above hypothesis, the techniques refined and evaluated in the first part of the project will then be used for a comprehensive search for statistical relationships between perturbations in the lidar backscatter intensity data and turbulence variables measured in situ on the tower. The result will be a better understanding of the spatial distribution and evolution of phenomena such as turbulent coherent structures, fine-scale gravity waves, and the interplay between turbulence and waves during stable conditions. The processed data set, in the form of images and animations of backscatter and wind fields, will be made publicly available on a website.This research will have several broader impacts. It will form the nucleus of a new interdisciplinary research and education program at the California State University, Chico, where the NCAR REAL resides on long-term loan. Students from a variety of disciplines including physics, computer science, engineering, agriculture and health sciences will benefit from participation in this program. The lidar system and wind measurement capability will be available for other investigators and students to use as new applications for the system develop. The lidar system will be useful wherever there is a need to monitor and predict the dispersion of particulate or hazardous material in the atmosphere. Potential applications include: monitoring the air-shed around air quality sensors; tracking and predicting the dispersion of hazardous material in the atmosphere including releases from chemical and nuclear power plants; monitoring fugitive dust from mining operations; monitoring the application of pesticides over large agricultural areas; monitoring the emissions from agricultural sites such as intensive piggeries; monitoring smoke plumes from agricultural operations such as burning off rice and sugar cane fields; early warning of wildfires and predicting the speed and direction of the fire movement; and monitoring the plumes from industrial sites such as smelters and coal-fired power plants.

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。将定量评估扫描人眼安全气溶胶激光雷达测量大气表层水平矢量风场的能力。这将通过计算空间相关函数从弹性后向散射激光雷达扫描图像位移的时间。这种方法利用了风引起的运动的气溶胶激光雷达的功能？扫描图像。主要的假设是，相关技术将在足够的湍流强度期间表现良好，并可能在强稳定性期间失败。 将通过比较位于扫描区域内的激光雷达和现场风速计的风矢量与扫描区域内塔上的仪器测量的湍流强度和稳定性的函数的一致程度来测试假设。除了测试上述假设外，在该项目的第一部分中改进和评估的技术将用于全面研究激光雷达中扰动之间的统计关系后向散射强度数据和在塔上现场测量的湍流变量。其结果将是更好地了解湍流相干结构、细尺度重力波以及稳定条件下湍流和波浪之间的相互作用等现象的空间分布和演变。处理后的数据集将以后向散射和风场的图像和动画的形式在一个网站上公开提供，这项研究将产生若干更广泛的影响。它将成为加州州立大学奇科分校一个新的跨学科研究和教育项目的核心，NCAR真实的长期贷款居住在那里。来自不同学科的学生，包括物理学，计算机科学，工程学，农业和健康科学将受益于参与该计划。激光雷达系统和风测量能力将可供其他研究人员和学生使用，作为系统开发的新应用。激光雷达系统将在需要监测和预测大气中微粒或危险物质扩散的任何地方发挥作用。潜在的应用包括：监测空气质量传感器周围的空气散逸;跟踪和预测有害物质在大气中的扩散，包括化学和核电站的排放;监测采矿作业的扬尘;监测大片农业地区的杀虫剂使用情况;监测集约化养猪场等农业场所的排放;监测稻田和甘蔗田燃烧等农业作业产生的烟羽;对野火发出预警，并预测火势移动的速度和方向;以及监测冶炼厂和燃煤发电厂等工业场所的烟羽。