RAPID: North Dakota Field Measurement Campaign to Improve Understanding of Fog Processes

雾是一种影响全球许多地区的高影响天气灾害，对道路交通、海洋运输，特别是航空运营造成严重干扰。雾的主要影响是能见度降低，可能导致经济损失、严重的道路交通事故、毁灭性的航空灾难和生命损失。因此，提高对雾的形成和消散的了解具有广泛的社会影响，因为这些知识将改进大气模式，使运输系统更加可靠和有效。这种改进对于无人机系统（UAS）在交通运输中的日常使用尤其重要，因为飞行需要靠近地面，远离操作员的视线。准确和详细的当前和近期大气条件信息，有助于确保UAS平台的安全和有效部署。教育学生提供这些必要的大气信息，使他们为新出现的工作做好准备，并使他们能够提供所需的科学进步。雾的产生和演变是许多大气过程（云、湍流、辐射）的结果，这使得雾的精确建模成为一项挑战。对大气条件的精确测量对于提高对雾过程和相关大气相互作用（云、气溶胶、湍流）的理解是必要的。更好地了解雾过程可以改进数值天气预报模式。该项目将在秋季和春季雾事件高峰期在北达科他州法戈的赫克托国际机场及其周边地区进行为期两个月的密集观测。现场项目将在地面位置、气球、飞机和气象无人机平台上部署一套复杂的气象、云和气溶胶仪器。利用这些机载平台可以对边界层的垂直结构进行详细的观测，这将为科学界提供一个独特的测量数据库进行分析。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Fog is a high-impact weather hazard over many locations worldwide causing serious disruptions to road traffic, marine transport, and especially aviation operations. The main impact of fog is visibility reduction that can lead to financial damages, severe road accidents, devastating aviation disasters, and loss of lives. Therefore, improved understanding of fog formation and dissipation has broad societal impacts since such knowledge will result in improved atmospheric models that enable a more reliable and efficient transportation system. Such improvements are especially critical for routine utilization of Unmanned Aircraft Systems (UAS) in transportation since flights need to be near the ground and out of sight of the operator. Accurate and detailed information on current, and near future atmospheric conditions, help to ensure safe and effective deployment of UAS platforms. Educating students to provide this necessary atmospheric information prepares them for emerging jobs and enables them to provide needed scientific advances.The genesis and evolution of fog is the result of many atmospheric processes (cloud, turbulence, radiation), which make accurate modeling of fog a challenge. Accurate measurements of atmospheric conditions are necessary for improved understanding of fog processes and related atmospheric interactions (clouds, aerosols, turbulence). Obtaining a better understanding of fog processes enables improvements in numerical weather prediction modeling. The project will conduct atmospheric observations during two month-long intensive observational periods at Hector International Airport (Fargo, North Dakota), and the surrounding area, during the peak period of fall and spring fog events. The field projects will deploy a complex suite of meteorological, cloud, and aerosol instruments at surface locations, and on balloon, aircraft, and weatherized UAS platforms. Utilizing these airborne platforms enables detailed observations of the vertical structure of the boundary layer, which will provide a unique database of measurements available to the scientific community for analysis.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.