Cold Fog Amongst Complex Terrain (CFACT)

这个名为“复杂地形中的冷雾”（CFACT）的项目是为了研究山谷中冷雾的形成。雾由微小的水滴或冰晶组成，悬浮在地球表面或附近的空气中，被认为是一种低洼的云。雾在高海拔复杂地形上形成的频率与水体上一样高，但人们对雾的了解较少。由于雾对能见度的影响，它是仅次于强风事件的第二大与天气有关的航空事故的常见原因。雾预报对人类活动、交通、空气质量、人类健康和农业都有重大影响。尽管雾和历史雾研究的影响，雾预报仍然是天气预报的一个挑战，因为在雾的形成过程中，陆地、水和大气条件之间复杂的相互作用。雾预报技术差反映了对雾的形成、发展和消散缺乏认识，这是研究的重点。预计本研究将有助于改善山区的雾预报，提高公众对雾天气状况的认识，并为决策提供信息。该项目涉及国内和国际多个机构的参与，在课堂和实地进行研究生和本科生培训。CFACT项目的总体目标是：1)利用最新的观测技术研究复杂地形下的冷雾发展和环境条件；2)改进数值天气预报（NWP）模型中使用的微物理参数化和能见度算法；3)为当前和下一代（如亚公里尺度）NWP模型开发数据同化和分析方法。该实地项目将于2022年1月至2月在犹他州Heber Valley进行，部署地面原位仪器和遥感平台网络，以获得热力学剖面、云微物理、气溶胶的物理和化学性质以及环境动力学的综合测量。天气研究与预报（WRF）模式具有多种物理参数化和陆地-大气耦合数据同化能力，将有助于改进NWP模式的雾预报研究。预计这些努力将导致1)提高对复杂地形中冷雾过程的理解，2)评估与能见度预测相关的影响冷雾微物理的整体成核条件，3)识别与非均匀复杂地形中冷雾生命周期相关的微观到天气尺度运动学和热力学过程的知识空白，4)理解物理(例如，粒子生长，形成、凝结、辐射)和雾事件生命周期中的动力机制（如湍流、垂直空气速度和波动）；5)评估地表条件，特别是地面积雪如何影响近地表和边界层大气过程，包括地面辐射平衡在冷雾形成和演变中的关键作用；6)改进微尺度到中尺度的nwp模式模拟。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。

The project, Cold Fog Amongst Complex Terrain (CFACT), is to investigate cold fog formation in mountain valleys. Fog consists of tiny water droplets or ice crystals suspended in the air at or near the Earth’s surface and is considered as a type of low-lying cloud. Fog forms in high-elevation complex terrain as frequently as over water bodies but is less understood. Because of its impacts on visibility, fog is the second most common cause of weather-related aviation accidents after strong wind events. Fog forecasts have significant impacts on human activities, transportation, air quality, human health, and agriculture. Despite the impacts of fog and historical fog research, fog prediction remains a challenge for weather prediction because of complex interactions between land, water, and atmospheric conditions in fog formation. Poor fog forecasting skills reflect a lack of understanding of fog formation, development, and dissipation, which is the focus of the research. This study is expected to contribute to improving fog forecasting in mountainous regions, enhancing public awareness of fog-weather conditions, and information for decision-making. The project involves the participation of multiple institutions nationally and internationally with graduate and undergraduate training in both classrooms and the field.The overarching goals of the CFACT project are to 1) investigate cold fog development and environment conditions in complex terrain with latest observation technology, 2) improve microphysical parameterizations and visibility algorithms used in numerical weather prediction (NWP) models, and 3) develop data-assimilation and analysis methods for current and next-generation (e.g., sub-kilometer scale) NWP models. The field project will be conducted in Heber Valley, Utah, during January and February 2022 with deployment of a network of ground-based in-situ instruments and remote sensing platforms to obtain comprehensive measurements of thermodynamic profiling, cloud microphysics, physical and chemical properties of aerosols, and dynamics of the environment. The Weather Research and Forecasting (WRF) model with various physical parameterizations and coupled land-atmosphere data assimilation capabilities will be used to facilitate the studies for improved fog prediction with NWP models. It is anticipated that the efforts will result in 1) improved understanding of cold-fog processes in complex terrain, 2) an evaluation of the bulk nucleation conditions that affect cold-fog microphysics related to visibility prediction, 3) identification of knowledge gaps in the micro- to synoptic- scale kinematic and thermodynamic processes associated with cold-fog life cycles in heterogeneous complex terrain, 4) understanding of interactions between physical (e.g., particle growth, nucleation, condensation, radiation) and dynamic mechanisms (e.g., turbulence, vertical air velocities, and wave motions) during the lifecycle of a fog event, 5) an evaluation of how land-surface conditions, especially snow on the ground, affect near-surface and boundary-layer atmospheric processes including the critical role of the surface radiative balance in cold-fog formation and evolution, and 6) improvement of microscales to mesoscales NWP-model simulations.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.