Cold Fog Amongst Complex Terrain (CFACT)

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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.