Cold Fog Amongst Complex Terrain

Oral Presentation 

Fog and low visibility are the second most common factors in aviation weather-related accidents. Despite its high impacts, fog is very difficult to forecast. Among several types of fog, cold fog forms via various thermodynamic, dynamic, and microphysical processes when the air temperature is less than 0°C. It occurs frequently during the cold season yet is challenging to detect using standard observations and is very difficult to predict. The Cold Fog Amongst Complex Terrain (CFACT) project was conceived to investigate the life cycle of cold fog in mountain valleys. The overarching goals of the CFACT project are to 1) investigate the life cycle of cold-fog events over complex terrain with the 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., subkilometer scale) NWP models. The CFACT field campaign took place in Heber Valley, Utah, during January and February 2022, with support from NSF’s Lower Atmospheric Observing Facilities (managed by NCAR’s Earth Observing Laboratory), the University of Utah, and Ontario Technical University. A network of ground-based and aerial in situ instruments and remote sensing platforms were used to obtain comprehensive measurements of thermodynamic profiles, cloud microphysics, aerosol properties, and environmental dynamics. Nine intensive observation periods (IOPs) explored various mountainous weather and cold-fog conditions. Field observations, NWP forecasts, and large-eddy simulations provided unprecedented data sources to help understand the mechanisms associated with cold-fog weather and to identify and mitigate numerical model deficiencies in simulating winter weather over mountainous terrain. This presentation summarizes the CFACT field campaign, its observations, challenges in fog prediction and recent results in data analysis, modeling and data assimilation, and model validation. 

[Reference: Pu, Z., E. Pardyjak, S. Hoch, I. Gultepe, A. G. Hallar, A. Perelet, R. Beal, G. CarrilloCardenas, X. Li, M. Garcia, S. Oncley, W. Brown, J. Anderson, J. Witte, A. Vakhtin, 2023: Cold Fog Amongst Complex Terrain. Bulletin of the American Meteorological Society. 104, E2030-E2052. https://doi.org/10.1175/BAMS-D-22-0030.1 ].