You might not initially think of fog as a form of severe weather, but when fog sets in and visibility plummets, transportation becomes dangerous.

Zhaoxia Pu

Fog is the second-most-likely cause of aircraft accidents after strong winds, but despite the high impact of fog events and a long history of research, fog prediction remains a long-standing challenge for weather prediction because of complex interactions among the land surface, water, and atmosphere. There’s still a lot of fundamental things about fog that we don’t know.

Zhaoxia Pu, University of Utah professor of atmospheric sciences and Eric Pardyjak, professor of mechanical engineering, hope to change that through a field campaign and scientific research using Utah’s Heber Valley as the laboratory.

For about six weeks, from 7 January to 24 February 2022, Pu, Pardyjak and their colleagues, including scientists from the National Center for Atmospheric Research (NCAR) and the Environment and Climate Change Canada as well as graduate students and undergraduate students from atmospheric sciences and mechanical engineering at the University of Utah, watched a network of sensors on the ground in the Heber Valley along with comprehensive sets of instruments from the NCAR's Erath Observing Laboratory and satellite observations. The valley is bounded by mountains, relatively flat in the basin and features two lakes — Jordanelle and Deer Creek reservoirs. Its conditions, Pu says, are representative of mountain valleys around the world.

On winter nights, cold air pools on the valley floor and creates favorable conditions for several forms of fog, including cold-air pool fog, ephemeral mountain valley cold fog and radiative ice fog. By observing how these different kinds of fog form and dissipate, the researchers are continuing to learn about the meteorological conditions and physical processes governing the formation of fog and improve fog prediction.

The study is funded by a $1.17 million grant from the National Science Foundation.

Now, in a recent paper in the Bulletin of the American Meteorological Society, Pu and her colleagues have published findings via The Cold Fog Amongst Complex Terrain (CFACT) project, conceived to investigate the life cycle of cold fog in mountain valleys.

The overarching goals of the CFACT project, according to the paper’s abstract, 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., sub kilometer scale) NWP models.

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. The paper summarizes the CFACT field campaign, its observations, and challenges during the field campaign, including real-time fog prediction issues and future analysis.

Comprehensive measurements

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. Over its seven-week course, the CFACT field campaign collected a diverse and extensive dataset, including high-frequency radiosonde profiles, tethered balloon profiles, remotely sensed thermodynamic and wind profiles, numerous surface meteorological observations, and microphysical and aerosol measurements. Nine intensive observation periods (IOPs) explored various mountainous weather and cold fog conditions.

Despite the drought in the western United States in 2022, which limited the occurrence of persistent deep fog events associated with persistent cold-air pools that regularly form in higher-elevation Intermountain West basins, the campaign observed highly spatially heterogeneous ephemeral fog and ice fog events. Since ephemeral fog and ice fog are extremely difficult to detect, model, and forecast, CFACT provided unprecedented datasets to understand both types of fog and validate the NWP model.

Meanwhile, the variety of non-fog IOPs provided valuable observations for understanding near-surface inversion, ice crystal formation, moisture advection and transportation, and stable boundary layers over complex terrain, all of which are essential factors related to fog formation. Comprehensive studies are ongoing for an improved understanding of cold fog over complex terrain.