Why predicting fog is still a mystery for meteorologists?

Fog, a common weather phenomenon, also holds quite a mystery. Particularly in areas of complex terrain like mountainous regions, people have long found fog intriguing and concerning. Meteorologists struggle to predict fog formation with the same accuracy they've achieved for other weather events, even though it poses a major hazard to transportation.

Professor Zhaoxia Pu from the University of Utah is leading a recent study that sheds new light on this issue, their findings from the Cold Fog Amongst Complex Terrain (CFACT) project. A part of the Cold Fog Amongst Complex Terrain (CFACT) project, aims to deepen our understanding of fog formation, with the goal of improving forecasting methods.

Air temperature, humidity, and the terrain itself influence the formation of fog close to the ground. Yet, predicting it still poses a challenge. Complex physical processes result in fog, making it harder to forecast than precipitation, wind, and other stormy events.

“Our understanding is limited. In order to accurately forecast fog we should better understand the process that controls fog formation,” said Professor Pu.

Challenge of predicting fog

The National Science Foundation funded the CFACT project with a $1.17 million grant, involving a team from the University of Utah’s Department of Atmospheric Sciences. The team includes Gannet Hallar and Sebastian Hoch, Eric Pardyjak from the Department of Mechanical Engineering, scientists from the National Center for Atmospheric Research (NCAR), and Dr. Ismail Gultepe from Ontario Tech University, Canada.

The primary objective of the project is investigating the life cycle of cold fog in mountain valleys, particularly in the Heber Valley, which is located about 50 miles southeast of Salt Lake City.

Public safety particularly needs improvements in fog forecasting. Fog reduces visibility significantly, thus posing dangers to all forms of transportation.

It is the second leading cause of aircraft accidents after high winds and is responsible for numerous automobile crashes and disruptions in ferry operations. Between 1995 and 2004, fog-related accidents in the United States resulted in 13,720 deaths.

Using the Numerical Weather Prediction (NWP) model, the researchers processed meteorological observations for weather predictions.

“Fog involves a lot of physics processes so it requires a computer model that can better represent all these processes,” explained Professor Pu. “Because fog is clouds near the ground, it requires a high-resolution model to resolve it, so we need models at a very fine scale, which are computationally very expensive. The current models (relatively coarser in resolution) are not capable of resolving the fog processes, and we need to improve the models for better fog prediction.”

Intensive observation periods 

This research found the ideal location in the Heber Valley, which features typical mountain valley topography. In the winter of 2022, over seven weeks, the team collected data from two major stations, equipped with 100-foot towers and various instruments.

Stations located near Deer Creek Reservoir and along the Provo River gathered data on humidity, wind, visibility, temperature, snow depths, and soil moisture. Multiple satellite sites also contributed to the data collection.

The team oversaw nine observation periods (IOPs) intensively spanning over 24-hour periods. High-frequency radiosonde profiles, tethered balloon profiles, remotely sensed thermodynamic and wind profiles, surface meteorological observations, and microphysical and aerosol measurements were included in these IOPs.

"The variety of non-fog IOPs provided insights into near-surface inversion, ice crystal formation, moisture advection and transportation, and stable boundary layers over complex terrain" is already in active voice.

Researchers are currently conducting this comprehensive study, and they have already begun to unravel the complexities of fog formation in mountain valleys. They hope to improve fog prediction models by understanding the meteorological conditions and physical processes involved.

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