A Review of Coastal Fog Microphysics During C-FOG

• Published in: Boundary-Layer Meteorology
• Main Authors: Gultepe, Ismail, Heymsfield, Andrew J., Fernando, H, Pardyjak, Eric, Dorman, Clive, Wang, Q, Creegan, E, Hoch, Sebastian, Flagg, D, Yamaguchi, R, Krishnamurthy, Raghavendra, Gabersek, S., Perrie, W, Perelet, A, Singh, D K., Chang, R, Nagare, B, Wagh, S, Wang, Sen
• Language: unknown
• Published: 2022
• Subjects: 54 ENVIRONMENTAL SCIENCES; Canada; Newfoundland
• Online Access: http://www.osti.gov/servlets/purl/1837554; https://www.osti.gov/biblio/1837554; https://doi.org/10.1007/s10546-021-00659-5

The goal of this paper is to provide an overview the coastal fog microphysical measurements and to evaluate microphysical parameterizations based on the C-FOG (Toward Improving Coastal Fog Prediction) field project. C-FOG is designed to advance understanding of liquid fog formation, development, and dissipation over coastal environments to improve fog predictability and monitoring. The project took place in Eastern Canada (Nova Scotia, NS and Newfoundland, NL) coastlines and open water environments during August-October of 2018 where environmental conditions play an important role for late season’s fog formation. Visibility (Vis), wind speed (Uh), and turbulence along coastlines are the most critical weather- related parameters affecting marine transportation and aviation. In the analysis, microphysical observations are summarized first and then they are, together with 3D wind components, used for fog intensity (visibility) evaluation. Results suggest that detailed microphysical observations collected at the supersites and aboard Research Vessel (RV) Hugh R. Sharp are useful to develop microphysical parameterizations. The fog life cycle and turbulence kinetic energy dissipation rate were strongly related to each other. The magnitude of 3D wind fluctuations was higher during the formation and dissipation stages. An array of cutting-edge instruments used for data collection provided new insight into the variability and intensity of fog (visibility) and microphysics. It is concluded that further improvements in microphysical observations and parameterizations are needed to improve fog predictability of NWP (Numerical Weather Prediction) models.