Journal
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY
Volume 102, Issue 2, Pages E244-E272Publisher
AMER METEOROLOGICAL SOC
DOI: 10.1175/BAMS-D-19-0070.1
Keywords
Fog; Aerosols; Atmosphere-land interaction; Atmosphere-ocean interaction; Drop size distribution; Visibility
Categories
Funding
- ONR [N00014-18-1-2472]
- DOE [DE-AC05-76 RL01830]
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C-FOG is a comprehensive bi-national project focused on studying the formation, persistence, and dissipation of coastal fog. Through field observations and modeling, it integrates research across various processes, dynamics, microphysics, and thermodynamics to address the complexity of coastal fog. The project aims to identify and remedy numerical model deficiencies by utilizing a multiplatform framework for interpretation of field observations.
C-FOG is a comprehensive bi-national project dealing with the formation, persistence, and dissipation (life cycle) of fog in coastal areas (coastal fog) controlled by land, marine, and atmospheric processes. Given its inherent complexity, coastal-fog literature has mainly focused on case studies, and there is a continuing need for research that integrates across processes (e.g., air-sea-land interactions, environmental flow, aerosol transport, and chemistry), dynamics (two-phase flow and turbulence), microphysics (nucleation, droplet characterization), and thermodynamics (heat transfer and phase changes) through field observations and modeling. Central to C-FOG was a field campaign in eastern Canada from 1 September to 8 October 2018, covering four land sites in Newfoundland and Nova Scotia and an adjacent coastal strip transected by the Research Vessel Hugh R. Sharp. An array of in situ, path-integrating, and remote sensing instruments gathered data across a swath of space-time scales relevant to fog life cycle. Satellite and reanalysis products, routine meteorological observations, numerical weather prediction model (WRF and COAMPS) outputs, large-eddy simulations, and phenomenological modeling underpin the interpretation of field observations in a multiscale and multiplatform framework that helps identify and remedy numerical model deficiencies. An overview of the C-FOG field campaign and some preliminary analysis/findings are presented in this paper.
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