The C-Fog Project: Toward Improving Coastal Fog Prediction

Fog consists of suspended water droplets and ice crystals in the atmospheric boundary layer, formed by favorable collusion of dynamic, microphysical and thermodynamic processes. Socio-economic and defense implications of fog abound, including impacts on ecosystems and agriculture, visibility impairment, disruption of air, marine and ground transportation as well as debasement of electromagnetic propagation, with particular relevance to infrared-based detection and tracking as well as directed energy technologies. A myriad of classifications are used for fog, based on either formation mechanisms, thermodynamic conditions, geographical location, microphysical properties or a mix thereof. The C-Fog project concerns fog in coastal areas (or coastal fog) controlled by the interactions of land, marine and atmospheric processes. Given the inherent complexity of coastal-fog dynamics, previous literature has mostly dealt with case studies with limited microphysical observations, and there is a critical need for research that integrates across fundamental processes (fog life cycle), dynamics (energetics, two-phase flow and turbulence), microphysics (droplet characterization, nucleation) and thermodynamics (radiative mechanisms, cooling, phase changes) through a symbiosis of well-designed field campaigns and modeling. Central to the C-Fog project is a field campaign conducted in eastern Canada in September-October 2018 at two supersites (in Nova Scotia and Newfoundland) rich in fog climatology and conducive to disparate fog types. An array of in situ, path integrating and remote sensing instruments, profilers, and a UAV is deployed, allowing measurements across a swath of space-time scales relevant to fog formation. Instrumented platforms will be located over both land and coastal ocean (aboard a research vessel). Satellite products, mesoscale numerical weather prediction (NWP) model outputs, microscale (direct-numerical and large-eddy) simulations and phenomenological modeling will help interpret fog observations in a multi-scale framework, identify physical mechanisms, test hypotheses, and develop physics-based parameterizations. NWP models (WRF, WRF-CHEM and COAMPS) will be validated vis-à-vis fog observations, and model deficiencies are to be identified. Newly developed physical parameterizations will be implemented in the NWP models and tested. The scope of C-FOG project calls for melding of expertise from a multidisciplinary group of researchers, which are drawn from universities, government laboratories and industry. (This research was funded by the Office of Naval Research Award # N00014-18-1-2472 entitled: Toward Improving Coastal Fog Prediction, C-FOG).