A comparison of visibility parameterizations using surface observations

Authorities for aviation, marine environments, and surface transportation require more efficient fog forecasting and accurate visibility (Vis) values to reduce financial and human loses. Better fog forecasting can improve both safety and traffic management in critical adverse weather situations. Fog microphysical parameterization schemes in the forecasting models need to be improved for better forecasting skills. A method developed by Gultepe et al (2006) using in-situ observations from the Radiation and Aerosol Cloud Experiment (RACE), representing low-level boundary layer clouds, was suggested as a new parameterization scheme. In their work, visibility is parameterized based on a combined parameter that is obtained using both droplet number concentration (Nd) and liquid water content (LWC). The objective of this work is to test their proposed visibility parameterizations using the observations collected during the Clermont-Ferrand fog project that took place in France during the winters of 2004-2006.