A model for predicting fog aerosol size distributions

An accurate model and parameterization of fog is needed to increase the reliability and usefulness of electro-optical systems in all relevant environments. Current models vary widely in their ability to accurately predict the size distribution and subsequent optical properties of fog. The Advanced Navy Aerosol Model (ANAM), developed to model the distribution of aerosols in the maritime environment, does not currently include a model for fog. One of the more prevalent methods for modeling particle size spectra consists of fitting a modified gamma function to fog measurement data. This limits the fog distribution to a single mode. Here we establish an empirical model for predicting complicated multimodal fog droplet size spectra using machine learning techniques. This is accomplished through careful measurements of fog in a controlled laboratory environment and measuring fog particle size distributions during outdoor fog events.