Intercomparison of single-column numerical models for the prediction of radiation fog

Abstract

The short-term forecasting of fog is a difficult issue that can have a large societal impact. Radiation fog appears in the surface boundary layer, and its evolution is driven by the interactions between the surface and lower layers of the atmosphere. Current NWP models poorly forecast the life cycle of fog, and improved NWP models are needed before improving the prediction of fog. Six numerical model simulations are compared for two cases from the Paris-Charles de Gaulle (Paris-CdG) fog field experiment. This intercomparison includes both operational and research models, which have significantly different vertical resolutions and physical parameterizations. The main goal of this intercomparison is to identify the capabilities of the various models to forecast fog accurately. An attempt is made to identify the main reasons behind the differences among the various models. This intercomparison reveals that considerable differences among models exist in the surface boundary layer before the fog onset, particularly in cases with light winds. The lower-resolution models crudely forecast the nocturnal inversion, the strong inversion at the top of the fog layer, and the interactions between soil and atmosphere. This intercomparison further illustrates the importance of accurate parameterizations of dew deposition and gravitational settling on the prediction of fog.