The prediction of fogs is one of the processes not well reproduced by the Numerical Weather Prediction (NWP) models. In particular, the role of turbulence in the formation or dissipation of fogs is one of the physical processed not well understood, and therefore, not well parameterized by the NWP models. Observational analysis of three different periods with fogs at the Spanish Northern Plateau has been carried out. These periods have also been simulated with the Weather Research and Forecasting (WRF) numerical model and their results have been compared to observations. The study includes a comparison of the skill of different planetary boundary layer (PBL) parameterizations, surface layer schemes and a test of the gravitational settling of clouds/fogs droplets option. A statistical analysis of this comparison has been evaluated in order to study differences between the periods and between the various parameterizations used. The model results for each PBL parameterization were different, depending on the studied period, due to differences in the features of each fog. This fact made it difficult to obtain generalized conclusions, but allowed us to determine which parameterization performed better for each case. In general, judging from the models results of liquid water content (LWC), none of the PBL schemes were able to correctly simulate the fogs, being Mellor-Yamada Nakanishi and Niino (MYNN) 2.5 level PBL scheme the best one in most of the cases. This conclusion is also supported by the root mean square error (RMSE) calculated for different meteorological variables.