Fog is characterized by the presence of liquid or solid water particles in the vicinity of Earth’ssurface, that leads to a reduction in visibility to less than 1 km. This reduced visibility posesa significant threat to humans, especially in transportation. However, numerical weatherprediction (NWP) models still frequently fail to predict fog correctly. This can be attributedto small-scale processes, which interact with one another on different scales. The researchpresented in this thesis consists of four research articles and aims to represent, understand,and quantify the significant processes during the life cycle of fog using highly resolved large-eddy simulation (LES).The first study investigates the effect of different microphysical parametrization on simu-lating fog. As found by other research, the number of cloud droplets is a crucial parameterdetermining the fog depth and the time of fog dissipation, which is, however, a fixed para-meter in many numerical models. After major model development to include a prognosticequation of the cloud droplet number concentration and schemes for activation and diffusio-nal growth, the error made by commonly used microphysical parameterizations (cloud bulkmodels) for simulating fog was evaluated. It was found that simulated fog reacts sensitive-ly to the method of calculating supersaturation, which determines the number of activateddroplets.However, bulk cloud models like the one used in the first study are not suitable to remedytheir immanent limitations, such as prescribing the shape of the cloud droplet size distribution(DSD) rather than simulating it. In the second study, an advanced method in cloud modeling(a so-called particle-based method) was applied for the first time to simulate fog. It was foundthat the shape of DSD in fog undergoes a temporal development. Moreover, compared to theparticle-based microphysics, the bulk cloud model tends to overestimate the droplet numberconcentration but underrate droplet sedimentation.The subject of the third study was a model intercomparison of LES and single-columnmodels (SCMs) for a radiation fog event. The study revealed significant differences betweenthe SCMs (which are based on NWP models), but the LES models also showed a non-uniformpicture. The representation of microphysics has been identified as the primary source ofuncertainty in the simulation of fog, but with surface-layer fluxes also contributing to theuncertainty.The final study in this thesis discusses the influence of nocturnal fog on the evolution of thedaytime boundary layer. The simulation results indicate that failing to resolve nocturnal fogleads to a faster boundary layer development, i.e., a higher temperature within the boundarylayer and a higher inversion height during daytime.