The relevant physical processes for the life cycle of radiation fog are influenced by a multitude of physical processes, like radiative cooling/heating, turbulent mixing, and microphysics, which all interact on different scales. In particular, microphysical processes are highly parameterized in NWP models and respective parameterizations are usually not designed especially for fog layers. However, an improved fog prediction is an essential task for safety reasons in transport as well as for economic needs.
In this talk we present results from a 3D large-eddy simulation study of radiation fog with an embedded Lagrangian cloud model (LCM) that allows resolving all microphysical processes relevant for fog by first principles instead of parameterizing them. These explicitly simulated processes include, among others, an improved advection scheme for particles with resolved droplet sedimentation, size-resolved activation and diffusional growth representation, and on-demand collision and coalescence processes.
The LCM is based on the so-called superdroplet method, in which one simulated particle (superdroplet) represents a large number of real droplets or aerosols.
By using this innovative approach it was possibly for the first time to explicitly simulate the development of the 3D cloud droplet size distribution (DSD) in a fog layer. In this talk we will demonstrate that our results provide new insights into the question of where and when unimodal or, as is often assumed, bimodal DSDs occurs and which parameters essentially influence the shape of the fog droplet spectra. Finally, activation and diffusional growth of fog droplets, which are key processes for fog were investigated in more detail. The ratio of activated and unactivated (but maybe swollen) cloud condensation nuclei, e.g., was determined for different aerosol environments which is typically overestimated in bulk-approaches.
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