Large‐eddy simulation with Lagrangian cloud modeling and large‐scale dynamics (L3$$ {\mathrm{L}}^3 $$) for studying the marine fog life cycle

Abstract Marine fog is a multiscale phenomenon, where the largest to smallest length‐scale ratio is of the order of . Fog formation and evolution depend not only on large‐scale (synoptic and mesoscale) weather systems but also on the intricate interactions and dynamics of smaller‐scale processes, such as micrometeorological and microphysical factors, along with aerosol behavior. Large‐eddy simulation (LES) effectively captures small‐scale processes such as turbulence, microphysics, and radiation, but large‐scale dynamics (LSD) are not considered or are poorly defined. To address this limitation, we modify the LES governing equations by adding specific terms to account for the effects of LSD. Additionally, we employ the Lagrangian cloud model (LCM) approach to analyze microphysical processes within fog. This combined method (LES, LCM, LSD), called coupling, is used to simulate marine fog observed during the Fog and Turbulence Interactions in the Marine Atmosphere (FATIMA) Multidisciplinary University Research Initiative (MURI) campaign. The simulations focused on two specific fog episodes observed on July 12 and 13, 2022. The simulation results for the liquid water content, mean volume diameter, droplet number concentration, and relative humidity were compared rigorously with measurements. The comparison highlighted the model's ability to capture the temporal and spatial characteristics of fog microphysics and dynamics, although some discrepancies in the onset of fog events were noted. The results demonstrate the utility of the coupling method for improving the spatiotemporal representation of fog dynamics. This study reaffirms the critical role of mesoscale and microscale processes in the life cycle of fog, highlighting the importance of coupling during the life cycle of fog. By integrating these scales effectively, the model is capable of simulating fog with realistic microphysical and dynamical properties and hence provides an effective approach for better understanding of fog lifecycle development.