Aerosol-Cloud-Rainfall Interactions and Land-Atmosphere Coupling from Micron to Hectometer Scales in Complex Terrain

Abstract
A coupled large-eddy circulation (LES) Land-Cloud model (CLCM) was built based on CM1 by incorporating spectral bin microphysics (SBM, Duan et al. 2019) and the most recent version of the Duke Coupled Hydrology Model with vegetation (DCHM-V, Liu and Barros 2024). One key goal is to investigate the impact of aerosol-cloud-precipitation interactions (ACPI) and land-atmosphere interactions on the diurnal cycle of clouds, including low-level clouds and fog, as well as precipitation across various scales, with a focus on their influence on the surface energy budget and the climate near the ground. Here we present a real-case simulation in the Southern Appalachian Mountains (SAM) conducted by CLCM with WRF-generated initial and boundary conditions and measured aerosol properties during the Integrated Precipitation and Hydrology Experiment in 2014 (IPHEx) (Barros et al. 2014). The simulation revealed that the land surface plays a crucial role in cloud development, with a distinct shift from intense morning fog to daytime cumulus congestus clouds consistent with satellite and radar observations. Analysis of the evolution of cloud DSDs shows that the model successfully captures the cloud life cycle, including aerosol activation, condensational growth, and enhanced collision-coalescence in the cloud updraft and downdraft regions, consistent with aircraft measurements, and produces raindrop size distributions consistent with disdrometer observations (Wilson and Barros 2014). Importantly, the CLCM successfully captures seeder-feeder interactions (SFI), a key mechanism for enhancing orographic rainfall rates that is not captured in numerical weather prediction models. SFI is quantified via process-rate analysis, which highlights the dominance of coalescence in precipitation formation. The vertical evolution of DSDs shows that the “seeder” raindrops grow more than 1 mm by scavenging small droplets from low-level clouds and fog (“feeder”) as they fall.

Bio
Lihui Ji is a Ph.D. candidate at the University of Illinois Urbana-Champaign, working with Dr. Ana Barros. His research focuses on multiscale cloud and precipitation processes. His work uses direct numerical simulation (DNS) and large-eddy simulation (LES) to investigate hydrometeor dynamics, precipitation microphysics, aerosol–cloud interactions, and land–atmosphere coupling, with the goal of disentangling precipitation processes across scales, from micrometer-scale hydrometeor dynamics to kilometer-scale convection. Particular emphasis is placed on complex terrain, where substantial uncertainties remain.