The role of aerosols and meteorological conditions in shaping cloud droplet development in New Mexico summer deep-convective systems

Abstract

The accurate representation of aerosol physicochemical properties is important when describing aerosol–cloud interactions. The Deep Convective Microphysics Experiment (DCMEX) aimed to improve the representation of microphysical processes in deep convective systems. As part of this project, an airborne campaign (July to August 2022) was conducted to characterize the thermodynamics–dynamic–aerosol–cloud system over the isolated Magdalena Mountains in New Mexico, US. Backward dispersion analyses identified a transition in dominant airmass origins from Northwest (NW) continental to Southeast (SE) aged oceanic flow, coinciding with substantial changes in meteorological conditions and aerosol characteristics. The SE-flow period generally exhibited lower lifting condensation levels, enhanced convection, higher boundary layer humidity, and more frequent and intense precipitation, compared to the NW-flow period. During the SE-flow period, aerosol size distributions showed a more pronounced bimodality, characterized by increased Aitken-mode concentrations and fewer but larger accumulation-mode particles, indicating enhanced cloud processing. Submicron aerosols exhibited larger sulfate fractions, more oxidized organics, and greater hygroscopicity. Correspondingly, clouds presented larger droplet sizes and liquid water contents. A bin-microphysics parcel model was also employed to simulate the development of cloud droplets, constrained by airborne observations. Model-observation comparisons highlight the critical role of aerosol entrainment in reproducing the observed broad cloud droplet spectra extending toward small sizes. The results underscore the combined influence of meteorological conditions and aerosol characteristics on cloud microphysics under different flow regimes and emphasize the importance of aerosol entrainment in the development of deep convective clouds. This study provides valuable constraints for improving parameterizations of aerosol–cloud interactions in convective systems.