Novel thermal tracking analysis of aerosol-deep convection interactions



Matsui, Toshihisa — Earth System Science Interdisciplinary Center at University of Maryland
van Lier-Walqui, Marcus — Columbia University

Area of research

Cloud-Aerosol-Precipitation Interactions

Journal Reference

Hernandez-Deckers D, T Matsui, and A Fridlind. 2022. "Updraft dynamics and microphysics: on the added value of the cumulus thermal reference frame in simulations of aerosol–deep convection interactions." Atmospheric Chemistry and Physics, 22(2), 10.5194/acp-22-711-2022.


Computational cloud-process simulations are used to investigate how atmospheric air pollution affects the dynamics and microphysics of isolated deep convection through a novel tracking analysis of cumulus thermals.


In comparison with traditional grid-based analysis, tracking small-scale spherical rising features (i.e., cumulus thermals) provides tight coupling between thermodynamics, cloud droplet, and raindrop formation within deep convective clouds perturbed by different air pollution levels. These results have the potential to serve as a stronger foundation for improving subgrid-scale convective parameterizations.


We investigate how aerosol concentrations modify key properties of updrafts in eight large-eddy-permitting simulations of a case study of isolated convection over Houston, Texas, in which convection is explicitly simulated and microphysical processes are parameterized. Dynamical and liquid-phase microphysical responses are investigated using 1) static cloudy updraft grid cells versus 2) tracked cumulus thermals. Both frameworks revealed that higher aerosol concentrations lead to higher cloud number concentrations and lower rain number concentrations, but they weakly affect convective dynamics. On the other hand, the novel thermal analysis provides more active convective air masses than traditional cloudy updraft grid analysis, especially at upper levels in terms of updraft velocity and cloud microphysics concentrations. To conclude, the novel thermal tracking analysis adds rich quantitative information about the rates and covariability of microphysical processes and thermodynamics throughout tracked thermal life cycles, which can serve as a stronger foundation for improving subgrid-scale convective parameterizations.