Can models represent aerosol-convection interactions if the microphysics is uncertain?

Abstract:

Aerosols affect deep convection through their influence on cloud and precipitation microphysics over a wide range of spatiotemporal scales. Despite their important microphysical effects, studies of aerosol-convection interactions often focus on the sensitivity of an idealised model with a single microphysics representation to perturbations of cloud condensation nuclei (CCN) or cloud droplet number concentration (CDNC). However, this approach assumes a reliable representation of microphysical pathways.

In this study we investigate the robustness of simulated aerosol effects on convection across different microphysics representations. High-resolution convection-permitting simulations are performed using the WRF model in three configurations. For each case we compare two frequently used double-moment bulk microphysics schemes and investigate the cloud system response to CDNC perturbations.

Microphysics representation dominates over response to CDNC in driving differences in the simulated cloud morphology and precipitation. Moreover, cloud and precipitation responses to CDNC are found not to be robust either between schemes or between cases. In a warm-rain case, autoconversion is shown to be the dominant pathway behind cloud and precipitation differences, but other pathways dominate in other regimes.

These results have significant implications for future modelling studies of aerosol-convection interactions.