Disentangling the Microphysical Effects of Fire Particles on Convective Clouds Through A Case Study

Aerosol emissions from forest fires may impact cloud droplet activation through an increase in particle number concentrations ("the number effect") and also through a decrease in the hygroscopicity  κ of the entire aerosol population ("the hygroscopicity effect") when fully internal mixing is assumed in models. This study investigated these effects of fire particles on the properties of simulated deep convective clouds (DCCs), using cloud-resolving simulations with the Weather Research and Forecasting model coupled with Chemistry for a case study in a partly idealized setting. We found that the magnitude of the hygroscopicity effect was in some cases strong enough to entirely offset the number/size effect, in terms of its influence on modeled droplet and ice crystal concentrations. More specifically, in the case studied here, the droplet number concentration was reduced by about 37% or more due solely to the hygroscopicity effect. In the atmosphere, by contrast, fire particles likely have a much weaker impact on the hygroscopicity of the pre-existing background aerosol, as such a strong impact would occur only if the fire particles mixed immediately and uniformly with the background. We also show that the differences in the number of activated droplets eventually led to differences in the optical thickness of the clouds aloft, though this finding is limited to only a few hours of the initial development stage of the DCCs. These results suggest that accurately and rigorously representing aerosol mixing and  κ in models is an important step toward accurately simulating aerosol-cloud interactions under the influence of fires.

Aerosol Indirect Effects on the Predicted Precipitation in a Global Weather Forecasting Model

Aerosol indirect effects on precipitation were investigated in this study using a Global/Regional Integrated Model system (GRIMs) linked with a chemistry package devised for reducing the heavy computational burden occurring in common atmosphere–chemistry coupling models. The chemistry package was based on the Goddard Chemistry Aerosol Radiation and Transport scheme of Weather Research and Forecasting with Chemistry (WRF-Chem), and five tracers that are relatively important for cloud condensation nuclei (CCN) formation were treated as prognostic variables. For coupling with the cloud physics processes in the GRIMs, the CCN number concentrations derived from the simplified chemistry package were utilized in the cumulus parameterization scheme (CPS) and the microphysics scheme (MPS). The simulated CCN number concentrations were higher than those used in original cloud physics schemes and, overall, the amount of incoming shortwave radiation reaching the ground was indirectly reduced by an increase in clouds owing to a high CCN. The amount of heavier precipitation increased over the tropics owing to the inclusion of enhanced riming effects under deep precipitating convection. The trend regarding the changes in non-convective precipitation was mixed depending on the atmospheric conditions. The increase in small-size cloud water owing to a suppressed autoconversion led to a reduction in precipitation. More precipitation can occur when ice particles fall under high CCN conditions owing to the accretion of cloud water by snow and graupel, along with their melting.