Previous studies on convective precipitation forecasting in South China have focused on the effects of multiscale dynamics and microphysics parameterizations. However, limited investigation has been conducted on how uncertainty in aerosol data might cause errors in quantitative precipitation forecast for South China's coastal convection. In this case study, we evaluated the impact of aerosol uncertainties on South China's severe coastal convection using convection‐permitting simulations. We estimated the variability range of aerosol concentrations with observations for the pre‐summer months. The simulation results suggest that the rainfall pattern and intensity change notably when aerosol concentrations are varied. Decreasing the concentration of water‐friendly (WF) aerosols intensifies precipitation through reduced cloud water number concentration and increased droplet size. Increasing the concentration of ice‐friendly (IF) aerosols results in up to 40% increase in vertical velocity and latent heat compared to minimal IF aerosol condition, by enhancing the heterogeneous process and dynamically intensifying convection. Consequently, the simulation with minimal WF and maximal IF aerosol concentrations shows prolonged intense precipitation over the entire life cycle of convection. However, when both WF and IF aerosols are set to minimal concentrations, the simulation produces the maximum peak rainfall rate, which is about 50% stronger than the simulation with the climatological mean concentration, due to an enhanced homogeneous process that results in a higher ice concentration and more efficient ice‐phase precipitation growth. Meanwhile, variation in aerosol concentration affects convection initiation (CI), with a lower concentration of WF aerosol inducing earlier CI onset. Decreasing hygroscopicity leads to higher precipitation.
Previous studies on South China’s convective precipitation forecast focused on the effects of multi-scale dynamics and microphysics parameterizations. However, how the uncertainty in aerosol data might cause errors in quantitative precipitation forecast (QPF) has yet to be investigated. In this case study, we estimate the impact of aerosol uncertainties on the QPF for South China’s severe convection using convection-permitting simulations. The variability range of aerosol concentrations is estimated with past observation for the pre-summer months. Simulation results suggest that the rainfall pattern and intensity change notably when aerosol concentrations are varied. The simulation with low aerosol concentrations produces the most intense precipitation, approximately 50\% stronger than the high-concentration simulation. Decreasing aerosol hygroscopicity also increases precipitation intensity, especially in pristine clouds. The aerosol uncertainty changes alter the number of cloud condensation and ice nuclei, which modifies the altitude and amount of latent heating and thereby modulates convection.
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