Importance of aerosols and shape of the cloud droplet size distribution for convective clouds and precipitation

作者：Christian Barthlott, Amirmahdi Zarboo, Takumi Matsunobu, Christian Keil · 发表于：Atmospheric chemistry and physics · 年份：2022 · DOI：10.5194/acp-22-2153-2022 · 被引用次数：42 · 研究领域：Atmospheric aerosols and clouds、Atmospheric chemistry and aerosols、Meteorological Phenomena and Simulations

The predictability of deep moist convection is subject to large uncertainties resulting from inaccurate initial and boundary data, the incomplete description of physical processes, or microphysical uncertainties. In this study, we investigate the response of convective clouds and precipitation over central Europe to varying cloud condensation nuclei (CCN) concentrations and different shape parameters of the cloud droplet size distribution (CDSD), both of which are not well constrained by observations. We systematically evaluate the relative impact of these uncertainties in realistic convection-resolving simulations for multiple cases with different synoptic controls using the new icosahedral non-hydrostatic ICON model. The results show a large systematic increase in total cloud water content with increasing CCN concentrations and narrower CDSDs, together with a reduction in the total rain water content. This is related to a suppressed warm-rain formation due to a less efficient collision–coalescence process. It is shown that the evaporation at lower levels is responsible for diminishing these impacts on surface precipitation, which lies between +13 % and −16 % compared to a reference run with continental aerosol assumption. In general, the precipitation response was larger for weakly forced cases. We also find that the overall timing of convection is not sensitive to the microphysical uncertainties applied, indicating that different rain intensities are responsible for changi...