Polarimetric Radar Convective Cell Tracking Reveals Large Sensitivity of Cloud Precipitation and Electrification Properties to CCN

摘要

Hypotheses have been proposed for decades about the effect of activated cloud condensation nuclei (CCN) on delaying the warm rain process, invigorating deep convective cloud vertical development, and enhancing mixed‐phase processes. Observational support has been only qualitative with mixed results due to the lack of regional measurements of CCN concentration (N_(CCN)), while simulations have not produced a robust consensus. Quantitative assessments of these relationships became possible with the advent of N_(CCN) retrievals from satellites; when combined with measurements by polarimetric radar and Lightning Mapping Array (LMA), tracking convective cells observed on radar and examining precipitation properties throughout the cells' life cycle has permitted the study of the impact of N_(CCN) on cloud and precipitation characteristics. We composited more than 2,800 well‐tracked cells in the Houston region and stratified them by N_(CCN), convective available potential energy (CAPE), and urban/rural locations. The results show that increased N_(CCN) invigorates the convection until saturation near N_(CCN) = 1,000 cm~3; increasing N_(CCN) from ~400 to an optimum of ~1,000 cm~3 increases lightning activity by an order of magnitude. A further increase in CCN decreases lightning rates. Adding CAPE enhances lightning only under lowN_(CCN) (e.g., less than 500 cm~3). The presence of the urban area enhances lightning for similarN_(CCN) concentrations, although this applies mainly under low N_(CCN) conditions. The urban heat island as manifested by cloud base height cannot explain this observation. It is suspected that the urban ultrafine aerosols contribute to the storm electrification. Plain Language Summary Deep convective clouds are propelled by rising air currents and are composed of cloud droplets that nucleate on CCN aerosols. Isolating the effects of CAPE and N_(CCN) on cloud properties has been an unresolved challenge. Tracking the time‐height evolution of a large n