부산대학교 도서관

This paper discusses cloud simulations aiming at quantitative assessment of the effects of cloud turbulence on rain development in shallow ice-free convective clouds. Cloud fields from large-eddy simulations (LES) applying bin microphysics with the collection kernel enhanced by cloud turbulence are compared to those with the standard gravitational collection kernel. Simulations for a range of cloud condensation nuclei (CCN) concentrations are contrasted. Details on how the parameterized turbulent collection kernel is used in LES simulations are presented. Because of the disparity in spatial scales between the bottom-up numerical studies guiding the turbulent kernel development and the top-down LES simulations of cloud dynamics, we address the consequence of the turbulence intermittency in the unresolved range of scales on the mean collection kernel applied in LES. We show that intermittency effects are unlikely to play an important role in the current simulations. Highly-idealized single-cloud simulations are used to illustrate two mechanisms that operate in cloud field simulations. First, the microphysical enhancement leads to earlier formation of drizzle through faster autoconversion of cloud water into drizzle, as suggested by previous studies. Second, more efficient removal of condensed water from cloudy volumes when a turbulent collection kernel is used leads to an increased cloud buoyancy and enables clouds to reach higher levels. This is the dynamical enhancement. Both mechanisms operate in the cloud field simulations. The microphysical enhancement leads to the increased drizzle and rain inside clouds in simulations with high CCN. In low-CCN simulations with significant surface rainfall, dynamical enhancement leads to a larger contribution of deeper clouds to the entire cloud population, and results in a dramatically increased mean surface rain accumulation. These results call for future modeling and observational studies to corroborate the findings.