Testing Convective Closures Using Cloud Resolving Model Simulations

English Abstract:

Closure is an important component of mass flux-based convective parameterization schemes and it determines the amount of convection with the aid of large-scale variables. In this study, we evaluate the relationship between commonly used closure variables and convection for a range of global climate model (GCM) horizontal resolutions. We use cloud resolving model simulations of both tropical and midlatitude convective systems from the ARM TWP-ICE and MC3E field experiments to create domain averages representing different GCM horizontal resolutions. Results show that moisture convergence and large-scale CAPE generation (dCAPE)-based closures work well. Other closures, such as CAPE and PBL turbulent kinetic energy (TKE)-based closures do not capture the variation of convection with the large-scale fields. It is found that the correlation between moisture convergence and convective precipitation is largest when moisture convergence leads convection. This correlation weakens as the subdomain size decreases to 8 km or smaller. Although convective precipitation and mass flux increase with moisture convergence or CAPE generation by GCM grid-scale circulation at a given subdomain size, as the subdomain size increases, the rate at which they increase becomes smaller. This suggests that moisture convergence and dCAPE-based closures should scale down the predicted mass flux as GCM resolution increases, implying that scale-awareness should be factored into convective parameterization closures as GCM resolution increases.