Improving dynamical assumptions in deep convective parameterizations

Abstract:

This research presents a new deep convective parameterization that determines cloud characteristics based on an assumed cloud size distribution. The vertical profiles of cloud properties are determined by analytic equations, which formulate entrainment with an inverse relationship to cloud width. In line with recent studies of large eddy simulations, cloud widths are assumed to be constant width height and mass flux characteristics of the clouds are therefore regulated by the vertical velocity profile. The parameterization is configured to work with existing cloud base mass flux closure formulations, with the closure predicting the total cloud area rather than the cloud base mass flux directly. Analytic formulae are also used to connect the vertical wind shear magnitude to the cloud size distribution, wherein larger shear magnitudes result in more numerous large updrafts than weaker shear magnitudes, which is in line width recent research results. Our model is compared against a 10 deep convective large eddy simulations with varying thermodynamic and vertical wind shear profiles. Results show dramatic improvements in the prediction of normalized vertical mass flux M, detrainment, and the properties of detrained air over the existing Zhang and McFarlane (1995) scheme. In particular, the new model is able to correctly portray the transition from a bottom-heavy M profile in weakly sheared environments, to a top-heavy M profile in strongly sheared environments.