Evaluation and Improvement of Turbulence Parameterization inside Deep Convective Clouds at Kilometer-Scale Resolution

Abstract

A challenge for cloud-resolving models is to make subgrid schemes suitable for deep convective clouds. A benchmark large-eddy simulation (LES) was conducted on a deep convective cloud with 50-m grid spacing. The reference turbulence fields for horizontal grid spacings of 500 m, 1 km, and 2 km were deduced by coarse graining the 50-m LES outputs, allowing subgrid fields to be characterized. The highest values of reference subgrid turbulent kinetic energy (TKE) were localized in the updraft core, and the production of subgrid TKE was dominated by thermal effects at coarser resolution (2 and 1 km) and by dynamical effects at finer resolution than 500 m. Countergradient areas due to nonlocal mixing appeared on the subgrid vertical thermodynamical fluxes in the updraft core and near the cloud top. The subgrid dynamical variances were anisotropic but the difference between vertical and horizontal variances diminished with increasing resolution. Then offline and online evaluations were conducted for this deep convective case with two different parameterization approaches at kilometer-scale resolution and gave the same results. A commonly used eddy-diffusivity turbulence scheme underestimated the thermal production of subgrid TKE and did not enable the countergradient structures to be reproduced. In contrast, the approach proposed by Moeng, parameterizing the subgrid vertical thermodynamical fluxes in terms of horizontal gradients of resolved variables, reproduced these characteristics and limited the overestimation of vertical velocity.