Tropical Cyclones in CAM7: Assessing the Impact of Prognostic Momentum Fluxes and Convective Parameterization at Global and Storm Scales

Accurately simulating tropical cyclones (TCs) in global climate models remains a key challenge due to not only multiscale interactions that govern storm genesis, intensity, and structure, but computational constraints that limit model grid spacing. Here we evaluate TC representation in a development version of the Community Atmosphere Model, version 7 (CAM7), which introduces several major updates, including higher vertical resolution, a revised Zhang-McFarlane deep convection scheme, and a new prognostic formulation for turbulent momentum fluxes in the boundary-layer scheme CLUBB. Using a suite of globally-uniform and variable-resolution simulations at 0.25deg grid spacing, we assess both large-scale statistics (global and basinwise TC frequency) and storm-scale characteristics (inflow angle, inflow depth, and wind structure).

CAM7 with prognostic momentum fluxes produces improved spatial patterns of TC activity and more realistic intensity metrics compared to prior CAM generations. However, default configurations overproduce storms by roughly a factor of two. By increasing the parameterized CAPE consumption by deep convection during TC genesis, we achieve a ~40% reduction in global TC counts and improved agreement with observed basin distributions. At the storm scale, we reduce boundary-layer diffusivity, leading to stronger tangential winds, larger inflow angles, and shallower inflow layers, consistent with idealized f-plane sensitivity experiments and more in line with both observations and large-eddy simulations.

These results demonstrate that targeted parameter tuning in deep convection and boundary-layer turbulence schemes can substantially improve both the frequency and structure of simulated TCs in CAM7, advancing its capability for high-resolution climate and weather prediction applications.