The Role of Parameterized Momentum Flux on Biases in Tropical Cyclones and the Mean State in the Community Atmosphere Model

With enhanced computational capacity, the treatment of subgrid processes in global Earth System Models (ESMs) has grown increasingly complex. Despite these enhancements, critical biases remain in the modeling of fundamental processes that govern both the mean climate and the development of extreme weather phenomena of high societal impact. Due to their potential to be better resolved in the next generation of ESMs, tropical cyclones (TCs) are extremes of particular interest. 

The importance of the parameterization of momentum flux within the boundary layer (PBL) for modeled TC structure has been established for numerical models run at a variety of spatial scales. However, few studies have specifically explored the modulation of TC structure by the PBL parameterization in a coarser-resolution ESM. In this study, we evaluate the role of the PBL scheme on modeled TC structure in the Community Atmosphere Model version 6 (CAM6), which is the atmospheric component of the Community Earth System Model version 2 (CESM2). CAM6 employs the Cloud Layers Unified by Binormals (CLUBB) scheme. To enhance generalizability of turbulent processes, we apply an experimental version of CLUBB (CLUBBX) with a prognostic formulation of momentum flux and a regime-specific formulation for the dissipation of turbulent eddies.  

We perform a sensitivity analysis, the Morris one-at-a-time (MOAT) method, to evaluate the influence of various tunable CLUBBX input parameters on process-based metrics that characterize TC structure in an idealized framework. We find that certain tunable CLUBBX parameters controlling vertical turbulent mixing in the PBL modulate key TC metrics like jet height, inflow angle, and surface heat flux. We further demonstrate that targeted perturbations to these influential parameters can reduce established ESM biases in modeled TC structure. 

However, in a global ESM, the accurate depiction of individual TCs should not come at the expense of the model’s depiction of the mean climate. Therefore, it is important to understand how the calibration of CAM6-CLUBBX impacts other aspects of the global and regional climate. We therefore repeat the MOAT sensitivity analysis on global ESM simulations to evaluate how these CLUBBX input parameters impact process-based climate metrics on regional and global scales. We leverage an ensemble approach with short, initialized runs (Betacast) to allow for computational tractability.  

We find that CLUBBX parameters that influence TC structure also influence various regionally and globally-averaged climate metrics, including thermodynamic profiles, cloud-radiative forcing, and surface wind stress, at short timescales (3 days). We further show that targeted perturbations to a handful of these influential input parameters can reduce global and regional biases in CAM6-CLUBBX at decadal timescales. We explore physical mechanisms for these demonstrated parameter sensitivities and discuss practical implications of targeted model tunings for long-term climate simulations.