Evaluating the Role of Parameterized Momentum Flux on the Global Climate in the Community Earth System Model

With enhanced computational capacity, the treatment of subgrid processes in global Earth System Models (ESMs) has grown increasingly complex. However, despite these enhancements, key biases remain in the depiction of fundamental processes that govern both the mean climate and the development of extreme weather phenomena. Owing both to their societal impacts and potential to be resolved in the next generation of global ESMs, tropical cyclones (TCs) are extreme weather features of particular interest.

Prior studies have shown that the parameterization of momentum flux within the boundary layer (PBL) has an appreciable influence on the modeled structure of TCs. However, in a global ESM, the accurate depiction of individual TCs should not come at the expense of the model's depiction of the global climate. Therefore, it is important to understand how the tuning of input parameters in the ESM's PBL scheme impacts other aspects of the global climate.

Here, we assess the influence of the PBL scheme on various global climate metrics in the Community Atmosphere Model version 6 (CAM6), which is the atmospheric component of the Community Earth System Model version 2 (CESM2). CAM6 uses the Cloud Layers Unified by Binormals (CLUBB) scheme to parameterize PBL turbulence. A sensitivity analysis, the Morris one-at-a-time (MOAT) method, is performed to characterize the response of global climate metrics to perturbing the values of selected input parameters in CLUBB. We specifically focus on a handful of CLUBB input parameters that were found to be influential for modeled TC structure in a previous study.

We find that input parameters that have an appreciable impact on modeled TC structure in idealized CAM6-CLUBB experiments also impact the modeled global climate, including the general circulation and cloud-radiative forcing. We also demonstrate that parameter sensitivity varies regionally, largely due to differences in the background atmospheric environment, surface forcing, and other model parameterizations. We explore pathways through which biases in parameterized momentum flux in the PBL grow upscale to affect the global climate. We discuss using a balanced model improvement approach to find a combination of input parameter values that improve the depiction of TCs without adversely affecting the rest of the global climate.