Earth System Models (ESMs) have a large number of tunable parameters in need of calibration. Uncertainty in the values of these parameters - particularly those associated with clouds and aerosol - can lead to a large spread in future climate projections. 

Here we addresses a critical step needed to improve model calibration: constraining E3SM model parameters from observations, particularly those related to cloud feedbacks and the pattern effect

We demonstrate that tunning to the radiative response to El Nino has the potential to help discriminate between optimal parameters, complementing efforts to tune to climatology. We also demonstrate that PPE efforts to reduce parametric uncertainty can help alleviate structural uncertainty.