A large part of the inter-model dispersion in the ECS is due to the choices made in the representation of cloud and convective pro- cesses, which occur at finer scale than the model grid mesh, through so-called parameterizations (5, 6). Ever since the first Atmospheric Model Intercomparison Project (AMIP) exercise (7), it is the quan- tification of the errors associated with modeling choices that has fundamentally motivated the climate “model inter-comparison pro- jects” (MIPs), in which rigorous simulation protocols are shared across modeling groups. Providing climate change projections with an estimation of this modeling uncertainty is an essential role of the Coupled Model Intercomparison Project (CMIP) exer- cises, which are conducted about every 7 years, in advance of Inter- governmental Panel on Climate Change (IPCC) reports. The multi- model CMIP ensemble is used as an entry for so-called impact studies, often using physical and statistical downscaling approaches, and recent advances in Monte Carlo methods pave the way to a sys- tematic use of the CMIP simulations ensembles in such studies (8).  However, the uncertainty quantification performed in CMIP is only partial. In practice, each modeling group provides numerical simulations performed with only one (or sometimes a few) model configuration, i.e., a specific choice of physical content, grids, and a particular set of values for the free parameters of the model. The free parameter values result from a long explicit or implicit calibration phase, often called tuning. Could other configurations of each model also simulate reasonable climates with other parameter set- tings? If so, how would this affect the range of ECS explored? What are the implications for the uncertainty of model-based climate change assessments and downstream impact studies? These issues are prompting some modeling teams to rerun “perturbed physics ensembles” (PPEs) with their particular model, in addition to CMIP multi-model ensembles, to more systematically explore the uncertainty in future climate projections to inform societal questions (9–12).
