Climate model Selection by Independence, Performance, and Spread (ClimSIPS)

As the number of models in Coupled Model Intercomparison Project (CMIP) archives increase from generation to generation, there is a pressing need for guidance on how to interpret and best use the abundance of newly available climate information. Users of the latest CMIP6 seeking to draw conclusions about model agreement must contend with an "ensemble of opportunity" containing similar models that appear under different names. Those who used the previous CMIP5 as a basis for downstream applications must filter through hundreds of new CMIP6 simulations to find several best suited to their region, season, and climate horizon of interest. Here, we present methods to address both issues, model dependence and model subselection, to help users previously anchored in CMIP5 to navigate CMIP6 and multi-model ensembles in general. We refine a definition of model dependence based on climate output to designate discrete model families within CMIP5/6. We show that the increased presence of model families in CMIP6 bolsters the upper mode of the ensemble's bimodal effective Equilibrium Climate Sensitivity (ECS) distribution. Accounting for the mismatch in representation between model families and individual model runs shifts the CMIP6 ECS median and 75th percentile down by 0.43˚C, achieving better alignment with CMIP5's ECS distribution.

 Subsequently, we present a new cost-function minimization-based approach to model subselection, Climate model Selection by Independence, Performance, and Spread (ClimSIPS). We demonstrate ClimSIPS by selecting sets of 2, 3, and 5 CMIP models for European applications, incorporating the new dependence definition along with a performance metric based on agreement with observed mean climate fields and the ensemble spread of projected midcentury change in mean surface air temperature and precipitation. Because different combinations of models are selected by the cost function for different independence, performance, and spread priority balances, we present all selected subsets in ternary contour "subselection triangles". ClimSIPS represents a novel framework to select models in an informed, efficient, and transparent manner and addresses the growing need for guidance and simple tools so those seeking climate services can navigate the increasingly complex CMIP landscape.