Evaluation of the seasonal to decadal variability in dynamic sea level simulations from CMIP5 to CMIP6

Abstract

Previous studies have revealed little progress in the ensemble mean of Coupled Model Intercomparison Project Phase 6 (CMIP6) models compared to Phase 5 (CMIP5) models in simulating global dynamic sea level (DSL). This study investigates the performance of the CMIP5 and CMIP6 ensembles in simulating the spatial pattern and magnitude of DSL climatology, seasonal variability, interannual variability, and decadal variability by using the pattern correlation coefficient (PCC) and root-mean-square error (RMSE) as metrics. We show that the top models of the CMIP6 ensemble perform better than those of the CMIP5 ensemble in the simulation of DSL climatology and seasonal and interannual variability, but not DSL decadal variability. An intermodel linear relationship between the RMSE and PCC is found for both the CMIP5 and CMIP6 ensembles; however, this intermodel relationship is more linearly correlated in the CMIP6 ensemble and not significant for DSL decadal variability. The results show that the finer-horizontal resolution models tend to yield a smaller RMSE and a larger PCC in the DSL climatology, seasonal variability, interannual variability but not decadal variability simulations, and the relationship is more evident for the CMIP6 ensemble than for the CMIP5 ensemble.