Uncertainties in climate change projections covered by the ISIMIP and CORDEX model subsets from CMIP5

Abstract

Abstract. Two international projects, ISIMIP (Inter-Sectoral Impact Model Intercomparison Project) and CORDEX (Coordinated Regional Climate Downscaling Experiment), have been established to assess the impacts of global climate change and improve our understanding of regional climate respectively. Model selection from the GCMs (general circulation models) within CMIP5 (fifth phase of the Coupled Model Intercomparison Project) was conducted using the different approaches for each project: one is a globally consistent model subset used in ISIMIP and the other is a region-specific model subset for each region of interest used in CORDEX. We evaluated the ability to reproduce the regional climatological state by comparing the subsets with the full set of CMIP5 multimodel ensemble. We also investigated how well the subsets captured the uncertainty in the climate change projected by the full set, to increase credibility for the scientific outcomes from each project. The spreads of the biases and Taylor's skill scores from the ISIMIP and CORDEX subsets are smaller than that from the full set for the regional means of surface air temperature and precipitation. However, the ISIMIP and CORDEX subsets show the larger spread than high-performance models from the full set, despite using a small number of models in ISIMIP and CORDEX. It was shown that better subsets exist that would have smaller biases and/or higher scores than the current subset. The ISIMIP subset captures the uncertainty range of the regional mean of temperature change projections by the full set better than the CORDEX subsets in 10 of 14 terrestrial regions worldwide. Compared with 10 000 randomly selected subset samples, the CORDEX subset shows low coverage of the uncertainty for the temperature change projections in some regions, and the ISIMIP subset shows high coverage in all regions. On the other hand, for the precipitation change projections, the CORDEX subsets show lower coverage in half of the regions than the randomly selected subsets, but tend to cover the uncertainty wider than the ISIMIP subset. In the regions where CORDEX used nine models or more, good coverage (>50 %) is evident for the projections of both temperature and precipitation. The globally consistent model subset used in ISIMIP could have difficulty in capturing uncertainties in the regional precipitation change projections, whereas it widely covers uncertainties in the temperature change projections. The region-specific model subset, like CORDEX, can cover the uncertainties in both temperature and precipitation changes well compared to the global common subset, but a large number of models is needed. By changing the number of models from the current ensemble members to at least nine members, high coverage for both uncertainties can be also obtained in the other regions, and this information would help model selection in the next generations.