We present an assessment of the CMIP5 global model simulations over a subset of CORDEX domains used in the Phase I CREMA (CORDEX RegCM hyper-MAtrix) experiment (Africa, HYMEX-MED (Mediterranean), South America, Central America and West Asia). Three variants of the transformed Mielke measure are used to assess (1) the model skill in simulating surface temperature and precipitation historical climatology, (2) the degree of surface temperature and precipitation change occurring under greenhouse gas forcing, and (3) the consistency of a model's projected change with that of the Multi Model Ensemble (MME) mean. The majority of models exhibit varying degrees of skill depending on the region and season; however, a few models are identified as performing well globally. We find that resolution improves the model skill in most regional and seasonal cases, especially for temperature. Models with the highest and lowest climate sensitivity, as well as those whose change most resembles the ensemble mean are also discussed. Although the higher resolution models perform better, we find that resolution does not have a statistically significant impact on the models' response to GHG forcing, indicating that model biases do not play a primary role in affecting the model response to GHG forcing. We also assess the three selected models for the CREMA Phase I experiment (HADGEM2ES, MPI-ESMMR and GFDL-ESM2M) and find that they are characterized by a relatively good level of performance, a range of high to low climate sensitivities and a good consistency with the MME changes, thereby providing a reasonably representative sample of the CMIP5 ensemble.