Ranking climate models by performance using actual values and anomalies: Implications for climate change impact assessments

Reducing uncertainty in climate projections can involve giving less credence to Atmosphere-Ocean General Circulation Models (AOGCMs) for which the simulated future climate is judged to be unreliable. Reliability is commonly assessed by comparing AOGCM output with observations. A desirable property of any AOGCM skill score is that resulting AOGCM-performance rankings should show some consistency when derived using observations from different time periods. Notably, earlier work has demonstrated inconsistency between rankings obtained for 20-year periods in the 20th century based on global and regional comparisons of simulated and observed near-surface temperature anomalies. Here, we demonstrate that AOGCM-performance rankings derived from actual temperatures, which incorporate AOGCM biases in climatological means, can be used to identify AOGCMs that perform consistently well or poorly across multiple 20-year periods in the 20th century. This result supports the use of comparisons of simulated and observed actual values of climate variables when assessing the reliability of AOGCMs.