 Evaluation of climate models occurs throughout the model development process. Parameterizations and component models are often tested individually “off-line” to see how they perform (Randall et al. 2007), and adjustments are made to try to improve them when they fall short of expectations. Likewise, there is testing and adjustment as the different model components are coupled. This evaluation can have both qualitative and quantitative dimensions. For instance, it might be checked that the model’s climate is basically realistic-looking, with salient features (e.g., of the atmospheric circulation) in roughly the right place. Quantitative evaluation produces scores on performance metrics. These can include measures of conservation and stability—how close does the model come to achieving a top-of-atmosphere energy balance?—as well measures of fit between model output and observational data. The evaluation that occurs in the course of model development, however, is rarely reported in publications. What is reported instead are features of the model, including how it performs, once it is fully constructed, tuned and ready to be released for scientific use.