evidence: Climate models have been subjected to "perfect model tests," in which the they were used to project a reference climate and then, with some minor tweaks to initial conditions, recreate temperatures in that same reference climate. This is basically asking a model to do the same thing twice, a task for which it should be ideally suited. In these tests, Frank found, the results in the first year correlated very well between the two runs, but years 2-9 showed such poor correlation that the results could have been random. Failing a perfect model test shows that the results aren’t stable and suggests a fundamental inability of the models to predict the climate. The ultimate test for a climate model is the accuracy of its predictions. But the models predicted that there would be much greater warming between 1998 and 2014 than actually happened. If the models were doing a good job, their predictions would cluster symmetrically around the actual measured temperatures. That was not the case here; a mere 2.4 percent of the predictions undershot actual temperatures and 97.6 percent overshot, according to Cato Institute climatologist Patrick Michaels, former MIT meteorologist Richard Lindzen, and Cato Institute climate researcher Chip Knappenberger. Climate models as a group have been "running hot," predicting about 2.2 times as much warming as actually occurred over 1998–2014. Of course, this doesn’t mean that no warming is occurring, but, rather, that the models’ forecasts were exaggerated.