[Considering that pretty much everything you say is wrong, listening to you makes no sense at all.
In this case, you are once again very wrong and totally confused. Too bad you're such a brainwashed retard.
Love the way you just toss stuff up and don't realize what it means.
""... represents an average of 58 simulations run on 14 different models..... "
You do realize that if the models were RIGHT in the first place -- you'd only have to run 14 simulations on 14 models to get the answers. Don't you?
When you look closely at the "results" the disagreement between model runs approaches the magnitude of the anomaly. Which means that SOME of these models are not all that good. That's why you need 14 models running MULTIPLE ASSUMPTIONS to produce anything approaching laudable.
Without knowing HOW the input feature vectors were mangled and tweaked -- you've got chaos. A LINE regression is pretty easy to generate. I could do the same thing with a 4th order polynomial fit and tweaking a few parameters. Changing the slopes and tossing in some perturbations from a volcano or two COULD REALLY impress the natives..
Thing about simulation is --- you don't just look at the output. Especially when you're backcasting for only one history trend. That would be like simulating the response of a complex electronic gadget (like a radio) to noise by using just one signal stream and just one noise source.
Next time you see a paper based on a model, you MIGHT want to pay more attention to the tuning assumptions and less time gasping in awe about the graph.
Virtually all of climatology is based on CM's. That's why they are never correct and ascribe evry ill on the planet to that evil little critter CO2. what I find amazing is that supposedly thinking people actually believe the models are the equivalent of data.
Boggles the mind.