All climate models include parameters that aren’t known precisely, so the model projections have to include that uncertainty to be meaningful.
All climate models are imprecise because they are models. They are statistical models based on a theory. You can only hope to nail it down as close to the truth as you can get, but knowing you're there, won't ever happen. That's by definition - science. Trial and error.... Hypothesis testing.
It's possible that many of the causal models (saying there's a connection between man-made CO2 and temperature) are almost completely incorrect. They may point to significant correlation of CO2 when, in reality, it's simply due to something like an omitted variable bias. When you include that variable (that's currently not included) in a multivariate analysis the correlation may flip completely or become insignificant.
Since, I've been told to "educate" myself a number of times here (more like indoctrinate, in my opinion). I really suggest global warming supporters take four or five advanced statistical modeling classes, or just simply take 2 graduate econometrics courses. After, then we can actually talk about these models in an educated manner and get into specifics.
Until then, a lot of you are simply cutting and pasting your opinions from green blogs. That was one of the most important points in that wsj article. Those green blogs you keep citing are based, very potentially, on flawed models and are, of course, bias... and there are incentives for them to continue with the charade. No amount of your regurgitation of their information will change that.
Further, no amount of stats provided to you or to them will ever prove that AGW is at all refutable... unless you learn statistics yourself. Science always involves the scientific method, particularly when there's millions of elements/variables at play.
But, keep reading if you'd like.