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Get your facts straight, Cynic.

Get your facts straight, Duck.

Over the six years studied

LOL! Which 6 years was that? Why only 6 years? A very carefully chosen 6 years, without a doubt.

Now matter how you cut it the models failed to predict the trend of the last 10 or 12 years. Whether you see it as down, flat, or slightly up, it's much cooler than what the IPCC predicted. Yeah, they have a ton of explainations for that now, El Nino and whatnot, but there were no such caveats when the prediction was first issued.

If El Nino is so important, then why is it not in the models? The answer is that there's nothing in the models to account for El Nino and a number of other things, and many of the assumptions built into the models to cover these things are turning out to be wrong.

But it's not just the last 10 years. Over a period of 18 years comparision of model output to subsequent weather data shows a no better than random correlation.*

But how could it be otherwise? The models are still in a primative state. The climate over the entire continental US, for example, is represented by and 8 by 8 grid. To the models the weather in Colorado and New Mexico is exactly the same. If a storm affects South Texas while North Texas is dry the models will never see it.

The same randomness infects the relationship between CO2 and global temperatures. Lead or lag? How do you predict, how do you know that it's leading this time? What other factors might enter in to spoil our assumptions? We don't know.

Nobody denies that CO2 increases heat forcing. The problem is that relative to other forcings this is a small effect. It might be quickly buried behind other changes. A slight change in cloud cover one year, for example, might completely nullify any effect of CO2, and we have no way of predicting cloud cover, certianly not with the models available now.

It has long been known that a slight change in the assumptions used to account for cloud cover would completely change a model's output. Modelers have addressed this so far by agreeing to use the same assumptions so that they get similar results. But there is no assurance that their agreed upon assumptions are correct.**
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*Koutsoyiannis, D., N. Mamassis, A. Christofides, A. Efstratiadis, and S.M. Papalexiou, Assessment of the reliability of climate predictions based on comparisons with historical time series, European Geosciences Union General Assembly 2008, Geophysical Research Abstracts, Vol. 10, Vienna, 09074, European Geosciences Union, 2008.

**Senior, C.A., and J.F.B. Mitchell, 1993: Carbon dioxide and climate: The impact of cloud parameterization. J. Clim., 6. 1995 1-15.
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