AGW acolytes also use a lot of "correlation = causation" arguments. NO flooded not because of "Global Warming". It flooded because it was beneath sea level when they built it, and it has stayed there ever since. Also, it flooded because of a cascade of stupid management and politics within its own government. They didn't reinforce their levees even though they'd been given millions of dollars to reinforce them.
No - they don't. That is simply a perception that is based on a couple of faulty reports that have been repeatedly debunked. The truth is that these so-called 'consensuses' are based on very dodgy, highly questionable secondary sourcing essays which had to be compiled in very specific ways so as to eliminate all the "scientists" who disagreed. When you throw out the 100,000+ scientists who disagree with you and refuse to acknowledge them, then it's awfully easy to focus on the 9,000 scientists who you DO say are "scientists" and say that only 6% disagree with you. See how that works?
And that's where the whole "97% consensus" myth came from. The author hand-picks a bunch of (surprise!) "climatologists". Many of these guys don't have PhDs or even Masters, but are really just undergrads writing thesis, or are ancillary workers in tangental fields to the climate (IE activists) who all agree with exactly what the author wants. They throw out the bulk of other real scientists, and then claim an imaginary consensus. How convenient. At the risk of playing duelling-websites, here's an interesting paper showing exactly how the trick is achieved... Doubtless the character of the speaker will be attacked, rather than the reality and accuracy of his data, but that's what the issue has come to - sadly.
http://scienceandpublicpolicy.org/im.../consensus.pdf
I've seen the IPCC data, the NOAA data, and reports, studies, and the SAPs (stat analysis plans) of many others. The data is junk. They routinely overweight human C02 emissions in their models, while completely ignoring or underweighting other known variables - many of which are far more powerful. You know - stuff like land cover, oceanic currents, El-nino/nina events, solar radiation, cloud cover, rain, water vapor - all those insignificant factors that get swept under the carpet in a typical stats model.
As a professional statistician, it is quite annoying to see the routine abuse my profession has to suffer through because of the politicization of this subject. Whenever you put together a statistical model, you have to justify the nature of its construction. If you weight a variable strongly, there must be a valid statistical reason for doing so. In every report I've read to date, the model artificially inflates the C02 variable while artificially minimizing (or eliminating) other more potent variables. And the reason for it? Well - so far all I've been able to see is ... ??? because the model just DOES it and never bothers justifying the underlying assumption.
When an analysis does that, the resulting conclusions are junk. Period.