So here is one for example; computer models need to be related to reality. Well durr, of course. Who would model a natural system and NOT try and test it in reality. So for example;
"Time to get real – not live in a false computer model world."
"Models that cannot even predict what has happened when fed hitoric [sic] data!"
So the suggestion here is that they hugely complex models that are built and tested using real-world data and continually tested and refined - are inaccurate because the people who built them don't realise the differemce between a computer model and real data. The suggestion is nonsense. Utter tripe and piffle.
Or (and you see this one time and time again);
"I think the conclusion has to be that at present the climate just isn't living up to predictions, if the models were correct this shouldn't be happening."
"The point is that the so called foolproof models that allowed the believers to quote "The scientists have spoken" did not predict the phase we are going through."
Again, the suggestion is that the natural variability that exists within climate and is a mainstay of any climate data would not have been accounted for in the data-sets. Again it's utter piffle and provably wrong - an error committed by people failing Climate 101 by failing to realise the difference between 'weather' and 'climate'.
However it begs the question - why do denailists, who have no expertise in climate science, and I suspect in most cases, no expertise in any scientific discipline - think they are able to pick apart the research of experts with such a simple sucker punch? Well there might be an answer; The Dunning-Kruger Effect;
The Dunning-Kruger effect is an example of cognitive bias in which "people reach erroneous conclusions and make unfortunate choices, but their incompetence robs them of the metacognitive ability to realize it". They therefore suffer an illusory superiority, rating their own ability as above average.
Put basically we tend to overestimate our own skill and underestimate other's abilities and the worse we are at understanding an area, the worse our estimation of how little we know. It explains a lot, I feel. So take this explanation by Tamino as to why the maths in a denialists talking-point is all wrong; It stretches my pretty-rubbish knowledge of maths. I have the ability to see that there is much in this area I am not equipped to deal with. That's why science has the peer-review process - so people who are equipped can critique each other's work. But the denailists would have us believe that they (somehow) have a special (magical?) insight into GSCE-level science that eludes a professional scientist?
Yup, that is what they think - and here are two good summaries about where the evidence is on the issue that I recommend;
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