One of the things most people are taught early in their scientific education is that extrapolation is unreliable. And yet it's always seemed to me that the tendency of the Human mind to extrapolate current trends to the unknown future is so reflexive that we barely notice ourselves or others doing it. A huge percentage of popular debate in many fields (politics, economics, culture, science) falls prey to this fallacy. The fallacy is especially visible right now in the totally debased discussion of the causes and effects of climate change. Few of the loud voices on either side of this discussion, no matter how many times they mention the word science
are actually doing anything remotely approaching a critical, sceptical, Popperian scientific method. It's the victory of Kuhn's description of science, but vulgarized to the level of cable news, and then repurposed for political ends. There's barely a word written on this topic that isn't dripping with confirmation bias. A plague on both your houses.
You would think that this should be sufficiently embarrassing to the since is settled
camp to give them at least pause for reflection. (But I doubt it.) Science is never settled. Falsification is always out there, in objective reality, waiting to eat your cherished theory and spit it out.
Absolutely spot on.
Human CO2 emissions do make the planet slightly hotter. But the evidence continues to mount that the actual impact is not harmful. It certainly doesn't justify the mitigation measures commonly proposed.
Lets surprise ourselves with the data of the coming years.
It would also have been nice if clivebest would publish a script for reproducing the plots (http://reproducibleresearch.net/index.php/How_to)
And its not a "victory of Kuhn's description" but Kuhn described past scientific progress in a way so accurate that you can extrapolate that it will not change ;-).
So you agree with Clive, who states:
(My emphasis.)
Now, I'm not sure what you mean by a regression line because you don't seem to have computed a regression coefficient, and I don't know what he means by the prediction, because he doesn't provide any confidence interval. And I personally would not have a clue what statistical model to use here. (I have some education in statistics but more in applied and pure maths, and all that was like 10 years ago.)
But, going along with the both of you, just for the sake of argument, I would say an observed <0.0175 degree per year change in temperature sounds to me like an interesting geophysical phenomenon meriting further curious, disinterested inquiry. Pity that nobody seems remotely interested in embarking on any such inquiry.
XKCD on extrapolation..
The problem is insufficient statistical units. We have less than a century of global temperature data, and only sporadic temperature data from the last millennia. Even a millennia's data is insufficient for deriving a predictor, given the known geological records that infer many overlapping, natural change-cycles of the Earth. The only thing that can be said with certainty is that our climate is changing and that the recent data shows that the afore-assumed trend is flattening.
"All models are wrong, but some are useful." - George Box
Regards,
J.V. Cybulski, M.B.A., M.Eng.
Not only that, but the environment, much like in any other complex system, such phenomena is rarely linear.
Think network performance, traffic jams, stock bubbles, bacteria growth...
Possibly more than confirmation bias.
I found this book quite interesting regarding thinking
Hardin, Garrett - Filters against folly.
Another book that covers other human foibles is
Cialdini, Robert B. - Influence: Science and Practice
My Link
Yes, unfortunately or not, it's due to an intrinsic property of human mind - induction. We tend to generalise things...
http://www.bbc.co.uk/news/world-asia-pacific-13807166
approaching: Xibalba Be (the Road to the Underworld)
http://en.wikipedia.org/wiki/Xibalba
enjoy.
and if you don't believe it then check out Terence McKenna's novelty theory writings (novelty is maximized on Dec 21, 2012). I sure hope something drastic happens, this is getting out of hand man...
I can't be bothered looking for the source but I believe (from having read criticisms elsewhere) the post you link to is using a graph in which the base of the projected temperature increase is artificially increased giving an incorrect impression of the misfit of projections to reality (even though there is still a misfit - given co2 output has increased greater than expected, we should be way above the top projection).
Have to say though, i'm out and out disgusted with climate scientists and incredibly skeptical of anything produced by them. They just cannot be trusted to properly peer review each others work.
http://www.guardian.co.uk/environment/cif-green/2010/mar/01/phil-jones-commons-emails-inquiry 'The most startling observation came when he was asked how often scientists reviewing his papers for probity before publication asked to see details of his raw data, methodology and computer codes. 'They've never asked,' he said.'
http://climateaudit.org/2006/03/09/ammann-and-wahl-july-2005-review/ 'In my capacity as a reviewer of the MBH 2004 submission, I asked for the residual series, cross-validation statistics and source code that Mann had refused to provide to me as an opponent in controversy. This provoked some soul searching at Climatic Change. Schneider said that no one had asked for such things in 28 years of his editing the magazine.'
So much for peer review.
The most damaging behaviour for their reputation is how they basically just lie for effect. A particularly great example is this: http://www.realclimate.org/index.php/archives/2005/02/dummies-guide-to-the-latest-hockey-stick-controversy/ 'As you might expect, throwing out data also worsens the validation statistics, as can be seen by eye when comparing the reconstructions over the 19th century validation interval. Compare the green line in the figure below to the instrumental data in red. To their credit, MM05 acknowledge that their alternate 15th century reconstruction has no skill.'
McIntyre and McKitrick (MM) showed (amongst other things) that by withholding just two of the proxy series, the reconstruction yielded temperatures that were in 1400-1500 comparable to, if not higher than, now. This was not their 'alternate reconstruction' it was them showing how just a couple of proxies significantly affected the result, because of the way the algorithm used returned hockey stick shapes if any of the data had the hockey stick shape (as those two proxies had). The idea that the verification statistics show 'skill' and that the reconstruction is therefor also 'skillful' based only on the presence of these two golden miracles of proxies is downright laughable, but that is the clear implication. The whole guide is basically very misleading on all points - it appalls me that scientists pushing public policies can put up such a black piece of spin.
PS session timeouts on long posts is incredibly annoying