Guest essay by Douglas J. Keenan
Temperatures on Earth’s surface—i.e. where people live—are widely believed to provide evidence for global warming. Demonstrating that those temperatures actually provide evidence, though, requires doing statistical analysis.
All such statistical analyses of the temperatures that have been done so far are fatally flawed. Astoundingly, those flaws are effectively acknowledged in the IPCC Fifth Assessment Report (AR5).
The flaws imply that there is no demonstrated observational evidence that global temperatures have significantly increased (i.e. increased more than would be expected from natural climatic variation alone).
Despite this, one of the main conclusions of AR5 is that global temperatures have increased very significantly. That conclusion is based on analysis that AR5 itself acknowledges is fatally flawed. The correct conclusion is that there is no demonstrated observational evidence for global warming.
Full critique at http://www.informath.org/AR5stat.pdf
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He closes with these quotes:
The reason for so much bad science is not that talent is rare, not at all; what is rare is character. People are not honest, they don’t admit their ignorance, and that is why they write such nonsense. — Sigmund Freud
Half the harm that is done in this world is due to people who want to feel important. They don’t mean to do harm — but the harm does not interest them. Or they do not see it, or they justify it because they are absorbed in the endless struggle to think well of themselves. — T.S. Eliot
You should, in science, believe logic and arguments,carefully drawn, and not authorities.—Richard Feynman
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“The flaws imply that there is no demonstrated observational evidence that global temperatures have significantly increased.”
And Santer’s deadline for human attribution of the insignificant increases is knocking at the door.
I love the quotes.
They go a long ways towards explaining the “sheeple” behaviour we see in so many individuals, especially surrounding this topic.
Especially applicable is the end of the quote that says “…they justify it because they are absorbed in the endless struggle to think well of themselves.”
Monte Carlo methods use pseudo-random number generators to simulate random processes. Both Monte Carlo and random number generators have been around for many decades.
The Mersenne Twister is a particularly good random number generator which I have used myself, but I fail to see how it could have caused a revolution in Monte Carlo methods. Perfectly adequate random number generators were around long before the Mersenne Twister arrived.
“The correct conclusion is that there is no demonstrated observational evidence for global warming.”
Yes douglas there was no little ice age and its not warmer today.
In fact if you use Keenan’s approach you can show that you have no evidence for natural variability of any kind much less warming since 1750.
Douglas J. Keenan:
Thankyou for providing your superb summary and I congratulate you on its presentation in plain English.
I commend everyone to read it especially its Section 10 and I copy your link to here so as to assist people going to it
http://www.informath.org/AR5stat.pdf
Richard
Steve Mosher I did not know that the Little Ice Age was between the 4th assessment and fifth assessment report I thought it was much earlier.
” Steven Mosher says:
October 30, 2013 at 8:02 am
Yes douglas there was no little ice age and its not warmer today.”
Thus proving that there is no “Anthropogenic Global Warming”, it is completely [natural], which is of course what Doug meant, as you well know.
You are a very devious person.
Steven Mosher says:
October 30, 2013 at 8:02 am
I guess you ignored this from above.
“The flaws imply that there is no demonstrated observational evidence that global temperatures have significantly increased (i.e. increased more than would be expected from natural climatic variation alone).”
Thanks, Douglas.
This is a very good post and your “Statistical Analyses of Surface Temperatures in the IPCC Fifth Assessment Report” deserves to be read.
With some of the other models that were nearly as likely as the chosen model, the increase in temperatures is not significant. To summarize—some likely model
DRAFT ⁞ Page 17
shows the increase as significant and other likely models show the increase as significant. Hence, we cannot determine whether the increase is significant. The main conclusion of Breusch & Vahid, however—based on their choice of model—is that the increase is significant. The main conclusion is thus actually baseless.
I think one of the significants in the above paragraph should be ‘not significant’
Stephen Mosher: Thus amplifying a point that is commonly unobserved. We are in an interglacial period in which TEMPERATURES RISE UNTIL THEY DON’T. Then we have another ice age.
Much and appreciative thanks to WUWT for posting this.
@rabbit
My critique gives a link for that, which you could click on for more details. Briefly, the linear congruential generators that you, presumably, were using sometimes led to inaccurate results. The BlumBlumShub generator was available, but so slow that hardly anyone used it.
@Ceri Phipps
Kind thanks—fixed.
I have also been questioned privately about something, and I thought it was worth leaving the reply here.
The question is this: if almost all statistical analyses of climatic data are wrong, does that affect the work done by McIntyre & McKitrick on the hockey stick? The answer is “No”. The hockey stick was a temperature reconstruction spanning the past several centuries; it was derived via statistical analysis by Mann-Bradley-Hughes (MBH). In other words, MBH drew a statistical inference. MM showed that there was an error in the analysis that underpinned the drawing of the inference. MM did not have their own temperature reconstruction; i.e. they did not draw a statistical inference themselves. For that reason, the issues discussed in my critique do not apply to MM.
Since publishing on the error by MBH, McIntyre & McKitrick have often done similar work, i.e. showing that the inferences drawn by other researchers are based on flawed analyses. Occasionally, however, they have claimed to draw statistical inferences themselves. Here is an example.
Ross McKitrick, Stephen McIntyre, Chad Herman (2010), “Panel and multivariate methods for tests of trend equivalence in climate data series”, Atmospheric Science Letters, 11: 270–277. doi:10.1002/asl.290
Preprint: http://www.rossmckitrick.com/uploads/4/8/0/8/4808045/mmh_asl2010.pdf
The paper is based on assumptions that are wholly unjustified by the authors, and might well be wrong. Hence the claims of statistical inference in the paper are invalid. Note that understanding the invalidity does not require specialist training in statistics; the invalidity is more basic than that.
This is another example of the problems discussed in my critique. An underlying issue here, with McIntyre, McKitrick, and almost all climate scientists, is that authors appear to not understand what the question is. The question is this: what statistical model should be chosen? That is the question that must be answered, before statistical inferences can be drawn. This is basic.
Mosher: “and its not warmer today”
All of the 128 yellow lines are Septembers warmer than September 2013. Some all the way back to the 1660s.
http://sunshinehours.files.wordpress.com/2013/10/hadcet-since-1659-monthly-mean-sep.png
http://sunshinehours.wordpress.com/2013/10/03/hadcet-september-2013-only-128-years-were-warmer-2/
That’s rich: quoting Sigmund Freud about nonsense.
Superbly written overview of the statistical assumptions and problems in IPCC AR5. Required reading.
We don’t know what the null distribution (the distribution absent a CO2 effect) for climate variability is. This has been written repeatedly.
One way to guess at a null distribution would be to take the most recent ensemble of GCM outputs, compute their mean, then compute the difference between each realization and the ensemble mean. That variation has been shown to be huge. With that estimate, which credits the models more than they are really worth, the natural variation is so large that the CO2 “signal” over the last decades is indistinguishable from 0.
What is the correct (or best) null hypothesis for a particular problem? That question can not be answered by statistical analysis. Taking a particular “effect size” to be 0 is merely a frequent convenience, no more.
Notice, however, that if you take the GCM model mean as the null hypothesis, the data since the ensembles were run strongly reject that hypothesis: the model mean is not an accurate representation of the process generating the data. There is a question, as rgb at duke has written, whether the ensemble of model trajectories can be reasonably treated as a sample from any population. So a hypothesis that the data come from a process of which that mean is a reasonable representative may not be testable.
In regard to Vaughan Pratt’s model I wrote that if you know the correct CO2 signal then you can estimate the natural variability; and if you know the correct distribution of the natural variation (aka “noise”) then you can estimate the CO2 signal. On present data, there is no good reason to conclude that either of those is “known”.
Matthew R Marler says:
October 30, 2013 at 9:53 am
“One way to guess at a null distribution would be to take the most recent ensemble of GCM outputs, compute their mean, then compute the difference between each realization and the ensemble mean. That variation has been shown to be huge. With that estimate, which credits the models more than they are really worth, the natural variation is so large that the CO2 “signal” over the last decades is indistinguishable from 0.”
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Very interesting comment. A rough estimate from the various climate model predictions between 1980 and 2025 gives a range of +/-0.75C over a 45 year period. That is comparable to the warming between 1950 and 2000 that has been IPCC-certified to be mostly due to anthro CO2 emissions.
Which of course means that news of IPCC’s dead-certainty has been greatly exaggerated.
Keenan just disappeared the LIA.. pretty funny.
Steven Mosher says:
October 30, 2013 at 8:02 am
“The correct conclusion is that there is no demonstrated observational evidence for global warming.”
Yes douglas there was no little ice age and its not warmer today.
In fact if you use Keenan’s approach you can show that you have no evidence for natural variability of any kind much less warming since 1750.
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Well, since the LIA ( NASA defines the term as a cold period between AD 1550 and AD 1850) is not in the range of the period examined by the IPCC (1880 – 2012) or the author, I don’t see how pointing out its existence offers anything useful about the paper.
I think that was the point of the paper. That there is no valid statistical model used so far (especially the linear models used predominantly) that allows for a valid conclusion that there is demonstrable observational evidence to be drawn about ANY trend in global surface temperatures up, down, or none. That is NOT saying that there isn’t one, nor that temperatures have not increased.
You need to show your work.
Typo in Excursus 3–“be” should (I think) be “by”:
Steven Mosher says:
October 30, 2013 at 8:02 am
The author deals only with HadCRU figures for 1880-2012, not with the earlier 19th & 18th centuries (let alone 17th & 16th), so says nothing about the LIA, for most of which time good instrumental temperature data are lacking. Proxies however show that the LIA cold phase was global. I’ve just been studying centennial-scale glacial advance & retreat on the scenic Villarrica volcano, Chile, for instance.
Dear Mr. Mosher – re: 10:41am — (eye roll)
It was in the FIRST instance, perhaps, a careless mistake made in your eagerness to refute Mr. Keenan… but after several other commenters clearly showed you your error, one can only conclude that you:
1. really do not understand; or
2. are impaired intellectually (perhaps, by pride) — no one unimpaired would intentionally make oneself look idiotic.
In case you would like to learn (even more, to prevent your succeeding in leading others astray), here is what Keenan said with my emphasis to point you to an accurate reading of his language:
I hope that, one day, Mr. Mosher, you will be free of the darkness that clouds your heart and/or mind and which so obviously impedes your thinking abilities. Instead of persisting in trying to think well of yourself, you would be wiser (and happier, no doubt) if you would strive to have those who are
honest and logical think well of you.
Hopefully,
Janice
Any data from desert regions that show night time temperatures are increasing?
Janice Moore says:
October 30, 2013 at 11:24 am
>>>>>>
You have just (partially) redeemed yourself….