Day of reckoning draws nearer for IPCC

According to Dr. Clive Best, A key prediction from the 2007 IPCC WG1 report fails statistical tests.

Abstract: Global temperatures measured since 2005 are incompatible with the IPCC model predictions made in 2007 by WG1 in AR4. All subsequent temperature data from 2006 to 2011 lies between 1 and 6 standard deviations below the model predictions. The data show with > 90%  confidence level that the models have over-exaggerated global warming.

Background: In 200o an IPCC special report proposed several future economic scenarios each with a different CO2 emission profile. For the 2007 assessment report these scenarios were used to model predictions for future global temperatures. The results for each of the scenarios were then used to lobby governments. It would appear that as a result of these predictions, there is  one favoured scenario – namely B1 which alone is capable of limiting temperature rises to 2 degrees.

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Jenn Oates

That’ll be on the front pages of all major media tomorrow morning, I’m sure.

Steptoe Fan

this is terrific ! I want to try and get this poster into local middle and high schools.


“the models have over-exaggerated global warming.”
Simple exaggeration wasn’t enough, they had to go and OVER exaggerate!
Great article.


What? The IPCC was wrong. Too bad. We just dismantled our heavy industry.,1518,816669,00.html


I’ve said it before and say it again that there is already a ready-made scare just waiting on the shelf to be dusted off…
Then down the memory hole it will all go…..

Um, this isn’t very good. Sure, it has been cooler than the models predict, and that’s important, but the confidence levels quoted are based on the error in measurements of global temperature only. Nobody ever claimed they could predict year-by-year temperatures with accuracy of +/- 0.05C, but that’s what’s been falsified.
I’m pretty sure if you look at the source of those A2 / A1B etc. curves there’s some error bars and they’re bigger than 0.05 degrees. Sorry I don’t have time to check.

So does statistical significance work in both directions?

Adam Gallon

And it still makes no difference, the political process will continue to grind along, as long as it can be dragged out for.

Mr Green Genes

This response on Dr Best’s website bears repeating.
So, if it walks like a duck, quacks like a duck and looks like a duck then it is definitely catastrophic global warming.
Congratulations to Boudumoon for that gem!


Hands up anyones who is surpirsed .

John Marshall

Even if the alarmist theories were to be correct why is 2C considered to be safe given that the MWP was 2-3C warmer and the RWP 5C warmer than today and the alarmist estimate of CO2 levels back then is 280ppmv. So with CO2 levels so low what caused the warming. Certainly neither the Romans nor Medieval people drove SUVs.

richard verney

DirkH says:
February 29, 2012 at 11:32 pm
It is difficult to understand what the politicians have been thinking these past 15 to 20 years.
High energy costs are simply madness, especially to an industrial based economy; it increases the costs of manufacture and the costs of distribution. For many industries, the cost of energy is the largest component in the costs of raw materials.
If it turns out that the case for CO2 emission reduction has been over egged whether because of incorrrect assumptions as to sensitivity (or otherwise), there will be severe back lash on this issue. It is something that will not simply disappear quietly given the unemployment and poverty resulting from the pursuit of green policies. The public will not only be demanding answers but also baying for blood.
Merkel’s decision with respect to nuclear was very strupid coinciding with mounting evidence of the high costs, unreliability and grid problems associated with wind and solar. She has given France the real prospects of a stranglehold over Germany. I envisage that the Germans will long rue the hasty and knee jerk decision made to close down much of their nuclear generating plants. .

richard verney

John Marshall says:
March 1, 2012 at 2:03 am
For anyone who claims that 2, 3, 4, 5 deg C warming would be catastrophic, it should be a pre-requisite for them to demonstrate what catastrophicc climate/weather problems beset man living during the MWP, the RWP, the Minoan Warm Period and the Holocene optimum. As far as we know from history, during the MWP, the RWP and the Minoan Warm Period, it was a time of plenty and man thrived.

The probability argument concerning the data is simply this :
The quoted error on a single temperature anomaly measurement is 0.05 deg.C (see here). If you measure the shortfall between the 6 anomaly measurements and the lowest of the 3 scenarios – B1 then you find shortfalls of (1,3,4,2,2,6) standard deviations. If this was due to noise then one would expect +- 1 or 2 standard deviations at most. The probability that randomly all of them lie so far below the scenarios is naively the product of each probability. This leads to a very low probability that the scenario predictions are correct. A proper analysis (curtesy of bbbeard) using the spread of measurements (0.08 deg.C) gives a probability of 1%. So the statement > 90% confidence is correct. The reason why all this is important is because these very scenario curves have been projected into long term predictions and then used to argue for drastic curbing of carbon emissions to limit warming to 2 degrees.
The question of model to model uncertainties: Here I think we have a different problem. Yes you are correct: the spread in model predictions seem to be getting larger leading to statements that the data are within the spread of models. This may be factually correct but that fraction of model calculations still consistent with the data are just those with low feedbacks.
A healthy scientific method should be as follows:
A theoretical model is developed to describe some physical process. The model will have a number of unknown parameters which determine the result. The values for these parameters start with best guess values and the model then makes predictions of measurable variables for experimentalists. Experiments then make the measurements and compare them to the theory. The model are then either modified with new parameters which can better describe the data, otherwise if this is not possible the model is rejected.
The problem with climate science seems to me that predictions of models made 22 years ago have had a massive political impact with the consequence that these predictions have been fixed in stone. This is not because the science has not evolved – it has. It is mainly due to the political fallout of being wrong. I fully accept the basic physics of AGW leading to ~1 degree warming for a doubling of CO2. The feedbacks (mainly due to water) however are rather uncertain and could even be negative. The models need to be tuned to fit the data and NOT the other way round !

Mike (One of the Many)

Unfortunately, “It’s the Sun, Stupid” never goes down very well with our not so friendly warmists…..
Traditionally, the approach that they’ve taken is to try and erase from history or marginalize both the MWP and the RWP
The sooner people get used to the fact that we live with a bit of a variable Star the better really – Well unless they want to start claiming that the Romans invented SUV’s, which their Medieval counterparts rediscovered and started driving around 😉

Peter Stroud

Another excellent technical paper that falsifies the IPCC, surface warming predictions. It should, of course, lead to a dismantling of the most stupid effects of the Climate Act, such as wind generation and biofuels. And a complete rethink of energy policy. But, it won’t. The policy makers will just ignore it, and continue to walk around with their fingers in their ears and their blindfolds on.

I pointed a commenter to Gavin Schmidt’s site where a similar chart exists and stated:
“All surface temperature models are running warm compared to reality.”
So I did interpret the chart correctly, I’m not that thick after all!
He didn’t like my source:
“No I asked for scientific institution. That’s a dude on a blog.”

Bill Illis

Hadcrut3 is now lower than every single one of the 23 climate models used in the IPCC AR4 (and there is quite a spread in these models).

This very well researched piece blows apart the latest rubbish.


Might “over-exaggerate” be considered a double negative?


The IPCC and the Gore-Mannian people are using the same flawed logic of the 18th century balloonist-would-be-astronauts who thought they could reach the moon if only they could pump in more hot air.

Frank K.

Garacka says:
March 1, 2012 at 4:53 am
“Might “over-exaggerate” be considered a double negative?”
Check it out here.
I agree with this answer:
“Exaggerate implies no degree, so it seems appropriate to indicate one sometimes: “He barely exaggerated!” or: “That was a huge exaggeration.” But I am not sure if “over exaggerate” is the same principle. It seems intended to describe a supposedly different concept, rather than a degree, but it doesn’t actually imply a different concept, because exaggerate does not mean “moderately exaggerate.””
Of course, with the IPCC, everything is an “over-axaggeration”! :^)
Meanwhile, the Earth’s temperature (according to the UAH AMSU Chan.5 daily temperature) is running quite cold…

So it sounds to me as if we need to reject the null hypothesis! There is sufficient evidence to conclude that these guys are full of it!

Reblogged this on gottadobetterthanthis.

John Greenfraud

The alarmist have lost, or are losing, on each and every scientific point. It doesn’t matter, CAGW fear mongering is not about science, it is about control. They will simply role out more equally absurd claims, or change the name again, and continue on as if nothing is wrong. Their goal is not to get the science correct, but to make it plausible enough to sway public opinion. That being said, I don’t wish to downplay the importance of the people here exposing CAGWs faulty methods, predictions and shoddy science, it’s invaluable. Just expect the progressive media to trot out more name-calling, demagoguery and personal attacks for the ’cause’. Thanks, keep up the good work.


HadCRUT4 will “fix” the problem 🙂

Sun is not helping either; watch out for more solar variability papers with
’ We propose that xyz can amplify small solar fluctuations
The latest SIDC SSN=33 (for February) is on low side.
Dr. Hathaway had already cut back his ‘prediction’.

Hey, we are near solar max for the SC24, and what do we have here is one sunspot and one spec.


Data between 2006 -2011…Um data, we don’t need data when we have perfectly good models…

michael hart

I’ve been wondering for a while about the IPCC models. At what point [for each individual model] does the statistical grim reaper appear and tap the IPCC on the shoulder?

Dr. Best’s “predictions” are actually “projections” and while predictions are falsifiable, projections are not.


michael hart says:
I’ve been wondering for a while about the IPCC models. At what point [for each individual model] does the statistical grim reaper appear and tap the IPCC on the shoulder?

The grim reaper will first have to find IPCC. He should look progressively deeper in the ocean, as that is where they will be hiding.


Terry Oldberg says:
Dr. Best’s “predictions” are actually “projections” and while predictions are falsifiable, projections are not.

Then “projections” are not science, and should not be misrepresented as such. Until that fact is reflected in practice, quibbling over the distinction is just semantics.


Testable hypotheses? We ain’t got no testable hypotheses. We don’t need no testable hypotheses. I don’t have to show you any stinking testable hypotheses.
(apologies to “Treasure of the Sierra Madre”)

Charlie A

The math on uncertainty and number of standard deviations, and therefore the probabilities are all incorrect.
See Lucia’s Blackboard for examples of the calculations done correctly. (blog link is in the right hand column of WUWT, under “Lukewarmers”

You seem to say that to make a distinction between predictions and projections is “just semantics.” Actually, to make this distinction is essential to one’s grasp of an important fact about the IPCC’s inquiry into AGW. Not wirhstanding IPCC representations to the contrary, the methodology of this inquiry was neither scientific nor logical.

Jim G

Macro Contrarian (@JackHBarnes) says:
March 1, 2012 at 12:20 am
“So does statistical significance work in both directions?”
Yes, as the confidence intervals are + or -. However, we must remember that significance testing is typically used for sample size error confidence, only. It does not limit or measure other types of errors such as data quality, observational error (heat islands), input errors, intentional selection of data points to push a theory, non-use of other independent variables more suited to the analysis, interdependence of independent variables (multicolinearity), etc. ad nauseum.

Jack Greer

Take a hint from Anomaly UK =>
… and Charles A. =>
I’m sorry but this analysis is nonsense. Clive is taking a temperature data-point accuracy error and applying it to a temperature time series. Makes no sense, whatsoever.

Septic Matthew/Matthew R Marler

Terry Oldberg: Dr. Best’s “predictions” are actually “projections” and while predictions are falsifiable, projections are not.
Why exactly is that? The projections are cited in Congressional testimony and written exhortations as though that is what will happen if we do not act. The conditions for which the projections were made are satisfied (except that CO2 continues to rise, and a few projections assumed non-rising CO2), and the projected temperatures have not occurred. Why does that not show that the projections have been incorrect?
If Dr. Best’s “predictions” are actually “projections”, when will the AGW promoters tell us that they are of no consequence and may be ignored?

Septic Matthew:
A “prediction” is an inference from the state of a system at the beginning of an independent statistical event to the state of the same system at the end of the same event. The former state is a condition on the Cartesian product of the values of the independent variables of the model. The latter state is a condition on the Cartesian product of the values of the dependent variables of this model. Conventionally, the latter state is called the “outcome” of the associated event. The complete set of events is an example of a “statistical population.” When the elements of a subset of these events are observed, this subset is a “statistical sample.” In testing a model, one compares the predicted to the observed relative frequences of the various possible outcomes. If there is not a match, the model is falsified by the evidence.
The relationship between the events and the predictions is one-to-one. Thus, a necessary condition for predictions to be made by a model is for a statistical population to be referenced by it. If you were to search AR4 for a citation to the statistical population underlying the IPCC’s conclusions, you’d draw a blank, for there is no population. It follows that: a) the IPCC models cannot be statistically tested and b) the methodology of the IPCC’s inquiry into AGW was not scientific.
In the minds of many, “projections” play the role of “predictions.” However, this cannot be so in view of the missing statistical population. The conflation, by professional climatologists and others, of the idea that is referenced by the word “projection” with the idea that is referenced by the word “prediction” has produced the ultimate disaster for the IPCC’s inquiry into AGW. This is for the inquiry to have been regarded as a scientific inquiry when it was not one.

Werner Brozek

The poster has the slope for CO2 wrong. Since 1997, it is about 2 ppm/year and not 1.
(slope = 1.95337 per year)

@Werner Brozek
Sorry for Typo – yes it should be 2ppm per year. It has been fixed now.

Werner Brozek

The January 2012 value for HadCrut3 at about 0.22 certainly does not help THE CAUSE. At 0.22, it would rank 18th hottest. And UAH for February certainly will not help either.


The strategy now used at RealClimate and Barry Brickmore is to state that the predictions are still within the experimental (data) errors as discusssed in Barry Brickmore’s blog on the WSJ article. The authors of this latter article argued that the overprediction of the temperature anomalies disproves the climate models. The spread in the different model predictions is so large that we may have to wait until 2030 to really test the predictive capability of the climate models. As argued by Judith Curry in her blog while discussing fig 9.7 of the FAR IPCC report, the model and experimental errors may be too large to effectively test the climate models.

kadaka (KD Knoebel)

Steptoe Fan on February 29, 2012 at 10:59 pm:
this is terrific ! I want to try and get this poster into local middle and high schools.
Werner Brozek on March 1, 2012 at 11:31 am:
The poster has the slope for CO2 wrong.
Are you all talking about this here poster linked to on the originating piece? If so, it might have been nice to clarify that point.
For myself, the attempted download of the poster on dial-up has now conked out early four times straight. Seems like a hosting issue, his site uses wordpress software but it doesn’t appear to be hosted on wordpress-dot-com. While I guess it’s interesting to look at, I’m giving up for now.


Heh … I’ve been betting on +0.3 deg C for a good many years … wish I’d bet real money!


Will the REAL deniers please stand up.
The really funny thing about the AGW con is that the “true believers” call opponents “deniers”.
Only a blind fool could miss the “Inconvenient Truth” that it is the true believers who are the deniers – they deny reality with their ludicrous theory which has NO substantiated evidence to support it.
They got the whole basis for their theory wrong by missing the really obvious fact that during the day the atmosphere acts to reduce the heating effect of the solar radiation – not add heat as they idiotically claim.
Is there any proof ??
You betcha – because without an atmosphere to REDUCE the heating effect of the solar radiation during the day – and after all during the day is all that matters as there is NO solar radiation at night – I thought that needed explaining to people who deny reality – the Earth would be subjected to temperatures like the Moon – about 120 degrees C.
After all, both the Earth and Moon are subject to the same intensity of solar radiation !!
So – CLEARLY – the Earth’s atmosphere actually REDUCES the heating impact.
Only a real DENIER could argue that isn’t true.
So the real “deniers” are actually the “true believers” – those who deny reality in favour of their pet “religion”.

kadaka (KD Knoebel)

Ha-ha! Great comment at the original story:

Jack Greer says:
March 1, 2012 at 2:48 pm
This is exactly the type of BS that will get you cross-posted at WUWT every time. You can’t be serious, Clive.

Jackie then included a link to RealTrueClimateStories, where presumably the Climate Science™-approved method to always uphold the IPCC is revealed. Guess that means if ain’t Team-reviewed then it ain’t science, and if it ain’t science then it is exactly the type of Gleick-ness suitable for posting at WUWT.
Ah Jackie, it’s good to know you have such a high opinion of this site. So, do you have any suggestions for improving the content on this site, that you’ll gladly and openly reveal here in Anthony’s home on the internet, right in front of Anthony’s virtual face?

Reply : Jack Greer et al.
The basic argument is that a prediction was made in 2007 for a future temperature trend. Now in 2012 we compare how well that prediction has performed fro 2011 until 2011. The conclusion is that it has significantly overestimated all temperatures for the last 6 years. These are not random errors – they are systematically low.
Each model should strive to fit the data independently. Taking an ensemble of different models with chosen parameters, then selecting the mean and using the spread as some sort of “model error” is also meaningless. Instead each individual model should be run multiple times varying climate sensitivity until it best reproduces the data. Fighting turf wars makes no sense. There is nothing wrong with being wrong. If it finally turns out that climate sensitivity is smaller than feared then we should celebrate. There is no need for gnashing of teeth ! The next ice age is anyway only 2000-3000 years away !


Terry Oldberg says:
March 1, 2012 at 12:57 pm

You and I are on the same page. The use of the “prediction/projection” distinction is a semantic argument by warmists to avoid responsibility for the scary stories they tell. In their lexicon, a “projection” is simply a “prediction” they made that turned out to be demonstrably false.
It is worth noting the official IPCC definitions, which suborns this nonsense:
Projection: “…a projection can be regarded as any description of the future and the pathway leading to it. However, a more specific interpretation has been attached to the term “climate projection” by the IPCC when referring to model-derived estimates of future climate.”
Forecast/Prediction: “When a projection is branded “most likely” it becomes a forecast or prediction. A forecast is often obtained using deterministic models, possibly a set of these, outputs of which can enable some level of confidence to be attached to projections.”
There is no formal distinction between an IPCC “climate projection” and a “forecast or prediction”, there is only their arbitrarily generated and ambiguosly quantified “confidence” that a projection is “most likely”.
They are responsible for this mess … and for their predictions, whether they want to call them that or not.

I’m not sure we’re on the same page. I’m saying that, as predictions are one-to-one with the events in a statistical population and as there is no population, there are no predictions. Thus, the use of the word “prediction” by Dr. Best, the IPCC and many others is false and misleading. While in the absence of a statistical population, a model cannot make predictions, it can make projections. Climatologists have muddied the waters by failing to draw a distinction between a “prediction” and a “projection” leading the naive to the false conclusion that the IPCC’s models can be statistically tested when they cannot be statistically tested. Do we agree?


On another blog, make a claim about global warming. I responded with actual data and a few links.
His response was something along the lines of:
Baseball has it’s umpires.
Football has it’s referees.
For science, we have the National Academy of Sciences.
Since the Academy has spoken, the issue is now settled.
He wouldn’t even debate the facts I presented. The NAS has spoken and that was it.

Jack Greer

@Clive Best says: March 1, 2012 at 2:22 pm
Clive, Please explain your logic for using a temperature data-point accuracy error value to estimate the statistical significance of how far adrift model projections are v. real measurement for a temperature time series. Seriously, I’m curious.

@Jack Greer.
My logic is the following: Quantum Chromodynamics predicts the cross-section for gluon production in quark-quark scattering. The calculation is difficult but eventually makes precise predictions about 3-jet events in a particle accelerator. Physicists work for several years to build an experiment to measure the cross-section for 3 jet production. QCD is compared to the results. and they agree within measurement errors.
Global Warming: At one instant in time – 2007: Some climate models which have been tuned to describe past temperature changes up to 2005 (or time series if you prefer) are then used to calculate forward in time to project/predict future temperature rises. These models include CO2 forcing trends and various assumptions for feedbacks, aerosols, albedo change etc.
Now in 2012 we can take the 6 new measurements since then and see how well the models performed. The answer in this case is not very well. All the points range from 1 to 6 standard deviations below the prediction.
What I think you want me to say is something like : Over a 50 year period the chi-squared agreement between climate models and the data is reasonably good so the models are doing just fine. However, this is based on “hindcasting” which I think is not quite the same thing. If I know the answer then It is easier to get the model to agree with the data. It is a bit like those mechanical models used to predict planetary orbits before Newton. By adding more cogs they get closer to an accurate description only if the underlying physics is very simple – Gravity.