Guest post by Robert E. Levine, PhD
The two principal claims of climate alarmism are human attribution, which is the assertion that human-caused emissions of carbon dioxide are warming the planet significantly, and climate danger prediction (or projection), which is the assertion that this human-caused warming will reach dangerous levels. Both claims, which rest largely on the results of climate modeling, are deceptive. As shown below, the deception is obvious and requires little scientific knowledge to discern.
The currently authoritative source for these deceptive claims was produced under the direction of the UN-sponsored Intergovernmental Panel on Climate Change (IPCC) and is titled Climate Change 2007: The Physical Science Basis (PSB). Readers can pay an outrageous price for the 996 page bound book, or view and download it by chapter on the IPCC Web site at http://www.ipcc.ch/publications_and_data/ar4/wg1/en/contents.html
Alarming statements of attribution and prediction appear beginning on Page 1 in the widely quoted Summary for Policymakers (SPM).
Each statement is assigned a confidence level denoting the degree of confidence that the statement is correct. Heightened alarm is conveyed by using terms of trust, such as high confidence or very high confidence.
Building on an asserted confidence in climate model estimates, the PSB SPM goes on to project temperature increases under various assumed scenarios that it says will cause heat waves, dangerous melting of snow and ice, severe storms, rising sea levels, disruption of climate-moderating ocean currents, and other calamities. This alarmism, presented by the IPCC as a set of scientific conclusions, has been further amplified by others in general-audience books and films that dramatize and exaggerate the asserted climate threat derived from models.
For over two years, I have worked with other physicists in an effort to induce the American Physical Society (APS) to moderate its discussion-stifling Statement on Climate Change, and begin to facilitate normal scientific interchange on the physics of climate. In connection with this activity, I began investigating the scientific basis for the alarmist claims promulgated by the IPCC. I discovered that the detailed chapters of the IPCC document were filled with disclosures of climate model deficiencies totally at odds with the confident alarmism of the SPM. For example, here is a quote from Section 8.3, on Page 608 in Chapter 8:
“Consequently, for models to predict future climatic conditions reliably, they must simulate the current climatic state with some as yet unknown degree of fidelity.”
For readers inclined to accept the statistical reasoning of alarmist climatologists, here is a disquieting quote from Section 10.1, on Page 754 in Chapter 10:
“Since the ensemble is strictly an ‘ensemble of opportunity’, without sampling protocol, the spread of models does not necessarily span the full possible range of uncertainty, and a statistical interpretation of the model spread is therefore problematic.”
The full set of climate model deficiency statements is presented in the table below. Each statement appears in the referenced IPCC document at the indicated location. I selected these particular statements from the detailed chapters of the PSB because they show deficiencies in climate modeling, conflict with the confidently alarming statements of the SPM, and can easily be understood by those who lack expertise in climatology. No special scientific expertise of any kind is required to see the deception in treating climate models as trustworthy, presenting confident statements of climate alarm derived from models in the Summary, and leaving the disclosure of climate model deficiencies hidden away in the detailed chapters of the definitive work on climate change. Climategate gave us the phrase “Hide the decline.” For questionable and untrustworthy climate models, we may need another phrase. I suggest “Conceal the flaws.”
I gratefully acknowledge encouragement and a helpful suggestion given by Dr. S. Fred Singer.
| Climate Model Deficiencies in IPCC AR4 PSB | |||
| Chapter | Section | Page | Quotation |
| 6 | 6.5.1.3 | 462 | “Current spatial coverage, temporal resolution and age control of available Holocene proxy data limit the ability to determine if there were multi-decadal periods of global warmth comparable to the last half of the 20th century.” |
| 6 | 6.7 | 483 | “Knowledge of climate variability over the last 1 to 2 kyr in the SH and tropics is severely limited by the lack of paleoclimatic records. In the NH, the situation is better, but there are important limitations due to a lack of tropical records and ocean records. Differing amplitudes and variability observed in available millennial-length NH temperature reconstructions, and the extent to which these differences relate to choice of proxy data and statistical calibration methods, need to be reconciled. Similarly, the understanding of how climatic extremes (i.e., in temperature and hydro-climatic variables) varied in the past is incomplete. Lastly, this assessment would be improved with extensive networks of proxy data that run up to the present day. This would help measure how the proxies responded to the rapid global warming observed in the last 20 years, and it would also improve the ability to investigate the extent to which other, non-temperature, environmental changes may have biased the climate response of proxies in recent decades.” |
| 8 | Executive Summary | 591 | “The possibility that metrics based on observations might be used to constrain model projections of climate change has been explored for the first time, through the analysis of ensembles of model simulations. Nevertheless, a proven set of model metrics that might be used to narrow the range of plausible climate projections has yet to be developed.” |
| 8 | Executive Summary | 593 | “Recent studies reaffirm that the spread of climate sensitivity estimates among models arises primarily from inter-model differences in cloud feedbacks. The shortwave impact of changes in boundary-layer clouds, and to a lesser extent mid-level clouds, constitutes the largest contributor to inter-model differences in global cloud feedbacks. The relatively poor simulation of these clouds in the present climate is a reason for some concern. The response to global warming of deep convective clouds is also a substantial source of uncertainty in projections since current models predict different responses of these clouds. Observationally based evaluation of cloud feedbacks indicates that climate models exhibit different strengths and weaknesses, and it is not yet possible to determine which estimates of the climate change cloud feedbacks are the most reliable.” |
| 8 | 8.1.2.2 | 594 | “What does the accuracy of a climate model’s simulation of past or contemporary climate say about the accuracy of its projections of climate change” This question is just beginning to be addressed, exploiting the newly available ensembles of models.” |
| 8 | 8.1.2.2 | 595 | “The above studies show promise that quantitative metrics for the likelihood of model projections may be developed, but because the development of robust metrics is still at an early stage, the model evaluations presented in this chapter are based primarily on experience and physical reasoning, as has been the norm in the past.” |
| 8 | 8.3 | 608 | “Consequently, for models to predict future climatic conditions reliably, they must simulate the current climatic state with some as yet unknown degree of fidelity.” |
| 8 | 8.6.3.2.3 | 638 | “Although the errors in the simulation of the different cloud types may eventually compensate and lead to a prediction of the mean CRF in agreement with observations (see Section 8.3), they cast doubts on the reliability of the model cloud feedbacks.” |
| 8 | 8.6.3.2.3 | 638 | “Modelling assumptions controlling the cloud water phase (liquid, ice or mixed) are known to be critical for the prediction of climate sensitivity. However, the evaluation of these assumptions is just beginning (Doutraix-Boucher and Quaas, 2004; Naud et al., 2006). |
| 8 | 8.6.4 | 640 | “A number of diagnostic tests have been proposed since the TAR (see Section 8.6.3), but few of them have been applied to a majority of the models currently in use. Moreover, it is not yet clear which tests are critical for constraining future projections. Consequently, a set of model metrics that might be used to narrow the range of plausible climate change feedbacks and climate sensitivity has yet to be developed.” |
| 9 | Executive Summary | 665 | “Difficulties remain in attributing temperature changes on smaller than continental scales and over time scales of less than 50 years. Attribution at these scales, with limited exceptions, has not yet been established.” |
| 10 | 10.1 | 754 | “Since the ensemble is strictly an ‘ensemble of opportunity’, without sampling protocol, the spread of models does not necessarily span the full possible range of uncertainty, and a statistical interpretation of the model spread is therefore problematic.” |
| 10 | 10.5.4.2 | 805 | “The AOGCMs featured in Section 10.5.2 are built by selecting components from a pool of alternative parameterizations, each based on a given set of physical assumptions and including a number of uncertain parameters.” |
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“Current spatial coverage, temporal resolution and age control of available Holocene proxy data limit the ability to determine if there were multi-decadal periods of global warmth comparable to the last half of the 20th century.”
This is not a criticism of the models but of the proxy-data.
I can think of much better places to conceal uncertainty than in the IPCC report.
It’s worse than we thought…..
I wonder how many delegates and contributors to this circus showe actually have
1) Read all 996 pages
2) Followed up all references
3) Understood it all
Reading just these selected highlights has made me go “Eh, what?” and I’ve a science degree, an IQ over 135 and am used to reading & interpreting medical clinical trial papers.
Reading this a few times leaves me with the following “take home message”
462 “We don’t know if the changes seen over the past decades are anything out of the ordinary as far as climate goes”
483 ” Ditto and we can’t even decide which, if any, set of treemometers, shellfish, layers of mud or offerings to the gods are the ones we should be using, nor can we agree how we should be analysing them, even if they are the right ones to use”
591 “Actually, we’ve been winging it ever since this circus started and we’ve still not even decided if we’re on the right track”
593 “We’re using a whole load of assumptions that we’ve really not got a shred of experimental data to support and we can’t even agree about what we should be measuring”
594 “We’ve been winging it and we’re still flapping like mad and getting nowhere fast”
595 “We’re still flapping our arms, we reckon we’ll fly because we’re doing basically what birds do and they fly”
608 “Anyone know what’s the best bird suit to wear whilst we flap?”
638 “Apparently, if we get enough monkeys typing, we’ll be able to produce the complete works of Shakespear!”
638″We’ve made a load of guesses, now we’ll start thinking about checking if they’re right.”
640 “However, we really don’t know how to check if our guesses are the ones we should have been using for the past, oooh, 30 years?”
665 “how warm is it anyway?”
754 “Quick, we really don’t know what we’re on about, write some management speak, pass me a copy of “The Dilbert Principle”!”
805 “Who’s for a quick game or three of Blackjack?”
I think I can sum it all up now.
A few scientists convinced themselves that we’re heading for trouble, a lot more thought it’d probably be a good idea to have a look at this, afterall, there’s not a lot else to do at the moment with all these new PhD students. Some politicians decided that this looked like a good band waggon to hitch a ride on; some of the scientists involved have been coughing discretely, and pointing out that we really don’t know enough yet, but possibly with a bit more time, money & research we’ll have a better idea. Some more scientists have also decided that now they’ve rubbed the lamp and a Genie’s popped out, they’d better start thinking hard about which three questions they should be asking it, because knowing what Genies are like, there’s going to be tears before bedtime if they don’t get it right!
In the mean time, plenty of hangers on have realised that there’s a few easy bucks to be made and careers to be advanced here and if anyone rocks the boat, there’s going to be trouble!
You’ve left out the primary statement buried in the Appendicies:-
“We definitely possibly maybe think we might know how it all works assuming our assumptions are right provided we really think we maybe have we’ve chosen the right assumptions to assume in the first place, assuming that the theory of manmade emissions of Carbon Dioxide really is a main driver of climate, assuming it really can procduce changes in global averaged temperatures as some Swedish bloke thought over a hundred years ago, providing that he was wrong to completely change his mind 10 years later!”
How is one supposed to interpret “ensemble of opportunity”?
(English is not my mother tongue)
It’s worse than I thought…..
Thanks ever so. With this, to the local publisher, sold out to “settled science.”
LabMunkey:
‘It’s worse than we thought…..’
Well not quite – there is considerable difference between model ensembles and individual models. Much of the IPCC’s caveats highlighted in this post are comments about the deficiencies of individual models which could be surmounted by a well constructed ensemble methodology and research design. In my view this is the direction of travel that climate research should follow. The problem is that it relies upon both individual and collective, highly coordinated effort.
It is well established through research into predictive markets that aggregation eliminates unrealistic assumptions/beliefs and gives a central moment which is much closer to the underlying reality. To give an example: a study of 43 independent groups forecasting five year EPS and DPS figures produced 43 valuations of a target company none of which were close to the actual share price. The average was, however, very accurate – being just 30c out on a $34 share price. This type of study has been replicated on numerous occasions in different contexts. Obviously ensemble modelling of stock prices is far more straight-forward than modelling climate but the underlying approach is sound. As far as I understand the construction of an ensemble such as this one needs a number of conditions in place: the modelling should be conducted independently with different research groups and should not be simple replications. They should capture a wide variety of both exogenous and endogenous uncertainties and a wide variety of initial conditions. They should also be done coterminously eliminating feedback of individual model results into subsequent modelling and so on. The research design should examine ensemble performance on a stringent back-test and finally, and most importantly the team who analyse the ensemble should not be one of the teams doing the modelling.
Given this and if the ensemble performed well – as I suspect it might – then I think we might get some really credible forecasts and ultimately understanding of the causes of climate change.
Well, of course they have to feign uncertainty, because if they let it be known that they actually know it all then they wouldn’t get funding for more research. Come to think of it, that’s probably why those trivial and very minor errors sometimes slip through into AGW papers and articles; the Illuminati just don’t want to reveal yet that, in sober truth, they know everything that is to be known. It would blow our tiny minds.
Like Pooh-Bah: “I am, in point of fact, a particularly haughty and exclusive person, of pre-Adamite ancestral descent. … But I struggle hard to overcome this defect. I mortify my pride continually. When all the great officers of State resigned in a body because they were too proud to serve under an ex-tailor, did I not unhesitatingly accept all their posts at once?”
“each based on a given set of physical assumptions and including a number of uncertain parameters”.
Translates as: “We make it up as we go along”.
@ur momisugly richard telford, October 21, 2010 at 12:12 am:
Proxy data are an integral part of the models. To say that something is “not a criticism of the models but of the proxy-data” is a tad tenuous, and kind of misses the point.
I can think of much better places to conceal uncertainty than in the IPCC report.
Good, I’m glad you can, and I’m sure most of us are aware of other examples of hiding uncertainty. But the fact remains that uncertainty has been concealed in the IPCC report.
Petter says:
October 21, 2010 at 1:22 am
‘How is one supposed to interpret “ensemble of opportunity”?
(English is not my mother tongue)’
Don’t worry, English *is my mother tongue and it still sounds like bs to me.
Professor Bob Ryan says:
October 21, 2010 at 1:30 am
LabMunkey:
‘It’s worse than we thought…..’
Well not quite – there is considerable difference between model ensembles and individual models. Much of the IPCC’s caveats highlighted in this post are comments about the deficiencies of individual models which could be surmounted by a well constructed ensemble methodology and research design. In my view this is the direction of travel that climate research should follow. The problem is that it relies upon both individual and collective, highly coordinated effort.
It is well established through research into predictive markets that aggregation eliminates unrealistic assumptions/beliefs and gives a central moment which is much closer to the underlying reality.
—————
If there are base deficiencies in the ASSUMPTIONS IN THE THEORY underlying the models then this point is invalid. You can refer to the stock market crash of 2008 caused by CDOs based on risky sub-prime mortgages bundled together and sold as AAA debt using the statistical trickery referred to above.
I have run a GCM on my computer and by changing the CO2 residence time from that stated by the IPCC, 100-200 years, to what current research has shown it to be, 5-10 years, the supposed critical temperature rise becomes a fall in temperature, everything else being equal. Just shows how you can confuse with rubbish inputs into models. Do they work with chaotic systems? I do not think that they do.
@Petter – Describing a data set as an ensemble of opportunity means that they haven’t got any plan for how to get an unbiased, representative data set – they’ve just used whatever data is available. They hope it is unbiased and representative, but who knows?
When you try to measure how reliable a product is, you pick samples on some random scheme that ensures the sample is representative. The current “ensemble of opportunity” of climate models is a bit like measuring reliability by testing all the ones that come back from customers because they don’t work – you will find that nearly 100% of them don’t work (there are some idiots out there, after all). But it’s a data set that is available to you, so unless you have access to a real sample then it might be the best you can do and you will have to infer from it what information you can.
What a strange post! The “deception” is proved entirely by quotes from the AR4!
But even stranger – the first two “deceptions” quoted don’t seem to have anything to do with models at all.
“As shown below, the deception is obvious and requires little scientific knowledge to discern.”
I think this is the most effective way to to restore truth in this debate. My own selection of deceptions in climate science, which can be understood by anyone, is the following:
1. The global temperature record is false:
The assumed transition from bucket to inlet measurements did not happen in 1941 as assumed by all global temperature data sets. This assumption is proven to be false.
A simple verification of types of measurements here
http://ssrn.com/abstract=1653928 (figure 3.3 in downloadable document)
or here
http://climateaudit.org/2010/09/01/icoads-hawaii/
is sufficient to verify that the temperature adjustment ending in 1941 is false.
Temperatures need to be adjusted upwards until perhaps the 1980s and the size of this error is about the size of the complete assumed warming since the 1940s.
This is arguably the most influential error in climate science and alone capable of refuting the whole agenda.
2. The IPCC hides the lack of knowledge about climate feedbacks:
A simple synopsys between the IPCC text and the referenced literature is sufficient to verify this claim.
http://climateaudit.org/2009/07/15/boundary-layer-clouds-ipcc-bowdlerizes-bony/
3. Hide the decline in context
Bringing the prima facie evidence of the climategate emails into context is an undisputable and easy to follow must see lesson for everyone.
http://climateaudit.org/2009/12/10/ipcc-and-the-trick/
4. Prima facie evidence of FOI obstruction and the false statement of the Muir Russel inquiry:
2 days after David Hollands FOI request, on the 29th May 2008, Phil Jones asked Michael Mann in an email:
“―Can you delete any emails you may have had with Keith re AR4? Keith will do likewise. He’s not in at the moment – minor family crisis. Can you also email Gene and get him to do the same? I don’t have his new email address. We will be getting Caspar to do likewise”.
The Muir Russel inquiry concluded boldly:
“we have seen no evidence of any attempt to delete information in respect of a request already made.”
http://climateaudit.org/2010/07/22/blatant-misrepresentation-by-muir-russell-panel/
As professor Ryan has said, an ensemble of models can produce good predictions by averaging their output.
However, this only works well if the models are constructed independently of each other. Unfortunately, all of the models which the ipcc has chosen to use make the same (extremely dubious) assumption about water vapour feedback being positive. My climate model also shows a large temperature increase by using a large positive feedback in water vapour. However, water vapour feedback could just as easily be negative; in this case, my climate model actually forecasts a modest fall in temperature in the next century.
The ipcc models are also assuming a large increase in the rate of carbon dioxide accumulation in the atmosphere. This also appears to be unrealistic; the rate of increase appears to be remarkably steady and shows no sign of acceleration. This assumption has the effect of hugely exaggerating the temperature increase in the model output.
Professor Bob Ryan, can you explain how averaging incorrect models produces a correct result? It seems like you are implying that averaging models with different assumptions produces a better result than averaging multiple runs of the same model. I’m not sure even that more limited statement is true.
There are two main problems with models, both of which result in incorrect results. First is the granularity, since models cannot model small scale convective processes, those must be parameterized and those assumptions dictate the results. Your claim may be true if different modelers are using a quantitatively full range of convective parameterizations. But I highly doubt that is the case, I have never heard of such an analysis. The second problem with models is the problem of chaos. In that case the statistics of lots of runs of the same model would be much more informative than the statistics of runs of different models. That still only reveals an average and an uncertainty which will be quite large.
So, to summarise, Playstation science has limited relevance to the real world.
Well since we are considering models here is my latest take on the basic parameters and observations that the models need to take account of, all drawn into a reasonably coherent climate description:
http://climaterealists.com/index.php?id=6482&linkbox=true&position=4
It is best to go to the PDF version because the layout is easier to follow than the site version.
If you were to bet on every horse to win in a particular race then you have framed your “ensemble of opportunity”. At the end of the race you can, barring disaster, claim to have correctly picked the winner.
Likewise with your climate model “ensemble”. Throw in a model that indicates cooling and you can safely claim that whatever climate seems to be doing is well within your “ensemble” of “projections”.
Petter says: (October 21, 2010 at 1:22 am) How is one supposed to interpret “ensemble of opportunity”?
Try this definition from the web, Petter: “In fluid mechanics, an ensemble is an imaginary collection of notionally identical experiments.”
After all, there is nothing much more “fluid” than climate science…
About two years ago in a climate thread on a non climate site I carried out a very similar exercise, highlighting many of those hidden doubts and uncertainties for the benefit of a wider audience and pointing out the scale of the discrepancy between those doubts and uncertainties and the Summary For Policymakers.
I think this is potentially a very fruitful way for those more expert than me to dismantle the credibility of the IPCC once and for all. The Summary is completely discredited by the huge numbers of reservations and qualifications set out by the contributors in the main body of the documentation leading up to the Summary.
It has long been my opinion that the Summary is essentially a work of fiction.
In fact it was observing that very situation that gave me the incentive to try and produce something better and more in tune with real world observations.
I put it a little more simply. NONE of the models ujsed by the warmaholics has ever been validated.