by Indur M. Goklany
Phil Jones famously said:
Kevin and I will keep them out somehow – even if we have to redefine what the peer-review literature is!” – Phil Jones 8/7/2004
Today, we have an example:
“[T]his is also the way science works: someone makes a scientific claim and others test it. If it holds up to scrutiny, it become part of the scientific literature and knowledge, safe until someone can put forward a more compelling theory that satisfies all of the observations, agrees with physical theory, and fits the models.” – Peter Gleick at Forbes; emphasis added. 9/2/2011
Last time I checked it was necessary and sufficient to fit the observations, but “fits the models”!?!?
So let’s ponder a few questions.
- 1. Do any AOGCMs satisfy all the observations? Are all or any, for example, able to reproduce El Ninos and La Ninas, or PDOs and AMOs? How about the spatial and temporal distribution of precipitation for any given year? In fact, according to both the IPCC and the US Climate Change Science Program, they don’t. Consider, for example, the following excerpts:
“Nevertheless, models still show significant errors. Although these are generally greater at smaller scales, important large scale problems also remain. For example, deficiencies remain in the simulation of tropical precipitation, the El Niño-Southern Oscillation and the Madden-Julian Oscillation (an observed variation in tropical winds and rainfall with a time scale of 30 to 90 days).” (IPCC, AR4WG1: 601; emphasis added).
“Climate model simulation of precipitation has improved over time but is still problematic. Correlation between models and observations is 50 to 60% for seasonal means on scales of a few hundred kilometers.” (CCSP 2008:3).
“In summary, modern AOGCMs generally simulate continental and larger-scale mean surface temperature and precipitation with considerable accuracy, but the models often are not reliable for smaller regions, particularly for precipitation.” (CCSP 2008: 52).
This, of course, raises the question: Are AOGCMs, to quote Gleick, “part of the scientific literature and knowledge”? Should they be?
- 2. What if one model’s results don’t fit the results of another? And they don’t—if they did, why use more than one model and why are over 20 models used in the AR4? Which models should be retained and which ones thrown out? On what basis?
- 3. What if a model fits other models but not observations (see Item 1)? Should we retain those models?
I offer these rhetorical questions to start a discussion, but since I’m on the move these holidays, I’ll be unable to participate actively.
Reference:
CCSP (2008). Climate Models: An Assessment of Strengths and Limitations. A Report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research [Bader D.C., C. Covey, W.J. Gutowski Jr., I.M. Held, K.E. Kunkel, R.L. Miller, R.T. Tokmakian and M.H. Zhang (Authors)]. Department of Energy, Office of Biological and Environmental Research, Washington, D.C., USA, 124 pp.
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omnologos says:
September 3, 2011 at 3:04 am
Excellent. Gavin reveals the deepest sort of sheer prejudice.
LazyTeenager: In short if you can’t calculate something chances are you don’t properly understand it.
Hmmm. I’ve got 13-20 models with 13-20 different calculated outcomes. Chances are….
“The models are a perfectly good part of science”
Agreed.. and what is the falsification test for the climate models? I think the current lack of warming has already falsifiied ALL of the IPCC models.
Any model that does not have a method of falsification is religion, not science.
LazyTeenager says:
September 3, 2011 at 6:32 am
“Well its not uncommon for people to put up their personal definition of science and scientific method and get it wrong. People here do that all the time.
Ordinary language is poor at describing the complexities of climate. In short if you can’t calculate something chances are you don’t properly understand it.”
I think most people here understand science and certainly scientific method more than you give them credit for. If by not understanding science and scientific method means that we hide data and obfuscate data that we do show others, then yes I would agree we do not understand science and scientific method.
The inabilty to calculate something does not mean that it cannot be understood. I do not reduce to mathematical equations everything I need to understand. If I did I would not be able to reply to your comments. As for the complexities of the climate, personally I don’t think there is a computer that has been built that can predict climate to any degree of accuracy. Especially when it has been fed a stream of supposition and bigotry masking itself as data.
Jim Cripwell says:
September 3, 2011 at 5:58 am
“There was no way to do any actual experiments on the atmosphere, so the only recourse to provide the needed proof was to use models.”
Excellent point. However, since that time, Svensmark and Kirkby have shown us how to do experiments on the atmosphere. Of course, what they have shown us was obvious to all scientists.
The Warmista have always found themselves arguing the truly childish position that they cannot experiment because they would need a second Earth to experiment on.
LazyTeenager says:
September 3, 2011 at 6:32 am
Well its not uncommon for people to put up their personal definition of science and scientific method and get it wrong. People here do that all the time. And climate modelers are the most proficient of all in “putting their personal definition of science and ignoring the scientific method.
We are talking about a Forbes article after all. Are you saing the publisher controls the content? I say where it’s published doesn’t matter; truth is truth.
The models are a perfectly good part of science. I refute your description of “perfectly good”. They’ve done a horrible job so far. They can’t even hindcast without significant adjustments so how, not knowing the future adjustments needed in the model, can they ever forecast?
In fact as a way of capturing understanding of climate they are much better than the enumerate hand waving that is popular here. Ordinary language is poor at describing the complexities of climate. In short if you can’t calculate something chances are you don’t properly understand it. Your concept of “capturing understanding” needs refutation–a model is simply a pile of code with a prior objective in mind; it only fortituously matches the real world.
Have you ever personally run computer models? I have–thousands of them. They do a huge number of mathematical calculations and spit out an approximation based on your basic assumptions and pre-programmed algorithms. Very seldom is there a surprising conclusion–you pretty much know the outcome beforehand. If not, you simply adjust the model and/or the data to arrive at a preconceived notion. And climate models are no different from the type of models I’m familiar with.
You put much more stock in models that I ever would. This article complains that some would require that “models” be part of the objective evaluation called “science”. I would completely disagree (waves hand).
If you study the claims made by climate change advocates, the political power levers they employ, you will learn much about how regime change is effected on decadal scales by the US power elites.
Whether that’s a comfortable thing for US Republicans to hear, I don’t know.
But there are significant parallels……..
Parametrized models as are used in climate science very consistently predict what model builders believe will happen, with very high accuracy.
Thus, it we require scientific theory to fit the models, then we are requiring theory to be consistent with bias. That is not science, it is superstition.
This has been shown time and time again. Parametrized models predict the bias of the model builders that set the parameters. They do not predict future climate, any more than they can predict the future price of gold.
The average person knows that gold is likely to go up in price over time, because this has been the pattern over time. We also know that temperature has been going up since 1750, so it is likely to go higher in future. Thus, it doesn’t take a computer model to predict this.
What we don’t know and can’t predict are the fluctuations. The increase in gold prices is not constant, thus there is money to be made if one can predict the local hills and valleys.
The same is true in climate. Global warming has been going on for 350 years. Any moron can predict that it will continue. However, within those 350 years there have been local peaks and valleys. Over the past 150 years they have occurred on a cycle of about 60 years. The question for a skilled prediction is whether we will get another 60 year cycle. None of the climate models have predicted is that this 60 cycle will repeat going forward. Current observations suggest otherwise, which suggests that the climate models lack skill.
a model is just a theory written in a programming language.
sharp point – nice post!
” In short if you can’t calculate something chances are you don’t properly understand it”
If you can calculate it you made assumptions!
Jim Cripwell:
Turn your question around, and you have the key: If the lapse rate does not change, can CAGW occur?
I have given the definitive answer to that with my Venus/Earth comparison. The lapse rate does not change, it is THE long-term governing effect, and CO2 AGW does not occur. Those who introduced the adiabatic lapse rate into the debate, as clear and convincing evidence against the greenhouse effect promulgated by the consensus, were right, and my Venus/Earth analysis makes that obvious and definitive for any real progress in a true climate science.
LazyTeenager says:
September 3, 2011 at 6:32 am
I have to agree, there is a lot of hand-waving here, as in most blogs. There is also a lot of good solid science, much of which admittedly goes over my head. That is uncommon.
I do have to say that al lot of your comments could and are interpreted as hand-waving, as this one is. Kind of ironic, really!
But what we are discussing is the actual science (non-hand-waving) of Spencer’s paper, and the very hand-waving excuse of the editor for resigning. More irony perhaps, or is that what you meant?
Peter Wilson says:
September 3, 2011 at 1:47 am
My understanding of the IPCC case for having confidence in the predictions of the GCMs can be summarised thus:
All the GCM models (13 I believe) are able to hindcast the climate of the twentieth century with acceptable accuracy, once the actual forcings (CO2, solar variations, volcanoes, aerosols etc) are programmed in. What is more, if the human CO2 emmisions are removed, the models fail to show the warming that actually occurred, thus proving that we are responsible for the increase in temperatures. The success of the GCM’s in hindcasting is powerful evidence that the forward projections of the same GCMs are valid and reliable.
Bold mine.
So, what if one of the other variables: solar variations, volcanoes, aerosols, etc. is removed? Do the models also fail to show the warming that actually occured, thus proving that that specific variable was responsible for the increase in temperatures?
Just askin’.
Gives a whole new meaning to the term “special needs science”.
Dear LazyTeenager,
There’s an old Irish saying: “Not everything that can be counted, counts – and not everything that counts can be counted.” Don’t confuse “calculation” with “understanding”, or “wisdom” with “intelligence”.
David, UK says:
September 3, 2011 at 1:32 am
To borrow from Al Gore: BULL[snip]! If all the models individually are crap, then 20 models together are a whole heap of steaming BULL[snip].
Snip? You can’t say “bullshit” here anymore? Not even in context to an intelligent crowd? I mean, who got hurt?
I’m beginning to think the biggest mistake is arguing against ‘the models’, it can certainly be entertaining, but it does nothing to inform the general public still unaware of just how duped they are.
Which ‘model’?
http://theresilientearth.com/?q=content/seven-climate-models-seven-different-answers
What’s really going on: http://hockeyschtick.blogspot.com/2010/04/nasas-changing-facts.html
It’s a complete and utter scam. That’s the only Model they have and the only one they use, all other ‘models’ are irrelevant except for continuing distraction from this ClimateScamModel.
That NASA is shown here to be without any scientific integrity whatsoever is what is important, because one of all the institutions using their historic science credibility to con us.
They are morally, and fiscally, responsible for the misery being imposed on the general population through their support of this ClimateScamModel. As is the IPCC.
LazyTeenager says: September 3, 2011 at 6:32 am
[…]
In short if you can’t calculate something chances are you don’t properly understand it.
You have described climate science quite aptly.
The overconfidence in climate models probably stems from the folks getting overexcited with the real beauty of simple models which are able to predict future outcomes.
An example of a successful model would be one which can predict how near to earth a comet may pass. While orbital mechanics is complex, the variables are relatively simple in comparison to those affecting planetary climate.
It seems that certain folks at NASA have gone a bridge too far with their models, and are having trouble crossing back over.
Peter Gleick contends there are three criteria for a new theory to replace the existing theory (of climate change?) It will be accepted when it “……..satisfies all of the observations, agrees with physical theory, and fits the models.”
It seems to me that a model could not be any more scientifically valid than the level of scientific understanding (LOSU) that provides its foundation. If one or more components of the scientific understanding are being questioned, one would expect there to be disagreement with the models that are founded on the science … or assumptions… in question.
There are several important areas in the climate science today that the IPCC admits the LOSU is low. Should not the assumptions arising from these imperfect understandings be subject to scientific inquiry without subjecting the inquiries to such a circular litmus test?
Hey, Ric Werme. Thanks for the link! I knew there was a reason I keep haunting this site. I have been properly re-educated. Oil ain’t abiotic, after all.
“Never mind if something works in reality. What is important is whether or not it works in theory.” That seems to be the attitude of some “scientists” who seem to be abysmally ignorant of the history of science.
The models don’t fit each other in climate science; not even one model run fits another model run, so Gleick is clearly talking about something he knows nothing about.
Fred Singer says in this talk that two model runs of the same model (over 20 or more years) produce global temperature trends that can be as far apart as an order of magnitude.
http://notrickszone.com/2011/09/03/fred-singer-at-suppressed-seii-presentation-1976-to-2000-warming-thats-fake-it-doesnt-exist/#comments
Taking Gleick by his words, we would have to discard the climate models first as they don’t fit each other; personally, I would welcome such a move. The broke western nations could use the spare money well.
Reminds me of the current administrations economic team. They model. They get it badly wrong as judged by apparent result. Make up data, based upon another model, to prove they were right. Exactly the same mind set as Warmists.
LazyTeenager says:
September 3, 2011 at 6:32 am
“In fact as a way of capturing understanding of climate they are much better than the enumerate hand waving that is popular here.”
As others have observed, your next sentence is a prime example of handwaving.
“Ordinary language is poor at describing the complexities of climate.”
I am sure the term “negative feedback” is not part of “ordinary language”. Also, I seldomly debate the Stefan-Boltzmann Law with “ordinary people”; they happen to not know it.
“In short if you can’t calculate something chances are you don’t properly understand it.”
Perfect description of climate modelers. The models have to show predictive skill. They haven’t by now, and they will not in the future, I say, because climate is chaotic (no reference to “complexities of climate” required; the word chaotic is well-defined in a branch of science called mathematics; look it up.) and they will, as a matter of simple logical principles, never be able to improve on the forecasting horizon of a meteorological forecasting model. No, running the model a few times more doesn’t help you very much; see the definition of chaotic.