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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Alan Wilkinson says:
September 3, 2011 at 1:20 am
Clearly a ridiculously stupid claim. A model is a scientific theory. Changes to the theory change the model.
AND:
Paul M says:
September 3, 2011 at 1:27 am
I baulked at that too. Firstly it’s a massive contradiction since no model (and certainly not all models) satisfy ALL observations so the stated criteria will never be met. Did he really mean what he just wrote? Baffling!
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AGREED
John Marshall says:
September 3, 2011 at 1:57 am
If your theory fits observations in climate science it will certainly NOT fit the models.
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YES. But equally true and compelling is that: if your theory fits the model, it sure as hell will not fit empirical observations!!!
A model is nothing more than software code.
It’s functions are written to perform operations on input data. They cannot do anything more than what the logic has told them to do, however right, wrong, or out of sequence.
Whatever means are used to mimic chaos (random numbers generators) they can never accuractely model such apparent chaos until all known and unknown cyclic variations are isolated from Climate. They will eventurally fail, and do fail, at some point, no matter how well the program has been adjusted to match the wiggles of a pre-selected run of data. They must fail at some point, because the functions and logic are not the actual forces operating in climate, and too much has not been accurately defined.
A weather forecast model begins to turn off the track at around 3 days, and the range of actual error will not be constant 3 days out. They become useless past 10-14 days. Climate models cannot be any better than those confines, being more complicated. They should not be used for prediction.
Climate Forecasters would be better suited, at this level of understanding, to using pattern matching skills and seat of the pants decision making and observation of animanl and plant behavior. Why? Because nature itself has embedded the necessary instincts into species to cope with climate change and seasonal extremes. That includes man. Over centuries, millenia and millions of years. You cannot model that because the entire Planet is the computer.
Truthseeker reiterates something which I have muttered about on these blogs for some time now, and its this.
The IPCC stands for the Intergovernmental Panel for Climate CHANGE…. not RESEARCH; Change. The presumption, as required by the scientific funding, is that CHANGE is what the scientists must be looking for.
Sustitute ‘statistics’ for ‘models’ and the old truism applies:
‘They use statistics as a drunk uses a lamppost; more for support than illumination…’
Indur
Last time I checked it was necessary and sufficient to fit the observations, but “fits the models”!?!?
Last time I checked, and that was in population health delivering population level programs that resulted in real outcomes for humans, we had to satisfy these criteria:
# necessary
# sufficient
# lack of temporal ambiguity.
I am not clear why you invoke only two criteria: ergoneccessary & sufficient in the deluded AGW ‘science’ debate,
@Gleick
> satisfies all of the observations, agrees with physical theory,
> and fits the models.
“model” is a fuzzy word. If Gleick meant that all future scientific theories must be validated through today’s GCMs, then yes that is a very silly statement. Sadly it seems to be embraced by the current regime of peer reviewers.
Science is not science without observations.
Having said that, I would like to point out that scientific observations are not possible without models for measuring physical entities. Perhaps there are gods who can perfectly perceive temperature, pressure and space/time directly, but we humans utterly depend on model-based transducers to perceive the universe around us.
We perceive using proxy devices whose symbolic output must be interpreted and are subject to noise and measurement error. A model must be created and applied to render these interpretations.
For example, there is no way to observe temperature without using some kind of non-trivial model based on the thermal properties of proxies such as alcohol/mercury expanding or contracting in a thin capillary or current flowing through a thermocouple.
Even our subjective sense of time and space cannot be trusted for scienfiic purposes. We must employ rulers (with modeled markings) and watches (with modeled electro-mechanical escapements) which operate using standard models (metric) that require interpretation and are thus subject to two kinds of errors: using a wrong model and making errors interpreting the model output. (Of course, “all models are wrong, some are useful” – Geo. Box)
The real problem is the ‘engineering fallacy’ that lets us forget that these instruments are really models of reality. But we pretend that we are gods who can perceive matter and energy precisely by merely “observing”.
Just saying.
Peter Wilson says @ur momisugly September 3, 2011 at 1:47 am “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.”
It is not the CO2 emissions that make the models yield well-fitting hindcasts. It is the the input of aerosols. And it is not the “actual forcings” of aerosols; rather it is estimated and conveniently chosen values for aerosols that make the hindcast fit well.
There are various choices on how to measure solar variations — and the scientific communitiy is not in agreement on which ones have primary impact on climate. The GCM models used by the IPCC use models that choose solar measures with little variation.
Barry WoodsBarry Woods says:
September 3, 2011 at 1:07 am
Barry,
The simple answer is politics driving subjective research. “I’ll pay you well to find evidence to support my agenda.”
The elegance of lying.
I guess Al Gore took a direct hit and his investors in his scam are coming for him.
I just read Gleick’s article. I knew his bias before, but I’m disturbed at his embrace of the political aspects of the story.
I don’t have an account at Forbes, and won’t bother to make one, but I was tempted to ask about the “fits all the models” phrase. If the observations do fit models, I’d argue that would be nearly proof that we completely understand the science. Clearly observations (poor as they are) don’t fit the models (poor as they are) and there’s a lot of science left to be done.
If Gleick seriously considered his statement that scientific progress requires that it fits the model, then his view of the scientific method forces observers in a single direction and puts models upon a pedestal that I think is reserved for good observations.
Piffle
As an AeroSp Engr student, I was taught to develop and use models to simulate flight dynamics. We were also taught that if the output of the model(s) did not match observations, you needed to change the model, not tweak the observational data. Maybe climate scientists should bring a couple of engineers into their groups?
Bill
Let me try my idea of WHY warmaholics trust models. When the IPCC was given a mandate to prove that CO2 caused CAGW, they had a problem. They could show that adding CO2 to the atmosphere changed the “radiative balance”, but they could not show, quantitatively, how much this change made to global surface temperatures. 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. If models do not provide the proof, as most scientists would agree, then this approach was simply nonsense. So the IPCC had to maintain, and still must maintain, that models provide actual proof, otherwise they must admit that CAGW is built on quicksand.
And there is still no science that enables anyone to estimate change in surface temperature from a change in radiaitve balance. Can anyone answer my simple question. If CAGW occurs, does the lapse rate change?
It’s simple: Climate science is an oxymoron.
jonjermey says:
September 3, 2011 at 2:04 am
You’re right–there are two universes: Models and Reality. The two seldom coincide.
“and fits the models”.
There are models and then there are models. More precisely there are theoretical models and there are practical models.
A theoretical model would be derived from the theory, but may be impractical in ordinary life (i.e. a theoretical model of an atom).
On the other hand, the quest for practical models (i.e. computer programs) for large chaotic systems such as weather and climate are easily arguable as “crude.” Some of these same techniques are used daily in an attempt to model the stock market, and some are actually used to “bet” money, but it is just that, a “bet” on a “gamble.” Often they work just fine, but when an new (or forgotten) scenario comes up, they, more often than not, will lose the farm.
Weather and climate practical models are easily arguable as “crude” because they have so little “training data.” Yes, it may be terabytes, but who can say they contain enough data points, let alone cover all possible scenarios for weather and climate. We all know that data does not exist.
Adam says:
September 3, 2011 at 1:12 am
“Why do people trust models.”
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Adam, the answer is a lot simpler than that…..
…”it’s all they’ve got”
Parameters in the models can be tweaked small percentages to get the answers they want. If the model doesn’t match observations, go back and tweak it again until it does….
Climate science morphed into computer programming a long time ago. They can’t even talk about the weather any more without saying “our most reliable model”
…it’s really disgusting
EDIT: The comments by Gleick, that is
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.
We are talking about a Forbes article after all.
The models are a perfectly good part of science.
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.
Theories must agree with the observations. The observations don’t have to agree with any theory. By George, the blasted theory may be WRONG.
This is equally, if not more so, true for Models.
Someone should hit Mr. Gleick with these truths. As if it would do any good with these High Priest of The Church of Global Warming,
@Peter Wilson
Peter hits the nail squarely on the head. Since the models don’t agree with each other predicting future climate, any claimed skill at hindcasting can be ignored. In fact, it can be concluded that any claimed skill at hindcasting is the result of scientific malfeasance, not blind luck.
@Gleick
> satisfies all of the observations, agrees with physical theory,
> and fits the models.
Gleick’s intellectual forbears said much the same thing at Galileo’s trial, with regard to the Ptolemaic model.
Nothing’s changed, except the claimed focal point of the worship. The *true* focal point, then as now, of course, is always the men who are running the system and who will do and say anything to keep it from being upended.
“In short if you can’t calculate something chances are you don’t properly understand it.”
Well, you got that right anyway.
Alan Wilkinson says:
September 3, 2011 at 1:20 am
“Clearly a ridiculously stupid claim. A model is a scientific theory. Changes to the theory change the model.”
This claim shows total incomprehension of the matter. If one had physical hypotheses that collectively make up a theory, one would not need models. Models are purely analytic tools that cannot do the synthetic work of hypotheses.
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.
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Thank you……
..obviously then, no one properly understands climate
Peter Wilson says:
September 3, 2011 at 1:47 am
“To then remove a forcing which did occur, and which is obviously believed by the model makers to be critical, and act as if the resultant divergence from observed reality is evidence of human causation, is circular reasoning in the extreme – just what did they expect would happen, no change to the model outputs?”
Brilliant post. The entire post is a must read.
And because they are using models, any particular “idea” about reality makes sense only within the context of the model. It is impossible to take from the model the “ideas” about CO2 and independently use them for prediction and possible confirmation. For that reason alone, these “ideas” are not physical hypotheses and do not belong to science.