Guest essay by Charles Battig, M.D.
There are reams of publications devoted to the mechanics of computer modeling of global climate dynamics, and the predictive results derived therefrom. Mathematicians, experts in chaos theory, fluid dynamics professionals, climatologists, geologists, oceanographers, satellite-data analysts all toil away at constructing a computer model which will accurately embody these sciences in a faithful representation of the global energy interplay known as climate. No one has quite succeeded yet, even with ever faster and more complex computers. The actual observed climate behavior of our planet continues to confound the very best efforts of the very best computer modelers and their models to replicate it.
True climate denial is the real-world denial by mother earth of faulty ersatz computer representations and impersonations.
Science and the arts have different ways of viewing the world, i.e. reality. It is in the field of visual fine arts that an elusive truth of climate dynamics has already been identified and documented. Long ago, an artist portrayed what many in the field of computer modeling of climate have not noticed, or have refused to acknowledge. Yet, his message is often ignored by the computer modeler whose passion for his program blinds him to the truth embodied by this artist. Ardent climate modelers have proclaimed their allegiance to their computer model, rather than to reality.
This icon of visual truth hangs in the Los Angeles County Museum of Art, a few miles away from the University of California at Los Angeles (UCLA). Just recently, a group from UCLA issued a report exploring climate mitigation via a number of modalities. Had members of that report visited the nearby County Museum, perhaps they might have tempered their enthusiasm for the reported findings, all based on studies…studies being shorthand for computer simulations.
“Ceci n’est pas une pipe,” or “This is not a pipe,” painted by René Magritte in 1928 shows a perfectly recognizable smoker’s pipe. Suppress that urge to declare that painter to be out of touch with reality. His painting is more in touch with reality than some climate modelers, for example Prof. Chris Folland, Hadley Centre for Climate Prediction and Research who illustrates such affection for his computer generated world that he proclaims: “The data doesn’t matter. We’re not basing our recommendations on the data. We’re basing them on the climate models.”
Such blind love of one’s own creation is immortalized in Greek mythology by the tale of Pygmalion. Falling in love with your own creation makes for interesting philosophical debates when it is a statue; when it is a climate model, it is science gone awry. It is no longer science but a fanciful detachment from reality.
Magritte’s visual message is that a copy or rendition of an object is not the original object itself. David Blakesley and Collin Brooke’s commentary on visual rhetoric notes that:
“Magritte highlights for our consideration the idea that an image of a pipe is not the same thing as the pipe itself (or the letters p-i-p-e). It is a representation of a pipe, once removed from its referent, the object to which it refers. He also forces us to consider our own reaction to the painting by suggesting that our compulsion to call the image a pipe reveals our predisposition to confuse the image with the thing it represents.”
Here then is the lesson offered by Magritte for the global climate modelers. The computer model is not reality; it is just your attempt to replicate reality. In the complex system known as global climate dynamics, the models are not reality on a computer chip. They are scenarios akin to the fabled three blind men describing an elephant. Stephen Few has used this tale as the starting point for his essay on perception and business intelligence. Each modeler may, or may not, capture a small piece of the climate puzzle correctly, but no one has gotten the whole picture reduced to a valid computer representation. The climate system is so complex and chaotic, that computer modelers have to settle for simplified constructs with open-ended assumptions (parameterizations). Like Magritte’s pipe, the final result is even further removed from reality.
Recently, the National Climate Assessment was released and claims to “detail(s) the multitude of ways climate change is already affecting and will increasingly affect the lives of Americans. Institutionalized computer forecasting masquerading as scientific fact does not make it fact.
Extending the reach of Federal control not only over us, but also over future global climate, the EPA has a new slogan: “Thirty per cent less by 2030.”
Perhaps the “30 by 2030” was chosen by a focus group because it has a rhythmical ring to it, or perhaps a computer projected it to have mass appeal.
Expectations of realistic research results and future climate states based on faulty underlying models are, well, just so many pipe dreams.
Charles Battig, M.D. , Piedmont Chapter president, VA-Scientists and Engineers for Energy and Environment (VA-SEEE). His website is www.climateis.com
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“Ceci n’est pas un climat,”
Magritte, like Folland, was a surrealist.
I used to work in the electricity industry in the UK and one of my roles was forecasting electricity prices. In the early days we had this thing called the ‘Pool” and basically all the generators bid into the Pool with their various operational parameters and prices. There were approximately 100 individual ‘gensets’ all with about 8 different operational parameters and all those parameters had associated prices.
The national grid company (NGC) then used a computer program called GOAL (can’t remember what that stood for) to schedule all the gensets to meet their forecast of demand in the most efficient way. There was then a set of rules to determine the most expensive price for each half hour of the day and this set the clearing price for all generators.
We had a copy of the GOAL program so we could run it ourselves. My first company owned about 30% of all the gensets and another owned about 55% with only 15% owned by others.
We obviously knew all the parameters of our own gensets and as this was shortly after the electricity industry was privatized (1990) we still knew quite a few of our competitor’s parameters. The only thing we didn’t know was their prices.
GOAL didn’t do a bad job of scheduling gensets to meet demand, but sometimes the resulting prices were all over the place and even though we knew 30% of the input with absolute certainty and had a very good feel for the other 70% we would never get the next day’s prices correct to within more than say 5% and often much much worse.
GOAL was so complicated and had been developed over such a long period of time that it was almost impossible to replicate a run even if you had all the inputs as the tiniest of changes to any input parameter could have dramatic and unexpected results.
In late 1993 I moved jobs from the 30% generator to a much smaller company in Scotland that made up a small part of that other 10% via an interconnector to England and had ambitions of building gas fired power stations to generate into the Pool.
My team had to forecast prices on a half-hourly basis for five years out. Obviously our half hourly forecast was only ever meant to be indicative. Prices in the UK spike at 17:00 in January and reach a low at about 04:00 in July and August, but the price profile, both daily and seasonal has a major impact on the viability of marginal gensets.
Back I the early 90’s running on a VAX, GOAL used to take about an hour to run so it would have been almost impossible to use it for our five year forecast, so instead we used a model developed in conjunction with an external consultancy and ourselves.
I had a fairly good idea of the general parameters that needed to go into our model, but whenever we ran it the prices always came out lower than expected. Often quite a lot lower. The main reason for this was that there were lots of new companies, including ourselves, building power stations that were all due to come on stream over the next five years (mostly gas) and sell into the pool.
Our model was imperfect. We knew this and to get anything that ever reasonably resembled actual prices in the short term we had to make many tweaks (parameterizations?), but we felt with all this extra generating capacity coming in to the market prices would ultimately have to fall.
We stuck to our views and fought many battles with our colleagues and even the Monopolies and Mergers commission at one point, who all thought that the dominant generators would maintain a monopoly and keep prices up.
We won those battles and the reason we won them was because we could tell a story about every single number we put into our model and could make a convincing argument as to why those numbers were valid. As it turned out price actually fell below where we were forecasting so we were vindicated.
So what is the purpose of this little story?
Well our model was complete fallacy, it was complete rubbish, but I could have defended any number that came out of it and not only that I could have produced any set of numbers to suit anyone’s aspirations and defended them just as well, high or low and also defended any number I put into it.
Perhaps we were lucky getting it more or less right (direction if not magnitude), but that was only because we thought it was logical that competition should bring the price down. The oil and coal price could have doubled and we may have got it completely wrong (show me someone who can predict the oil price and I’ll show you the richest person in the world!).
Moral of the story: Models with hundreds of parameters can tell any story you want, you just have to be able to sell it.
Charles, thanks for the entertaining reminder that mathematical models of Mother Nature are not reality. Sadly, climate scientists who try to determine how much our climate will warm due to doubling atmospheric GHG levels, are relying almost entirely on their un-validated computer climate dynamic models, simulating climate response to an unrealistic, sudden step function doubling of external radiative forcing of atmospheric GHG levels, instead of examining readily available data on slowly rising GHG levels and global average surface temperature anomalies.
The slowly rising atmospheric GHG levels provide a very close approximation to a static solution for a forcing of the complex climate system with a constant external force (the external GHG “radiative force” applied to complex climate dynamic models), in much the same way as a single degree-of-freedom spring-mass-damper system can be used experimentally to determine its spring constant by applying a very slowly changing external force to the mass and recording the slowly changing displacement of the mass without exciting the system dynamic responses, but only the static response. The effects of slowly rising GHG levels on global temperatures should have a response signature that looks somewhat similar to the time history of the slowly rising external “radiative force”.
The anonymous “Jeff L” was close to getting the right answer in his Feb 13, 2014 essay in this WUWT forum where I left more detailed comments regarding the Transient Climate Sensitivity (TCS) rather than Equilibrium Climate Sensitivity (ECS) that he identified from the data, without using a complex climate dynamic model. The Right Climate Stuff Research Team of retired NASA Apollo Program veterans has documented a much more detailed discussion of this “experimental approach” to identifying and bounding Transient Climate Sensitivity (our definition vs. the IPCC’s unverifiable Transient Climate Response (TCR) metric based on un-validated climate model results) on our website at:
http://www.therightclimatestuff.com/BoundingClimateSensitivityForRegDecisions.pdf
captainfish says:
I’ve always wondered why it is 30% by 2030 based on 2005 levels. Why 30%?
It’s like 20 by 2020 or 40 by 2040, it’s catchy. Doesn’t have to mean anything scientifically, it’s just catchy. Easy to remember, nice slogan, fits on a tee-shirt.
It also has the other appealing factor of being so far off no one is going remember by then and far enough of that it seem too remote for people to strongly oppose it now.
Greg says:
“Ceci n’est pas un climat,”
Magritte, like Folland, was a surrealist.
I’ll call that the CNPUC model , you have to have a good acronym to be taken seriously.
ffohnad says:
June 3, 2014 at 12:05 pm
“It is useless to attempt to convert a true believer, no matter the belief. Once one enters this stage a blindness to and antagonism toward anything that conflicts with this belief is mandatory.”
_________________________
Your assessment exactly matches my own experiences, especially the antagonism part. A simple question to a believer has led on more than one occasion, to immediate anger on the part of the believers, escalating to heavy doses of verbal abuse, physical violence and being abruptly thrown out of social gatherings at the homes of such believers.
example:
Believer: 97% of scientists say that Global Warming is real.
Non- believer: Do you know that statement is a logical fallacy?
Believer: You’re no climate scientist! Who the hell do you think you are? You deniers are responsible for ruining the planet! You must work for one of the oil companies. People like you should be rounded up and shot! blah blah blah in a voice getting louder and screechier by the second until… out of the gathering of hostiles, also cursing and screeching, up steps a red- faced woman who tried to scratch the non- believers face and then, the situation deteriorated. One simple question…
once upon a time, oral roberts told people they had to buy a kinder-garten tracing of his hand or god would wipe him off the earth.
mann sold his hockey stick pic for more.
see, you don’t need sex to sell crap (let me say, though, that just because it’s crap doesn’t make it art).
death carries the big frisson and sells just as well.
and it is a morality of death being promoted, here.
Village Idiot says:
June 3, 2014 at 12:07 pm
Hmm. What a bitter man! Distilling away the pretentious waffle, the take-home message is we must be 100% sure of the future before we do anything? Does anyone here live life like that? Or don’t we all just basically live in a world of probabilities?
___________________________
Since the possibility exists that your home might be struck by cosmic debris, have you made your home in a bunker, or does merely wearing your tinfoil hat suffice as protection?
Oh the Humanity, off by 0.2 percent or less. I should learn not to use percents with anomolies.
If the coming El Nino spikes temps like the 98 one, everything will all be back in agreement, see you all around Christmas.
Village Idiot:
You should be acquainted with the Rule of Nines. For whatever reason: evolution, cultural history, psychological conditioning [choose your reason], the human brain is nine times more likely to accept a falsehood as true; Wm McClenny wrote an extended essay on the subject. If I found it (without looking for it) you should be able to as well.
“The Sky is Falling, or On Revising the Nine Times Rule”
It should cause you think about what you believe … … …
Insanity: Continually confusing the map with the territory.
I just5 created my own climate model by throwing some paint at a canvas.
Sadly, it’s probably no farther off the mark than the whoop-de-do contraptions rigged up by global warming alarmists.
Friends:
I write to support the above article because several comments in the thread demonstrate that some people fail to recognise they share the problem described in the article.
Models are not reality and are not intended to be reality.
A model is a simplified representation of reality.
Being simplified, no model is an exact emulation of reality; i.e. no model is a perfect and no model is intended to be perfect.
A model is constructed for a purpose.
For example, a model of heat loss from a cow may assume that a cow is shaped as a sphere with the surface area of a real cow. And this simple model may provide an adequate quantitative indication of how heat loss from a cow varies with the cow’s metabolic rate. Thus, this hypothetical model may be very useful.
But that model of a cow cannot be used to indicate the movements of a cow. A model of a cow which includes legs is needed for that.
Another model of a cow may be constructed purely for the pleasure of the modeller. In this case it may be carved from wood and painted.
Possible purposes for models are infinite.
A model may have many forms.
It may be physical, abstract, algebraic, numeric, pictorial or an idea. If its form fulfils the desired usefulness then it is an appropriate model; i.e. it can fulfil its purpose.
And all of the above is why the indications of a model cannot be assumed to indicate anything about reality unless those indications have been demonstrated to match reality.
In other words, as Check succinctly says at June 3, 2014 at 2:55 pm,
Richard
James (June 3, 2014 at 12:42 pm) “The models do include rain, wind and snow.”
So a snow globe is actually a model. Learn something new every day.
Tsk Tsk Roy-
You missed the point…”this is not a pipe”. “This is not Roy’s Chart. It’s a digital duplication of Roy’s Chart. You did not paint that. *evil grin* Love ya!
No one has quite succeeded yet, even with ever faster and more complex computers. The actual observed climate behavior of our planet continues to confound the very best efforts of the very best computer modelers and their models to replicate it.
Complex computers ain’t makin’ it and they never will. But it can be done. Two things are required: a pencil and the back of an envelope.
I’ve said this until I’m blue in the mouth: To simulate an inconceivably complex and chaotic system, you need to do it top down. I know what I’m talking about. I used to do this for a living.
The Reification Fallacy Returns
Confusing a representation with what is represented is easily the most common instance of the fallacy, but more generally, reification entails treating an abstract concept — a mental place holder intended to represent an indeterminate number of things of the same kind — as if it were a concrete reality, or as Aristotle would say, treating a “such” as if it were a “this”. The Earth’s climate is a “this”. Have you ever noticed that science is not really good at studying unique things? Science works best studying *kinds” of things. Unlike astronomers studying the spectra, motions, changes, etc. of thousands of stars before trying to understand certain kinds of stars, make predictions about them, and occasionally about a particular star, the global climatologist starts with the atmosphere of one and only one earth-like planet, compares it to nothing similar, and pretends to understand the “this” because he thinks he understands all the little “such”es of which it is made. A dubious science, this science of a one-of-a-kind thing.
My previous comment on an earlier thread discuses the reification of mathematics at some length:
http://wattsupwiththat.com/2014/05/26/well-color-me-gobsmacked/#comment-1646826
All (including me) commenters on this and other threads are wasting their time.
When I read about the Democratic politicians walking out on a presentation, I realised that the sceptics are just talking to each other.
No one in power is listening.
A wise person told me, in a similar situation, just stop talking.
Dont waste effort on doing anything until you know it will be effective.
Badly. See what Dr. David Legates says about their handling of precipitation here (from halfway down page 9 thru page 12):
https://wattsupwiththat.files.wordpress.com/2014/06/6-3-14-witness-testimony-legates.pdf
“The map is not the territory… The only usefulness of a map depends on similarity of structure between the empirical world and the map…”
― Alfred Korzybski
richardscourtney Yes models are constructed for many purposes but the person whom craved a model of a cow never expect to be able to milk it. I can’t say that for climate modelers. There think there models can be milked and moo, yet about the only think their model produce is male bovine f, we let put it this way you don’t want to eat it. Neither should you believe it.
A picture is a representation of reality, as are models, and also words. They are distinct from reality.
We humans are tuned to the range of visible light, which represents a tiny slice of the vast EM
spectrum. I submit we are primarily visual creatures. Seeing is believing.
Even better…Learning never ends. Unfortunately, neither does forgetting.
/strange formatting mode
The EPA’s new CAGW propaganda slogan, “Thirty per cent less by 2030.” does sound better than say, “0.018C less by 2100”, which, according to EPA’s own model calculations, is what EPA’s war on energy will hypothetically accomplish…
Machiavelli said it best in his book The Prince, “For the vast majority of mankind accept appearances as though they were reality, and are influenced more by those things that seem, than by those things that are.”
This Machiavellian truism is the foundation upon which the entire CAGW scam is based. It’s about optics, deception and obfuscation rather than on empirical evidence and the truth.
And so it goes…until freedom and truth are restored.
Very good article. The most difficult task in training young engineers who are going to be using models is explaining that the model is not reality. Richard S. Courtney makes the point quite clearly above.