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.
otter17 says:
September 3, 2011 at 10:22 am
Any takers on creating a model that can perform better and show that CO2 is not one of the primary drivers of climate?
? We have real data, such as Vostok and countless other studies, which show conclusively that CO2 lags behind temperature by c800 years – a real modeller disciplined in real science wouldn’t bother including it as a driver, let alone a ‘primary’ driver..
Get peer review approval from the Journal of Geophysical Research? If not, step aside and let the people brave enough to address the issue using the best evidence we have figure out what to do.
Brave enough to address a non-issue? With no evidence that CO2 is even a driver? What can you possibly imagine they will be able to figure out other than garbage out? That their ‘peers’ think this is science is our loss, even yours.
You’re arguing that magic, illusion, is science because you’re really beginning with a premise that Carbon Dioxide drives climate 800 years after climate temperatures have changed. In other words, your ‘driver’ does nothing for 800 years while great changes take place. Can’t you see how illogical that is? That’s magic, ‘CO2 without doing anything directs great temperature changes for 800 years and then decides to come out and see his handiwork’.
And you really think we should take any of the models seriously? Peer reviewed by like-minded irrationalists peddling mumbo-jumbo?
Friends:
I have posted the following on WUWT before (when some appreciated it) and it seems appropriate to post it again in response to the silly comment by Peter Gleick that is quoted in the above article.
Any model should be validated against empirical observations. This is especially the case for climate models because they do not emulate the climate system of the Earth: I explain this as follows.
None of the climate models – not one of them – could match the change in mean global temperature over the past century if it did not utilise a unique value of assumed cooling from aerosols. So, inputting actual values of a cooling effect (such as a negative feedback from clouds) would make every climate model provide a mismatch of the global warming it hindcasts and the observed global warming for the twentieth century.
This mismatch would occur because all the global climate models and energy balance models are known to provide indications which are based on
1.
the assumed degree of forcings resulting from human activity that produce warming
and
2.
the assumed degree of anthropogenic aerosol cooling input to each model as a ‘fiddle factor’ to obtain agreement between past average global temperature and the model’s indications of average global temperature.
More than a decade ago I published a peer-reviewed paper that showed the UK’s Hadley Centre general circulation model (GCM) could not model climate and only obtained agreement between past average global temperature and the model’s indications of average global temperature by forcing the agreement with an input of assumed anthropogenic aerosol cooling.
And my paper demonstrated that the assumption of aerosol effects being responsible for the model’s failure was incorrect.
(ref. Courtney RS An assessment of validation experiments conducted on computer models of global climate using the general circulation model of the UK’s Hadley Centre Energy & Environment, Volume 10, Number 5, pp. 491-502, September 1999).
More recently, in 2007, Kiehle published a paper that assessed 9 GCMs and two energy balance models.
(ref. Kiehl JT,Twentieth century climate model response and climate sensitivity. GRL vol.. 34, L22710, doi:10.1029/2007GL031383, 2007).
Kiehl found the same as my paper except that each model he assessed used a different aerosol ‘fix’ from every other model.
Kiehl says in his paper:
”One curious aspect of this result is that it is also well known [Houghton et al., 2001] that the same models that agree in simulating the anomaly in surface air temperature differ significantly in their predicted climate sensitivity. The cited range in climate sensitivity from a wide collection of models is usually 1.5 to 4.5 deg C for a doubling of CO2, where most global climate models used for climate change studies vary by at least a factor of two in equilibrium sensitivity.
The question is: if climate models differ by a factor of 2 to 3 in their climate sensitivity, how can they all simulate the global temperature record with a reasonable degree of accuracy?
Kerr [2007] and S. E. Schwartz et al. (Quantifying climate change–too rosy a picture?, available at http://www.nature.com/reports/climatechange, 2007) recently pointed out the importance of understanding the answer to this question. Indeed, Kerr [2007] referred to the present work and the current paper provides the ‘‘widely circulated analysis’’ referred to by Kerr [2007]. This report investigates the most probable explanation for such an agreement. It uses published results from a wide variety of model simulations to understand this apparent paradox between model climate responses for the 20th century, but diverse climate model sensitivity.”
And, importantly, Kiehl’s paper says:
”These results explain to a large degree why models with such diverse climate sensitivities can all simulate the global anomaly in surface temperature. The magnitude of applied anthropogenic total forcing compensates for the model sensitivity.”
And the “magnitude of applied anthropogenic total forcing” is fixed in each model by the input value of aerosol forcing.
Thanks to Bill Illis, Kiehl’s Figure 2 can be seen at
http://img36.imageshack.us/img36/8167/kiehl2007figure2.png
Please note that the Figure is for 9 GCMs and 2 energy balance models, and its title is:
”Figure 2. Total anthropogenic forcing (Wm2) versus aerosol forcing (Wm2) from nine fully coupled climate models and two energy balance models used to simulate the 20th century.”
It shows that
(a) each model uses a different value for “Total anthropogenic forcing” that is in the range 0.80 W/m^-2 to 2.02 W/m^-2
but
(b) each model is forced to agree with the rate of past warming by using a different value for “Aerosol forcing” that is in the range -1.42 W/m^-2 to -0.60 W/m^-2.
In other words the models use values of “Total anthropogenic forcing” that differ by a factor of more than 2.5 and they are ‘adjusted’ by using values of assumed “Aerosol forcing” that differ by a factor of 2.4.
Therefore, each climate model emulates a different climate system. But the Earth has only one climate system. Therefore, at most only one of the models emulates the climate system which exists, and it is probable that none of them do.
Averaging their outputs does not solve this problem because average wrong is wrong.
Hence, it is ridiculous for Peter Gleick or anybody else to imply that doubt is provided to an empirical result by the disagreement of that result with behaviours of the climate models.
Richard
otter17 says:
Any takers on creating a model that can perform better and show that CO2 is not one of the primary drivers of climate?
*************************
There is a better theory which has been proposed in the peer reviewed literature.
Give me $!0,000,000 and a staff of programers and I will create the model. [On second thought make it $ 100 Million. ]
1) There is a 1/2 ° C per century warming which started when records began [at the end of the little ice age] and continues today. Feedback can continue for hundreds of years according to Dr Hansen.
Increased solar activity [and effects like ionization creating clouds and feedbacks .] account for the increase in temperature
2) Superimposed on this there is a 60 year /cooling sine wave going nowhere. Its only effect is to scare the alarmists into saying we are going into an ice age [1978] or going to bake to death [1998]. both are wrong.
http://www.woodfortrees.org/plot/hadcrut3vgl/from:1860/to:2012/plot/hadcrut3vgl/from:1910/to:1940/trend/plot/hadcrut3vgl/from:1860/to:1880/trend/plot/hadcrut3vgl/from:1978/to:1998/trend
1860 to 1880 = Least squares trend line; slope = 0.0104956 per year
[total = .208]
1910 to 1940 = Least squares trend line; slope = 0.0152788 per year
[total = .456]
1978 to 1998 = #Least squares trend line; slope = 0.0122255 per year
[Total = .244]
The last one 1978 to 1998 is the only warming which MIGHT be caused by CO2.
Lazy teenager, people who have problems with math(s) are innumerate not enumerate. Very sloppy, must try harder.
Our friend otter17 believes that Spencer is part of a Big Conspiracy inspired by Big Tobacco’s ways, and that the Remote Sensing paper was published with the intent of getting mud into the water and providing the creationist climate denialist hordes with a straw to clutch as the Merchants of Doubt prevent the betterment of the planet.
Hence any taker of otter17’s challenges will be quickly classified as another member of the Conspiracy, and models and peer-reviewed papers dismissed at once as 100% flawed even when 100% impossible to be retracted.
All arguments with otter17 are therefore pointless. It’s like talking to a chemtrailer or Moon hoax believer.
While computer models have their drawbacks, in fairness I have to point out that computers do have the advantage of getting the wrong answer faster.
The GCM oracles must be master thespians as well.
Though strongly against the direction of Jerome Ravetz’s ‘Post-Normal science’ (beloved by many climate scientists), his observations are usually very perceptive. He reminds us that scientific models are metaphors. So whoever heard of a theory that had to fit a metaphor? With regard to climate models, Ravetz has this to say:
“…climate change models are a form of “seduction”…advocates of the models…recruit possible supporters, and then keep them on board when the inadequacy of the models becomes apparent. This is what is understood as “seduction”; but it should be observed that the process may well be directed even more to the modelers themselves, to maintain their own sense of worth in the face of disillusioning experience.
…but if they are not predictors, then what on earth are they? The models can be rescued only by being explained as having a metaphorical function, designed to teach us about ourselves and our perspectives under the guise of describing or predicting the future states of the planet…A general recognition of models as metaphors will not come easily. As metaphors, computer models are too subtle…for easy detection. And those who created them may well have been prevented…from being aware of their essential character.”
If the observations fit ALL the models, then the observations would all disagree, and the uncertaintly would be enormous….which describes the models predictions perfectly.
Models could be (and almost certainly are) giving the right answer for the wrong reasons. Science has lost its way.
Gary Hladik says:
September 3, 2011 at 2:54 pm
While computer models have their drawbacks, in fairness I have to point out that computers do have the advantage of getting the wrong answer faster.
_________________________________________________________________________
Computers ALWAYS get the RIGHT answer.
The problem is whether they are being asked to do the correct sums….
Adam says:
September 3, 2011 at 1:12 am
Here’s a discussion starter. I’ve been reading climate blogs for two years and actively seeking an answer go the question, “Why do people trust models.” I haven’t gotten an answer, and after two years of searching that’s a little disappointing to say the least.
———-
Well I would conclude then that you have been looking in the wrong place. Blogs, any blogs, but especially blogs whose agenda is the make AGW go away no matter what, will not tell you anything about climate models.
You need to go to the local university library and read the papers describing the models.
Jack says:
September 3, 2011 at 12:49 am
Stating the obvious but models depend on the observed or recorded data being input. The whole basis of warmist science is that because the act of observing, biases the data, then they can manipulate the data however they like to make the models right.
What they do not account for is the statistical testing.
They still use statistics but only to confirm their desired outcome.
———–
Please tell us that you have a deep insider knowledge of how climate science works.
Or is this really a concoction of stuff you made up after reading other peoples dubious Internet opinioons.
Before bloviating about an ill chosen choice of words I always take time to consider how much weight the person saying those words really placed on them, because it is the easiest thing in the world to misspeak oneself. Were those considered words with thought behind them that he intended to stand behind. Somehow I doubt it.
In particular note that this is the third thing in a list of three. Never put much weight on those. It looks to me like he got caught in a “three things” trap, by which I mean that the sentence structure and flow of prose he was using needed three things to complete itself in a satisfying way, so he put “agreement with models” in there as an ill considered third choice simply to complete the sentence.
I would classify this as a Lapsus Linguae – a slip of the tongue. I won’t hang a man for that because I trip over my tongue all the time.
Gary Mount says:
September 3, 2011 at 3:18 am
Imagine if Boeing designed and built airplanes just using computer models and never testing in a wind tunnel. Would the FAA certify such a plane? Yet something as complex as the climate system if certified as a go using models only.
———–
You raise a good point. So ask another question. Why is Boeing using computer models at all? If they were completely useless they would not be in use.
The climate models can be thought of in some ways as engineering rather than science. Each of the model components by themselves represents some component of the climate system. So for the atmosphere the equations arising from the science and engineering of aerodynamics is used.
It would be utterly clueless to suggest that we should not trust aerodynamics because it gives an answer we dont like.
All of the other components of the climate models are used because they have been studied separately from the climate models and found to be correct.
So a climate model is like a house made out of bricks. The house may have weaknesses because some of the bricks are not as strong as the others. But generally the house will stand and function like a house.
If you want to panic about models then you you need to consider these engineering models are used all over the place, you just have not heard about them. So the panic is selective.
LazyTeenager says:
September 3, 2011 at 4:14 pm
“You need to go to the local university library and read the papers describing the models.”
============
Ah yes, the transparency theory.
Makes one wonder why there are FOI laws.
Peter Plail says:
September 3, 2011 at 2:41 pm
Lazy teenager, people who have problems with math(s) are innumerate not enumerate. Very sloppy, must try harder.
——–
Thanks, I will.
Roy of UK says
So to rephrase your comment, and to ask a question, “In fact as a way of capturing understanding of climate, models are much better than using observational data.”. Is this what you really think?
————
Roy, observational data does not give you “understanding”. For example observing rain is not enough. You have to have a theory that rain comes from evaporated water and that the amount of rain is related to the humidity.
If you assemble a bunch of these theories you have a climate model. If the theories by themselves are correct, and the way they interact is correct, then this catalogue of things can be said to represent some degree of understanding.
So an understanding of climate is a catalogue of theories about:
Air
Clouds
Aerosols
Oceans
Heat transfer
Solar radiation
Water chemistry
Etc..
A verbal description of all this is completely inadequate. In the past this understanding would have been captured in a book or encyclopedia. Now its captured in a computer model.
The accuracy of understanding can now be tested by comparing the observations with the outcome of the computer model.
u.k.(us) says:
September 3, 2011 at 4:48 pm
LazyTeenager says:
September 3, 2011 at 4:14 pm
============
Ah yes, the transparency theory.
Makes one wonder why there are FOI laws.
——————
Makes me wonder why you would rather not go to a library and but instead write a letter to a university, put other people to a whole lot of trouble and then rummage through a whole lot of personal correspondence to gain some understanding of computer models.
Myrrh says
——–
? We have real data, such as Vostok and countless other studies, which show conclusively that CO2 lags behind temperature by c800 years – a real modeller disciplined in real science wouldn’t bother including it as a driver, let alone a ‘primary’ driver..
———–
Myrrh, the thing you are missing here is the concept of a feedback loop. Solar radiation uptake by the earth and CO2 in the oceans are likely part of a feedback loop.
From a modelling perspective it should be possible for the models to reproduce the behavior where an increase in solar energy retention by the earth causes an increase in CO2 800 years later..
Don’t know if there are any published papers on this. Maybe you could download some model code and run it if you are interested. Probably too big job for an amateur though.
Ian H concludes
I would classify this as a Lapsus Linguae – a slip of the tongue. I won’t hang a man for that because I trip over my tongue all the time.
———
I would second that
Bill Yarber says:
September 3, 2011 at 5:49 am
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?
————–
The climate modelers do for climate exactly what you do for airplanes. Climate modelling resembles engineering more than science.
Engineers should get over the professional arrogance thing. Its become something of a joke.
ScientistForTruth says: “Though [I am] strongly against the direction of Jerome Ravetz’s ‘Post-Normal science’ …his observations are usually very perceptive. He reminds us that scientific models are metaphors. …With regard to climate models, Ravetz has this to say:
“…climate change models are a form of “seduction”…but it should be observed that the process may well be directed even more to the modelers themselves…As metaphors, computer models are too subtle…for easy detection. And those who created them may well have been prevented…from being aware of their essential character.”
I agree about Ravetz; he often puts his finger precisely on the troublesome spot. Here, his words hark back to Feynman’s “The most important person not to fool is yourself,” as well as the classic error of mistaking the map for the territory. Beyond some point (which varies with what is being modeled), added complexity doesn’t improve the model as much as it obscures its nature. The subtleties of stochastic and empirical routines with ensemble runs, on top of ad hoc fudge factors, further prevent a realistic grasp of what the model is. As with the famed PhD, the modeler eventually “knows everything about…nothing.”
LazyTeenager says: “Myrrh, the thing you are missing here is the concept of a feedback loop….From a modelling perspective it should be possible for the models to reproduce the behavior where an increase in solar energy retention by the earth causes an increase in CO2 800 years later..”
So the earth’s energy retention goes up without benefit of CO2 greenhouse effect, THEN the temperature rises, and, FINALLY, 800 or so years later, the CO2 goes up. If so, this proves…what? The existence of a chronokinetic greenhouse effect? Most amusing. Did you intend it to be?
To LazyTeenager.
If you believe you are qualified, peer review these two presentations (with statistical models) for me.
http://www.kidswincom.net/climate.pdf and http://www.kidswincom.net/CO2OLR.pdf. You can find my contact information on http://www.kidswincom.net. Others are welcomed.
Fred
Retired environmental scientist