There is a new critique of IPCC climate projections doing the rounds of the blogosphere from two ‘scientific forecasters’, Kesten Green and Scott Armstrong, who claim that since the IPCC projections are not ‘scientific forecasts’ they must perforce be wrong and that a naive model of no change in future is likely to be more accurate that any IPCC conclusion. This ignores the fact that IPCC projections have already proved themselves better than such a naive model, but their critique is novel enough to be worth a mention.
The authors of this paper actually have a much larger agenda, and that is to improve the quality of forecasting used in public policy and business everywhere – by the use of ‘scientific forecasting principles’ (of which they have enumerated 140). Most of these principles seem commonsensicial (don’t overfit a statistical model, test models on out of sample data etc.) and are listed on one of their many websites. Basically, you just assign a subjective numerical score for reflecting how well you match a particular principle and at the end you get a ‘scientific’ number that says how well you are doing.
Armstrong helped set up a journal dedicated to this goal, as well as running yearly meetings for scientific forecasters. However, in a recent review of progress he notes: “the diffusion of useful forecasting methods has been disappointing”, and that “forecasting meets resistance from academics and practitioners”. This seems surprising – why wouldn’t people want better forecasts?
G+A’s recent foray into climate science might therefore be a good case study for why their principles have not won wide acceptance. In the spirit of their technique, we’ll use a scientific methodology – let’s call it ‘the principles of cross-disciplinary acceptance’ (TM pending). For each principle, we assign a numerical score between -2 and 2, and the average will be our ‘scientific’ conclusion…
Principle 1: When moving into a new field, don’t assume you know everything about it because you read a review and none of the primary literature.
Score: -2
G+A appear to have only read one chapter of the IPCC report (Chap 8), and an un-peer reviewed hatchet job on the Stern report. Not a very good start…
Principle 2: Talk to people who are doing what you are concerned about.
Score: -2
Of the roughly 20 climate modelling groups in the world, and hundreds of associated researchers, G+A appear to have talked to none of them. Strike 2.
Principle 3: Be humble. If something initially doesn’t make sense, it is more likely that you’ve mis-understood than the entire field is wrong.
Score: -2
For instance, G+A appear to think that climate models are not tested on ‘out of sample’ data (they gave that a ‘-2’). On the contrary, the models are used for many situations that they were not tuned for, paleo-climate changes (mid Holocene, last glacial maximum, 8.2 kyr event) being a good example. Similarly, model projections for the future have been matched with actual data – for instance, forecasting the effects of Pinatubo ahead of time, or Hansen’s early projections. The amount of ‘out of sample’ testing is actually huge, but the confusion stems from G+A not being aware of what the ‘sample’ data actually consists of (mainly present day climatology). Another example is that G+A appear to think that GCMs use the history of temperature changes to make their projections since they suggest leaving some of it out as a validation. But this is just not so, as we discussed more thoroughly in a recent thread.
Principle 4: Do not ally yourself with rejectionist rumps with clear political agendas if you want to be taken seriously by the rest of the field.
Score: -2
The principle climatologist that G+A appear to have talked to is Bob ‘global warming stopped in 1998’ Carter, who doesn’t appear to think that the current CO2 rise is even anthropogenic. Not terribly representative…
Principle 5: Submit your paper to a reputable journal whose editors and peer reviewers will help improve your text and point out some of these subtle misconceptions.
Score: -2
Energy and Environment. Need we say more?
Principle 6: You can ignore all the above principles if you are only interested in gaining publicity for a book.
Score: +2
Ah-ha!
In summary, G+A get a rather disappointing (but scientific!) score of -1.66. This probably means that the prospects for a greater acceptance of forecasting principles within the climate community are not good. Kevin Trenberth feels the same way. Which raises the question of whether they are really serious or simply looking for a little public controversy. It may well be that there is something worth learning from the academic discipline of scientific forecasting (though they don’t seem to have come across the concept of physically-based modelling), but this kind of amateur blundering does their cause nothing but harm.
In association with their critique, G+A have also launched a very poorly thought out ‘climate challenge‘ that is essentially a bet on year to year weather noise. No one is likely to take them up on that, and they don’t seem to be interested in the rather better thought through bets on offer from James Annan and Brian Schmidt. Thus again, the conclusion must be that they are not serious about their stated goals. That’s a shame.
Shorter Armstrong and Green: If our publications are not cited, climate sensitivity is zero.
‘Shorter’ concept by Daniel Davies and Elton Beard
What BPL said at #40. And said well.
Best,
D
Sorry, Gene Hawkridge # 6.
RE 23.
Gavin, the supporting data for the plots is half there. The plot selection allows you to pick a time period for the ModelE runs and specify a window for the moving average. So, for example, I select 1880-2003 with a 12 month window and the data table gives me the year ( in decimal months so 1895.085 for example) and the 12 Moving average of ANOMALY ( reference 1951-1980) recorded every month.
Thats nice, but the GISS observation data comes in a yearly average form ( same reference period) I’ll sort out how to align the two data sets, but it would be nice if you guys would make absolute C available. This would allow for alternative smoothing approaches, and easier comparision with CRU, for example, who use a 1961-90 period.. is that right?
Anyway, thanks for the pointer and consider my friendly suggestion about make absolute C (in addition to anomaly) available.
Since the data table contains data in a decimal form ( like 1880.917) I’m wondering how time gets intgrated in the model ( just curious, I know there are probably varying time steps for various components) Actually there is a substantive reason for asking. When you calculate a Tmean for a period of time. lets say a day.
Do you actually calculate a TMAX and TMIN? for each day?
When you figure a Tmean for every day do your specify a Time of Observation?
[Response: In the model, Tmean is a true Tmean – i.e. the average of every temperature taken at 30 min intervals ( which is the main physics timestep). You should be able to get just the annual mean from the 12 month running mean if you want – just pick the values from the mid-point of each year. Alternatively, don’t average at all (i.e. 1 month running mean), and create your own annual average. – gavin]
By the way, I recall seeing somewhere, on one of Dr. Anderson’s pages, his mention of a response he received — he’d submitted a comment on the draft IPCC report, recommending they adopt his approach. They explained to him that they were not doing weather forecasts, if I recall correctly. It’s probably in the archive of comments somewhere.
RE 54: Well, I could be wrong, but I do not think so, but there is no difference in what a weather forecasting model is doing and what a climate forecasting model is doing. If some one could cite where a GCM has not been updated, modified, etc. and the models of just a few years ago matched the ones now, I would like to see it. If anyone could show that the models done in the 80s got the global climate of today right, please point me to it. The models are huge and incorporate what the modeler believes is the correct assumptions that reflect the complex chaotic system that is climate.
I fail to see the difference, one is used to guess what the micro climate is going to be and the other is used to guess what the macro climate is going to be. No matter how you word it, forecasting is being done. Even though the IPCC said they were not doing forecasting, that is not what it says in the IPCC report.
These do not claim to experts on climate models or climate, just on forecasting. They have peer reviewed standing in the science of forecasting and they say that how it is being applied by the IPCC is wrong.
So why not quit bashing them as individuals and show why the forecasting guide lines do not apply to the IPCC in forecasting the future climate?
[Response: Weather forecasts take today’s situation and calculate how it will evolve over the next few days. They are initial value problems. Climate models do not assimilate current data but instead produce changes in climate as a function of changing boundary conditions, and thus are a boundary value problem – that is not the same as a forecast (which would require an estimate of the ‘weather’ component as well as the climate component). If you know anything about differential equations, you know those are fundamentally different kinds of problems. If you want models from the 80’s showing results for today, read about Hansen’s projections. Finally, try reading what I wrote, I never said their principles didn’t apply – I said they were mostly commonsensical – and my critique was based on their inadequate knowledge when applying their checklist, not the checklist itself. As I challenged a previous commenter, if you want more details, pick any 10 of the principles they marked IPCC down for and I’ll show you why the got it wrong. – gavin]
RE 53,
Thanks Gavin, On the Tmean issue. In some of the actual observation data I have looked at there appears to be a difference ( I would not call it systematic, since I only viewed a couple of sites )
Between the TAve and Tmean. from a physics perspective I suppose one would choose Tave. From the historical reality of observation stations we have Tmean.
So, in GISSTEMP, [the observation record] you report Tmean ( (tmax+tmin)/2))
and in the Model you report Tave — with a integration step of 30 min.
Was anybody curious in the least bit about how ModelE
Tmean would compare against Historical Tmean? Not a issue.
My sense is you are primarly concerned with a trend metric, so that differences between Tmean and Tave
are immaterial since you are concerned with trend?
Correct?
Thanks again
#42, No I haven’t, could you please provide a link?
My suggestion was just to find a better linear predictor than the ‘naive model’ (should be easy, as local temperatures are clearly not random walk… ). Maybe they would not qualify it as “currently
available fully disclosed climate model”, but that’s when you hire
the lawyers ;)
#17 Bob,
It may be possible to affect the weather/climate by producing/controlling “vertical” winds as stated in the article “Taming Tornadoes to Power Cities, pbublishd in the Toronto Star on July 21. (article by Tyler Hamilton, Energy Reporter).
http://www.thestar.com/Business/article/238291
L. M. Michaud, P.E., Inventor of the AVE says:
“If people accept it, the potential is unlimited. He says down the road, hundreds of vortex engines could be located in the ocean along the equator, where the warm tropical water would provide an endless source of energy.”
Why would anyone do such a thing?
“To cool the planet, Michaud says. Greenhouse gases in the atmosphere are what prevent the sun’s heat from radiating back into space, he explains. A series of controlled tornados along the equator would carry that heat to the outer edges of the atmosphere, where it could more easily escape.”
In other words, Michaud believes man-made tornados could function as exhaust systems for the planet, a massive air conditioner that could help manage global warming.
“There’s simply too much at stake to ignore this potential, he says.” more at http://www.vortexengine.ca
Comments?
_________
Re #43
Vernon,
it is clear that both you and G&A don’t really understand at all the difference between the typical forecasting methods used in economics and those of physics-based modeling as used for climate change predictions.
The type of forecasting that G&A seem to know how to do is a pure exercise in curve fitting using mathematical models that have very little connection with the underlying mechanisms that are responsible for the behavior of the system being modeled. In a pretty arrogant way, they think that because they are experts on that particular type of forecasting they know anything about how climate models are built. They probably think that climate models are just a bunch of equations that climate scientists took out of their hat in a whim and then fitted to past climate records to try to “forecast” future climates. Dead wrong!!!!
The models used to predict future climates are all physics-based, and are thus fundamentally different from forecasting models used in economics. So G&A have a lot of studying to do before they can say anything remotely intelligent about climate modeling. Most of their claims about climate modeling reveal such deep ignorance of the subject that they are pretty funny.
It’s as if a gardener, who digs small holes in a yard to plant
flowers, were to feel such an expert in Digging that he could knowledgeably criticize the way civil engineers dug the Panama Canal.
Is it not clear that one cannot forecast the future state of a system without knowing (at the very least) something about the system?
If the future state of an economic system is to be forecast and I know nothing about economics how am I to weigh the relative importance of the input variables? In fact how can I even reliably choose the input variables?
How do I know if a dependent variable reacts in a linear, nonlinear or chaotic fashion in response to a change in an independent variable?
If I build a linear statistical prediction model and the dependent variables respond in a highly non-linear way to a change in the predictor variables of what value is my statistical model? The situation is even more critical in physical prediction models.
Even more unsettling in the face of lack of knowledge of the system that is to be predicted is how do we know if we are merely dealing with correlations when we should be dealing with causation?
Credible forecasting requires an indepth knowledge of technique AND system dynamics.
Rafael Gomez-Sjoberg (#59) in his final paragraph touches on a point that plagues forecasting in the atmospheric sciences – SCALE.
I am assuming we have all heard of the “butterfly effect”. Can a butterfly flapping its wings in the Amazon Basin really affect the weather in the mid latitudes?
Of course the answer is no because the forces operating at that scale determine that the turbulent effects of the butterfly wings will not be of global consequence.
Just like the expert gardener in Rafael Gomez-Sjoberg’s post may know what is best for the small scale garden and the civil engineer may know what is best for the large scale dig, techniques that work at the small scale may not have any influence at the large scale while large scale excavation could very well obliterate any and all efforts in the small scale garden.
How does the small scale interact with the large scale (temporal and/or spatial)? Is the interaction linear or non-linear, chaotic, random or deterministic? Is there a continuous cascade of mass and energy from the large scale through the intermediate scales to the smallest? Do the smaller scales enhance the larger through feedbacks?
No matter how good one is at forecasting methodology if knowledge of the system that is being predicted is lacking forecast skill is likely to be null. fail Why? Because the questions posed here cannot be answered reliably.
I have never seen any of the posters here say non-climate scientists could not speak about climate. I have seen them indicate that people who completely disrespect and ignore decades to a century of work by the vast majority OF climate scientists are a priori fishy. I would say climate scientists, even the ones in the far end of the Bell Curve either way on acceptance of AGW and its dangers, have something in common – they all know the history of climate research, and have a day to day experience of reading the literature with a purpose. Of what’s been a pitfall, of what’s been fairly solid.
#re 29
Sarcastic? Yes. Irrelevant? Hardly!
Sure Gavin has chose a ‘cute’ way to format his response to G&A, but unwrap his comments from the “principles” and the “scores,” and you will see that each of the points made are serious (with the exception of the last which is merely cynical) and go to the heart of the errors G&A make. Of course their methodology is a soft target and so laughable that arguably it should not be dignified with a reply. But if a reply is made, surely sarcasm is the only appropriate tone to adopt.
“One can only conclude that you haven’t got the guts or the science behind you to respond in proper scientific terms to their paper.”
Paper? What paper?
Scientific terms?
Bwa ha ha ha ha ha ha ha!!!!
Oh, geez, this is opening up unexplored heights of the ludicrous. It is unfortunate that Gavin and the good folks at RC actually had to respond to such a load of dung, because their not doing so would have been exploited by the denialists as “haha! they can’t reply to that!”
But seriously, this thread should not go much on further, it just gives legitimacy to the “paper” that wasn’t one, and the trolls feeding off of it!
Sometimes, I wish that the reality based crowd would have the same means of engaging in large scale mind manipulation as the, well, what could be the appropriate word? Other people? I’m not sure; as a non native english speaker, I’m out of words to describe nonsense and its promoters.
However, wouldn’t it be funny if a campaign of the same magnitude could be waged against all the very real flaws and failures of economic theories and “marketing” (quotations marks because I’m not sure what the word means any more), or even say, “Political “science? (oh, that would be so precious!!).
Working in health care gives me the opportunity to see how much more solid the science behind climatology is than much of what is accepted practice in medicine, and yet all those throwing stupid, lawyer-like rethoric at climate science wouldn’t think twice about taking FDA aproved drugs. All I can say to the denialists is that, every day that goes by, their “camp” (that is really what they made themselves into) looks more and more pathetic to me, regardless how much they can sway public opinion.
It is now to the point where it really undermines the process of understanding climate. Any new idea or study has to “belong” to a political side, while its only focus should be better understanding of reality. What a shame.
Rafael Gomez-Sjoberg (#59)
This is really part of the beauty of climate models – and at an abstract level, one of the most fundamental principles of climate modeling itself. It argues from general principles, typically fundamental principles of physics – although not strictly – as when the responses of organisms are incorporated into the models. It doesn’t allow the arbitrary element of curve-fitting. Such an approach would have little grounds for regarding its conclusions as applying to anything outside of what the curve was based on – and given the complexity of what we are dealing with, it would quickly evolve into a Rube Goldberg device which no one could understand the basis for – but which we would adopt merely like superstitious rats which are randomly rewarded – dancing about in the belief that some increasingly complex set of motions determines whether or not they get the reward.
But since climate models are based upon our scientific understanding of the world, we have every reason to believe that the more detailed the analysis, the more factors we take into account, the better the models will do at forecasting the behavior of climate systems. Since it is based upon our scientific understanding of the world, it is not some sort of black box. If we see that the predictions are not matching up, we can investigate the phenomena more closely, whether it is in terms of fluid dynamics, spectral analysis, chemistry or what have you and see what we are leaving out.
This would seem to be the only rational approach that climatologists can take, and if this general approach did not work, this would seem to imply that natural science is a failed project, that its success up until this point has simply been some sort of illusion, and that the world simply doesn’t make sense.
*
Anyway, I am as sick as a dog, a very, very sick dog. Not the kind that is feeling reasonably well. Going back to bed.
Modeling in the physical sciences vs forecasting in economics are as different as night and day. For example, in the physical realm, neural nets are capable in many, not all, settings of “learning” complex relationships between casually-related physical variables and “forecasting” the behavior of some derived statistic based on evolving inputs. In economics, the causally-related economic variables are unobservable – only derived statistics can be measured. When techniques like nets are applied directly to these derived measures, the results are very unsatisfactory because in economics the relations between various derived measures are in fact quite unstable. Any solution will probably be worse than a random walk could do. That is why economists have to set the bar very low and take a very dim view of what can be achieved. In fact, as an example of the inherent instability of the relations, it is true that in economics consensus can often be a bad sign, because it means that a lot of people have made their bet in the same direction – the opposite may very well occur soon. Economic systems are, at the margin, predominately mediated through human behavior, but the human actors are also standing off to the side and watching what the system is doing, which then affects their behavior, and so on adfinitum.
What seems more worrying here is the lack of understanding that some other scientists and scientific disciplines seem to have of climate change. We all know that the media will report on any contrarian stance on climate change and hence is this why some scientists are trying the contrarian viewpoint ?
OK so climate change is a political science crossing economics, politics and energy physics and energy policy and locking horns with the wealthiest companies in the world but all the same from whgat is being reported here you would suggest that its the scientific silly season.
[[BTW, where is the best place to find the actual calculation of direct CO2 effect, in calories per m^2, and then temperature change, from the CO2 and other GH gases?]]
Neil,
In the composition range from about 1 ppm to 1400 ppm, radiative forcing by CO2 in watts per square meter can be found with this equation:
RF = 5.35 ln (C / C0)
where C is concentration, C0 reference concentration (usually taken as the preindustrial 280 parts per million by volume), and ln is the natural logarithm operator. For a doubling of CO2, this yields a change in radiative forcing of 3.7 watts per square meter, and given a climate sensitivity of 0.75 degrees K. per watt per square meter, this results in about 2.8 degrees K. temperature increase at Earth’s surface. This includes all the feedbacks.
Source for the equation:
Myhre, G., E.J. Highwood, K. Shine and F. Stordal, 1998. “New estimates of radiative forcing due to well mixed greenhouse gases.” Geophysical Research Letters 25(14), 2715-2718.
[[What BPL said at #40. And said well.]]
Hee hee! Thanks, Dano. :)
[[Working in health care gives me the opportunity to see how much more solid the science behind climatology is than much of what is accepted practice in medicine, and yet all those throwing stupid, lawyer-like rethoric at climate science wouldn’t think twice about taking FDA aproved drugs. ]]
I see your point. But to some extent, I find that people who accept one pseudoscience will often accept others as well. I have run into AGW deniers who think Venus is hot because it was molten a few thousand years ago and is still cooling down (i.e., Velikovsky freaks). Others deny AGW and insist that tobacco smoke doesn’t cause cancer. The antiscience attitude often carries over into several issues.
Re: Gavin, Rafael Gomez-Sjoberg (#59) and others
G & A indeed reference Bob Carter, writing:
“In practice, the GCMs failed to predict recent global average temperatures as accurately as simple curve-fitting approaches (Carter 2007, pp. 64 – 65). They also forecast greater warming at higher altitudes in the tropics when the opposite has been the case (p. 64)…”
Now, the Carter paper referenced claims that simple curve fit models, such as that in Loehle’s paper, is to be believed, writing:
“As an alternative to the deterministic GCM approach, there exist several other types of computer model of empirical nature. Such models use analysis of a portion of the climate record to establish the pattern of past temperature change and then project this pattern into the future…”
Bob Carter pointed to Loehle’s paper in his testimony before congress last year. Trouble is, Loehle’s analysis is deeply flawed, having violated a basic requirement of time series analysis called the Nyquist-Shannon sampling theorem.
http://en.wikipedia.org/wiki/Nyquist%E2%80%93Shannon_sampling_theorem
I pointed this out in a Letter to the Editor of EM, which they published. Here’s the reference:
Comments on “Climate change: detection and attribution of trends from
long-term geologic data” by C. Loehle [Ecological Modelling 171 (4)
(2004), 433–450]
Carter also used the wrong data when claiming that the troposphere is not warming. In both his 2007 paper and his congressional testimony, he presented a plot of Christy & Spencer’s MSU analysis for channel 2, the so-called “Mid-Mroposphere” product (called TMT). It’s long been clear that this product includes some of the well known cooling trend from the stratosphere, thus the TMT has an incorrect cooling trend. The C & S “Lower Troposphere” analysis introduced in 1992 (called TLT) was intended to address this problem. That Carter has relied on these outdated and misleading data further proves that he is not interested in the truth.
Re: #70
The reference to my letter should have included this:
Ecological Modelling 192 (2006) 314–316
E. S.
Eric Swanson (#70) wrote:
I used to think it would be so refreshing to run into a prominent creationist who was still honest. I finally gave up. At this point I am finding the same to be true of the leading AGW skeptics. As far as I can see, there are none left.
re: 40. And sadly, yet another “drive-by” poster (21) apparently has slithered back into their abode without acknowledging that they learned anything about the science, the scientific process or being able to admit that they could possibly be wrong. It seems no apparent effort was made or intended to learn. :-(
Timothy, get well soon!
Philippe, maybe you can get some of your medicine cohorts to remove that bug from your butt…[;-)
Barton says “…Others deny AGW and insist that tobacco smoke doesn’t cause cancer….”
Now cut that out!!
Barton should have written “Another denies ….” I think.
You can look this stuff up. Try Lindzen. http://tobaccodocuments.org/
No way, Rod, there is no peer-review study indcating any health benefit from doing so.
Plus, I don’t have time, I’m disseminating info to all the species that have shifted their ranges because they read erroneous information based on flawed temperature data from bad surface stations. Those butterflies really have no critical thinking skills. It’s going to be harder to convince the ice that it can start freezing earlier and thawing later again, but not nearly as hard as to convince the tropopause to come back to its normal level. We’re also working at elucidating who the tropopause got its communist propaganda from.
Cheers.
Re modeling vs forecasting: Maybe a concrete example of the difference would be useful. Take astronomy. If you happen to be an ancient Babylonian or Mayan, you can keep detailed records of astronomical occurences for hundreds of years, and apply forecasting techniques to predict everything from the seasons to eclipses to the apparent motion of the planets through the sky. Or if you happen to be Issac Newton, you can come up with a model of the physics.
Now you can use either the forecasting or the model to predict future events, and as long as you’re dealing with things you have a record of, you would probably get similar accuracy. But suppose something unexpected happens: say a comet appears, or you make a telescope and discover the moons of Jupiter. Forecasting tells you nothing about this, while if you have the model, you can plug in new facts and immediately get useful predictions.
Seems to me that’s why forecasting just isn’t equipped to deal with something like global warming. G&A remarked that one should avoid non-linearities in forecasting, but with GW the non-linearity is in the physics.
#72- Timothy, I’ve tried to avoid comparing global warming deniers to Creationists, but really it is the only proper comparison. However, apart from the cheerleaders, I suspect most normal peoples attitutde is like that of the majority of ID supporters- they accept it without much questioning, because it fits with their presuppositions.
Mind you, it gets so bad these days that I had to point an apparently otherwise intelligent and well educated person to talkorigins. They thought Darwinism didn’t make any predictions, and seemed to be basing their equivocation between ID and evolution on half remembered schoolboy science from 30 years ago. Fortunately they seemed interested in actually learning why they were wrong.
gutherie (#78) wrote:
Well, I think there is a real spectrum, but when it comes to prominent advocates, I believe that honesty becomes a real issue. They have to have at least some familiarity with the science – or think that it is completely irrelevant. In either case… I think the same is necessarily true of the creationists who get involved in online debate – there is probably a short period in which they could turn either way. But given the debate they have constant exposure to more and more than they must disregard.
Odd, too, as this is something which they are presumably doing in the name of morality. Nothing corrupts the foundation of an individual’s moral being like systematic dishonesty. Except perhaps an us vs. them view of the world, but I believe that is largely implicit in creationism, given our scientific knowledge. It involves a rejection of modernity and implies alienation from the modern world. And how completely unnecessary this is, but that is a topic for another time and another place.
Eric, can you post the text of your letter somewhere, or point to it?
Google’s cache has the original Loehle article readable
http://64.233.179.104/scholar?hl=en&lr=&safe=off&q=cache:aGhcZqennt4J:www.geogra.uah.es/~emilio/pdf/cambio%2520climatico%2520natural/loehle2004.pdf
but I didn’t find your comment letter (resp. 70 above) online
Odd, too, as this is something which they are presumably doing in the name of morality. Nothing corrupts the foundation of an individual’s moral being like systematic dishonesty.
Thus the proliferation of websites pointing out this dishonesty. This site included and at the forefront. Other sites have proliferated that look at the rhetorical tactics used.
Best,
D
Re: # 80 Hank,
I found a direct link thru Science Direct’s pay site:
http://linkinghub.elsevier.com/retrieve/pii/S0304380005002899
If you (please, not everybody) send me your e-mail address and I’ll send you a copy.
I’m at: e_swanson ( at ) skybest dot com
Of course, remove the spaces and replace dummy portions… :-)
Interdisciplinary teams are necessary for input into models on possible future social and economic choices, such as a ‘business as usual’ scenario where we use carbon at the current rate, or a future where people switch to alternative energy sources that burn less CO2. Also economists and social scientists should be part of the team that makes conclusions and recommendations to the decision makers.
However,economists,social scientists,and political scientists have no more credentials to critique the physics and climatology of the models than climate scientists have to critique the economics of social choices and human behavior, that might ignore, mitigate or stabilize climate change. We’re all free to express ourselves in fields outside our own, but that’s all that it is, an opinion, not a scientific conclusion.
I would suggest Prof Armstrong expands his (imo rather snide) seer-sucker principle to cover when marketing and economics bods decide to comment on the realm of climatology.
#79- testimony from several people who were creationists or ID friendly to begin with, was that they started turning against it all partly because or mainly bceause they realised that their leaders were feeding them lies.
So it is with this- many people will keep their heads in the sand, but we can win people over by piling on the data and arguments, such that the lies become clear.
Re #78: [Timothy, I’ve tried to avoid comparing global warming deniers to Creationists…]
Apropos of which, I just ran across this news story:
http://news.yahoo.com/s/nm/20070725/sc_nm/pope_environment_dc;_ylt=AlO.I3EZ3_iQRZyh8xjb0b5pl88F
Which, if the link doesn’t work, reports a recent statement by Pope Benedict, supporting both action against climate change, and evolution.
Perhaps the problem with a lot of the economic analysis of climate change is that economists are not required to learn much basic science – such as the First Law of Thermodynamics, for example.
It does seem that an economist can use the results of real scientific analysis to judge the problem, but for any honest economist the IPCC reports should be the primary source of information.
Furthermore, very few economists have discussed the economic difference between a renewable energy-based economy and a fossil fuel-based economy.
Economic predictions that aren’t based on good science have little value. Really, economic education needs some serious changes. Some people have tried to do this with “physical economic theory”.
Economists have a notoriously poor record when it comes to forecasting future trends, so why should anyone take an economist’s unscientific critique of climate science forecasting efforts seriously? How many ‘economic forecasts’ have turned out to have any value whatsoever?
What’s funny is, economists know that if you print a whole lot of paper money and put it into circulation, the prices on everything change.
They know the change from say the steam engine to the diesel locomotive completely changed the costs and prices of the rail industry.
They know what the cotton gin or the combine did to farm prices.
They know if you make a permanent change to a highway system, or an electrical transmission system, or a shipping port, the numbers change. They would never assume things would just go on the same when something they know matters changes.
Re 87:
So why aren’t we asking why, if G&A didn’t predict the tech crash of 2000, they think they can predict the average temperature of the world in 2050?
re – a bunch: Not being one to let any mine go unstepped on… This veiled guilt by association (with creationists) and declaring that one who disagrees with another’s solidly held belief, convincing without question to them, dishonest is the same gibberish as those who want to prosecute skeptics for crimes against humanity. Frankly not very becoming.
Hey! Another mine! There is considerable evidence for intelligent design of the Universe, or at least some omnipotent entity having some say and engineering of the process. I differentiate this from “creationism” as defined by fundamentalist, especially those who insist on a (silly) strict interpretation of the Bible, despite St. Augustine’s caution against doing just that. Plus I don’t accept how the Creationists have also co-opted the term “intelligent design” (or creative design), so I use the term in its pure meaning.
Timothy, you might try Francis Collins. There was an interesting article last November in, I think, Time of a discussion between Collins and Richard Dawkins. Or try Fred Hoyle. Or Einstein. Or a whole potful of, I trust, non-liars! Let’s don’t string them up quite yet….
Since I’m way off topic, Hoyle had an interesting and credible theory of the Universe that is orthogonal to the “Big Bang”.
#89: Clearly, forcasting the 2000 tech crash and far future weather are very different challenges; Economics are driven by intelligent agents enjoying information imbalance, while weather in the year 2050 is caused largely by chaotic events like the beating of butterfly wings in Brazil. We understand chaos theory much better than the stock market, the latter being mostly mob psychology punctuated by random acts of greed. So why shouldn’t we be able to predict far future weather and not so near future market movements? Butterflies are just stupid bugs, no challenge there.
Ha. That was fun. Let’s see if they quote me in the NYT.
Tim:
Go to Lubos Motl’s site and ask that same exact question. See if you don’t see a pattern emerging.
Economics is highly problematic because most of frameworks, neoclassical being predominant, do not readily allow for modelling of systems far from equilibrium. Physics also has its problems though. For example, the basic orders implied in relativity and in quantum theory are qualitatively in complete contradiction. Relativity requires strict continuity, strict causality and strict locality in the order of the movement of the particles and fields. In esssence quantum mechanics implies the opposite. What they have in common though is actually a quality of unbroken wholeness, as has been described by Bohm, for example.
It is perhaps unbroken wholeness, familiar in ecology, that needs to be addressed by economics, particularly with respect to ‘economics’ emergent through climate change. For example, one of the areas that is worthy of attention is the nature of a world economy under conditions of sea level rise of 5 metres, a BAU scenario for say 2100. By evaluating sea level impacts on multiplicities of nodes in diverse global supply chains it is possible to identify mechanisms of breakage, and, as importantly, permanancies of breakage (or relaxation times). Physical economics can say a great deal about that, although it has to be said that the formalisms used (Hamilton-Jacobi formalisms, catastrophe theory, far-from-equilibrium systems methods, organisational ecology, etc) are challenging on account of their application in such new areas. But in many respects, there is little difference with physics, partly because many of the tools being used to evaluate these scenarios are ported directly from physics, but also because there are no text books with the answers in the back.
As far as G&A are concerned, the tools thay use do have uses and it seems that one of the areas that might be addressed is the use of neural networks to detect patterns of behaviour from paleoclimatic records of sea level rises. Would it be possible to discern potential patterns of micro meltwater pulses (constituing a 5 m sea level rise to 2100) from such historical records? That would be useful in terms of risk profile evaluation for coastal infrastructure.
#86- The ID website Uncommon descent, day to day running in the hands of one Dave Scott, had a good old bash at global warming a few months ago. Needless to say they were wrong on every count. Credulity on one thing seems to me to be loosely correlated with credulity on lots of other things, but that sounds like a good study for someone to do, if they havn’t already done it.
Re #90 [There is considerable evidence for intelligent design of the Universe, or at least some omnipotent entity having some say and engineering of the process.]
Omnipotent entity? Complete klutz, I’d say, judging by the results!
Seriously, Rod, I think you’re making Timothy’s point for him.
[Response: That’s all fine, but no more ID/evolution discussions – go to PZ for that… – gavin]
Thanks for the head’s up, Gavin. I work professionally in the foresight business, and I *do* run in to climate skeptics quite often. When you go at them with evidence and some RealClimate-inspired counterarguments, they usually conclude that you know more than they do and back off. Individually, that is. They don’t usually change their slide deck for the next presentation, which makes me wonder where their head is at.
I find it rather shameful that the forecasting business is too much informed by econometrics – as dubious a “science” as I’ve ever heard – and not enough by rigorous sciences with solid predictions of the future. Astronomy and demography are quite good, really. I think that the shake-up that climate modelling is inspiring in the forecasting and foresight fields is a positive thing. We _need_ forecasting methods that work like the climate field does, modelling impacts for future events based on available evidence and science-based projection. We’ll be seeing a lot more initiatives like this in the 21th century, with varying degrees of success.
For example, take a look at G+A’s methodology tree (at http://www.forecastingprinciples.com/methodologytree.html ), the closest thing they have to “derive a model, test it, and use it predict outcomes” is “rule-based forecasting”, which appears to derive from “Univariate statistics” and “Intentions/expectations”. You might think that the “causal models” box comes closer to what we do in science, but you can see that it only applies to “linear” systems. Looking at the mouse-over box, “Causal models aided by the use of econometrics has been found to improve accuracy. The use of system dynamics has not.” Somebody better phone up the guys at Science and Nature and tell them to go find real jobs… you can’t forecast with science. You shouldn’t be able to publish in econometrics until you’ve passed a general science class. They wouldn’t write such rubbish otherwise.
#90- rod B- if Gavin will permit one last suggestion on the topic- go here:
http://www.antievolution.org/cgi-bin/ikonboard/ikonboard.cgi?s=46949b03fd9b71eb;act=SF;f=14
Where you can discuss your evidence for omniscient beings and designed universes. No censorship, down and dirty scientific discussion, a bit like we get on here.
Re 85: Guthrie says:
“So it is with this- many people will keep their heads in the sand, but we can win people over by piling on the data and arguments, such that the lies become clear.”
I wish it were so, but some people will never be convinced. About a dozen years ago, then Pres. Bill Clinton said that the “science is in”. I believed it then and I believe it now. The debate should have been over a decade or more ago. But there will always be diehards.
The late biologist Steven Jay Gould, speaking about about another topic (the belief in the supposed ‘fallacy’ of Darwinism), said,in an interview shown on TV, that there were millions of scientists in the world and you’d never get them all to agree, at least on that particular subject. There will continue to be a minority of contrarians. The same thing is taking place on anthropenegic global warming. Trying to get some of the diehards to agree to this, is like King Kanute trying to persuade the tide to reverse direction.
Thank you Real Climate for this valuable, much needed website!
Speaking of climate projections near or over the edge, James Hansen’s latest paper on “Climate change and trace gases” argues that the West Antarctic Ice Sheet is very sensitive to climate forcing and is unlikely to remain intact through the century. This implies, of course, that sea level rise this century will likely be very much faster and greater than predicted in IPCC4. I hope that Real Climate will devote some time to discussing the strengths and weakenesses of this important paper. Perhaps a conversation with James Hansen and Stefan Rahmstorf could be arranged?
Hansen’s paper appeared in Phil. Trans. R. Soc. A 365:1925, 2007, and is pubically available via the Royal Society website.
Rod B (#90) wrote:
Not wanting to get into any sort of disagreement with anyone on this topic, let me just say that I believe you misunderstood me. I like Augustine and it is the opposite view that I was criticizing.
Anyway, if you would like, write me:
“timothy chase @ g ma il. com”
(No spaces) – and I believe I might have something you would like. (Or perhaps not – but I still might like to get your reaction.)