Climate Science has selected two errors in Chapter 1 of the 2007 WG1 IPCC Report to highlight in this weblog.
These are
1. They write
“This is the so-called butterfly effect: a butterfly flapping its wings (or some other small phenomenon) in one place can, in principle, alter the subsequent weather pattern in a distant place. At the core of this effect is chaos theory, which deals with how small
changes in certain variables can cause apparent randomness in complex systems.” [page 105]
This is an incorrect statement of what the “butterfly effect” really means, as discussed on Climate Science
The perpetuation of the incorrect understanding (that in the real climate system, such a small perturbation can affect large scale weather systems) illustrates how poorly written and researched the IPCC Chapter actually is.
2. The second error (and it is a big one) is their unsubstantiated claim that
“Projecting changes in climate due to changes in greenhouse gases 50 years from now is a very different and much more easily solved problem than forecasting weather patterns just weeks from now. To put it another way, long-term variations brought about by changes in the composition of the atmosphere are much more predictable than individual weather events.” [from page 105]
This is a remarkable claim, and forms the basis of the entire IPCC concept. The hypotheses that need to be tested to support their claim (and which should have been presented in Chapter 1 of the IPCC Report) are discussed on the Climate Science weblogs:
Three Hypotheses On The Role of Human-Climate Forcings In The Climate System
Is Climate Prediction Sensitive To Initial Conditions?
Their claim that�
Projecting changes in climate due to changes in greenhouse gases 50 years from now is a very different and much more easily solved problem than forecasting weather patterns just weeks from now.”
is such an absurd, scientifically unsupported claim, that the media and any scientists who swallow this conclusion are either blind to the scientific understanding of the climate system, or have other motives to promote the IPCC viewpoint. The absurdity of the IPCC claim should be obvious to anyone with common sense.
I’m glad you’ve started a blog on this topic Roger. When I first read that chapter I was livid. They make the assertion that GCM models are only predicting average weather, but the analogy they give reveals sleight of hand. They assert that computations of ‘average weather’ are no different from predictions of average life spans. It is impossible to predict how long an individual will live, they say, but it is perfectly simple to give the age the average individual lives to. A little thought shows that this is a false analogy. It would be more accurate to say they are attempting to predict the age the average individual will live to a century in the future. I don’t mean to within the nearest twenty years (although even that is a wild guess) but to within the same range of accuracy they are predicting future temperature increases. Say 5k out of the baseline average of 290K or 1.7%. Thus it is equivalent to predicting the average lifespan of a human a century hence to within 1.2 years. If they really believe this then they are deluded.
Comment by Vince Causey — May 18, 2007 @ 1:16 pm
I read through the sections of the IPCC chapter which contain these statements, and I must say, Roger, the two you pulled out are just the tip of the iceberg. There are so many absurd and unsupported statements in this chapter that I lost count. How about the analogy of the predictability of climate with the predictability of a coin or dice toss! Just amazing…
One question that springs to my mind is the following. If, as they say, the atmospheric dynamics cannot be predicted beyond a few days, why then do most of the climate models have a “dynamical core” - i.e. they solve unsteady equations for the spatial evolution of momentum, energy, etc.? Why bother with spatial discretization in the first place? Why not just treat the entire atmosphere as a giant, well-mixed, closed system (thermodynamically) and solve it with a couple of ODEs? You could probably get the same results and not require any expensive supercomputers (probably a spreadheet would do!)…
Frank K.
Comment by Frank K. — May 18, 2007 @ 1:53 pm
Chapter 1 of the 4AR (which didn’t exist in the TAR) is a lengthy obsfucation disguised as science but it has not much to do with science. Not so surprising that such misleading presentations could be found: “butterfly effect” translated in activist terms by “Earth’s climate is very fragile and men are disturbing it” and “weather is not climate” translated to “weather prediction is bad SO climate prediction is good”.
Comment by Demesure — May 18, 2007 @ 3:14 pm
I was surprised that a recent response to a question of mine concerning uncertainties in climate change forecasts on the AMS Climate Policy site included a link to a similar discussion that “explained” why climate prediction is easier to accomplish than weather prediction. They never did seem to treat the “change” in climate change… somehow, by recognizing that one could with a high degree of confidence forecast that the tropics are climatologically warmer than mid latitudes, or that summer is warmer than winter in mid latitudes, this was supposed to demonstrate that climate change forecasts could be produced with a similar high degree of confidence. The link provided was:
http://www.realclimate.org/index.php/archives/2006/08/short-and-simple-arguments-for-why-climate-can-be-predicted/#more-318
Concerning the butterfly analogy, I picture it as similar to considering the chance of the air in a room suddenly going to one side of the room leaving a person to suffocate on the other side of the room due to the random chance arrangements of the molecules of air in the room. While not impossible, statistical techniques (Maxwell-Boltzmann perhaps?) could show that this would be an event with a probability extremely close to zero. While it is “possible” for a butterfly to produce “the tornado in Texas”, I would imagine (I admit that I don’t KNOW) that it could be likewise demonstrated that the probability would be VERY close to zero!
Comment by Richard Berler — May 18, 2007 @ 5:04 pm
Indeed, the link is to the same simple discussion that is referred to in Dr. Pielke’s blog! I can’t believe that the AMS blog directs folks to this as a worthwhile answer to questions concerning uncertainties in climate change predictions!
Comment by Richard Berler — May 18, 2007 @ 8:37 pm
Regarding the butterfly effect, Roger, I have to admit I had forgotten the extent of the scope ultimately attained by that kerfuffle. My working hypothesis from the whole thing was that the number of climate scientists it takes to get you to admit error exceeds by at least one the total number of climate scientists (in the world). It’s true that there were only five or six of them participating (plus a couple of physicists, but they hardly count), but that seems to me to be enough to make the point. Some of the ClimateAstrologers tried to come to your rescue, but they were a bit out of their depth. Then there was that poor colleague of yours who ended up disappearing behind the proverbial cloud o’ ink…
Anyway, I thought this comment from James Annan summed things up neatly:
“To be blunt, when a professor of atmospheric physics starts claiming that momentum in the atmosphere is internally dissipated into heat, it is time to duck out of the conversation.
“Roger, your wrong-headedness on this point is beyond belief. I don’t think it much of an exaggeration to say that such comments may expose you to public ridicule.”
Comment by Steve Bloom — May 18, 2007 @ 9:16 pm
Projecting emission scenarios 20-30 years is quite easy as was shown by Hansen in 1988, easier still if you look for total greenhouse forcings and try and bracket the changes. Mostly this is because in the limit of relatively small changes non-linear functions are well modelled by linear approximations. 40-60 years is harder but the point still holds. It is only when you get out into time scales (100 years or so) where the non-linearity of the emission scenario takes hold that it becomes hard. Most people learn this in Cal II or wherever they first meet Taylor series.
Comment by Eli Rabett — May 18, 2007 @ 9:50 pm
“Projecting changes in climate due to changes in greenhouse gases 50 years from now is a very different and much more easily solved problem than forecasting weather patterns just weeks from now. To put it another way, long-term variations brought about by changes in the composition of the atmosphere are much more predictable than individual weather events.�
Perhaps you should elaborate on why it is such an absurd claim. There are really two statements in here, so perhaps you should clarify which one you’re calling absurd.
1. Climate predictions are very different than weather forecasts. This is undeniably true. If you take a weather forecasting model and run it for 50 years, you don’t have a climate model. Similarly, if you run a climate model for 7 days, you have not generated a weekly weather forecast.
2. Climate predictions are much more easily solved than weather forecasts weeks ahead of time. Of course, this IS scientifically supported. We have many different climate models which give predictions for different GHG scenarios 50 years from now. They have error bars which reflect uncertainties in how certain things (like clouds) will respond. The uncertainty on multi week weather predictions is substantially greater. Hence, climate predictions for 50 years from now ARE easier than weather forecasts multiple weeks from now.
Comment by LogicallySpeaking — May 19, 2007 @ 12:30 am
Roger, I don’t think your description of the butterfly effect is correct either. The book by Vallis ‘Atmospheric and Oceanic Fluid Dynamics’ (Cambridge) discusses the topic of predictability in a much better way. Information in a chaotic turbulent flow moves also upscale, which is widely known.
Furthermore, I can predict the mean annual temperature for my country five years from now within an accuracy of p/m 1 degree, I don’t need a computer model for that. However, I can’t predict the weather over two weeks within an accuracy of p/m 1 degree. So the claim doesn’t sound so stupid to me.
Comment by tom — May 19, 2007 @ 5:29 am
Steve B. -
Apparently you did not read the entire thread on this issue which confirmed the accuracy of the Climate Science presentation. Please return to make comments on this subject when you have something of scientific substance to contribute.
Comment by Roger Pielke Sr. — May 19, 2007 @ 5:31 am
Logically Speaking and Tom - Here are the answers to your questions:
1. Regarding the issue of the “butterfly effect”, all of the information can dissipate into heat without upscaling if it is a small enough perturbation. This was clearly explained by Professor Richard Ekyholt who is an international recognized expert on chaos and nonlinear dynamics. [see http://www.climatesci.org/2005/10/12/more-on-the-butterfly-effect/.
2. Climate prediction includes all aspects of weather prediction plus all other components of the climate system. On weather prediction time scales, many aspects of the climate system can be prescribed as constant in that time period; e.g. sea surface temperatures. On longer time scales, these components of the climate system must be predicted.
Thus nonlinearities in medium and long term feedbacks become important. We have discussed this issue in the multi-authored paper
Rial, J., R.A. Pielke Sr., M. Beniston, M. Claussen, J. Canadell, P. Cox, H. Held, N. de Noblet-Ducoudre, R. Prinn, J. Reynolds, and J.D. Salas, 2004: Nonlinearities, feedbacks and critical thresholds within the Earth’s climate system. Climatic Change, 65, 11-38.
http://www.climatesci.org/publications/pdf/R-260.pdf
The observations show nonlinear behavior on all time scales, with the IPCC models demonstrating absolutely no skill at predicting any of them.
What this means for predicting climate decades from now in response to the human input of CO2, or other human climate forcing, is that we do not know what the effect will be. It could move the climate system towards or away from important climate regime shifts.
The prudent path is to reduce the human forcing of the climate system since we do not know its consequences. However, what the IPCC has failed to do is to adequately assess the relative role of all climate forcings. As we have discussed on Climate Science and have published on (e.g. see and see), the heterogeneous climate forcings due to aerosols and land use/land cover change appear to be more significant in terms of our future climate then the radiative effect of CO2.
Comment by Roger Pielke Sr. — May 19, 2007 @ 5:48 am
“The observations show nonlinear behavior on all time scales, with the IPCC models demonstrating absolutely no skill at predicting any of them.”
“What this means for predicting climate decades from now in response to the human input of CO2, or other human climate forcing, is that we do not know what the effect will be. It could move the climate system towards or away from important climate regime shifts.”
Thank you Roger - in two paragraphs you have perfectly summarized my opinion of the current state of climate modeling. For further eviendence, one can visit the NCAR web site and review the predictive skill of current climate models for temperature and precipitation patterns over North America one year in advance - they’re not very good.
I think society would benefit much more from climate model forcasts if we could just predict temperature patterns and the likelihood of droughts or rainy periods 12 - 24 months in advance. Based on these outlooks, farmers, for example, could direct their resources appropriately to optimize crop planting and harvesting. Certainly, improving short term climate forecasts would be a better use of funding for climate research than feeding the current global warming hysteria (which appears to be the mission statement of the IPCC).
Comment by Frank K. — May 19, 2007 @ 7:36 am
Dr. Pielke,
Your site has been the most informative and objective of all those I have visited on the subject of climate change. I thank you for your invaluable contribution.
I apologize for being off topic here, but your comment on “prudent path” leads me to another of my many concerns with the IPCC. They tell us how bad it will be if we do not follow their recommendations. But have they published their model results for future climate if we do follow all of their recommendations, or if we follow 80% of them, or 20% of them? More important, to discover what actions are prudent we need to understand the costs or penalties associated with those actions. If it is foreseeable that some action will increase deaths due to malnutrition or exposure it would not be prudent to take it.
I understand you may not want to take on the issue, but someone needs to do a serious cost/benefit analysis of the proposed remedies to global warming. Only then will we understand what measures are prudent.
Comment by Allan J — May 19, 2007 @ 8:01 am
Allan J. - Your comment is excellent and captures what Climate Science concludes is needed. The approach, to assess vulnerabilities of important societal and economic resources, was recommended in the multi-authored book
Kabat, P., Claussen, M., Dirmeyer, P.A., J.H.C. Gash, L. Bravo de Guenni, M. Meybeck, R.A. Pielke Sr., C.J. Vorosmarty, R.W.A. Hutjes, and S. Lutkemeier, Editors, 2004: Vegetation, water, humans and the climate: A new perspective on an interactive system. Springer, Berlin, Global Change - The IGBP Series, 566 pp. {see Chapter E Section 3, Section 5, and Section 7, for example]
An important, much-needed perspective on this subject was recently published
Pielke, Jr., R.A., Prins, G., Rayner, S. and Sarewitz, D., 2007. Lifting the taboo on adaptation. Nature, Vol. 445, pp. 597-598.
The IPCC should have started their assessment by first assessing what are the important vulnerabilities to essential social and environmental resources. Instead, they chose to cloak energy policy in terms of an inappropriately narrow view of the climate system.
Comment by Roger Pielke Sr. — May 19, 2007 @ 10:00 am
Leaving aside for the moment the ability to project forcings such as solar, greenhouse gases, etc., let us assume that all information in the climate system is randomized over a period of a week or two. In that case the calculation becomes pretty easy if you are looking for the average property 20-50 years from now over some relatively large geographical area and a time period much longer than the randomization time(3 months say), then the calculation becomes much easier as all you have to do is create an ensemble of trajectories over a surface which describes the forcings and average. Previous history is unimportant.
Comment by Eli Rabett — May 19, 2007 @ 12:39 pm
Speaking of computer models. While living in Boulder I visited NCAR on numerous occasions. In their mueseum they had a display that elegantly illustrated how realworld inaccurate computer models are. The display consisted of a T-arm that had hanging weights on three arms that rotated when the arm was rotated. The physics of the motion was completely understood using simple mechanics. Despite being a simple fully understood system the computer models of it always diverged from the actual motion as time progressed in the models.
I was suprised that a climate modeling supercomputer center would have such a display since it undermined their work. The problems with multi-decadal climate models are far more fundamental than getting the equations, parameters and data correct. Even if we knew with perfect accuracy all the components of a computer model they still would diverge from reality as time progresses in the model. Most scientists either don’t know this or are in a state of denial about the limits of computer modeling.
Comment by Reid — May 19, 2007 @ 1:08 pm
Now I am really confused. Eli is saying that climate models do have predictive skill, but others say not. The question is,can these models predict the climate? What sort of results are there? Steve B, I couldn’t follow your argument. Who’s Annan and what does his comment sum up? Sorry to appear obtuse, but there’s so much contradictory evidence, it’s hard to make much sense out of anything.
Comment by Vince Causey — May 19, 2007 @ 1:39 pm
Eli - You are making a fundamental assumption concerning the climate system that “all information in the climate system is randomized over a period of a week or two” which is not supported by the observations.
Observations show clear non-random behavior at short, medium and long time scale,(e.g. see the Rial et al paper). Weather prediction seeks to predict the non-random behavior at daily, multiday and weekly time scales. Climate prediction seeks to extend this to seasonal, annual and multi-decadal time scales. More nonlinear feedbacks become important as the time scale is lengthened.
Comment by Roger Pielke Sr. — May 19, 2007 @ 4:30 pm
After reviewing the ‘butterfly effect’ argument, it occurred to me that the model defenders are taking an artifact of the mathematics and insisting that it actually exists in reality.
The result of every iteration of the model run is, by definition, an approximation. This approximation is then used to start the next iteration of the model run, resulting in a larger approximation. Thus, even the smallest perturbation becomes larger over time.
The real world, however, does not function this way. When reality steps forward in time, the result is a new reality, not the approximation of a new reality. There is no carryover of an error induced by an approximation. In reality, the smallest perturbations can and do dissipate.
Because of the inability of our mathematics to truly model the atmosphere, all models tend towards ridicules solutions with time. This problem is not a function of our ignorance, but is inherent in the mathematics we use to model the system. No matter how much knowledge we have of the initial conditions and/or atmospheric processes, the mathematics will always lead to ever growing errors and ridicules solutions.
The modelers prevent this by assuming that certain feedbacks apply, resulting in constraints in the approximation error. The net result is that the models are a product of the initial assumptions. If the IPCC modelers assume that CO2 is the main driver of global climate change, the models must give results that indicate CO2 is the primary driver of global climate change. It is a useless, expensive, circular argument.
Worse than that, it is the argument used to demand an expensive and counter-productive reorganization of global energy consumption. It is an argument used to frighten the global population into harming themselves. It is an argument for behaviors that can not possible result in the desired climatic outcomes. It is an argument for a ‘solution’ that will undoubtedly be worse than the ‘problem’ it promises to solve!
Comment by Jim Clarke — May 19, 2007 @ 6:56 pm
Re #10: Roger, as you well know I was there at the time, and FYI I re-read all of that material to refresh my memory prior to commenting. I make plenty of science-based comments here, as do others with far greater qualifications than I have, but your views seem unaffected by any of them. I persist in hoping that this situation will change, but perhaps that hope is forlorn.
Re #17: Sorry for the obscurity. For context, I can only suggest that you read the two threads Roger linked in the post. James Annan is a climate scientist.
Comment by Steve Bloom — May 19, 2007 @ 7:52 pm
Re #19: Ah, I get it now — the heavy math backgrounds of the modelers trick them into an illusion. In a sense, they know too much!
Comment by Steve Bloom — May 19, 2007 @ 7:55 pm
Re #21: As Al Gore quoted, …it’s what they know that just ain’t so. They have the illusion that the equations describing atmospheric processes are actually more ‘correct’ than reality. Even though we can not find such things as a butterfly’s wings changing weather in the real world, such things do exist in the models, so the modelers reason that such things must occur in reality.
This irrational argument constantly appears in the AGW discussions each time the real world presents us with more evidence that CO2 is not the primary driver of global climate change. It is assumed that the models must be correct, so if reality doesn’t seem to fit, an unprovable mechanism is put forth as an explanation for the flaws IN REALITY!
All of this is so counter to the scientific method, it is difficult to imagine why so many continue to defend these practices, even when sarcasm is the only tool they have left.
Comment by Jim Clarke — May 19, 2007 @ 9:31 pm
Steve, you are sadly mistaken in #21. The “math background” of climate modelers does not seem to exceed Calculus 301, if I take comments of William, James, Gavin, and Eli as a benchmark. This kind of background is not heavy enough to comprehend things like structural topological stability of differentiable manifolds or understand invaint sets in dissipative dynamical systems, less deal with these concepts in practical modeling.
These people seem to believe that the climate is nothing but a calm equilibrium of all fluxes, and all those glaciations and rapid deglaciations are results of some evil external forces, eruptions, comets, or due to 0.1% changes in integral insolation. Their “math background” apparently disallows them to consider a possibility that the climate may evolve as a result of interactions of several quasi-stable objects as polar cups, permafrosts, ocean belts, all coupled through atmospheric jets and biomasses, when the whole system maintains only _dynamic_ equilibrium along its natural attractor. This “dynamic equilibrium” may be locally similar to their primitive fixed point attractor, that’s why they may be somewhat successful in modeling of short-lived effects as volcano eruptions. But their models lack all these long-term interactions (or “feedbacks”) by design, so it is of no surprise that they have stable averages at climatological time scale of 30 years. Even if some of elements that might cause long-term variations have accidentally slipped into models in a form of fundamental non-altered physics, they tend to dissmiss those runs on the grounds that they deviate too much, or in wrong direction, or due to some computational error, just like the climateprediction.net is doing.
Regarding the “Butterfly effect”, I believe that all given answers to the paradox are incorrect. The correct answer is that while the Flap of a Butterfly’s Wings in Brazil will not set off a Tornado in Texas by itself (all tornados will be set off regardless of the flap), the touchdown point or its path may be altered by few millimeters. The energy to do this will be still immensely higher than the energy of the flap. However, over many-many years, the path of all tornados may shift significantly, even if one could guarantee that there were no other perturbations to climate trajectory due to other flaps or external disasters.
In conclusion, I would strongly advise you and above mentioned individuals to listen more carefully to what Prof.Pielke is saying, and try to comprehend the fundamental meaning of it.
Regards,
- Alexi
Comment by Al Tekhasski — May 20, 2007 @ 1:05 am
RE # 23
Alexi, I readily admit I do not:
[comprehend things like structural topological stability of differentiable manifolds]
But, I am a parent of two children and I read every account of the alarming concern of Chinese and Indian government officials measuring the melt back of the Himalayan and Tibetan glaciers. I do not need Calculus 301 to know that warm melts ice.
Is the glacier-melting warm attributed to natural sources? Nothing in the sunspot activity records can account for this century-long measured glacial retreat.
Has earth orbit shifted closer to the sun? No. Is the earth’s core radiating more heat via increased volcanic activity? No.
Has the atmosphere collected a new input of 100 ppm CO2 in the past century? Yes.
We might not prove with 100 percent certainty the velocity of the bullet but we can instantaneously know the consequences of it piercing the victims heart.
Will we forever argue the need for complete certainty while the future of our children and their children become less certain?
Eventually, the pin becomes unstable when too many are dancing on it.
Comment by John L. McCormick — May 20, 2007 @ 6:30 am
Re #22, This is quite true. Consider, for instance, that modelers see their model run results as “data”.
http://www.mad.zmaw.de/IPCC_DDC/html/ddc_gcmdata.html
Comment by Steve Hemphill — May 20, 2007 @ 6:33 am
Steve Bloom:
When you stop to be so dismissive of physicists, it will be too late!
Comment by Paolo M. — May 20, 2007 @ 9:43 am
Re: 7
Eli,
You have presented an interesting and intuitive point of view that – if I understand it correctly – linear approximations tend to work for some period of time and tend to degrade in predicting the behavior of non-linear systems as time (or the extremity of the forcing) proceeds.
A specific point is that you say: “Projecting emission scenarios 20-30 years is quite easy as was shown by Hansen in 1988�. I assume that this shorthand for saying that projecting the temperature impact of various emissions scenarios is easy for 20 to 30 years. Is that a correct assumption?
There is currently, as I’m sure you’re aware, a very active discussion thread at RealClimate on the evaluation of Hansen’s 1988 forecast. What’s fascinating about this is that you don’t even need some kind of linear model for CO2 impact on temperature; you just have to expect a continuation of the prior trend. Using Hansen’s data, there is no statistically significant difference between the 1964 to 1988 temperature trend and the 1989 – 2006 temperature trend. If you build the distribution of prior trends for numerous periods before 1988 and then look at the results of the Hansen Scenario B model results for the period 1988 to 2006, you can not reject the null hypotheses that we have simply experienced a continuation of prior trends. There is no demonstration of incremental information provided by the model.
Hansen himself was pretty clear about this in his 2006 NAS paper evaluating this model prediction when he said that a 17 year post period was not long enough to permit precise evaluation of model results.
In sum, the 1988 Hansen results vs. actual as of 2006 are ‘consistent’ with a predictive model, but have not ‘demonstrated’ or ‘proven’ skill.
Comment by Jim Manzi — May 20, 2007 @ 2:10 pm
Mr. McCormick,
I am the father of 3 children and have been studying the science of global warming for nearly 20 years. Initially, I feared the threat of human-induced climate change, but for the last 17 years I have grown to fear the ideaological movement and disinformation behind the concept of human induced climate change much much more.
I can not convey all that I have learned in these short paragraphs, but I can ask you to consider a few facts and a basic observation. It is a fact that the warming effect of CO2 diminishes as more CO2 builds up in the atmosphere. While we are just over a third of the way to doubling the CO2 concentration, the warming of that ‘third’ is more than half the total warming of a doubling of CO2.
Now consider the history of the last 100 years. Which has been more devastating to humanity and the planet: the 0.6-0.8 degrees of warming, or governments that have run amock by adopting a noble cause and instilling a fear for that cause in the populace? Which has had more impact on your life and the lives of your parents and grandparents?
Nations have used the threat to noble causes to directly and indirectly kill well over 100 million people in the last 100 years (and still do), while climate change has likely been a net benefit to the biosphere in general and humans in particular during the same time span.
Intelligent nations have been led to commit terrible crimes against their fellow man with fear-mongering and the exaggeration of threats to things they hold dear. Global warming is the first time such manipulation has been attempted on a global scale.
Your children have little to fear from climate change, which is impossible to control and easy to adapt to, and much to fear from ideological crusades, which have a long history of producing the type of misery that is very hard for today’s average Westerner to even comprehend.
I truly wish the best for your children!
Comment by Jim Clarke — May 20, 2007 @ 2:16 pm
Chaos and Butterflies yet again:
The NWP and GCM communities cannot think that a Butterfly will have any influence whatsoever on any physical phenomena or processes of interest. Instead the phenomenology of The Butterfly Effect as exhibited by the numerical calculations of some systems of ordinary differential equations is invoked by hypothesis into NWP and GCM models/methods/codes. I think we need to limit discussions to the Lorenz-like systems of ODEs, as these seem to be the basis for invoking the phenomenology into the NWP and GCM communities. Otherwise we will get side-tracked into discussions of the “chaotic response of complex dynamical systems� in general.
The phenomenology, however, is a strictly numerical artifact observed in some simplified and specialized systems of, generally, simple systems of non-linear ODEs. None of these equation systems are known to describe any known fluid flows. As noted by Jim Clarke above, the Butterfly Effect has not been observed in the natural systems of interest. The effect cannot be, and will not ever be, observed in the natural systems of interest.
Importantly, the phenomenology cannot be determined to be present in the continuous equations and its presence is based solely on observations of numbers produced by calculations by numerical solution methods. That is, there are no mathematical ‘necessary and sufficient’ tests that can be applied to the small simple systems of ODEs to know a priori that chaotic response is an expected and correct outcome. While complexity, non-linearity, and sensitivity to initial conditions are frequently used interchangeably with chaotic response, none of these alone, or even all together provide necessary and sufficient conditions.
In view of the necessity of determination of the phenomenon of chaotic response by calculated numbers it is imperative that the numbers be actual solutions to the continuous equations. It should also be necessary that the continuous equations be complete and accurate descriptions of the physical phenomena and processes of interest. In the absence of meeting these conditions, it seems that the phenomenology cannot be assigned to the physical systems of interest.
The uncertainty of this situation is compounded by the fact that NWP and AOLGCM continuous equations are large systems of complex PDEs plus ODEs plus numerous algebraic equations for the parameterizations. That is, these are not small systems of simple ODEs. And additionally compounded by the fact that it is known that the numerical methods in both the NWP and AOLGCM fields have yet to produce numbers that are not functions of the discrete increments in time and space. Thus the calculated numbers are known to not be solutions of even the discrete approximations and the convergence to solutions of the continuous equations is not even yet addressed. Under these conditions, the observed chaotic response is at the very best only some kind of response for the specific calculation. The observed chaotic response cannot in any way be assigned to the continuous equations and most certainly cannot be assigned to the physical systems.
And while the communities seem very eager to adapt the notion of chaotic response of dynamical systems, they do not seem to accept all the consequences that come with the total concept. The known fact that long-range predictability might not be possible for the specific applications of interest is an example. Dissipative systems have multiple attractors, if the concept of an attractor(s) can even be shown to apply to systems having an infinite number of dimensions, and an associated basin. There is no way to ensure to which basin assigned initial conditions belong and so even statistical properties based on the calculated numbers are not predictable.
The Global Climate Model community seems to be counting on the over-riding effects of the forced boundary conditions to control the course of a calculation as a new state of radiative equilibrium is approached. In a sense, the radiative equilibrium state represents the stable fixed point to which dynamic systems return in the absence of chaotic response. The numbers calculated from ODEs that exhibit chaotic response do not show that a fixed point is attained. Only some regions of the calculated response are approached, and then under only certain conditions, but a stationary fixed point is never attained.
The end states of thermodynamic systems are functions of the path taken (processes encountered) to those states. As each (never-ending) path in systems that exhibit chaotic response is different for each set of initial conditions, the thermodynamic states all along the paths are different. The internal adjustments to the calculated states of the materials that make up the physical systems, as determined by the mathematical representations of the physical phenomena and processes, will all be different for different initial conditions and the contents of the mathematical models. It is no wonder then that all the models/codes are calculating different numbers for the states of the systems. If the calculations were allowed to continue to the point that the applied boundary conditions begin to assert controlling guidance as radiative equilibrium is approached, the internal adjustments are very likely to be inconsistent with the actual state of the physical systems.
And we haven’t yet even started to investigate and discuss the over-riding importance of numerical solution methods on the calculated numbers. These methods are the ultimate source of the displayed results. To put it in another light, the thermodynamic states of the system as now calculated by the NWP and AOLGCM models/codes are functions of the discrete representations of the continuous equations. Thermodynamic principles cannot be allowed to be functions of approximate solutions to approximate representations of physical systems. The hypothesis that the physical systems of interest in NWP and GCMs exhibit chaotic response has yet to be tested and has yet to be proven correct.
All corrections appreciated.
Comment by Dan Hughes — May 20, 2007 @ 2:28 pm
John L. McCormick,
consider that solar magnetism have increased 130% since the end of the little ice age and you have a perfectly natural culprit to blame for most of the warming. As Harrisson showed in 2006, cosmic rays (partly diverted by solar magnetism) influence cloud cover within hours from the change in cosmic rays. As Svensmark showed in 2007 there is a plausible mechanism. As Shaviv and others have shown, there is very strong correlation between ice-house and hot-house periods and cosmic rays and the correlation is there on all timescales.
Also consider the reports by Pielke and others showing a significant influence on climate from land-use changes, and take into account the large population growth and rapid urbanisation. Yet again you have a plausible explanation for much of the warming.
If you take too costly action on flimsy evidence you are not cautios. Quite the opposit.
Comment by Lars Berg — May 20, 2007 @ 3:24 pm
RE # 30,
Lars, I will not dispute increased, intensified, prolonged solar activity can warm the erath’s atmosphere and surface.
However, I refer you to the following links that weigh more heavily in the direction of AGW.
http://data.giss.nasa.gov/gistemp/graphs/Fig.A2_lrg.gif
and:
http://www.mps.mpg.de/images/projekte/sun-climate/climate.gif
originating from the research of Prof. Sami K. Solanki, solar physicist and director at the Max Planck Institute for Solar System Research.
Borrowing from the August 2nd, 2004 MPI Press release, Dr. Solanki was quoted as follows:
“The influence of the Sun on the Earth is seen increasingly as one cause of the observed global warming since 1900, along with the emission of the greenhouse gas, carbon dioxide, from the combustion of coal, gas, and oil. “Just how large this role is, must still be investigated, since, according to our latest knowledge on the variations of the solar magnetic field, the significant increase in the Earth’s temperature since 1980 is indeed to be ascribed to the greenhouse effect caused by carbon dioxide,”
And, while the solar contribution debate rages on, there is still that not so insignificant issue of ocean acidification to worry about.
Oh, these pesky details!!
Comment by John L. McCormick — May 20, 2007 @ 6:27 pm
Re #22: Jim C., you write “This irrational argument constantly appears in the AGW discussions each time the real world presents us with more evidence that CO2 is not the primary driver of global climate change.” Do you say that because you’re a 1984 fan (as in “more is less”) or is it just a matter of “La, la, la, I can’t hear you”?
Then in #28 you write “It is a fact that the warming effect of CO2 diminishes as more CO2 builds up in the atmosphere. While we are just over a third of the way to doubling the CO2 concentration, the warming of that ‘third’ is more than half the total warming of a doubling of CO2.”
Wrong, wrong, wrong, as has been carefully explained to you on multiple occasions, and yet you persist in repeating it. Who do you think you’re fooling (aside from yourself)?
Re #23: Alexi, IIRC there are a couple of analysis PhDs in that crowd. Roger’s math background seems a bit thinner by comparison. Yours?
Re #26: Yeah, Paolo, it seems that physicists can’t get no respect these days. I blame string theory.
Re #27: Jim M., one of the first things I learned about climate science is that scientists like to see long-term trends (commonly thirty years) before drawing too many conclusions. But that’s just climate science, and this is Climate Science! Here it is asserted that five and ten year trends are sufficient, and on that standard Hansen’s model qualified years ago. Hansen doesn’t think so, as you point out, but what does he know?
Just so that others have clarity, the issue with Hansen’s model isn’t whether it has detected an AGW signal (which it did, as Hansen famously announced in 1988) and adequately tracked climate behavior over the last nineteen years (which it has, and the significance of it having not gone off the rails over that time should not be minimized), but at what point it can start to be used to constrain climate sensitivity (the “holy grail” of climate modeling).
Comment by Steve Bloom — May 20, 2007 @ 8:32 pm
Re #30/1: John, IIRC Lars has been repeating those talking points for quite some time. I don’t think any amount of evidence that the solar stuff is discredited (to the extent that it ever had much credit) will change that.
But as long as we’re on the subject, as Ray Pierrehumbert has pointed out on several occasions over at RC, the most blatant case of the solar gas hitting the climate science impermeable membrane is the Pleistocene glaciations.
There also this amusing recent episode.
Comment by Steve Bloom — May 20, 2007 @ 9:00 pm
Lars…
Do you really mean an increase of 130%, or do you mean 130% of what it was?
Comment by Steve Hemphill — May 20, 2007 @ 9:29 pm
Re #31: Speaking of pesky details;
The anthropogenic greenhouse warming hypothesis states that the troposphere should be warming at a much faster rate than the earths surface. However, observations show that the earths surface is warming much faster than the troposphere. Hence the anthropogenic greenhouse hypothesis has been falsified.
The fact that no greenhouse signal has been detected bolsters Roger Pielke Sr. hypothesis that earth surface changes are the most important anthropogenic climate forcing.
Oh, those pesky details!!
Comment by Reid — May 21, 2007 @ 4:18 am
Eli,
You are making the assumption that the physics of the atmosphere is understood with 100% accuracy.
Such an assumption cannot be scientifically supported.
For example, a recent study found that as ice melted in the arctic, the albedo remained essentially unchanged. This was because the extra water created more clouds.
This was totally unexpected and ran counter to the assumptions built into every single one of the computer models.
Comment by MarkW — May 21, 2007 @ 6:26 am
McCormick,
Why would you want to worry about CO2 acidifying the ocean?
Just a few million years ago, the atmosphere held as much as 10 times as much CO2 as it does today, and ocean life did just fine.
Carbonic acid is an extremely weak acid, if the concentrations of it increase a teensy amount, so what?
Comment by MarkW — May 21, 2007 @ 6:35 am
Re #32:
Steve,
The irrational argument I was referring to is the prevailing notion that the models (theory) are more accurate than reality. This argument manifests itself in discussions of Antarctica, tropospheric warming, historical climate and CO2 changes, hemispheric trends, regional trends, UHI effect, aerosols and so on. In each case, the mechanisms used to keep reality in check with the models (theory) are unfalsifiable at the time. In other words, it is not science, but unsupportable speculation generated for the sole purpose of reconciling reality with the models (theory).
Since I am obviously talking about specific observations and the specific rationalizations used to try and explain those observations, I must be listening very intently! Your accusation that I have my head in the sand, besides being an ad hominem attack, is not supported by the evidence.
Your second point is slightly more on target, but still not helpful in bolstering your side of the argument. When I wrote “…the warming of that ‘third’ is more than half the total warming of a doubling of CO2.â€?, I should have used the word ‘forcing’ instead of warming. The difference, of course, is that the warming from the forcing could be delayed. (Had I used ‘forcing’, then my statement would be right, right, right!)
The reason why this doesn’t help your side is because recognizing a delay in warming from a forcing increases the suns role in 20th century climate change. The delay in atmospheric warming would be more pronounced with a forcing that doesn’t heat the atmosphere directly (like the sun) to one that does (like increasing CO2).
The AGW supporters use the delay argument to insist that increasing CO2 is still very much a threat, but ignore the delay argument when insisting that solar forcing is not a significant part of the warming of the last three decades. Since I readily accept that there will be a delay in warming from both forcings (although of different magnitudes), my viewpoint is logically consistent. AGW supporters, on the other hand, want to employ the physics when it supports their theory and ignore it when it doesn’t, revealing yet again the weakness of the CO2-centric climate change theory.
Since the sun directly heats the surface, which is largely ocean, ocean cycles would play a significant role in the manifestation of a solar effect on global atmospheric temperatures. Increasing solar energy at the surface would be largely masked (stored) during a cool phase of the PDO (like the mid-20th century) and largely released during the warm phase (lake the last 3 decades). This reduces the amount of warming that can possibly be atributed to increasing CO2 in recent decades.
In order to make the statement that humans are responsible for most of the warming in recent decades, the IPCC must ignore the the role of the sun, the oceans and land use changes on climate, plus all of the many valid challenges to the ‘accepted’ climatological data, and focus only on a slowly increasing trace gas in the atmosphere. Talk about your cherry-picking!
In scientific terms, the IPCC position is not logically defensible. In laymans terms, it is delusional!
Comment by Jim Clarke — May 21, 2007 @ 8:40 am
Re #31:
Mr. McCormick,
See the above argument (#36) as to why the graphs you linked to do not support AGW forcing over solar forcing in the last 3 decades and the real world evidence Dr. Solanki must ignore to make his statement.
Comment by Jim Clarke — May 21, 2007 @ 9:01 am
Hello John,
If you take a look at this:
http://www.climateaudit.org/?p=1579
and then at this:
http://www.mps.mpg.de/images/aktuelles/pressenotizen/pressenotizen_2004/pressenotiz_20041027_2.jpg
you might look at it inh a different way!
If a chinese general is unsure about if he should or not launch an atomic rocket and is disturbed by a butterfly, he might launch the rocket against his will. THIS could result in a hurricane in Texas
If a small rise in sunactivity can result in Dansgaard-Oeschger-events or in a Warmperiod of 10.000 years, the sun’s rise in activity is a butterfly! One can not say, that this effect doesn’t exist.
Best regards
Edouard
Comment by Edouard — May 21, 2007 @ 9:41 am
Re 34: I mean 130% increase. The Harrison report detected a 19% higher probability for an overcast day with “high cosmic rays” (above 36*10^4) compared to days with low cosmic rays. This is for short term fluctuations, the effect on longer timescale is of course larger as the influence from the heliosphere, supernovas, galactic arms et c comes in. Harrisons study can be found at: http://www.met.rdg.ac.uk/cag/publications/2006/harrison2006.pdf
Re 31: So your links imply that anthropogenic greenhouse gases and land use changes share the blame for a 0,3 - 0,4 deg celsius increase. If the first half of all known fossile resources gave us less than 0,3 degrees increase I find that little motivation for sacrifizing world wellfare. And anyhow, your links refer to *irradiance* only, not taking account of the high energy cosmic ray flow that affect low level clouds.
Comment by Lars Berg — May 21, 2007 @ 11:09 am
I just want to clarify one thing. What Svensmark claim, is that *high* energy cosmic rays, on the impact with earth atmosphere, creates particles (muons) with sufficient energy to reach the lower atmosphere (below 3 km) and there ionise particles that aggregate into cloud condensation nuclei. The effect of low level clouds is to cool the world on average and the effect should be reveresed over areas with dust free snow, most notably Antarctis.
Over at realclimate and other “pro-CO2″ sites they tend to pretend that any solar change is the same and that any cosmic ray is the same. Hence you need to see to that a comparison put forward against the cosmic ray link actually compare HIGH energy cosmic rays and LOW level clouds and their effect on the radiative balance of earth.
Comment by Lars Berg — May 21, 2007 @ 11:41 am
Dissipation of Fluid Motions into Thermal Energy
In all the previous discussions of chaos and dissipation in the posts/threads listed above in this post, there was no mention of the thermal effects of physical dissipation in the fluid motions of interest. To be clear I am referring to the conversion of fluid motions into thermal energy via the viscous shear-stress terms in momentum balance equations. These are momentum diffusion contributions to the momentum balance equations. The thermal energy due to viscous dissipation appears as a positive-definite contribution to the various forms of the thermal energy conservation equation. Viscous dissipation always acts to increase the thermal energy of the fluid. If a temperature representation is used as the thermal energy equation, it always acts to increase the temperature.
Viscous dissipation is a volumetric process occurring at all times so long as fluid motions are present. The process is constantly acting to increases the thermal energy content of the fluid and increase its temperature.
In contrast I am not referring to the explicit and implicit viscous-like terms that arise from, or added to, the discrete approximations to the continuous form of the momentum equations. Somewhat ironically, these terms are frequently labeled as ‘momentum dissipation’. The label momentum dissipation seems to be used in the GCM world more than in other computational fluid dynamics applications. I think it is a good assumption that the viscosity-like coefficients that are used for momentum dissipation are not used to calculated the viscous dissipation contributions to thermal energy equations.
It is of course true that these momentum dissipation additions to the momentum balance equations have an indirect effect of the viscous dissipation to the extent that they modify the velocity distributions and gradients in the flow.
Modeling and calculation of the viscous dissipation and consequent thermal energy addition in GCM models has a somewhat checkered history. This is due in part to the evolutionary nature of the models and changing application areas. More nearly complete and comprehensive accounting of the components of, and physical phenomena and processes occurring in, the climate system have generally developed over decades of time. Applications to calculations of the thermal history of the planet over hundreds of years has required that the energy-conservation aspects of the modeling be fundamentally sound and theoretically correct. However, a large contribution to addressing the fundamentally sound and theoretically correct model has been the approximations made at the continuous-equation level of the modeling. The momentum balance equations used in the models are simplified versions of the complete equations. More specifically, the thin-atmosphere approximation on a spherical surface, the representation of surface drag, the no-slip condition at land-atmosphere interfaces, the corresponding boundary condition at ocean-atmosphere interfaces, and the decomposition of the velocity into horizontal and vertical fields has also contributed to the problem. While calculations and analyses with the GCM models/codes have been carried out over four or five decades, it seems that only late in the 20th century and early in the 21st century have the problems with the modeling and calculations of the viscous dissipation been corrected in some of the models/codes. Two somewhat recent discussion have been given by Boville and Brethron and Becker.
Again this situation is most likely a reflection on the interests in carrying out calculations for 100s of years of time.
It is my understanding that the global-average volumetric viscous dissipation in the atmosphere is calculated to be equivalent to about 2W/m^2 of energy; and I have seen much higher values. I do not know if there are estimates available from measured data in the atmosphere. A very wide spread has appeared in the literature over the years. This conversion of fluid motions into thermal energy has occurred for as long as the present composition and motions in the atmosphere have been roughly equivalent to the present-day conditions.
The standard argument is that this is a small number relative to the other energy-addition contributions to an energy balance for the planet. However, the radiative-equilibrium argument means to me that, as equilibrium is approached few energy additions can be consider to be a small number and neglected. Almost all finite numbers will not satisfy attempts to make 0 = 0. As I understand the situation, the effect of doubling of CO2 in the atmosphere is equivalent to about 1.6 W/m^2 and that the effects of the consequent changes in the thermal-energy state for the planet will be easily measured and observed in time spans of only 100s of years. How can an equilibrium-based approach to descriptions of the thermal-energy state of the planet neglect
I think another important issue is related to the development of the continuous equations used in CGM models/codes. Taken as a whole these equations are known to be incomplete. The basic-equation models for the fluid motions and thermal state are not the complete equations that describe the motions and energy conservation. The all-encompassing parameterizations, many of which deal with mass and energy sources and sinks and interchanges across sub-system interfaces, are ad hoc/heuristic, best-expert-approximations (EWAGs) and thus cannot be assured of complete accounting of the mass and energy balances for the processes that are parameterized. In summary, the continuous equations very likely do not accurately account for the mass and energy conservation that actually occur in the physical system. I suspect it is easily possible for the lack of completeness and complete understanding to be responsible for several W/m^2 difference between the model equations and physical reality.
Is it not possible that the differences between the model equations and the actual physical phenomena and processes incur errors on the order of a few W/m^2. Again this might be a small number relative to the macroscopic energy balance for the planet, but as equilibrium is approached, and the imbalance is accumulated over 100s years of time in a calculation, significant differences are very likely possible. It is an important issue that the level of incompleteness and imbalances in the modeling at the continuous-equation level, relative to physical reality, must be significantly less than the physical imbalances that are driving the planet toward a new equilibrium state.
Finally we come to, as we always do, the fact that the numbers are the results of numerical solution methods. In order to ensure that strict accounting and conservation of the energy distributions within the system requires extremely close attention to how the numerical methods are developed and implemented. An example of how easily it is to overlook important details is given by the usual practice of numerically integrating different parts of a model system using different time steps. A related issue is calculations using parallel-computing capabilities by various approaches to domain de-compositions. Exchanges of mass and energy at interfaces between subsystems presents another opportunity to overlook mass and energy conservation requirements. Generally these must be evaluated at the same time-step level in order to ensure strict conservation.
It is important to note that while there are many ways to account for the mass and energy conservation of a given calculation, this process in no ways ensures that the calculations are in accord with and reflect the actual mass and energy balances and conservation in the physical phenomena and processes. However it is an important issue that the numerical imbalances must be significantly less than the physical imbalances that are driving the planet toward a new equilibrium state.
As a stable equilibrium state, the radiative equilibrium state for example, is approached, no imbalance can be counted as small and dismissed. The imbalance between physically reality and the continuous model equations is almost certain to be a genuine problem. The effects of the viscous dissipation, constantly acting to increase the thermal energy of the atmosphere is physical reality. I am uncertain of the actual physical value. The imbalances introduced by numerical solution methods is very likely a problem in some GCM models/codes. This problem has been discussed as recently as 2003. Small imbalances acting constantly over long periods of time cannot be ignored as equilibrium states are approached.
Here is a curious side issue that was discussed in this olde paper by H. A. Dwyer from 1973 located here. The results given in the paper indicate that the effects of his estimate of the power generation activities by humans can easily be seen in the calculations with his model. He used 15.0 x 10^18 BTU/yr (1.58 x 10^22 Joules/yr) as the ‘heat generation’ by mankind over a period of 100 years. Energy conversion activities by humans is another one of those processes that is constantly occurring and adding energy into the climate system
Worldwide energy consumption by the human race is over 446 Quadrillion BTUs at the present time. This is equivalent to 131,400 TWhr or 471,000 PJ (= 10^15 J) per year. If we take an average efficiency to be 33%, the total energy conversion is about 3 times the consumption, or 1,413,000 PJ per year = 1.413 x 10^21 J/year. This is within a factor of 10 of the value used by Dwyer. (While we consumed about one-third of the total conversion, all the energy converted will always reside in the climate system until it is lost to space. Can this be another source of internal energy conversion that cannot be ignored over long time scales as an equilibrium state is approached.
The thermal state of the planet, as measured by the temperature, is a strong function of the thermodynamic processes occurring within the climate system. The temperature distribution near the surface is determined by the transport and storage of the energy additions to the system.
Comment by Dan Hughes — May 21, 2007 @ 11:58 am
Re #38: Jim wrote “Increasing solar energy at the surface would be largely masked (stored) during a cool phase of the PDO (like the mid-20th century) and largely released during the warm phase (lake the last 3 decades).” Interesting. Please cite to a paper on that or describe how this would work. In particular, where would the heat be stored and how could the 1976 transition be missed if it involved such a large-scale ocean-atmosphere flux (noting that with ENSO, which sounds like it would have to be a snaller-scale event, the flux is quite obvious)?
And “The delay in atmospheric warming would be more pronounced with a forcing that doesn’t heat the atmosphere directly (like the sun) to one that does (like increasing CO2).” Really? I would think they’d have to behave pretty similarly since the lag is due to the time necessary to warm up the oceans. That said, the difference is that we have a committed warming from past CO2 emissions, whereas a similar effect from the sun would require that there be an increase that isn’t going away. Since none has been measured in the past fifty years, it seems that there would be a need to reconcile the recent acceleration in warming with a lack of change in irradiance. There’s also the small issue of the stratospheric cooling that is inconsistent with solar forcing.
And “the IPCC must ignore the the role of the sun, the oceans and land use changes on climate(.)” I seem to recall all of those being discussed at some length in the WG1 report.
Comment by Steve Bloom — May 21, 2007 @ 12:49 pm
Thank you for raising this issue, and for trying to bring some sense of reality to IPCC. The notion that — “Projecting changes in climate due to changes in greenhouse gases 50 years from now is a very different and much more easily solved problem than forecasting weather patterns just weeks from now.â€? — reflects an obsolete view of the universe that I think can be demonstrated to be in error. Given a few random numbers, we can always compute an average and a variance, and so on. Many well educated people believe that these moments will always exist, and will be always representative of subsequent samples of the random process. But it is easy to find common examples where neither average nor variance in any way predict the future. (We can start with the stock market.) It is less obvious that most weather processes also have fractal statistics, and do not always have convergent moments. What we often have is chaos. Most importantly, it is likely not true, and absolutely not proven, that we can predict the results of meteorological processes at any point in the distant future any more accurately than we can compute them for next week. To put it very simply, there is no such thing as a Gaussian distribution, least of all in meteorological processes. In the real world it is not appropriate to assume the existence of stationary distributions underlying a set of measurements. Each must be proven. Few have. For those who would like to see more on fractals, Google “mandelbrot fractalsâ€?.
Comment by Allan Ames — May 21, 2007 @ 3:34 pm
“Projecting emission scenarios 20-30 years is quite easy as was shown by Hansen in 1988, easier still if you look for total greenhouse forcings and try and bracket the changes. Mostly this is because in the limit of relatively small changes non-linear functions are well modelled by linear approximations. 40-60 years is harder but the point still holds. It is only when you get out into time scales (100 years or so) where the non-linearity of the emission scenario takes hold that it becomes hard. Most people learn this in Cal II or wherever they first meet Taylor series.”
I had to respond to such a statement. By reading this… you would think the greenhouse effect is the only climate factor on this plant. Hanson will be wrong on all 3 of his scenarios because of the PDO phase shift. This -PDO phase effects ENSO by causing more la ninas. This will cause global temperatures to at least slightly cool over the next 20-30 years. Lower solar activity could easily cause more cooling as that goes down.
Comment by Kevin Kiefer — May 21, 2007 @ 5:47 pm
I am a practising chemical engineer and a layman as far as climate science is concerned. I have followed the global warming “debate” closely for the climate processes are mirrored in the everyday processing in our chemical plants. I have never understood how anyone can model climate without a thorough grounding in fluid dynamics, heat transfer and vapour/ liquid equilibria but that may be just my ignorance. From my musings I would like to throw in the following:
1. Anyone familiar with modelling should know that a step in validating the model is a reality check. This is where plant data is fed into the model and predicted results compared to real data. Only then may the model be used for prediction outside current operation. I do not see any evidence of this in the climate models. As the models cannot go forward then why not start from today and go back 200 years and see what is predicted.
2. I would like the term “greenhouse” deleted from the lexicon of climate talk. It re-inforces a false mechanism of warming. I have even contemplated that CO2 and water vapour actually contribute to cooling the planet (strike me down with lightening) and that CO2 is a response to global warming not a cause and eventually starts to cool. My argument is that nitrogen and oxygen have extremely low absorptivities and emissivities ie radiant energy has little effect on temperature. The heating of the atmosphere comes from convective heat transfer from the oceans and surface of the earth ( who hasn’t felt the hot wind off the desert). At night the surface radiates to basically a heat sink at 0 K. Because of the low emissivity of the major components of the atmosphere they do not radiate and remain heated with some convective cooling only. CO2 and water vapour have much higher emissivities and lower absorptivities ie they emit more than absorb and these components emit in all directions not just back to the surface so in effect are the cooling components of the atmosphere. Now how is that for a paradigm shift?
3. There are other possible mechanisms for energy transfer from the sun besides radiant energy and also why do we focus on the sun. We are sitting on a giant glob of molten iron. It has to be cooling , doesn’t it? Is the earth a giant induction furnace swirling through the suns magnetic field. Surely the switching of magnetic poles every 11 years has to have some effect?
Shoot me down!
Comment by Gary Wilson — May 21, 2007 @ 9:56 pm
RE: #47 - I cannot shoot you down. What you have mentioned here may actually be a causal factor resulting in errors in not only climate models but even the shorter term weather models. There is currently a harsh debate between camps who try to dismiss the fluid dynamics approach and ones who are tuned into what you have mentioned. Look at the Reynolds numbers vs reality, look at the “parameterizations” used to “tune” the models so they don’t “blow up” and depict singularties and massive “dead zones”, among other ills. Of course, if one dares bring these issues up to the orthodoxy, particularly the orthodoxy at NCAR and NASA, be prepared to be smeared and brutalized, at least figuratively speaking.
Comment by Steve Sadlov — May 22, 2007 @ 11:22 am
Jim (#19): The butterfly effect is not an artifact of mathematics. Unfortunately, it is a hardcore reality. You are mixing numerical implementation of a model with inherent mathematical properties of it. Fortunately, topological properties of hydrodynamic models are such that approximations induced by numerical iterations usually fall back into the same invariant set, so one can continue iterations jumping every time to a slightly different system trajectory, but eventually it is possible to explore the whole set, find averages or higher momentums of the real distribution, etc.
“Inability of our mathematics to truly model atmosphere” is also a substantially distorted statement. Navier-Stockes Equations of compressible fluid are a very good mathematical model of atmosphere. The trouble is that mathematics does not have simple analytical solutions to them, especially when the boundary conditions are non-expressible in simple functions (lands shape and elevations), with non-contiguous boundaries that are flexible and oscillating (ocean surface), when coupled to transport of heat (convective and radiative), with sources and transport of moisture with phase transitions, etc. Mathematics of all of this is pretty well known and understood in each separate and simplified aspect, and even general mathematical properties of global aspects (strange attractors) of the system motion are understood. The bigger trouble is that practical details of a particular atmosphere on a particular planet with particular air properties and boundary would require practical calculations of everything, but, as I said above, all of them are non-analytical. Therefore, we need some other way to formulate boundary and initial conditions, which is in tabular form using computer memories as holders for tabulated conditions and resulting variables. Theoretically it should be sufficient to “truly model” the atmosphere, and no “ever growing errors and ridiculous solutions” should emerge (if computational method is adequately applied). Practically, it is impossible. Therefore, researchers tend to reduce complexity of the global model making various assumptions and gross simplifications. That’s where lots of unjustified and wishful nonsense comes in, with lack of adequate instrumental data for adequate validation of those assumptions. The assumptions in climatology are piled upon assumptions of assumptions, forming a fragile chain. Ironically, a similar problem exists even in pure mathematics; take a look at this fascinating article:
http://pauli.uni-muenster.de/~munsteg/arnold.html
Of immediate importance is the following paragraph:
“It is obvious that in any real-life activity it is impossible to wholly rely on such deductions. The reason is at least that the parameters of the studied phenomena are never known absolutely exactly and a small change in parameters (for example, the initial conditions of a process) can totally change the result. Say, for this reason a reliable long-term weather forecast is impossible and will remain impossible, no matter how much we develop computers and devices which record initial conditions. ”
Cheers,
- Alexi
Comment by Al Tekhasski — May 22, 2007 @ 11:14 pm
Alexi (#49),
I think it depends on which definition of the butterfly effect you are talking about. My point is that the real world and the mathematical world do not treat the effect in the same way, resulting in the inability of the models to truly mimic the atmosphere. Roger’s definition exists in the real world. I do not believe that the RealClimate definition does.
I agree with you on the rest of what your wrote, but know that AGW supporters argue climate change is not an initial-values problem. I don’t buy that argument and recall that Roger has effectively argued otherwise in a BAMS paper many years ago.
Thank you for the link!
Comment by Jim Clarke — May 23, 2007 @ 7:46 am
Jim - Thank you for the feedback. The BAMS paper that you refer to is
Pielke, R.A., 1998: Climate prediction as an initial value problem. Bull. Amer. Meteor. Soc., 79, 2743-2746.
Comment by Roger Pielke Sr. — May 23, 2007 @ 8:19 am
Responding to 18, the point being that if the system has memory on all scales why are you claiming that chaotic behavior makes it impossible to predict climate?
As to carbonic acid being a week acid, it is strong enough that the pH of sea water has shifted about 0.1 units, and that is significant. At 2x CO2 you have to start worrying about the viability of a many types of sea life, and btw, CO2 was many times higher hundreds of millions to a billion years ago, when there was not much living stuff around. You can find some links to paleoclimate stuff here
http://rabett.blogspot.com/2006/12/where-has-all-co2-gone.html
Comment by Eli Rabett — May 23, 2007 @ 9:55 pm
Jim (#50), Let me try to reconcile both views. The short answer is: Annan-Connolley-Schmidt (A-C-S) are implicitly referring to “normal coordinates” of weather attractor, Lorenz variables as an example. At the scale of Earth, the normal coordinates would be associated with amplitudes of some global spatio-temporal structures as jet streams, with tails spreaded maybe across the whole globe and up into stratosphere. When they say “small perturbation”, they essentially are talking about a small perturbation of the amplitude of the whole jet stream. In contrast, a classic Batterfly affects the state of atmosphere only at a small local point in regular coordinate representation. While, mathematically speaking, the butterfly changes the state of atmosphere, projection of local butterfly flap on the global structure of the size of globe-around jet stream is infinitesimal. In other words, to get comparable effect on essential atmospheric attractor’s variable , there must be billions of butterfies strategically located along the whole jet stream (and maybe across the whole NH) all flapping in certain phase and direction. So, Rodger and A-C-S are talking about incomparable things. Actually, Annan almost got it right when he mentioned thousand of butterflies in the other thread.
Let me know if you need further elaborations. BTW, I completely agree with the concept of BAMS-98 paper.
Regards,
- Alexi
Comment by Al Tekhasski — May 23, 2007 @ 11:12 pm