Dr. Richard Lindzen writes to me with news of this significant new paper saying “It has taken almost 2 years to get this out. “. Part of that problem appears to be hostile reviewers in earlier submissions to JGR, something we’ve seen recently with other skeptical papers, such as O’Donnell’s rebuttal to Steig et al (Antarctica is warming) where Steig himself inappropriately served as a reviewer, and a hostile one at that.
Hostile reviewers aside, the paper will now be published in an upcoming issue of the Asia-Pacific Journal of Atmospheric Sciences and I am honored to be able to be able to present it here. The authors state that:
“We have corrected the approach of Lindzen and Choi (2009), based on all the criticisms made of the earlier work (Chung et al., 2010; Murphy, 2010; Trenberth et al., 2010).”
…
The present paper responds to the criticism, and corrects the earlier approach where appropriate. The earlier results are not significantly altered, and we show why these results differ from what others like Trenberth et al. (2010), and Dessler (2010) obtain.
So, while that may satisfy some critics, given the hostility shown to the idea that there is a low sensitivity to forcings, I’m sure a whole new crop of critics will spring up for this paper. The response to this paper in AGW proponent circles, like the feedback posited for Earth’s climate system, will surely be negative. Let the games begin.
Some highlights:
However, warming from a doubling of CO2 would only be about 1°C (based on simple calculations where the radiation altitude and the Planck temperature depend on wavelength in accordance with the attenuation coefficients of wellmixed CO2 molecules; a doubling of any concentration in ppmv produces the same warming because of the logarithmic dependence of CO2’s absorption on the amount of CO2) (IPCC, 2007).
…
This modest warming is much less than current climate models suggest for a doubling of CO2. Models predict warming of from 1.5°C to 5°C and even more for a doubling of CO2
…
As a result, the climate sensitivity for a doubling of CO2 is estimated to be 0.7 K (with the confidence interval 0.5K – 1.3 K at 99% levels). This observational result shows that model sensitivities indicated by the IPCC AR4 are likely greater than than the possibilities estimated from the observations.
…
Our analysis of the data only demands relative instrumental stability over short periods, and is largely independent of long term drift.
Willis Eschenbach will no doubt find some interesting things in this paper, as it speaks of some of the same regulation mechanisms in the tropics as Willis has opined on here at WUWT. Here’s the Abstract and Conclusion, a link to the full paper follows:
==============================================================
On the Observational Determination of Climate Sensitivity and Its Implications
Richard S. Lindzen1 and Yong-Sang Choi2
1Program in Atmospheres, Oceans, and Climate, Massachusetts Institute of Technology, Cambridge, U. S. A.
2Department of Environmental Science and Engineering, Ewha Womans University, Seoul, Korea
Asia-Pacific J. Atmos. Sci., 47(4), 377-390, 2011 DOI:10.1007/s13143-011-0023-x
Abstract:
We estimate climate sensitivity from observations, using the deseasonalized fluctuations in sea surface temperatures (SSTs) and the concurrent fluctuations in the top-of-atmosphere (TOA) outgoing radiation from the ERBE (1985-1999) and CERES (2000-2008) satellite instruments. Distinct periods of warming and cooling in the SSTs were used to evaluate feedbacks. An earlier study (Lindzen and Choi, 2009) was subject to significant criticisms. The present paper is an expansion of the earlier paper where the various criticisms are taken into account. The present analysis accounts for the 72 day precession period for the ERBE satellite in a more appropriate manner than in the earlier paper. We develop a method to distinguish noise in the outgoing radiation as well as radiation changes that are forcing SST changes from those radiation changes that constitute feedbacks to changes in SST. We demonstrate that our new method does moderately well in distinguishing positive from negative feedbacks and in quantifying negative feedbacks. In contrast, we show that simple regression methods used by several existing papers generally exaggerate positive feedbacks and even show positive feedbacks when actual feedbacks are negative. We argue that feedbacks are largely concentrated in the tropics, and the tropical feedbacks can be adjusted to account for their impact on the globe as a whole. Indeed, we show that including all CERES data (not just from the tropics) leads to results similar to what are obtained for the tropics alone – though with more noise. We again find that the outgoing radiation resulting from SST fluctuations exceeds the zerofeedback response thus implying negative feedback. In contrast to
this, the calculated TOA outgoing radiation fluxes from 11 atmospheric models forced by the observed SST are less than the zerofeedback response, consistent with the positive feedbacks that characterize these models. The results imply that the models are
exaggerating climate sensitivity.
Conclusion:
We have corrected the approach of Lindzen and Choi (2009), based on all the criticisms made of the earlier work (Chung et al., 2010; Murphy, 2010; Trenberth et al., 2010). First of all, to improve the statistical significance of the results, we supplemented ERBE data with CERES data, filtered out data noise with 3-month smoothing, objectively chose the intervals based on the smoothed data, and provided confidence intervals for all sensitivity estimates. These constraints helped us to more accurately obtain climate feedback factors than with the original use of monthly data. Next, our new formulas for climate feedback
and sensitivity reflect sharing of tropical feedback with the globe, so that the tropical region is now properly identified as an open system. Last, the feedback factors inferred from the atmospheric models are more consistent with IPCC-defined climate sensitivity
than those from the coupled models. This is because, in the presence of cloud-induced radiative changes altering SST, the climate feedback estimates by the present approach tends to be inaccurate. With all corrections, the conclusion still appears to be
that all current models seem to exaggerate climate sensitivity (some greatly). Moreover, we have shown why studies using simple regressions of ΔFlux on ΔSST serve poorly to determine feedbacks.
To respond to the criticism of our emphasis on the tropical domain (Murphy, 2010; Trenberth et al., 2010), we analyzed the complete record of CERES for the globe (Dessler, 2010) (Note that ERBE data is not available for the high latitudes since the field-of-view is between 60oS and 60oN). As seen in the previous section, the use of the global CERES record leads to a result that is basically similar to that from the tropical data in this
study. The global CERES record, however, contains more noise than the tropical record.
This result lends support to the argument that the water vapor feedback is primarily restricted to the tropics, and there are reasons to suppose that this is also the case for cloud feedbacks. Although, in principle, climate feedbacks may arise from any
latitude, there are substantive reasons for supposing that they are, indeed, concentrated mostly in the tropics. The most prominent model feedback is that due to water vapor, where it is commonly noted that models behave roughly as though relative humidity
were fixed. Pierrehumbert (2009) examined outgoing radiation as a function of surface temperature theoretically for atmospheres with constant relative humidity. His results are shown in Fig. 13.
Specific humidity is low in the extratropics, while it is high in the tropics. We see that for extratropical conditions, outgoing radiation closely approximates the Planck black body radiation (leading to small feedback). However, for tropical conditions, increases in outgoing radiation are suppressed, implying substantial positive feedback. There are also reasons to suppose that cloud feedbacks are largely confined to the tropics. In the
extratropics, clouds are mostly stratiform clouds that are associated with ascending air while descending regions are cloudfree. Ascent and descent are largely determined by the large scale wave motions that dominate the meteorology of the extratropics, and for these waves, we expect approximately 50% cloud cover regardless of temperature (though details may depend on temperature). On the other hand, in the tropics, upper level clouds, at least, are mostly determined by detrainment from cumulonimbus towers, and cloud coverage is observed to depend significantly on temperature (Rondanelli and Lindzen, 2008).
As noted by LCH01, with feedbacks restricted to the tropics, their contribution to global sensitivity results from sharing the feedback fluxes with the extratropics. This led to inclusion of the sharing factor c in Eq. (6). The choice of a larger factor c leads to
a smaller contribution of tropical feedback to global sensitivity, but the effect on the climate sensitivity estimated from the observation is minor. For example, with c = 3, climate sensitivity from the observation and the models is 0.8 K and a higher value
(between 1.3 K and 6.4 K), respectively. With c = 1.5, global equilibrium sensitivity from the observation and the models is 0.6 K and any value higher than 1.6 K, respectively. Note that, as in LCH01, we are not discounting the possibility of feedbacks in the extratropics, but rather we are focusing on the tropical contribution to global feedbacks. Note that, when the dynamical heat transports toward the extratropics are taken into account, the overestimation of tropical feedback by GCMs may lead to even greater overestimation of climate sensitivity (Bates, 2011).
This emphasizes the importance of the tropical domain itself. Our analysis of the data only demands relative instrumental stability over short periods, and is largely independent of long term drift. Concerning the different sampling from the ERBE and CERES instruments, Murphy et al. (2009) repeated the Forster and Gregory (2006) analysis for the CERES and found very different values than those from the ERBE. However, in this
study, the addition of CERES data to the ERBE data does little to change the results for ΔFlux/ΔSST – except that its value is raised a little (as is also true when only CERES data is used.). This may be because these previous simple regression approaches include
the distortion of feedback processes by equilibration. In distinguishing a precise feedback from the data, the simple regression method is dependent on the data period, while our method is not. The simple regression result in Fig. 7 is worse if the model
integration time is longer (probably due to the greater impact of increasing radiative forcing).
Our study also suggests that, in current coupled atmosphereocean models, the atmosphere and ocean are too weakly coupled since thermal coupling is inversely proportional to sensitivity (Lindzen and Giannitsis, 1998). It has been noted by Newman et al. (2009) that coupling is crucial to the simulation of phenomena like El Niño. Thus, corrections of the sensitivity of current climate models might well improve the behavior of coupled
models, and should be encouraged. It should be noted that there have been independent tests that also suggest sensitivities less than predicted by current models. These tests are based on the response to sequences of volcanic eruptions (Lindzen and Giannitsis, 1998), on the vertical structure of observed versus modeled temperature increase (Douglass, 2007; Lindzen, 2007), on ocean heating (Schwartz, 2007; Schwartz, 2008), and on
satellite observations (Spencer and Braswell, 2010). Most claims of greater sensitivity are based on the models that we have just shown can be highly misleading on this matter. There have also been attempts to infer sensitivity from paleoclimate data (Hansen
et al., 1993), but these are not really tests since the forcing is essentially unknown given major uncertainties in clouds, dust loading and other factors. Finally, we have shown that the attempts to obtain feedbacks from simple regressions of satellite measured outgoing radiation on SST are inappropriate.
One final point needs to be made. Low sensitivity of global mean temperature anomaly to global scale forcing does not imply that major climate change cannot occur. The earth has, of course, experienced major cool periods such as those associated with ice ages and warm periods such as the Eocene (Crowley and North, 1991). As noted, however, in Lindzen (1993), these episodes were primarily associated with changes in the equatorto-
pole temperature difference and spatially heterogeneous forcing. Changes in global mean temperature were simply the residue of such changes and not the cause.
==============================================================
Dr. Lindzen has the full paper on his personal website here:
http://www-eaps.mit.edu/faculty/lindzen/236-Lindzen-Choi-2011.pdf
Discover more from Watts Up With That?
Subscribe to get the latest posts sent to your email.
didn’t Matt have a simple equation ( fits on the back of an envelope ) he was going to show us ?
Matt says: August 17, 2011 at 7:33 am
Please actually read the IPCC report. Their formula for the change in forcing from additional CO2 absolutely accounts for the logarithmic impact of increasing concentrations :
(http://www.grida.no/publications/other/ipcc_tar/?src=/climate/ipcc_tar/wg1/222.htm).
I don’t even think that Lindzen disputes this formula (5.35 log C/C0). His argument is with the climatic response to the forcing from doubled CO2, not with the magnitude of that forcing. If you are going to spout rumors that you don’t even fact check, you may want to reconsider who you are calling the idiots.
The “IPCC formula” delta T = 5.35*ln(ending CO2/starting CO2) [based on flawed calculations by Arrhenius] predicts climate sensitivity of 3.7C per doubling of CO2. Lindzen is in effect saying, if the climate sensitivity is 0.7C per doubling, the “IPCC formula” should instead be delta T = ln(ending CO2/starting CO2) [since ln(2) ~ 0.7]. The 5.35 is the IPCC fudge factor for climate alarm.
Since the observations Lindzen relies on don’t cover the polar regions, where diminished ice-cover can play an out of proportion positive feedback role, as albedo swings from the high value of white snow and ice, to the low values of open water, his results may be biased to the low end as much as he suggests the GCM models are biased too high.
A few centuries are a blink of time.
If the confidence interval for mean sensitivity is 0.5ºC to 1.3ºC, rather than 1.5ºC to 5.0ºC increase in average global surface temperature for doubling of CO2, AT BEST, we only have ‘a little more time’ to try to avoid serious consequences of AGW, for the sake of our descendents!
We’ve been dumping excess CO2 into the ‘atmospheric commons’ for free, by burning fossil fuels to increase OUR standard of living. Equity demands that we, NOT OUR DESCENDANTS, pay for most of the resulting costs, more or less in proportion to OUR individual gains. That isn’t changed by Lindzen’s small – even if valid – ‘correction’ to the analysis.
Willis, I’m sorry but maybe I wasnt clear. when you say ‘tell us nothing” you need to be more specific. I dont think we disagree and I think you may have missed my point and held’s point.
here try this its much more comprehensive and rigorous than your approach, and of course paul gives you the appropriate hat tip
http://rankexploits.com/musings/2011/equilibrium-climate-sensitivity-and-mathturbation-part-1/
you’ll note that in part two paul confirms what I’ve said about trying to deduce ECR from 100 years of data. TCR– ok, ECR? no cookie.
Also, check out the TCRs for climate models ( when they actually show them) I think you will find that the TCRs are rather close to what Lindzen finds observationally. in short, whether you are looking at models or data inside the 100 year period you are diagnosing the TCR. the transient part of the response. you slam the gas pedal and you look at the first few seconds of data. Inertia is not your friend, but you will see a transient response. When you reach terminal velocity , then you have a data point for the ECR. With the earth, 100 years aint enough. not with a model not with an observational dataset. Do the models give you an answer? sure. Is it worth much? na, read what paulK wrote.
Willis Eschenbach says:
August 17, 2011 at 11:35 am
Matt says:
August 17, 2011 at 7:33 am
… Also, it should be pointed out that (so far) the bulk of observation-based climate sensitivity measurements have yielded higher sensitivities.
Thanks, Matt, for some good points. For this one, however … citation? Here’s one for a start … obviously they relate to sensitivity at varying timescales.
Regards,
w.
——————-
The paper you linked to is entitled “CO2-induced global warming: a skeptic’s view of potential climate change”. Doesn’t bode well for its objectivity, does it? Imagine I linked to a paper entitled “… an alarmist’s view of potential climate change”. I can almost hear the outrage from here: begging the question, what happened to the scientific method, aren’t you supposed to get the results first and then reach your conclusions, etc., etc.
Which brings me back to criticisms of my remarks about skepticism and consensus. What’s good for the goose should be good for the gander. You can’t go deriding the mainstream consensus along the lines of “science doesn’t work by consensus” and then praising the allegedly emerging alternative consensus. I say “allegedly” because if you look at these papers, the only thing they all agree on is that they disagree with the mainstream view. And you really should be skeptical of “skeptical” papers, too. AGW may be a flawed hypothesis, but that doesn’t mean every word that contradicts it can be taken as gospel.
@Gary Young Swift
“But we don’t know the equilibrium time. In the car analogy, this would be like not knowing the horsepower and slope of the road. What if your snapshot was taken before the crest of a hill? How good would your physics 101 calculation be if you didn’t know that?”
My calculation would be perfect. Why? Because the calculation uses all known variables. If we -know- there will be a hill, and we know -when- it’ll be, then that’s included and there’s no issue. A snapshot does not, in any way, shape, nor form, preclude calculating an end state. This is common in all kinetic theory.
The problem is when you don’t know all the variables. When you can’t know if there is a hill, or even what a hill is, or what a hill will do to the force vectors. Then you have a problem and while you can calculate all day long on what you do know, you won’t know if you match reality until the actual observations come to pass. And that’s how science advances.
But from pure math, there’s no problem at all. You and Mosher are using a logical fallacy: that we can’t do the calculation at all because we might have unknowns. But we can do the calculation at any time based on what variables we do know, and if we’re off (if the calculation does not match the observed reality), that tells us something important–again, that’s how science advances.
Do you feel we know enough about the climate system to calculate the ECR from the TCR? If you think we don’t know enough about climate to do such a straight forward calculation, how can you begin to believe we can ever calculate the ECR?
well since nobody answered my question here
http://wattsupwiththat.com/2011/08/16/new-paper-from-lindzen-and-choi-implies-that-the-models-are-exaggerating-climate-sensitivity/#comment-721752
I must reject the paper
The paper effectively says: the effect of the CO2 is much smaller than what we thought it would be.
That just provides an easy way out for all those scientists with eggs on their face who promoted the idea that an increase of 0.01% of a natural gas could make any difference to the climate. And it still does not say that more of it is better.
http://www.letterdash.com/HenryP/more-carbon-dioxide-is-ok-ok
timetochoose.
I’m not in a position to criticize or endorse hansens particular work.
‘BTW, Mosher, paleo will only give correct sensitivity if one knows the correct forcing that caused a temperature change. If you don’t know the forcing, the sensitivity you get is wrong.”
elementary. yes. of course.
The point is this. If ( see that word) you have a system that has both fast feedbacks and slow feedbacks, then you cannot estimate the total system response to a forcing unless you have an observational time window that is long enough to capture the full effect. It goes without saying that you have to be able to estimate the following
1. the forcing
2. the response.
It also goes without saying that IF you want to measure the response, the total system response. the response when temperature ‘stabilizes’ that you have to pick a long enough period. With the earth system, thats a big uncertainty. How long is long enough. well, how long would it take for the arctic to melt out and change albedo? pretty darn long.
You slam the pedal to the floor. your wheels spin. I measure your distance traveled in that time and concluding that slamming the pedal to the floor has no response. Well, thats both right and terribly wrong.
Immunity and blindness to irony is not an intellectually or socially attractive trait.
David A says:
August 17, 2011 at 3:42 am
what are ” all the observations that were previously thought to have been explained by the previous paradigm of high sensitivity’ Which observations are you thinking of?
————
There are primarily two sets of such observations: paleo records showing the correlation of CO2 and temperature (yes, we know all about the lag) from whih a sensitivity can be deduced, and present day observed temperatures vs. projections based on a sensitivity. e.g. the much derided (around here) Hansen prediction of 1988:
Scenario B is the one to look at. Hansen used a sensitivity of around 4C. It would have performed even better had he used the now widely accepted 3C per doubling sensitivity.
Please, no graphs of only the last 5 or 10 years, that just ain’t scientific.
slight correction:
The “IPCC formula” delta Forcing = 5.35*ln(ending CO2/starting CO2) [based on flawed calculations by Arrhenius] predicts climate sensitivity of 3.1C per doubling of CO2. Forcing of 1 W/m2 supposedly causes 0.85C increase in temperature [TSI of 1367/4=342 W/m2, average Earth temp = 290K, 290/342 = 0.85K]. Lindzen is in effect saying, if the climate sensitivity is 0.7C per doubling, the “IPCC formula” should instead be delta F = 0.82*ln(ending CO2/starting CO2) [since ln(2) ~ 0.7]. The 5.35 is the IPCC fudge factor for climate alarm.
John B,
Lucia posted what is, I think, a much more accurate graph:
http://rankexploits.com/musings/wp-content/uploads/2008/06/hansencomparedrecent.jpg
Hansen is a failed alarmist. He tried three different predictions and got every one of them wrong. That takes a certain amount of negative talent.
Smokey says:
August 17, 2011 at 1:14 pm
He tried three different predictions and got every one of them wrong. That takes a certain amount of negative talent.
—————
No he didn’t, and you know it. He used three different scenarios for CO2 emissions and volcanic activity. B was the closest to what actually happened, so A and C are irrelevant.
Or were you trying to be funny?
observa says:
August 17, 2011 at 7:30 am
============
Brilliant. I liked, in particular:
“A stunning example of Blairs Law perhaps, whereby ‘the world’s multiple idiocies will come together in one giant useless force’. Well if that’s a bit harsh, then certainly the sublime irony of a bunch of professional Maoists telling a gaggle of amateur Westen leftists- ‘In your dreams monitoring us and telling us what to do’. “
Hansen got all his predictions wrong. John B is using the discredited surface station chart, which is another subject that’s been covered here in several articles. They can be found in an archive search. Short version: satellite measurements are much more accurate, and that’s what Lucia’s chart used. Here’s another chart I ran across comparing Hansen’s alarmism with reality:
http://theresilientearth.com/files/images/hansen_forecast_1988-2.jpg
If the ECR is over hundreds of years or even several decades, it’s as policy-irrelevant as it gets.
That which is correct and that which is incorrect is not decided by a vote.
The word “consensus” in the context of scientific endeavour should be banned.
An Einstein quote:- “No amount of experimentation can ever prove me right; a single experiment can prove me wrong.”
Lindzen and Choi are to be warmly congratulated for their continued application of the scientific methodology in the presentation and correction of their findings. Their paper is now in the public domain and it will stand or fall only on its scientific merits.
And this is how science should be.
John B says:
“B was the closest to what actually happened, so A and C are irrelevant.”
That is known as the Texas Sharpshooter fallacy: shoot holes in a barn door, then draw a bullseye around one and declare yourself an expert marksman. The holes outside the bullseye are irrelevant.☺
Since Hansen got all three predictions wrong, his opinion isn’t worth much, if anything.
Here’s an interesting view on climate sensitivity:
http://theresilientearth.com/?q=content/sensitive-kind
Len Ornstein says:
August 17, 2011 at 12:34 pm
AT BEST, we only have ‘a little more time’ to try to avoid serious consequences of AGW, for the sake of our descendents!
Go add up all the ‘economically extractable’ coal,oil and natural gas on the planet. Then try to figure out how you could drive CO2 concentrations to 1,000 ppm even if you wanted to using only economically extractable coal, oil and natural gas.
At some point putting a solar panel on my roof won’t be anymore expensive then putting shingles on my roof and burning coal will cost $$$$ money.
John B says:
August 17, 2011 at 12:39 pm
Which brings me back to criticisms of my remarks about skepticism and consensus. What’s good for the goose should be good for the gander. You can’t go deriding the mainstream consensus along the lines of “science doesn’t work by consensus” and then praising the allegedly emerging alternative consensus
Yes you can, since it is Climate Science itself that has set some of the rules for its own Unscientific Game involving “consensus”, as I explained above – and it has lost so far, about 10,000 to 75.
You also demonstrate the same problem with your thinking to the effect that, within the practice of real science, “skepticism” is a bad word. Another “loss”!
George E. Smith says:
August 17, 2011 at 9:55 am
Responses are in line:
“Well Theo, I don’t know how YOU rationalize ANY difference between a THEORY, and a MODEL.”
The differences are very well articulated. You can buy some rather challenging books on the difference.
“To me, a THEORY is simply a description of the properties that the MODEL is endowed with; by those who created the model in the first place.”
One definition of a model is that it is an interpretation of a formalism that makes all the sentences in the formalism true. So, for example, you can have a formalism in mathematics and independently of that formalism you can specify a set of objects, maybe in set theory or the real numbers, which makes all the sentences of the formalism true. You can formalize a scientific theory and do the same thing for it. If you are talking about this concept of model then I can pretty much agree with your remarks that I quoted immediately above.
“Both are equally fictitious; as are all the mathematical tools that have been created to manipulate the model, in that nothing in any of that actually exists in the real universe.”
They are not entirely fictitious. Searching for an interpretation that makes a formalism true can lead you to discover that the formalism contains inconsistencies. A formalism that contains inconsistencies is not fictitious but radically false; that is, it contains an inconsistency and has no model that will render it true.
When you are working with the fictitious, there is no falsehood. Run into inconsistencies? Just change the story. You are making it up after all. Remind you of anyone we know?
But physical theories that have been used and are used are not merely formalims; rather, they are interpreted; that is, they are about the world. No sentence of a formalism or a fiction is about the world.
For example, the scientists at CERN who are searching for the Higgs Boson hold theoretical statements that they understand as being about the world and the scientists believe that they know some observable consequences of the statements that they believe. They might discover that their predictions are true. In that case, they will discover much more, flesh out their ideas about the Higgs Boson, and learn that their theory predicts things they had not imagined. See how important the real world focus is.
By contrast, ask yourself what it would be like for the scientists to specify a model that makes their theory true. Does the fact that they can specify such a model mean that they have discovered the Higgs Boson? No.
“We can “observe” by any of a whole array of means, what we believe the real universe is doing; and has done in the past; and we can artificially create our models and their descriptive theories, so that they can be shown to behave in some way as close to what we perceive the real universe behaves; but those theories and models are not substitutes for the observations of the real universe.”
There is a strain in Pragmatism, most prominently William James and John Dewey, that held this view of scientific theory. However, the first casualty is truth. If the only purpose of my theory is to facilitate my observations, then it is neither true nor false but a mere formalism that is convenient for…how long? Well, nobody can know. Until the observations get difficult again. On this account of theory, Ptolemy’s system of epicycles is no less valuable than Kepler’s conceptually accurate description of the solar system or Newton’s mathematization of it. And you cannot compare Ptolemy and Kepler on the matter of truth because the Pragmatists ruled out truth. (By the way, James’s teacher, Charles Sanders Peirce, disowned him and renamed his philosophy Pragmaticism.”) We do agree that planetary orbits are ellipses (Kepler) and not perfect circles sitting on perfect circles (Ptolemy), right George?
“Of course, we can use our theories to predict (sometimes quite precisely) how the model will behave in the future; or what the outcome would be, if we performed an experiment with our model, that has never been performed. We like it when some analagous experiment that we perform in the real world, results in observations of an apparent behavior of the real universe, that appears to us to be similar to that predicted of the model.”
We cannot predict how the model will behave in the future or experiment with the model because the model has been fully specified. It is set in stone. For example, the fact that our formalism turns out to be true in the real numbers means nothing to the real numbers. They were fully specified many decades ago. The model serves purely as an analytic tool.
“The real world itself is far too complex for us to predict the future behavior; or result of some as yet never performed experiment.”
Have the faith of a mustard seed. The scientists at CERN will figure out all this Higgs Boson stuff, though it might turn out to be the Higgs Boson***. Read about their work if you think the real world is too complex for accurate prediction.
John B says:
August 17, 2011 at 10:23 am
“To such people, any criticism of the paper will be seen as merely proof that “The Team” are up to no good. I trust you are not one of those people, but you cannot deny they exist.”
Fine. In the future when you make such claims, you will explicitly exclude me and and my friends, right?
“…any criticism of the paper will be seen as merely proof that “The Team” are up to no good.”
The Team will always be up to no good until they embrace transparency and the scientific method, both of which they purposely ignore.
steven mosher-The main reason for a different “Transient Response” versus equilibrium sensitivity is not slow feedbacks, the main problem is the thermal inertia of the ocean. If one wants to get into slow feedbacks, that’s another difficulty. However the main feedback processes are clouds and water vapor, and these tend to have very short time scales. A carbon cycle feedback is probably mostly slow, and I would argue pretty weak. The Ice Albedo feedback may be slow in it’s greatest magnitude (ie large ice sheets) but also highly non linear (the feedback is much stronger when there are large ice sheets in the midlatitudes, as during the ice ages, as that combines high reflectance with high insolation compared to the high latitudes.) Going forward in the warm direction I don’t think you’ll find a strong positive feedback globally from ice.
On many levels though, the true equilibrium response is kind of an academic issue, of little interest to what actually matters. If it’s one degree a thousand years but five in a million, just say, well who cares about the million year response? Nobody in the real world, surely. Well, okay, so the “equilibrium response” will be larger than the transient response. But the degree to which the response is caused by fast feedbacks (which at least in models it generally is) one can assess the feedback that gives the equilibrium response. If you still think Lindzen is measuring a transient response, it must be that you think slow feedbacks are really important. At least in current models, however, the main factor which causes the difference between TCR and ECS is the thermal inertia of the ocean. As long as feedbacks scale near instantaneously with temperature, which mostly they do, then there is no infection of “transient response” in Lindzen’s estimate. A forcing-change comparison over a short time would be infected by “transient response” an assessment of feedbacks mostly isn’t which can be seen from the fact that Lindzen’s estimates of the senstivity of the various models, using the same method, are not systematically lower than the sensitivities of the models in question.