New paper on mathematical analysis of GHG

Thank you for one more “nail in the coffin”……
Roger

If true, another paper supportive of my suggestion that more greenhouse gases cause the hydrological cycle to speed up thus neutralising the effect on tropospheric temperatures and maintaining the basic equilibrium between sea surface and surface air temperatures dictated by sun and oceans as they interact over time.

Interesting indeed. What is really amazing though is the slew of papers that are surfacing now that would not have done so even a few months ago or at best would have been met with scorn and derision. This sort of balance has been suppressed for too long.

Well they are economists, not journalists who write for the WWF, so there’s little chance their paper will survive the IPCC ‘review’ process.

Might I be so bold as to suggest that alarmist politicians, at least around here, are stationary in differences of the 3rd kind.

From both a mathematical standpoint, and the very marginal “science” involved in this paper…it is pure crap.

Richard M (13:17:03) :
OT, Dr. Spencer has a new post that shows the Jan. temperature variation across the world. What I see does not seem to agree with some reports at WUWT. Particularly, it has Canada completely above average and I seem to remember several posts complaining of cold temps in central Canada. It also begs the question of where the cold air came from that led to the cooler temps in the US.
Was wondering where that cold air come from myself. I would have thought that it came from the Pole, but the westward motion of the jet streams and the warm anomaly over Canada seems to preclude it getting there.
Maybe it just fell out of the sky.

I wonder if this paper will get published. What is linked looks like a submission rather than a pre-print.

Hmm. They come out swinging in the abstract with, “Therefore, greenhouse gas forcings, global temperature and solar irradiance are not polynomially cointegrated, and AGW is refuted.”

Where the hell do these guys get off using “nonstationary time series” and “methodology of polynomial cointegration”? Looking through their paper, they say things like “The method of cointegration is designed to test hypotheses with time series data that are non-stationary to the same order, and to avoid the pitfall of spurious regression.” So what. How was it designed? Under what circumstances will this design succeed in modeling reality and how might it fail? And this is supposed to be a Nature paper of general interest? How are they establishing causality where others have failed? There is no discussion nor any proof. They simply assert that they are correct on the strength of tests that they don’t explain.
The statements they make are uninterpretable to anyone but them and a small group of people like this methodology. If I were to spend a couple weeks figuring out what their ridiculous jargon means, I suspect it could be rewritten using much simpler mathematics. I’ve done this before with other fields, but, I’m really getting sick of it. These authors are doing their level best to be priests of climatology. I condemn their efforts and have zero confidence in their conclusions until the put forward a convincing argument that other people can follow.

I second @Hank (13:32:44) what is the status of this paper? Also, what does stationary in 1st or 2nd differences mean as described in the paper? In googling the terms it seems to simply mean that the 1st derivative is a constant or the second derivative is a constant, respectively. Any help?

rbateman (13:58:21)
“How about biological cycle speeding up? More C02 = more bacteria, protozoa, plankton, etc. If I leave the contents of my refrigerator out in the warm air, it gets eaten whether I am able to get to it first or not.
If the bugs don’t eat it, it ain’t food.”
If you can show that a change in the speed of the biological cycle can shift the air circulation patterns in the same way that changing sea surface temperatures seem able to do then yes, I’d go along with that 🙂
As for the paper at the head of this thread it does seem a bit ‘thin’ on detail so we’ll just have to wait and see what others say when they’ve deconstructed it.

“Tom P (14:05:38) :
This is certainly the first work to state “it is not the level of greenhouse gas forcings that matters, but the change in the level.” There is no physical basis for such a behaviour, and none is even suggested in this paper.”
May i help you. A given level of greenhouse gas forcings leads to a certain equilibrium temperature. If you want a higher temperature you need to add greenhouse gases (assuming there were no negative water vapour feedback, this could even work). Simple enough?

Tom P (14:05:38)
The physical basis would be that it takes a while for the neutralising process to catch up so there is only a measurable effect whilst the change in rate of emissions is still in progress.
It’s too foggy for me to be too confident about it at the moment though the results would be convenient.

While I am not qualified to meaningfully critique this paper I would not discount mathematical methods entirely. The climate is thought to be deterministically chaotic and the various forcings and feedbacks are obviously deterministic.

If I understand this paper correctly, and I wouldn’t bet that I do, the part of global temperature influenced by GHG will remain fixed if the rate of increase of GHG is fixed. If the rate of increase is increased or reduced then the global temperature will go up or down, following the GHG trend. This seems a bit too simple which usually means I need to read it again.

I never cease to be amazed how credulous climate skeptics are. Constantly forgetting that the theory of AGW depends on an understanding of radiative physics, and hyping the most dubious of analyses. Like this paper. The findings of which are blatently aphysical. I defy anyone to come up with a reasonable physical mechanism to explain this “our results clearly indicate that it is not the level of greenhouse gas forcings that matters, but the change in the level”

Richard M
Central Canada (manitoba) has been moslty extremely cold or extremely warm this winter. Recently it has been about seasonal, but Nov was very warm, Dec very cold, then Jan half and half (of the extremes). iirc.

Richard Telford: who is being “credulous”? Most of the posts commenting on the paper are questioning its status or disputing its claims. Methinks you’re seeing what you want to see.

Where are the data tables?

I “read” the paper, but please don’t ask me!

Not heretics? Or deviants better not discussed. Abominations?
Well, as some one said, they are still economists. So they have not defected, sinned, or mutated into beasts.
They must be “ignorant beyond belief” instead.
We shall see. The PDF doesn’t seem to tell enough about the code used or the data. I don’t see that as reason for concern it will show up. Or not.
I look forward to what the experts will tell us.

Frederick Davies:

The link points to a PDF named Nature_Paper091209.pdf, so guess where it has been submitted…

And accepted?
A Google scholar search shows nothing, and a Nature.com search shows nothing.
In his resume webpage – http://economics.huji.ac.il/facultye/beenstock/cv.pdf – it is listed under “current working papers”.

I’m reading it now… so far so good. I’ve been saying the same thing about polynomial cointegration for years but no one would listen (okay, not really). However, this looks like a draft. Was it really accepted by Nature? If so, has hell frozen over?

Stephen Wilde (14:20:11) :
I was going along a line even simpler: Coytoes and rabbits.
If you have an explosion of rabbit pop, the Coyotes prosper.
When the rabbits thin out, so do the Coyotes.
If we release a lot of prehistoric biofuels, there should be a biological response to consume them.
If they are not biofuels in origin, biological forces won’t eat them, geology will, and it’s really slow unless the oceans get really cold fast.

Doug Badgero (14:17:35) :
Also, what does stationary in 1st or 2nd differences mean as described in the paper? In googling the terms it seems to simply mean that the 1st derivative is a constant or the second derivative is a constant, respectively. Any help?”
I would expect it means the process is stationary in a stochastic sense in 1st or 2nd differences, as e.g., Brownian motion is stationary in 1st differences.
Richard Telford (14:43:26) :
“I never cease to be amazed how credulous climate skeptics are.”
I never cease to be amazed at how AGW enthusiasts believe failure to suppress information is equivalent to endorsing it.

I’m with pRadio at the top that, thank heavens, this is another nail in the AGW coffin. But then we still will have to deal with “guerilla” thermofascists in industrial and political positions of power as well as the general public, people who are superstitious as far as science is concerned and whose beliefs regarding AGW bear no relation to the findings of real science.

Richard Telford,
It means there’s a lag for something like the oceans to catch up and compensate.
It’s like the inflation rate. The inflation rate doesn’t actually matter as long as it’s constant because everyone can factor it in. It’s the change in the inflation rate that burns some people and makes other rich as they are forced to adjust to the new rate, depending on how they’ve invested and how their compensation is calculated.
On the scientific point, if global warming could be simply explained with radiative physics then this wouldn’t be the 15th year without any stastically significant warming (according to Phil Jones, former head of CRU).

David (14:13:02) :
Why is it in all the books that I have read on the subject of climate change; all the newspaper articles etc etc, I have not seen any mention of Precession. as I understand it (and I am not in any way qualified) all the calculations for a planetary rise in temperature are inaccurate unless Precession is taken into account as a base figure.
David,
  It takes the earth 26,000 years to complete one precession cycle.  Obliquity takes 40,000 years to complete a cycle.  The contribution that a change in precession and/or obliquity contributes to climate over a hundred year period is correspondingly minuscule. 
 http://www.sciencecourseware.org/eec/GlobalWarming/Tutorials/Milankovitch/
Mike Ramsey

DCC (13:21:52) :
I think you caused the economics.huji.ac.il web site to crash 🙂
Better them that CA! 🙂

OT – but concerns robust and glaciers.

“The scientist at the centre of the storm over mistakes by the UN’s climate change panel has broken his silence on the affair to defend his report as “robust and rigorous“.
……..
[Martin] Parry was co-chair of the Intergovernmental Panel on Climate Change’s (IPCC) working group on impacts, which produced a 2007 report that included the false claim that Himalayan glaciers would melt by 2035.”

If the findings of this paper are correct (I presume they are until further notice) then it’s more than just another nail in the AGW coffin. It’s a direct nuclear blast that destroys it completely, and there’s nothing left to even have the need for a coffin. It is now time for the likes of Al Gore, Rudd, Obama, Jones, Mann, etc. to call a truce and re-think the whole AGW debate. Otherwise, they should now be called upon to defend their agendas and theories in a court of law and if found guilty be punished accordingly.

Their basic claim is that CO2 follows the statistical pattern you’d get if you took a stationary time series (one where the distribution is constant over time) and integrated it twice. Temperature, they say, matches a stationary series integrated only once. These are two completely different sorts of behaviour that can’t remain correlated for long – so any correlations you do see must be spurious.
The cointegration stuff is about bending over backwards to allow for statistical oddities, because there are some exceptions to the above rule in which variables can be genuinely related even though they appear to have different orders. Cointegration occurs when two time series are both non-stationary, but there is a stationary linear combination of the variables (or their nth differences) – i.e. the difference between them has a constant distribution. This sort of thing can happen if there are certain sorts of feedback mechanisms. So they perform some additional tests to eliminate this possibility, which take up the bulk of the paper.
If anyone wants to check it, I’d start off thinking about their first claim, that the time series are of different orders meaning that the correlation is (without cointegration) necessarily spurious. I’d be concerned that all they’re testing is whether the trend in temperature is entirely down to CO2, which given the noisy jagged temperature and the smooth quadratic Keeling curve it is pretty obviously not. If you have a fast first-order process on top of a slow second order one, it could look first order to tests, although it had a strong second order component. They do cite some earlier papers which might be worth examining. (e.g. v, vi.)
But if that first argument does work, the second part with the cointegration test will probably go through on the same reasoning. However, I’m not a specialist at this sort of thing – you need to find a statistician and ask.
Basically, it’s saying that there is some sort of unknown feedback mechanism, adjusting some other quantity, that compensates for the effect of changes in CO2 within a few years. i.e. CO2 warms the atmosphere, which permanently releases something else, which cools the atmosphere again.

scienceofdoom
“For example – not that I am convinced by the argument – but the modeling community says that when they run their models with the effects of CO2 AND aerosols, they can explain the last 100 years of climate history. (Seems like a necessary but not sufficient proof of climate models..)”
They only do this by assuming the warming is CO2 because the models cannot explain the warming otherwise. Bottom line: the models do not understand the magnitude of natural variation and are thus stuck with a tautology.
I do agree, however, in not understanding exactly what this paper is doing. There seems to be something missing or something sideways. IOW, something I can’t articulate bugs me about it.

So if the effect of the absolute CO2 level is temporary, not long term, would it be going too far to say that CO2 affects “weather, not climate”?
Just had to throw that out there. 🙂

In a shock revelation, the organization known as the IPCC said they agree with the new unpublished paper by Beenstock and Reingewertz.
A high level IPCC scientist admitted last night:
We hid the results away so that no one could find them
Finally, forced by angry public pressure to release the location, this top scientist pointed to an obscure website called http://www.ipcc.ch.
Now that the media have had a chance to examine the revelation, they found this shocking comment buried away in the Executive Summary of Chapter 8 “Model Evaluation” (2001 Third Assessment Report):

Confidence in the ability of models to project future climates is increased by the ability of several models to reproduce the warming trend in 20th century surface air temperature when driven by radiative forcing due to increasing greenhouse gases and sulphate aerosols. However, only idealised scenarios of only sulphate aerosols have been used.

And later, even harder to find without actually reading it:

As noted in the SAR, the inclusion of the direct effect of sulphate aerosols is important since the radiative forcing associated with 20th century greenhouse gas increase alone tends to overestimate the 20th century warming in most models. Groups that have included a representation of the direct effects of sulphate aerosols have found that their model generally reproduces the observed trend in the instrumental surface air temperature warming, thereby suggesting that their combination of model climate sensitivity and oceanic heat uptake is not unrealistic (see Chapter 9, Section 9.2.1 and Figure 9.7).

-More shocking revelations of stuff the IPCC never told anyone, coming up next hour..

It´s the SUN….! PERIOD.

The salient point of this analysis is that in order to determine what CO2 will do in the future in a complex system it is more instructive to look at what it has done in the past in that system rather than to argue on the basis of a single theoretical physical effect component.
Data always trumps theory.

Beware of Geeks bearing gifts!
However high-falluting the language of these theorists may sound and however much I’d love to believe their findings but I’m ‘sceptical’! Perhaps I may be turning into a “suspicionist”
If the past few decades have shown us anything that took root in our awareness then, for me, it’s been the willingness of so many to clamber aboard bandwagons!
Yesterdays gravy-train rewarded its passengers for rooting out the sin of SeeOTwo (in Science CO2 but, phonetically, rendered into a format that multitudes of Scientifically unaware, but easily duped, could cope with)
Today, work in progress, the popular paradigm appears to be shifting. Possibly Man is not the primary driver as once thought!
I’m not impressed by the prognostications of currently resident Robust-Man, Gavin, but neither am I interested in him being replaced by an equivalent contrarian!
Forget the models. Today’s or tomorrows! Listen to the data.
That’s why I go to CA to sit before SMc, Mosh, Bender et al. Ditto for WUWT, AV and BH etc.
Beware of Geeks bearing Gifts.

R. Gates (13:53:54) :
From both a mathematical standpoint, and the very marginal “science” involved in this paper…it is pure crap.
_____________________________________________________________________________
Everyone here is entitled to their own opinion. The problem here for me is, I don’t know your background, so how can assign a relative value to your opinions? You may well be right, for all I know.
That being said, which disciplines of science and/or mathematics do you hold advanced degrees in? What facts are you basing your very strong opinion on? Did you already find and read all of the supportive works cited in the paper? Where did the authors err, in your analysis? Inquiring minds want to know!
_________________________________________________________________________
I have noticed that with very few exceptions, most posters and guest authors here do not state their qualifications. For instance, I am considered to be a reasonably intelligent fellow with a degree in Political Science. While I may not be able to follow all of the advanced math and science, I can follow the authors’ reasoning and supporting arguments. As always, the devil is in the details. I need to hear what other qualified mathematicians or scientists in the fields related to climate science have to say about the paper; people who understand the math and the jargon so they can opine with some authority. Perhaps R. Gates is so qualified, but I don’t know that.
One can draw an informed opinion from analyzing the concurring and dissenting arguments of people well qualified in the subject matter to do so. However well informed one may be, they are still a layman and not a qualified scientist. I am no different than our elected policy makers in this regard. With much of the supporting “settled” science in question and the compromised integrity and veracity of many of the scientists involved, a prudent approach would be to affect a Missouri attitude (Show Me or skeptical).
No disrespect meant to R. Gates or anyone else here. I just like to know who’s who.

At the end of the day, what Miskolczi said was an increase in CO2 would cause a temporary fluctuation that would settle out to an equilibrium about the same as before. What this paper says is that an increase in CO2 would cause a temporary fluctuation that would settle out to an equilibrium about the same as before.
The notion that this paper defies physics is correct… provided that it is physics as per the IPCC and others who argue that increase in CO2 is a positive feedback that will in the long term exceed negative feedback. If its physics governed by the laws of thermodynamics including conservation of energy though, then it supports the physics.

I really am amazed at how the warmist trolls in this post come out immediately attacking something they obviously don’t understand and don’t have the credentials to understand. Let time take its course and we will see if this is refuted or clarified by those mathematicians, physicists, and climatologists who should understand it. I only remember polynomials from my high school algebra class, so I don’t know what the heck “polynomial cointegration” is, either.

Miskolczi Interview
“Former NASA scientist defends theory refuting global warming doctrine“
http://www.heliogenic.net/2010/02/13/miskolczi-interview/

I can help explain the first and second derivatives being a constant.
Consider the equation of a line, Y = mX + b, where m is the slope of the line. The first derivative dY/dx results in m, a constant. Thus, the equation is first order, because the first derivative (dY/dx) yields a constant. The term ‘b’ disappears, as the derivative of a constant is, by definition, zero.
But, when this is done with a curve, such as a parabola, the first derivative yields the equation of a straight line. The parabola equation is y = ax^2 + bx + c. The first derivative is then dY/dx = 2a x + b. We must then take the second derivative to obtain a constant. Thus the equation is second order.
What the paper appears to state is that portions of the problem are first-order and other portions are second-order.

Man-made global warming caused 9/11.
“(CNN) — The thin wisps of condensation that trail jet airliners have a significant influence on the climate, according to scientists who studied U.S. skies during a rare interruption in national air traffic after the September 11 terrorist attacks.
During the three-day commercial flight hiatus, when the artificial clouds known as contrails all but disappeared, the variations in high and low temperatures increased by 1.1 degrees Celsius (2 degrees Fahrenheit) each day, said meteorological researchers.”
9/11 Study: Air Traffic Affects Climate
http://archives.cnn.com/2002/TECH/science/08/07/contrails.climate/index.html

From the Conclusion, page 13 of the pdf:
We have shown that greenhouse gas forcings do not polynomially cointegrate withglobal temperature and solar irradiance. Therefore, previous claims that carbonemissions permanently increase global temperature are false.
http://economics.huji.ac.il/facultye/beenstock/Nature_Paper091209.pdf

[quote bob (14:55:55) :]
Where are the data tables?
[/quote]
They’re at the end of the article.
Anyway, I’ll label this paper as “interesting”. That the rate of change in CO2 matters is certainly a new idea. But I’ll wait till I see someone come up with a physical process that occurs when the rate of change of CO2 changes before I take the findings of this paper seriously.

I’m really amused by some of the comments regarding the data. The time series of cointegrated comments over the last 15 years sounds like this:
Warmists – this data shows that CO2 is heating up the planet
Skeptics – that data is all messed up
Warmists – is not!
Skeptics – is too!
New Paper – the data shows that CO2 is NOT heating up the planet
Skeptics – that data is all messed up
Warmists – that data is all messed up
Skeptics – yeah, that… huh? what?
I also think it would be very interesting to see this analysis done again, but with a better data set because I think the methodology itself makes sense.

David L. Hagen (15:45:26)
_______________________________________
As you noted, the Beenstock and Reingewertz paper did not include water vapor in their calculations and you refer to the recent work by Miskolczi in which water vapor is a central issue. I would like to suggest that the Miskolczi model and the rationale underlying Willis Eisenbach’s Thermostat hypothesis may in fact have a lot in common. Miskolczi sees the water effect as stabilizing the IR layer to a constant value while Eisenbach thinks of cloud formation, which depends on water vapor, as the fundamental “governor” of global temperature. My own experience as a sailor in the Caribbean resonated very strongly with the effects described by Eisenbach. My belief is that the Earth is a huge heat engine about which know little. I feel that both Miskolczi and Eisenbach are on the right track to helping our understanding.

Michael (17:57:08) :
Man-made global warming caused 9/11.

Do you think perhaps your thesis should be totally reversed, for both ’cause and effect’ and the direction of effect, vis-a-vis:
“9/11 caused man-made global cooling ”

“During the three-day commercial flight hiatus … the variations in high and low temperatures increased by 1.1 degrees Celsius (2 degrees Fahrenheit) each day, said meteorological researchers.”

.
.

George Turner
My point is not to defend any GCM models. I would be amazed if they could predict the future.
And who knows, I might find out that buried away in that paper they actually reviewed the results of an actual climate model. Or the derivative of a climate model.
It’s just seems like the Coleman report all over again – disproving the IPCC by proving something the IPCC agrees with.
Call me old-fashioned but I find it more enjoyable to see a discussion where the presenter actually knows what his opponents believe and demonstrates the flaw in those arguments.
I’m clearly in a minority though, but that’s ok.

I wouldn’t put any more faith in this paper than I would have if it pointed in some other direction. Sounds like mumbo jumbo to me. “If all the economists in the world were laid end to end they would still point in different directions.”

I wouldn’t put any more faith in this paper than I would have if it pointed in some other direction. Sounds like mumbo jumbo to me>
I think some people are nervous about these results or rejecting them outright because the analysis technique is so foreign to how we look at data, but this technique is not new. I first came across it 20+ years ago when I was introducing this revolutionary computer technology called a graphics terminal (yes! you can draw lines on the screen!) to researchers. One of my customers was a geophysicist who was trying to locate micro-seismic events in three dimensions from an array of sensors. I remember him showing me some of his data capture from the sensors on the screen. There was a squiggle and he’d show me the math to determine how far away and how deep (back then I could still do the math…. now not so much). Then another squiggle which he identified as a heavy truck going by on the nearby highway. Another squiggle was from heavy artillary at a military base a few miles away. Then a BIG squiggle. What was that? Using similar techniques he showed that the big squiggle was a seismic event, a truck going by, and an artillary strike all at the same time. He could figure out how much of the squiggle was seismic event and how much was “other stuff”.
One of the first big events he captured was too far away for him to calculate location, just distance, but we knew it was big. The next morning the quake that clobbered Mexico City was on the news, so about 1985 I think?

It may seem strange having a couple economists using one of their statistic techniques on climate, but both sciences are about finding cause and effect in a massively chaotic system. Data-wise, I see more similarities than differences and I think economics is a little more mature on the statistics side…..
Does anyone know any other studies that can account for CO2 only having a temporary effect? Could that be attributable to the black carbon issue or is a 1 year half-life too long for that?

jorgekafkazar (15:05:34) :
JDN (14:13:26) : “Where the hell do these guys get off using “nonstationary time series” and “methodology of polynomial cointegration”? … [snip]
Part of the risk of visiting science blogs is that you may run into terminology peculiar to areas of science of which you are partly or totally ignorant. Most people either look it up or let it go, instead of flaunting their ignorance in public.
Actually, I’m flaunting my disgust. I’m a scientist of various training with a heavy emphasis on mathematics and biology at this point, so, I’m accustomed to being ignorant of one subject or another. This paper is a case of people deliberately trying to obfuscate their work. You see it all the time in mathematics. At this point, if people refuse to write clearly and try to disguise their methods, I’m not interested in looking it up. They need to summarize their independent variables, justify their choices of variables (e.x. they introduce rfCO2 without explanation… it could be anything), explain why they are using linearized equations for those variables instead of raw data, provide some explanation on how their statistical method (something not useful for establishing causality) overturns predictions that have explicit causality (AGW calculations for all their flaws still pretend to be causal), etc., etc., & etc. As far as I’m concerned, this paper reads like the Sokal hoax.

I hadn’t known, before reading this paper, that it is already known that CO2 is I(2) and temperature is I(1). In economics, a finding like that that is normally taken to mean “Game Over” for any theory that says a permanent increase in the level of CO2 will cause a permanent increase in temperature. The theory has failed at the very first empirical hurdle. I am surprised that this result has not been more widely publicised. It’s a big problem for the CO2 theory.
(What Beenstock and Reingewertz do is try to help the CO2 theory jump over that first hurdle, by getting some help from solar irradiance. Even with help, the CO2 theory fails to jump the first hurdle. But solar irradiance can jump the first hurdle.)

mikep (15:08:23) :
http://www.ulrich-fritsche.net/Material/murray1994.pdf
Thank you for this link!!
This should be read (short, clear, sweet) before tackling the subject of the post.

Richard Tol: “Temperature has increased linearly. CO2 has increased exponentially. If CO2 would have driven temperature, it would have increased exponentially too.”
That sounds a dubious statement. CO2 is subject to saturation effects. Therefore temperature should increase at logarithmic function of CO2. If CO2 is increasing exponentially that would make temperature linear as found?

“JDN (20:43:35) :
[…]
summarize their independent variables, justify their choices of variables (e.x. they introduce rfCO2 without explanation”
“In Table 1 we provide details of the classification procedure for the radiative
forcing of CO2 (rfCO2).”
Questions?

Don’t want to sound like a broken record but I probably do.
It would be wonderful to see an analysis of actual climate model outputs against reality.
Rather than a fictional result (CO2 correlated to temperature) which everyone including the IPCC all agree won’t produce good results.
A real climate model has more than CO2 affecting climate.
Surely someone can produce an analysis.

R. Gates (13:53:54) :
“From both a mathematical standpoint, and the very marginal “science” involved in this paper…it is pure crap.”
Actually, if they were using a computer with available “climate data” then, I totally agree with you!
The one thing I have learnt in the last few years is that we are light years away from being able to model chaotic systems, especially when one ….fudges the figures but as usual I will leave it to Lord S. McIntyre to debunk the numbers.
Honest! The Queen will be over to Canada very soon to get the blade out on S.M. if only to shut up “He who Talks to Plants”!

“Still, rfCO2 is I(2) — in this and other studies — that is, the second partial derivative is positve. Temperature is only I(1) — that is, the first partial derivative is positive but the second is not.”
It means the second derivative is stationary, not necessarily positive.
It is true that if temperature really is I(1) then it cannot be driven by CO2. But if you take an I(1) process and add a very small amplitude I(2), the result is strictly speaking I(2), but looks I(1) on short time scales. You need to collect a huge amount of data for the I(2) behaviour to come out.
I’m beginning to think that what this paper says is that the null hypothesis – of any correlation being spurious/temporary – cannot be rejected on the evidence available. That’s not the same as the positive statement of saying the correlation is entirely spurious/temporary. It’s also nothing to get excited about.

Pa Annoyed (03:30:38) :
The paper states:
“We confirm previous findings (ii,iii,v,vi,iix) that the radiative forcings of greenhouse gases (C02, CH4 and N2O) are stationary in second differences (i.e. I(2)) while global temperature and solar irradiance are stationary in first differences (i.e. I(1)).”
There is no analysis given in this paper that temperatures are I(1) – it is just asserted. As for the previous findings, if you look at the latest Kaufmann work they cite, it actually says “temperature itself is not I(1)”, hardly what this paper claims to confirm.
This is a sloppy and obscurantist piece of work.

‘Street (20:08:02)’ put it very well when he made the comparison between economics and climatology.
Methodologically speaking, climatological modeling looks much more like economic modeling, than modeling in the exact sciences. Climatology, just like economics, relies mainly on non-experimental data to verify it’s hypotheses (i.e. models).
The main differences are:
(1) economists know econometrics, and climatologists just wing it as they go along (ask E. Wegman or J.S. Armstrong).
(2) economists have access to many different time series. This is quite important if one realizes that, in (statistical) time series modeling, an observed series is treated as a single drawing from an (unknown) data generating process.
In broad lines, the paper posted above empirically tests whether we find CO2 effects on temperature. The Time Series methods employ assume very little about the underlying data generating process; it is a statistical procedure, much akin to measuring a correlation. Very simply put: rather than looking at the relationship between levels in the variables studied, one looks at the relationship between growth rates (or changes in growth rates), which should be just as solid if the hypothesized relationship between levels is valid.
The conditions tested are furthermore necessary for causality, rather than sufficient. This paper therefore rejects the necessary conditions for measurable causality. I say ‘measurable’ because it is quite plausible that CO2 levels impact temperature in some way. It is however very unlikely that they impact them such a straightforward and unambiguous manner as proposed by Mann et al.
Furthermore, methodologically speaking, what amounts to ‘scientific proof’ of a hypothesis in climatology is very disturbing. The argument propagated by both Mann (in his recent Washington Post editorial) and Jones (in his recent BBC interview), is that Man-Made CO2 is the culprit because the coefficient is significant in their regression.
Note that this is also their ONLY empirical/fact-based argument, the rest of their ‘arguments’ are hypotheses (i.e. models) and anecdotes.
Mann wrote: “Scientific evidence for the reality of human-caused climate change includes independently replicated data documenting the extent of warming; unprecedented melting of glaciers; rises in global sea levels; increasingly widespread continental drought; and models that predict all of these things but only when human impacts are included.”
Rough translation:
(1) We tried to explain the variance in temperatures with a model including total CO2, the coefficient was insignificant.
(2) We then split total CO2 into Natural and Man-Made CO2, where the latter series (which represents only a small part of total CO2) is equal to 0 for most of the last millennium, and shows a positive trend since the industrial revolution.
(3) In our new regression, the positive Man-Made CO2 trend (now entered separately from Natural CO2) coincides with the modern warming trend, and therefore ‘sucks up’ the variance. The Man-Made CO2 variable then ‘explains’ the Modern Warming.
I furthermore bet that the coefficient on the Man-Made CO2 variable is very high. This shouldn’t surprise anybody. You are dividing a warming trend with a (relatively) small Man-Made CO2 trend, the outcome will be a very high amount of ‘warming’ per unit of Man-Made CO2.
Do note that it is only of marginal importance how exactly Man-Made CO2 enters the right hand side of the equation. As long as the hypothesized relationship is positive, it is very likely to be ‘validated’ by regressing two positive trends on each other.
From this it should also be clear why Michael Mann really wants to eliminate the Medieval Warm Period from the official temperature record. If the temperature record is flat (i.e. has low variance) before the Modern Warming Period, his Man-Made CO2 variable will have an even stronger and more statistically significant effect (the temperature variance in the past won’t ‘disturb’ his two-trend regression).
..
This type of analysis wouldn’t pass as a Bachelor thesis in econometrics at the university where I graduated.

@Tom P / Pa Annoyed
I was just trying to summarise the paper for people who do not know econometrics.
The paper does not volunteer many details, but Beenstock is a fine econometrician. Besides, the core argument — the different orders of integration — is well-established.
The innovation of the paper is the polynomial integration.

Joe (18:22:04) : JonesII (16:22:37) : It´s the SUN….! PERIOD.
“If it was truly the sun then it would only effect heat and cold. Not evaporation or precipiation that is increasing.”
Where does your information on increasing evaporation/precipitation? The atmosphere is drying out: http://i38.tinypic.com/30bedtg.jpg

Leif Svalgaard (20:35:49) :
red432 (18:52:40) :
Sounds like mumbo jumbo to me.
To me too !
Of course the arrival of mumbo jumbo conjurors in the skeptical camp is pretty good evidence that the tides of intellectual fashion are turning, perhaps decisively. These guys may not know how to predict climate, but they know how to get papers published…

And I bet that the statistics used to analyse tree ring data for the Hockey Stick, falls into the same trap.
Stationary statistical methods used for non-stationary data leading to spurious correlation.
Didn’t Steve McIntyre say this some time ago?

Just to follow up on this, I plotted the 1st and 2nd derivatives of monthly CO2. The 1st derivative gives you a wave that matches monthly changes to the solar ephemeris, which is the distance between the sun and earth.
The 2nd derivative gives you basically the same thing, but with a longer sequence wave repeating in the series. This longer wave generally matches the up and down trends of both cosmic rays and monthly sunspot groups, at least between the period of Sept, 1983 to Dec, 1995. Between Cosmic Rays and Sunspot groups, I’d give an edge to cosmic rays as both the cosmic rays trend and the 2nd deriv CO2 trends are flat, where as the sunspot trend edges up slightly.
So basically, I’d say if this paper has hit upon something, it’s that there’s a correlation between the 1st deriv of CO2 and the solar ephemeris, and the 2nd deriv of CO2 and reversed cosmic rays.
Anyone wanting to repeat this analysis or explore it further can get the data I used from my Climate Scientist Starter Kit here:
https://sourceforge.net/projects/cssk/files/Climate%20Scientist%20Starter%20Kit.zip/download

Hi all. Matt Briggs here.
I’ve not had time to read all the comments, but I have, on the request of an email, read the paper.
I do not find it especially interesting and cannot support its conclusion “that greenhouse gas forcings do not polynomially cointegrate with global temperature and solar irradiance.”
What the authors did was fit a particular kind of times series model to a couple of sets of data (not the only sets). They came to the conclusion that, since their model more or less fit their sets of data, the “previous claims that carbon emissions permanently increase global temperature are false.”
There are many kinds of time series models; some will fit better than others. Regardless of how close any of them fit any set of data, no measures of fit of those models can disprove—or prove—the AGW theory.
Statistical models can add weight to the evidence that the AGW theory is true or false, but none can ever prove it false, as the authors have claimed.
Too, their model is not especially convincing and rather divorced from the physics. Also, the more a statistical model strays from the physics, the less weight we should give it.
Last, like nearly all similar analyses, the authors do not account for the uncertainty in the sets of data. These numbers aren’t measured perfectly, and that uncertainty should be carried through and expressed in the final results.

davidmhoffer,
But the car ride is politicized and there’s a guy citing tipping point theory saying, “There’s a bomb on the bus. If the bus goes below 50 the bomb will explode. What do you do, hotshot?!”
I agree with your analogy, though.
If there’s no discernable statistically valid correlation between CO2 and temperature, then continued claims that CO2 increases will cause temperatures to rise is falsified. AGW people may wave their hands, citing physical theory and complexity as reasons why no such correlation can be found (which is like mumbling “God works in mysterious ways!”) , but for their warnings that CO2 will devastate the planet through increasing temperatures there MUST be a detectible correlation between CO2 and temperature. This paper used accpeted and sophisticated statistical techniques and failed to find such a correlation.

mattstat,
I disagree that the more a statistical model strays from the physics, the less weight we should give it.
The whole debate about global warming boils down to this simple model.
CO2 increase -> black box -> equillibrium surface temperature increase.
With sufficient experimentss you could reduce it to a simple graph of CO2 level versus long term global average surface temperature. The lack of that one simple graph is why governments are spending billions – with the end result of one day producing that graph.
One way to unequivacally produce it would be to vary atmospheric CO2 levels over thousands of years with a sweeping frequency modulation, then use a Fourier transform to find the same sweeping frequency component in the temperature records. But that would take thousands of years.
The current data set is so limited that rough curve fits are too easily produced by dreaming up a couple of confounding effects whose magnitude is essentially a guess, allowing everyone to use their favorite fudge factors to get a better looking fit and reducing the science to arguments about whose fudge factor model is best.

Willis,
It is fine to post a paper here to determine if it is true, but the paper was not really introduced that way. It was introduced more like “Game over. We have the paper that disproves AGW.” Indeed, that is the claim the authors make.
It would have been better if the paper had been introduced as “Here’s an interesting paper that draws very strong conclusions. It has not been published yet or accepted for publication, but let’s look at the data, methods and conclusions and see if the paper has value.”
In pursuit of that goal, I have provided a link to a paper which claims to use some of the same tests. Only this paper claims the tests prove AGW. It would be interesting to see an analysis of why the same tests get such different results. See http://www.springerlink.com/content/h0tx44h508602755/

George Turner;
If there’s no discernable statistically valid correlation between CO2 and temperature, then continued claims that CO2 increases will cause temperatures to rise is falsified>
Not quite. What the said is that there IS a stasticaly valid correlation between CO2 INCREASE and temperature. What they show is that the amount of increase is like a bump in the road…. so the increase causes an oscillation, but no long term change. Hence their comments about the rate of increase being important like the size of bump in the road. But it is the RATE OF INCREASE the defines the size of the bump in the road, and hence the oscillations in temperature, which will damp out to zero. Not the amount of CO2 itself.
Which fits exactly with the physics.

Mark Sawusch (08:33:37) :
“the coefficient in the quadratic term of 5E-05 is so small that it’s essentially zero”
Not at all. It’s just that the fit is to year-squared values that are very high (e.g. 1900^2). Hence the coefficient will necessarily be small, but that doesn’t make it essentially zero.

@Tom P
I took the series magicjava posted (global mean temperature, 1900/01-2009/03) and averaged the non-normalized data for each year (I was too lazy to make monthly/seasonal adjustments).
Augmented Dickey Fuller test (no intercept, 3 lags, selection based on SIC) on annual global mean temperature. Note that the H0 of the ADF test is that the series in fact has a unit root.
ADF test stat: -1.134301
(1% critical value, -2.587172)
One sided, MacKinnon (1996), p-value < 0.2323
Augmented Dickey Fuller test (no intercept, 2 lags, selection based on SIC)) on the first difference of annual global mean temperature:
ADF test stat: -9.720368
(1% critical value, still, -2.587172)
One sided p-value < 0.0000
At first sight, temperature seems to be I(1), as the authors claim.

I would like to point out that there is a difference between econometrics, and economics. Econometrics is concerned with numerical analysis and hypotheses, which may or may not be valid.
WRT the findings on the data they examined, I find it interesting that no correlation has been found, despite the best efforts of the warmists to make the case for warming so convincing by modifying the data. Should the methodology they used withstand critical scrutiny, it would seem to be a powerful way of detecting bad data.

science of doom. you can go get the results yourself. they are available.
terabytes. Hop over to Lucia’s she works that problem and some of her regulars as well ( chad )

davidmhoffer (18:21:08) :
I love that little logic knot as well. my favorite version is this.
Skeptic1: the temperature data is all messed up.
Warmist: is not.
Skeptic1: is too.
Skeptic2: Here I show how sunspots correlate with the temperature data.
Warmist: Your pal said the data was screwed up.
Skeptic2: err, ya but.
There are of course ways to wriggle out of this knot, but the fundamental question of the accuracy of the record remain and all analysis that uses that data is subject to caveats. GIGO for one GIGO for all.

WRT the physicality of the argument. I want to show you a little logic trick you may find useful. (Hat tip to GE Moore)
Suppose that you read a long detailed statistics paper that claimed the earth was flat. What would you conclude? and why?
assume you don’t know statistics? assume you know statistics but can find any error in the paper. Can you rationally reject this paper and it’s conclusions even IF you can’t find the error? why.
How can I reject this paper without even checking it?

grumpy old man (09:50:44) :
What is the feedback mechanism that makes the increase temporary?
The two suspects seem to be humidity levels and cloud formation behavior.
George Turner (09:04:22) :
The current data set is so limited that rough curve fits are too easily produced by dreaming up a couple of confounding effects whose magnitude is essentially a guess, allowing everyone to use their favorite fudge factors to get a better looking fit and reducing the science to arguments about whose fudge factor model is best.
Well said – that is a very frightening proposition if GCMs have actually been produced this way
Ron Cram (09:07:37) :
this paper claims the tests prove AGW. It would be interesting to see an analysis of why the same tests get such different results. See http://www.springerlink.com/content/h0tx44h508602755/
Very interesting! Abstract from the linked paper:
Abstract To characterize observed global and hemispheric temperatures, previous studies have proposed two types of data-generating processes, namely, random walk and trend-stationary, offering contrasting views regarding how the climate system works. Here we present an analysis of the time series properties of global and hemispheric temperatures using modern econometric techniques. Results show that: The temperature series can be better described as trend-stationary processes with a one-time permanent shock which cannot be interpreted as part of the natural variability; climate change has affected the mean of the processes but not their variability; it has manifested in two stages in global and Northern Hemisphere temperatures during the last century, while a second stage is yet possible in the Southern Hemisphere; in terms of Article 2 of the Framework Convention on Climate Change it can be argued that significant (dangerous) anthropogenic interference with the climate system has already occurred.
Perhaps the difference is due to the GES paper only looking at CO2 and temperature, while the BR paper looks at CO2, irradiance and temperature. I think, in theory at least, econometrics techniques should give consistent results between a 2 variable analysis and a 3 variable analysis (assuming proper methods, same data set, same time frames, etc)… but for a sec let me eyeball and summarize the trends using NOAA’s summary data (assuming of course that the data is correct):
Temperature – long term upward trend since bottoming out around 1910, stalled from around 1945 to 1977/78 (http://www.climatewatch.noaa.gov/2009/articles/climate-change-global-temperature)
CO2 – exponential upward trend since the 1950’s (http://www.climatewatch.noaa.gov/2009/articles/climate-change-atmospheric-carbon-dioxide)
Irradiance – long term upward trend since the early 1900’s (http://www.climatewatch.noaa.gov/2009/articles/climate-change-incoming-sunlight)
Personally, I am quite at a loss to understand how the increase between 1910 and 1945 (~.5 C), and 1977/78-current (a smidge under .6 C) fit with a constant up-trend in irradiance over the entire period that accounts for 10% or less of warming, and an exponentially increasing level of CO2 from 1960-on – which is, as I understand it, the official explanation… but anyway
I would be very interested to see the timeframes for the two analyses. As strange as it is, I can imagine that both analyses could be technically correct if the timeframe for GES was 1960-on and BR was from 1910-on… which would then beg the question which one is more correct(?)

“”” Merv Hobden (05:19:43) :
My own opinion is that water vapor is such a powerful blocker of long wave IR – mainly by reflection, because of reststrahlen and the difference of refractive index, that CO2 effects are orders of magnitude lower. A simple water cell, with 1/2″ of water in it will completely block the longwave IR from a 300W tungsten lamp. And, the water does not boil, as the mechanism is reflective, not absortive. Below the cut off wavelength of 4.5microns, the water is completely transparent – the visible and near IR pass straight through. You can put your hand in front of the cell – there is some heating from near IR absorption, but little serious effect. Without the cell -Ouch! “””
Well Merv, I don’t know where you get your physical properties of water or water vapor from; but they don’t jibe with anything that I find in standard handbooks.
Far from being completely transparent below 4.5 microns, water does in fact have very significant absorption bands below 4.5 microns, and one particular band at 3.0 microns, has almost ten times the absorption coefficient that water demonstrates in the range, from about 4.0 microns to beyond 10 microns. Other bands at 2 and 1 microns are very well known; and water vapor starts having significant impact on for example the solar spectrum, at wavelengths from about 760 nm.
As to your belief; well you call it “your own opinion” that water’s interraction with LWIR is primarily reflective; standard textbooks (such as “The Infra-Red Handbook” show no untoward reflection from water out to at least 13 microns; that is no reflectance that is not fully explained by normal Polarised Fresnel Reflection; that changes over that wavelength range in accordance with the refractive index variation. So it is never as much as 5% reflectance at normal incidence, and is mostly under 3% over that range.
Water vapor is a major greenhouse gas; THE major one, and water in its liquid and solid phases also has major climate and weather related effects; clouds for instance.
But I’m with Phil; your water cell demonstration is hardly indicative of what actually happens in the real atmosphere (or oceans either.

NickB,
Thank you for some reasonable comments. The time frame analyzed could be a big reason for the difference in the two papers.
As an aside, if you use CRU data, I think the warming from 1910-1945 is slightly greater than the warming from 1975-2005.
I would love to see a thorough and convincing refutation of CAGW.

NickB. (11:26:56) :
grumpy old man (09:50:44) :
What is the feedback mechanism that makes the increase temporary?
The two suspects seem to be humidity levels and cloud formation behavior.
———
Makes sense, clouds would seem to be the answer. This would indicate that the system is very stable, and would explain why we have not had runaway warming in the past. I do not see how humidity levels could be directly responsible, though.

Let’s make that more realistic. Suppose you did an experiment that showed sub-atomic entities were waves. Then you did another that showed they were particles. What would you conclude?>
That they’re wavicles?

i knew the flat earth part of that would trip folks up . lemme splain another way.
you get the gist is the Moorian argument. The point I would make is that many people approach these problems in the “common sense” manner.
( hmm maybe it was wittegenstein, whatever)
Especially when operating in the normal science paradigm. radiative physics is a given ( or rather it’s given a secure status owing to a variety of factors, like we design crap that actually works by using modtran etc ) when somebody shows me a paper that claims to contradict it, it’s usually a waste of time to even read it. I can confidently ( with some measure of probablity that I dont need to compute ) just reject it on its face as being wrong.
That’s the tactic at least.

If this paper does get published please let me know – populartechnology (at) gmail (dot) com
I would like to add it to the list,
500 Peer-Reviewed Papers Supporting Skepticism of “Man-Made” Global Warming
Yes it does give the paper more credibility if it is published. No it does not matter if it is published in Nature or Science, there are plenty of reputable climate journals to get it published in.

steven mosher:

..you can go get the results yourself. they are available.
terabytes. Hop over to Lucia’s she works that problem and some of her regulars as well.

Of course, I follow Lucia’s work, it’s excellent.
I’m more about understanding the physics than the statistics. I hope others will perform statistical analysis of the terabytes..
It would be interesting to see some work which covers:
a) analysis of some individual models forecast vs reality for temperature predictions 2001-2010 (rather than ensembles – how good is one model?)
b) analysis of specific models forecast vs reality for other outputs, 2001-2010:
– ocean temps in specific regions
– humidity
– cloud cover
– albedo
– tropopause height in different locations
c) analysis of the “hindcast results” of specific models, 1950-2000:
– regional temps
– ocean temps in specific regions
– humidity
– cloud cover
– albedo
– tropopause height in different locations
And in a journal would be even better but not essential of course.
Now this would be interesting.
Maybe there are papers around which have done this.. (I know about the Douglass and Christy paper), I have been looking at other areas so far.

Is CO2 being measured anywhere besides Mauna Loa? Isn’t it a little disingenuous to extrapolate global CO2 levels from the measurements at a volcano?
According to the USGS (http://hvo.wr.usgs.gov/maunaloa/current/monitoringdata.html), “gathering SO2 and CO2 data while Mauna Loa is quiet is important to establish normal background levels for gases emitted from the volcano.”
If they’re still establishing normal background levels, than any variation so far tells us… what, exactly?
Is there another CO2 monitoring facility at Mauna Loa? I mean, one that’s not intended to monitor volcanic gasses? Please tell me there is.

Some Guy:
Excellent point!

Phil, George,
Firstly, the water cell has very thin windows, made from large microscope cover glasses.
Secondly, a tungsten lamp is a broad band emitter with less than 2% of its energy input transformed into the visible. 48% of its input is transformed into the near IR, the rest comes out as ‘heat’ – longwave IR to well above 5micron. So a 300W tungsten lamp outputs 144W in the near IR, and the water cell was used to isolate this spectral area.
Thirdly, the water absorption spectrum is continuous, from 2E-4 1/cm in the visible through to 5E3 1/cm at 10microns. There are peaks at around 3micron, 2 micron, and 1.5 micron, but they are generally part of what is a logarithmic increase with wavelength, unlike the discrete absorption lines seen with CO2. This spectral response continues over the full longwave range, only dropping by an order of magnitude from 10 micron into what we call the TeraHertz region.
If we clear the measurement of the reflectivity due to the difference of refractive index of the glass, water, and back into air, the difference is only about 10% at normal incidence. I did check for Fabry-Perot resonance, due to the thickness of the cell wall – it was not apparent, and with no water in the cell the ouch! factor was still very significant.
Water cells have been used in microscopy for at least 150 years, to protect valuable objectives from heat radiation. There are now specialist glasses to perform that function, but most of these block out the near IR as well as longwave IR. If ordinary soda glass alone was effective, I am sure that our Victorian ancestors would have made good use of it – but that was the crown glass in their objectives after all. Glass can be used in greenhouses at the relatively low intensity of the transformation from the near IR to longwave IR, however absorptive glass would rapidly perish if you used it alone in front of an intense long-wave IR source. In the above experiment close to 100W of heat was going somewhere – less the reflection and absorption of the bulb envelope – if the glass in the cell absorbed it, the water would boil, if the water absorbed it, it would boil.
Radiation back into space from the heated surface of the planet covers the range 5 – 60microns. What the experiment demonstrates is the huge difference between water, and gases such as CO2. Water vapor is very little different to water in its spectral response, the lower molecular density decreases the effect, and the effect is further diminished at lower pressures, but this also applies to CO2.
What I would like to see is the experimental method used to establish the ‘reflectivity’ of CO2 – it does not seem to be apparent – most sources only state the absorption, as is the case for water. Is this just a theoretical calculation stuffed into a computer model, or is it based on some real science? I would love to find out!

steven mosher (10:34:08) :
Skeptic2: Here I show how sunspots correlate with the temperature data.
Warmist: Your pal said the data was screwed up.
Skeptic2: But, you said it wasn’t.

davidmhoffer,
Yes, seriously. Most models are simplified versions of the shallow water equations developed by a guy who wore a powdered wig and tube socks. The exceptions is MIT’s model which, as I’ve been told, is pure Navier-Stokes equations, which is great except that Navier-Stokes equations are invalid in conditions of evaporation or condensation (ie. the weather).
Fluid flow is a very difficult problem, and weather flows depend on tiny differences which would disappear into the round-off error of an airplane wing plowing along at hundred miles an hour, a flow which itself assigns empirical fudge factors for turbulence.
As one research paper pointed out, the equations used to model fluid flow are reversible, so they’re perfectly happy unmixing a fluid. They can have time flow forward or backward with equal accuracy, which means that, as currently formulated, they ignore effects that maintain important laws of thermodynamics. In short, they ignore entropy, turbulence, and other crucial phenomenon, but do at least provide a passable guess at some short term or large scale behaviors.
So they’re not completely useless, just not accurate and no way to achieve accuracy as currently mathematically formulated.

davidmhoffer (20:13:02) :
I think you’ve taken the term radiative forcing too literally. From wikipedia (not the best source… got it):
“In climate science, radiative forcing is loosely defined as the change in net irradiance at the atmospheric boundary between the troposphere and the stratosphere (the tropopause). Net irradiance is the difference between the incoming radiation energy and the outgoing radiation energy in a given climate system and is measured in Watts per square meter. ”
So AGW is not saying CO2 generates that energy. It’s saying it’s changing the transmission rate of the energy between parts of the atmosphere ie increasing energy storage (something you agree it can do).
This effect of CO2 does not violate thermodynamics. CO2 slows escape of energy, so outgoing radiation is REDUCED by CO2. Since incoming radiation is still constant (relatively), then there is energy buildup in the atmosphere until the incoming/outgoing radiation balances again. More energy in the atmosphere = higher temps.
As a skeptic, I agree with all of this. Where I think AGW went wrong is in calculating the effect. I believe that other atmospheric processes produce a negative feedback, not a positive one as AGW requires.
The idea that CO2 to be an I(2) is an interesting idea. Since the CO2 is not removed from the air, then perhaps it is an effect of the generation of the CO2 and not the CO2 itself. So what is it about burning fossil fuels that would have a temperature effect with a half-life of 1 year? The chemical energy released? The black carbon?
Or maybe the correlation isn’t physical, but socio-economic. I’ll bet the increase in the rate of CO2 emissions is highly correlated with the UHI. Every time we build a building or add a road, increasing UHI, we also increase the rate of CO2 emissions to power the building or fuel the car that drives on the road. That might make urbanization an I(1) variable, proving the temperature record is badly contaminated by UHI.

@Tom P (17:45:14) :
“I’d like to see your results from the whole period of GISTEMP, 1880 to present, and Hadcrut, from 1850. Truncation of a series will tend to hide any I(2) behaviour. Both full series show very similar positive second derivatives.”
Tom, where do Kaufmann et al (2006) state that temperature is not I(1)?
I’ve scrolled through their paper (I didn’t read it carefully, I admit, the baseless hypothesizing was too much to handle while digesting lunch ;), and the ADF stat for GLOBL (the temp seires) is not listed. They do however find that RFAGG is I(1) in Table 1.
They then proceed to estimate a cointegration relationship between GLOBL and RFAGG, which implies that they think that GLOBL is I(1), because otherwise there couldn’t be a cointegration relationship to start with.
Furthermore, in an earlier paper, Kaufmann and Stern (2002), write:
“Consistent with the results of previous research (Woodward and Gray, 1995; Bloomfield and Nychka, 1992; Stern and Kaufmann, 1999), the results in Table 1 show that the temperature data are I(0) or I(1).”
Table 1 in Kaufmann and Stern (2002) furthermore gives the ADF stats for the temperature series NHEM and SHEM.
Northern Hemisphere (test statistic)
Level (don’t reject h0) -2.85.
First difference (reject h0) -11.67
Conclusion: I(1)
Southern Hemisphere (test statistic)
Level (reject h0) -3.55
Conclusion: I(0)
Where the employed significance level is 0.05 (with 0.1 both series would be I(1)). In any case, there seems to be no concrete evidence of temperature being I(2).
I also went on to look through Kaufmann and Stern (2002)’s references, listed above. Note that I had no (free) access to Bloomfield and Nychka (1992), so I didn’t check that one.
Woodward and Grey (1995): In section 6 they reject the H0 that the series is I(0), but for some curious reason they fail to continue for an unit root in the I(1) series.
Kaufmann and Stern (1999): In section 3.3 they perform the univariate unit root tests, with some modifications and conclude that “The KPSS test shows that all the temperature series are I(1),” They furthermore state that these tests were performed on the longest series available.
Finally, I took the data you suggested (CRUTEM3, GISSTEMP, HADCRUT), and performed the tests, I employed the same methodology as earlier (e.g. SIC based lag selection). For all three datasets the conclusion is unambiguous: global temperatures are I(1).
** CRUTEM3, global mean, 1850-2008:
Level series, ADF test statistic (p-value<):
-0.329923 (0.9164)
First difference series, ADF test statistic (p-value<):
-13.06345 (0.0000)
Conclusion: I(1)
** GISSTEMP, global mean, 1881-2008:
Level series, ADF test statistic (p-value<):
-0.168613 (0.6234)
First difference series, ADF test statistic (p-value<):
-11.53925 (0.0000)
Conclusion: I(1)
** HADCRUT, global mean, 1850-2008
Level series, ADF test statistic (p-value<):
-1.061592 (0.2597)
First difference series, ADF test statistic (p-value<):
-11.45482 (0.0000)
Conclusion: I(1)
…
So, can we agree that temperature is I(1)? 🙂
PS. I notice that some people in this thread are taking the results in the paper and then figuring out how to 'fit' a physical model to them. Note that this kind of practice (i.e. data mining) is heavily frowned upon in the econometrics community: you first come up with your hypothesis, and then you test it. That's the only clean way to go about it.

PPPS. Excuse the spam, but the results for that last test should read:
Levels: -0.301710 (0.5752)
First differences: -10.84587 (0.0000)
The conclusion doesn’t change.

Street;
This effect of CO2 does not violate thermodynamics. CO2 slows escape of energy, so outgoing radiation is REDUCED by CO2. Since incoming radiation is still constant (relatively), then there is energy buildup in the atmosphere until the incoming/outgoing radiation balances again. More energy in the atmosphere = higher temps>
1. The outgoing radiation is in fact reduced. TEMPORARILY
2. As you said, there is energy build up until incoming and outgoing balance….which is why the reduced outgoing radiation from CO2 increase is TEMPORARY
3. The process by which the complexities of the system as a whole fluctuate to arrive at a new equilibrium produce oscillations in temperature that are TEMPORARY.
4. When a new equilibrium point is reached, the steady state will be a higher temperature that is a minor increase in comparison to the TEMPORARY oscillations.

davidmhoffer (06:20:11) :
Please keep in mind, I’m just clarifying how the physics works. I disagree with AGW about the magnitude of the effects. I am also not talking about what this paper implies as no one has suggested a physical mechanism by which CO2 would have such a fast effect. I believe it may exist, but we can’t really discuss it until someone figures out what it is…..
“1. The outgoing radiation is in fact reduced. TEMPORARILY”
According to AGW, the reduction persists until the temperature goes up to a level that increases outgoing radition to balance the input. In that sense it is temporary, but the energy storage (temp) of the atmosphere persists as long as the CO2 is there. The physical mechanism for this in AGW is a long-term process.
“2. As you said, there is energy build up until incoming and outgoing balance….which is why the reduced outgoing radiation from CO2 increase is TEMPORARY”
Same as #1.
“3. The process by which the complexities of the system as a whole fluctuate to arrive at a new equilibrium produce oscillations in temperature that are TEMPORARY.”
That statement cannot be evaluated until we know what processes we are talking about. The radiative physics alone would imply the temperature would persist as long as the CO2 persists. With negative feedback, I believe this temp increase would be small, but it would exist. If you talking about the results of this paper, again we don’t know the physical mechanism that results in CO2 being an I(2).
“4. When a new equilibrium point is reached, the steady state will be a higher temperature that is a minor increase in comparison to the TEMPORARY oscillations.”
If your basing that off this paper, then I agree that it may be true. However, without a physical mechanism, all we have are some interesting statistics.

@ grumpy old man (13:43:10)
The humidity theory was a reference to the post by Gary Palmgren (16:15:27) that summarized Miscolczi’s theory as such:
Miskolczi claims that the semitransparent nature of the atmosphere in contact with an essentially infinite source of greenhouse gas in the form of water vapor from the oceans is in a state of dynamic equilibrium. As CO2 increases, a little water vapor rains out to keep the net optical density of the atmosphere constant. Remarkably, radiosonde data shows that the humidity above 300 mb has decreased over the last 50 years as CO2 has gone up. This fact rejects all of the GCMs that assume constant relative humidity (which is, or was, all of them).
@ Some Guy (16:59:14)
@ Brent Hargreaves (03:48:13)
I don’t have the link handy but there was a link here to a report about “lumpy” CO2 distributions detected by one of the NASA satellites – the “lumpy” part was very much overstated (delta was in the neighborhood of 6 or 8 ppm if I remember correctly, definitely within the 10 ppm Brent referenced) – but the average distribution was well in line with the Mauna Loa observations.
So the theory that CO2 is quickly and relatively well distributed through the atmosphere seems to be confirmed, and the Mauna Loa data seems to be a valid representation of atmospheric CO2 levels as a whole

Thank you Nick B. for the humidity info. I wish I understood what the mechanism was for causing the water vapor to decrease when CO2 rises.
Now that I have a dog in this hunt (http://www.2bc3.com/warming.html), I’ll change to my real name Lon Hocker, from my accurate name “grumpy old man”.

Lon Hocker (09:55:45)
Welcome sir! The first rule of Fight Club is you do not talk about Fight Club 😉
A quick note on Miscolczi, the last time I looked at least, the underlying physics for his theory is very complex and there have been allegations made by the RC crowd of fundamental flaws in his approach. Again, AFAIK, these critiques have not been responded to. His theory does seem to match the observed data better than the prevailing consensus approach used in the GCMs, so there very well could be something groundbreaking here. Here’s the WUWT thread on him: http://wattsupwiththat.com/2008/06/26/debate-thread-miskolczi-semi-transparent-atmosphere-model/