UPDATED – see below
Monckton provides these slides for discussion along with commentary related to his recent post on CO2 residence time – Anthony
There is about one molecule of 13C in every 100 molecules of CO2, the great majority being 12C. As CO2 concentration increases, the fraction of 13C in the atmosphere decreases – the alleged smoking gun, fingerprint or signature of anthropogenic emission: for the CO2 added by anthropogenic emissions is leaner in 13C than the atmosphere.
However, anthropogenic CO2 emissions of order 5 Gte yr–1 are two orders of magnitude smaller than natural sources and sinks of order 150 5 Gte yr–1. If some of the natural sources are also leaner in CO2 than the atmosphere, as many are, all bets are off. The decline in atmospheric CO2 may not be of anthropogenic origin after all. In truth, only one component in the CO2 budget is known with any certainty: human emission.
If the natural sources and sinks that represent 96% of the annual CO2 budget change, we do not have the observational capacity to know. However, we do not care, because what is relevant is net emission from all sources and sinks, natural as well as anthropogenic. Net emission is the sum of all sources of CO2 over a given period minus the sum of all CO2 sinks over that period, and is proportional to the growth rate in atmospheric CO2 over the period. The net emission rate controls how quickly global CO2 concentration increases.
CO2 is emitted and absorbed at the surface. In the atmosphere it is inert. It is thus well mixed, but recent observations have shown small variations in concentration, greatest in the unindustrial tropics. Since the variations in CO2 concentration are small, a record from any station will be a good guide to global CO2 concentration. The longest record is from Mauna Loa, dating back to March 1958.
The annual net emission or CO2 increment, a small residual between emissions and absorptions from all sources which averages 1.5 µatm, varies with emission and absorption, sometimes rising >100% against the mean trend, sometimes falling close to zero. Variation in human emission, at only 1 or 2% a year, is thus uncorrelated with changes in net emission, which are independent of it.
Though anthropogenic emissions increase monotonically, natural variations caused by Pinatubo (cooling) and the great el Niño (warming) are visibly stochastic. Annual changes in net CO2 emission (green, above) track surface conditions (blue: temperature and soil moisture together) with a correlation of 0.93 (0.8 for temperature alone), but surface conditions are anti-correlated with δ13C (red: below).
The circulation-dependent naturally-caused component in atmospheric CO2 concentration (blue above), derived solely from temperature and soil moisture changes, coincides with the total CO2 concentration (green). Also, the naturally-caused component in δ13C coincides with observed δ13C (below).
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ADDED (the original MS-Word document sent by Monckton was truncated)
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The naturally-caused component in CO2 (above: satellite temperature record in blue, CRU surface record in gray), here dependent solely on temperature, tracks not only measured but also ice-proxy concentration, though there is a ~10 µatm discrepancy in the ice-proxy era. In the models, projected temperature change (below: blue) responds near-linearly to CO2 concentration change (green).
In the real world, however, there is a poor correlation between stochastically-varying temperature change (above: blue) and monotonically-increasing CO2 concentration change (green). However, the CO2 concentration response to the time-integral of temperature (below: blue dotted line) very closely tracks the measured changes in CO2 concentration, suggesting the possibility that the former may cause the latter.
Summary
Man’s CO2 emissions are two orders of magnitude less than the natural sources and sinks of CO2. Our emissions are not the main driver of temperature change. It is the other way about.
Professor Salby’s opponents say net annual CO2 growth now at ~2 μatm yr–1 is about half of manmade emissions that should have added 4 μatm yr–1 to the air, so that natural sinks must be outweighing natural sources at present, albeit only by 2 μatm yr–1, or little more than 1% of the 150 μatm yr–1 natural CO2 exchanges in the system.
However, Fourier analysis over all sufficiently data-resolved timescales ≥2 years shows that the large variability in the annual net CO2 emission from all sources is heavily dependent upon the time-integral of absolute global mean surface temperature. CO2 concentration change is largely a consequence, not a cause, of natural temperature change.
The sharp Pinatubo-driven cooling of 1991-2 and the sharp Great-el-Nino-driven warming of 1997-8, just six years later, demonstrate the large temperature-dependence of the highly-variable annual increments in CO2 concentration. This stochastic variability is uncorrelated with the near-monotonic increase in anthropogenic CO2 emissions. Absence of correlation necessarily implies absence of causation.
Though correlation between anthropogenic emissions and annual variability in net emissions from all sources is poor, there is a close and inferentially causative correlation between variable surface conditions (chiefly temperature, with a small contribution from soil moisture) and variability in net annual CO2 emission.
Given the substantial variability of net emission and of surface temperature, the small fraction of total annual CO2 exchanges represented by that net emission, and the demonstration that on all relevant timescales the time-integral of temperature change determines CO2 concentration change to a high correlation, a continuing stasis or even a naturally-occurring fall in global mean surface temperature may yet cause net emission to be replaced by net uptake, so that CO2 concentration could cease to increase and might even decline notwithstanding our continuing emissions.
Natural temperature change and variability in soil moisture, not anthropogenic emission, is the chief driver of changes in CO2 concentration. These changes may act as a feedback contributing some warming but are not its principal cause.
“It does, because the long term slope in temperature matches the long term slope in dCO2/dt.”
Bart , see my recent article on Climate Etc about filters
http://judithcurry.com/2013/11/22/data-corruption-by-running-mean-smoothers/
http://www.woodfortrees.org/plot/esrl-co2/derivative/mean:24/mean:18/mean:13/plot/gistemp/from:1959/scale:0.2/offset:0.075/mean:24/mean:18/mean:13
Those of you who remember the story of David slaying Goliath (you can find it in 1 Samuel ch.17) may recall that the Philistines put forward their giant champion to challenge the armies of Israel. None dared take up the challenge save the shepherd boy David. With neither armour nor sword, but just a sling (and five stones) David slays Goliath with just one slingshot (‘…the stone sank into his forehead; and he fell upon his face to the earth’).
Faced as we are with just about every supra-national body, the EU and UN with its IPCC, a host of green NGOs, such as WWF, Friends of the Earth and Greenpeace and other hugely wealthy lobby groups, along with a supposed global consensus of scientific opinion that the burning of fossil fuels is catastrophically changing the climate, we might indeed feel intimidated and fearful to challenge this awesome multi-headed giant.
Here Prof Murry Salby comes to our rescue. With one deadly and precise piece of science he has slain the giant phantom of CACC.
I’m being a bit hyperbolic about the rest of us – I don’t suggest we’ve been fearful of attacking the giant, but I do think Murry’s science is both precise and utterly fatal to the AGW/ACC/CACC giant.
Greg Goodman (November 24, 2013 at 1:40 pm)
> eric: “That is clear from the 1998-99 graph where CO2 is positive and temperature is negative. ”
> that’s because the primary fast relationship is with the derivative. plot d/dt(CO2)
> and it’s in phase and it works.
It works in 1998-99, but not in 1997-98 where the derivative of CO2 is essentially opposite sign from temperature: http://www.woodfortrees.org/plot/esrl-co2/derivative/from:1997/to:1998/scale:0.1/plot/rss/from:1997/to:1998
An why do you expect to compare CO2 to lower tropo ?
SST looks good to me
http://climategrog.wordpress.com/?attachment_id=223
http://climategrog.wordpress.com/?attachment_id=233
What do expect to find? One simple linear regression that fits perfectly and explains all climate since the last deglaciation?
@eric1skeptic: Always good to bring your best argument and not your weakest. Comparing monthly values with a yearly smoothed for Mauna Loa just isn’t good form. As well, using tropospheric temperature is a bit of whoops, especially if discussing anything that relates to ice core data or surface temps and conditions. And, of course, anyone can bust any correlation by taking the timescale low enough that the inherent noise swamps the signal. Better to have a good crack at it with a stronger showing on your part.
Greg Goodman: “see my recent article on Climate Etc about filters”
This cannot be stressed enough. It’s a general concern in climate records generally. And a specific issue in any specific analysis; such as here with Salby.
eric1skeptic says:
November 24, 2013 at 12:34 pm
These are superficial, and misleading, relationships. You have two increasing variables, and you scale them so they are increasing at roughly the same rate. It is a trivial exercise, but it tells you nothing about causation.
What we are talking about here is the fact that the temperature to CO2 relationship is very much of the form
dCO2/dt = k*(T – Teq)
CO2 = atmospheric CO2 concentration
k = coupling factor
T = temperature anomaly w.r.t. its own baseline
Teq = equilibrium temperature w.r.t. that baseline
This relationship indicates that temperature is driving CO2, and that human inputs have little impact. It moreover implies that temperature dependence on CO2 is, at best, negligible. Otherwise, there would be a positive feedback loop and the system would be unstable.
Greg Goodman says:
November 24, 2013 at 1:46 pm
“Bart, see my recent article on Climate Etc about filters”
Not sure if you are taking issue with my statement, or merely pointing out some considerations with regard to filtering. Are you suggesting that the slope is not what it appears to be? I would disagree.
Jquip says:
November 24, 2013 at 2:43 pm
“s well, using tropospheric temperature is a bit of whoops…”
All of the temperature sets are more or less affinely related. It doesn’t really matter which one you choose. For the purposes here, none of the temperature sets likely captures fully and faithfully the true dynamic signal we are looking for. They are all bulk, global averages, and likely miss or smudge out the pertinent signal.
“And a specific issue in any specific analysis; such as here with Salby.”
Perhaps you guys could explicitly state your concern. If you want a smoothed filter output with zero phase everywhere, here is one.
Ferdinand Engelbeen says:
November 24, 2013 at 5:43 am
Greg Goodman says:
>>> Doesn’t CH4 match the ‘plateau’ in temps quite well too?
Hardly:
http://www.aemet.izana.org/images/stories/news/CH4_IZO_1984_2009.pdf
What is that data you posted. Nocturnal CH4 in Madrid ??
Looks nothing like MLO CH4 which is perfectly flat from 1999-2007 (then rises).
Bart, it is true that I scale one variable (CO2) but that’s only so both traces are viewable in a single URL on WFT. Your graph http://www.woodfortrees.org/plot/esrl-co2/derivative/mean:12/from:1979/plot/rss/from:1959/scale:0.19/offset:0.14 that you linked above several times shows a maximum of 4-5 ppm per degree K which you do not dispute. As temperature varies up and down due to weather the CO2 goes up and down about 4-5 ppm per degree K at most in that plot. That means your theory that 1 degree of temperature rise has caused 140 ppm of CO2 rise is incorrect.
The same ratio is clear in my plots except that my plots also show that there is no correlation between the two variables for short term periods, nor any consistent correlation between temperature and the derivative of CO2. For example, here is Jan1997-Jan98: http://www.woodfortrees.org/plot/esrl-co2/derivative/from:1997/to:1998/scale:0.1/plot/rss/from:1997/to:1998 When the temperature rises in the latter half of 1997, the derivative of CO2 goes negative. IOW, the CO2 decreases with a rise in temperature. The temperature series of course has the annual correction built in and CO2 has no smoothing in my plot, but the key point is that in 1998 the opposite is true, that is, the temperature rise correlates with a positive derivative of CO2 in accord with your theory.
You can’t have a theory that includes some years, e.g. 1998, and excludes certain years, e.g. 1997, without a reason to do so (i.e. by adding another variable like a non-temperature side effect of ENSO).
eric1skeptic says:
November 24, 2013 at 3:52 pm
“…shows a maximum of 4-5 ppm per degree K which you do not dispute.”
Of course I dispute it. I dispute the entire premise that CO2 and temperature are affinely related to one another. They aren’t. The rate of change of CO2 is affinely related to temperature anomaly.
You’re not even wrong, because you are not even grasping the argument.
“Your graph http://www.woodfortrees.org/plot/esrl-co2/derivative/mean:12/from:1979/plot/rss/from:1959/scale:0.19/offset:0.14 …”
You do realize that is a graph of the derivative? Are you acquainted with differential calculus?
Dear Greg Goodman,
Re: 11:35pm on 11/23/13
I apologize for my poorly written post (at 11:13am on 11/23) which gave you the mistaken impression that I am more than an enthusiastic fan of Dr. Murry Salby. I had and have nothing to do with his lecture except that I’ve posted it several times on WUWT and watched it and taken notes. I have no way of contacting him. I’m sorry that I cannot help you with that.
Glad to know that, so far anyway, heh, you are not one of the ones (oh, yes, there are several regular skeptic posters and a mod (wince) who do — and those are just the 4 or 5 that I’m aware of, lol — detest and or have utter contempt for me and or my opinions) who find me abhorrent. I’m a firmly anti-AGW skeptic who, since to date no evidence has been provided, firmly believes that CO2 (even less, human CO2) is not a significant cause of climate (or weather, lol).
Sorry to take so long to respond. I glanced at your 11:35pm post about 12 hours ago, but could not bring myself to read what I was sure would be yet another snarl full of bitterness. What a relief to find out that you didn’t talk like that at all. Whew. (I can only take so much of that in 1 week).
Well, Mr. Goodman, guessing from what you have revealed of your personality on WUWT over the past 7 months (that I’ve been here) that this post has been trying your patience for about 10 lines now, I’ll stop.
And leave you …
and also all of you skeptics who DO find me (and or my opinions) detestable:
With this #(:)) — I may be annoying, but…
“You’ve Got a Friend in Me”
(UNLESS you go over the Dark Side… then, watch out,
bwah, ha, ha, ha, haaaaaaaaaaaaaaaa!)
Your WUWT pal (I hope),
Janice
“Don’t over-rate your own importance.” (Greg Goodman at 11:35pm on 11/23)
Thank you for your insightful rebuke. I needed to hear that.
Janice
It has been every bit as interesting a discussion as I had hoped. In particular I should like to pay tribute to the extraordinary, patient persistence of Ferdinand Engelbeen in explaining many points of the underlying science. On any view, his knowledge is profound and he has thought about these questions in detail.
He makes the intriguing statement that the e-folding time of CO2 is simply the total anthropogenic excess against pre-industrial concentration (in round numbers 100 micro-atmospheres) divided by the current annual net increment in CO2 emission, represented by a concentration increase of 2 ppmv/year (or, equivalently, 200 PgC excess divided by 4 PgC/year net emission): thus, 50 years.
It would be helpful if he would be kind enough to answer these questions, which I ask not because I disagree with him (as a layman I do not know) but because his answers will help me to understand.
1. How does he define e-folding time? The e-folding time is the period after which the [excess] concentration is expected to fall to 1/e = 1/2.718 = 37% of its current concentration, but under what conditions? For instance, is he calculating the e-folding time under the assumption that from today no further net CO2 emission occurs? Or that net emission continues at 2 microatmospheres/year?
2. Why is the e-folding time defined in the answer to 1 as simply derived as he derives it? How does the math hang together?
Many thanks.
In q.1 above, I meant to write “the EXCESS concentration is expected to fall to …37% of its current value”. Sorry for the confusion.
For me there is a great deal of confusion in this article. There seem to be several errors and ill-defined terms when it ought to be fairly straightforward and VERY important. It needs some critical reworking.
Thanks for taking it in good spirit, I have a tendency to be a bit direct at times 😉
Monckton of Brenchley says:
“2. Why is the e-folding time defined in the answer to 1 as simply derived as he derives it? How does the math hang together?”
The basics of the flux-rate / time constant relationship is covered in Gosta Pettersson’s papers , which you may have seen already.
http://www.false-alarm.net/author/gosta/
I too would be interested to see exactly how Ferdinand applies this clearly laid out, since I think he has misapplied this in the past. Obviously, if he has applied it correctly it would valuable to have a clear account rather than just a simple declaration of that’s the way it is.
In reply to:
In reply to: Ferdinand Engelbeen says:
November 24, 2013 at 3:05 am
William Astley says:
November 23, 2013 at 6:01 pm
William: Your comments are again nonsense and do not address the scientific problems. You are ignoring the fact as pointed out by Salby that the recent CO2 changes in the atmosphere correlate with the integral of ocean temperature rather than change in anthropogenic CO2 emissions. That is an astonishing unexplained anomaly that requires an explanation. See my comments above. What is the alternative explanation?
There is an overwhelming set of observations/analysis results to support the assertion that Thomas Gold’s deep earth CH4 mechanism/hypothesis is correct. The deep earth CH4 mechanism is directly related to Salby’s observation and is required to explain the variance of CO2 in modern times and throughout the geological record, is required to explain a long list of anomalies related to hydrocarbon deposits on the planet, is required to explain the evolution of the atmosphere in geological time, is required to explain why oceans cover 70% of the planet, and so on. (H2O is dissociated by UV radiation in the upper atmosphere and the H2 is removed by the solar wind. If there was not a constant new source of CH4 release into the atmosphere the earth would be dry and lifeless.)
Light oil deposits, heavy oil deposits, natural gas, and most coal deposits are the result of deep primordial release of CH4 from the earth’s core at it solidifies. The immense pressure at the core enables the CH4 to break the rock of the mantel and migrate up to the surface of the planet. As the CH4 moves through the crust it picks up heavy metals which explains the heavy metals and sulfur in heavy oil, light oils, and in coal.
The CH4 mechanism’s immense pressure and breaking of the mantel rocks provides a path to enable helium (which is of course inert) to move migrate with the CH4 and through the CH4 created paths up into the oil formations. That explains why there is 100 times concentration of helium in the oil formations. There is no physical explanation (with the ridiculous biogenic hypothesis) as to why helium should be concentrated in oil formations.
The ocean surface is saturated with CH4 which indicates there is a significant deep ocean source of CH4. Another clue is the massive methyl hydrate deposits on the ocean floor.
The primordial CH4 is deficient in C13 which explains the astonishing low C13 contain of ‘natural’ gas.
The hydrocarbon deposits are all deficient in C13 however the accumulated carbon deposits from precipitation out of the ancient oceans do not vary in C13 over geological time. That supports the assertion that there is a continual new source of carbon from the deep earth. If there was not, the C13 in the atmosphere and in the carbon deposits would gradually increases due to the immense deposits of deficient C13 in the hydrocarbon deposits. (i.e. If carbon was recycled as required in the late veneer hypothesis then the C13 content of the atmosphere and the deposits would gradually increase.) The deep earth CH4 hypothesis explains the formation of mountains on the planet, the floating of the continents on the mantel crust, and the breakup and evolution of the continents with time.
eric “You can’t have a theory that includes some years, e.g. 1998, and excludes certain years, e.g. 1997, without a reason to do so (i.e. by adding another variable like a non-temperature side effect of ENSO).”
Really, what are you expecting to find in noisy, corrupted and “corrected” data, a perfect mathematical correlation between two variables. Get real.
The “another variable” is noise of data corruption or that global SST average is not a perfect match to the regions that dominate CO2 at MLO. So a strong correlation is an indication of a physical link.
d/dt(CO2) correlates better than CO2 directly even if you lag it. That suggests where the primary relation can be found. It’s clearly not full story.
Bart: “You do realize that is a graph of the derivative? Are you acquainted with differential calculus?”
I graphed the derivative in one of my plots above but also graphed without derivative for clarity. Using the derivative graph, the Y axis units are CO2 per unit time. The highest rate of change is about 0.3 ppm / month. During 1997 CO2 rose 1.6ppm and temperature rose 0.35K for a ratio of 4.6 ppm / K.
The units for that calculation are ppm of CO2 per year divided by degrees K per year which results in ppm per degree K. Having a rise of 4.6 ppm of CO2 per degree K during a good year (1997) shows that it is impossible to achieve 140 ppm for 1 degree K. Furthermore the temperature dropped during 1998 but CO2 still rose which shows that the two are not correlated in the short run.
We also know that CO2 and temperature are not correlated in the short run because weather changes the global average temperature as much as 0.1 or 0.2C in a month. CO2 does not change that rapidly apart from a few very minor fluctuations that are visible using a 12 month moving average.
Another thing to consider is that the global average temperature does not have much meaning when considering CO2 release and uptake. The latter depends on specific conditions at the equator where CO2 is generally released and at the poles where it is generally absorbed. Thus the overall weather patterns will modulate CO2 slightly independent of the seasonal cycle and manmade secular rise.
Greg Goodman (November 25, 2013 at 3:07 am)
> The “another variable” is noise of data corruption or that global SST average is not a perfect
> match to the regions that dominate CO2 at MLO. So a strong correlation is an indication of a
> physical link.
You are correct that global temperature is different from the MLO area where CO2 is being measured in the plots that I linked to. BTW, I did not use global SST in my plots (nor did Bart in his plot) but instead used MSU lower troposphere temperature which has even less physical correlation to the areas in the ocean where CO2 is absorbed and released.
The bottom line however is that the short term (month by month) correlation of CO2 and temperature is very small.
Dear Lord Monckton,
Thanks for your kind words. I am from the old school, where science was teached as a broad field, unlike the current education system where they deliver a lot of specialists to the real world who have enormous knowledge of a very small field and virtually none outside their field…
In the case of CO2, like in many chemical and physical reactions, the atmosphere and other reservoirs (mainly oceans and vegetation) are in continuous exchange with each other. That are dynamic equilibria reactions, where temperature and pressure (difference) are the main players.
Of importance for the calculation of the e-fold decay rate is that the response to an increase of CO2 into the atmosphere is linear, which seems the case:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/temp_co2_acc_1960_cur.jpg
Where the accumulated sinks are the difference between accumulated emissions and accumulation in the atmosphere.
For the year by year accumulation/sink rate:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/dco2_em2.jpg
If we compare the increase in the atmosphere of the first graph with the increase in sink rate of the second graph, there is a slight curvature in both (besides the short term variability caused by temperature variability) which makes that the relationship between them is near-linear.
If the relationship between a disturbance to an equilibrium and its response is linear then:
T = excess / outflow
Because the excess is reduced by the outflow (without further disturbance), the outflow reduces over time with an e-curve. Therefore T gives us the e-fold time for any linear process.
Some theoretical background:
http://en.wikipedia.org/wiki/E_folding
Specific for the decay rate of CO2 in the atmosphere from Peter Dietze at the late John Daly’s web site:
http://www.john-daly.com/carbon.htm
Interesting to see that his calculation from 1997 and the current estimates 15 years later still are quite similar…
Further disturbances, like continuous human emissions have no influence on the e-fold time, but of course both influence how much is retained in the atmosphere. With a small T, most emissions would disappear in short term and the increase in the atmosphere would be modest. With constant emissions, the increase in the atmosphere will assymptote to a new equilibrium, etc…
That doesn’t proof that human emissions are the cause of the increase, but it is a strong indication.
The alternative view from Bart and Salby is that the e-fold time is very short and that some other huge temperature dependent process is involved.
As the human emissions are slightly quadratic increasing as does the increase in the atmosphere, any alternative temperature driven process must give a slightly quadratic CO2 response to temperature (which did more or less linearly increase) and completely parallel human emissions in the same time frame. Such a process thus also must give a 3-fold increase in turnover (a 3-fold decrease in residence time) in the period 1960-current to mimic and dwarf human emissions in the same time frame.
But there are no indications of any increase in turnover in the more recent estimates of the residence time or in changes of the 13C/12C and 14C/12C ratio trends…
” I did not use global SST…”
Since we are discussing whether out-gassing from the oceans is correlated, it would seem obvious to use an SST dataset.
“The bottom line however is that the short term (month by month) correlation of CO2 and temperature is very small.”
I don’t think that conclusion will surprise anyone, which is why most people investigating this relationship remove the annual cycle. This can best be done with successive 12,9 and 7 month running averages which can be done on WTF.org. as I already demonstrated in a link to such a graph.
This was noted years ago and has been repeated by several people including myself and I have linked my plots several times including in this thread.
Knit-picking about any small deviation is irrelevant, you won’t get perfect correlation is this kind of data. It would be helpful to move forward to trying to understand the cause of this relationship.
Greg, my understanding of the cause is simply that ocean temperature modulates CO2 uptake and release. We all agree that there is always uptake and release going on simultaneously in various locations around the globe. With warmth there will be less uptake and more release and with cooling there will be more uptake and less release. Generally high latitudes will have uptake and low latitudes will have release so local weather is important, not just global averages.
The small fluctuations in the CO2 graph (more visible using running averages) that match the temperature graph are a manifestation of the relationship of temperature and CO2.
Looking at these somewhat correlated fluctuations, the only difference between the “anthropogenic CO2” theory and yours is that the A-CO2 theory has significant net uptake of CO2 and yours has net release, but both allow modulation of the rate. In the A-CO2 theory, the rate of uptake will rise and fall with temperature but there will always be net uptake. Thus the A-CO2 theory is coherent with the evidence that you and Bart present.