Guest post by Lance Wallace
The carbon dioxide data from Mauna Loa is widely recognized to be extremely regular and possibly exponential in nature. If it is exponential, we can learn about when it may have started “taking off” from a constant pre-Industrial Revolution background, and can also predict its future behavior. There may also be information in the residuals—are there any cyclic or other variations that can be related to known climatic oscillations like El Niños?
I am sure others have fitted a model to it, but I thought I would do my own fit. Using the latest NOAA monthly seasonally adjusted CO2 dataset running from March 1958 to May 2012 (646 months) I tried fitting a quadratic and an exponential to the data. The quadratic fit gave a slightly better average error (0.46 ppm compared to 0.57 ppm). On the other hand, the exponential fit gave parameters that have more understandable interpretations. Figures 1 and 2 show the quadratic and exponential fits.
Figure 1. Quadratic fit to Mauna Loa monthly observations.
Figure 2. Exponential fit
From the exponential fit, we see that the “start year” for the exponential was 1958-235 = 1723, and that in and before that year the predicted CO2 level was 260 ppm. These values are not far off the estimated level of 280 ppm up until the Industrial Revolution. It might be noted that Newcomen invented his steam engine in 1712, although the start of the Industrial Revolution is generally considered to be later in the century. The e-folding time (for the incremental CO2 levels > 260 ppm) is 59 years, or a half-life of 59 ln 2 = 41 years.
The model predicts CO2 levels in future years as in Figure 3. The doubling from 260 to 520 ppm occurs in the year 2050.
Figure 3. Model predictions from 1722 to 2050.
The departures from the model are interesting in themselves. The residuals from both the quadratic and exponential fits are shown in Figure 4.
Figure 4. Residuals from the quadratic and exponential fits.
Both fits show similar cyclic behavior, with the CO2 levels higher than predicted from about 1958-62 and also 1978-92. More rapid oscillations with smaller amplitudes occur after 2002. There are sharp peaks in 1973 and 1998 (the latter coinciding with the super El Niño.) Whether the oil crisis of 1973 has anything to do with this I can’t say. For persons who know more than I about decadal oscillations these results may be of interest.
The data were taken from the NOAA site at ftp://ftp.cmdl.noaa.gov/ccg/co2/trends/co2_mm_mlo.txt
The nonlinear fits were done using Excel Solver and placing no restrictions on the 3 parameters in each model.
Interesting. Need to check the results of other observatories (the time is shorter), to see weather the deviations are global or local.
The late 1980s show a large departure. It would be interesting to plot these residules against the rates of increase/decrease in global temperature.
The fluctuations appear to fit global temperature fluctuations. This intuitively would make sense because warming sea surface temperatures would cause release of CO2 to the atmosphere, and conversely, as sea surface cools, would increase CO2 absorption into the oceans from the atmosphere.
Because I’m an alround bad guy, I’ll suggest that you could also have fit the data with a scaling distribution, you know, and asymmetrical one with a long tail.
Interesting that it appears the ramp starts kind of when the LIA started petering out. But that couldn’t have anything to do with it…
Shouldn’t we be looking at this sort of data on a logarithmic rather than arithmetic Y-scale?
Hmmm. It cant follow the same formula forever, of course. If it did,it appears we’ll one million parts per million by the year 2540.
I’d suggest fitting a sine curve to it, too.
And another thing which might be interesting to look at is annual cycle. That would require unadjusted data, though. Does annual cycle follow the concentration curve (i.e. does its amplitude grow with concentration) or does it stay constant?
Mauna Loa had better stop spewing out that CO2 crap other wise it will be slapped with a carbon tax, Australia PM gillard will find a way
All this means that CO2-doubling will be completed by 2050 along with
the climate forcing of 3.7 W/m2…… thus earlier than 2100 as given by
AGW…
Which GMT would result in 2050?
The last volcanic eruption of Mauna Loa was in 1984. Prior to that it had erupted quite regularly with 39 eruptions since 1832. Would this be a factor?
Doesn’t the constant emission of volcanic gases from the national park mean that perhaps this was not the best choice of monitoring sites for a gas that is known to be emitted from volcanoes ?
I’m sure they adjust the data to compensate.
If this trend continues……
who would have thought that man’s measly 5%
Joachim Seifert says:
June 2, 2012 at 3:58 pm
Which GMT would result in 2050?
Your guess is as good as anyone’s …
My shot at explaining the residuals is that the dips reflect recessions in the West — the 70s and early 90s. So why isn’t there a dip for 2008+? Ans: China never had a recession.
i would say the response to human emissions would be linear due to the time frame being considered mainly being from an upward slope of temperature rise.
if the natural component due to increasing ocean heat content is considered, then the ‘man made’ portion will be a fraction of the increase. to just draw a line through a complex system smacks of climate science at work.
what happens when the temps fall is the question, not what curve it fits.
Thanks Lance. Keep exploring.
For some detailed CO2 data and analysis with latitude and time see:
Fred H. Haynie, Future of Global Climate Change http://www.kidswincom.net/climate.pdf
And CO2 & OLR
David Stockwell in his Solar Accumulation theory predicts a Pi/2 (90 degree) phase lag for ocean temperature vs solar forcing for the Schwab solar cycle. e.g. 2.75 years for the 11 years solar cycle forcing. See Key evidence for the accumulative model of high solar inuence on global temperature
From that I predicted a similar 3 month (12/4) lag between annual solar forcing and ocean temperature, and thus the CO2 signal. similarly, the Arctic lag should be 6 months displaced from the Antarctic lag in the annual cycle. This appears to be supported by Haynie’s slides 16, 10, 11 and 18/59:
(Note the Antarctic lag is reduced from the solar forcing because of less polar latitude). See also CO2 & Temperature discussion under <a href=http://judithcurry.com/2011/09/15/on-torturing-data/On Torturing the Data
The CO2 lags corresponding with the ocean temperature lags which are predicted from the annual solar forcing and with the Arctic ~6 months different from the Antarctic lag provides strong evidence for solar driven temperature with annual CO2 variations responding to the temperature.
For economic activity vs CO2 see:
Detection of Global Economic Fluctuations in the Atmospheric CO2 Record
Just some guy says:
June 2, 2012 at 3:43 pm
Hmmm. It cant follow the same formula forever, of course. If it did,it appears we’ll one million parts per million by the year 2540.
As well, the oxygen would get too low for life to exist. See
http://www.disclose.tv/forum/atmospheric-oxygen-levels-fall-as-carbon-dioxide-rises-t29534.html
“…we are losing nearly three O2 molecules for each CO2 molecule that accumulates in the air.
“if the oxygen level in such an environment falls below 19.5% it is oxygen deficient, putting occupants of the confined space at risk of losing consciousness and death.”
EVERYBODY PAY ATTENTION!!! THE FOLLOWING IS SUPER IMPORTANT!!!
The concentration of CO2 in the atmosphere as determined at Mauna Loa is valid only for highly-purified, bone dry air which is comprised only of nitrogen, oxygen, the inert gases, and carbon dioxide and which does not occur anywhere in the atmosphere. In real air, there is always water vapor and the concentrations of the gases are lowered in portion to that volume fraction of water vapor.
The use of the concentration of CO2 based upon the data from Mauna Loa is an absolute fatal flaw for all climate model calculations. For fluid dynamic calculations, mass per unit volume should be used.
At STP (273 K and 1 atmosphere pressure), one cubic meter of dry air presently has about 390 mls (390 ppmv) or 17.4 mmoles. If this dry air is heated to ca. 333 K (60 deg C), which slightly higher than max temp every recorded in the desert in Pakistan, the concentration of CO2 is still 390 ppmv but its mass is 14.3 mmoles. If the dry air is cooled 183 K (-90 deg C, lowest temp ever recorded in Antarctica), the concentration of CO2 is still 390 ppmv but its mass is 26 mmoles.
The mass of atmospheric gases in any unit volume of the atmosphere depends upon temperature, pressure and absolute humidity. Weather maps show there is no uniform distribution of temperature, pressure and rel humidity in space and time. Thus there is no unifrom distribution of the greenhouse gases in real air.
The reason the climate scientists say the greenhouse gases are well-mixed is due to the methods of atmospheric gas analysis. In general a sample of local air is filtered to remove particles, dried to remove water, scrubbed to volitile organic compounds, oxides of sulfur and nitrogen, and CFC’s. This procedure produces the highly-purified bone dry air mentioned above.
The composition of the atmosphere of local air from remote locations is fairly uniform thu out the world except for minor variations in the concentration of CO2. However, in locals where there is lots of human activities the concentration of CO2 can vary greatly in space and time suchas during rush hour in major cities or in winter in temperate zones.
All the guys who do atmo. gas analyses know what I have stated above is the absolute truth. But they keep their mouths shut so the climate scientists can make the claim that the greenhouse gases are well-mixed and to avoid vilification. We all know what happened to Ernst Beck after he published he review of atmospheric CO2 gas analyses.
For really good data on the composition and properties of the atmosphere go to:
http://www.uigi.com/air.html
Ya know, these climate science guys really don’t know what they are doing.
I plotted Mauna Loa with tropics temps over at woodfortrees and there is no correlation.
I presume the curve matches the world population curve without much of a residual. Still, the CO2 sinks into the oceans eventually, don’t know how fast that happens.
So strange that the curve follows such a simple mathematical pattern and doesn’t seem correlated to economic activity, world oil consumption, etc. The residual doesn’t seem correlated either. See http://www.indexmundi.com/energy.aspx Oil consumption was dropping in the early 80’s and here the residual is increasing.
The fluctuations in the residual do seem to track the fluctuations in global temperatures though. Makes me wonder if outgassing from the oceans is what’s driving CO2, not fossil fuel use.
I recall reading that the guys on Mauna Loa throw out the “outliers,” when they take CO2 readings. The reasons for throwing out the high CO2 readings involved possible burps of the volcano, and mobs of exhaling tourists in belching busses. However the reasons for throwing out the low readings of CO2 always puzzled me, (and made me a little nervous, because if you throw out enough low readings you can get the reading that “fits” a preconcieved theory.)
My understanding was that the low readings were due to “upslope winds.” Can anyone explain what happens downslope that uses up the CO2? Lush foliage?
http://www.woodfortrees.org/plot/esrl-co2/isolate:60/mean:12/scale:0.2/plot/hadcrut3vgl/isolate:60/mean:12/from:1958
(from http://forum.wetteronline.de/showthread.php?p=181540 )
It looks like the temperature changes are similar to El Nino/La Nina, with CO2 lagging temperature.
From 1948, there seems to have been a steady downward trend in global atmospheric RH. Could this effect Mauna Loa CO2 measurement ?
http://members.shaw.ca/sch25/FOS/GlobalRelativeHumidity300_700mb.jpg
Harold Pierce Jr says:
…For really good data on the composition and properties of the atmosphere go to: http://www.uigi.com/air.html”
Harold, don’t take this the wrong way, but that link leads to some sort of classified ads website.
What I fail to understand is how climate scientists attribute all the increasing CO2 to man… If
– man only contributes (less than) 5% of the total new atmospheric CO2 annually
– the amount of man-made CO2 is increasing faster than most models assumed
– CO2 is the primary cause of warming
– since 1992 (or there-abouts) most global warming is caused by humans
then shouldn’t we see a deviation of some sort from a nice curve? (starting around 1992)
If on the other hand the ocean’s are degassing we would not see such a man-made deviation – it would be too small to measure. Hmm, and that’s what we see…
I think if you take more recent data, you will find the growth starting to approach a more linear rate. The latest number are only accelerating at 0.002 ppm/yr/yr which is very, very, just slightly exponential.
Anything as regular as this data says one of two things.
1. Manmade CO2 pump sitting next to the sensor and never shuts off and is exquisitely tuned to a rythmic increasing beat.
2. Artifact of the “fudge” factor part of the CO2 calculation.
Of these two scenarios, I think #2 has the greater chance of being the culprit. It is exceedingly rare for anything on Earth to be that regular (even if caused by human polution) unless someone fine tuned it to be that regular. It’s like finding a perfectly square rock in the mountains and finding out nature made it. Ain’t gonna happen. Chances are something that regular is wholly artifact. That a person can build a simple model to express the regularity of the signal is revealing, to say the least. Someone have the complete maths sequence for the CO2 calculation?
The Earth has been warming since the LIA, a 500 year stretch of lower temperatures on land and sea surfaces. We have warmed about 1C since 1860 and over 2C since the coldest portion of the LIA – right around 1730. Can anyone calculate how much net CO2 the world’s oceans would outgas with 2C warming of sea surface temperatures. My guess is that amount will account for 90+% of the additional CO2 in our atmosphere. Would make a great research paper.
I’m also willing to guess, if Earth’s temps remain relatively constant for another decade, the rate of increase in CO2 concentration will slow back to 0.7ppm
Bill
Mauna Loa may not be active right now, but the whole of Big Island is volcanic and various parts erupt at different times. Kiluaea is on the windward side and the station is on the lee side of Mauna Loa, I actual saw the station from the saddle road last year. Kiluaea has been erupting non-stop for about 30 years now but volcanos do not have to be erupting to release CO2. I still naively feel that cyclical changes in the CO2 output of this place must be taken into account but they don’t seem to be.
“Interesting that it appears the ramp starts kind of when the LIA started petering out. But that couldn’t have anything to do with it…”
+1
What we know:
There is about 50 times as much CO2 in the oceans as there is in the atmosphere.
Warming water will release CO2 from solution.
The seasonal and short term changes in CO2 correlate well with temperature and lousy with anthro emissions.
Considering only the amount of anthro emissions, the CO2 levels in the atmosphere should be rising faster.
Yet, most scientists don’t seem to even consider the possibility that the rising CO2 levels are due primarily to the long term warming of the earth and oceans since the LIA.
To NZ Willy,
The Arctic Ocean is the big sink that is covered with ice much of the year. When the ice is a minimum, the net sink rate is around 50ppm/year over the cold open water.
Thanks, Lance, this was fun. But there’s not a whole lot of science, here. Using a curve fit for a 56 year period, then extrapolating backwards and forwards is very shaky. There’s no reason to assume that the multiple mechanisms resulting in atmospheric CO2 concentrations are identical at the start and end of the period; thus the exponential, though convenient, is not necessarily valid as a predictor or analytical tool of any sort.
If you have the time, though, you might want to push this a stage further. At a minimum, I’d like to see error bars fore and aft, as well as a correlation coefficient adjusted for autocorrelation. I think you’ll find your 1723 date should be ±200 years. Worse, trying to tie the date of the knuckle of the exponential to any invention is completely unjustified. Natural CO2 variation may likely overwhelm any man made emissions, distorting the actual curve beyond recognition.
NZ Willy says: “I presume the curve matches the world population curve without much of a residual…”
Bad assumption.
just some guy says on June 2, 2012 at 5:57 pm:
Harold Pierce Jr says:
…For really good data on the composition and properties of the atmosphere go to: http://www.uigi.com/air.html”
Harold, don’t take this the wrong way, but that link leads to some sort of classified ads website.
You are right. There is real monkey business going. I called company and left a message. I will call on monday to find out about what is happening. Maybe they don’t know.
I googled: Universal Industrial Gases, Inc. The company name with their main web url comes up and links to all their other sites. If you click on any of these, you are taken to the ad site.
UIGI is really big company. I can’t imagine their webmaster hasn’t found about the “hijacking” of their url.
However, most of industrial customers probably don’t use the links, and use email to contact the company directly.
I note that NOAA are tumpeting a record-breaking 400ppm CO2 in the Arctic http://researchmatters.noaa.gov/news/Pages/arcticCO2.aspx
Harold;
That domain leads nowhere now; uigi.com is a blank screen, all sub-pages included.
“””””…..I am sure others have fitted a model to it, but I thought I would do my own fit. Using the latest NOAA monthly seasonally adjusted CO2 dataset running from March 1958 to May 2012 (646 months) I tried fitting a quadratic and an exponential to the data. The quadratic fit gave a slightly better average error (0.46 ppm compared to 0.57 ppm). On the other hand, the exponential fit gave parameters that have more understandable interpretations. Figures 1 and 2 show the quadratic and exponential fits……”””””
So I didn’t see any conclusion as to whether the Mauna Loa CO2 data best fits an exponential curve or whether a power series curve is a better fit for the 1722 to 2050 data.
Just suppose we could, (well I’m not at all saying this is possible but just for now assume it might be) som how best fit an exponential curve itself to a power series; some generic form; for example,
like exp(x) = ax/1! + bx^2/2! + cx^3/3! + dx^4/4! + ….. you get the idea, where a, b, c, d, etc are arbitrary parameters to be statistically determined from a sequence of values for exp(x), over some useful range of that function.
Now if you used that power series instead of the exponential function, do you think you could get an even beter fit to the Mauna Loa CO2 data ?
It might be interesting to try.
Now what would happen if you used the actual real measured data; like what actually was found at the top of Mauna Loa, instead of some seasonally adjusted substitute ? Was Briffa’s Yamal Christmas tree seasonally adjusted ?
Why did you choose to start your extrapolated prediction; excuse me, that’s projection, from the year 1722. Aren’t you concerned about being accusede of cherry picking, by selecting that year; rather than say 1769; the year that Captain Cook, (re)discovered New Zealand ?
CO2 is a biotic gas and so changes in the biotic affect CO2 and vise versa. If you want to have a gas that is a marker of changes in the temperature of ocean vs. atmosphere than Argon works nicely. Keeling has also looked at the changes in the Ar/N2 ratio at Mauna Loa. I don’t know where the archive for this data is.
Dr Burns says: June 2, 2012 at 5:55 pm
Dr. Burns, I have a couple copies of that chart, but do not know the source, nor what data was used to compile the graph. Do you? Any information would be appreciated. Thanks
Here is a more recent version: http://i48.tinypic.com/2qlfnzn.jpg
Eureqa Formulize, a free program from Cornell Creative Machines Lab is a tool which allows researchers to sift through huge numbers of different curve fitting algorithms. That is, it not only does the curve-fit and regression analysis for one specified formula, it searches for other formulae according to the user’s choices of mathematical form. Well worth a look.
Of course, it should also carry a scientific ‘health warning’ cautioning of the perils of letting yourself be seduced into unwarranted conclusions by the ease of squiggle-matching with a computer.
[Idiots with computers can cause a lot of grief, but most readers of this blog probably don’t need that warning.]
Harold Pierce Jr says:
For fluid dynamic calculations, mass per unit volume should be used.
And from what do you base this rather unusual claim?
I am afraid that the substance of your claim is no more solid than your link.
The projected co2 chart is scary only ‘cuz it assumes unlimited supply of fossil fuels (as in IPCC scenarios). It is rather more reasonable (423-ppm 2029) when adjusted to reflect peak oil, peak gas & peak coal: http://trendlines.ca/free/climatechange/index.htm#fossil
Dear Anthony et al.
Just yesterday I was looking if there would be any news on the discussion of the Essenhigh paper
I found this:
http://www.skepticalscience.com/news.php?n=1259
And would like to direct the interested reader to comments #20 and #26 there.
These two comments kind of summarize in my opinion about the state of the discussion:
Essenhigh came up with a model, which basically removes anthropogenic CO2 from the equation due to its low residence time, the published answer by Cawley uses a very similar model to “reinstate” the anthropogenic CO2, but fails to disprove Essenhighs assumptions and conclussions.
It seems when asked to comment there Essenhigh even said something like “you have your model, I have mine”.
Now here is my question: Is there anywhere a full discussion of the current state of the science? Or perhaps would you be willing to ask Essenhigh or Segalstad to comment on the Cawley paper here at WUWT?
Personally I think this is one of the most important questions, if Essenhigh’s estimates have some merit! (As shown by him and also mentioned in this comment #20 the fact that we produce more anthropogenic CO2 than remains in the atmosphere every year, is not a prove, that this is a cause for anything (due to the low residence times for CO2), especially not since we are still near the end of the little ice age and seeing centuries of high solar activities.
REPLY: I’ll look into this – Anthony
Looks to me like the co2 records got corrupted just like everything else the ipcc get it’s hands on.
Dr. Tim Ball explaining:
http://drtimball.com/2012/pre-industrial-and-current-co2-levels-deliberately-corrupted/
Sorry, your curve fitting is quite meaningless and has no predictive properties whatever. The data would make an equally convincing fit to a sine curve, and many other functions.
This question has been solved. The derivative of CO2 tracks the variation in sea surface temperature remarkably well. Temperature drives CO2. Human inputs are rapidly sequestered and have no significant observable impact.
A simple analogous (not precise in every detail, but able to provide guidance as to physically possible and plausible behavior) system model is as follows:
dC/dt = (Co – C)/tau1 + k1*H
dCo/dt = -Co/tau2 + k2*(T-To)
C = atmospheric CO2 content
H = human input
Co = nominal set point of CO2 in the atmosphere dictated by temperature
tau1 = fast time constant
tau2 = slow time constant
k1, k2 = coupling constants
For tau2 long, dCo/dt becomes approximately equal to the integral of the temperature anomaly with respect to a particular baseline – in effect, you can say that approximately over a relatively short timeline
dCo/dt := k2*(T-To)
With tau1 short, the H input is attenuated to insignificance and C tracks Co tightly. The requirement that C track Co tightly means that tau1 must be short and must attenuate H to a level of insignificance.
Starting here, I show a series of simulations demonstrating this. Use the “Next” button to forward through the plots, the last one at viewing 6 of 29.
The prevailing paradigm simply does not make sense from a stochastic systems point of view – it is essentially self-refuting. A very low bandwidth system, such as it demands, would not be able to have maintained CO2 levels in a tight band during the pre-industrial era and then suddenly started accumulating our inputs. It would have been driven by random events into a random walk with dispersion increasing as the square root of time. I have been aware of this disconnect for some time. When I found the glaringly evident temperature to CO2 derivative relationship, I knew I had found proof. It just does not make any sense otherwise. Temperature drives atmospheric CO2, and human inputs are negligible. Case closed.
The reason for the large variations in the error is because the model is a just a mathematical curve fit and not based on what really controlls the variation of the CO2 increase. I don’t think you can read much into the error for that model except it does not handle anthropogenic and natural variations.
Werner Brozek says:
June 2, 2012 at 5:08 pm
“if the oxygen level in such an environment falls below 19.5% it is oxygen deficient, putting
occupants of the confined space at risk of losing consciousness and death.”
Here is an interesting article on CO2 levels that can be tolerated.
http://www.nap.edu/openbook.php?record_id=12529&page=112
Caleb- Downslope from Mauna Loa are miles of recent lava flows and then miles of rainforest. The Observatory is 11,000 feet high and enjoys pretty steady wind. They throw out readings tainted with vog or low altitude pollutants. Not a perfect observatory but pretty good.
The ML period (1959 – present) is enough to see some interesting correlations.
http://www.esrl.noaa.gov/gmd/webdata/ccgg/trends/co2_data_mlo_anngr.pdf
The annual growth in atmospheric CO2 correlates very well with the SST ‘anomaly’ and other global temperature indices. The correlation would be even better with the corresponding latitude band SST anomaly. Annual cycle is caused by the annual temperature cycle.
http://2.bp.blogspot.com/-AoUzuwoFQyA/T29AMKmFP7I/AAAAAAAABB8/O58gpDrQ-r4/s1600/co2_sst.gif
Interestingly, according to the dCO2 vs T correlation, it doesn’t take warming to rise the atmospheric CO2 – a sufficiently high constant temperature will cause rising CO2 (dCO2 = const). At some sufficiently low temperature CO2 will stop rising (dCO2 = 0). I once compared HADCRUT3 and ML dCO2 and got:
dCO2 = 2*Ta + 1.2 (R2 ~ 0.6).
Ta = 0.4, dCO2 = 2 ppm/years (like in this decade)
Ta = 0.0, dCO2 = 1.2 ppm/year (like in the ~70s)
If the correlation holds and global temperatures decline, dCO2 will decline too.
I agree with Tim Ball here, that Jaworowski is crucial, and has been brutally trashed by CAGW rednecks for his temerity in challenging the corruption of the science. I personally tend to leave Beck aside as though I regard his evidence as very important, it involves too many distracting issues. I did a whole page on the CO2 issue way back in 2009 and it is still relevant as ever.
People simply forget Henry’s Law, the titanic outgassing ability of the oceans in the tropics, and the ability of plants to suck in any spare CO2 – as the recent greening of the Sahel shows. These factors are what I believe the good Ferdinand Engelbeen fails to appreciate. And many others. The above “fit” is indeed seductive. But push the boundaries and the fit breaks down.
Now think. CO2 lags temperature by 800 years, according to Caillon et al. What happened 800 years ago?? Anyone?? And what cycle takes 800 years to happen?? Anyone??
Again the same discussions com up every few months…
To begin with: The Mauno Loa and other stations CO2 data are as solid as one can have on this earth. Indeed some of the raw data are discarded (still available, but not used for daily to yearly aveages), because they are influenced by downwind conditions from the nearby volvanic vents or by afternoon upwind conditions, which brings up slightly depleted by vegetation CO2 levels from the valey. Both give raw values which are +/- 4 ppmv around the “background” seasonally variable levels. Including or excluding these outliers for averaging doesn’t influence the yearly average or trends for more than 0.1 ppmv. The Mauna Loa “extremes” don’t exist at the South Pole, where the first continuous measurements ever were made, but they have more mechanical problems in the harsh conditions there. For an impression of the raw data vs. the “cleaned” averages at Mauna Loa and the South Pole see:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/co2_mlo_spo_raw_select_2008.jpg
take into consideration the blown up scale of CO2!
The raw data of 4 stations can be found at:
ftp://ftp.cmdl.noaa.gov/ccg/co2/in-situ/
The rules for exclusion of data and the calibration procedure at Mauna Loa can be found at:
http://www.esrl.noaa.gov/gmd/ccgg/about/co2_measurements.html
Pieter Tans of NOAA has been very cooperative in the past and sent a few days of raw instrument voltage data on simple request, so I could check the calculation procedure which is used to get the raw CO2 data. No problems found.
So far so good for that part.
Then the cause of the increase.
– The oceans are not the cause:
Pure on solubility parameters, an increase of 1°C causes an increase of 16 microatm of CO2 in the oceans surface waters, thus back into dynamic equilibrium causes an increase of about 16 ppmv in the atmosphere. It doesn’t matter how much CO2 is in the oceans, only the extra pressure matters. Take a 0.5 or 1 or 1.5 liter bottle of coke and shake that, the pressure in the above space will get the same. Regardless of the triple amount in the larger bottle, if for the amount that is lost from the liquid into the atmosphere. Amounts are hardly important, the pressure (difference) is.
But an increase in temperature also increases the uptake by vegetation. The net result over very long periods is that an increase of 1°C in ocean temperature gives some 8 ppmv increase in CO2. Thus the ~1°C warming since the LIA gives at maximum 8 ppmv increase of CO2. But we see an increase of over 100 ppmv since the start of the industrial revolution…
Moreover, an extra amount of CO2 from the oceans would increase the 13C/12C ratio of CO2 in the atmosphere, but we see a continuous decrease.
– vegetation is not the cause:
In principle, if there was more vegetation decay than growth, that would increase the total amount of CO2 and give the same 13C/12C decline as observed. But one can deduce the biological balance from the oxygen balance: some less oxygen is used as calculated from fossil fuel use. Thus vegetation is a net oxygen producer, dus a net CO2 absorber.
Oh by the way, a simple formula to calculate the CO2 levels at any moment in the future (or past);
CO2(new) = CO2(old) + 0.55xCO2(emiss) + 4xdT
all in ppmv
That explains the trend and the temperature dependent variability…
The human body consists of 70% O2.
0.7* 7,000,000,000 * 170lb = 833,000,000,000,000lb of O2 bound up in the human population of the planet. As the population grows we use up more of the O2 in the atmosphere.
170lb is just my guess for the average weight of us humans.
That’s just humans. All biomass contains O2.
Unfortunately as a number of commentators have pointed out, the predictive part of the curve assumes unlimited and increasing change.
Now if humans are the cause then there will ultimately be a point when the rate of increase in fuel consumption slows. Personally I doubt this because the curve is far too even to be of anthropogenic origin. Consider this for example, when this curve started most of europe used open fire coal heating, through a series of clean air legislation this changed until ultimately most people were using gas. Equally 1958 was the year that the Ford Edsel came out. Since then cars world- wide have become increasingly more fuel efficient. I would think that these changes would have some impact if humanity was the cause, but no apparently not.
If the cause is a natural cycle then it will end, when it ends.
Laws of Nature says:
June 3, 2012 at 12:21 am
Just yesterday I was looking if there would be any news on the discussion of the Essenhigh paper
I found this:
http://www.skepticalscience.com/news.php?n=1259
The Essenhigh paper was fully responded to in another article in Energy & Fuels by Dr. Gavin Cawley:
“On the Atmospheric Residence Time of Anthropogenically Sourced Carbon Dioxide”
See: http://pubs.acs.org/doi/abs/10.1021/ef200914u
The essence of the error by Essenhigh (and many others) is that he uses the residence time of human CO2 in the atmosphere, which is short, but that doesn’t tell us anything about how long it takes for an injection of an extra amount of CO2 (whatever its source) to bring the whole cycle back into dynamic equilibrium (the “adjustment” time)… It is the same as the throughput of goods and thus capital in a factory (which can be huge) and the financial gain of the same factory, which can be positive, zero or negative, whatever the throughput is.
For some reason, it seems to be very difficult to see the difference between the residence time and the adjustment time, even by very knowledged people…
I don’t see how you can get an exponential growth from a cyclic process using a limited product.
Harold Pierce Jr says:
June 2, 2012 at 5:21 pm
What you write is true, but completely unimportant for the distribution of CO2 and other gases. The only reason that the air is made bone dry for CO2 analyses is that water vapour interferes with the CO2 measurements. As water vapour is extremely variable in any direction, counting CO2 as in dry air makes a comparison of CO2 levels in different altitudes and latitudes far more easy.
The only place where the difference between dry and wet air is important is for the CO2 exchange between oceans (and plant alveoles) and atmosphere. In that case, the pCO2 in the atmosphere is used, thus taking into account the water vapour. The difference between ppmv and pCO2 assumes full water vapour saturation, but even then is quite small.
Bart really has this thing figured out.
Pamela Gray says:
June 2, 2012 at 6:08 pm
Anything as regular as this data says one of two things.
1. Manmade CO2 pump sitting next to the sensor and never shuts off and is exquisitely tuned to a rythmic increasing beat.
2. Artifact of the “fudge” factor part of the CO2 calculation.
Neither. In fact, the regularity indicates that no natural process is responsible for the increase. The regularity is caused by the regularity of the human emissions:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/temp_emiss_increase.jpg
Even in times of economical crisis, the emissions hardly change and in general show a steady increase over time, which results in a near constant increasing increase of what resides in the atmosphere. The year by year variability in atmospheric increase rate is caused by temperature swings, but that largely cancels out over time.
Keith Battye says:
June 3, 2012 at 3:16 am
Bart really has this thing figured out.
Bart is a very good theoretician, but he makes an essential error: he only looks at the inputs. That makes that the human input is only a fraction of the total input and simply disappears in the cycle. And error many here seems to make. But as is proven in the mass balance: the natural sinks are larger than the natural sources, at least over the past 50+ years. Thus it doesn’t make any difference what the height of the natural input is, or what its trend or variancy is, as the only point that counts is the difference between natural inputs and outputs, which is negative all over the years and the human input is the only source of the increase in the atmosphere. That doesn’t need a fast response from the natural sinks. The observed sink rate is about 40 years half life time…
Ferdinand,
I would greatly appreciate it, if you would do a peer review of http://www.retiredresearcher.wordpress.com and let me know where I may have made errors in my analysis. I agree with you that the CO2 data is our best source for following climate change. However, it is a lagging indicator. The effects of anthropogenic emissions on background levels as reported as monthly averages shows up about 10 years after they have been originally put into the air. These effects are added to always changing natural cycles that are indicated by the ice core and other proxie data. You can comment here or on my blog as you wish. Also, you can click on my name and then click on the URL there. I welcome others to do the same.
edim says:
June 3, 2012 at 1:51 am
Interestingly, according to the dCO2 vs T correlation, it doesn’t take warming to rise the atmospheric CO2 – a sufficiently high constant temperature will cause rising CO2 (dCO2 = const).
There is a fundamental problem here: your formula assumes that the CO2 level continuous to rise with a constant elevated temperature, but that can’t be true. The main source in the past were the oceans. These emit CO2 with rising temperatures until a new equilibrium is reached, that is when the pCO2 of the ocean surface and the pCO2 in the atmosphere are in average equal (thus as much CO2 is absorbed as is released).
So there is an increase if the temperature increases, but limited to at maximum the new equilibrium. which in the past was about 8 ppmv/°C (MWP-LIA, glacials-interglacials), on short term that gives about 4 ppmv/°C of variability around the trend.
Ferdinand, no one’s claiming that the natural environment is a net source of CO2, it’s obvious that the annual growth is smaller than the anthropogenic input, so the environment has been a net sink. The claim is that the growth in atmospheric CO2 is determined by global temperature. What do you think would have happened with CO2 if the temparatures haven’t increased since ~1960s? According to the correlation, the growth would be in average let’s say ~0.9 ppm/year instead of 1.45 ppm/year and the total accumulation until now would be ~45 ppm instead of ~80 ppm. So, we would be at ~360 ppm instead of 395 ppm.
Total accumulation is dependent on the average temperature during the period of accumulation. That’s the observed behaviour.
>>Steve Keohane says:
>>June 2, 2012 at 10:20 pm
>> … but do not know the source …
http://www.esrl.noaa.gov/psd/cgi-bin/data/timeseries/timeseries1.pl
Steve McIntyre and Roy Spencer have papers discussing the effects and how the trends differ from IPCC model assumptions.
>> Ferdinand Engelbeen says:
“Again the same discussions com up every few months…”
Well, this tends to happen if someone decides basically mid-sentence to remove himself from the discussion! The topic doesnt go away by itself
>> FerdiEgb says:
“The essence of the error by Essenhigh (and many others) is that he uses the residence time of human CO2 in the atmosphere,”
These numbers are known well enough, so Essenhigh and Barts choice are reasonable and not in “error”. What is missing from your side is any prove that they did anything wrong!
In what way does Essenhighs or Barts choices contradict not your believe, but a value measured in nature?
“Bart is a very good theoretician, but he makes an essential error: he only looks at the inputs. That makes that the human input is only a fraction of the total input and simply disappears in the cycle. And error many here seems to make. But as is proven in the mass balance: the natural sinks are larger than the natural sources, at least over the past 50+ years.”
Wow, a full circle again.. perhaps time to read again, what I wrote yesterday:
Laws of Nature says:
“Essenhigh came up with a model, which basically removes anthropogenic CO2 from the equation due to its low residence time, the published answer by Cawley uses a very similar model to “reinstate” the anthropogenic CO2, but fails to disprove Essenhighs assumptions and conclussions.”
The very reason Essenhigh published his paper was to show that there is indeed another possible solution, taking realistic parameters.
Just you saying its wrong doesnt prove it wrong, I sense a lack of arguments!
Ferdinand Engelbeen says:
“But one can deduce the biological balance from the oxygen balance:”
Here you seem to ignore soil bacteria and the whole NOx-circle.
Ferdinand Engelbeen says:
“The oceans are not the cause:
“Pure on solubility parameters, an increase of 1°C causes an increase of 16 microatm of CO2 in the oceans surface waters, thus back into dynamic equilibrium causes an increase of about 16 ppmv in the atmosphere.”
Over at http://www.seafriends.org.nz/issues/global/acid2.htm#why_problem we can read the following statement:
“The oceans contain far more CO2 than air: 38,000Gt versus 700 Gt (about 50 times). A slight warming of the ocean expels CO2 while becoming more acidic, about 1000-1500Gt per degree C (see graph in part 1 => http://www.seafriends.org.nz/issues/global/global16.gif ) .”
Would you agree to that?
Bart says:
“dC/dt = (Co – C)/tau1 + k1*H
dCo/dt = -Co/tau2 + k2*(T-To)”
It would be interesting if you could change the constants to either support Essenhigh’s or Cawley’s conclussions. And then compare them
All the best regards,
LoN
edim says:
June 3, 2012 at 4:17 am
The claim is that the growth in atmospheric CO2 is determined by global temperature. What do you think would have happened with CO2 if the temparatures haven’t increased since ~1960s? According to the correlation, the growth would be in average let’s say ~0.9 ppm/year instead of 1.45 ppm/year and the total accumulation until now would be ~45 ppm instead of ~80 ppm. So, we would be at ~360 ppm instead of 395 ppm.
You still make the assumption that the growth rate remains the same at a constant (increased or decreased) temperature.
As the seawater temperature changes up and down year by year, it is hard to see that the CO2 growth rate is temperature change related and not absolute temperature related, there are no multi-year periods with a near constant temperature…
If you start at constant 1 ppmv/yr at e.g. 15°C global average sea surface temperature and the next year there is a 0.1°C increase, that would give an increase in the growth rate to ~1.4 ppmv for that second year. The third year there is no further seawater temperature increase, so the CO2 increase rate falls back to ~1 ppmv/year. The influence of seawater surface temperature is short (~1.5 years) to bring the ocean surface layer and the atmosphere in equilibrium for CO2 levels.
The increase in (ocean) temperature since the LIA is at maximum 1°C, good for maximum 8 ppmv extra over that full period, that’s all.
Bart says:
June 3, 2012 at 1:21 am
I know, we have been there many times… but…
When I found the glaringly evident temperature to CO2 derivative relationship, I knew I had found proof.
Except that any relationship in the derivatives has zero predictive power for any releationship in the original variables…
Dr Burns says: June 3, 2012 at 4:37 am
Thank you sir! I was taking flak from joelshore on another thread for posting that without providence. I see implications regarding enthalpy.
Just noting that the AIRS satellite has a number of videos for mid-tropospheric CO2 concentrations covering 6 or 7 years now.
Just search “Airs CO2” on Google video.
(they are mainly Youtube products so putting up a direct link would imbed the video in the thread and I don’t think that is necessary).
You will see there is considerable variability and it is entirely possible that someone might measure 500 ppm in Europe or some locality every few days. The numbers have to be averaged out over long periods and there will always be outliers. The Arctic has a strong outburst in the winter months as one of the videos is a polar view.
Also search for “Airs Methane”. With all the Arctic methane bubbles stories going around, it is helpful to see that the actual global data shows Methane comes from everywhere and cycles around the planet extremely fast with the prevailing winds.
How does the CO2 data fit a bell curve with the current rise the left side of the bell? Once oil production goes into terminal decline, CO2 increases should slow, then level off, then drop.
Wow, it seems that I have missed the Salby discussions of April 19 on -again- the same topic… Had a nice trip in Western Australia in the past 5 weeks (Perth to Darwin), should have contacted Dr. Salby, but I suppose he was somewhere at the other side of that (large, did drive over 7000 km…) continent.
Continued (near) exponential growth is a physical impossibility, since fossil fuel resources are finite. The rate of growth in use will fall as price drives conservation and substitution. If one believes the “peak petroleum” predictions, liquid fuels growth will turn negative within a decade or so. Coal and natural gas are more complicated, but these too must eventually stop increasing. From a practical standpoint (say 25 – 30 years horizon), it makes little difference what the historical record says; atmospheric CO2 will continue to increase between about 2.5 and 3 PPM per year.
jrwakefield says:
June 3, 2012 at 6:38 am
Nah, I think all that is just religious crap. Mankind is to blame, repent, and all that.
Have a look at what Prof. Salsby has to say about it;
Bart says: June 3, 2012 at 1:21 am
This question has been solved. The derivative of CO2 tracks the variation in sea surface temperature remarkably well. Temperature drives CO2. Human inputs are rapidly sequestered and have no significant observable impact.
________
Probably true.
I discovered this dCO2/dt relationship with temperature in late Dec2007 and published in Jan2008. And the CO2 signal lags temperature by ~9 months. See
http://icecap.us/index.php/go/joes-blog/carbon_dioxide_in_not_the_primary_cause_of_global_warming_the_future_can_no/
Murry Salby came to the same conclusion in his 2011 video at
The warmists arm-waive that this relationship and resulting lag is a “feedback effect”.
But there is also a CO2-after-temperature lag of ~800 years in the ice core record on a longer time cycle, probably related to deep ocean phenomena.
And there are probably other intermediate cycles as well.
And of course there is the seasonal CO2 “sawtooth”, apparently dominated by the larger Northern Hemisphere land mass.
My hypothesis is that these natural cycles all contribute to the resulting CO2 curve, which is more likely to be a ~sine curve than the subject ~exponential curve.
Natural CO2 flux is much greater than the humanmade component. Furthermore, I have sought and found no human component in the CO2 signal. The increase in atmospheric CO2 appears to be entirely, or almost entirely natural.
P.S.
Apologies for the sentence fragments, … and starting three sentences with “and”. But there are worse sins, like squandering a trillion dollars on global warming nonsense.
I also predicted global cooling in an article written in 2002. If this cooling is severe enough to affect the grain harvest, we will look back on current days with great fondness. Hope I’m wrong, but just in case: Bundle up.
Laws of Nature says:
June 3, 2012 at 4:58 am
As I said, it seems very difficult to see the difference between the residence time of human CO2 in the atmosphere and what happens to any injection of extra CO2 into the same atmosphere…
1. The residence time;
Every year, some 20% of all CO2 in the atmosphere is exchanged with CO2 from/to other reservoirs. Thus if human input ceased, the remaining human CO2 molecules should reduce by about 20% per year (as is seen in the 14C record). That gives a residence time of slightly above 5 years. But be aware: this exchange doesn’t change the total amount of CO2 in the atmosphere. as long as there is balance between inputs and outputs.
2. The adjustment time:
If we may assume that temperature (as seen in the past) is the main driver for CO2 levels, then at a certain temperature, there is a given “normal” CO2 level. Any extra amount of CO2 (whatever its source) above that level would be removed until the equilibrium is reached again. Currently we have a level of 100 ppmv CO2 above the temperature dictated setpoint. That is the driving force which moves extra CO2 into the oceans an plants. This causes an unbalance in the natural inputs and outputs: some 4 GtC (2 ppmv) more CO2 is absorbed by nature than is released. If we should stop to emit any CO2, the 100 ppmv difference would be the same at the start, 98 ppmv next year, 96.2 ppmv, etc… until back to the temperature equilibrium. The adjustment e-fold time therefore is 210/4 or ~53 years, quite a difference with the residence time.
The problem now is that many use the residence time to show that the human contribution is negligible, but that only shows how fast the human CO2 molecules are replaced by natural molecules, but that is completely irrelevant of what happens to the total amount in the atmosphere, which still is (near) completely caused by the human addition.
To illustrate that, here a graph of what happens if humans should have added all emissions to data at once some 160 years ago:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/fract_level_pulse.jpg
All “human” CO2 is gone in about 60 years, while CO2 levels remain higher even after 160 years. The extra level above the old equilibrium still is caused by the initial human injection, even if no single human CO2 molecule is left…
Ferdinand Engelbeen says:
“But one can deduce the biological balance from the oxygen balance:”
Here you seem to ignore soil bacteria and the whole NOx-circle.
soil bacteria are included in the oxygen balance (they use O2 to produce CO2). NOx is not, but how much does that change the oxygen balance?
A slight warming of the ocean expels CO2 while becoming more acidic, about 1000-1500Gt per degree C
I fear that the NZ coalition is completely wrong here: expelling CO2 from the oceans makes the oceans more alkaline, which is not observed and the DIC (totally dissolved inorganic carbon) content of the ocean surface is increasing, thus these are absorbing more CO2… Moreover as said previously, it doesn’t make any difference how much CO2 is in the oceans, only the CO2 pressure difference between the atmosphere and the oceans matters. If the oceans heat up 1°C, that gives at maximum 16 ppmv extra in the atmosphere, no matter how much resides in the oceans.
Hi Ferdinand,
I hope you are well.
For the record, I have no problem with CO2 measurement accuracy. The CO2 measurements at Barrow, Mauna Loa, the South Pole and many other sites correlate well and make sense.
Also, we don’t need to discuss yet again your “mass balance” argument – I will leave that to you and Richard C. I agree with Richard – the system just does not work the way you say it does.
Humanmade CO2 emissions are very small compared with natural CO2 flux, which is not only huge on a seasonal basis, but also huge on a daily basis.
I would really like you to be correct, because if you were, humanity would survive better than under my most probable scenario, which is moderate or severe global cooling.
The only impact I can see of humanmade CO2 emissions is that we are making little flowers happy.
To counter the wild claims of the global warming alarmists, I leave all of you with this note from George Carlin, and wish you a very pleasant Sunday. 🙂
Regards, Allan
Warning: Language.
George Carlin – The Planet is Fine !
edim says:
June 3, 2012 at 1:51 am
“…a sufficiently high constant temperature will cause rising CO2…”
I think it is likely that what we are seeing is that the end of the LIA forced a new equilibirum level for temperature which has not yet settled out, and for which humankind bears no responsibility. When it settles, or reverses, we will see CO2 levels level follow. Judging by the numbers, I expect that will be a long time yet.
FerdiEgb says:
June 3, 2012 at 3:49 am
“But as is proven in the mass balance…”
My system analogy above produces the same mass balance. I have explained to you many times why your mass balance argument is faulty.
Laws of Nature says:
June 3, 2012 at 4:58 am
“It would be interesting if you could change the constants to either support Essenhigh’s or Cawley’s conclussions”
The important one which cannot be changed is tau1. That sets the bandwidth of the system. A wide bandwidth system maintains its equilibrium point tightly, with low sensitivity to disturbances. That is what we see in the data – the (quasi-)equilibrium point, which is proportional to the integral of temperature anomaly, is tightly tracked. That demands a wide bandwidth system, which in turn demands low sensitivity to human inputs. Whatever the actual form of the system, however it may deviate from my simple analogy, the dynamics must add up to the same thing: the equlibirum dynamics are very low bandwidth, so that the CO2 level is effectively the integral of temperature anomaly in the “near” term (relative to tau2) when there has been a change of state, and the regulator dynamics are very high bandwidth, so that the CO2 tightly tracks that integral, and human inputs are quickly sequestered and have little effect on the overall level.
FerdiEgb says:
June 3, 2012 at 5:43 am
It’s all right here. The CO2 level is effectively the double integral of temperature anomaly with respect to the proper baseline. These plots were made using GISS LOTI, before Werner Brozek and others pointed out that there is a better match, which is theoretically reasonable, to SST.
FerdiEgb says:
June 3, 2012 at 5:54 am
“Except that any relationship in the derivatives has zero predictive power for any releationship in the original variables…”
We do not need to “predict” it since it is in the past, and can be inferred. I’ve had intense arguments with others who insist this is a weak point in my argument, but there really isn’t any alternative when the bandwidth of the system is observably so wide. It is the excellent tracking of the temperature anomaly in the CO2 derivative which demands that the bandwidth must be wide (short sequestration time). And, wide bandwidth constrains the effect of human emissions to be small.
Allan MacRae says:
June 3, 2012 at 8:19 am
Sorry, Allan, I should be giving you credit. I only do this as a hobby, and I forget the names of the people I have interacted with more than a few weeks ago.
From above: “The CO2 level is effectively the double integral of temperature anomaly with respect to the proper baseline.” My brain skipped a grove, it’s just the single integral.
The exponential model presented here has no coefficient that multiplies the exponential, and therefore, implies that this coefficient is 1.0ppm, and is a constant in the model–not determined by data at all. This seems extremely unlikely. Is this a typo?
The observed data are all contained within one e-folding time far along in the time series, So the coefficients are correlated to one another and not well determined.
BIll Illis:
Yep part of the state of the art in Keeling’s measurement was in picking sites where the diurnal variation in CO2 was minimized. If anybody is really interested, they should go back to the decade or so of measurements that Keeling took before he established the Mauna Loa observatory.
On another note, one should look at the ratio of C14 to C12 in the CO2 in the atmosphere. If it’s coming from fossil fuel burning, the ratio should increase. If it’s inorganic CO2, it should stay constant. EM Smith noted that the increase in CO2 corresponded to the end of the LIA. Well, since CO2 is thought to act as a GHG, does that suggest an idea for how they might be linked?
This is one of my favorite graphics. It shows that the Northern hemisphere (where most of the trees are) shows the largest annual variation in CO2, and the south pole (where there are very few trees ;-)), shows almost no variation.
If this is all faked, they thought of everything. Maybe people need to consider their sources a bit more carefully, and if somebody consistently is making outlandish claims, consider writing them off as a nut.
Just saying.
Steve Keohane says:
June 2, 2012 at 10:20 pm
I created the graph. It is in the “Water Vapour Feedback” section of my “Climate Change Science essay at
http://www.friendsofscience.org/assets/documents/FOS%20Essay/Climate_Change_Science.html#Water_vapour
A link to the NOAA data source is given just above the graph. To recreate the graph use Variable “Relative Humidity”, select “Seasonal average”, First month of season “Jan”, second month “Dec”. Select “Area weight grids”. You can select “analysis level” from 1000 mb to 300 mb.
A proper regression model provides residual plots that have a random pattern with mean zero. Due to the obvious pattern here, this residual plot indicates some key variable(s) is omitted or the modeling challenges of a nonlinear fit were not overcome. Seems like some basic transformations and an attempt to use a linear model is in order.
Sorry this is a misstatement on my part:
The ratio should decrease because fossil fuels have very low ratios of C14 to C12. If the CO2 is coming from the ocean the ratio of C14/C12 should stay approximately constant.
Here’s a more complete explanation lifted from another source:
I think it’s also important to emphasize that on decadal-scales there is substantial variation in the variation of ocean temperatures, and certainly you can expect CO2 to come in and out of dissolution as natural fluctuations in ocean temperatures result in CO2 releases into and absorption from the atmosphere. Thus one can get changes of C13/C12 that don’t follow the basic long-term patterns expected, because other physical processes play a more dominant role on those time scales.
No worries Bart,
I am a hobbyist as well, and NOT “trying to get on full time” in the climate science business – it is a fascinating subject, but the quality of debate is too often degraded.
The problem with too many of the climate “full-timers” is that they are drinking each-others’ bath water, and the result is the current lamentable state of climate science and its dogmatic and repressive intellectual environment.
The irony is that BOTH sides of the rancorous “mainstream climate debate” , which is basically an argument about H20 feedbacks and ‘sensitivity” to CO2, probably have “the cart before the horse” – in fact, the primary cause is increasing temperature over past centuries, and increasing atmospheric CO2 is the result.
This would all be quite funny, except that a trillion dollars has been squandered on CAGW nonsense.
Intelligent use of these scarce global resources would have easily saved as many people as died in Hitler’s WW2, or Stalin’s purges, or Mao’ s Great Leap Backward.
On my bleaker days, I must conclude that we are governed by scoundrels and imbeciles.
“The increase in (ocean) temperature since the LIA is at maximum 1°C, good for maximum 8 ppmv extra over that full period, that’s all.”
Maybe so for a static unit of water.
But how about constant upwelling of fresh water from depth being exposed to solar shortwave which has increased beyond the increase in raw TSI at top of atmosphere as a result of decreasing global cloudiness during the warming spell ?
Just as observed during the late 20th century.
And then suppose, too, that the upwelling water is not as cold as it was due to warmth injected into the depths during the MWP and only now returning to the surface.
Both those factors would reduce ocean surface absorption of atmospheric CO2 allowing it to build up in the air.
The observed large proportionate change in CO2 ppm is not reflected well in ice cores but then we don’t really know whether the ice core record is sensitive enough to record multicentennial variations in atmospheric CO2 in full detail..
Plant stomata are more sensitive and do indeed record greater variability in CO2 than ice cores but even they may be too coarse for a full representaion of actual multicentennial CO2 variability.
The isotope argument used to be invoked to justify ignoring such matters but new data is weakening that and I don’t hear it much these days. There are plenty of natural sources of CO2 showing the same isotope ratios as human emissions.
“This is one of my favorite graphics. It shows that the Northern hemisphere (where most of the trees are) shows the largest annual variation in CO2, and the south pole (where there are very few trees ;-)), shows almost no variation.”
More likely that would be caused by greater seasonal sea surface temperature changes in the northern hemisphere due to the larger landmasses obstruction energy diffusion around the globe.
The unobstructed circumpolar current would minimise variations in the most southern oceans.
Carrick says:
June 3, 2012 at 10:03 am
“There has been a decline in the 14C/12C ratio in CO2 that parallels the increase in CO2.”
14C cannot be used for anything with confidence since the birth of the Atomic Era.
“If the increased CO2 was due to warming of the oceans, there should not be a reduction in the ratios of C-13 and C-14 to C-12.”
The quirks of diffusion process do not justify such linear logic.
Thus one can get changes of C13/C12 that don’t follow the basic long-term patterns expected, because other physical processes play a more dominant role on those time scales.
Airy assertion, with no proof. Every physical process tends to become more significant over longer time scales, as a result of the inherent low pass characteristic of stable systems.
What you cannot get around is this relationship. Temperature variation accounts for the entire shooting match. Any role of human emissions in overall atmospheric concentration is small (I estimate 4-6%). See my preceding posts for background.
Allan MacRae says:
June 3, 2012 at 10:05 am
Those are my good days!
Stephen Wilde:
That’s another possibility. Do you have a reference? I haven’t looked at the latitudinal variation in ocean temperatures, so that’s something that would be a test of your hypothesis.
but the variation increases with latitude.
Either mechanism would predict a peak in atmospheric CO2 in summer months, so you can’t use that to eliminate either hypothesis. I’ll have a look at HADSST3 when I get a chance and see if I can produce a plot.
One thing that works against your hypothesis is the ocean surface is only accounts for 20% of the surface the Earth at high Northern latitudes and nearly 100% at high southern latitudes see this—this would suggest you’d need a huge variation in temperature south-to-north to account for what amounts to a factor of 8 difference in annual variation.
Bart, I’m not certain it’s considered scientifically rigorous to hand-wave away ever piece of evidence that doesn’t fit your theory. 😉
Carrick says:
June 3, 2012 at 10:34 am
You offer speculation and call it “evidence”. I’m giving you hard data with a direct bearing on the problem. Physician, heal thyself.
“you’d need a huge variation in temperature south-to-north to account for what amounts to a factor of 8 difference in annual variation”.
Would I ?
We are considering a tiny proportionate annual variability in CO2 release / absorption rates not absolute quantities.
The SH could produce a vast amount with virtually no seasonal variation whilst the NH could produce a much smaller amount with a significant seasonal variation.
Anyway, the essence of my point is that you can’t just pin it on trees which is what you tried to do.
.
Forgive an innocent little bunny for asking, but how does the derivative of the smoothed CO2 concentration with time explain the roughly 90 ppm increase in CO2 concentrations over the last century? You differentiated that out.
Now the derivative may have some relationship to the variation in global temperature through NPP or outgassing of the oceans but that is a different matter.
It is much the same as the fit to a quadratic or an exponential. That has no explicative power. If, on the other hand, you fit it to emissions you might have something interesting. Of course to know what will happen in the future, you would have to know what future emissions will be.
REPLY: you aren’t a bunny, and you aren’t innocent. When are you going to give up this bizzare persona/charade? -A
How does any quadratic or exponential curve fit with historical A-CO2 generation?
Does the putative cumulative A-CO2 generation show a similar quad/expon relationship?
Would this not mean that the presence of CO2 is facilitator of more CO2? Would this not mean the residence time of CO2 was >1000 years?
Regression is the most erroneously applied statistical tool. It doesn’t take much knowledge and skill to use (leads to poor application) and there are too many who need specific results, thus biased (leads to “cooked” results). Without knowing the process by which the model was built and the accompanying diagnostics (various stats and residual plots), any regression model should be treated with skepticism. Academia has been corrupted by performance demands that are impossible. Research supported by proper statistics take much longer and desired results much harder to achieve. Due to poor training and apathy, it is quite likely most of today’s PhD’s would not meet the statistic bar of a generation ago. If the results are welcome, how the statistics were achieved are likely to be given only a glance. If the results were distasteful, the post hoc cycle then begins. But that is off the main topic.
And then there is the data factor. Data are everything. Anyone who does not provide full access to their data is hiding something. It is juvenile to think any work can be taken seriously if the history of its input cannot be independently verified so the results can be duplicated. To minimize proper review, academia hides behind processes that would inspire Rube Goldberg. Those pushing the CO2 game take the cake. In the climate game, they claim global catastrophe if their advice is not adhered to. Yet they were unable to or refuse to do what is necessary to validate their work. Original data lost? Researchers protect their data better than their children. If they can’t maintain a data base, how can their analyses be trusted. They don’t know what the input is.
The real point here is due to the cost of doing nothing and the cost of the “fix” that the climate “scientists” claim and demand, absolutely in no uncertain terms, an environment of total transparency is required. To do otherwise is too self-serving. Are they willing to let the world cook while some arcane academic principle is maintained? I think not. It must be because their work is garbage.
It doesn’t take an expert to know whether a speaker, presenting himself as an expert in the same area, is a fraud or not. A well-educated man can see through whatever flimsy is present. Not being able to produce data is a bad joke anyone with a modicum of sense can get.
Eli Rabett says:
June 3, 2012 at 11:05 am
“You differentiated that out.”
As I explained, the excellent tracking between the temperature and the CO2 derivative demands a high bandwidth system. And, that high bandwidth necessarily means human inputs are attenuated to a level of insignificance.
This is a sophisticated argument which requires an advanced level of understanding of how feedback systems work.
Doug Proctor says:
June 3, 2012 at 11:17 am
“Would this not mean the residence time of CO2 was >1000 years?”
Would this not mean that CO2 regulation in the planet’s atmosphere would be extremely weak, and there is no way to maintain any kind of narrow equilibrium under those conditions given random contributions to the CO2 level?
Why yes, yes it would.
Doug Proctor says:
June 3, 2012 at 11:17 am
And, please note, scale and bias similarity between emissions and CO2 measurements means very little. It is necessary, but not sufficient for the one to be driving the other. A similar quadratic/exponential curve emerges when integrating the temperature anomaly.
Ferdinand wrote:
“There is a fundamental problem here: your formula assumes that the CO2 level continuous to rise with a constant elevated temperature, but that can’t be true. The main source in the past were the oceans. These emit CO2 with rising temperatures until a new equilibrium is reached, that is when the pCO2 of the ocean surface and the pCO2 in the atmosphere are in average equal (thus as much CO2 is absorbed as is released).
So there is an increase if the temperature increases, but limited to at maximum the new equilibrium. which in the past was about 8 ppmv/°C (MWP-LIA, glacials-interglacials), on short term that gives about 4 ppmv/°C of variability around the trend.”
I think we have to forget about the past for a moment – no splicing and different methods please. No need, we have more than 50 years of continuous measurements at ML and other sites as well. Annual growths and therefore the long term accumulation (sum of the annual growths) seem to be dependent on global temperature indices. The conclusion is that the average temperature during the period of accumulation drives the total accumulation. It did since 1959. This still doesn’t mean that the warmth is the sole cause – it could be only because of the human input that the climate system is doing something in response to the human emissions.
You say that constant temperatures causing the rise cannot be true, well you don’t know that. It could very well be that cycles in SST, even without any long term trend, are driving the rise. Degassing CO2 from the oceans is faster (when warming in the cycle, due to volumetric source) than the uptake by oceans (when cooling, due to surface sink), so after every cycle CO2 ends up somewhat higher, depending on temperatures. A reciprocating-type CO2 pump, sort of.
Eli, nothing is differentiated out. Any accumulation (smallest being the annual one) is dependent on the average temperature during the period of accumulation. That’s the correlation. The annual growths only increased because temperature increased since 1959. At the 60s level the annual growth was ~0.9 ppm. If temperatures declined in 70s/80s/90s, the annual growth would have been lower and maybe even negative, at sufficiently low temperatures.
As Just some guy says: June 2, 2012 at 3:43 pm
However, it is useful to compare this CO2 concentration extrapolation to the IPCC CO2 concentration projections.
The IPCC uses a large number of emission scenarios, and calculates a forecast of CO2 concentrations using the Burn carbon-cycle model. The data is here:
http://www.ipcc.ch/ipccreports/tar/wg1/531.htm
There are six main story-lines: A1B, A1T, A1FI, A2, B1 and B2.
The Burn CC model gives a “reference”, a “low” and “high” case for each of the six scenarios, so 18 cases in all.
The “low” case assumes a “fast ocean” (ocean uptake of 2.54 PgC/yr for the 1980s) and no increase of animal respiration. A “high”case assumes a “slow ocean” (ocean uptake of 1.46 PgC/yr for the 1980s) and capping CO2 fertilisation.
Here is a graph of the CO2 extrapolation using the parameters given in the lead post, with some selected IPCC scenarios. Note the huge range of CO2 projections to the year 2100; 1248 ppm in the A1F1 high case, 486 ppm in the B1 low case.
http://www.friendsofscience.org/assets/documents/CO2_IPCC_ScenVsActual.jpg
The A2 Reference case is very close to the CO2 model extrapolation.
edim says:
June 3, 2012 at 11:38 am
“Eli, nothing is differentiated out.”
He has a semi-valid point, one which Richard C. and Robert B. beat me over the head with on another thread. There is still an arbitrary constant which could be added and in which there is room for a (significantly reduced) anthropogenic effect.
However, the argument fails because getting a significant anthropogenic effect still demands a low bandwidth, but the data before us says the bandwidth must be high, or we will not get the excellent tracking between CO2 derivative and temperature anomaly. I illustrated this in the simulations proffered earlier (hit Next to peruse the plots up to viewing 6 of 29).
Bert:
What I am offering is a line of converging evidence–data not speculation. The only suggestion I had was why the data behave in a certain manner. But the data is the evidence I would refer to, not my speculative ideas for why it behaves that way. Any theory has to explain all of the data, not just your pet data.
Your single line of evidence showing a correlation between temperature and CO2. That suggests a cause and effect relationship? If you look at the long-term correlations, do you want to predict which sign you’ll find for the correlation, and which hypothesis that supports?
Bart, I can’t see the arbitrary constant, if you could elaborate (some tried at Climate etc). I still may be wrong, but it’s not only variation around some average growth that correlates with the temperatures. The whole of the annual growth does and at some other temperatures the average growth would be different as well, and therefore the long term accumulation. The correlation holds at other partial growths too. The conclusion is that the average growth over some period (annual, biannual, half-decadal, decadal) is determined by the average temperature during the period.
deltaCO2 = c*Tav, Tav is average anomaly
Personally I find the histrorical results from Mauna Loa a bit too exquisite, definite, and singular to be entirely believable, and I guess many of your readers feel the same.
So, I propose that it be worth a blog from someone about the results from other CO2 measuring stations/devices around the world, that are independent of the Scripps-based methods & locations such Mauna Loa.
Also, a blog on a really close look at the Mauna measuring instrument itself, especially around the Analog-Digital conversion arrangements, to identify the inherent non-linearities and assymetries. Even quite small values would be a possible source of upward bias (or drift) in the totalisation, if there is differentiation and subsequent integration in the data processing.
Bart says:
June 3, 2012 at 9:32 am
It’s all right here. The CO2 level is effectively the integral of temperature anomaly with respect to the proper baseline. These plots were made using GISS LOTI, before Werner Brozek and others pointed out that there is a better match, which is theoretically reasonable, to SST.
In essence, there is the same problem as what Edim figured out here before: at a constant temperature above a baseline, the formula applied gives a constant rate of CO2 increase. Thus with average ~0.3°C increase in temperature, one can have 70 ppmv increase over a period of 50 years.
The first problem is that both the oceans and the biosphere are proven sinks for CO2, thus can’t have delivered that amount of CO2.
The second problem is that there is no physical mechanism which can do that. The oceans give at maximum 16 ppmv/°C (dynamic equilibrium between ocean surface and atmosphere, according to Henry’s Law). The biosphere only sinks more CO2 by growing harder individually and in increasing total area, and the rest of the earth is too slow in reaction.
Then think about the glacial/interglacial events: the increase in temperature from the depth of a glacial to the height of an interglacial is ~10°C, it takes about 5,000 years and CO2 increases ~80 ppmv over that traject. With a temperature (anomaly) dependent rate for CO2, however small, that simply is impossible.
The rate of change of CO2 is influenced by the change in temperature, not the absolute temperature (or anomaly), only the equilibrium CO2 levels are absolute temperature dependent.
Bart, I also think one needs to at least look at the correlation you pointed out in the context of a simple 0-d radiative model (e.g., Lucia’s 2-box model). And then look at it in terms of a stoichiometric model of ocean/atmosphere and ask yourself what are the time constants associated with CO2 release from the ocean in response to heating.
I think Josh/Eli’s observation deserves a bit more than a rhetorical wave-off, something you are quite prone to doing, as I’ve observed in previous interactions with you. Also, if you can’t keep this at an adult level you can have the floor.
The only thing that’s differentiated out is the start condition (atmospheric CO2 at t0), but it’s a known value.
edim says:
June 3, 2012 at 11:32 am
You say that constant temperatures causing the rise cannot be true, well you don’t know that. It could very well be that cycles in SST, even without any long term trend, are driving the rise. Degassing CO2 from the oceans is faster (when warming in the cycle, due to volumetric source) than the uptake by oceans (when cooling, due to surface sink), so after every cycle CO2 ends up somewhat higher, depending on temperatures. A reciprocating-type CO2 pump, sort of.
Sorry, but degassing/uptake by the oceans surface is already fast; a new CO2/temperature equilibrium is reached in 1-2 years. Deep oceans exchange is a different matter, but that doesn’t go faster by higher temperatures (seems more the contrary). It is the absolute temperature of the oceans surface which governs how much CO2 is absorbed or released (Henry’s Law), not influenced by any cycle. The latter can influence the speed at which that happens, but that is not the problem here. And at what CO2 increase rate you think a glacial-interglacial transition would be?
But let’s go the other way out:
If you agree that in the past (and today) the CO2 levels are temperature dependent, shouldn’t be the dCO2 rates dT dependent?
Carrrick says: June 3, 2012 at 9:47 am
“This is one of my favorite graphics. It shows that the Northern hemisphere (where most of the trees are) shows the largest annual variation in CO2, and the south pole (where there are very few trees ;-)), shows almost no variation.”
http://scrippsco2.ucsd.edu/images/graphics_gallery/original/co2_sta_records.pdf
A beautiful graphic, thank you Carrick – I plotted it from raw data years ago. It clearly shows the huge magnitude of seasonal (natural) atmospheric CO2 flux compared with humanmade
CO2 emissions.
The seasonal CO2 “sawtooth” varies almost 20ppm at Barrow Alaska, and about 2ppm at the South Pole. I think this primarily reflects the larger land mass in the Northern Hemisphere. In comparison, global atmospheric CO2 concentration is increasing at a rate of about 2ppm/year.
Further, the daily flux in CO2 is also huge.
Here is recently observed Rose Park data at Salt Lake City:
http://co2.utah.edu/index.php?site=2&id=0&img=30
Please examine the Daily CO2 and Weekly CO2 tabs for all measurement stations.
.
Peak CO2 readings (typically ~500ppm) occur during the night, from midnight to ~8am, and drop to ~400 ppm during the day.
1. In contrast, human energy consumption (and manmade CO2 emissions) occur mainly during the day, and peak around breakfast and supper times.
2. I suggest that the above atmospheric CO2 readings, taken in semi-arid Salt Lake City with a regional population of about 1 million, are predominantly natural in origin.
IF points 1 and 2 are true, then urban CO2 generation by humankind is insignificant compared to natural daily CO2 flux, in the same way that (I previously stated) annual humanmade CO2 emissions are insignificant compared to seasonal CO2 flux.
IF these results are typical of most urban environments (many of which have much larger populations, but also have much greater area, precipitation and plant growth), then the hypothesis that human combustion of fossil fuels is the primary driver of increased atmospheric CO2 seems untenable.
Here is one of my favorite graphics. I can see no impact of man in this impressive display of nature’s power.
http://svs.gsfc.nasa.gov/vis/a000000/a003500/a003562/carbonDioxideSequence2002_2008_at15fps.mp4
Humanmade CO2 emissions are lost in the noise of the much larger natural system, and most humanmade CO2 emissions are probably locally sequestered.
Finally, I have no confidence in the C14/13/12 ratio argument. I think others have demolished it and I need not do so again.
“Sorry, but degassing/uptake by the oceans surface is already fast; a new CO2/temperature equilibrium is reached in 1-2 years. Deep oceans exchange is a different matter, but that doesn’t go faster by higher temperatures (seems more the contrary). It is the absolute temperature of the oceans surface which governs how much CO2 is absorbed or released (Henry’s Law), not influenced by any cycle. The latter can influence the speed at which that happens, but that is not the problem here. And at what CO2 increase rate you think a glacial-interglacial transition would be?”
Absolute temperatures of the ocean surface oscillate in annual cycles. Land surface temperatures too. Different latitudes in different phases and different amplitudes. In oceans we have currents, upwelling, downwelling etc, which must influence CO2 fluxes at ocean/atmosphere interface.
“But let’s go the other way out:
If you agree that in the past (and today) the CO2 levels are temperature dependent, shouldn’t be the dCO2 rates dT dependent?”
I can’t say what they should or not. The observed behaviour is that dCO2 is T dependent. Like I said, I cannot accept ice core records, different methods splicing etc. There’s no need.
Edim and Bart,
Have a look at what Pieter Tans of NOAA says about CO2 growth rate and temperature anomaly + precipitation:
from page 14 on:
http://esrl.noaa.gov/gmd/co2conference/pdfs/tans.pdf
He shows everything with the trends removed and the resp. response functions of CO2 vs. temperature and precipitation.
Regarding measurements in close proximity of volcanoes:
The amount of carbon dioxide (and other volcanic gases) is an indicator when an outbreak is about to occur. The amount increases exponentially before …
You are pointing at something important …
The “green stuff” takes care of that (as you know) … Not to forget, because there are a number of different oxidation processes in nature, including those in our bodies, we need an abundance of carbon dioxide, so that the “green stuff” can produce the oxygen we need … (More carbon dioxide contributes to more “green stuff” contributes to more oxygen …)
Yes, even a “dead” volcano emit gases, including carbon dioxide.
Friends:
The important point is that the dynamics of the seasonal variation in atmospheric CO2 concentration indicate that the natural sequestration processes can easily sequester ALL the CO2 emission (n.b. both natural and anthropogenic), but they don’t: about 3% of the emissions are not sequestered. Nobody knows why not all the emissions are sequestered. And at the existing state of knowledge of the carbon cycle, nobody can know why all the emissions are not sequestered. But that is the issue which needs to be resolved.
Importantly, it is certain that accumulation of the anthropogenic emission is NOT the cause of the rise in CO2 indicated by the Mauna Loa data.
The curve fitting exercise of the above article is pointless. If a curve is fitted then the equation of the curve provides a description of the shape of the curve but no information is gained by such an exercise. And it cannot assist in explaining why all the emissions are not sequestered.
In the above discussion, Bart claims his model of the carbon cycle is ‘right’ so all other models should be ignored. However, there are several models of the carbon cycle which each assumes a different mechanism dominates the carbon cycle and they each fit the Mauna Loa data. We published 6 such models with 3 of them assuming an anthropogenic cause and the other 3 assuming a natural cause of the rise in CO2 indicated by the Mauna Loa data: they all fit the Mauna Loa data.
These issues were ‘done to death’ in the thread at
http://wattsupwiththat.com/2012/05/24/bob-carters-essay-in-fp-policymakers-have-quietly-given-up-trying-to-cut-%C2%ADcarbon-dioxide-emissions/
The discussion in that thread is worth a read by those interested in the ‘carbon cycle debate’.
Richard
edim says:
June 3, 2012 at 1:13 pm
I can’t say what they should or not. The observed behaviour is that dCO2 is T dependent. Like I said, I cannot accept ice core records, different methods splicing etc. There’s no need.
Regardless of what you think about ice cores, there are plenty of other proxies which show a lot ot temperature change over glacials and interglacials.
E.g. the previous Interglacial was 2°C warmer than today (up to 10°C in Alaska, Siberia,…) during about 3,000 years, followed by a period of 7,000 years with 1°C warmer than today. With a constant CO2 rate over these periods, where should the CO2 levels be at the end?
The opposite is one of the main problems with that theory: glacials were 100,000 years long and far below the current temperatures, thus certainly with a huge negative CO2 rate according to your assumptions. Thus ending at zero CO2 already after a few hundred years…
edim says:
June 3, 2012 at 12:16 pm
The point those other guys made is that anthropogenic inputs are effectively linear in rate over the time span. With medium level bandwidth, that becomes a linear output in CO2. It still says the output would be drastically reduced from a straight accumulation, though.
A linear output is also the result of integrating the anomaly offset in the temperature. Ergo, they claimed, I could trade off the one for the other.
But, I cannot, because it would lessen the tracking efficiency to the point where the CO2 derivative would not keep pace with the temperature variation.
I assert that these are the facts, folks:
1) CO2 is very nearly proportional to the integral of temperature anomaly from a particular baseline since 1958, when good measurements became available.
2) Because of this proportionality, the CO2 level necessarily lags the temperature input, therefore in dominant terms, the latter is an input driving the former.
3) The temperature relationship accounts for all the fine detail in the CO2 record, and it accounts for the curvature in the measured level.
4) This leaves only the possibility of a linear contribution from anthropogenic inputs into the overall level, which can be traded with the only tunable parameter, the selected anomaly offset.
5) Anthropogenic inputs are linear in rate. Therefore, to get a linear result in overall level from them, there has to be rapid sequestration. (Else, you would be doing a straight integration, and the curvature, which is already accounted for by the temperature relationship, would be too much.)
6) With rapid sequestration, anthropogenic inputs cannot contribute a significant amount to the overall level.
Now, you may quibble about this or that, and assert some other relationship holds here or there, but your theories must conform with the reality expressed by these six points, because this is data, and data trumps theory.
mondo says:
June 2, 2012 at 3:42 pm
Shouldn’t we be looking at this sort of data on a logarithmic rather than arithmetic Y-scale?
Indeed if we subtract the constant term of 260 ppm, we get a straight line on semilog paper:
ln (CO2) = 0.0169 (t-1958) + 3.979 with an R^2 of 99.86%
richardscourtney says:
June 3, 2012 at 2:31 pm
“We published 6 such models with 3 of them assuming an anthropogenic cause and the other 3 assuming a natural cause of the rise in CO2 indicated by the Mauna Loa data: they all fit the Mauna Loa data.”
I’m sure neither of us wants to revisit the rancor of our earlier exchange, but I must insist that the phrase “they all fit” be qualified. I think I am being fair in characterizing your definition of “fit” as “within the instantaneous uncertainty level of the MLO data.” I have insisted, reliably I might add, that it is quite possible to dig below that level for long term underlying processes by filtering, and that is where you will find whether they agree or not with the fine detail mandated by the temperature relationship. For the life of me, I do not know why you refuse to do that particular analysis.
Unfortunately, as you have informed us, your paper is not generally available to the general public, being behind a paywall, and we cannot check your assertion for ourselves. Nor do I have access to the precise data you used to verify your models. So, until presented with evidence otherwise, I am not going to believe that all of the “fits” are equally good. In fact, I very much expect that the fits which use less anthro and more natural will be better.
jorgekafkazar says:
June 2, 2012 at 7:16 pm
Thanks, Lance, this was fun. But there’s not a whole lot of science, here. Using a curve fit for a 56 year period, then extrapolating backwards and forwards is very shaky. There’s no reason to assume that the multiple mechanisms resulting in atmospheric CO2 concentrations are identical at the start and end of the period; thus the exponential, though convenient, is not necessarily valid as a predictor or analytical tool of any sort.
If you have the time, though, you might want to push this a stage further. At a minimum, I’d like to see error bars fore and aft, as well as a correlation coefficient adjusted for autocorrelation. I think you’ll find your 1723 date should be ±200 years. Worse, trying to tie the date of the knuckle of the exponential to any invention is completely unjustified. Natural CO2 variation may likely overwhelm any man made emissions, distorting the actual curve beyond recognition.
Thanks Jorge, indeed I did it just for fun and make no scientific claims. The fit was so good I assumed the error would be small, but since you ask I redid the nonlinear fit in Statistica (I had used Excel before). There were some small differences in the point estimates: Background CO2 was 257 ppm (SE 1.05 ppm) compared to 260; the start year was 1711 instead of 1723 (darn! missed Newcomen’s invention by a year!) (SE 3.94 years, well short of your suggestion of about 100); and tau was 61.3 (SE 0.7) years, compared to 59. So indeed the errors are amazingly small, especially considering the last 20 years of intense focus on CO2 with apparently little effect.
I wasn’t actually too serious about the Newcomen invention, just trying to track the beginning of the curve to the beginning of the Industrial Revolution since that is so often fingered as the culprit. Note that the curve takes 40 years(!) to increase from 261.4 ppm to 262.4 ppm.
Pamela Gray says:
June 2, 2012 at 6:08 pm
Anything as regular as this data says one of two things.
1. Manmade CO2 pump sitting next to the sensor and never shuts off and is exquisitely tuned to a rythmic increasing beat.
2. Artifact of the “fudge” factor part of the CO2 calculation.
I too am gobsmacked by the regularity of the curve. If it is mostly due to increasing anthropogenic emissions, one would think as others have pointed out that there would be more serious impacts of economic lulls and booms. If mostly natural on the other hand, why the constant acceleration rather than a linear or possibly deceleration following the LIA? But it is rather fun to see the complete lack of any visible effect of all the Kyotos, Balis, Copenhagens,and Rios.
George E. Smith; says:
June 2, 2012 at 8:40 pm
1) So I didn’t see any conclusion as to whether the Mauna Loa CO2 data best fits an exponential curve or whether a power series curve is a better fit for the 1722 to 2050 data.
2) Why did you choose to start your extrapolated prediction; excuse me, that’s projection, from the year 1722. Aren’t you concerned about being accusede of cherry picking, by selecting that year; rather than say 1769; the year that Captain Cook, (re)discovered New Zealand ?
Well, as to 1) above, I did mention that the quadratic gave a better fit over the 50-odd years than the exponential. But the exponential fit has much more attractive interpretations of the three parameters. For example, I did not “choose to start” at 1722–that was a free-floating parameter that was “chosen” by the Excel nonlinear fitting function. The other parameters (background of 260 ppm, doubling period of 41 years for the incremental CO2 above background) were also completely a function of the fit. The background value, for example,is fairly close to the 280 ppm that is presently regarded (I presume due to multiple lines of observational evidence–at least I hope so) as the level before the Industrial Revolution. These parameters did not have to come out so nicely, and in that case there would be no particular reason to look further at the exponential fit.
MikeG says:
June 3, 2012 at 12:48 am
Sorry, your curve fitting is quite meaningless and has no predictive properties whatever. The data would make an equally convincing fit to a sine curve, and many other functions.
Well, the exponential fit did have some nice properties, like predicting a background level and an initial starting point both of which have observations in fairly close agreement. Also, based on the 50-year period with residuals seldom exceeding 1 ppm, I would be willing to bet that the curve will be no more than 1 ppm in error 5 years from now.
Bart says:
June 3, 2012 at 1:21 am
A simple analogous (not precise in every detail, but able to provide guidance as to physically possible and plausible behavior) system model is as follows:
dC/dt = (Co – C)/tau1 + k1*H
dCo/dt = -Co/tau2 + k2*(T-To)
Well,you have 5 adjustable parameters here and you know what von Neumann said about that.
Freddy Hutter, TrendLines Research says:
June 2, 2012 at 11:29 pm
The projected co2 chart is scary only ‘cuz it assumes unlimited supply of fossil fuels (as in IPCC scenarios). It is rather more reasonable (423-ppm 2029) when adjusted to reflect peak oil, peak gas & peak coal
I actually assumed nothing, just let the observations do what they would. The idea that peak fossil fuels drive the curve is certainly possible, but is also an assumption.
Ferdinand Engelbeen says:
June 3, 2012 at 2:10 am
Oh by the way, a simple formula to calculate the CO2 levels at any moment in the future (or past);
CO2(new) = CO2(old) + 0.55xCO2(emiss) + 4xdT
Thank you Dr. Engelbeen for the useful references. Your proposed formula seems to suggest that at times of decreasing or plateauing temperatures, the CO2 emissions would need to increase at just the right speed to offset the reduced effect of temperature and maintain the eponential increase.
Dave Walker says:
June 3, 2012 at 1:46 am
Caleb- Downslope from Mauna Loa are miles of recent lava flows and then miles of rainforest. The Observatory is 11,000 feet high and enjoys pretty steady wind. They throw out readings tainted with vog or low altitude pollutants. Not a perfect observatory but pretty good.
==============
They decide what is or isn’t this claimed ‘well-mixed’ background – without ever proving there is such a thing as this, or showing even if there was how they can tell the difference. They merely decide what the figure will be, that isn’t science. They’re not measuring anything.
Keeling was anti-coal and went to a laboratory on the world’s largest active volcano, surrounded by constant volcanic activity in venting and thousands of earthquakes every year above and below sea level, over a huge hot spot creating volcanic islands in a warm sea, all constantly releasing carbon dioxide, and he claimed with less than two years data that he had definitely established there was a trend, established that global levels from man-made carbon dioxide were rising. WUWT?? Doesn’t ring any warning bells? The man had an agenda, all his decisions can be seen to be agenda driven, and, he and his son had control over the stations for years and now all within the coordinated ‘consensus’ to prove AGW – there is nothing to suggest the Keeling curve is anything but make believe.
What happens here? The disjuncts are just ignored. Why hasn’t AIRS produced the top and bottom of troposphere data? Too much proof from their conclusions of mid troposphere that carbon dioxide was lumpy and not well-mixed? And they’d have to go away and learn something about wind systems…
Here, a real picture of carbon dioxide levels worth a thousand words:
http://www.biomind.de/realCO2/literature/evidence-var-corrRSCb.pdf
Evidence of variability of atmospheric CO2 concentration during the 20th century
Dipl. Biol. Ernst-Georg Beck, Postfach 1409, D-79202 Breisach, Germany
Discussion paper May 2008
From page 9:
CO2 in Troposphere/Stratosphere 1894 -1973
“Figure 4 Tropospheric and stratospheric measurements of CO2 from literature 1894-1973 (see Table 2) graphed from 66 samples, calculated as 18 yearly averages.
Despite the low data density, the CO2 contour in troposphere and stratosphere confirms the direct measurements near the ground that suggest a CO2 maximum between 1930 and 1940.
The CO2 peak around 1942 is also confirmed by several verified data series since 1920 sampled at ideal locations and analysed with calibrated high precision gas analysers used by Nobel awardists (A. Krogh since 1919) showing an accuracy down to ±0.33% in 1935. Figure 5 shows the 5 years average out of 41 datasets (see Table 1). For comparison the reconstructed CO2 from ice records according to Nefttel et al. is included.”
The Nefttel et al on next page 10, but don’t let that distract you from the picture on page 9…
Then see picture on page 12:
“Considering Figure 8 we can see that Callendar selected only the lowest sample values and omitted several data sets. His averages are mostly lower than the correct values. His so-called “fuel line” is therefore about 10 ppm higher than he calculated. Furthermore he ignored thousands of correctly measured data on the sea, continent and in the troposphere for reasons we can only speculate.”
And if objective, that speculation leads to the inevitable conclusion that this was agenda driven and the Keeling Curve should be flagged as such in science teaching.
Kevin Kilty says:
June 3, 2012 at 9:42 am
The exponential model presented here has no coefficient that multiplies the exponential, and therefore, implies that this coefficient is 1.0ppm, and is a constant in the model–not determined by data at all. This seems extremely unlikely. Is this a typo?
The observed data are all contained within one e-folding time far along in the time series, So the coefficients are correlated to one another and not well determined.
Actually, I struggled with that for a time and don’t really know who won. There IS a coefficient of sorts–write the exponential as a product and the coefficient is exp(-t0/tau). If we add another coefficient, leaving the rest of the equation alone, the new coefficient just interacts with this coefficient and makes everything ambiguous. If on the other hand we replace the exp(-t0/tau) with just the new coefficient, we lose the knowledge of when the exponential rise began and also the time constant, although it is probably the case that the fit would be as good.
Ken Gregory says:
June 3, 2012 at 11:45 am
Here is a graph of the CO2 extrapolation using the parameters given in the lead post, with some selected IPCC scenarios. Note the huge range of CO2 projections to the year 2100; 1248 ppm in the A1F1 high case, 486 ppm in the B1 low case.
http://www.friendsofscience.org/assets/documents/CO2_IPCC_ScenVsActual.jpg
The A2 Reference case is very close to the CO2 model extrapolation.
Many thanks Ken for applying the model above and comparing it to the IPCC models. Quite delightful that a simple exponential model tracks so closely to a highly sophisticated multiple-parameter model employing the full panoply of hard-won climate science findings.
Lance Wallace says:
June 3, 2012 at 4:48 pm
“Well,you have 5 adjustable parameters here and you know what von Neumann said about that.”
It isn’t a “fit”, so the criticism is inapposite. It is the simplest model possible to elucidate the behavior dictated by the data, and you know what Einstein said about that.
Wallace, I think the key finding here is in your residuals. They show that there is a temperature dependency but it’s very small. +/- 1.5 max over the period of the data.
That in itself is very useful because I have seen a number of people suggesting that most of CO2 rise was to temperature rise ( like happens during and after deglaciation ).
The other thing to notice is that the quadratic is a better fit. The exponential starts too big and ends too small. That is a bad sign in view of the extrapolations you do at both ends.
As your plot shows the two can be grossly similar over that short a section and many observers have loosely categorised the change as “exponential” because it is growing ever faster.
There was some paper (reported on WUWT) that had found “super-exponential” growth in CO2. This attracted much derision here from the uneducated howlers who thought it was alarmist propaganda. In fact, as I pointed out at the time, in mathematics super-exponential just means a function that grows faster than an exponential. The papers finding was that a quadratic was a better fit and noted that a quadratic is super-exponential. Your plot basically confirms this.
The other problem with extrapolating in either direction is that there is very little of the curved section to fit to so very small errors could lead to large changes in the coeffs of the fit. It also implies the assumption that whatever caused / is causing the rise is unchanging on the century scale, eg. ecomonic growth had been and always will be a fixed percentage per year ( a fixed %age growth gives an exponential).
I did the exponential plotting thing two or three years ago. I found it best to do three different exp. fits: pre-1900; 1900-1965 and 1965 onwards. I was using economic data for fossil fuel extraction and scaling the result to Mauna Loa record.
I’ll try to dig out my results.
The curve fitting exercise of the above article is pointless. If a curve is fitted then the equation of the curve provides a description of the shape of the curve but no information is gained by such an exercise. And it cannot assist in explaining why all the emissions are not sequestered.
I have to agree — indeed, the very impossibility of distinguishing a quadratic from an exponential (or, as pointed out, from a harmonic function or many other possibilities) is indicative that the baseline is too small to prove much of anything at all.
I also agree with your argument on non-uniqueness — Indeed, one thing that IS apparent in this curve is that the variation ABOUT exponential, or quadratic, or sinusoidal, is almost completely irrelevant compared to the dominant behavior. It can be modeled quite accurately by:
C(t) = C_0(t) + V(t)
where C_0(t) is either of the empirical fits above (or any other fit to the smooth curve) and V(t) describes the “anomaly” — the noise on the curve, and is visibly over two orders of magnitude smaller. LOTS of things could determine the shape of C_0(t). Lots of combinations of things, at that. The problem continues to be the absurdly short baseline. Monotone increasing is not only boring, it is impervious to analysis — any monotonic driver can be correlated with it and will “work”. A completely separate cause — which might or might not be a significant component of the cause of C_0(t) — could be responsible for the small secular variations in V(t).
The same argument works both for and against the CAGW CO_2 is the devil argument. Over the last 110+ years, there is at least some correlation between the solar cycle and global temperatures. There is also (presumably) monotone/exponential or whatever increasing CO_2. It has been argued that CO_2 is responsible for the increasing temperature, with solar cycle at best a minor modulator around the overall average increase. However, one can also fit the data with the solar cycle being a primary driver and CO_2 an all but irrelevant modulator. This sort of thing is often possible when fitting nonlinear curves — there is an almost irresistible temptation to commit the sin of seeking confirmation from the success of a fit to some set of functions that tells a good story (that is, the story you want to believe) and blind yourself to the fact that there might be a dozen equally or even more successful fits (and a few less successful ones) that tell a very different story, and that (nature being nature) one of the less successful fit/stories could end up being the true one, given the (usually unstated or unknown) errors in the measurements and methodology that comprise the fit data.
There is a really, really lovely paper by Koustoyannis that illustrates the general problem quite beautifully. In fact, on its first page the figure alone says it all, and shows why Anthony’s curve fitting is meaningless — it is half way between window A and window B, where the data could be quadratic, exponential sinusoidal or just spectral noise on a really long term deterministic behavior that hasn’t even begun to be resolved. You can grab a preprint of his paper here:
http://itia.ntua.gr/en/docinfo/673/
Koustoyannis is actually a Really Bright Guy, and the essence of his paper is that the entire statistical basis of climate science is tragically flawed. He goes on and shows that the entire concept of causality in climate science is badly broken; that it should really be described not by ordinary classical statistics but rather by Hurst-Kolmogorov statistics, which is basically a peculiar structure of stochastic state transitions modulated by non-stochastic noise. I find his argument rather compelling. You can see one of the talks he has presented on HK statistics in climate science here:
http://www.cwi.colostate.edu/nonstationarityworkshop/SpeakerNote/Wednesday Morning/Koustayannis.pdf
Sadly, I think his math is way beyond the level of understanding of most climate scientists. I keep hoping Bob Tisdale sees one of my posts of his work, though, as his models precisely reproduce the stochastic jump followed by trendless noise Bob observes in SST data. Hurst-Kolmogorov process — stationary noise plus scaling behavior.
I also just finished Taleb’s The Black Swan and found it quite revelatory. It, too, warns against the abuse of statistical methods designed for Mediocristan — that part of the world where Gaussian statistics and concepts like standard deviation have meaning and life is rather predictable and boring (like mainline classical physics) — by applying them in Extremistan, places where nonlinearity and scaling behavior render any application of traditional statistical methods completely invalid and capable of making dangerous and expensive mistakes. He also warns — repeatedly — against the danger of confirmation bias, the ability of humans to go looking for data that will confirm their pet theory and find it, at the minor cost of ignoring all the other data that confounds it.
Places like climate science. The very first question that should have been asked in climate science before starting a sky-is-falling-and-we-must-tell-the-king scandal is is there anything truly unusual about the climate today. The answer is very clearly no. A resounding no. A statistically certain, overwhelming no. Whether one looks at 25 million years of proxy-derived climate data, 5 million years of proxy-derived climate data, 1 million years of proxy-derived climate data, 100,000 years of proxy-derived climate data, or 10,000 years of proxy-derived climate data, there is absolutely nothing remarkable about the present. It isn’t the warmest, the most rapidly warming, the coolest, the rainiest, or the -est of anything. It is boring.
The entire CAGW fiasco is a clear example of how humans implicitly believe the largest thing they’ve ever seen to be the largest thing in existence.
rgb
OK, found my exp fits. The data I used has this header, should be enough to find its source.
#*** Global CO2 Emissions from Fossil-Fuel Burning,
#*** Cement Manufacture, and Gas Flaring: 1751-2007
#***
#*** June 8, 2010
#***
#*** Source: Tom Boden
#*** Gregg Marland
#*** Tom Boden
#*** Carbon Dioxide Information Analysis Center
#*** Oak Ridge National Laboratory
#*** Oak Ridge, Tennessee 37831-6335
The extraction data was integrated by addition of each years output to get total emissions and then plotted on a log scale. This shows three quite clear stages in development and underlines the fact that fitting just one curve or any sort is too simplistic.
As is generally known, industrial output only really took off after about 1960.The log plot shows there were three stages of fairly constant annual percentage growth. The post 1960 period corresponds to the Mauna Loa record and allows scaling the industrial extraction data to the residual airborne CO2 concentration. This scaling produces a preindustrial CO2 level of around 295 ppm, suggesting the favorite figures of 260-270 are rather too low.
The later segment was fitted from 1965 onwards and the actual data rises slightly quicker than the fitted line near the end, so the 2050 projection of 462ppm may be somewhat low *if* current rate of growth continues.
http://imagebin.org/index.php?mode=image&id=215058
http://imagebin.org/index.php?mode=image&id=215060
[mods, these images are only good to 15days, please copy them if possible.]
I looked at the correlation between d(S_CO2)/dt and HADSST3(?), and the results were pretty much what I was expecting (ironically based in part on work that Bart had done previously).
The peak correlation corresponds to approximately a 2 month lag between change in CO2 and temperature, with temperature lagging CO2. It’s actually easy to see which lags which with a zoom in of Bart’s chart.
Here’s my figure.
Cause and effect suggests that CO2 is driving temperature change, and what we’re looking at here is predominately the “fast response” of climate to changes in CO2.
I’m guessing that Bart never tested the lag when he made this claim:
(That’s par for the course from my experience.)
Allan:
Depends on whether you are looking at surface measurements, or “full atmospheric column” as to whether this is true or not.
The Phoenix dome regularly achieves surface CO2 concentration levels over 600 ppm, but that has a negligible effect on Phoenix temperatures because it’s all concentrated near the surface. The whole point of measuring on Mauna Loa is related to looking at the “well-mixed” portion of the atmosphere, well above regional scale changes (and being situated above a tropical jungle there are substantial diurnal variations in CO2 driven by natural variability–again well studied by Keeling.)
People who are going to criticize the work of others, should really take the time needed to understand the rationale of the original experimental setup. Otherwise you’re not being skeptical you’re being overly credulous to your own pre-conceived notions. Keeling spent roughly 10 years researching the optimal way of collecting these data, and before him, for reasons you’ve managed to elucidate it was generally accepted it was not achievable. Part of the credit he has received, and it was well-deserved, was working out how to side step many of the issues you and others have raised (and these are patty-cake level issues you’re raising compared to the critics of the day he had to face).
This is just another one of those wave-offs you guys like to do for facts you can’t readily counter. “Demolished” just means somebody wrote some nice sounding words that don’t standup to the scrutiny of the skeptical mind.
Carrick says:
June 3, 2012 at 10:47 pm
Honestly, Carrick, I would have expected better than such a series of elementary errors from you. But, then again, that’s par for the course from my experience.
We’re talking about the relationship between the CO2 level and the temperature. You are looking at the derivative of the former versus the latter. With a 90 degree phase lead from the derivative, what the hell else would you expect?
As for zooming in on my chart, the CO2 data is processed with a 2 year non-causal filter, being the centered average. The WoodForTrees site automatically centers the average to make up for the phase delay. So, it’s hardly surprising that the data points anticipate the future when half of each one is made up of information from the future.
Massive fail, dude.
OK , let’s try again for those plots.Imagebin seems to appropriately named , if you don’t want anyone to see your image: image bin it!
http://image.bayimg.com/iaongaadp.jpg
http://image.bayimg.com/jaonfaadp.jpg
I hate to say it, but this analysis is meaningless. You can’t just fit a curve to something and extend it, that’s the kind of thing that the AGW alarmists do.
Instead, you need to look at the actual rates at which CO2 is emitted, and the rate at which it is sequestered. This is an exponential rate of sequestration of some kind, in which the amount sequestered increases as the atmospheric concentration increases.
One of the characteristics of this type of exponential decay is that if the emissions are constant, you end up with a “sigmoid function”, where eventually the amount sequestered will increase to match the amount emitted and the rise in atmospheric levels will stop.
Now, the author shows us this image, claiming doubling by 2050 …
However, there is no reason to prefer his curve over this sigmoidal curve, which matches the data just as well as his does …
In reality, nothing in nature continues to grow exponentially.
w.
Carrick, could you explain why you expected the rate of change of CO2 to ’cause’ a temperature rise?
It is well known that higher water temp will produce outgassing, on the other hand if you are suggesting CO2 conc is producing a “forcing” that is producing a temperature change you should be looking at CO2 conc vs dT/dt
Perhaps you could explain your thinking. I seem to have missed the causal relationship you are suggesting.
Lance Wallace says:
June 3, 2012 at 5:01 pm
Thank you Dr. Engelbeen for the useful references. Your proposed formula seems to suggest that at times of decreasing or plateauing temperatures, the CO2 emissions would need to increase at just the right speed to offset the reduced effect of temperature and maintain the eponential increase.
The human emissions are near linearly increasing over time, that is the basis for the trend. The 0.55 is pure coincidence, as that depends of the reaction speed of the process, but remarkably constant over the past 100 years or so (the “airborne” fraction of the emissions – in mass – remains constant). As the influence of temperature on short term (seasonal: 5 ppmv/°C, interannual ~4-5 ppmv/°C around the trend) is rather small, its influence on the trend if averaged over 2-3 years is near negligible.
BTW, no need to plot the accumulated CO2 trend on log paper, even on lineair scale there is a remarkable correlation with the emissions:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/acc_co2_1900_2004.jpg
BTW2: No Dr. here, have a B.Sc. in chemistry, but changed to a M.Sc, job in process automation some 25 years ago, now already 8 years retired…
Willis : “In reality, nothing in nature continues to grow exponentially.”
Your point about many curves matching such a short segment if fair, but the whole AGW debate is all about a change that is NOT natural : economic growth (and hence fossil fuel usage) has been growing exponentially since the 60’s (about 2% per year).
So I don’t see why you suggest a sigmoid, which would correspond to constant emissions. No sign of that happening in the near future. 🙁
Bart says:
June 3, 2012 at 3:24 pm
I assert that these are the facts, folks:
1) CO2 is very nearly proportional to the integral of temperature anomaly from a particular baseline since 1958, when good measurements became available.
That is nice, but much too short to give a straight answer. If you extent that back to before the MLO time, the temperature was below your baseline for the full period 1900-1935, average -0.2°C. That is good for a CO2 drop of 84 ppmv, if you integrate over that period. Whatever the quality of the historical measurements, other proxies (like stomata) or ice cores, none of them shows such a drop. To the contrary, all show some increase. Extending that further to the depth of the LIA (some 0.4°C below baseline during several centuries), about all CO2 would be used up.
That simply shows that the correlation between temperature and rate of change of CO2 is mainly on the variability, but on the trend itself that is a spurious correlation.
Second, there is no known physical mechanism which can deliver 70 ppmv in 50 years time into the atmosphere for an increase of only 0.2°C in average. The equilibrium CO2 level between ocean surface and atmosphere for a 0.2°C increase is +3 ppmv. Vegetation acts in opposite ways and both are proven net sinks for CO2. All other sources are too slow or too small.
Further, there are lots of other observations which need to be fitted, whatever the source of the increase may be, temperature driven or not:
– the decline in d13C/12C ratio in the atmosphere and oceans
– the pre-bomb decline in d14C/12C ratio
– the increase of biomass (oxygen balance)
– the increase of DIC (total inorganic carbon) in the oceans
– the overall mass balance
2) Because of this proportionality, the CO2 level necessarily lags the temperature input, therefore in dominant terms, the latter is an input driving the former.
Agreed, except that this is true for the influence of temperature variations on the variations in increase rate, not on the increase rate itself.
3) The temperature relationship accounts for all the fine detail in the CO2 record, and it accounts for the curvature in the measured level.
The first is true, the second is for 96% spurious (the remaining 4% is the effect of the increase in overall temperature over that period)
4) This leaves only the possibility of a linear contribution from anthropogenic inputs into the overall level, which can be traded with the only tunable parameter, the selected anomaly offset.
That is where we differ in opinion: You can have the same fit of both curves if the human emissions are responsible for most of the trend and temperature variability is responsible for most of the variability in the derivative of the trend.
5) Anthropogenic inputs are linear in rate. Therefore, to get a linear result in overall level from them, there has to be rapid sequestration. (Else, you would be doing a straight integration, and the curvature, which is already accounted for by the temperature relationship, would be too much.)
As the temperature-trend relationship is largely spurious, there is no need for rapid sequestration (as can be seen in the observed adjustment time).
6) With rapid sequestration, anthropogenic inputs cannot contribute a significant amount to the overall level.
Again, the observed sequestration is not rapid, it is in the order of 53 years.
Now, you may quibble about this or that, and assert some other relationship holds here or there, but your theories must conform with the reality expressed by these six points, because this is data, and data trumps theory.
As your theory already trumps the data in the first point, your theory is falsified…
Duh, looks like links only work from my IP where I uploaded them. The day WP has a page preview we’ll all do a lot better. let’s try again……
Bart says:
June 3, 2012 at 7:27 pm
Lance Wallace says:
June 3, 2012 at 4:48 pm
“Well,you have 5 adjustable parameters here and you know what von Neumann said about that.”
It isn’t a “fit”, so the criticism is inapposite. It is the simplest model possible to elucidate the behavior dictated by the data, and you know what Einstein said about that.
Excellent riposte, Sir, and I fully deserved it for being flippant. Models with some sort of underlying physics are much to be preferred over my simple curve-fitting exercise. I checked your link and could see that a small tau1 was better than a large one, but didn’t see what values you obtain for tau2 or the other parameters and wondered whether you cared to present the values here and perhaps comment on their interpretation.
Willis Eschenbach says:
June 3, 2012 at 11:41 pm
“I hate to say it, but this analysis is meaningless. You can’t just fit a curve to something and extend it, that’s the kind of thing that the AGW alarmists do.”
Ouch! You really know how to hurt a guy, Willis. I’m hardly defending what I did in a lighthearted way for an hour or two a couple of days ago, it was just that the fit resulted in a rather good estimate of both the rough time of the beginning of the rise (some 200 years ago) and the rough level of the background CO2 level (about 260 ppm). Then it turned out, as RGBrown noticed above, that the residuals were on the order of 1 ppm, two orders of magnitude below the CO2 levels. Finally, the residuals may be conveying some information to us, which several people above have tried their hand at interpreting. For example, the single almost pure spike occurred in 1998, contemporaneous with the super El Nino and the temperature spike. Without the “meaningless” model, one would not see the departures from the model, which could provide clues to the underlying physics. For example, there appear to be some sort of annual-to-decadal cycles visible in the residuals.
That said, I have no argument at all with those who have correctly noted that other approaches can provide equally good fits. Presumably Bart’s coupled differential equation model, Willis’s sigmoid, Brown’s model with a main monotonic curve plus a small noise term, Koustoyannis’ Hurst-Kolmogorov statistics arising from stochastic step functions followed by trendless noise, P. Solar’s three-exponential model, can all fit the data equally well, and I would expect them all to show the exact same behavior of the residuals that was shown by both the quadratic and exponential models I used. If so, then there is something that the common “noise” afflicting all these models is trying to tell us about the underlying physical reality.
Lance,
I have been statistically curve fitting most of the avialable climate data for several years. Most recently I have worked with the Scripps column 10 CO2 and 13CO2 data monthly averages from the South Pole to Alert, Canada. I included global anthropogenic emissions in these regressions. This analysis indicates less than 10% anthropogenic contribution added onto a rising segment of a 200 year natural cycle. Take a look at http://www.retired researcher.wordpress.com. So far I have had no peer reviews of this work. Only one comment so far. With all the smart people that visit this site, I expected more.
Just learned about Julian Flood’s theory the Kriegesmarine Effect with a temperature spike at the same time as the CO2 in upper troposphere and stratosphere spike in the Beck paper I posted.
http://wattsupwiththat.com/2012/06/03/shocker-the-hansengiss-team-paper-that-says-we-argue-that-rapid-warming-in-recent-decades-has-been-driven-mainly-by-non-co2-greenhouse-gases/#comment-1000669
Carrick says: June 3, 2012 at 11:03 pm
Sorry Carrick,
First, you totally miss the point of the urban CO2 readings – it’s about Ferdinand’s mass balance argument, which fails not only on a seasonal basis but even on a daily basis, imo.
Your conclusions are technically wrong because you have not taken the time to understand the issues. You are missing one or more steps in the process of Read, Think, Write.
Your comment on the 2 month lag is just plain wrong on several counts. Look carefully at my original graphs in my 2008 paper. All the original data is in Excel sheets there.
The C14/13/12 issue has been done to death here at WUWT and elsewhere (by Roy Spencer and many others) – Google it.
Finally, your condescending tone demeans you. Forgive me for responding in kind.
Yet another attempt at getting a frigging image into this blog.
http://imagebin.org/index.php?mode=image&id=215058
http://imagebin.org/index.php?mode=image&id=215060
Lance Wallace:
At June 4, 2012 at 3:20 am you say:
I notice that you do not mention my post at June 3, 2012 at 2:31 pm which says
Each of our models matched each annual value of atmospheric CO2 concentration indicated by the Mauna Loa data to within the measurement accuracy of the Mauna Loa data. So, none of them have any “residuals” or “noise”. This was explained in the link.
But our three basic models each assumed a different mechanism dominates the behaviour of the carbon cycle. And they can each be used to emulate a natural or an anthropogenic cause of the rise in the Mauna Loa data.
Hence, our findings falsify your suggestion that “there is something that the common “noise” afflicting all these models is trying to tell us about the underlying physical reality”.
Richard
PS Our pertinent paper is
Rorsch A, Courtney RS & Thoenes D, ‘The Interaction of Climate Change and the Carbon Dioxide Cycle’ E&E v16no2 (2005)
Carrick – Here are just a few C13/C12 articles I found in 2 minutes of searching – there are many more.
http://wattsupwiththat.com/2008/01/28/spencer-pt2-more-co2-peculiarities-the-c13c12-isotope-ratio/
http://wattsupwiththat.com/2008/01/25/double-whammy-friday-roy-spencer-on-how-oceans-are-driving-co2/
http://chiefio.wordpress.com/2009/02/25/the-trouble-with-c12-c13-ratios/
Myrrh says:
June 3, 2012 at 5:13 pm
Despite the low data density, the CO2 contour in troposphere and stratosphere confirms the direct measurements near the ground that suggest a CO2 maximum between 1930 and 1940.
Myrrh, I have had a lot of discussions with the late Ernst Beck about the validity of his data. The tropospheric data don’t confirm the direct measurements on the ground, simply because these were sometimes hundreds of ppmv higher than near ground. Shows that the data are completely useless. Unfortunately so. That is also the case for most data which show the 1942 “peak”, mostly taken at places with a huge diurnal variation and extreme variation. That alone already shows that the data are highly contaminated by local sources.
The data at Mauna Loa are sometimes contaminated by local sources too, but not more than +/- 4 ppmv, compared to e.g. Giessen where the longest 1939-1941 series was taken with a variability of 68 ppmv (1 sigma!). How can one deduce a “global” signal from such a series?
Correction. http://www.retiredresearcher.wordpress.com
Allan MacRae says:
June 4, 2012 at 4:05 am
First, you totally miss the point of the urban CO2 readings – it’s about Ferdinand’s mass balance argument, which fails not only on a seasonal basis but even on a daily basis, imo.
The mass balance must be always obeyed, no matter what happens where. But that is only calculatable on a yearly basis, as we only have yearly inventories of the emissions. Urban readings anyway are irrelevant for the mass balance, as are all readings in the lowest few hundred meters above land. That represents only 5% of the air mass where the CO2 is not well mixed due to a lot of local sources and sinks. In the rest of the global air mass, the yearly averaged measurements are all within 2 ppmv for the same hemisphere and 5 ppmv between the hemispheres, where the SH lags the NH but the trends are exactly the same:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/co2_trends_1995_2004.jpg
Allan MacRae says:
June 4, 2012 at 5:08 am
Carrick – Here are just a few C13/C12 articles I found in 2 minutes of searching – there are many more.
Allan, I am afraid that Dr. Spencer was quite wrong with his article and I have commented there extensively and on his blog, by mail, which he published. It is clearly not his field. The main problem for the origin of the d13C decline could be the release by biomass degradation, but the oxygen balance shows that total biomass is growing…
Other main sources of low 13C are either too small (or also mainly of human origin like CH4), or unknown, but there is no reason to assume that these started to emit increasingly together with the human emissions. For underwater volcanoes: that CO2 is captured by the deep oceans in the deep oceans, which are near zero per mil d13C.
Jeeeuz! Does anyone have any idea what is going on with these friggin pastebin services today. ?
Are they rigged to ban their use from WUWT or what ?!
The last link I posted just returns an empty page , not even your basic empty html tags, Just sweet F.A.
The same link works fine locally and if I open the link in a new tab (still blank at first) then I do refresh , finally I get to see my image.
Now that looks to me like they must be checking HTTP_REFERRER and if it is this site they refuse to serve the image.
Someone care to check that?
http://imagebin.org/index.php?mode=image&id=215058
http://imagebin.org/index.php?mode=image&id=215060
If I’m going quietly mad it would be handy to have so confirmation too, then I can go and seek treatment 😉
FerdiEgb says:
June 4, 2012 at 1:06 am
“…the temperature was below your baseline for the full period 1900-1935, average -0.2°C.”
The impetus to CO2 is approximately proportional to dT + 0.5, where dT is the temperature anomaly relative to whatever the baseline is in the data. At no time in the modern era or even a little before would that quantity have been negative or zero. In fact, it suggests that CO2 will keep rising for some time to come, until long term limiting factors kick in.
The rest of your post is an appeal to magick.
P. Solar says:
June 4, 2012 at 8:49 am
You’re not mad. The images are not coming through.
Lance Wallace says:
June 4, 2012 at 2:38 am
“…but didn’t see what values you obtain for tau2 or the other parameters and wondered whether you cared to present the values here and perhaps comment on their interpretation.”
tau2 is only required to be large relative to the record length, so that the “equilibrium” level of CO2 (the level to which the current temperature is driving it) will be approximately the integral of the temperature anomaly over the relevant time interval. I need not have put in a term involving it at all to match the data, but there must be some ultimate limit to the equilibrium value, and a time constant is one way of enforcing one. For this exercise, I simply set the feedback gain to zero (tau2 = infinity).
The value of k2 is 0.2 and the value of To is 0.5. These were chosen to be consistent with the data.
The value of k1 was chosen to be 0.5. This is consistent with the IPCC insistence that roughly half of the emitted CO2 is almost immediately dissolved in the oceans. As you can see, I tried a variety of values for tau1, with the most realistic ones being on the order of 3 years or less to be consistent with the data. With such values of tau1, the contribution from H becomes negligible, so the value of k1, which must be less than or equal to one in any case, is fairly moot.
In the last figure you can see the decline of industrial production after 1990 in the former East Block.
Ferdinand, thanks for taking the time to respond to Allan’s comments. That was helpful for me at least. (I don’t claim to be an expert, nor do I choose to argue as if I were, on this topic.)
Allan, I suspect you know full well my comments weren’t intended in a condescending manner (though your original one and your responses clearly were), I suggest that you read here. I’d suggest there’s quite a bit left for you to learn before you can argue as an expert on the matter of atmospheric measurements in general, and CO2 isotopic measurements in particular.
Bart:
From your experience, I assume you are referring to the thread on McIntyre’s blog as that and Nick’s blog where you repeated the same errors are our only real brush.
I’ll let others judge who came out on top on that discussion. 😉 You are the one who claimed you can’t have negative delays in an impulse response function and confused physical causality with signal causality, not me.
Since your experience of me making “elementary errors” is so great, I’m sure you can point to one or two of them from those threads (and maybe including your admission after approximately 50 ad hominems from you, I didn’t count them, but I should have, that you were wrong).
if you take the derivative of a function, say I(tau), if I(tau) = 0 for tau < 0, then I'(tau) = 0 for tau < 0. Taking derivatives in general does not induce a group delay, phase shifts are different than temporal shifts.
This is a bit of a red herring. You were plotting derivative of CO2 against temperature, I showed that there was a delay both computationally and confirmed it with a visual plot.
But in any case, centered average can splatter some high frequency noise into negative time bins, but it doesn’t shift the low-frequency components, and you can still deduce the delay using that. (Or directly numerical as I also did.) The fact the two agree shows your argument doesn’t matter.
If you want to make an argument using an other quantity such as S_CO2, you should make it based on that quantity, not using a quantity that doesn’t show what you claim to be arguing.
P. Solar:
It’s the fact that CO2 changes that causes the forcing. I wouldn’t have plotted it the way Bart did, but that’s how he did it, and that’s why I addressed the delay the way I did.
I expected the delay for the “fast” response to be about two months, because I had previously computed it for S_CO2 versus global mean temperature. I realized from that analysis that you needed better resolution than one month to pull out the actual delay (because it’s between one and two months).
There is a real physical effect as you correctly pointed out relating to response of the oceans to atmospheric temperature in which as the temperature rises, CO2 comes out of solution in the ocean. However, there is a rather large delay associated with that, and it’s not impulsive, because there is a latency that depends on depth in the response of mean ocean temperature to forcings from atmospheric temperature. It’s on the order of years.
I knew from previous discussions that any effect where you see near simultaneous response of atmospheric temperature and atmospheric concentration of CO2 can’t be explained by CO2 dissolution from the ocean. So what Bart was showing wasn’t based on a physical understanding of the processes and his conclusions were unphysical.
(He’s not really big on admitting mistakes so don’t expect a “recall” of this theory of his anytime soon, in fact, even when he makes a mistake, it sounds like “We were both right…” even when he was completely wrong.)
You may have heard of 350.org.
Well here I am with 500.org.
Anything to try and soften the inevitable coming macro decline. But even 500 will be a mere band aid against massive forces.
Carrick says:
June 4, 2012 at 10:42 am
“but it doesn’t shift the low-frequency components”
Switch to a twelve month average, and see how your argument holds up.
“You are the one who claimed you can’t have negative delays in an impulse response function and confused physical causality with signal causality, not me.”
Obviously, you cannot have real negative delays, just apparent ones indicated by the particular analysis tool. And, I showed your argument was inapplicable to the case at hand. As was Nick’s criticism. I was right about the transfer function, and remain so to this day.
Yes, I jumped to a conclusion about a negligible matter (because you were being such a —-) but quickly came clean about it and put it aside. You should take a lesson from that experience – it does you no good to argue an untenable position into the ground. The best thing to do is come clean about it and move on to more substantive issues. There is a quote attributed to the great British economist Sir Maynard Keynes, who was known to change his positions, sometimes in mid-argument. When challenged on this by a critic, he fixed him with an unwavering stare and replied: “When I find that I am wrong, I change my mind. What do you do?”
Here is some advice: when you find yourself holding the absurd position that temperature responds to the rate of change of CO2… stop digging. Your arm-waving here merits no further response.
Carrick says:
June 4, 2012 at 10:59 am
“I knew from previous discussions that any effect where you see near simultaneous response of atmospheric temperature and atmospheric concentration of CO2 can’t be explained by CO2 dissolution from the ocean.”
You aren’t looking at “atmospheric concentration of CO2”. You are looking at its derivative. Do you know the differential (pun intended)?
You are wrong. Ridiculously, uproariously, hilariously so. Admit it, and move on, and people will think better of you.
Bart says:
June 4, 2012 at 9:25 am
FerdiEgb says:
June 4, 2012 at 1:06 am
“…the temperature was below your baseline for the full period 1900-1935, average -0.2°C.”
The impetus to CO2 is approximately proportional to dT + 0.5, where dT is the temperature anomaly relative to whatever the baseline is in the data. At no time in the modern era or even a little before would that quantity have been negative or zero. In fact, it suggests that CO2 will keep rising for some time to come, until long term limiting factors kick in.
OK, that is the “fudge factor” to match the increase rate and its variability. No problem with that. But still so, if the period 1900-1960 still was positive, I am quite interested how much CO2 that injected in the atmosphere (or how little there was at the beginning of the 20th century). And further back to the LIA which was, depending of the reconstruction, 0.3-1.0°C cooler than today. Still no problem for CO2 levels? Even further back: near 100,000 years of glacials…
The rest of your post is an appeal to magick.
I am sure that you are a very good theoretician, but sometimes one need to bring that kind of people back to the ground on their two feet. What you have worked out is theoritically magnificent, but there are some practical problems:
There is no natural process that I know of or ever heard of or ever read of that can deliver 70 ppmv (and according to your formula far beyond that in the future) in only 50 years, only based on a sustained increase of a few tenths of a °C.
If you think that is possible, please give an indication what process that might be with references.
FerdiEgb says:
June 4, 2012 at 6:15 am
Myrrh says:
June 3, 2012 at 5:13 pm
Despite the low data density, the CO2 contour in troposphere and stratosphere confirms the direct measurements near the ground that suggest a CO2 maximum between 1930 and 1940.
Myrrh, I have had a lot of discussions with the late Ernst Beck about the validity of his data. The tropospheric data don’t confirm the direct measurements on the ground, simply because these were sometimes hundreds of ppmv higher than near ground. Shows that the data are completely useless. Unfortunately so. That is also the case for most data which show the 1942 “peak”, mostly taken at places with a huge diurnal variation and extreme variation. That alone already shows that the data are highly contaminated by local sources.
Ferdinand we’ve been through this argument before – your premise begins with belief in “well-mixed global” so everything you see as out of the ordinary is “local contamination” – but, again, until you can show how Keeling arrived at his “well-mixed” claim then all that exists in reality is local.
AIRS data found that; the pictures they showed downplayed what they actually said in their conclusion – that to their astonishment carbon dioxide was not at all well mixed, but lumpy, and so couldn’t be playing any major role in ‘global warming’, and, that they needed to go and understand wind systems to get a grasp of what was going on.
There is no, none, zilch, nada, eff all, way that Keeling could establish such a thing as “well-mixed” background level from where he was measuring. It is simply not physically possible to tell apart even if such a creature existed as “well-mixed global”. He was measuring local and they are still measuring local, arbitrarily deciding what local they will include and what not to present this mythical “well-mixed global”.
I have shown you the man had an agenda, his only interest was to show a rise in man-made CO2 levels – so his curve. You may well be shocked by the enormity of what it takes to link all those stations into his and Callendar’s avowed agenda, but as we’ve had reams and reams of proof, this is done regularly and with coordinated exactness in manipulating world temperature records.
I’m sorry Ferdinand, you may well trust this, but nothing I’ve learned about it shows Keeling and Callendar as anything but cherry pickers who came up with the unproven idea that there is such a thing as “well-mixed background”. AIRS did not find it. AIRS will not release top of troposphere or bottom of troposphere, why not?
Because they can fudge the mid troposphere regardless they came out with the HONEST conclusion that “it was not at all well-mixed, but lumpy” and was “insignificant in global warming”.
It’s lumpy, because, it’s all local.
All you’re doing is what Callendar did, taking out everything that doesn’t fit your unproven premise.
And you believe it because they kept repeating that it exists. What that means to all the hard and dedicated work you’ve built on it, I can only imagine, but first prove “well-mixed background” exists, because Callendar showed not such thing in his cherry picking:
“Considering Figure 8 we can see that Callendar selected only the lowest sample values and omitted several data sets.”
The data at Mauna Loa are sometimes contaminated by local sources too, but not more than +/- 4 ppmv, compared to e.g. Giessen where the longest 1939-1941 series was taken with a variability of 68 ppmv (1 sigma!). How can one deduce a “global” signal from such a series?
As above, their adjustments are arbitrary, there is no physics that can separate a supposed ‘global’ signal from local production. There is no global signal, it’s all local. Global is lumpy.
There’s a huge amount of data of this lumpy CO2, which, is fully part of the Water Cycle, and which, is one and a half times heavier than air so will always sink displacing Air without work being done – either way, however high it gets it will come down to Earth where plants exist waiting for it…
And, because it is heavier than Air is will not readily rise into the atmosphere. It takes wind, or heat as gases expand, or as it joins with water vapour rising into the cold heights as carbonic acid where it condenses into rain releasing its heat in the cold heights, or, it can be expelled direct into the heights by volcanic force, or planes. And all that within the wind systems, which do not cross the equator but stick to their own hemispheres, winds are volumes of Air on the move because of the difference in temperature, pressure – hot air rises and cold sinks – this is convection, exactly what happens in a classroom when a bottle of scent is opened… There is no “spontaneous diffusion of molecules into empty space” – Air is not empty space. That’s why we have sound, because the molecules don’t “spontaneously diffuse as per ideal gas law” – but vibrate where they are making their neighbour volumes of gas vibrate passing on sound, and then stop vibrating.
All this to show, there is no physics which makes “well-mixed global background”. That premise has to be rejected, or empirically and by real physics proved..
Myrrh,
If you look at the at the raw event flask data, you will find many spikes in the CO2 data that are flagged and not included in monthly averages. Most of these spikes are not errors because there is usually a corresponding spike in the 13CO2 data. The recorded monthly averages represent background levels that vary with latitude but not longitude. I think that cold water in clouds is absorbing the CO2 and transporting it to the upper atmosphere and the poles.This process is moderating the measured concentration near the surface and gives the appearance of “well mixed”.
Also, it can explain the higher concentrations in the upper atmosphere in the mid latitudes. The equator is the source and the cold water near the poles are the sinks.
Looks a lot like the growth curve for human population. Try fitting one on top of the other. Good fit eh? Not surprising. We all make our little contribution.
Bart:
You’re the one who was originally looking at dS_CO2/dt versus HADSST and now I’m wrong.
LMAO. Sure.
Well, I have worked out the simplest formula of all to mimic the CO2 increase in the atmosphere. That is just a start, based on yearly averages for temperature and CO2 levels, so that may need fine tuning to monthly values and the coefficients need fine tuning too.
Here is the simple formula:
CO2(new) = CO2(old) + 0.55*emissions + 4*dT
That holds for any change in temperature, any period or any amount of emissions (the latter pure coincidence for the past 110 years…). Even ice ages and interglacials, but for longer periods the factor 4 for dT increases to a factor 8 (you know, that 800 year lag via the deep oceans…).
Here the plots:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/acc_der_temp.jpg
and
http://www.ferdinand-engelbeen.be/klimaat/klim_img/acc_temp_atm.jpg
Discussion: The first term is essentially the integral of Bart’s first formula:
dC/dt = (Co – C)/tau1 + k1*H
where k1 = 1 and H = emissions, C is the current CO2 level, Co the pre-industrial level at ~290 ppmv, the latter influenced by temperature, at a rate of about 8 ppmv/°C.
As the current difference is over 100 ppmv, a small shift in Co has little effect on Co – C and that change can be neglected for the current period. tau1 is large, so that only about halve H is removed, despite the large Co-C difference.
Co in my opinion is simply directly correlated with absolute temperature and not anomaly dependent. That is one difference with what Bart made. The other is that the except for the shift in Co, the influence of temperature on CO2 levels is constrained to temperature differences, with a finite amount and time duration. That means that for fast changes (1-3 years, ocean surface, vegetation), the influence is about 4 ppmv/°C temperature difference, while for longer time spans that increases to 8 ppmv/°C.
The essential difference with Bart’s solution is that except for the “equilibrium” setpoint, the influence of the emissions and the temperature influence on CO2 levels are completely independent of each other, where the temperature influence is mainly visible in the variability of the increase rate and around the trend, while the influence of the emissions is mainly visible in the average height of the increase rate and in the trend itself.
FerdiEgb says:
June 4, 2012 at 1:34 pm
“The essential difference with Bart’s solution is that…” Ferdinand’s solution does not match the derivative of CO2 to the temperature anomaly, as is clearly indicated by the data. Hence, Ferdinand’s model fails to reflect the real world.
Myrrh says:
June 4, 2012 at 12:41 pm
AIRS data found that; the pictures they showed downplayed what they actually said in their conclusion – that to their astonishment carbon dioxide was not at all well mixed, but lumpy, and so couldn’t be playing any major role in ‘global warming’
The CO2 data from AIRS looks lumpy, because their scale is only +/- 4 ppmv. If you see a variability of 2% of full scale, while about 20% of all CO2 goes in and out the atmosphere over the seasons, then I call that well-mixed. How much difference do you think that it makes for global warming (as far as there is) if you have 396 ppmv or 404 ppmv? It is the 100+ ppmv increase which may make the difference…
About Keeling: I have the highest respect for him. He was only interested in better CO2 measurements and devoted all his life on that one item, including the invention of new measurement methods of unprecedented accuracy and allowing continuous measurements. Read his autobiography for what obstructions he did overcome to continue the measurements at Mauna Loa and other stations against the administrations:
http://scrippsco2.ucsd.edu/publications/keeling_autobiography.pdf
I have not the slightest interest in complot theories that the CO2 data are manipulated in any way. I have controlled them from raw voltage data to what is openly archived. There is no manipulation. Or how can you convince hundreds of people involved from some 70 baseline stations (+400 others over land), from different countries, and different instutions to collectively and continuously lie about the data? Even the pensioners, that they still shut their mouth over such huge scientific scandal?
Please, it is not because you don’t like the data that they must be proven false at all cost, you only disprove yourself as a valid opposant on other items where the other side is not on such firm ground…
Bart says:
June 4, 2012 at 1:45 pm
Ferdinand’s solution does not match the derivative of CO2 to the temperature anomaly, as is clearly indicated by the data. Hence, Ferdinand’s model fails to reflect the real world.
Peanuts. If I should use the monthly values like you did, that would show a better match, but I can return the favor: your temperature influence doesn’t match the CO2 trend as good as the emissions:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/temp_co2_1900_2004.jpg
where a temperature change of halve the scale gives 5 ppmv change in CO2 levels, but the whole scale should give a 80 ppmv increase?
And:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/acc_co2_1900_2004.jpg
a near perfect match…
Thus we may agree that the temperature variation is a real world perfect match for the variability in increase rate, while the emissions are a real world perfect match for the trend itself. But I think that it is of more interest to know what the cause is of the trend than the cause of the variability of the increase rate…
BTW, I am still interested in your backcalculation to 1900 and over the LIA. For the latter you may use any recontruction, except Mann’s HS, for obvious reasons…
And already a process found which can deliver 70 ppmv CO2 with a a continuous elevated temperature of a few tenths of a degree C?
Bart and Ferdinand,
I submit my statistical model is a better fit than both and better satisfies mass balance. It includes both anthropogenic and natural sources. http://www.retiredresearcher.wordpress.com.
To Ferdinand Engelbeen /
Since there have been a number of recent posts/threads on CO2 and the Carbon cycle here at WUWT, I have been wondering when you might show up!
Re your comment @ 6/3 – 2:10 a.m.: You state in part, “The net result over very long periods is that an increase of 1 deg. C in ocean temperature gives some 8 ppmv increase in CO2. Thus the ~ 1 deg. C warming since the LIA gives at maximum 8 ppmv increase of CO2. But we see an increase of over 100 ppmv since the start of the industrial revolution…” I have always been impressed by this argument (which you often make) which turns on the observed (or better, reconstructed) glacial-interglacial temperature vs. CO2 relation. But I am somewhat puzzled by the 1 deg. C = 8 ppmv CO2 premise, for in that case then either (1) the resulting shifts in temperature increase and CO2 increase are significantly smaller than those reconstructed from ice cores, or (2) granted that the glacial-interglacial temp. increases at the poles were greater than the estimated globally averaged increases [5-6 deg. C], then during the G-IG transitions, CO2 was not at all “well mixed.” There may be something packed into the “ocean temperature” qualification you make, but even at or near the poles, I doubt that ocean temperatures increased nearly as much as ice cap temperatures. They were significantly warmer at glacial maxima to begin with. So, same problem. Does my concern make any sense?
FerdiEgb says:
June 4, 2012 at 2:30 pm
“…your temperature influence doesn’t match the CO2 trend as good as the emissions:”
Sure it does. You forgot to integrate, since it is the CO2 rate of change which is proportional to temperature.
fhhaynie says:
June 4, 2012 at 2:49 pm
I will have to look it over more carefully when I have a moment to spare. However, this plot is not something I think I agree with. As I believe CO2 is essentially controlled by temperature, I do not see “controls” making much difference.
…which is proportional to temperature anomaly.
I expect this post is well past its natural lifetime. One last comment. Integrating the exponential provides an estimate of the total amount of CO2 contributed to the globe since the rise began (around 1720 as predicted by the fit). By 1958, the total increase was 37,000 ppm-months. Conveniently enough, the super-El Nino of 1998 was almost exactly one half-life further on, and the total was 74,000. Now the total is 94,000. That is, since the temperature flattened out 14 years ago, the atmospheric levels have increased by the addition of 21% of all the CO2 added to it in the last 200 years. Yet the temperature is not cooperating. Where is the temp-CO2 correlation now?
Well, actually the increase was 27% of the total amount added by 1998, or 21% of the total to date.
Bart,
The ice core data indicates global temperatures fluctuate in several cycles of varying length. That 200 year cycle observed in the CO2 data could well be controlled by a 200 year temperature cycle with an unknown lag time. Some of the shorter less significant cycles are very likely temperature controlled. A cycle around 20 years is possibly related to ENSO.
P. Solar says:
June 4, 2012 at 12:24 am (emphasis mine)
Not even close, P. Solar, not even close.
Source
Note that per capita emissions have been dropping faster than total emissions, and that the population growth has been slowing down, and that population is due to stabilize by around 2050 …
Please, people, do your homework. It saves you from a host of miseries, not the least of which is people publicly correcting your errors.
w.
Willis,
Your input/output model should produce the best fit. Basically, it is what Ferdinand uses. The problem is that it does not seperate natural from anthropogenic emissions. Ferdinand assumes that natural net input/output is in “dynamic equilibrium” thus the net accumulation is all anthropogenic. Bart says that the natural changes in the input/output are so much greater than anthropogenic emissions that they make little difference. My analysis indicates that, at present anthropogenic emission rates, they are statistically significant, but account for less than 10% of the accumlation. http://www.retiredresearcher.wordpress.com.
http://www.nist.gov/data/PDFfiles/jpcrd427.pdf
solubility of co2 in water.
something i find quite odd- they rely on models a whole lot.
why would they do that when actual experiment is so easy and gives actual data?
Lance Wallace says:
June 4, 2012 at 3:20 am
My apologies, Lance, I was commenting on the analysis. The problem is that bad science done by skeptics diminishes the reputation of the blog as well as the reputation of all skeptics. In addition, I get busted all the time for not commenting on skeptical papers, since most of my analyses are of AGW supporting papers. So I try to come down equally hard on both sides.
The problem is that the rise in CO2 is just a bit off of linear, just slightly curved. As a result, you can fit a whole host of curves to it. If you do the statistics, you’ll see that the difference in how good the fit is tends to be very small. As a result, we have absolutely no information that would allow us to pick one curve over the other.
If you want to fit a curve, my suggestion is that you fit a curve with some physical meaning to it. The amount of CO2 remaining in the air can be very closely modeled by a sink which sequesters a few percent of the atmospheric excess amount each year.
For example you can use a time step equation
A(t) = E(t) + .968 * A(t-1)
where A(t) is the amount of the emissions remaining in the atmosphere in year t, E(t) is emissions in year t, and A(t-1) is the amount remaining in the atmosphere in year t-1.
To convert from ppmv to gigatonnes of carbon (GtC), multiply by 2.1838. This assumes a pre-industrial CO2 level in 1850. I’ve put an Excel spreadsheet up here to show how it can be done.
Using that, you can get a pretty good read on what will happen under various future scenarios, you put in the emissions, it will tell you the airborne CO2 concentration. I’ve included an example of freezing emissions at the 2005 level, you can put in what you want.
All the best,
w.
Allan MacRae says: June 4, 2012 at 4:05 am
First, you totally miss the point of the urban CO2 readings – it’s about Ferdinand’s mass balance argument, which fails not only on a seasonal basis but even on a daily basis, imo.
FerdiEgb says: June 4, 2012 at 6:26 am
The mass balance must be always obeyed, no matter what happens where. But that is only calculatable on a yearly basis, as we only have yearly inventories of the emissions. Urban readings anyway are irrelevant for the mass balance, as are all readings in the lowest few hundred meters above land. That represents only 5% of the air mass where the CO2 is not well mixed due to a lot of local sources and sinks. In the rest of the global air mass, the yearly averaged measurements are all within 2 ppmv for the same hemisphere and 5 ppmv between the hemispheres, where the SH lags the NH but the trends are exactly the same:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/co2_trends_1995_2004.jpg
_____________
You are missing the point Ferdinand. The SLC urban CO2 readings show that even a the typical SOURCE of manmade CO2 emissions (the URBAN environment), the natural system of photosynthesis and respiration dominates and there is NO apparent evidence of a human signature. If your premise was correct, you would see CO2 peaks at breakfast and supper times and the proximate (in time) morning and evening rush hours, when power demand and urban driving are at their maxima. This human signature is absent In the SLC data, and yet the natural signature is clearly apparent and predominant.
Similarly, in the AIRS animation I posted earlier, there is NO human signature and the power of nature is clearly evident. Here it is again.
http://svs.gsfc.nasa.gov/vis/a000000/a003500/a003562/carbonDioxideSequence2002_2008_at15fps.mp4
These are huge natural DYNAMIC systems that are apparently NOT impacted by the relatively small human contribution. Sadly, Nature apparently just ignores our humanmade CO2 emissions, as irritating as that must be for you.
I know you have made up your mind on this point Ferdinand, and nothing will shake your belief. Try watching the George Carlin video again – George gets it. 🙂
Here are a few more references on C13/12:
There are many more such references our there, Ferdinand – but no doubt you think Murry Salby is totally out of his depth too, just like Roy Spencer.
http://wattsupwiththat.com/2012/04/19/what-you-mean-we-arent-controlling-the-climate/
http://wattsupwiththat.com/2011/08/05/the-emily-litella-moment-for-climate-science-and-co2/
Here is your dilemma Ferdinand:
CO2 lags temperature at all measured time scales, and yet you insist that CO2 drives temperature.
You may be right and I may be wrong, but please explain to me again how the future can cause the past.
P. Solar;
Both those images work fine for me. But you misspelled “inferred” on the title line(s).
>:)
Bart says:
June 4, 2012 at 3:54 pm
Sure it does. You forgot to integrate, since it is the CO2 rate of change which is proportional to temperature.
And that is the problem:
The rate of change indeed is proportional to the temperature (change). But temperature near completely explains the variation in rate of change, not the whole rate of change.
Where it goes wrong is that, by scaling and offsetting the temperature, you attribute the total of the rate of change to temperature, including the part that is introduced by the scaling and offset. But there is nothing that allows you to attribute the bulk of the rate of change to temperature, as even if you detrend the whole bunch (and the integral is essentially zero), the correlation between temperature (change) and rate of change variation remains the same.
See:
http://esrl.noaa.gov/gmd/co2conference/pdfs/tans.pdf
page 14 and following,
Thus in my informed opinion, the bulk of the rate of change is caused by human emissions (at about twice the rate of change) while the variability of the rate of change is caused by temperature changes, (near) completely independent of each other.
Leigh B. Kelley says:
June 4, 2012 at 3:30 pm
The 8 ppmv/°C is based on the Vostok ice core, recently confirmed by the 800 kyr Dome C ice core:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/Vostok_trends.gif
The bulk of the variability around the trend is caused by the variable lag of CO2 vs. temperature: about 800 years during a glacial-interglacial transition, but several thousands of years during the opposite transition (therefore more deviation at the upper side than at the lower side). I didn’t compensate for the lags, that should have given even a better fit.
CO2 is already well mixed within a few years, thus as Vostok is a mixture of (about 600) years, that is no problem. The temperature is a proxy: either hydrogen (dD) or oxygen (d18O) isotopes are used. The origin of the isotope changes is mainly in the sea water surface temperature of where the water vapour of the clouds/snow/ice of the core originated and partly the temperature at the condensation place and the freezing pace. For more coastal ice cores like Law Dome, the bulk of the vapour originates from the nearby Southern Ocean, while for the high altitude, inland ice cores like Vostok and Dome C, most originates from a wide area all over the SH. Thus in general, the temperature proxy of Vostok reflects the whole SH oceans…
There may be some problems if the NH showed a different behaviour, but besides some shifts in the start and other episodes of the glacial/interglacial events, the NH behaves quite similar as the SH.
Another confirmation of the around 8 ppmv/°C is in Law Dome:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/law_dome_1000yr.jpg
There is an app. 6 ppmv drop in CO2 around 1600, at the coldest part of the LIA. Law Dome can not be used as global temperature proxy (it is regional, but see the current discussion at ClimatAudit), so we need to compar that to one of the “spagetthy” reconstructions of global temperature over the past 1,000 years. I compared it to these with the highest MWP-LIA difference (Mann’s HS has the lowest difference) like Esper, Moberg,… which show a change of ~8°C over the time span of interest, which brings us again to around 8 ppmv/°C.
There are several other proxy ranges for the CO2/temperature ratio, the full range is, if I remember well some 4-20 ppmv/°C. But it seems to me that the ice cores in this case gives the best, at least hemispheric answer.
A constraint on the upper bound is the change introduced by ocean warming: any warming of the ocean surface (including the upper 700 m, the “mixed layer”) gives according to Henry’s Law an increase of 16 microatm of the pCO2 at the surface. Thus an increase of ~16 ppmv in the atmosphere is sufficient to compensate for that. But as at the other side vegetation works harder at higher temperatures (and increased precipitation), the average increase would be lower when everything again is in dynamic equilibrium…
Ferdinand Engelbeen says: June 5, 2012 at 1:51 am
“Thus in my informed opinion, the bulk of the rate of change is caused by human emissions (at about twice the rate of change) while the variability of the rate of change is caused by temperature changes, (near) completely independent of each other.”
____________
Comment to Bart:
It is possible that Ferdinand is correct and I am wrong (but I really doubt that).
Ferdinand is correct in that the short-cycle derivative dCO2/dt apparently does not significantly impact the trend of the overall CO2 versus temperature relationship – it just explains the “wiggles” in that trend.
The question is what primarily causes what – does atmospheric CO2 drive temperature or does temperature drive CO2? Do current humanmade CO2 emissions significantly increase atmospheric CO2, or are they “lost in the noise” of the much larger dynamic natural system?
My contention is, adapting Ferdinand’s wording:
“ the bulk of the rate of change is NOT caused by human emissions, BUT IS A RESULT OF ONE OR MORE LONGER-TIME NATURAL TEMPERATURE CHANGE CYCLES, CONSISTENT WITH the SHORT-TIME-CYCLE variability of the rate of change THAT IS ALSO caused by temperature changes.”
I prefer my hypo because
1. My hypo is more consistent with Occam’ s Razor – whereas Ferdinand’s hypo requires opposing trend directions at different time scales in the system, mine does not, such that all trends are consistently in the same direction (temperature drives CO2) at all time scales.
2. My hypo is consistent with the fact that CO2 lags temperature at all measured time scales, from an ~800 year lag on the longer time cycle as evidenced in ice cores, to a ~9 month lag on the shorter time cycle as evidenced by satellite data.
3. I have yet to see evidence of a major human signature in actual CO2 measurements, from the aforementioned AIRS animations to urban CO2 readings ( although I expect there are local data that I have not seen that do show urban CO2 impacts, particularly in winter and locally in industrialized China.)
The impacts on humanity of these two opposing hypotheses are significant:
If Ferdinand’s hypo is correct, we will likely see a little more global warming – not the catastrophic warming of the IPCC scenarios (driven by ridiculously high “climate sensitivity” and positive feedback assumptions), but a modest warming that will actually be (net) beneficial to humanity and the environment, imo.
If I am correct in my overall assessment (and not just this hypo), we are likely to see some global cooling, which may be moderate or severe. Historically, humanity has done very poorly during periods of severe global cooling. For example, many millions starved in Northern countries circa 1700, during the depths of the Little Ice Age and the Maunder Minimum.
The implications of the current obsession with global warming mania is that, ironically, society will be unprepared should a period of global cooling occur.
During the last period of global cooling, tens of thousands of innocent people were burned as witches, in many cases because they were accused of causing the cold weather that devastated crops and resulted in widespread starvation.
If there is another period of severe global cooling, I would not like to be one of the many climate scientists who has profited from stoking the fires of global warming hysteria.
Allan, you are right, 100%….. My new paper on 4 longterm global
warming/cooling mechanisms will show it for over a 10,000 years.
time frame….It is all just a matter of a few more months…JS
Shyguy says:
June 3, 2012 at 12:26 am
Looks to me like the co2 records got corrupted just like everything else the ipcc get it’s hands on.
Dr. Tim Ball explaining:
http://drtimball.com/2012/pre-industrial-and-current-co2-levels-deliberately-corrupted/
///////////////////////////////////////////////////////////
I am sceptical of the reasons justifying the ignoring of this old experimental data and what it tells us of 19th and early 20th century CO2 levels.
It would be interesting to repeat those old experiments using the same location, same time of year, same equipment and same methodology etc and see what results are achieved today.
Not even close. Spaghetti.
Leigh B. Kelley says:
June 4, 2012 at 3:30 pm
Sorry, mistake on the MWP-LIA difference which was 0.8°C in several reconstructions, lucky for our ancestors (and us), not 8°C…
Allan MacRae says:
June 4, 2012 at 7:38 pm
You are missing the point Ferdinand. The SLC urban CO2 readings show that even a the typical SOURCE of manmade CO2 emissions (the URBAN environment), the natural system of photosynthesis and respiration dominates and there is NO apparent evidence of a human signature.
Depends where and when you measure… Mauna Loa had problems with local traffic CO2 when that increased over the years, until they banned all traffic there. And have a look at the data from Diekirch (Luxemburg), in a shielded valley with forests + urban + small factories:
http://meteo.lcd.lu/papers/co2_patterns/co2_patterns.html
Especially Fig. 12 for the differences between Sunday and weekday pieks during rush hour…
Of course the human signal is small (about 3%) compared to the diurnal and seasonal fluxes. But that is only important if the natural fluxes are in unbalance and add or substract some net amount of CO2. Well, it is proven that nature as a whole substracts CO2 from the atmosphere: each year in quantity about halve what humans emit. Thus momentary measurements near huge sources and sinks don’t tell you what happens in the total atmosphere, but a lot of stations and airplanes and ships surveys and nowadays AIRS in the “wel mixed” atmosphere do.
To make a comparison:
You have a fountain where the water is pumped out of a bassin and recirculates back in the bassin. The fountain has some computerised valve system which regulates the height of the fountain from 60% to 100% height on a regular basis. The maximum flow over the fountain is 1000 liter per minute. Now someone opens a small supply into the main waterflow at 10 liter per minute, he goes away on another job and forgets that the was adding water.
The extra supply is only 0.1% of the maximum flux. That is practically unmeasurable in the huge 40% change of the main waterflow. But will we have an overflow of the bassin sooner or later, or not?
Further, I missed the end of April discussion, as I was travelling through West-Australia, but I have intensively discussed at the Salby discussion last year, read my comments there again…
http://wattsupwiththat.com/2011/08/05/the-emily-litella-moment-for-climate-science-and-co2/
Here is your dilemma Ferdinand:
CO2 lags temperature at all measured time scales, and yet you insist that CO2 drives temperature.
Well, it was true until 1850 that temperature dictated the CO2 levels with different lag times, but since 1850, the CO2 levels were increasing far beyond what the temperature shows. At the current temperature, CO2 levels should be 290-300 ppmv. but the counts are ticking up and we reached near 400 ppmv already. Thus at this moment CO2 is leading with 100+ ppmv… Still temperature swings cause (a few months) lagged swings in the CO2 rate of change, but that are swings around the trend, not the trend itself.
Thus at this moment the CO2 levels lead the temperature to a far extent. If that will have a huge impact on temperature, that is an entirely different question. My opinion is that the inpact will be small (around 1°C), hardly a problem and mainly beneficial. But my fear is that opposing every single bit of what climate research shows, even based on solid evidence, works contraproductive for where the skeptics are right.
Allan MacRae says:
June 4, 2012 at 7:38 pm
No use, Allan. I have demonstrated in excrutiating mathematical detail that Ferdinand’s “mass balance” argument is completely bogus. It made no dent in his armor.
Ferdinand Engelbeen says:
June 5, 2012 at 1:51 am
“…the correlation between temperature (change) and rate of change variation remains the same.”
You cannot arbitrarily detrend the data. The slope of the temperature is what produces the curvature in the accumulated CO2, and it matches exactly. That leaves no room for a significant human influence.
Allan MacRae says:
June 5, 2012 at 5:15 am
“It is possible that Ferdinand is correct and I am wrong (but I really doubt that).”
I have addressed this issue at several points in this thread, e.g., here, and here, and here.
fhhaynie says:
June 5, 2012 at 6:34 am
“My analysis indicates that, at present anthropogenic emission rates, they are statistically significant, but account for less than 10% of the accumlation.”
My estimate is between 4% and 6%.
“I have addressed this issue at several points in this thread…”
First link should have been here.
Gah! Here.
Ferdinand @ 6/5 – 3:23 a.m.
Thank you for your reply. After rereading my post of yesterday, I was appalled. It seems that after years of relative isolation in rural Montana, my writing style has devolved into an amalgam of Kant (in the Critique of Pure Reason) and Henry James (in Wings of the Dove), with the piercing clarity of Hegel thrown into the mix!
Some of my puzzlement remains. Using the first graph you linked to, we have a range of ~187 ppmv CO2 to ~292 ppmv CO2 and ~ -9.5 deg. C to +3 deg. C for temp. These give total dCO2 of 105 ppmv and total dT of 12.5 deg. C. Using your hypothesized 8 ppmv CO2 per 1 deg. C, we have 105 ppmv / 8 ppmv = 13.125 deg. C dT, reasonably close to the ~12.5 deg. C I eyeballed from your graph. Here is my problem. Whether the temperature change is referred to the “nearby Southern Ocean” (presumably at very high latitude) or to the entire SH (mostly to the oceans); and whether it is referred to the change in SST or to the entire 0-700 m mixing layer, this sort of temp. change for/in the ocean seems confoundingly large (at least to me). I note that you qualify the processes contributing to the ice core(s) dT by adding where the condensation takes place and what the freezing pace is, but still… I got similarly high dT’s using the 8 ppmv per 1 deg. C formula for other G-IG transition dCO2 increases ranging from 180-300 ppmv to 200-260 ppmv for dCO2. It seems that there has to alot to this “place of condensation” and “freezing pace” business. Please throw me a line!
richard verney says:
June 5, 2012 at 5:54 am
I am sceptical of the reasons justifying the ignoring of this old experimental data and what it tells us of 19th and early 20th century CO2 levels.
There were two problems with the olde data: first the methods. Some were really bad (accuracy +/- 150 ppmv, but intended for measuring CO2 in exhaled air, still OK with such accuracy), the better were +/- 10 ppmv, good enough for average measuring, but even the seasonal swings are hard to detect.
The main problem is where was measured: Some series were from mid-towns, within forests, some at the coasts, some on seaships. It may be clear that measuring one or a few samples per day at a place where the diurnal variation may be a few hundred ppmv is not really representative for the CO2 levels of that time in the bulk of the atmosphere…
Those measurements that were made on seaships and at the coast, with seaside wind, all are around the ice core measurements.
The modern measurements, invented by C.D. Keeling and used since 1958 at the South Pole and Mauna Loa has an accuracy of +/- 0.2 ppmv and is fully continuous. The calibration happens each hour to maintain the accuracy.
It happens that we have some interesting data from a modern station near Giessen, Germany, near where the longest historical series in the period 1939-1941 was taken. The old data show a variability of 68 ppmv (1 sigma). Have a look at the diurnal variation from the modern station near Giessen, compared to baseline stations (Mauna Loa, Barrow and the South Pole), all raw data:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/giessen_background.jpg
The historical sampling in Giessen was 3 times a day, of which the morning and evening samplings were on the flanks of the highest changes…
Thus, unfortunately, most of the historical measurements can’t be used to know the real background CO2 levels of that time.
This keyboard is cursed. The first link where I explained why the derivative information is dispositive was here.
Friends:
This thread has become an ‘angels on a pin’ discussion with various participants each asserting that their model of carbon cycle behaviour is right (so everybody else is wrong).
I remind that I began my post on this thread at June 3, 2012 at 2:31 pm by saying
I repeat the important question is
Why don’t the natural sequestration processes sequester all the emissions (natural and anthropogenic) when it is clear that they can?
Nobody has addressed that question although Allan MacRae (at June 4, 2012 at 7:38 pm) touches on it when he writes
Exactly so.
But that takes us back to my question.
It rephrases my question as being,
Why does the system behave as it does when it could easily sequester all emissions and when it does sequester the local anthropgenic emissions?
At June 5, 2012 at 5:15 am, Allan MacRae asserts that the answer is the observed increase in atmospheric CO2 emission is a delayed response to global temperature rise over the past century.
I admit that I think he is right but I point out that the change could be in part or in whole the anthropogenic emission. I explain this as follows.
The carbon system may be adjusting to a new equilibrium in response to a change such as the temperature rise, the anthropogenic emission, a combination of those two effects, and/or something else.
The rate constants of some processes of the carbon system are very slow so they take years or decades to adjust. Hence, any change causes the system to adjust towards a new equilibrium which it never reaches because the system again changes before the new equilibrium is attained.
As I said in my post at June 3, 2012 at 2:31 pm and repeated in my post at June 4, 2012 at 5:05 am, using that assumption
ref. Rorsch A, Courtney RS & Thoenes D, ‘The Interaction of Climate Change and the Carbon Dioxide Cycle’ E&E v16no2 (2005)
The real issue is that the Mauna Loa data is little different from a straight line relationship with time. Hence, almost any model with two or more variables can be tuned to match the Mauna Loa data to within the measurement error (n.b. to a perfect fit to each datum).
Hence, arguments which amount to “My model works so it must be right” get nowhere: a wide variety of models ‘work’.
I again repeat, the important question is
Why don’t the natural sequestration processes sequester all the emissions (natural and anthropogenic) when it is clear that they can?
Richard
Cause and effect suggests that CO2 is driving temperature change, and what we’re looking at here is predominately the “fast response” of climate to changes in CO2.
I’m guessing that Bart never tested the lag when he made this claim:
I already pointed this out, in detail, on another thread where many things were discussed including the ability of his own model to fit variable contributions of CO_2 to the final growth in concentration without losing the correlation between temperature fluctuations and the derivative of CO_2 concentration (which I demonstrated numerically and posted the code for). Richard Courtney also commented that he has successfully fit multiple models to the CO_2 data within the error bars on the data, making it difficult to use pure “agreement with the data” to resolve differences between models.
However, Bart had an answer for the “lead/lag” problem in that discussion. I haven’t (I admit) gone all the way back to the raw data to investigate the claim, but he alleges that the order inconsistency is due to the fact that his curve uses 24 month running averages, so (one presumes) certain fluctuations can cause dCO_2/dt to run up before T. However, one would have to look at the raw data to see if in fact this is what is happening, and I have not done so. It could equally well be the case that the raw dCO_2/dt data is leading the T data — statistically, this is the most likely possibility simply because of the very sharpness of the correspondence, the very thing he argues for to make his case. The fluctuations match shape at a derivative granularity of the minimum time step size, or very nearly so, making it unlikely (in my own opinion) that this as an artifact of smoothing. But I am not sure, and unless/until you recompute the running averages on different timescales you will not be sure either. I’m too busy to do this, but woods for trees does make it pretty easy to do it, so play through.
Second, because sometimes dCO_2/dt leads T, and sometimes T leads dCO_2/dt (or they are closely synchronized) it is also important to bear in mind that inferring causality from correlation is weak in both directions. A better explanation is that both of them are being driven by a third variable, with a differential and somewhat random lag. For example, global atmospheric temperatures and fluctuations in CO_2 concentration could both be driven by global SSTs, or even local SSTs in only e.g. the south central pacific. Or by variations in cloud based albedo. Or by seasonal business and heating energy consumption in east asia. Or by space aliens, who are heating the Earth with an invisible heat ray that uses dark energy beamed from a secret base on the Moon to cause global warming with the intent of making us extinct in a couple of hundred years (no hurry, their colonization party is en route and the trip will take them a half century or more).
But exotic speculations aside, I think the fairest response so far is Richard’s. There are many models, with very different presumed underlying causal mechanisms, that CAN fit the CO_2 data. Some of those models make the bulk contribution come from anthropogenic sources — and work well enough to describe the data within error bars. Some models (like Bart’s) make the bulk contribution come from temperature-dependent shifts in e.g. chemical equilibrium in global sources and sinks that regulate the base atmospheric CO_2 concentration almost completely independent of what humans contribute.
In both cases there is some weak evidence confounding the simple explanations, but we simply lack objective, model-assumption free measurements from real data of the presumed processes that would permit us to conclusively favor any model over all the others (and in a complex system like the planet, may never obtain the needed information because the true model may NOT be simple, or simplifiable — it may involve solving a double coupled nonlinear Navier-Stokes problem on a global scale with intimate coupling of source and sink chemistry to local non-Markovian state, so that all of the fluctuations and variation we see is the “accidental” correspondence of a complex nonlinear system with one of the many variables that drive it that a momentary shift to a different Poincare cycle will then confound. We might just lack the long time scale data (with a sampling density and precision sufficient to be useful) to resolve the question, and might not HAVE it for a century or more of “modern” precision measurements at a still final granularity than the network of SST buoys or weather stations permits at present.
Given this, it is entirely plausible that Bart is correct. It is entirely (but somewhat less) plausible that he is incorrect. It is silly to argue that he must be right or must be wrong, because this is yet another variant of the eternal “correlation is causality” argument and is known to be scientifically and logically invalid, easily confounded by both accidental correspondence (which happens) and by additional variables with completely distinct causality that control both correlated variables. Smoking does not cause teen pregnancy, in spite of the fact that one can show a positive correlation between teens that smoke and teens that participate in activity that does cause teen pregnancy. We can never resolve the argument with better or worse matches in the correlation, though — we have to appeal to a considerable amount of completely independently derived science and measurement and raw sociology to understand what really (most probably) causes the observed correlation — teen hormones that encourage risk taking and social rebellion and uninformed participation in experimental sexual behavior simultaneously.
rgb
The real issue is that the Mauna Loa data is little different from a straight line relationship with time. Hence, almost any model with two or more variables can be tuned to match the Mauna Loa data to within the measurement error (n.b. to a perfect fit to each datum).
Damn skippy, Richard. Although I would have just asserted monotonic nonlinear relationship with time, so a near-infinity of nonlinear models with 1-3 parameters can fit it to within annualized fluctuations, and it is then VERY trivial to superpose any of those primary models with a secondary model that explains only the fluctuations including correspondence in the derivative of CO_2 and temperature!
Given such a short and monotonic baseline behavior, we understand almost nothing on the basis of mere numerical correspondence. Nor are any of the physical arguments or models particularly convincing — they depend way too much on the prior beliefs and biases of the arguer, with little to no way to falsify any of them using the data alone. What would help would be some sign of significant non-monotonic variation at the current monotonic scale (that is, not teensy annualized noisy fluctuations) that can only be predicted or hindcast with a subset of those models, but so far, that isn’t visible in the Mauna Loa data, especially not after they throw part of it away on the basis of (biased) arguments to produce a “cooked” product. The raw data, including the data that they throw away because of the direction the wind blows etc, might tell a different story because accepting or rejecting any part of the data according to external considerations forces the conclusion away from anything that omitted data might confound.
It isn’t worth going through the sins against the logic of statistical analysis routinely committed in climate science, but they are manifold and mortal.
rgb
Ferdinand:
re. your post at June 5, 2012 at 9:30 am
The ‘background’ CO2 level is meaningless. An IR photon interacting with a CO2 molecule does not ‘know’ if the molecule is ‘background’ or not. So, the total number of CO2 molecules in the atmosphere is all that matters, especially when CO2 is “well mixed” in the air.
At issue is to determine how the total amount of CO2 in the atmosphere has varied with time. Local measurements can do that for their localities. We use Mauna Loa as a proxy for the global total but, in principle, anywhere would do.
Richard
Robert Brown:
Please forgive my ignorance of your local idiom. What does “Damn skippy” mean, please?
And, while I am asking, I take this opportunity to say I agree everything else you said in that post (I did understand that).
Thanking you in anticipation.
Richard
Robert Brown says:
June 5, 2012 at 10:56 am
“However, one would have to look at the raw data to see if in fact this is what is happening, and I have not done so.
Do so. Here, I take the smoothing level down to 12 months (you have to average out the yearly variation). You’ve still got a 6 month advance because of the WoodForTrees centering of the average, but your spurious leads have vanished.
“Second, because sometimes dCO_2/dt leads T, and sometimes T leads dCO_2/dt (or they are closely synchronized) it is also important to bear in mind that inferring causality from correlation is weak in both directions.”
No, it isn’t. The variables of interest are the temperature and the total CO2, not the derivative. A change in temperature shows up in overall CO2 concentration at a later time. The temperature leads.
richardscourtney says:
June 5, 2012 at 10:45 am
“Hence, almost any model with two or more variables can be tuned to match the Mauna Loa data to within the measurement error (n.b. to a perfect fit to each datum).”
No, not perfect. The word perfect has a very specific meaning. Only within the arbitrary bounds you have set as a threshold.
“Why don’t the natural sequestration processes sequester all the emissions (natural and anthropogenic) when it is clear that they can? “
They very nearly do. If the system were in equilibrium, they would.
Please forgive my ignorance of your local idiom. What does “Damn skippy” mean, please?
It means “yes, I most emphatically agree”. I have no idea where it comes from, but of course Google has some ideas and at least one definition.
http://en.wiktionary.org/wiki/damn_skippy
So you could have replied to me with “Damn skippy to your damn skippy!” yourself instead of the more sedate “I agree (with) everything else you said in that post”:-).
rgb
richardscourtney says: @ June 5, 2012 at 10:45 am
…I repeat the important question is
Why don’t the natural sequestration processes sequester all the emissions (natural and anthropogenic) when it is clear that they can?….
_______________________________________
SWAG.
#1. CO2 is not evenly distributed throughout the atmosphere.
#2. CO2 has not remained more or less constant for eons but fluctuates a great deal more than the Warmists want us to know.
#3 There is competition between C3 and C4 plants. C3 plants do not take CO2 down below around 300 ppm based on the open field wheat study. If there is abundant CO2 the C3 plants have an advantage over the C4 plants and crowd them out. (SWAG)
#4 WIND – Trade winds and the jet streams. We have seen a change in the trades (El Nino, La Nina and a change in the location of the jets)
#5 The temperature has stopped rising and maybe falling (see Beck’s comment about 1941 blip)
In 2000 the mean annual air -sea flux for CO2 http://www.ldeo.columbia.edu/res/pi/CO2/carbondioxide/image/annfluxgmm2u2windmap.jpg
Models again but they mention that the air-sea gas transfer rate is a function of WIND SPEED.
From the Air Vent, a comment by Ernest Beck:
various references:
Carbon starvation in glacial trees recovered from the La Brea tar pits, southern California
http://www.co2science.org/subject/b/summaries/biodivc3vsc4.php
plant response to CO2: http://i32.tinypic.com/nwix4x.png
CO2: stomata http://www.geocraft.com/WVFossils/stomata.html
CO2 Aquittal: http://www.scribd.com/doc/31652921/CO2-Acquittal-by-Jeffrey-A-Glassman-PhD
ON WHY CO2 IS KNOWN NOT TO HAVE ACCUMULATED IN THE ATMOSPHERE &
WHAT IS HAPPENING WITH CO2 IN THE MODERN ERA: http://www.rocketscientistsjournal.com/2007/06/on_why_co2_is_known_not_to_hav.html#more
Satellite Data:
http://www.jaxa.jp/press/2009/10/20091030_ibuki_e.html
http://chiefio.wordpress.com/2011/10/31/japanese-satellites-say-3rd-world-owes-co2-reparations-to-the-west/
CO2 Flux Estimated from Air-Sea Difference in CO2 Partial Pressure: http://www.ldeo.columbia.edu/res/pi/CO2/carbondioxide/pages/air_sea_flux_2000.html
Robert Brown and Bart:
Robert, thankyou. As you say, I should have Googled it. Sorry.
Bart, I strongly object to your saying
The fit was perfect in that each datum from each model matches each corresponding datum in the Mauna Loa data set to within the measurement error. That IS a perfect fit. And the measurement error is not “arbitrary bounds” I made. I told you its value (Ferdinand has said the same above) and I provided you with a link to the Mauna Loa Lab.’s own explanation of how they derive it.
I do NOT make arbitrary choices (but I sometimes make mistaken ones). In this case I used the only valid “threshold”.
Richard
richardscourtney says:
June 5, 2012 at 10:45 am
“Only within the arbitrary bounds you have set as a threshold.”
The measurement error is a wideband process. The “signal” you are looking for is at low frequency. As a result, you can apply a low pass filter to remove high frequency noise, revealing the low frequency signal hiding in it. This is especially the case for numerically differentiated data, as the differentiation process amplifies noise at high frequency.
In general, there is a particularly strong yearly signal you want to remove. A twelve month average will do this, though it does not have particularly good passband characteristics (gain falls off from unity at dc fairly rapidly). A better filter can be designed using standard packages, but that requires specialized knowledge.
A succession of 12 month averages really clobbers noise in a derivative, as you can see in this plot.
Now, in that plot, you will see that I divided the temperature series up into segments, because there appears to be a step change around 1990. In the analogous model I suggested above, this could result from a step change in the variable To, the equilibrium temperature. This suggests that those arguing above on this thread for deep ocean upwelling as the source of the temperature differential needed to drive the levels of CO2 to their current levels may be on the right track. Around 1990 or so, there might have been a sudden shift in the thermodynamic state of the upwelling water.
On the other hand, the Hadley SST here may not be very precise, or have been subject to various “adjustments” which are not readily available to us.
Bart:
Your response to my post is a travesty. It quotes your words as being mine when yhose were the very words I had explained are a lie. It then waffles on with complete misunderstanding of what measurement error indicates when I have previously explained this basic science to you in a previous thread.
I see no point in answering you further whatever you post unless it is to refute another misquotation of me.
Richard
Richard, “Why don’t the natural sequestration processes sequester all the emissions (natural and anthropogenic) when it is clear that they can? “
The annual cycle in the Arctic is a clue. The cold water and biological activity could be considered a great sink limited only by how fast the CO2 is transfered to the water surface. During much of the year most of the surface is covered with ice. As the ice closes the sink drain in the fall, the CO2 concentration rises as CO2 continues to be delivered from the south. The concentration reaches a maximum around the middle of February when most of the ocean is covered with ice. It reaches a minimum when the area of exposed cold water is a maximum. Also, the partial pressure difference between air and water is a factor (transfer rate a function of concentration). Another factor to consider is the length of time any extra absorbed CO2 takes to get back to the equator where it is readmitted into the atmosphere. Think about the life and death cycle of phytoplankton.
Bart says:
June 5, 2012 at 9:07 am
You cannot arbitrarily detrend the data. The slope of the temperature is what produces the curvature in the accumulated CO2, and it matches exactly. That leaves no room for a significant human influence.
It is not only about the slope of the temperature, it is mainly about the offset. That is what “matches” the accumulated CO2, but both are simply chosen to match the CO2 data when integrated. That is curve fitting, which in this case is easely fitted, because the underlying trend in the data is quite linear and the temperature variability matches the variability in
CO2 increase rate, because that is a clear cause-effect relationship.
Where it goes wrong is that the slope and the offset are as good (or even better) fitted by the emissions, which are twice as high as the observed rate of change. Thus your slope and offset are completely arbitrary and can be replaced by 0-55% of the emissions, the upper bound does leave only a little room for the influence of temperature.
Indeed we have had many discussions on this topic, but besides the mass balance argument, the main problem with your theory is that you made the human emissions and the temperature too interdependent, while the influence of both on CO2 levels is (near) completely independent of each other. Therefore there is no need for a rapid sequestration of human (or any other) CO2, which anyway is not what is observed.
But again, there is a simple proof that your formula does or doesn’t work if you use the same coefficient and offset for the past periods (1900-1960 and LIA-1900).
And still I am waiting for any knowledge of a physical process that delivers 70 ppmv CO2 over 50 years only from a continuous small elevated CO2 level…
fhhaynie:
Thankyou for your post at June 5, 2012 at 12:46 pm.
Yes, but none of that is quantified. In fact almost nothing in the carbon cycle is.
I again post the processes which we considered most important.
Short-term processes
1. Consumption of CO2 by photosynthesis that takes place in green plants on land. CO2 from the air and water from the soil are coupled to form carbohydrates. Oxygen is liberated. This process takes place mostly in spring and summer. A rough distinction can be made:
1a. The formation of leaves that are short lived (less than a year).
1b. The formation of tree branches and trunks, that are long lived (decades).
2. Production of CO2 by the metabolism of animals, and by the decomposition of vegetable matter by micro-organisms including those in the intestines of animals, whereby oxygen is consumed and water and CO2 (and some carbon monoxide and methane that will eventually be oxidised to CO2) are liberated. Again distinctions can be made:
2a. The decomposition of leaves, that takes place in autumn and continues well into the next winter, spring and summer.
2b. The decomposition of branches, trunks, etc. that typically has a delay of some decades after their formation.
2c. The metabolism of animals that goes on throughout the year.
3. Consumption of CO2 by absorption in cold ocean waters. Part of this is consumed by marine vegetation through photosynthesis.
4. Production of CO2 by desorption from warm ocean waters. Part of this may be the result of decomposition of organic debris.
5. Circulation of ocean waters from warm to cold zones, and vice versa, thus promoting processes 3 and 4.
Longer-term process
6. Formation of peat from dead leaves and branches (eventually leading to lignite and coal).
7. Erosion of silicate rocks, whereby carbonates are formed and silica is liberated.
8. Precipitation of calcium carbonate in the ocean, that sinks to the bottom, together with formation of corals and shells.
Natural processes that add CO2 to the system:
9. Production of CO2 from volcanoes (by eruption and gas leakage).
10. Natural forest fires, coal seam fires and peat fires.
Anthropogenic processes that add CO2 to the system:
11. Production of CO2 by burning of vegetation (“biomass”).
12. Production of CO2 by burning of fossil fuels (and by lime kilns).
Several of these processes are rate dependent and several of them interact.
At higher air temperatures, the rates of processes 1, 2, 4 and 5 will increase and the rate of process 3 will decrease. Process 1 is strongly dependent on temperature, so its rate will vary strongly (maybe by a factor of 10) throughout the changing seasons.
The rates of processes 1, 3 and 4 are dependent on the CO2 concentration in the atmosphere. The rates of processes 1 and 3 will increase with higher CO2 concentration, but the rate of process 4 will decrease.
The rate of process 1 has a complicated dependence on the atmospheric CO2 concentration. At higher concentrations at first there will be an increase that will probably be less than linear (with an “order” <1). But after some time, when more vegetation (more biomass) has been formed, the capacity for photosynthesis will have increased, resulting in a progressive increase of the consumption rate.
Processes 1 to 5 are obviously coupled by mass balances. Our paper assessed the steady-state situation to be an oversimplification because there are two factors that will never be “steady”:
I. The removal of CO2 from the system, or its addition to the system.
II. External factors that are not constant and may influence the process rates, such as varying solar activity.
Modeling this system is a difficult because so little is known concerning the rate equations. However, some things can be stated from the empirical data.
At present the yearly increase of the anthropogenic emissions is approximately 0.1 GtC/year. The natural fluctuation of the excess consumption (i.e. consumption processes 1 and 3 minus production processes 2 and 4) is at least 6 ppmv (which corresponds to 12 GtC) in 4 months. This is more than 100 times the yearly increase of human production, which strongly suggests that the dynamics of the natural processes here listed 1-5 can cope easily with the human production of CO2. A serious disruption of the system may be expected when the rate of increase of the anthropogenic emissions becomes larger than the natural variations of CO2. But the above data indicates this is not possible.
The accumulation rate of CO2 in the atmosphere (~1.5 ppmv/year which corresponds to ~3 GtC/year) is equal to almost half the human emission (~6.5 GtC/year). However, this does not mean that half the human emission accumulates in the atmosphere, as is often stated. There are several other and much larger CO2 flows in and out of the atmosphere. The total CO2 flow into the atmosphere is at least 156.5 GtC/year with 150 GtC/year of this being from natural origin and 6.5 GtC/year from human origin. So, on the average, ~3/156.5 = ~2% of all emissions accumulate.
The above qualitative considerations suggest the carbon cycle cannot be very sensitive to relatively small disturbances such as the present anthropogenic emissions of CO2. However, the system could be quite sensitive to temperature. So, our paper considered how the carbon cycle would be disturbed if – for some reason – the temperature of the atmosphere were to rise, as it almost certainly did between 1880 and 1940 (there was an estimated average rise of ~0.5 °C in average surface temperature).
Clearly, much more needs to be known if we are to answer my question.
And, as you point out, ocean circulation is but one of several variables additional to those we considered.
Richard
Allan MacRae says: June 5, 2012 at 5:15 am ADDENDUM – ADDED POINT 4. BELOW.
The question is what primarily causes what – does atmospheric CO2 drive temperature or does temperature drive CO2? Do current humanmade CO2 emissions significantly increase atmospheric CO2, or are they “lost in the noise” of the much larger dynamic natural system?
My contention is, adapting Ferdinand’s wording:
“ the bulk of the rate of change is NOT caused by human emissions, BUT IS A RESULT OF ONE OR MORE LONGER-TIME NATURAL TEMPERATURE CHANGE CYCLES, CONSISTENT WITH the SHORT-TIME-CYCLE variability of the rate of change THAT IS ALSO caused by temperature changes.”
I prefer my hypo because
1. My hypo is more consistent with Occam’ s Razor – whereas Ferdinand’s hypo requires opposing trend directions at different time scales in the system, mine does not, such that all trends are consistently in the same direction (temperature drives CO2) at all time scales.
2. My hypo is consistent with the fact that CO2 lags temperature at all measured time scales, from an ~800 year lag on the longer time cycle as evidenced in ice cores, to a ~9 month lag on the shorter time cycle as evidenced by satellite data.
3. I have yet to see evidence of a major human signature in actual CO2 measurements, from the aforementioned AIRS animations to urban CO2 readings ( although I expect there are local data that I have not seen that do show urban CO2 impacts, particularly in winter and locally in industrialized China.)
[new point 4]
4. My hypo is more consistent with the Uniformitarian Principle.
Richard, I awoke very early this morning and have had little sleep – accordingly, I may tackle your excellent question in more detail later.
My high-risk, sleep deprived response is that Jan Veizer probably has it mostly right in his landmark 2005 GSA Today paper.
In my own words, the CO2 cycle “piggybacks” on the water cycle, and is a huge, DYNAMIC, DISPERSED (global in area) and HETEROGENEOUS system that is condemned to chase equilibrium in time and space into eternity.
Obviously, I need some sleep.
Best personal regards, Allan
Robert Brown says:
June 5, 2012 at 11:10 am
The raw data, including the data that they throw away because of the direction the wind blows etc, might tell a different story because accepting or rejecting any part of the data according to external considerations forces the conclusion away from anything that omitted data might confound.
Look for yourself if throwing out some of the data at MLO or other stations has any effect on the trend and/or slope of the “cleaned” data. For four baseline stations, the raw (hourly averaged) data are available at:
ftp://ftp.cmdl.noaa.gov/ccg/co2/in-situ/
I have plotted the raw data and the “cleaned” averages from MLO and SPO here:
http://www.ferdinand-engelbeen.be/klimaat/klim_img/co2_mlo_spo_raw_select_2008.jpg
But mind the CO2 scale!
richardscourtney says:
June 5, 2012 at 11:10 am
The ‘background’ CO2 level is meaningless. An IR photon interacting with a CO2 molecule does not ‘know’ if the molecule is ‘background’ or not. So, the total number of CO2 molecules in the atmosphere is all that matters, especially when CO2 is “well mixed” in the air.
The influence of CO2 on radiation effects is over the whole air column. Over the oceans, the CO2 levels are rather uniform up to 20 km height. Over land you can have enormous differences in the first few hundred meters, due to huge local sources and sinks. But if you look at the radiation, even if you have 1,000 ppmv in the first 1,000 meters, its effect would be minimal.
Thus measurements in the first few hundred meters over land shouldn’t be used for possible local effects (which are negligible), neither for trends, although in average the trends may resemble what happens in the bulk of the atmosphere.
Ferdinand:
Please read the final paragraph in my post you answered. You seem to have missed the point of my post in your answer.
Richard
richardscourtney says:
June 5, 2012 at 12:34 pm
I quoted words so you would know where in the conversation I was picking up. Anyone following the thread knows who said what.
And, you are just plain wrong about the measurements. I have tried to explain basic filtering theory to you, but you just plug your ears and shout “nah, nah, nah!”
Your sheltered arrogance is astounding. You are denying an entire field of research from such giants as Fisher and Kalman, and ubiquitous application. How do I reach through to you to do even a modicum of research, or just try what I have explained you need to do?
FerdiEgb says:
June 5, 2012 at 2:31 pm
“It is not only about the slope of the temperature, it is mainly about the offset.”
No, it is not. I have explained this at length. I am tired of explaining.
richardscourtney says:
June 5, 2012 at 12:21 pm
“The fit was perfect in that each datum from each model matches each corresponding datum in the Mauna Loa data set to within the measurement error. That IS a perfect fit.”
No, it is not perfect. Perfect means PERFECT.
The measurement error is distributed in frequency, much of it in the high frequency region in which we are not interested. That error can be filtered out.
Here is a very simple example. Suppose I tell you a signal is known to be a constant plus uncorrelated zero mean noise with standard deviation of S. By your logic, I can never determine the constant value to less than +/-S.
But, if I take N samples and average them, my estimate will have an uncertainty of +/- S/sqrt(N). As the number of points N goes to infinity, I asymptotically approach perfect (really perfect, not just pretend perfect) knowledge of the constant.
A constant is very low frequency, uncorrelated noise is evenly distributed across all frequencies, and an average is a low pass filter. It’s the same general deal.
richardscourtney says:
June 5, 2012 at 12:34 pm
“I see no point in answering you further whatever you post unless it is to refute another misquotation of me.”
In that case, richardscourtney said above, and I quote, “I enjoy molesting puppies.”
Now, you have to respond 😉
FerdiEgb says:
June 5, 2012 at 2:31 pm
“But again, there is a simple proof that your formula does or doesn’t work if you use the same coefficient and offset for the past periods (1900-1960 and LIA-1900).”
A) we do not have reliable measurements from those times
B) different operating conditions mean different parameters. This is typical of linearized approximations of nonlinear systems – they only hold in a local neighborhood of the time in which the linearization is performed. Right now, in the modern era, these parameters hold, and they explain the last several decades of atmospheric CO2 concentration and rule out singificant human contribution to it.
“And still I am waiting for any knowledge of a physical process that delivers 70 ppmv CO2 over 50 years only from a continuous small elevated [temperature] level…”
Deep ocean upwelling, as I and others have commented.
Shyguy says:
June 3, 2012 at 12:26 am
Looks to me like the co2 records got corrupted just like everything else the ipcc get it’s hands on….
___________________________
All I had to do is read what Mauna Loa said. The “selection process” at Mauna Loa Observatory.
“Nough said.