The question arose recently, is it really true that atmospheric CO2 concentration is not just increasing but actually accelerating? Let’s take a look at some data.
Mauna Loa recently released the estimated CO2 concentration for December 2008, bring the year to a close. The initial value was a repeat of the value for November, which would be a very unusually low value (CO2 generally increases from November to December as part of its annual cycle). But this appears to be just a simple mistake because the value has been revised, the new figure fitting expectation well and conforming to the existing annual cycle pattern. Here’s the current data from Mauna Loa:

CO2 concentration shows both a long-term increase (indicated by the smoothed curve) and an annual pattern. We can remove the annual pattern (and the average value) in order to define CO2 anomaly:

I’ve plotted a straight-line fit to the anomaly data, which indicates visually that the CO2 concentration follows a curved path rather than straight, one which curves upward. So let’s remove, from the original data, both the average annual cycle and a best-fit straight line, which will give us CO2 residuals:

On this plot I’ve superimposed a parabola (a 2nd-order polynomial). The parabola indicates that the CO2 concentration does indeed curve upward, and the amount of curvature indicates that the growth rate of CO2 concentration is increasing at about 0.024 +/- 0.005 ppm/yr/yr. That increase is most definitely statistically significant (in fact it explains nearly 91% of the variance of these residuals). That does not mean that CO2 concentration is following a parabola, or that the growth rate is increasing with perfect regularity; it isn’t. But it does confirm that the growth rate is not constant, it’s been increasing.
We can also take the original CO2 anomaly data and determine the growth rate separately for each decade. We get this:

Clearly the decadal growth rates are on the rise, although just as clearly the increase in growth rate has not been steady. Nonetheless, even with only five decades we get a statistically significant increase in the growth rate of 0.029 +/- 0.009 ppm/yr/yr.
We can also compute annual average CO2 concentration, and from those we can compute the annual growth in CO2 concentration:

Once again we see that the growth rate has increased; linear regression indicates that it’s increasing by about 0.026 +/- 0.009 ppm/yr/yr, so this result too establishes the increase of growth rate with statistical significance.
In short, there’s no doubt whatever that not only is atmospheric CO2 concentration growing, the growth rate itself is also growing. The rate of increase of CO2 since 2000 is about 2.1 ppm/yr, and the long-term growth rate of the growth rate is about 0.025 ppm/yr/yr.

65 responses so far ↓
counters // January 13, 2009 at 12:16 am |
Thanks for working through the analysis for us, tamino. It’s a shame that even a thorough mathematical argument such as this isn’t enough to persuade certain people that the growth rate CO2 concentration is in fact increasing.
Colin Aldridge // January 13, 2009 at 12:30 am |
I don’t think even the most hardened sceptic would argue with your analysis. CO2 is obviosly going up and at an increasing rate and there is no sign of this increase slowing during the last 10 years or so when there has been a paause of a sort to the warming trend which undermines a popular scptic argument that warm globe drives CO2 not the other way round. Godd stuff.
Any thoughts on the kink in the 85 95 period
Colin Aldridge // January 13, 2009 at 12:31 am |
I mean good stuff .. of course
David B. Benson // January 13, 2009 at 1:10 am |
Once again, very clear!
ScruffyDan // January 13, 2009 at 1:29 am |
You might want to take a look at a recent post over at the stoat blog.
http://scienceblogs.com/stoat/2009/01/sea_absorbing_less_co2_scienti.php
How does your post relate to that?
Hank Roberts // January 13, 2009 at 2:34 am |
William said a few years back it looked linear but if we kept increasing fossil fuel use that would change. Maybeso?
Also
http://www.pnas.org/content/104/47/18866
Hank Roberts // January 13, 2009 at 2:36 am |
> few years ago
For a value of “few” equal to just slightly more than one, I mean:
http://scienceblogs.com/stoat/2007/10/airbourne_fraction.php
Ricki (Australia) // January 13, 2009 at 3:01 am |
I would like to see how the emissions compare to the IPCC scenarios. It has been bandied around that we are tracking above the IPCC scenarios but I have not been able to set up the data to show this. Can you please do this?
Ricki (Australia) // January 13, 2009 at 3:04 am |
Also,
The latest research on sea level rise by Grinsted et al. (Proudman Oceaneographic Laboratory and others) http://www.nbi.ku.dk/english/news/sea_level_rise_of_one_meter/
The result: 0.9m to 1.2m by 2100 (11mm/yr by 2050, 20mm/yr by 2100) with long term rise projected to be much higher.
Note that
GHG concentrations used in the projections are still based on IPCC scenarios (eg. A1B) that are known to be below current annual increases in emissions.
the long term rise (beyond 2100) is constrained to a min. of 0.5m per degree C based on historical and paleo data.
Ice sheet dynamic melt contribution identified as the most likely contributor to the projections being 3 times IPCC.
The equation is assumed to be linear while non-linear conditions have been known to occur in the past (see section 9).
IPCC levels are stated as being much too low for both the fast and slow response times.
No account is made of dynamic ice sheet collapse, change in albeido (planetary ice/vegetation cover), the effect of sea level rise on ice loss, acceleration in forcing due to increased methane from permafrost, collapse of ocean currents, etc. [although it could be argued that some of these are reflected in the paleo data].
I have two problems with this paper:
A) It assumes 3-4 deg rise by 2100 (a bit of an underestimate if we take no proper action). The result is that if we take concerted action, we will STILL see changes of this magnitude. If we take no action, as repeatedly looks likely, we are facing much worse sea level rises.
B) The rates are assessed on related temperatures/sea level in historical and paleo data (as it is the only data we have). This is not the same as the current situation where forcing is accelerating as we put more GHGs up into the atmosphere with the temperature rising in a much faster way than ever before seen. Previous changes to forcing relate mostly to continental drift and Milankovitch cycles (as far as ice ages are concerned). Therefore, this paper can only approach the type of conditions we face, not define it – with consequently reduced certainty on the projections.
My guess at long term rise from the rates given in the paper is around 5m to 15m by say 2200-2300 AD. Of course, if we melt all the ice on the planet, we get of the order of 70m sea level rise. This could still happen if we don’t get our act together.
[Response: I'd say there's a lot of uncertainty about future sea level rise. We really don't know how the ice sheets will respond and how long they'll take to do so, and the thermal expansion of the oceans will take a very long time as it takes so long for heat to penetrate to the deep oceans.
I'll look up some data on sea level and on CO2 emissions, and see what I can find.]
paulm // January 13, 2009 at 3:57 am |
Also look up data on sea level vs temp and the rate of rise.
There are some scary precedents….
naught101 // January 13, 2009 at 4:43 am |
Tamino,
I probably have a (very) slightly better grasp of climate science than the average person on the ‘web, but I have to say that I get massively confused following most if your science/stats-based posts. I can see that there are a huge number on here, and some are much simpler than others, but I don’t know where to start.
I’d love it if you could create a new page to complement the “climate data links” page, with a list of links (either to your blog or elsewhere) ordered in a way you think appropriate, such that new comers have a good place to start. Such a page could serve as a massively helpful resource to all those reading about climate science on the ‘web.
Steve Bloom // January 13, 2009 at 5:10 am |
Colin (second comment), the annual plot shows that the kink lines up with the Pinatubo eruption (cooler SSTs => decreased absorption rate) and the Soviet industrial semi-collapse (which was accompanied by something of a global recession). I suspect that’s the answer, but I have no idea how the blame would be distributed among those factors.
William Connolley // January 13, 2009 at 8:33 am |
Nice post, thanks.
Could you post a ref to the CO2 data as a service to humankind? – I can never find the most up to date stuff :-(
Question (which SD has already raised): how far, from the atmospheric concentration, can you constrain plausible airbourne fraction values, and more topically how far can you constrain the fraction going into the ocean?
Suppose you assume that 25% of emitted CO2 goes ino the atmos, and 25% into the ocean (or has, over the long term) can you demonstrate that “The results showed the amount of CO2 absorbed during 1999 to 2007 was half the level recorded from 1992 to 1999.” (reported by http://www.guardian.co.uk/environment/2009/jan/12/sea-co2-climate-japan-environment) can’t be true globally?
William Connolley // January 13, 2009 at 8:34 am |
…under a helpful banner such as “Climate Data Links”, perhaps. Ah well, I know now. Thanks.
koen // January 13, 2009 at 8:48 am |
@Ricki,
You may find details & references here:
http://www.globalcarbonproject.org/carbontrends/index.htm
the .ppt has slide 7 comparing emissions to IPCC scenarios (and reality is worse than expected :)
michel // January 13, 2009 at 8:52 am |
These things operate, assuming they do, over very long periods. A divergence over 10 years can’t prove anything either way. Temps may start rising again. Or, less likely, CO2 levels may start to fall. But either way, there’s no reason they should move in lockstep over a period as short as 10 years.
Back in Paleo, CO2 rises seem to have lagged by 700 years. The explanation given is that small initial temp rises caused CO2 rises that then led to large subsequent temp rises. Long time intevals though.
Chris // January 13, 2009 at 9:34 am |
http://www.esrl.noaa.gov/gmd/ccgg/trends/
(Annual Mean Growth Rate)
Back of the envelope says:
growth rate for last 5 years (2004-8) = 1.91 ppm/yr
For previous 5 (1999-2003) = 1.82 ppm/yr
For previous 5 (1994-1998) = 1.99 ppm/yr
Hence no (significant) acceleration in the last 15 yrs?
[Response: This is getting ridiculous.
Back of the envelope says:
1994-1998: 1.99 plus or minus 0.6 ppm/yr
1999-2003: 1.82 plus or minus 0.6 ppm/yr
2004-2008: 1.91 plus or minus 0.4 ppm/yr
Linear regression 1994-2008: +0.011 plus or minus 0.065 ppm/yr/yr.
I shouldn't take it out on you, you just asked a question. But after all the effort I've put into increasing awareness of the statistics of trend analysis, having to deal (again) with the ridiculous comments from Lee Kington is pretty discouraging. There seems to be no end to claims about trends based on too little data data and no statistical analysis at all; are my efforts futile?]
Ray Ladbury // January 13, 2009 at 1:26 pm |
Tamino says: “There seems to be no end to claims about trends based on too little data data and no statistical analysis at all; are my efforts futile?”
I will refer you to the wisdom of Mr. Twain:
“Never try to teach a pig to sing. It doesn’t work and it annoys the pig.”
For some folks, there is no evidence the learning curve has a positive slope. For some of us, however, you perform a valuable service and a reminder that any fool can lie with statistics, but properly used, statistics are one of the few tools we have to keep us from lying to ourselves.
Deech56 // January 13, 2009 at 1:56 pm |
Tamino says: “There seems to be no end to claims about trends based on too little data data and no statistical analysis at all; are my efforts futile?”
What you have done is teach the rest of us critical evaluation skills – we’ve shaken off the cobwebs of our own stats courses (and regression courses – oh, yeah, residuals – for some of us) to make your arguments elsewhere. I am sure that a number of us saw the obvious mistakes in the Asher DailyTech post even before your thorough analysis.
Brad Beeson // January 13, 2009 at 3:34 pm |
I’ve enjoyed playing with the numbers published by Mauna Loa Observatory, too.
If you overlap the data set with itself, with a 25.33 year offset, there seems to be a remarkable correspondence. (The peaks of 1973 and 1998 line up, as do many of the eralier and later features).
25.33 is 3.619 * 7, which you’ve mentioned before as being a possible periodicity.
Do you think this is significant, or just the human brain’s ability to find patterns in noise?
Dano // January 13, 2009 at 4:04 pm |
What you have done is teach the rest of us
When you teach, you don’t teach for everybody. If you do, you’ll get frustrated real fast. You teach for those who want to learn. The rest you try to keep awake.
Best,
D
Jay // January 13, 2009 at 4:07 pm |
I used the rate data provided by the Mauna Loa site (available at their website) & got pretty much the same result & almost the exact same rate graph shown here. (Starting strictly from the annual, or monthly data as done here would have been easier by calculating the first derivitive from the data points & plotting that; the analysis here seems like a harder way to illustrate the point; but simply plotting the rate data from the Mauna Loa CO2 site was almost effortless….).
Based on simple (emphasizing “simple”) curve fitting (using the “eyeball technique”) the overall trend is clearly up (and picking points from my graph matched the figures here within a tenth of the units of measure!), but some interesting subtrends are very apparent:
The Mauna Loa data (for measures taken at Mauna Loa) shows a distinct deceleration (slowing) in the rate of CO2 acceleration starting in about 1992, give or take a little (not doing any kind of analysis to assess residuals, etc. this is plus/minus a year or two). After, about, 1992 CO2 levels are still going up, but clearly not as fast.
THAT is a curious pattern. And totally unexpected given the unimpeded rate of industrialization. ….. but … that’s only for data measured at one site (Mauna Loa).
IN CONTRAST, the world CO2 growth rate (using the data provided at the Mauna Loa website) shows a steady acceleration in CO2 without such a slowdown–just as one would expect.
I’m not sure if this means anything more than the nuances associated with weather, etc. patterns at the Mauna Loa measurement site given the “noise” in the data.
george // January 13, 2009 at 6:01 pm |
Tamino:
Rest assured. Your efforts are certainly not “futile”.
Far from it.
My bet is that someday, someone will probably write the book
“All I really need to know about statistics I learned from Tamino’s blog”
TCOisbanned? // January 13, 2009 at 6:02 pm |
I agree that the added paramater gives 91% explanation of residuals, but think it may be more interesting to compare the rsq of the fits themselves. Obviously the second degree polynomial will be a better fit than the first degree, but I wonder how much difference.
The acceleration seems pretty moderate. Between and 1 and 2% of the rate per year, which itself is a bit less than 1% of current total. Interesting to look at final extrapolated values at say 25 and 100 year marks, given a linear extrapolation and given a paraboloic one. Then we can consider how much difference there is functionally (in terms of temp) with the two fits.
I assume that there are various factors of input for CO2 and maybe more than one factor of take-up. Would be interesting to look at these in a list and understand something about how each is changing, or will change. For instance some may be independant of concentration, some may be functions of it. While we can’t “predict the future”, playing with these functions should help us think about the mass balance situation over time, how different scenarious affect it, etc.
David B. Benson // January 13, 2009 at 6:06 pm |
The carbon dioxide information center has information about emissions. Here is a graph of yearly emissions:
http://cdiac.ornl.gov/trends/emis/tre_glob.html
Here is a news article about a recent attempt to estimate sea level rise (by a new method):
“Sea Level Rise Of One Meter Within 100 Years”
http://www.sciencedaily.com/releases/2009/01/090108101629.htm
Elery Fudge // January 13, 2009 at 6:25 pm |
Elery Fudge
Tamino says: “There seems to be no end to claims about trends based on too little data data and no statistical analysis at all; are my efforts futile?”
I know diddly about statistics but your efforts are appreciated.
Elery
Zeke Hausfather // January 13, 2009 at 11:16 pm |
Ricki,
Re: current CO2 emissions relative to IPCC scenarios, I dug up a few things in a reply over at Lucia’s: http://rankexploits.com/musings/2009/moncktons-artful-graph/#comment-8596
You can see emissions relative to the IPCC scenarios here:
http://67.220.225.10/~clim2165/cs/wp-content/uploads/2008/09/ipcc-scenarios.jpg
And atmospheric concentrations relative to the (TAR) IPCC scenarios here: http://www.skepticalscience.com/images/ipcc_2001_co2.gif
Wish I could find the actual numbers for the IPCC scenarios somewhere though… I figure I’d have to dig though the SRES datasets, though I’m not sure which are being used and how they have been modified for the AR4.
Jay // January 13, 2009 at 11:25 pm |
In reviewing the GROWTH in CO2 emissions its seems (intuition) that the greatest sources for the growth are in places like China–where there’s no significant, or negative, incentive to restrict this CO2 contribution.
Question: what are the sources for the majority of the overall CO2 growth?
dko // January 13, 2009 at 11:32 pm |
A second-order fit through MLO trend data (to Dec 2008) shows an r^2 of 0.9988.
Run the regression formula forward and it predicts 400 ppm in 2015 and 450 ppm by 2035.
blue // January 13, 2009 at 11:33 pm |
Tamino wrote: “There seems to be no end to claims about trends based on too little data data and no statistical analysis at all; are my efforts futile?”
My guess is that people come here for the first time, read the most current post and comment. This way you’ll always start at zero again in the discussion. I kind of like naught101’s idea of having a “Tamino’s Essentials” page with links to selected posts of yours displayed prominently on the front page. It would be a very helpful resource and might reduce the number of comments rehashing well-known errors.
TCOisbanned? // January 14, 2009 at 12:23 am |
Right. And sometimes people don’t get my remarks either. What a bunch of newbies. NEW….BIES! Look at the NEW….BIES! (Said in a Mr. Garrison voice.)
David B. Benson // January 14, 2009 at 12:30 am |
Jay // January 13, 2009 at 11:25 pm — Look to the Carbon Dioxide Information Analysis Center for answers to such questions.
TCOisbanned? // January 14, 2009 at 12:38 am |
I’m just kinda noodling here. I’m trying….grasp towards inferences.
Does the high explanatory power of a quadratic indicate some sort of quadratic process? Or just the better fit that you tend to get when adding terms? How would adding an exponential (instead of squared term) compare in terms of fit? How much of the residuals from the quadratic would be taken care of if we made it a cubic?
Please don’t take any of the preceding babble as critical. If I have to make a prediction for 2020(and don’t have access to specific predictions from fundamental analysis), my “Bayesian bet” would be to use Tammy’s quadratic.
[Response: The quadratic model doesn't imply an actual quadratic process. It really only establishes that the trend is definitely not linear, and the nonlinearity is such that the growth rate of CO2 is going up rather than down. I don't know whether an exponential fit would be better or worse, but it wouldn't establish an exponential pattern either; it would just show the same things, that the trend is nonlinear and the growth rate is going up rather than down.
The noise level is high enough that i doubt it's possible to establish the form of the pattern, beyond saying that it's nonlinear and curves upward rather than downward.
Any "smooth" function can be expressed as a Taylor's series, so in essence it can be expressed as an infinite-order polynomial. Fitting higher and higher order polynomials may be able to explore more and more terms in that series, but we'd need a lot more evidence to conclude that we've actually divined the form of the pattern.
It's also very dicey to attempt to forecast the future using polynomial approximations. One can compute an "error function" (not the "error function" which refers to the normal probability distribution) which gives the probable error in such a forecast based on random noise alone (let alone due to incorrect specification of the form of the function!), and for polynomial models the error function explodes rapidly beyond the limits of the observed data. This is for a lot of reasons, including the fact that polynomials are unbounded. But the bottom line is: don't forecast with polynomial fits beyond a tiny future span, unless you have overwhelming support that the polynomial model is real.]
Mark // January 14, 2009 at 1:07 am |
Ray Ladbury wrote: “any fool can lie with statistics, but properly used, statistics are one of the few tools we have to keep us from lying to ourselves.”
That line is almost worthy of Mark Twain, whom you quoted in the previous paragraph.
It’s not a quote from Mark Twain, is it? Or someone else?
Ray Ladbury // January 14, 2009 at 1:48 am |
It is my own line. You are free to use it.
Kevin // January 14, 2009 at 7:25 am |
Please explain why temperature increase is not accelerating during the same period. CO2 causes the global temperature increase right? From what I see temperatures are decreasing over the same period that the CO2 increase is accelerating. How can this be?
[Response: This "temperatures are decreasing" notion betrays a failure to understand even the basics, and it certainly betrays a lack of having read and understood what's on this blog.
I really do need a "start here" link.]
EliRabett // January 14, 2009 at 1:16 pm |
Keeping with my betting policy, Eli bets a bunch of carrots and one beer that the rate of increase will fall sharply in 2009 mostly because the economy in the US, EU and China are tanking. You can see the same effect btw 1990 and ~1995 when the FSU and eastern europe collapsed economically.
Crud is coupled.
Nick Zervos // January 14, 2009 at 1:45 pm |
Tamino, where did the values of annual CO2 growth in your last graph come from? They don’t seem to agree with the numbers shown in the table at the right side of the Mauna Loa web page
http://www.esrl.noaa.gov/gmd/ccgg/trends/
Just a couple of examples: your graph gives about 0.9 ppm/yr for 1960, 1.6 for 1970, 1.3 for 2000 vs. 0.51, 1.02, and 1.74, respectively, in the Mauna Loa table.
[Response: I computed the annual average CO2 concentration, then took the difference between each year's value.]
Gavin's Pussycat // January 14, 2009 at 3:10 pm |
dko,
there is a reason that Tamino goes from a linear to a quadratic fit… the interesting thing here is the non-linearity. That’s what his R^2 = 0.9091 is referring to.
BTW you can only use Pearson’s correlation and significance value for time series that are not significantly autocorrelated. You can see already by looking at the residuals wrt the parabola that that just isn’t the case here: I would visually guess 5-10 years correlation length.
From the fifth picture it looks like the derivative is close to “white”; if true, that would mean that CO2 itself is “red”.
Tamino, 0.024 +/- 0.005, 0.026 +/- 0.009: those were derived properly with autocorrelation, right? (Your teachings have made me a paranoid wreck :-)
[Response: Yes.]
John Mashey // January 14, 2009 at 4:52 pm |
If you do a “Start Here”, seriously consider doing a “Catalog of Cherry Picks” of which many have been well-illustrated here:
1) Too short time series [purposeful or accidental]
2) Series/graph without statistical significance [purposeful or accidental]
3) Selection of carefully-chosen segment of a time-series, with graph to disappear important effects [one thinks of CO2 vs temperature, picked for any small sequence of years where temperature isn't rising].
4) Selection by geography.
5) Selection by subset of a time-series chosen to emphasize some effect or lack thereof. Example: ice-extent during Arctic winter, ignoring summer.
6) Adding two sequences together, when one is just doing random jiggling: add Arctic and Antarctic ice together, and by picking right tiem period, you can prove anything.
george // January 14, 2009 at 4:56 pm |
Nick
If i am not mistaken, the difference (between tamino’s values and those of NOAA) is caused by the different way that NOAA calculates annual mean rate of growth of CO2
http://www.esrl.noaa.gov/gmd/ccgg/trends/
compare that to tamino’s method:
Though the method for calculating annual mean growth may be different, the slope of the trend (from 1959-present) obtained with the numbers from the NOAA table is basically the same as what tamino gets: 0.026ppm/yr/yr
By the way, Tamino what noise model have you used for CO2?
TCOisbanned? // January 14, 2009 at 4:59 pm |
What is the rsq of the linear fit?
koen // January 14, 2009 at 5:20 pm |
Eli,
I fear all bets are off. I agree with you that this crisis will lower a number of sources. But the articles from globalcarbon also indicate the ocean sinks lowering in capacity. I don’t know yet whether they do cliff-diving or not (hope not ).
Also, Tamino reported on ABCs, which were said to cause lower temps (1-2° IIRC). With industrial output and shipping falling through the floor, we might see these ABCs diminish if not disappear.
So in the end, we could have lower CO2 emissions and higher temperatures. Now that will be fun in some circles.
(No I don’t take bets)
Richard Steckis // January 14, 2009 at 6:35 pm |
William Connolley:
“Could you post a ref to the CO2 data as a service to humankind? – I can never find the most up to date stuff :-(”
For those with R, the following script will give you a plot of the Mauna Loa data straight from their FTP server:
url=”ftp://ftp.cmdl.noaa.gov/ccg/co2/trends/co2_mm_mlo.txt”
mld<-read.table(url, skip=20, fill=T, na.strings=-99.99)
names(mld)<-c("year", "month" ,"yymm", "co2", "co2interp", "co2trend")
attach(mld)
x<-yymm
y<-co2
plot(x,y, main="Mauna Loa co2 Data", xlab="Year", ylab="co2 (ppm)", col="red", pch=16, type="l")
Gerda // January 14, 2009 at 6:42 pm |
thanks, very useful.
i’m still awake, and i understood nearly all of the statistics jargon!
i agree though, some kind of ’stats 101′ list would be very handy.
i sort of hope it is china rather than decreasing absorption by oceans that is the dominant factor in the recent acceleration. we will see – if it levels off again during this recession or continues to rise.
Richard Steckis // January 14, 2009 at 6:58 pm |
Just make sure you redo the double quotes around the url statement.
george // January 14, 2009 at 6:59 pm |
Given the large variability from year to year, how could one know that even a fairly large decrease was due largely to a change in economic activity (ie, CO2 emissions)?
eg, Mauna loa Annual Mean
Growth Rate
1990 1.31
1991 1.02
1992 0.43
1993 1.35
1994 1.90
1995 1.98
1996 1.19
1997 1.96
1998 2.93
1999 0.94
2000 1.74
The dip from 1991 to 1992 does stand out, but is not clear that it can be attributed primarily to economic downturn.
Pinatubo also may have had a significant effect.
Large Volcanic Eruptions Help Plants Absorb More Carbon Dioxide From the Atmosphere (December 10, 2001)
Gareth // January 14, 2009 at 8:18 pm |
koen,
IIRC, total GHG forcing at present is something like 430ppm CO2e, but aerosols reduce that to about 385ppm CO2e.
A substantial reduction in aerosols due to a fall in industrial activity (or concerted efforts to clean up smokestacks) could provide a very nasty kick to overall warming.
george // January 14, 2009 at 8:34 pm |
From 1991 – 1992, the atmospheric CO2 growth dropped by 58%. (from 1.02ppm/yr to 0.43ppm/yr for Mauna loa)
Actually, it’s fairly clear that was not due primarily to any downturn in economic activity (in eastern europe or anywhere else)
In order for that to have been the case, the percent change in emissions (as a % of the previous year’s emissions), would have to have been similar to the percent change (drop) in the atmospheric CO2 growth from the previous year (ie, -58%). And it was not in that case (not even close).
(The volcanic explanation I linked to above is a far more plausible explanation in that case)
Even with a steep economic downturn, I doubt we would (will?) see a 50% drop in emissions (not unless the downturn lasted several years. 5 years at 10% yearly decline in emissions would be another story, of course.
And it seems to me that even the effect (on atmospheric CO2 growth) of a 5-10% drop in total worldwide human CO2 emissions (more plausible if there is a rather severe worldwide economic contraction) might still get lost in the “noise” (assuming a 5-10% drop in total human emissions leads to about a 0.1- 0.2ppm drop in the atmospheric CO2 growth.)
In fact, according to NOAA,
“The estimated uncertainty in the Mauna Loa annual mean growth rate is 0.11 ppm/yr”.
Hank Roberts // January 14, 2009 at 9:57 pm |
George, you’re using logic without RTFM, mistakenly assuming the number reflects changes ” …from the previous year (ie, -58%). And it was not in that case (not even close).”
Read the information at the Mauna Loa site on the time lags known between when changes in CO2 sources/sinks occur and when the change will appear in the mountain numbers.
These can be tied back to seasonal changes, longterm large drought events, and such as well as economic changes in fuel use and methane leaks. No, we don’t know how leaky the natural gas system of the USSR was before they shut it off or how well they’ve fixed it. We have some idea of their fossil fuel use though.
george // January 15, 2009 at 4:11 am |
Hank,
I think you missed the context of my above posts.
My post was a response to Eli’s comment
The main point of my above two posts was that that is simply not a plausible explanation for the drop in the yearly CO2 growth that occurred in the early 90’s (reaching a local min of 0.43ppm/yr in 1992)
The fact is, the total yearly world emissions went down very little (less than 1%) over that period, even though the USSR and eastern European emissions did decline significantly.
here are the world totals for the years in question
http://www.scribd.com/doc/5951/World-Carbon-Dioxide-Emissions-
88 20,992 million metric ton CO2
89 21,317 million metric ton ..
90 21,402 million metric ton
91 21,301 million metric ton
92 21, 243 million metric ton
93 21,483 million metric ton
94 21,666 million metric ton
95 22, 034 million metric ton
As I also indicated, the Pinatubo eruption is much more plausible as a reason, but the actual reason behind the drop in the yearly CO2 growth in early 90’s is not something i was even speculating about (only that it was most probably not due to economic downturn in the former USSR.
Also, I was under the impression (perhaps incorrect) that CO2 emissions (from burning of fossil fuels) mix in the atmosphere fairly quickly ( within a few months in northern hemisphere). This is where Mauna loa is, of course, and also where the former USSR was and Eastern Europe is, which is what Eli’s comment referred to. (and also where most of the world’s industrial activity is)
The relatively short initial mixing time means a downturn in economic activity in the former USSR and eastern Europe, which resulted in a decrease in emissions from that region, would have (in principle, at least) shown up fairly quickly (within months) in the Mauna Loa number, if the total decrease in world emissions had been large enough to “fall outside” (in this case below) the noise, that is.
But the point of my above posts was that the decrease was not large enough to have produced an effect on atmospheric CO2 that would have fallen outside the noise.
The total CO2 emissions decrease that accompanied the economic downturn in those regions (USSR, etc) in the early nineties would simply not have produced a big enough effect on total world emissions (< 1% change) to show up clearly (ie, outside the noise) in the Mauna loa number.
That’s what an order of magnitude estimate like I gave above indicates and it would apply even if the fossil fuel emissions (in this case from former USSR) took a year or more to mix in the northern hemisphere.
And for future reference, Hank, comments like your "RTFM" one detract from your posts. It’s more than a little arrogant (and not even justifiably so, in this case, in my opinion). Whence the hostility, anyway? Did I offend you in some way?
dko // January 15, 2009 at 5:25 am |
Gavin’s Pussycat wrote:
…BTW you can only use Pearson’s correlation and significance value for time series that are not significantly autocorrelated. You can see already by looking at the residuals wrt the parabola that that just isn’t the case here: I would visually guess 5-10 years correlation length.
From the fifth picture it looks like the derivative is close to “white”; if true, that would mean that CO2 itself is “red”.
OK, justly chastised on r^2; I should have caught that. But can someone clarify correlation length and how to estimate it visually. Also, what is the significance of white vs. red noise?
lowlander // January 15, 2009 at 3:39 pm |
George,
Do not forget that Mauna Loa measures not emissions but concentration of CO2 in the atmosphere. Therefore, changes year on year simply measure the rate of CO2 acumulation in the atmosphere.
There is no reason to believe that the rate of acumulation of CO2 in the atmosphere behaves in a linear way with anthropogenic emissions of CO2, in fact, since its accumation in the atmosphere is a consequence of an inbalance between emissions and sinks, that relationship should NOT be linear, it is much more likely to be logarithmic.
Remember that you are comparing variables which are related only in a indirect way.
Hank Roberts // January 15, 2009 at 4:26 pm |
Yep. George, people do come to climate sites posting their beliefs as though they were facts, based on their own logic and their own math, without any reference to the published sources, and then invite readers to prove them wrong.
You may have come up with your theory on your own rather than found it somewhere else and brought it here, I can’t tell without seeing your work. But the statements you make as though they were factual that I do recognize like the mixing rate don’t match what I recall of the published science.
If you showed your sources it’d be possible to read them and discuss them.
If you’d read the information at CDIAC and cited at least that, you’d have some facts on which to base your calculations.
It’s not you. It’s not your theory. It’s the lack of sources that makes people’s theories so hard to discuss. That’s why I mention the idea of reading the fine material available along with the charts at websites like CDIAC.
Hank Roberts // January 15, 2009 at 4:29 pm |
Here’s one. Just as an example, I found this via some of the links at CDIAC; look at the footnotes to this article, look up other research citing this article, look at other work by the authors, and look at the authors’ websites where you may find full text for material only available online as short abstracts. Again, it’s an example of how to find the discussion about this general topic – not meant as an authoritative paper answering it.
http://www3.interscience.wiley.com/journal/118652800/abstract?CRETRY=1&SRETRY=0
“… Our analysis also shows that the decadal average growth rate, linked primarily to human activity, has fluctuated around an all-time high value of ∼1.5 ppm yr−1 over the past 20 yr. A statistical model analysis is performed to identify the regions which have the maximum influence on the observed growth rate anomaly at Mauna Loa.”
Hank Roberts // January 15, 2009 at 4:32 pm |
Here’s a college lab page; note the suggestion to compare several different site records.
From: http://eesc.columbia.edu/courses/ees/climate/labs/co2/index.html
“… Task 4: What is responsible for the long-term change in CO2 concentrations measured at Mauna Loa? Go back to the graph showing the entire time series. Determine the long-term rate of change of the Mauna Loa CO2 concentrations by adding a trendline and displaying the equation of that line on the graph. What is the rate of change (including units)? Using the regression equation, extrapolate CO2 concentrations to the year 2100. How long will it take for CO2 to rise by 50% of the last measurement at this rate?
So far, you have assumed that the rate of increase in CO2 is constant. Is there evidence that the rate is actually systematically increasing or decreasing over the years? Do you have an explanation of this phenomenon? Based on the shape of the curves, do you think that you over- or underestimated the time it will take to exceed the latest measurement by 50%?…”
Hank Roberts // January 15, 2009 at 4:39 pm |
Ah, this one’s available in PDF from JAMSTEC.
So someone who actually knows something about this might be able to improve on my amateur attempts at finding good info.
http://www.jamstec.go.jp/frcgc/research/d4/prabir/papers/2004j.1600-0889.2005.00159.x.pdf
Tangential hello to a climate blogger there:
http://www.jamstec.go.jp/frsgc/research/d5/jdannan/#publications
Chris // January 16, 2009 at 8:00 pm |
[Response: This is getting ridiculous.
Back of the envelope says:
1994-1998: 1.99 plus or minus 0.6 ppm/yr
1999-2003: 1.82 plus or minus 0.6 ppm/yr
2004-2008: 1.91 plus or minus 0.4 ppm/yr
Linear regression 1994-2008: +0.011 plus or minus 0.065 ppm/yr/yr...........]
I’m sure some people will have wondered nonetheless on an intuitive level, how can the five-year averages go 1.99, 1.82, 1.91 and yet the linear regression for the fifteen-year period is up?
Well I would suggest it is largely due to the pattern of the “noise” in the middle 5 years, since the annual growth rates at Mauna Loa for 1999-2003 were 0.94, 1.74, 1.59, 2.56 and 2.25.
This pattern is clearly linked with ENSO. If you average the NOAA ONI for each of the years 1999-2003, you should get the following: -1.06, -0.74, -0.12, +0.78, +0.48. Hence La Nina in the first two years, neutral in the middle, and El Nino or very close to it in the last two years.
http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/lanina/enso_evolution-status-fcsts-web.pdf
If ENSO is linked with annual CO2 growth, and ENSO is itself largely “noise”, then is your trend therefore up (i.e. accelerating CO2 at ~0.01ppm/yr/yr) for arbitrary reasons?
I tried doing a linear regression for Mauna Loa annual CO2 growth, but with the figures for 1999-2003 changed to the following: 1.72, 1.77, 1.82, 1.87, 1.92 (centred on the actual average for the five years which was 1.82). Clearly I have chosen an acceleration that is 0.05 ppm/yr i.e. still five times the linear regression trend you highlight for the 15-year period, but of course much less than the actual ENSO-related acceleration during those 5 years.
The result I got is a trend of +0.000ppm/yr/yr i.e. dead flat.
Leaving wider arguments aside, or comments such as those of Mr Ladbury comparing me to a pig which I will not rise to, I simply would suggest this indicates the justification for posting my back-of-the-envelope check.
Chris // January 16, 2009 at 8:17 pm |
I should have added the starred bit below towards the end of my last post
“I tried doing a linear regression for Mauna Loa annual CO2 growth ***from 1994-2008***, but with the figures for 1999-2003 changed to the following……”
Also here’s the link for convenience of anyone else crunching these numbers. BTW I did my sums quite quickly just now so can’t guarantee they’re right, though i think they are.
http://www.esrl.noaa.gov/gmd/ccgg/trends/
gmo // January 16, 2009 at 10:25 pm |
*warp back in time one year*
http://www.esrl.noaa.gov/gmd/ccgg/trends/
(Annual Mean Growth Rate)
Back of the envelope says:
growth rate for last 5 years (2003-7) = 2.05 ppm/yr
For previous 5 (1998-2002) = 1.95 ppm/yr
For previous 5 (1993-1997) = 1.68 ppm/yr
*warp forward in time to present*
gmo // January 16, 2009 at 10:32 pm |
Doc Brown-ing it back two years gives:
growth rate for last 5 years (2002-6) = 2.13 ppm/yr
For previous 5 (1997-2001) = 1.83 ppm/yr
For previous 5 (1992-1996) = 1.37 ppm/yr
Somehow it does not seem like a good idea for me to claim that in the last two years the trend in CO2 growth rate has gone from around 0.07 ppm/yr/yr to about nil ppm/yr/yr
Back of the envelope can be interesting, but it can also deserve a quick bat-down.
Chris // January 16, 2009 at 11:15 pm |
1992 and 1993 = post Pinatubo (average annual CO2 growth rate for 1992 and 1993 combined was +0.89 ppm/yr)
c.f. sea and land temp anomalies
NH SST anomaly:
1990: 0.226
1991: 0.161
1992: 0.033
1993: 0.037
1994: 0.173
http://www.cru.uea.ac.uk/cru/data/temperature/hadsst2nh.txt
NH land surface temp anomaly:
1990: 0.345
1991: 0.245
1992: 0.037
1993: 0.079
1994: 0.234
http://www.cru.uea.ac.uk/cru/data/temperature/hadcrut3nh.txt
“Somehow it does not seem like a good idea for me to ….”
To me it does not seem like a good idea to dismiss the trend of the past 15 years on the basis of the two unusual years preceding them.
Chris // January 16, 2009 at 11:28 pm |
Correction I accidentally posted NH combined land/ocean as land data in last post.
Here’s true NH land surface temp anomaly (greater temperature dip in 1992 and 1993 than for ocean of course)
1990: 0.592
1991: 0.418
1992: 0.085
1993: 0.174
1994: 0.434
http://www.cru.uea.ac.uk/cru/data/temperature/crutem3nh.txt
Brian Klappstein // January 18, 2009 at 7:32 pm |
The significant question is not whether the growth rate change is accelerating or not, it’s whether the rate is accelerating as predicted or not, relative to the growth rate in emissions, i.e. what are the sinks doing?
My intuition, based on attempts to correlate the growth rates in anthropogenic emission vs. atmospheric CO2 is that the sinks are not weakening.
However, as Chris correctly notes the growth rate is influenced by the ENSO state and so the relationship is complicated.
Regards, BRK
Brian Klappstein // January 18, 2009 at 8:14 pm |
Correction to my point above. The sinks DID appear to be weakening through the late 70’s to the late 90’s. And any trends thereafter I’m not allowed to talk about since they aren’t trends if they’re not statistically significant.
Regards, BRK