Guest commentary by Barry R. Bickmore, Brigham Young University
If you look around the websites dedicated to debunking mainstream climate science, it is very common to find Lord Christopher Monckton, 3rd Viscount of Brenchley, cited profusely. Indeed, he has twice testified about climate change before committees of the U.S. Congress, even though he has no formal scientific training. But if he has no training, why has he become so influential among climate change contrarians? After examining a number of his claims, I have concluded that he is influential because he delivers “silver bullets,” i.e., clear, concise, and persuasive arguments. The trouble is his compelling arguments are often constructed using fabricated facts. In other words, he makes it up. (Click here to see a number of examples by John Abraham, here for a few by myself, and here for some by Tim Lambert).
Here I’m going to examine some graphs that Lord Monckton commonly uses to show that the IPCC has incorrectly predicted the recent evolution of global atmospheric CO2 concentration and mean temperature. A number of scientists have already pointed out that Monckton’s plots of “IPCC predictions” don’t correspond to anything the IPCC ever predicted. For example, see comments by Gavin Schmidt (Monckton’s response here,) John Nielsen-Gammon (Monckton’s response here,) and Lucia Liljegren. Monckton is still happily updating and using the same graphs of fabricated data, so why am I bothering to re-open the case?
My aim is to more thoroughly examine how Lord Monckton came up with the data on his graphs, compare it to what the IPCC actually has said, and show exactly where he went wrong, leaving no excuse for anyone to take him seriously about this issue.
Atmospheric CO2 Concentration
By now, everyone who pays any attention knows that CO2 is an important greenhouse gas, and that the recent increase in global average temperature is thought to have been largely due to humans pumping massive amounts of greenhouse gases (especially CO2) into the atmosphere. The IPCC projects future changes in temperature, etc., based on projections of human greenhouse gas emissions. But what if those projections of greenhouse gas emissions are wildly overstated? Lord Monckton often uses graphs like those in Figs. 1 and 2 to illustrate his claim that “Carbon dioxide is accumulating in the air at less than half the rate the UN had imagined.”
Figure 1. Graph of mean atmospheric CO2 concentrations contrasted with Monckton’s version of the IPCC’s “predicted” values over the period from 2000-2100. He wrongly identifies the concentrations as “anomalies.” Taken from the Feb. 2009 edition of Lord Monckton’s “Monthly CO2 Report.”
Figure 2. Graph of mean atmospheric CO2 concentrations contrasted with Monckton’s version of the IPCC’s “predicted” values over the period from Jan. 2000 through Jan. 2009. Taken from the Feb. 2009 edition of Lord Monckton’s “Monthly CO2 Report.”
It should be noted that Lord Monckton faithfully reproduces the global mean sea surface CO2 concentration taken from NOAA, and the light blue trend line he draws through the data appears to be legitimate. Unfortunately, nearly everything else about the graphs is nonsense. Consider the following points that detail the various fantasies Monckton has incorporated into these two graphics.
Fantasy #1.
Lord Monckton claims the light blue areas on his graphs (Figs. 1 and 2) represent the IPCC’s predictions of atmospheric CO2 concentrations.
Reality #1.
The IPCC doesn’t make predictions of future atmospheric CO2 concentrations. And even if we ferret out what Lord Monckton actually means by this claim, he still plotted the data incorrectly.
The IPCC doesn’t really make predictions of how atmospheric CO2 will evolve over time. Rather, the IPCC has produced various “emissions scenarios” that represent estimates of how greenhouse gas emissions might evolve if humans follow various paths of economic development and population growth. The IPCC’s report on emissions scenarios states, “Scenarios are images of the future, or alternative futures. They are neither predictions nor forecasts. Rather, each scenario is one alternative image of how the future might unfold.” Lord Monckton explained via e-mail that he based the IPCC prediction curves “on the IPCC’s A2 scenario,which comes closest to actual global CO2 emissions at present” (2). In his “Monthly CO2 Report” he added, “The IPCC’s estimates of growth in atmospheric CO2 concentration are excessive. They assume CO2 concentration will rise exponentially from today’s 385 parts per million to reach 730 to 1020 ppm, central estimate 836 ppm, by 2100,” which is consistent with the A2 scenario. In other words, Monckton has picked one of several scenarios used by the IPCC and misrepresented it as a prediction. This is patently dishonest.
Monckton’s misrepresentation of the IPCC doesn’t end here, however, because he has also botched the details of the A2 scenario. The IPCC emissions scenarios are run through models of the Carbon Cycle to estimate how much of the emitted CO2 might end up in the atmosphere. A representative (i.e., “middle-of-the-road”) atmospheric CO2 concentration curve is then extracted from the Carbon Cycle model output, and fed into the climate models (AOGCMs) the IPCC uses to project possible future climate states. Figure 3 is a graph from the most recent IPCC report that shows the Carbon Cycle model output for the A2 emissions scenario. The red lines are the output from the model runs, and the black line is the “representative” CO2 concentration curve used as input to the climate models. I digitized this graph, as well, and found that the year 2100 values were the same as those cited by Monckton. (Monckton calls the model input the “central estimate.” )
Figure 3. Plot of atmospheric CO2 concentrations projected from 2000-2100 for the A2 emissions scenario, after the emissions were run through an ensemble of Carbon Cycle models. The red lines indicate model output, whereas the black line represents the “representative” response that the IPCC used as input into its ensemble of climate models (AOGCMs). Taken from Fig. 10.20a of IPCC AR4 WG1.
Now consider Figure 4, where I have plotted the A2 model input (black line in Fig. 3), along with the outer bounds of the projected atmospheric CO2 concentrations (outer red lines in Fig. 3). However, I have also plotted Monckton’s Fantasy IPCC predictions in the figure. The first thing to notice here is how badly Monckton’s central tendency fits the actual A2 model input everywhere in between the endpoints. Monckton’s central tendency ALWAYS overestimates the model input except at the endpoints. Furthermore, the lower bound of Monckton’s Fantasy Projections also overestimates the A2 model input before about the year 2030. What appears to have happened is that Lord Monckton chose the correct endpoints at 2100, picked a single endpoint around the year 2000-2002, and then made up some random exponential equations to connect the dots with NO REGARD for whether his lines had anything to do with what the IPCC actually had anywhere between.
Figure 4. Here the black lines represent the actual A2 input to the IPCC climate models (solid) and the upper and lower bounds of the projected CO2 concentrations obtained by running the A2 emissions scenario through an ensemble of Carbon Cycle models. This data was digitized from the graph in Fig. 3, but a table of model input concentrations of CO2 resulting from the different emissions scenarios can be found here. The red lines represent Monckton’s version of the IPCC’s “predicted” CO2 concentrations. The solid red line is his “central tendency”, while the dotted lines are his upper and lower bounds. Monckton’s data was digitized from the graph in Fig. 1.
John Nielsen-Gammon also pointed some of this out, but Lord Monckton responded:,
[Nielsen-Gammon] says my bounds for the 21st-century evolution of CO2 concentration are not aligned with those of the UN. Except for a very small discrepancy between my curves and two outliers among the models used by the UN, my bounds encompass the output of the UN’s models respectably, as the blogger’s own overlay diagram illustrates. Furthermore, allowing for aspect-ratio adjustment, my graph of the UN’s projections is identical to a second graph produced by the UN itself for scenario A2 that also appears to exclude the two outliers.
It is fair enough to point out that Fig. 10.26 in IPCC AR4 WG1 has a plot of the projected A2 CO2 concentrations that seems to leave out the outliers. However, Monckton’s rendition is still not an honest representation of anything the IPCC ever published. I can prove this by blowing up the 2000-2010 portion of the graph in Fig. 4. I have done this in Fig. 5, where I have also plotted the actual mean annual global CO2 concentrations for that period. The clear implication of this graph is that even if the A2 scenario did predict atmospheric CO2 evolution (and it doesn’t,) it would actually be a good prediction, so far. In Figures 1 and 2, Lord has simply fabricated data to make it seem like the A2 scenario is wrong.
Figure 5. This is a blow-up of the graph in Fig. 4 for the years 2000-2010. I have also added the annual global mean atmospheric CO2 concentrations (blue line), obtained from NOAA.
Fantasy #2.
Monckton claims that “for seven years, CO2 concentration has been rising in a straight line towards just 575 ppmv by 2100. This alone halves the IPCC’s temperature projections. Since 1980 temperature has risen at only 2.5 °F (1.5 °C) per century." In other words, he fit a straight line to the 2002-2009 data and extrapolated to the year 2100, at which time the trend predicts a CO2 concentration of 575 ppm. (See the light blue line in Fig. 1.)
Reality #2.
It is impossible to distinguish a linear trend from an exponential trend like the one used for the A2 model input over such a short time period.
I pointed out to Lord Monckton that it’s often very hard to tell an exponential from a linear trend over a short time period, e.g., the 7-year period shown in Fig. 2. He replied,
I am, of course, familiar with the fact that, over a sufficiently short period (such as a decade of monthly records), a curve that is exponential (such as the IPCC predicts the CO2 concentration curve to be) may appear linear. However, there are numerous standard statistical tests that can be applied to monotonic or near-monotonic datasets, such as the CO2 concentration dataset, to establish whether exponentiality is being maintained in reality. The simplest and most direct of these is the one that I applied to the data before daring to draw the conclusion that CO2 concentration change over the past decade has degenerated towards mere linearity. One merely calculates the least-squares linear-regression trend over successively longer periods to see whether the slope of the trend progressively increases (as it must if the curve is genuinely exponential) or whether, instead, it progressively declines towards linearity (as it actually does). One can also calculate the trends over successive periods of, say, ten years, with start-points separated by one year. On both these tests, the CO2 concentration change has been flattening out appreciably. Nor can this decay from exponentiality towards linearity be attributed solely to the recent worldwide recession: for it had become evident long before the recession began.
In other words, the slope keeps getting larger in an exponential trend, but stays the same in a linear trend. Monckton is right that you can do that sort of statistical test, but Tamino actually applied Monckton’s test to the Mauna Loa observatory CO2 data since about 1968 and found that the 10-year slope in the data has been pretty continuously rising, including over the last several years. Furthermore, look at the graph in Fig. 5, and note that the solid black line representing the A2 climate model input looks quite linear over that time period, but looks exponential over the longer timeframe in Fig. 4. I went to the trouble of fitting a linear trend line to the A2 model input line from 2002-2009 and obtained a correlation coefficient (R2) of 0.99967. Since a perfectly linear trend would have R2 = 1, I suggest that it would be impossible to distinguish a linear from an exponential trend like that followed by the A2 scenario in real, “noisy” data over such a short time period.
Temperature Projections
Atmospheric CO2 concentration wouldn’t be treated as such a big deal if it didn’t affect temperature; so of course Lord Monckton has tried to show that the Fantasy IPCC “predictions” of CO2 concentration he made up translate into overly high temperature predictions. This is what he has done in the graph shown in Fig. 6.
Figure 6. Lord Monckton’s plot of global temperature anomalies over the period January 2002 to January 2009. The red line is a linear trend line Monckton fit to the data, and the pink/white field represents his Fantasy IPCC temperature predictions. I have no idea what his base period is. Taken from the Feb. 2009 edition of Lord Monckton’s “Monthly CO2 Report.”.
FANTASY #3. Lord Monckton uses graphs like that in Fig. 6 to support his claim that the climate models (AOGCMs) the IPCC uses to project future temperatures are wildly inaccurate.
REALITY #3.
Monckton didn’t actually get his Fantasy IPCC predictions of temperature evolution from AOGCM runs. Instead, he inappropriately fed his Fantasy IPCC predictions of CO2 concentration into equations meant to describe the EQUILIBRIUM model response to different CO2 concentrations.
Monckton indicated to me (5) that he obtained his graph of IPCC temperature predictions by running his Fantasy CO2 predictions (loosely based on the A2 emissions scenario) through the IPCC’s standard equation for converting CO2 concentration to temperature change, which can be found here.
The problem is that the equation mentioned is meant to describe equilibrium model response, rather than the transient response over time. In other words, they take the standard AOGCMs, input a certain stabilized CO2 concentration, and run the models until the climate output stabilizes around some new equilibrium. But it takes some time for the model systems to reach the new equilibrium state, because some of the feedbacks in the system (e.g., heat absorption as the ocean circulates) operate on fairly long timescales. Therefore, it is absolutely inappropriate to use the IPCC’s equation to describe anything to do with time evolution of the climate system. When I brought this up to Lord Monckton, he replied that he knows the difference between equilibrium and transient states, but he figures the equilibrium calculation comes close enough. But since the IPCC HAS published time-series (rather than just equilibrium) model output for the A2 scenario (see Fig. 7,) why wouldn’t he just use that?
Figure 7. Ensemble AOGCM output for the A2 emissions scenario, taken from Fig. 10.5 of IPCC AR4 WG1.
The answer is that if Lord Monckton had used the time-series model output, he would have had to admit that the IPCC temperature projections are still right in the ballpark. In Fig. 8, I have digitized the outer bounds of the model runs in Fig. 7, and also plotted the HadCRUT3 global annual mean temperature anomaly over the same period. The bottom line is that Monckton has put the wrong data into the wrong equation, and (surprise!) he got the wrong answer.
Figure 8. The blue and green lines represent the upper and lower bounds of the global average temperature anomaly from AOGCM output for the A2 emissions scenario during the 2002-2010 period. The black line represents the HadCRUT3 global temperature anomalies for that timeframe, normalized to the same base period.
Summary
I have shown here that in order to discredit the IPCC, Lord Monckton produced his graphs of atmospheric CO2 concentration and global mean temperature anomaly in the following manner:
- He confused a hypothetical scenario with a prediction.
- He falsely reported the data from the hypothetical scenario he was confusing with a prediction.
- He plugged his false data into the wrong equation to obtain false predictions of time-series temperature evolution.
- He messed up the statistical analyses of the real data.
These errors compound into a rather stunning display of complete incompetence. But since all, or at least nearly all, of this has been pointed out to Monckton in the past, there’s just no scientifically valid excuse for this. He’s just making it up.
flxible (#347)
I think Canadian politics might be slightly off topic, but I will reply (but only once out of respect for the comment policy).
I think you are misreading why the prime minister is taking the stance he is. IMHO, he isn’t doing it to swell the federal coffers (although he’s certainly not turning it away). Ask yourself why is it only recently has the tar sands been exploited? The amount of oil there is one of the largest reserves in the world (possibly the largest although it’s hard to say since the Saudi’s refuse to say how big their reserve is). However, back in the 80’s only a small section was accessible since it required so much energy to extract it. Even this was essentially taken away from Alberta because of the National Energy Program. Alberta has invested a lot of time, energy and money into developing these resources in an efficient manner. Just when they succeed (partially due to oil prices as well) they are being told that all their work was dirty money and they are fossils.
As a moderate conservative, I would support using the money generated from the oil sands in order to develop cleaner energy and industries in Alberta, but you cannot just tell them to shut down the oil sands (decimating only Alberta, essentially) and tell them on top of all that we are taking away all the money that you made from the oil sands since it is dirty money and give it to other countries (since they need it more). That argument doesn’t work with me and it won’t work with any conservative I imagine.
The lesson that this can give to the rest of the world in how to secure action to climate change, is that any deal needs to recognize that each country is in a unique situation. Also, denigrating world leaders as fossils (however much you think they are) will not likely get them to change their mind. Reasoned discussion in order to find policies acceptable to all will. As Jon Stuart said “Why can’t we all be reasonable!” How apropos!
BTW, flxible, if you want to know more about my position (I personally like hearing differing viewpoints), I have no trouble corresponding with you by email. Can one of the moderators pass my email along if needed (I actually don’t know)?
I’m going to miss Christopher, and told him I’ll drop by Hyde Park in about ten years to listen to his ravings from atop a cardboard box. McIntyre (“The hockey stick is broken!”) and Watts (temperature stations) have been equally discredited, just in the last year. They will also have special places in my heart.
In response, Koch and Tillerson appear to have gone to the bullpen for actual scientists like Christy and Curry, albeit from the Bible Belt. They might as well have gone to the barnyard for all the good it did. On any factual analysis, this is over, and the facts may be finally creeping up on both journalists and the public.
No thanx Sambo, I understand your position – better than you understand why it took high petro prices to make the tar sands a profitable proposition. If you think “efficiency improvements” by the province is why it’s possible for the petro companies to make a profit there, and so pay a lot of royalties and taxes, you’re not paying attention. Comparing the tar sands to Saudi conventional deposits is obfuscation, about 10% of the extant deposits were considered “profitable” at 2006 market prices, the further past peak oil we get, the greater that percentage may get, but the environment is paying a very high price so Canada and the U.S. can proceed with business as usual. The lesson the rest of the world is learning is that N.Americans have little concern for the rest of the planet or future generations, and Canada has no regard for international agreements it signs.
323 Lynn Vincentnathan: “what kind of alarm clock will it take to wake up people”
It would take raising their intelligence and giving them degrees in physics. They see 2 people who are dressed alike and both are called “scientists.” One is a fake, but they have no idea which one. As I said before, Monckton is dangerous precisely because he appears to be doing science, just like the real scientists. Most people literally cannot figure out what is going on. It helps a lot if you tell them that the fossil fuel industry has a $1 TRillion/year cashflow and that is enough money to hire a lot of liars to pretend to be scientists. It helps to show them the book “Climate Cover-Up” or tell them what the book says. The problem is in getting the information to them in spite of the obvious bias of the media.
333 Septic Matthew: “Civilization has survived many catastrophes already”
But not catastrophes that killed 99.99% of the citizens.
Please read: “The Long Summer” by Brian Fagan and “Collapse” by Jared Diamond.
“As a moderate conservative, I would support using the money generated from the oil sands in order to develop cleaner energy and industries in Alberta, but you cannot just tell them to shut down the oil sands (decimating only Alberta, essentially) and tell them on top of all that we are taking away all the money that you made from the oil sands since it is dirty money and give it to other countries (since they need it more).” – 351
So as a Conservative you argue that it isn’t the job of corporations and the free market to use oil profits to develop a sustainable energy industry in Alberta?
It would seem that example of Corporations failing to see the writing on the wall is another example of the inability of corporations to act rationally and in their own long term best interest.
How do you propose that they be prompted to act responsibly and in their own best interest? Regulation or Taxation? Or do you have some other magical means of influence?
@ #304 – I have Hashimoto’s, which is kind of the opposite of Grave’s, but shares some of the same symptoms, still being a malfunction of the immune system affecting the thyroid. For either one, once it is adequately treated, the major symptoms abate quickly, save for some lingering discomfort and annoyances. So, presuming that he has actually gotten adequate treatment, I’m afraid we can’t blame his rantings on his autoimmune condition. Alas, he therefore comes by it as part of his baseline personality.
[Response: People’s medical histories and personal issues are completely off topic. Let’s please stick to the relevant climate science. Thanks. – gavin]
RE #183 – The Turing test is science fiction? – Do you have any idea what the test is or who Turing was?
Who would take someone who actually uses the full title Lord Christopher Monckton, third Viscount Monckton of Brenchley seriously? What an absurd character.
A site HTML problem:
In Safari 4.1.1, the tan vertical side bar is placed about 5 spaces to the left and writes over the header. The word ‘index’ is obscured except for the ‘i’ and long link address also get truncated. Thought someone would want to know.
catman306 at the gmail.com
Sorry, Gavin, I only meant to point out that Monckton’s position on climate change is not likely due to a medical condition.
Re #357 — the biggest puzzler for me in post 183 was listing the “Dean drive” as a prediction. The drive was a simple hoax, claiming to have invented a miracle reactionless drive. The last time I recall seeing this hoary old fraud was in the mid-1970s when it briefly resurfaced in the Analog sci-fi magazine.
358 gc asks: ‘Who would take someone who actually uses the full title Lord Christopher Monckton, third Viscount Monckton of Brenchley seriously?’
This is not his full title, it is an incorrect version used by journalists and foreigners. He is correctly known as ‘Christopher Monckton, 3rd Viscount Monckton of Brenchley’, addressed as ‘Lord Monckton’ in person or as a salutation, and as ‘The Viscount Monckton’ on an envelope [though this is going out of use].
The style ‘Lord Christopher Monckton’ is used only for the younger sons of a duke; the duke’s eldest son uses one of their father’s lesser titles as a ‘courtesy title’.
There is a fuller explanation at: http://en.wikipedia.org/wiki/Forms_of_address_in_the_United_Kingdom
[edit – take the cherry-picking and denier talking points elsewhere]
Is it true that the models showing the effect of increasing co2 in the atmosphere have been scaled down to fit recent data as lord monckton says.If temperatures are going to be so much warmer in fifty years time than they are now. When are they going to start rising?
[Response: Almost nothing that Monckton says is true, and this is no exception. The models have not been ‘scaled in any way. And temperatures are rising. – gavin]
PhilC saw fit to draw attention to Lewis Carroll’s The Hunting of the Snark as somehow relevant to his comment thread, or this post. I must thank him, as I haven’t re-read The Snark in some time, and in so doing it occurred to me just how well it relates to the question at hand (as well as J. Curry’s recent use of the word “snark”).
With apologies to Lewis Carroll, for my very slight modification of his words, and with apologies to the serious posters here, for my wholly inappropriate injection of levity, here are the first verses from that poem’s “Fit the Second, Lord Monckton’s Speech”:
Re 275 wili – Why would it stop falling at that rate after 3 weeks? – because, maintaining the same rate of respiration/decay, the organic C in marine biota (now about 3 Gt according to the website http://es.carboncycle.aos.wisc.edu/global-carbon-cycle/ ) would be completely oxidized at that point (but see below for some added wrinkles).
(This is setting aside oxidation of organic C that has settled to the seafloor; there is a significant amount (about 50 times the marine biota) but the flux is very slow – the total C added to the sea floor each year is about 0.2 Gt, which is a tiny fraction of the 50 Gt cycled through marine biota; even if that were all organic C (I think it is actually mostly inorganic), the rate of oxydation of organic C in the ocean would still have to be almost equal to the rate of organic C production, which is the approximation I used before in calculating the rate of O2 uptake by that process.
However, a double check of the diagram shows that it doesn’t distinguish between organic and inorganic C in the deep and intermediate ocean, so the total amount of organic C within the ocean that is available to be oxidized at that rate (using O2 at a rate of 0.011 % of atmospheric O2 per year) could be larger; however, oxygen depletion in the deeper ocean water wouldn’t pull O2 out of the atmosphere until that water resurfaced.) Almost 80 % of the flux of C out of marine biota is back to the upper ocean water; assuming it is inorganic, that implies that, of the 0.011 %/year oxydation rate (in terms of the amount of atmospheric O2), almost 0.0088 % is directly from organic C in the upper ocean and a bit more than 0.0022 % occurs in the deeper ocean. Halting the production of marine biota C and maintaining the same fluxes of C out of marine biota, the marine biota C would be used up in about 3 weeks, at which point a 0.0022 % / year ** drawdown of O2 could persist for some longer time (**the actual removal of O2 from the atmosphere via oxidation in the deeper ocean may occur over a timescale of 1000 years, but the oxydation of organic C in the ocean might be completed over a significantly shorter time, so the actual removal of O2 from the atmosphere may be slower than 0.0022 %/year) – but it still wouldn’t have much total effect on the amount of atmospheric O2. Of course, the actual rates of oxydation wouldn’t stay constant as organic C either in the upper or deeper ocean is used up; the rate would tend to slow down more gradually over time as organic C is used up.)
(if 20 % of geologic burial of C (0.2 Gt/year) is organic C and if that is nearly balanced by oxidation of geologic organic C, that would be a C flux of 0.04 Gt/year, which is 0.08 % of 50 Gt/year, so the oxygen depletion, as a fraction of total atmospheric O2, would be 0.08 % * 0.011 %/year = 0.0000088 %/year – or 8.8 E-6 %/year; it would take a bit more than 10 million years to use up all atmospheric O2 by such a process. I don’t know how much geologic organic C there is offhand but there’s a lot (far more than in recoverable fossil fuels); of course, there’s also the ferrous Fe O2-sink, and the O2 source of H-escape to space that would continue to operate if biological processes ceased (although lack of atmospheric CH4 would slow the H-escape.)
Help, help. Anyone want to tell me what’s going on with this chart (which shows glaciers decreasing supposedly at the same rate before “hydrocarbon use”: http://scienceandpublicpolicy.org/images/stories/press_releases/goreerrors/15.gif
I have to give a response to this
363: [edit – take the cherry-picking and denier talking points elsewhere]
ok
Lynn Vincentnathan @367 — Hydrocarbon burning is considered to have begun increasing around 1750 CE; see the emissions graph posted on website for Carbon Dioxide Information Analysis Centeer @ ORNL.
Glaciers respond the local temperature and precipitation. Both have been changing (global temperature increasing, on average, from before 1750 CE according to some analyses). Glaciers world-wide haven’t been measured with any accuracy before quite recently; I presume the graph you link is based on the Swiss glaciers, only one (small) region.
Lynn, as David B. implies, I would recommend requesting the source of SPPI’s data for that graph.
It’s not like making sh*t up is beyond them.
I downloaded the Mauna Loa CO2 monthly data from March 1958 through July 2010 and plotted it (Interpolated) using a common spreadsheet program that has trending analysis. There are 629 monthly data points.
Results-
Linear Trend
Y=0.1201x+308.62
R^2=0.9771
Exponential Trend
y=310.13e^0.003x
R^2=0.9822
The conclusion, based upon the data, is that the monthly level of CO2 increase at Mauna Loa can be accurate represented by either a Linear Trend or an Exponential Trend, with the Exponential trend having a slightly higher R^2 value.
However, the plot for the month to month Delta PPM is hardly convincing that the rate of change is growing alarmingly.
For the monthly rate of change in Delta PPM (Interpolated) results are as follows-
Linear Trend
y=0.0002x+0.0566
R^2=0.0009
Re Orkneygal (nice name!) – However, the plot for the month to month Delta PPM is hardly convincing that the rate of change is growing alarmingly.
Have you tried subtracting the longer term trend from the data and then fitting the result with some sinusoidal functions?
I think at this point just holding the rate of change steady is more than sufficient cause for concern.
It seems that make believe does not stop in childhood…
Thanks David #369 and Chek #370. I also thought — knowing a tiny bit about history — that the industrial revolution began around 1800, and coal had been burned for centuries before that.
Anyway, speaking of the devil. Guess who’s on the personnel list of that org that has that graph — the Lord himself almighty of “Monckton Makes It Up” fame… see http://scienceandpublicpolicy.org/personnel.html
Patrick 27-
The NOAA data set includes a column for seasonally adjusted values, which is generally agreed removes the cyclical patterns caused by the NH season changes (i.e. more growth during NH spring means more CO2 from bio-mass expiration.)
With the slope of the rate of change effectively “0”, and the known seasonality adjustments already included in the NOAA data set, what additional information do you think your suggestion might offer?
Would it be at all possible for you to create your interpretation or provide some “official interpretation”, in graph form, what the IPCC implies in their findings (I assume from your statement the IPCC makes no predictions, but they do lay down a framework of effect of GW that surely has measurable effects over time) so that we can compare it against what Lord Monckton has plotted? It would make all this much more clear for we lay people to see the graphical view of the IPCC’s perspective jotted down next to the Viscount’s plots.
Ob 367, coal use started earlier than that chart implies. I also wonder, though, what role soot (from any source) may have played in darkening the surface of some glaciers and hence hastened their melt rate.
Lynn,
After some googling i found that the graph is taken from this article.
http://www.oism.org/pproject/GWReview_OISM600.pdf
They source it with this study that uses glacier length as temperature proxies.
http://home.badc.rl.ac.uk/mjuckes/mitrie_files/docs/mitrie_glaciers.pdf
I found the latter a very interesting read but it is not clear how they derived their graph from this study…It does not seem to support their hypothesis (glacier melt a linear trend since 1810) at all…
hope this helps..
(moderator, please delete my previous post and this sentence, the first link was wrong)
Sanford and Sun: In my view, figure 5 above is the clearest summary of the situation.
The argument is threefold:
1) The actual observed CO2 is exceedingly close to the real IPCC A2 model input.
2) The real IPCC range is much larger than “estimated” by Monckton.
3) A2 is only a scenario, so projecting it forward and comparing it to projected CO2 is comparing one guess with another: spectacularly silly.
Really, Monckton’s graphs are just plain confusing until you accept that he’s simply lying.
Thanks, David, Chek, Harmen, and Wili,
Here is what I responded:
Thanks again for your time and efforts.
On a related note to the Monckton article, I would like to switch gears and commend a very reliable expert on global warming, Gavin Schmidt, for appearing on a major news outlet source and reaching the “global public square”.
More scientists with his rank and articulation skills are needed for major media appearances speaking on the science of global warming. This is the only way that everyday people will hear a clear message on where we are, where we are headed and what our options are. To all the reliable expert scientist out there, please keep up the wide exposure route of communications along with the excellent websites and blogs already available.
Lynn Vincentnathan — 14 August 2010 @ 6:48 PM
They deceptively create a breakpoint by using “hydrocarbon” as a proxy for CO2/temperature/glacier melt – CO2 emissions per gigajoule will decrease as oil and natural gas are substituted for coal. They also plot tons of fuel instead of the log of CO2 concentration.
Re 375 Orkneygal – Okay; sorry I misunderstood your comment.
Lynn Vincentnathan (367), as a skeptic I’m probably incented to read into the graph what you read and what the graph asserts. But, while I did not do any rigorous statistical graphical analysis, I can not see anything in the chart that points to hydrocarbon use not being a factor in glacial shortening. Even though the chart picks a somewhat late date for the start HOC use increase, and as much as I would prefer to believe them, to the unaided eye it sure looks like glacial shortening is right in lockstep with HOC use. Maybe it is not the whole answer (and I believe it is not), but how they got the negative answer is boggling.
Orkneygal #371:
I made that mistake initially too. The problem with trying to extrapolate the Mauna Loa data into the future as an exponential fit is that the sample period is too short. First, you need to look at the data in this format:
Linear CO2 trends since 1960
It’s obviously going up exponentially. Then, Rick Baartman has come up with an equation that shows if we keep to the current trend of CO2 emissions, we will ‘achieve’ doubling around the year 2050, at approximately 550ppm:
CO2 = 275 + 2^((year-1780)/33.41)
(based on the anthropogenic component of CO2 doubling about every 30 years since the start of the industrial revolution). But as with the IPCC projections, that is based on the current scenario where anthropogenic CO2 doubling occurs every ~30 years. It could well get worse than that :-\
Secular Animist, I agree. Quality blogs such as this one should be addressing catastrophe scenarios, whether we pause for a little fun with His Lordship or not. When a new study about methane comes out, the instinct at RC is a bit too much on the cautious side, even if the relevant data (Shakova, Walter) is solid.
Steve Metzler @385
I’m not sure what supposed error you are referring to.
I did not make any attempt to extrapolate the regression models into the future in my report above. I only reported what the two regression techniques calculate using a simple spreadsheet tool.
As I noted, the two R^2 values (for linear and exponential fit) are very close to each other.
Also, the slope of the monthly rate of change is nearly 0 and there are over 600 data points in the trend charts. Since CO2 is released continuously into the atmosphere by human activity, biomass activity and geologic activity, one would think that any exponential growth would be clearly visible and clearly differentiated in the statistical analysis of over 600 monthly measurements, in my opinion.
Irrespective of my opinion, the dataset analysis gives a slight nod to exponential growth based upon R^2. Just as the IPCC AR4 suggests is possible. However, the growth rate is “just barely” exponential as the high R^2 value for a linear fit attest.
orkneygal: “just barely exponential” you say. Actually,it is “just barely” second-order polynomal (even higher R^2 for that one, 0.999). Another problem is that the residuals are not randomly distributed for the linear fit, with at the start and end part of the curve up to 6 ppm deviation from the fitted value, and in the middle -3.5 ppm.
For the exponential growth it is 5 and -3, respectively; the second-order polynomal the largest deviation in either direction is a mere 2 ppm (and that’s in the middle.
If I extrapolate to 2050 (x=1116), you’ll see what the difference becomes:
linear fit => 442.5 ppm
exponential fit => 457.0 ppm
second-order poly => 493.8 ppm
Now, you may claim that 14.5 ppm doesn’t matter that much for the linear vs exponential fitting. But how about the 50 ppm difference for the second-order polynomal?
Small differences matter…
Orkneygal: I don’t understand you at all. Why do you want the exponential coefficient to be so high that it is “clearly visible”? What is your problem with the low, low figure that is almost a straight line over a short period?
You accept that it is a better fit, so why do you reject it? I don’t understand how you state your conclusion, then turn around and claim the opposite. It’s not consistent.
Clearly, you are thinking ahead, and subconsciously saying “this curve isn’t going to keep going, so the linear model must be better”. But that’s not valid logic, which is why you haven’t thought about it openly. Over the data we have, the exponential fit works better. And if you look at historical data, an exponential fit has more justification than, say, a quadratic fit.
And guessing about the future is pure speculation – so the IPCC have covered all the bases in their scenarios.
Orkneygal #387:
You’re not isolating the anthropogenic component from the total ppm in the atmosphere, so that’s why your R^2 value is “just barely” exponential. Try this instead as suggested in my previous post:
CO2 = 275 + 2^((year-1780)/33.41)
For the first year that Mauna Loa measurements began, 1959, you get this value:
CO2 = 316 ppm (measured average for 1959 was: 315.98 ppm)
And 2010:
CO2 = 393.12 ppm (reading for June of this year was: 392.04 ppm)
Little high, but we still have 6 months to go this year. Also, try somewhere in the middle, say 1990:
CO2 = 353 ppm (measured average for 1990 was: 354.19 ppm)
Seems like a pretty good fit. And now the scarier stuff:
2030: 453.87 ppm
2050: 545.86 ppm
That’s just about a doubling from pre-industrial CO2 concentration by 2050. Yikes. But hey, I’m a ‘warmist’, so my assumptions must be wrong. Really, there’s nothing to worry about. Not at all. Pumping 28 billion metric tonnes of CO2, a known greenhouse gas, into the atmosphere every year couldn’t possibly have any undesirable effect on Earth’s fragile biosphere, could it? Nah.
Steve Metzler-
Thank you for your response to my simple calculations.
However, I am not sure what “mistake” you are referring to.
I simply ran the data through commonly available spreadshet functions.
That simple data analysis clearly shows that CR^2O2 level increases at the Hawaii measuring site are slightly better described by an expontential, based upon R^2.
I made no error.
What error did you make?
Orkneygal, to see the super-linear–indeed super-exponential–growth–you need to look at the rate of increase of the rate of increase. Use yearly figures, as you will have less noise. Look at:
delta[CO2]ij/[CO2]i as a time series. This rate of increase exhibits a clear linear upward trend, showing that CO2 concentration is increasing faster than exponentially.
Didactylos
Thank you for reading my post so carefully. I am honoured.
Let me make my simplistic point again. Based upon the published data from the Hawaii CO2 Observatory it is clear that R^2 comparison shows that CO2 is better described by Exponential analysis I provided aboven than by a linear regression.
NOAA is predicting (or forecasting, or modeling) a fairly dramatic cooling fairly soon:
http://www.cpc.noaa.gov/products/people/wwang/cfs_fcst/images2/glbT850Sea.gif
(today, that image is dated August 16. I do not know how often they update it or how easy it will be to search archives later.)
386 Mike Roddy: Secular Animist, I agree. Quality blogs such as this one should be addressing catastrophe scenarios, whether we pause for a little fun with His Lordship or not. When a new study about methane comes out, the instinct at RC is a bit too much on the cautious side, even if the relevant data (Shakova, Walter) is solid.
For public relations purposes, I’d propose that you hold off on the heat-related disaster warnings until after we find out whether the prediction is accurate, and if it is accurate then wait for high temps to rebound, as they surely will.
Orkneygal: see, you didn’t qualify it that time. That was my only complaint. Thank you.
Orkneygal, hi again,
As I said earlier:
You see, this equation:
CO2 = 275 + 2^((year-1780)/33.41)
takes the pre-industrial (baseline) CO2 concentration of ~275 ppm and *adds* the anthropogenic (contributed by mankind) component to it. The 33.41 in the equation is the number of years it takes for us to double the anthropogenic component (so far it does, anyway. But this rate may be increasing as well).
I believe that expressing it this way is more accurate than trying to curve fit the total ppm. Because, as Marcos points out, it’s not obvious what sort of polynomial you are trying to fit.
In fairness to people who took me to task, I should point this out:
http://m.wired.com/wiredscience/2010/08/antarctic-ice-future/
Global warming increases Antarctic sea ice. One of the authors is Judith Curry
Orkneygal— Please consider
http://tamino.wordpress.com/2010/08/09/mo-better-monckey-business/
regarding CO2 concentration rate studies.
Septic Matthew wrote: “Global warming increases Antarctic sea ice.”
Right.
From the link you posted:
The Wired magazine article notes that Fox News described the study thusly: “Ice is expanding in much of Antarctica, contrary to the widespread public belief that global warming is melting the continental ice cap.”
Right.
#399–Ah, yes, Fox–always “objective.”
(If by “objective” one means “devoted to their object.”)