Guest Post by Willis Eschenbach
I’ve argued in a variety of posts that the usual canonical estimate of climate sensitivity, which is 3°C of warming for a doubling of CO2, is an order of magnitude too large. Today, at the urging of Steven Mosher in a thread on Lucia Liljegren’s excellent blog “The Blackboard”, I’ve taken a deeper look at the Berkeley Earth Surface Temperature (BEST) volcano forcings. It’s a curious tale, with an even more curious outcome. Here’s the graph in question:
Figure 1. BEST comparison of hindcast temperature changes due to CO2 plus volcanoes (heavy black line) with the BEST temperature data (light black lines). SOURCE
I asked Steven Mosher where the BEST folks got the data on the temperature change expected from volcanic forcing as shown in the heavy black line above … no reply. Setting that question aside, I decided to just use the data I had. So … I did what I usually do. I digitized their figure, since their underlying data wasn’t readily available. That allowed me to analyze their data, which revealed a very odd thing.
Their explanation of the black line in Figure 1 above (their Figure 5) is as follows:
A linear combination of volcanic sulfates and CO2 changes were fit to the land-surface temperature history to produce Figure 5. As we will describe in a moment, the addition of a solar activity proxy did not significantly improve the fit. The large negative excursions are associated with volcanic sulfate emissions, with the four largest eruptions having all occurred pre-1850; thus our extension to the pre-1850 data proved useful for the observation of these events. To perform the fit, we adjusted the sulfate record by applying an exponential decay with a two year half-life following emission. The choice of two-years was motivated by maximizing the fit, and is considerably longer than the 4-8 month half-life observed for sulfate total mass in the atmosphere (but plausible for reflectivity which depends on area not volume).
OK, that makes me nervous … they have used a linear regression fit to the temperature record of the lagged exponential decay, with a separately fitted time constant, of an estimate of volcanic sulfate emissions based on ice cores … OK, I’ll buy that, but at a discount. They are using the emissions from here, but although I can get close to the figure above, I cannot replicate it exactly.
I wanted to extract the volcanic data. My plan of attack was as follows. First, I would digitize the heavy black line from Figure 1 above. Then I’d match it up with the logarithm of the CO increase since 1750. Once I subtracted out the CO2 increase, the remainder would be the hindcast change in temperature resulting from the volcanic eruptions alone.
Figure 2 shows the first part of the calculation, the digitized black line from Figure 1 (CO2 + volcanoes) with the log CO2 overlaid on it in red.
Figure 2. The black line is the digitized black line from Figure 1. The red line is three times the log (base 2) of the change in CO2 plus an offset. CO2 data is from Law Dome ice cores 1750-1950, and from Mauna Loa thereafter.
I fit the CO2 curve to the data by hand and by eye, by manually adjusting the slope and the intercept of the regression, because standard regression methods don’t fit it to the top of the black line. A couple of things indicated to me that I was on the right track. First is the good fit of the log of the CO2 data to the BEST data. The second is that it turned out that the best fit is when using the standard climate sensitivity of 3°C for a doubling of CO2. Encouraged, I pressed on.
Subtracting the volcanic data from the CO2 data gives us the temperature change expected from volcanoes, as shown in Figure 3.
Figure 3. Volcanic temperature changes (cooling after eruptions) as hindcast by BEST (black line), and as fit from the lagged emissions as described in their citation above (red line).
Note that as I mentioned above, I can get close to the temperature changes they hindcast (black line) using a lagged version of their sulfate data as they described (red line), but the match is not exact. Since the black line is what they show in Figure 1 above, and the differences are minor, I’ll continue to use the heavy black line.
Now, let’s pause here for a moment and consider what they have done, and what they have not done. What they have done is converted changes in atmospheric CO2 forcing in watts per square metre (W/m2) to a hindcast temperature change (in degrees C). They did this conversion by using the standard climate sensitivity of 3°C of warming for each doubling of CO2 (doubling gives an additional 3.7 W/m2).
They have also converted stratospheric injections of volcanic sulfates (in Teragrams) to a hindcast temperature change (in degrees C). They have done this by brute force, using a lagged model of the results of the stratospheric sulfate injections which is fit to the temperature.
But what they haven’t done, as far as I could find, is to calculate the forcing due to the volcanic eruptions (in W/m2). They just fitted the sulfate data directly to the temperature data and skipped the intermediate step. Without knowing the forcing due to the eruptions, I couldn’t estimate what climate sensitivity they had used to calculate the temperature response to the volcanic eruptions.
However, there’s more than one way to skin a cat. The NASA GISS folks have an estimate of the volcanic forcing (in W/m2, column headed “StratAer” for stratospheric aerosols from volcanoes). So to investigate BEST’s climate sensitivity, I used the GISS volcanic forcings. They only cover the period 1880—2000, but I could still use them to estimate the climate sensitivity that BEST had used for the volcanic forcings. And that’s where I found the curious part. Figure 4 shows the volcanic forcing in W/m2 from NASA GISS, along with the BEST hindcast temperature response from that forcing.
Figure 4. Black line shows the BEST hindcast temperature anomaly (cooling) from the eruptions. Red line is the change in forcing, in watts per square metre (W/m2), from the eruptions. Green line shows the best fit theoretical cooling resulting from the GISS forcing. Note the different time period from the preceding figures.
As you can see, the regression (green line) of the GISS forcing gives a reasonable approximation of the BEST temperature anomaly, so again we’re on the right track. The curious part is the relative sizes. The change in temperature is just under a tenth of the change in forcing (0.08°C per W/m2).
This equates to a climate sensitivity of about 0.3°C per doubling of CO2 (0.08°C/W/m2 times 3.7 W/m2/doubling = 0.3°C/doubling)… which is a tenth of the canonical figure of three degrees per doubling of CO2.
So in their graph, in the heavy black line they have combined a climate sensitivity of 3°C per doubling for the CO2 portion, with a climate sensitivity of only 0.3°C per doubling for the volcanic portion …
Now this is indeed an odd result. There are several possible ways to explain this finding of a climate sensitivity of 0.3°C per doubling. Here are the possibilities
1. The NASA GISS folks have overestimated the forcing due to volcanoes by a factor of ten, a full order of magnitude. Possible, but very doubtful. The reduction in clear-sky sunlight following volcanic eruptions has been studied at length. We have a pretty good idea of the loss in incoming energy. We might be wrong by a factor of two, but not by a factor of ten.
2. The BEST temperature data underestimates the variation in temperature following volcanic eruptions by a full order of magnitude. Even more doubtful. The BEST temperature data is not perfect, but it is arguably the best we got.
3. The BEST data and the NASA data are both wrong, but providentially they are each wrong in the right direction to cancel each other out and give a sensitivity of three degrees per doubling. Odds are thin on that happening by chance, plus the reasons above still apply.
4. Both the NASA and BEST data are roughly correct, and the climate sensitivity actually is on the order of a tenth of what is claimed.
Me, I go for door number four, small climate sensitivity. I say the climate is buffered by a variety of homeostatic mechanisms that tend to minimize the temperature effects of changes in the forcing, as I have discussed at length in a variety of posts.
However, as always, alternative hypotheses are welcome.
Regards to everyone,
w.
DATA: I did this on an excel spreadsheet, which is here. While it is not user-friendly, I don’t think it is actively user-aggressive … the BEST temperature data on that spreadsheet is from here. Note that curiously, the BEST folks have not removed all of the annual cycle from their temperature data, there remains about a full degree of annual swing … go figure.
[UPDATE] Richard Telford in the comments points out that what I have calculated is the instantaneous sensitivity, and he is correct.
However, as I showed in “Time Lags in the Climate System“, in a system that is driven cyclically and that picks up and loses heat via exponential gain and decay, the instantaneous sensitivity is related to the longer-term sensitivity by the relationship
where t1 is the lag, t is the length of the cycle, and s2/s1 is the size of the reduction in amplitude. Since in this case we are dealing with the BEST land-only temperatures, where the lag is short (less than a month on average) that means that the short-term sensitivity is about 64% of the longer-term sensitivity. This would make the longer-term sensitivity about 0.46°C per doubling of CO2. This is still far, far below the usual estimate of 3°C per doubling.
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Not concluded reading the post yet Willis but looking forward to it as i do with many of your posts. The early thing that struck me was Mosher not forthcoming with information? That seems odd given his proclivity for hounding others for data.
( as usual my full name available privately if required by anyone, I prefer a nickname, it’s been with me a looong time.)
“This equates to a climate sensitivity of about 0.3°C per doubling of CO2 (0.8°C/W/m2 times 3.7 W/m2/doubling = 0.3°C/doubling)… which is a tenth of the canonical figure of three degrees per doubling of CO2.”
Isn’t 0.8 x 3.7 almost exactly 3.0, rather than 0.3?
[My bad, should be 0.08, fixed. -w.]
Excellent post Willis. Makes more sense compared to the faffling Mosh and Co have done.
Letenus me throw another wrinkle, the cleaning of the atmosphere. Eruption introduces the dust, cosmic rays, or whatever create a moisture path, which moves with the wind, collecting the upper atmosphere dust, precipitating to the ground, reinforcing the hydraulic cycle, which is why a cold planet like mars, a hot planet like venus do not have many clouds like ours or too many clouds traping the heat into a runaway situation.
AFAIK climate sensitivity studies using observational evidence, not relying on climate models or paleoclimatic reconstructions, all show climate sensitivity to be low i.e. below 1C – 1.5C per doubling. All studies using climate models and paleoclimatic reconstructions show high climate sensitivity.
And isn’t climate sensitivity what this whole argument boils (oops) down to?
Makes me wonder why the IPCC prefer models and paleoclimatic reconstructions.
Willis you write “I’ve argued in a variety of posts that the usual canonical estimate of climate sensitivity, which is 3°C of warming for a doubling of CO2, is an order of magnitude too large.”
Could I suggest this ought to read “I’ve argued in a variety of posts that the usual canonical estimate of climate sensitivity, which is 3°C of warming for a doubling of CO2, is AT LEAST an order of magnitude too large.`
My capitals.
common sense – (technobabbel/1) = common sense
The conclusions as to forcings depends on belief in the GHG theory which is questionable at the best of times. Temperature accuracy is also questionable and not the best metric of climate because water content of the atmosphere at the point of measurement is ignored but vital is calculating heat available which is the real driver of weather/climate. But heat content has no relationship to atmospheric CO2 content but to solar insolation at the time.
Volcanic eruptions are more a proxy than a cause of any significant climatic changes beyond a year or two.
http://www.vukcevic.talktalk.net/Ap-VI.htm
Ignore or take a note makes no difference to the climate, but it might help to the understanding.
Possibility 5. Eschenbach’s methods are unfit for purpose (not for the first time).
Volcanic forcings are of short duration so the climate system, especially the oceans, does not reach equilibrium. Therefore, dividing the temperature change by the forcing is guaranteed to underestimate sensitivity.
Willis,
Firstly, I think you mean ‘0.08’ rather than ‘0.8°C per W/m2’.
Secondly, you’re missing the different timescales involved in CO2 versus volcanic forcing. Volcanic forcing is near-instantaneous, and is followed up a couple of years later with a quick forcing increase as aerosols are scrubbed. Conversely, CO2 has been accumulating gradually, with a persistent forcing in the same direction over the ~200 year period.
The best comparison to use for applying some form of check on your hypothesis are model outputs from 2xCO2 instantaneous forcing scenarios. There’s one in Climate Explorer for the GISS-EH model. I’ve produced output files for the land and land+ocean data (I don’t know how long these files stay on their servers, but you can output new ones yourself). If you look at these files, 10 years after a ~4W/m^2 forcing there is about 0.5ºC temperature increase (land, ~0.25ºC land+ocean) despite the fact that its ECS is 2.7ºC.
Willis-
There is a typo here- “The change in temperature is just under a tenth of the change in forcing (0.8°C per W/m2).”
Should be 0.08 C per W/m^2, no?
The same typo also appears here- “This equates to a climate sensitivity of about 0.3°C per doubling of CO2 (0.8°C/W/m2 times 3.7 W/m2/doubling = 0.3°C/doubling)…”
Should be 0.08C/W/m2.
Also, the GISS forcing of just under 3 W/m^2 at peak for Pinatubo is anomalously small when compared with the measured change in optical opacity of the atmosphere which peaked at 0.15 in the visible, giving a negative forcing of about 35 W/m^2 at peak, or ten times larger than what GISS climate models expectorate.
Last time I checked, 0.8×3.7 was 2.96.
Two little questions for you. First, how long do volcanic aerosols persist in the atmosphere, typically? And second, how long, all else being equal, would the atmosphere take to reach an equilibrium response to the aerosol forcing?
Oh, and one more if you would – roughly how many scientific papers which make estimates of the climate sensitivity have you read?
Willis: In your past posts about volcanoes, have you looked at the response of Land+Sea Surface Temperature data, like GISS LOTI, to the Mount Pinatubo eruption? If so, what was the maximum initial temperature drop that you found for it?
hmmm, don’t worry Willis, Mosher will be along real soon with a cryptic clue as to where you went wrong. I am sure his cryptic clues will be enough to satisfy everyone that BEST are doing their best.
Personally I think you are doing better than BEST.
Well, you can hit someone with the same strength, but depending where, how and with what you hit him, the pain can be quite different….
This simplistic comparison between the temperature response to a doubling of co2 or a volcanic eruption just doesn’t make a lot of sense.
The “canonical” estimate does not come from the Vatican, sole source of authorized canon, after lengthy conciles!
Let’s see how your finding correlates with model calculation.
So far models go like this:
– for any doubling of CO2 the forcing will be ΔF = 5.35 · ln(C/Co) = 5.35 · ln(2) = 3.7 W m-2. This is a physical spectrometric finding, not related to climate. Not too much to be discussed here.
– responding to such a forcing, and looking for a equilibrated energy balance, the primary temperature increase shoud be approx. 0.8°C. Other global models may offer little differences (before any feedback consideration). Regional variations may be larger in some places (e.g. Northern hemisphere) and smaller somewhere else.
– taking into account an overall negative feedback of -1.3 W m-2 K-1 from all known mechanisms (Planck, water vapour, lapse rate, albedo, and clouds. See: http://journals.ametsoc.org/doi/pdf/10.1175/JCLI3819.1) this temperature response is reduced by half to approx. 0.6°C.
Neo-Vatican: IPCC’s basic feedback assumption is that an overall negative feedback of -1.3 W m-2 K-1 will provoke a positive temperature increase of 3.7/1.3 = 2.85 °C. This is dimensionally OK, but an absolute physical non-sense: negative feedback provoking positive reinforcment, infinitely small feedback with infinitely high system response. This was never discussed nor criticized in any paper, but blessed by the IPCC report committee, presided by authors of this non-sense.
This means that any temperature increase that would surpass 0.6°C would probably be due to other [non anthropogenic] factors than doubling CO2 atmospheric concentration by human made emissions.
And please note that we are far from doubling: we are at approx. 395 ppm as compared to historical pre-industrial 280 ppm (if we accept this baseline), just a 41% increase. So we speak here of approx. 0.4°C temperature increase attributable to CO2 emissions since two centuries.
Willis: your findings, taken out of temperature records statistics, is 0.3°C for any doubling. This would mean that homeostatic mechanisms are stronger than assumed in the underlying feedback paper wher a wide uncertainty range is also given.
Anyway, it’s difficult to establish a therory based on experimental work since we have only one Earth and one experiment. Let’s remain in conjectures.
John Marshall says:
August 13, 2012 at 6:53 am
The conclusions as to forcings depends on belief in the GHG theory which is questionable at the best of times.
How much heat could atmospheric CO2 possibly impart on the oceans compared to other factors: For instance a hundred year increase in solar activity compared to total atmosphere density and composition changes?
What about local CO2 concentrations? In a closed system, where CO2 is suggested to have such a dynamic effect on temperature, then a greenhouse with 1200 ppm parked next to a greenhouse with 120 ppm should demonstrated a very significant temperature difference.
Willis, always enjoy your enlightening and easily followed posts. Anyone who has been trained in or exposed to process control theory knows that a system dominated by positive feedbacks will saturate at one extreme or the other until affected by a dominant outside forcing! Earth has experienced at least two periods or near total glacial encapsulazation – 600 m & 2.4 b years ago. However, there is no indication that the Earth has even been more than 7C warmer than today. The obvious conclusion is that Earth’s climate is dominated by negative feedback that are periodically and also sporadically overridden by external forcings. Melankovich cycles are an obvious such external forcing. Sun spot cycles plus Dalton, Maunder et al minima are more frequent perturbations to Earth’s climate. Contiental drift and location near the equator is another long cycle forcing.
CO2 concentrations are estimated to have reached 7,000 ppm (4 doublings from today’s 400 ppm) but we have no evidence of runaway warming. CO2 and GHG’s may have a small impact, but trivial at best. I, therefore, agree with your estimate of 0.3C/doubling at MOST!
I’m very disappointed that process control engineers and professors around the world have not raised their voices in protest of this absurd AGW movement!
Bill
The likely reason why the apparent sensitivity for the long term change is large is because it’s land temps, rather than global surface temps. The change is very likely larger.
BTW Willis, surely .8/W/m^2 should be .08, other wise the change is almost exactly 3 C per doubling-which is again, even if correct, not the right answer due to completely excluding the ocean. There is a lot that’s wrong with the BEST “attribution”-the linear regression approach completely ignores physics and gives inconsistent answers.
Echo chamber criticisms and affirmations aside, thanks for doing this. Paul S’s comment above is cogent – and I suspect if you followed it through, you’d get a number for sensitivity >0.3. However, I’ll guess it will also be a lot less than 3.0. Take odds?
“The choice of two-years was motivated by maximizing the fit, and is considerably longer than the 4-8 month half-life observed for sulfate total mass in the atmosphere”
This is all about forcing the data to fit the theory – the exact OPPOSITE of science, but the also the EXACT rationalization of theology.
In other words, “We know what we know and we will not be confused by the facts.”
Degree of “forcing” is indeed a critical factor in any self-dealing Warmist model. Alas, facts to hyper-politicized propagandists are immaterial. What might yet resolve this issue to mutually impartial, objective, rational satisfaction? Given the wholly qualitative nature of Warmists’ meretricious reliance on non-empirical data, we fear the answer is: Nothing.
“Me, I go for door number four, small climate sensitivity. I say the climate is buffered by a variety of homeostatic mechanisms that tend to minimize the temperature effects of changes in the forcing, as I have discussed at length in a variety of posts.”
Could you also present us the links of the “variety of posts” so we can verify them ourselves please?
richard telford says:
August 13, 2012 at 6:57 am
Gosh, telford, do you work at being snide, or is it just your natural state of being?
Number 5 is always a possibility … but in this case you haven’t thought the question all the way through. As I showed in “Time Lags in the Climate System“, in a system that is driven cyclically, the instantaneous sensitivity is related to the longer-term sensitivity by the relationship
where t1 is the lag, t is the length of the cycle, and s2/s1 is the size of the reduction in amplitude. Since in this case we are dealing with the BEST land-only temperatures, where the lag is short (less than a month on average) that means that the short-term sensitivity is about 64% of the final sensitivity. This would make the final sensitivity about 0.46°C per doubling of CO2.
w.