Guest Post by Willis Eschenbach
In the leaked version of the upcoming United Nations Intergovernmental Panel on Climate Change (UN IPCC) Fifth Assessment Report (AR5) Chapter 1, we find the following claims regarding volcanoes.
The forcing from stratospheric volcanic aerosols can have a large impact on the climate for some years after volcanic eruptions. Several small eruptions have caused an RF for the years 2008−2011 of −0.10 [–0.13 to –0.07] W m–2, approximately double the 1999−2002 volcanic aerosol RF.
and
The observed reduction in warming trend over the period 1998–2012 as compared to the period 1951–2012, is due in roughly equal measure to a cooling contribution from internal variability and a reduced 2 trend in radiative forcing (medium confidence). The reduced trend in radiative forcing is primarily due 3 to volcanic eruptions and the downward phase of the current solar cycle.
Now, before I discuss these claims about volcanoes, let me remind folks that regarding the climate, I’m neither a skeptic nor am I a warmist.
I am a climate heretic. I say that the current climate paradigm, that forcing determines temperature, is incorrect. I hold that changes in forcing only marginally and briefly affect the temperature. Instead, I say that a host of emergent thermostatic phenomena act
quickly to cool the planet when it is too warm, and to warm it when it is too cool.
One of the corollaries of this position is that the effects of volcanic eruptions on global climate will be very, very small. Although I’ve demonstrated this before, Anthony recently pointed me to an updated volcanic forcing database, by Sato et al. Figure 1 shows the amount of forcing from the historical volcanoes.
Figure 1. Monthly changes in radiative forcing (downwelling radiation) resulting from historical volcanic eruptions. The two large recent spikes are from El Chichon (1983) and Pinatubo (1992) eruptions. You can see the average forcing of -0.1 W/m2 from 2008-2011 mentioned by the IPCC above. These are the equilibrium forcings Fe, and not the instantaneous forcing Fi.
Note that the forcings are negative, because the eruptions inject reflective aerosols into the stratosphere. These aerosols reflect the sunlight, and the forcing is reduced. So the question is … do these fairly large known volcanic forcings actually have any effect on the global surface air temperature, and if so how much?
To answer the question, we can use linear regression to calculate the actual effect of the changes in forcing on the temperature. Figure 2 shows the HadCRUT4 monthly global surface average air temperature.
Figure 2. Monthly surface air temperatures anomalies, from the HadCRUT4 dataset. The purple line shows a centered Gaussian average with a full width at half maximum (FWHM) of 8 years.
One problem with doing this particular linear regression is that the volcanic forcing is approximately trendless, while the temperature has risen overall. We are interested in the short-term (within four years or so) changes in temperature due to the volcanoes. So what we can do to get rid of the long-term trend is to only consider the temperature variations around the average for that historical time. To do that, we subtract the Gaussian average from the actual data, leaving what are called the “residuals”:
Figure 3. Residual anomalies, after subtracting out the centered 8-year FWHM gaussian average.
As you can see, these residuals still contain all of the short-term variations, including whatever the volcanoes might or might not have done to the temperature. And as you can also see, there is little sign of the claimed cooling from the eruptions. There is certainly no obvious sign of even the largest eruptions. To verify that, here is the same temperature data overlaid on the volcanic forcing. Note the different scales on the two sides.
Figure 4. Volcanic forcing (red), with the HadCRUT4 temperature residual overlaid.
While some volcanoes line up with temperature changes, some show increases after the eruptions. In addition, the largest eruptions don’t seem correlated with proportionately large drops in temperatures.
So now we can start looking at how much the volcanic forcing is actually affecting the temperature. The raw linear regression yields the following results.
R^2 = 0.01 (a measure from zero to one of how much effect the volcanoes have on temperature) "p" value of R^2 = 0.03 (a measure from zero to one how likely it is that the results occurred by chance) (adjusted for autocorrelation). Trend = 0.04°C per W/m2, OR 0.13°C per doubling of CO2 (how much the temperature varies with the volcanic forcing) "p" value of the TREND = 0.02 (a measure from zero to one how likely it is that the results occurred by chance) (adjusted for autocorrelation).
So … what does that mean? Well, it’s a most interesting and unusual result. It strongly confirms a very tiny effect. I don’t encounter that very often in climate science. It simultaneously says that yes, volcanoes do affect the temperature … and yet, the effect is vanishingly small—only about a tenth of a degree per doubling of CO2.
Can we improve on that result? Yes, although not a whole lot. As our estimate improves, we’d expect a better R^2 and a larger trend. To do this, we note that we wouldn’t expect to find an instantaneous effect from the eruptions. It takes time for the land and ocean to heat and cool. So we’d expect a lagged effect. To investigate that, we can calculate the R^2 for a variety of time lags. I usually include negative lags as well to make sure I’m looking at a real phenomenon. Here’s the result:
Figure 5. Analysis of the effects of lagging the results of the volcanic forcing.
That’s a lovely result, sharply peaked. It shows that as expected, after a volcano, it takes about seven-eight months for the maximum effects to be felt.
Including the lag, of course, gives us new results for the linear regress, viz:
R^2 = 0.03 [previously 0.01] "p" value of R^2 = 0.02 (adjusted for autocorrelation) [previously 0.03] Trend = 0.05°C per W/m2, OR 0.18 ± 0.02°C per doubling of CO2 [previously 0.13°C/doubling] "p" value of the Trend = 0.001 (adjusted for autocorrelation). [previously 0.02]
As expected, both the R^2 and the trend have increased. In addition the p-values have improved, particularly for the trend. At the end of the day, what we have is a calculated climate sensitivity (change in temperature with forcing) which is only about two-tenths of a degree per doubling of CO2.
Here are the conclusions that I can draw from this analysis.
1) The effect of volcanic eruptions is far smaller than generally assumed. Even the largest volcanoes make only a small difference in the temperature. This agrees with my eight previous analyses (see list in the Notes). For those who have questions about this current analysis, let me suggest that you read through all of my previous analyses, as this is far from my only evidence that volcanoes have very little effect on temperature.
2) As Figure 5 shows, the delay in the effects of the temperature is on the order of seven or eight months from the eruption. This is verified by a complete lagged analysis (see the Notes below). That analysis also gives the same value for the climate sensitivity, about two tenths of a degree per doubling.
3) However, this is not the whole story. The reason that the temperature change after an eruption is so small is that the effect is quickly neutralized by the homeostatic nature of the climate.
Finally, to return to the question of the IPCC Fifth Assessment Report, it says:
There is very high confidence that models reproduce the more rapid warming in the second half of the 20th century, and the cooling immediately following large volcanic eruptions.
Since there is almost no cooling that follows large volcanic eruptions … whatever the models are doing, they’re doing it wrong. You can clearly see the volcanic eruptions in the model results … but you can’t see them at all in the actual data.
The amazing thing to me is that this urban legend about volcanoes having some big effect on the global average temperature is so hard to kill. I’ve analyzed it from a host of directions, and I can’t find any substance there at all … but it is widely believed.
I ascribe this to an oddity of the climate control system … it’s invisible. For example, I’ve shown that the time of onset of tropical clouds has a huge effect on incoming solar radiation, with a change of about ten minutes in onset time being enough to counteract a doubling of CO2. But no one would ever notice such a small change.
So we can see the cooling effect of the volcanoes where it is occurring … but what we can’t see is the response of the rest of the climate system to that cooling. And so, the myth of the volcanic fingerprints stays alive, despite lots of evidence that while they have large local effects, their global effect is trivially small.
Best to all,
w.
PS—The IPCC claims that the explanation for the “pause” in warming is half due to “natural variations”, a quarter is solar, and a quarter is from volcanoes. Here’s the truly bizarre part. In the last couple decades, using round numbers, the IPCC predicted about 0.4°C of warming … which hasn’t happened. So if a quarter of that (0.1°C) is volcanoes, and the recent volcanic forcing is (by their own numbers) about 0.1 W/m2, they’re saying that the climate sensitivity is 3.7° per doubling of CO2.
Of course, if that were the case we’d have seen a drop of about 3°C from Pinatubo … and I fear that I don’t see that in the records.
They just throw out these claims … but they don’t run the numbers, and they don’t think them through to the end.
Notes and Data
For the value of the forcing, I have not used the instantaneous value of the volcanic forcing, which is called “Fi“. Instead, I’ve used the effective forcing “Fe“, which is the value of the forcing after the system has completely adjusted to the changes. As you might expect, Fi is larger than Fe. See the spreadsheet containing the data for the details.
As a result, what I have calculated here is NOT the transient climate response (TCR). It is the equilibrium climate sensitivity (ECS).
For confirmation, the same result is obtained by first using the instantaneous forcing Fi to calculate the TCR, and then using the TCR to calculate the ECS.
Further confirmation comes from doing a full interative lagged analysis (not shown), using the formula for a lagged linear relationship, viz:
T2 = T1 + lambda (F2 – F1) (1 – exp(-1/tau)) + exp(-1/tau) (T1 – T0)
where T is temperature, F is forcing, lambda is the proportionality coefficient, and tau is the time constant.
That analysis gives the same result for the trend, 0.18°C/doubling of CO2. The time constant tau was also quite similar, with the best fit at 6.4 months lag between forcing and response.
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In this case it’s the Sato paper, which provides a dataset of optical thicknesses “tau”, and says:
The relation between the optical thickness and the forcings are roughly (See “Efficacy …” below):
instantaneous forcing Fi (W/m2) = -27 τ
adjusted forcing Fa (W/m2) = -25 τ
SST-fixed forcing Fs (W/m2) = -26 τ
effective forcing Fe (W/m2) = -23 τ
And “Efficacy” refers to
Hansen, J., M. Sato, R. Ruedy, L. Nazarenko, A. Lacis, G.A. Schmidt, G. Russell, et al. 2005. Efficacy of climate forcings. J. Geophys. Res., 110, D18104, doi:10.1029/2005/JD005776.
Forcing Data
For details on the volcanic forcings used, see the Sato paper, which provides a dataset of optical thicknesses “tau”, and says:
The relation between the optical thickness and the forcings are roughly (See “Efficacy …” below):
instantaneous forcing Fi (W/m2) = -27 τ
adjusted forcing Fa (W/m2) = -25 τ
SST-fixed forcing Fs (W/m2) = -26 τ
effective forcing Fe (W/m2) = -23 τ
And “Efficacy” refers to
Hansen, J., M. Sato, R. Ruedy, L. Nazarenko, A. Lacis, G.A. Schmidt, G. Russell, et al. 2005. Efficacy of climate forcings. J. Geophys. Res., 110, D18104, doi:10.1029/2005/JD005776.
(Again, remember I’m using their methods, but I’m not claiming that their methods are correct.)
Future Analyses
My next scheme is that I want to gin up some kind of prototype governing system that mimics what it seems the climate system is doing. The issue is that to keep a lagged system on course, you need to have “overshoot”. This means that when the temperature goes below average, it then goes above average, and then finally returns to the prior value. Will I ever do the analysis? Depends on whether something shinier shows up before I get to it … I would love to have about a dozen bright enthusiastic graduate students to hand out this kind of analysis to.
I also want to repeat my analysis using “stacking” of the volcanoes, but using this new data, along with some mathematical method to choose the starting points for the stacking … which turns out to be a bit more difficult than I expected.
Previous posts on the effects of the volcano.
Prediction is hard, especially of the future.
Pinatubo and the Albedo Thermostat
Dronning Maud Meets the Little Ice Age
New Data, Old Claims about Volcanoes
Willis: “Thanks, Michael, but actually I’m not talking about feedback. Instead, I’m talking about a governed system, which is a very different critter. See my post called “It’s Not About Feedback” for a discussion of the difference.”
“Regarding Thomas’s questions, the earth appears to be “bi-stable”, that is it has two different states, and it can shift from one to the other.”
Willis, you need to make your peace with the word feedback. The bi-stable system you refer to implies a positive feedback bounded by -ve f/b. Your governor , like any governor, requires a negative feedback to work (as I pointed out in your original thread in relation to steam engine governors, which appear to be your conceptual base.).
If you equate the word “feedback” with “linear negative feedback” only , of course it’s inadequate but if you refuse to recognise the whole concept of feedbacks, +/ve and -/ve, linear and non-linear, in describing the tropical storm “governor” and turn you back on the rest of science and engineering , I fear you will not get much traction for your hypothesis.
As you know I am quite supportive of your basic idea.
I again suggest you repeat this analysis on tropics and extra-fropical regions.
If you extend the lag range I’m fairly sure that in the tropics you will find a similar negative correlation following the initial peak (which will itself be weaker).
You will also find a stronger , more correlated signal in extra tropics (especially NH).
That again will substantiate your hypothesis that it is the tropics that are stabilising global climate with respect to changes in radiative forcing.
Best regards, Greg.
Youkillmeandyoudomegood: says “The Kiehl-Trenberth budget “396″ (W/m2) surface radiation value ”
What does that “value” represent? Surface upward IR would presumably include 0.7*S-B black body emission, 0.3*reflected solar, reflected atmospheric backscatter/re-emission.
Not the same as “blind theoretical calculation using Stefan-Boltzman law.”
Willis Eschenbach says: September 24, 2013 at 1:11 am
I’m sure you can see the problem. Yes, there was a drop after Pinatubo … but it was only about 0.2°C, not the 0.6°C that is often claimed. That was the amount the models predicted for the drop.
_______________________________________
This is what I like about Willis – he goes back to the data, not the models. And even the layman can see what he is saying in that graphical data. I took an eyeball-squint of the lagged temperature-drop, and came out with 0.2 oc for Pinatubo and 0.15 oc for El Chichon, with a lag of one year. How does climate ‘science’ think it is anything different?
And I like the way Willis will defend his ideas and assertions. There are so many so-called scientists (not just in climate ‘science’) who will make an assertion and then retire to a bunker – and actively prevent discussion by deleting adverse comments and banning dissenters. That, is not science. THIS, is science.
.
Willis, thanks for the extra details on Fe et al
Here is an interesting quote from Douglass & Knox 2006, linked above :
The sensitivity appears to be at variance with
0.46 °C/(W/m2 ), corresponding to a T2x of 1.7 °C
associated with a CO 2 doubling, expected by Wigley
et al. [2005b]. There is no discrepancy if one acknowl-
edges that the sensitivity for CO2 doubling is not
necessarily the same as that for aerosol forcing. The
reason for the difference in this case is that the models
applied to CO2 doubling are designed for an approach
to a long-term steady state (called ‘‘equilibrium’’) and
that the assumed processes involved include positive
delayed feedback. The CO2-doubling sensitivity is in-
appropriate for the volcano forcing, which activates
only rapidly occurring feedbacks.
Willis: “None of these methods are dimensionally correct, because they all use a units fudge factor. Remember we are transforming forcing (W/m2) into temperature (°C), which are incommensurate.”
Well they require the heat capacity of a mass to do the transformation which is why IRRC Frank was claiming the need to assess the interaction with the ocean mixed layer. The short cut you do here to go straight for the resultant temperature as seen in the surface data. I assume the ‘fudge factor” is sensitivity. It not not dimensional fudge but does assume a linear response, which is of questionable accuracy. The fudge is in choosing to do a linear regression not the units.
That does not get around the need to integrate or differentiate as appropriate. With or without the fudge you can not regress power against energy. I think that point is unavoidable. This plays back into Paul_K’s point about the frequency dependency. This is saying the same thing.
Ignore last para for now, needs more explanation. out of time for now.
Hi again Willis,
“I’m sure you can see the problem. Yes, there was a drop after Pinatubo … but it was only about 0.2°C, not the 0.6°C that is often claimed. That was the amount the models predicted for the drop.”
I agree that it is remarkably difficult to pull out a volcano signal because the high frequency variance in the temperature datasets from ENSO, solar, cloud fluctuations and other effects (including measurement and methodological errors) leaves a low S/N ratio. That said, I think you are lowballing the estimate somewhat. The (MONTHLY) Hadcrut3 dataset shows a 0.38 deg C change in temperature from June 1991 to 3Q 1992 when the Pinatubo volcanic cooling was approaching its low point. This is before any correction for known ENSO and solar effects. The satellite data (UAH or RSS TLT data) shows a substantially larger temperature change – 0.5 to 0.6 deg C still without correction for ENSO and solar. See here for example:- http://wattsupwiththat.com/reference-pages/global-weather-climate/global-temperature/
Corrections for ENSO and solar tend to increase the magnitude of the temperature change by order 0.1 deg C.
Studies by sceptical scientists (Douglass and Knox 2005, Roy Spencer blog comments) and mainstream scientists (Soden et al 2002, Wigley 2005) alike have accepted a Pinatubo-induced TLT temperature change of around 0.6 deg C after correction for known ENSO and solar. This does not make it right, of course, but it should make you pause for thought given the very low temperature response that your work is implying here.
In addition to the information that you use here, for Pinatubo, we also have satellite-derived measurements of changes in TOA radiation. The integral of the change in net flux gives us some idea of the total energy loss from the system after Pinatubo. This is substantially larger than can be explained using your fitted parameters for lambda and tau. Shameful personal plug – see here
http://rankexploits.com/musings/2012/pinatubo-climate-sensitivity-and-two-dogs-that-didnt-bark-in-the-night/ for my calculations, with an update here:-
http://rankexploits.com/musings/2012/pinatubo-climate-sensitivity-revisited/
I always enjoy Willis Eschenbach’s posts, but I do feel wary about his ‘heretical’ belief in some kind of natural ‘thermostat’ in the Earth’s climate system. A thermostat requires negative feedback in both directions around some central level, and some kind of damping mechanism to ensure that the system does not oscillate wildly. It is obvious that the Earth’s climate system has both negative and positive feedback components, but there is no a priori reason to think that negative feedback will prevail, or that feedback will be ‘damped’ to give the required stability. (Lovelock’s Gaia hypothesis would give us such a reason, but I don’t recall that Willis has ever endorsed Gaia, and I really hope he is not resting on such a shaky foundation.) In the absence of any a priori reason (i.e. some well-established scientific principle, such as the laws of thermodynamics), it all comes down to evidence. And I really don’t see much evidence that global mean temperature is thermostatically controlled. If it is, how come we get the major long-term changes, such as the MWP and the LIA, which presumably most of us here believe in?
David B said:
“And I really don’t see much evidence that global mean temperature is thermostatically controlled. If it is, how come we get the major long-term changes, such as the MWP and the LIA, which presumably most of us here believe in?”
Solar induced changes in cloudiness would produce the MWP, LIA and Modern Warm Period.
If global albedo changes then the effect at the surface is the same as if ToA insolation had changed and so that does reset the thermostat.
“A thermostat requires negative feedback in both directions around some central level, and some kind of damping mechanism to ensure that the system does not oscillate wildly.”
The oceans do the damping because of their huge thermal capacity and long term internal variability.
The central level has to be provided by something that is constant, otherwise no stability. That is why it must be atmospheric mass (leading to surface pressure when gravity is applied).
Willis is contemptuous of that idea.
“I hold that changes in forcing only marginally and briefly affect the temperature. Instead, I say that a host of emergent thermostatic phenomena act quickly to cool the planet when it is too warm, and to warm it when it is too cool.”
Which begs the question, apart from cooling from volcanoes, what else at the scale of ESNO events is causing it to be warmer and cooler?
Would still appreciate if somebody were willing to tell me why my earlier idea is wrong. I’m sure it’s got to be, since it’s so simple, but I’ve no clue why and am curious.
Thanks in advance,
Russ in Texas
RC Saumarez says:
September 24, 2013 at 1:35 am
Naw, it was supposed to be this strange thing called “humor” …
RC, you’ve made that same claim above, based on your overall experience, that small changes in the data lead to large changes in the model parameter.
Me, I’ve actually tried the experiment a number of times using real data, and found no such thing. Given the choice between my experiments and your theory, sorry, but I’m going with the experiments.
I’ve been very clear about my methods and my data. How about you grab the data and actually try making some small changes, and see what happens.
“Account for the fact”? Your claim is that my results, when compared with the climate model results, have an R^2 of ~ 0.98 but the ACF is different? Could be … but how different, and why does that make a difference? And why would slight differences in the ACF, particularly at longer lengths, invalidate the model? I’m not trying to emulate the ACF of the results, I’m trying to emulate the results themselves, and doing quite well.
I have not “failed to address” anything. I’ve not ever seen you produce a scrap of evidence that my results have a different ACF than the model results that they emulate. If you can show such a thing, not just claim it but come up with data that shows that the ACF of my model results is significantly different than the ACF of the climate models, I’m happy to address it.
Whoa, there, cowboy. I didn’t plagiarize one damn thing. The quickest way to get your vote cancelled is to accuse me of lying or of theft. Perhaps you engage in those kinds of things. I don’t.
Authority? You think that scientific questions revolve around authority? I don’t give a fig for authority, I’m interested in data and observations and math.
RC, that’s wonderful. My congratulations. What does it have to do with my analysis?
And yet here you are … still reading my opinionated, ill-educated, pretentious words.
RC, you have said any number of times that there is some giant error in my “black box” analysis of the climate models. Here’s one of your claims, for example:
But when I went to the post you claims “corrects my rubbish”, I and my work are not mentioned anywhere by you. Not one word, not one scrap of my data, no discussion of my model, nothing. Despite that, you clearly walked away thinking you had shown something …
Now, perhaps there is some huge error in my “black box” model. But I fear that you declaiming that an error exists is far different from you demonstrating and explaining the error. I just did a search of your comments on my threads, and I don’t find such an exposition anywhere.
As a result, to data you’ve given me nothing. Well, nothing but grief. You may be correct, but jumping up and down and saying that you have a PhD and you’re a published expert … well, I’m afraid that at WUWT that loses you points. We’ve had an unending string of PhDs who it turns out were clueless … you can start with Michael Mann and move on from there. So claiming expertise merely makes people wonder. As my great-grandfather used to say, If you have to hang your diploma on the wall, there’s something wrong with your education.
Now, I’m perfectly happy to reboot this discussion. You can try starting over, and cutting way, way back on the arrogant, paternalistic tone. If you think I’m wrong, and I have been many times, then I invite you to QUOTE MY WORDS that you think are wrong, and then explain to us exactly where and why I’m wrong.
Simply put, around here, we follow the motto of the Royal Society, even though they no longer do so all that much. Their motto is “Nullius in verba”, which means “Don’t take anyone’s word for anything” … and I’m afraid that means that your PhD-backed, “published a substantial number of papers” word is worth absolutely nothing. Not only that, but the more you hammer on your qualifications, the less you impress anyone.
If you want to get traction around here, you need to demonstrate errors, not simply claim that they exist. And I’m happy for you to do that, it’s how I learn.
Best regards,
w.
Willis wrote in his post: “For the value of the forcing, I have not used the instantaneous value of the volcanic forcing, which is called “Fi“. Instead, I’ve used the effective forcing “Fe“, which is the value of the forcing after the system has completely adjusted to the changes. As you might expect, Fi is larger than Fe.”
According to the link he provided, the effective forcing appears to correct the aerosol forcing for latitude and may not reflect any adjustment to changes after the system. Using the effective forcing and a lagged analysis may not correct for the amount of time it takes the system to respond and therefore won’t produce an Equilibrium climate sensitivity.
RC Saumaurez, here’s the ACF for the Forster climate model results, and for my emulation.
Yes, the ACF of the emulation is not an exact match to the ACF of the climate model results … but I fail to see why that slight difference invalidates my emulation as you claim.
w.
Frank says:
September 24, 2013 at 8:33 am
Thanks, Frank. Actually, the difference between Fi and Fe has nothing to do with latitude. It’s all explained in the link to the “Efficacy” paper.
w.
tumetuestumefaisdubien1 says:
September 24, 2013 at 2:04 am
Say what? The emissivity of water in the IR spectrum is on the order of 0.96 for the spectral region from 9 to 12 microns … which makes the reflectivity about an order of magnitude smaller than you claim. See e.g. here.
Unfortunately, as a result of that error, your entire argument collapses.
w.
Willis Eschenbach says:
“Like I said … this myth of eruptions having some big cooling effect is hard to kill …”
Speak to Toba as Pinatubo was a fly speck on what was Toba. The earth seems to have, indeed, always come back, even from the Milankovich cycles, but some volcanic eruptions have long lasting effects. The problem is that all of the truly major ones being so far in the past rely on paleo data of questionable worth for determining their effects. Plus all of your regressions necessarily and understandably ignore all of the unmeasured exogenous variables which are also having a contemporaneous effect. Chaotic is a word that comes to mind for the system. But we do indeed always seem to eventually readjust as you postulate. Eventually is a big word here.
Greg Goodman says:
September 24, 2013 at 2:24 am
Thanks, Greg. You seem to think that the two terms are equivalent. They are not, which is why we say that an engine has a “governor”, and we don’t say it has a “feedback”. It’s also why we note that James Watt invented the “flyball governor”, he didn’t invent the “flyball feedback”
The difference is simple. A simple feedback applies a force which is either positive or negative. Neither the amount nor the sign of the feedback are a function of the current output of the system. Instead, the amount and sign of the feedback are fixed in advance.
A governor, on the other hand, applies a force which moves the output of the system towards some predetermined “set point”. You could think of it as a house with a furnace, an air conditioner, and a thermostat that turns one or the other on depending on the temperature. As a result, both the sign and the amount of the feedback applied by the governor are functions of the current output of the system.
All the best,
w.
Willis Eschenbach says:
“3) However, this is not the whole story. The reason that the temperature change after an eruption is so small is that the effect is quickly neutralized by the homeostatic nature of the climate.”
Any ideas about the what and wherefore of your “governor” and the homeostatic nature of the climate other than it is “invisible”? Cite me a previous paper if you want. What about the repetitive glaciations the earth experiences? The fact that the earth was much warmer (supposedly) 500mm ybp? Again, not that I disagree with the models being wrong as that is indisputable based upon observations. Just an old engineer trying to understand a little better.
Jim G says:
September 24, 2013 at 9:34 am
A good question. My first paper on the subject was “The Thermostat Hypothesis“. You might also enjoy “It’s Not About Feedback“, “The Details Are In The Devil“, “The Tao of El Nino“, and “Emergent Climate Phenomena“.
Come back if you have questions or ideas,
w.
Here’s my version of a “governor”(with some “overshoot”to make it more stable kinda like a suspension system on a …car).
http://en.wikipedia.org/wiki/File:Phase_diagram_of_water.svg
and also:
http://chemwiki.ucdavis.edu/Physical_Chemistry/Physical_Properties_of_Matter/Atomic_and_Molecular_Properties/Intermolecular_Forces/Unusual_Properties_of_Water
and also:
http://www.engineeringtoolbox.com/air-psychrometrics-properties-t_8.htm
…something about latent heat changing the moisture content with out changing the temperature.
Maybe i’m “overshooting”…whatever,just something to think about.
Thanks for all of your interesting articles and comments.
“Thanks, Greg. You seem to think that the two terms are equivalent. ”
No Willis, I do not think they are the _same_ but a governor will include a feedback. IIRC the Watts governor was centrifugal weights which actuate a vertical slider which controls the flow of steam to the piston. As the balls turn faster the pressure is reduced, this is a -/ve feedback. In fact it will be non-linear alteration of the slider with rpm because of the central pivot of the ball arms. This will be non-linear in the sense of less than linear. I would imagine that the valve action would be highly non linear with relaxation to the slider position but probably something like forth power with the turbulent flow of the stream through it.
That’s all back of envelop description but it gives an overall strong, continuous, non-linear negative feedback. This will be sufficient to control the engine rpm within a very close tolerance over a wide range of load and boiler pressure.
It needs some kind of negative feedback to perform the role of governor. Being non-linear will make it more responsive at the risk of some overshoot and oscillation. It would be incorrect to say a governor IS feedback but it requires a feedback to work.
As far a I can trust my volcano stack graphs , it appears the tropics goes one better and controls the integral. This would be like the Watts governor also ensuring that if the engine was temporarily slowed by increased load, it not only restored the engine speed to the control value but it also overshot in rpm to ensure total counter per hour did not slip. This way you could run a clock at the same time as the plough without it losing time.
This also is not the same as a feedback but relies on feedbacks. Is ‘governor’ define precisely enough to say this action is or is not a kind governor too, I don’t know but suspect it is not that precisely defined.
The point you seem to rail about is whether such an action is a feedback on the climate system as a whole. Well since it seems to fairly effectively counteract changes in radiative forcing the answer has to be yes and it have to be negative in sign. Whether it is linear or non-linera requires further inspection.
In terms of the tropics I would suggest it’s strongly non-linear (governor++) . Ex-tropics benefit from the stabilising influence and get basic governor regulation, I don’t see an obvious reason to say this more than linear, though it could be.
I hope that helps to explain why saying tropics are “a feedback” on climate does not mean the same a them being a linear feedback and how it is not contrary to your suggestion of ‘governor’ type behaviour.
My volcano graphs are not rigorous science but do suggest strong non-linear feedbacks controlling temperature in the tropics. This is why I thought it would be interesting to run your analysis here on tropics / ex-tropics to see whether is contradicted or corroborated what I found.
best.
Jim G says:
September 24, 2013 at 9:03 am
I would consider Tambora in 1815 to have been a major eruption. It’s the only unambiguous VEI-7 eruption (ejection of at least 100 cubic kilometers) to have been directly observed in recorded history. The effects of a few others were observed by ancient civilizations, & of course archaeology & geology record the effects of others during the Holocene & earlier epochs.
Willis and Paul_K: There is a discrepancy between the surface and satellite temperature records after Pinatubo. The global Hadley anomaly record Willis is using peaked at +0.37 degC in January 1992 (7 months after the eruption), the sixth highest monthly reading to this time*. Looking at three-month averages, the maximum drop in the surface temperature record appears to be about 0.3 degC below the highs seen in 1990 and the first half of 1991, not the 0.6+ degC drop seen in the satellite record. June-Nov 1992 averaged about 0.0 degC at the surface. Unfortunately, annual averages for the second half of the 1980’s ranged between 0.0 and +0.3 degC, so the 0.30 “drop” associated with the maximum influence of Pinatubo doesn’t look like anything out of the ordinary. If Willis was feeling nasty, he could accuse those who compiled the data that Paul_K reanalyzed of cherry-picking the record that shows Pinatubo having the biggest effect on temperature. If Paul_K had analyzed the surface temperature record, he certainly would have obtained a different ECS than he reported at The Blackboard. The confidence interval for any result should reflect the uncertainty in the data used to generate that result.
*Not surprisingly, all of the highest temperature readings occurred in Jan-Mar of El Nino years, (usually January) and were somewhat similar to the blip in Jan 1992. It sure looks like 1992 was an El Nino year. Perhaps it takes some time for the high values in SSTs to spread into the atmosphere, because the January 1992 blip is not apparent in the satellite record. The validity of any El Nino adjustment seems critical to any analysis of this event. Figure 1 of Wigley (2006) shows the 0.3 degC discrepancy between surface and satellite (TMT) records in January 1992. The adjusted TLT record used by Paul_K looks different from the TMT and surface records. )Perhaps the TLT record is the one that is least distorted by El Nino events and therefore easiest to analyze.) http://journals.ametsoc.org/doi/pdf/10.1175/JCLI3611.1
Paul_K: “The input stimulus (forcing) is normally given as an end-period cumulative . . . The formula used by Willis uses the stimulus at the START of the timestep to yield the temperature value at the END of the timestep.”
Thank your for the clear explanation, which makes perfect sense if one assumes (appropriately, in my view) the fiction that the forcing is a superposition of step functions that commence at the beginnings of respective time intervals n, continue forever, and have respective magnitudes F_n – F_{n-1}. That is, the forcing is piecewise constant, at value F_n in each interval n.
In Mr. Eschenbach’s formula T2 = T1 + lambda (F2 – F1) (1 – exp(-1/tau)) + exp(-1/tau) (T1 – T0), that is, the temperature T2 that prevails at the end of Time Interval 2 is the sum of the following right-hand-side terms:
(1) the temperature T1 at the start of time interval 2,
(2) the response lambda (F2 – F1) (1 – exp(-1/tau) to the step function (of magnitude F2 – F1) that started with that interval, and
(3) the increment exp(-1/tau) (T1 – T0) in the response to the step functions that commenced in previous intervals and whose sum was F1 in the previous interval.
Actually, I had already understood that the forcing data used (such as those in Column G in Mr. Eschenbach’s “Forcing” table) would be “end-period cumulative” if what you mean by that is consistent with the exegesis above.
The source of my confusion is that I would never have thought that the temperature data the models are to match take the form you describe. I would have thought, for instance, that each monthly temperature datum (Column J) would represent an average over the respective month rather than, as I now see that Mr. Eschenbach’s formula implies, the value the temperature had reached at month’s end.
And I confess that I’m reluctant to abandon that interpretation.