By Joe Born
Introduction
A long line of this site’s posts dated March 19, 2018, March 27, 2018, March 30, 2018, April 6, 2018, April 24, 2018, July 30, 2018, August 15, 2018, June 3, 2019, June 5, 2019, June 8, 2019, July 22, 2019, February 1, 2021, May 9, 2021, July 8, 2021, December 2, 2021, April 3, 2022, April 6, 2022, July 2, 2022, and September 9, 2022, advanced the theory that the reason for high estimates of equilibrium climate sensitivity (“ECS”) is that modelers failed to take sunshine into account. (ECS is the equilibrium-temperature change that doubling the atmosphere’s carbon-dioxide content would eventually cause.)
Slogging through that compilation of changing values, ambiguities, and non sequiturs was a dispiriting exercise, but a reasonably clear distillation of the theory eventually did turn up, in what was triumphantly called “the end of the global warming scam in a single slide.” By focusing last year on that slide we demonstrated that this forgotten-sunshine theory amounts to no more than bad extrapolation and that the purported feedback law on which the theory rests actually doesn’t rule high ECS values out at all.
Perhaps as a result of that demonstration a new slide was substituted and emphasis was shifted to a new definition of the feedback law that high ECS values were claimed to violate. In this post we use that new slide as our focus.
What we will find as a result is that the rule imposed by the new slide’s calculations is not a valid feedback law and that the new definition either (1) imposes linear proportionality that feedback theory doesn’t require or (2) fails, by allowing the nonlinearity that feedback theory permits, to rule out high ECS values. In the process we will dispose of some of the ancillary claims that have been made in support of this theory.
Background
To the extent that there actually is such a thing as ECS, many observation-based papers such as those by Lindzen & Choi, Otto et al., and Lewis & Curry have found its value to be significantly lower than most prominent models’ estimates. “However,” Christopher Monckton said of such papers’ authors, “they can’t absolutely prove that they are right. We think that what we’ve done here is to absolutely prove that we are right.”
The key, he says, is feedback theory. The climate is a feedback system, so it must follow the laws that apply to feedback systems generally. And since in absolute terms the global-average surface temperature isn’t much greater than it would be without feedback, he says, feedback law prohibits high ECS values. But he’s never defined with clarity just what the feedback law is that would rule high ECS values out.
That’s not to say that he’s never attempted such a definition. The noun clause in the following passage’s first sentence, for example, is one he’s primarily used until recently:
[T]he main point . . . is that such feedbacks as may subsist in a dynamical system at any given moment must perforce respond to the entire reference signal then obtaining, and not merely to some arbitrarily-selected fraction thereof. Once that point – which is well established in control theory but has, as far as we can discover, hitherto entirely escaped the attention of climatology- is conceded, as it must be, then it follows that equilibrium sensitivity to doubled CO2 must be low.”
We’ll call that clause his “entire-signal law,” and perhaps it can be so interpreted as to be valid. But, contrary to what the foregoing passage’s second sentence contends, the entire-signal law doesn’t necessarily imply low ECS values. To see why he nonetheless imagines it does, let’s consider how he views feedback.
In the climate context temperature feedback refers to the effects of temperature determinants that in turn depend on temperature. Water vapor and clouds, for example, affect temperature, which in turn affects evaporation and thereby water vapor and clouds. Similarly, albedo—i.e., the fraction of solar radiation that the earth reflects rather than absorbs—affects temperature, which in turn affects ice and snow cover and thereby albedo. Feedback is typically distinguished from “direct” effects of, say, the sun and the atmospheric concentrations of non-condensing greenhouse gases like carbon dioxide, whose minor temperature dependence is usually ignored in such discussions.
Fig. 1 illustrates how Lord Monckton looks upon the equilibrium global-average surface temperature E: as the sum of (1) the value R (“reference signal”) it would have without feedback and (2) a feedback response F equal to the product of E and a feedback coefficient f. The without-feedback temperature R can be thought of as the sum of “direct input signals” S and C, where S is the value that R would have if there were no non-condensing greenhouse gases and C is the difference between that value and the value to which such greenhouse gases raise R. (If thus adding temperatures makes you feel queasy, please hold your physics objections in abeyance and for present purposes just focus on the math. Similar forbearance is requested of those who unlike Lord Monckton look upon feedback as only a small-signal quantity, i.e., as operating only on departures from some baseline condition.)
It is widely accepted that if there were no feedback the equilibrium-temperature increase caused by doubling carbon-dioxide concentration would be modest; Lord Monckton’s new slide calls it 1.05 K, which he refers to as the “reference climate sensitivity,” or “RCS.” So the change in F for a 1.05 K change in R has to be large if ECS estimates are greatly to exceed that modest RCS value. According to the forgotten-sunshine theory, however, feedback theory tells us that large feedback-response changes are inconsistent with the fact that (at least according to him) the pre-industrial value of the total equilibrium feedback response F was only 24 K.
That pre-industrial value of F is represented (but not to scale) by the ordinate of the red dot in Fig. 2. The upper green dot’s ordinate represents (again, not to scale) what doubling carbon-dioxide content would change F to if ECS were high: the result of adding to F’s pre-industrial value the difference between the RCS value and a high ECS value. By in effect projecting through those points to F = 0 as the green dashed line suggests, Lord Monckton concluded that instead of making the feedback “respond to the entire reference signal then obtaining” climate modelers had made the “grave error” of forgetting that signal’s sunshine constituent S.
He claims the scientific literature supports this conclusion. For example, he frequently cites a 2010 Science article by Lacis et al. entitled “Atmospheric CO2: Principal Control Knob Governing Earth’s Temperature.” That paper’s ECS estimate is high, and presumably from the thereby-implied high extrapolation slope Lord Monckton inferred that according to Lacis et al. the feedback response would reach zero at the 255 K value they gave as the “emission temperature.”
But that’s a bizarre interpretation of Lacis et al.’s following passage:
A direct consequence of this combination of feedback by the condensable and forcing by the noncondensable constituents of the atmospheric greenhouse is that the terrestrial greenhouse effect would collapse were it not for the presence of these noncondensing GHGs. If the global atmospheric temperatures were to fall to as low as [255 K], the Clausius-Clapeyron relation would imply that the sustainable amount of atmospheric water vapor would become less than 10% of the current atmospheric value. This would result in (radiative) forcing reduced by [about 30 watts per square meter], causing much of the remaining water vapor to precipitate, thus enhancing the snow/ice albedo to further diminish the absorbed solar radiation. Such a condition would inevitably lead to runaway glaciation, producing an ice ball Earth.
Lacis et al. say evaporation and albedo feedback would persist, that is, even if the complete loss of carbon dioxide and other “noncondensable constituents of the atmospheric greenhouse” were to reduce the surface temperature to a value as low as the 255 K emission temperature. So the reason why Lacis et al.’s estimate was too high isn’t that they had “forgotten that the Sun is shining.”
As Fig. 2’s hypothetical feedback curve suggests, modelers more likely did indeed take sunshine into account but believed that the feedback coefficient f would be lower at lower E values than it is now, i.e., that F is a nonlinear function of E and thus of R. (Actually, F and E probably are not single-valued functions of R, but for the sake of discussion we’ll assume they are.)
Lord Monckton nonetheless thinks modelers neglected sunshine, so to take it into account he extrapolates from the origin. He thereby arrives at the lower feedback quantity represented by Fig. 2’s blue dot.
Extrapolation
After Lord Monckton had for years used the above-quoted entire-signal language to define the purported feedback law on which he based such calculations, “An Electronic Analog to Climate Feedback” illustrated how high ECS values can result even if the feedback does respond to “the entire reference signal.” (The feedback element in that electronic analog responded to the entire voltage difference between a virtual ground and an output node whose voltage was proportional to the entire sum of the input and feedback currents.) Lord Monckton thereafter introduced a “strict proportion” formulation we’ll see in due course. He still says of climate modelers, though, that “[w]hat the poor saps had forgotten is that the Sun is shining,” and his new slide, to which we presently turn, purports to depict that error and his “correction.”
We will see that in the new slide, too, his correction amounts to linear extrapolation from the origin and thereby imposes linear proportionality. Since linear proportionality isn’t a valid feedback law, though, he denies that the slide’s “corrected” calculation amounts to extrapolation:
To head off the trolls who tend to maunder on to the ineffectual effect that that calculation is ‘inappropriate extrapolation’, there is no extrapolation at all: for there was a temperature equilibrium in 1850. It was, of course, the perpetrators of the error, not I, who had extrapolated, in that they had imagined that the ratio of equilibrium to directly-forced warming in 2100 would be about the same as it was in 1850.” </blockquote>
But that first sentence is a non sequitur; nothing about the existence of an 1850 temperature equilibrium is inconsistent with the proposition that the new slide depicts the simple linear extrapolation we learned in high-school analytic geometry.
Remember how we were asked in high school to estimate a third point C on an unknown curve from two known points A and B? We would be given C’s x coordinate, and to estimate the y-coordinate difference between Points B and C we would multiply the x-coordinate difference between B and C by an extrapolation slope m calculated as the ratio that A and B’s y-coordinate difference bears to their x-coordinate difference.
Fig. 3 illustrates that operation, with R’s and E’s substituted for our high-school x’s and y’s. The hypothetical unknown E(R) function starts at the origin because E and R are absolute temperatures and therefore positive-valued, and for illustration purposes we’ve made that function more convex than high-ECS proponents probably would. The green dot represents the extrapolated estimate of the hypothetically true value that the top red dot depicts.
Such simple linear extrapolation is exactly what the first two rows of Lord Monckton’s above-copied new slide illustrate. (We’ll eventually see that the slide’s third row is just a distraction.) The slide’s first row represents calculating the extrapolation slope m = ΔE/ΔR, while its second row represents calculating ECS by taking the product of that extrapolation slope and the 1.05 K RCS value.
The slide’s first, “FALSE” column represents the climatology error that Lord Monckton has allegedly discovered. Its second, “CORRECTED” column represents the calculation that his feedback law dictates. Both columns take as their Point B the (R, E) = (263 K, 287 K) state of pre-industrial equilibrium that Lord Monckton says prevailed in 1850. But the two columns’ calculations arrive at different ECS values (4.2 K and 1.1 K) because they base their extrapolation-slope calculations on different Points A.
The “FALSE” column’s Point A is the (R, E) = (255 K, 255 K) state that Lord Monckton says modelers believe would prevail in the absence of non-condensing greenhouse gases: the with- and without-feedback temperatures E and R are identical because according to Lord Monckton modelers think the feedback response F would be zero at the 255 K temperature that (we accept for the sake of argument) would result if the sun were the only source of “direct” warming. Accordingly, the slide’s “FALSE” column calculates its ECS value 4.2 K by taking the product of the RCS value 1.05 K and the extrapolation slope m = 4 (= 32 K ÷ 8 K) calculated as the ratio ΔE/ΔR of the temperature differences ΔE = 32 K (= 287 K – 255 K) and ΔR = 8 K (= 263 K – 255 K) between Points A and B. (Obviously, Fig. 3 exaggerates RCS’s magnitude with respect to ECS’s, and it greatly exaggerates ECS’s magnitude with respect to ΔE’s.)
As we observed above, Lacis et al.’s paper provides no support for Lord Monckton’s contention that they “forgot the sun is shining.” Moreover, their reasoning appears to be the reverse of what Lord Monckton’s “FALSE” column depicts. Instead of inferring ECS from, among other things, the conditions that would have prevailed without carbon dioxide, they apparently started with an ECS value already calculated by other means and used it to infer from the climate’s current state what the conditions would be like at 255 K and maybe below. But for the sake of discussion we’ll accept Lord Monckton’s version of their ECS calculation. And, as Lord Monckton said, that calculation does indeed amount to extrapolation.
Contrary to his denial, though, so does his own calculation. Specifically, his “CORRECTED” column’s calculation is exactly the same as the “FALSE” column’s except that to impose linear proportionality it replaces that column’s Point A, (R, E) = (255 K, 255 K), with the origin, (R, E) = (0 K, 0 K), which Fig. 5 accordingly labels A’. Represented in that plot by the vertical distance from Point B to the blue dot, the “CORRECTED” column’s ECS value 1.1 K is therefore the product of the RCS value 1.05 K and the extrapolation slope m = 1.095 that according to Lord Monckton’s arithmetic is the ratio ΔE/ΔR of the temperature differences ΔE = 287 K (= 287 K – 0 K) and ΔR = 263 K (= 263 K – 0 K) between Points A’ and B.
In short, his correction imposes a linear-proportionality requirement that true feedback theory does not.
The Nose of Wax
His numeric examples always impose such linear proportionality, and linear proportionality seems to be required by the “strict proportion” language he has recently emphasized. Here’s how he recently expressed the new formulation:
As any professor of control theory (the science of feedback) would tell Them, at any given moment in the evolution of a dynamical system moderated by feedback, especially where that system is at that moment in equilibrium, the total feedback response must be attributed in strict proportion to the relative magnitudes of the direct input signals to which the feedback processes extant in that system at that moment respond.
Given the pre-industrial equilibrium state that Lord Monckton assumes, this linear-proportionality interpretation would indeed (if it were a valid feedback law) rule out high ECS values.
But note the language: the feedback response must be “attributed.” Attribution can mean a merely mental act, an act that has no physical consequence. I can attribute the current temperature to the price of tea in China, but that attribution tells me nothing about what will happen to temperature when the price changes. So whether that language actually imposes linear proportionality—and thereby rules out high ECS values—is murky.
Such murkiness seems to be a feature, not a bug; it enables him to treat his feedback-law description as a nose of wax, twistable to any form. He benefits from the impression, given by the “strict proportion” language, that feedback theory rules out high ECS values. But when he’s faced with the fact that linear proportionality is not a valid feedback-theory law he rejects the “rebarbatively-repeated but actually false representation that I assume linearity in feedback response.”
Here’s his rationale for divorcing “strict proportion” from linear proportionality of F as a function of R:
[W]e are not dealing with an evolutionary curve across time, where the feedback processes might not necessarily respond linearly to changes in temperature as the climate evolves. We are dealing with a particular moment, and a moment of equilibrium in the crucial variable at that.
What does that mean? Can we so interpret it as to divorce his verbal formulation’s “in strict proportion” language from the linear proportionality that his numerical examples actually implement? Well, in the next paragraph we’ll try.
Under doubled-carbon-dioxide conditions, just as under the pre-industrial, year-1850 conditions, all portions ΔF of the feedback response F “must be attributed,” he seems to say, “in strict proportion” to corresponding portions ΔR of the without-feedback temperature R: the proportionality coefficient k ≡ f/(1 – f) in ΔF = kΔR must be the same for all ΔF and corresponding ΔR. But there’s no physical experiment that could test that attribution. This is because E’s value under pre-industrial conditions—at that “given moment”—can differ from its value at a different “moment,” such as when carbon-dioxide concentration has doubled. Since f and therefore k can vary in response to changes in the with-feedback temperature E, the common k that prevails for all feedback-response portions ΔF under doubled-carbon-dioxide conditions needn’t be the same as the common k that prevailed for all portions under pre-industrial conditions.
Clear as mud, right? Sorry about that; it’s challenging to make sense of his verbiage. If you did follow that proposed interpretation, though, you’ll recognize that it does indeed avoid implying “linearity in the feedback response”; linear proportionality would require that k be independent of E, whereas the foregoing-paragraph interpretation does not. But you’ll also see that by allowing k to depend on and therefore potentially increase with E it fails to prohibit the high-ECS “FALSE” calculation or dictate the low-ECS “CORRECTED” calculation. In other words, such an interpretation wouldn’t imply what Lord Monckton set out to prove.
So here’s the situation. If his “strict proportion” language does require the linear proportionality that his numerical examples always impose, then it rules out high ECS values but the proof fails because the purported feedback law it defines isn’t valid. If that language doesn’t require linear proportionality, on the other hand, then his proof still fails, because even if the resultant feedback law isn’t erroneous it doesn’t require ECS to be low.
The Third Row
Lord Monckton makes a further assertion: that “after correction of climatology’s error in forgetting that the Sun was shining, even a minuscule change in the feedback-driven system-gain factor would engender a very large change in final warming per unit of direct warming, compared with 1850.” It’s not at all clear how he thinks low ECS values follow from this assertion, but apparently the new slide’s third row is intended as an illustration.
The third row purports to illustrate the ECS effects of a 1% “system-gain factor” increase. In the first column it increases E(R)’s slope dE/dR by 1% on only the RCS = 1.05 K interval between Points B and C. Not surprisingly, it thereby increases ECS by 1%, from 4.20 K to 4.24 K. In the second column, too, the third row increases E(R)’s slope by 1%, but this time throughout the entire 264.05 K interval between Points A’ and C. Here, too, the ECS increase would be 1%, in this case from 1.15 K to 1.16 K.
However, Lord Monckton ignored the fact that thus extending the slope change over the entire domain would increase not only E’s doubled-carbon-dioxide, Point C value but also its pre-industrial, Point B value. So instead of correctly calculating the new ECS value by taking the E-value difference between the new Points B and C he calculated it erroneously by taking the E-value difference between the old Point B and the new Point C. That would have resulted in an apparent increase of about 260%, from 1.1 K to 4.0 K, but apparently because of an arithmetic error the slide says the increase is 340%.
In short, he obtained an orders-of-magnitude difference by performing two completely different calculations. How does that prove that feedback theory rules out high ECS values? It doesn’t. And such absences of logical connection between premise and conclusion afflict much of what he says about his theory.
Not Very Nonlinear
Now, some observers may have actually worked through the logic and/or noticed that in none of the dozen or more head posts in which Lord Monckton has argued for the alleged feedback law has he ever provided a mathematical proof of the purported feedback law, given details of the series of experiments claimed to have been performed at a national laboratory of physics, or identified a passage in any control-systems textbook that states such a law (although his theory seems to have been based initially on a misinterpretation of Hendrik Bode’s Network Analysis and Feedback Amplifier Design). However that may be, it’s clear that not everyone has been distracted from the central question.
“What if the system gain factor is not invariant with temperature?” is how Lord Monckton described the way in which that question was raised by University of Alabama meteorologist Roy Spencer. The gist of his answer seems to be that, yes, E(R) can be non-linear, but it can’t be so non-linear as to result in a high ECS value.
Now, let’s be clear. One might plausibly argue that other skeptics who believe ECS is low thereby also imply that E(R) can’t be very nonlinear. But such skeptics would be reasoning from a low ECS value to a near-linearity conclusion. Lord Monckton instead reasons in the other direction, i.e., to a low ECS value from the premise that E(R) can’t be very nonlinear. And that raises the following question: Why can’t E(R) be that nonlinear if we don’t assume a priori that ECS is low?
Lord Monckton’s reasoning isn’t exactly syllogistic on that question, either. But it has sometimes involved the claim that according to the Intergovernmental Panel on Climate Change (“IPCC”) the “feedback parameter” and the “climate-sensitivity parameter” are “nearly invariant.” And here Lord Monckton mixes apples with oranges.
Specifically, discussions of such parameters tend to concern small-signal quantities and be restricted to the narrow range of global-average surface temperatures that man has experienced or is likely to. And, as the “‘Near-Invariant’” section of “Remystifying Feedback” explained, nothing about whatever near-invariance the IPCC has claimed over such ranges rules out high ECS values; Lord Monckton seems to have confused small-signal quantities with large-signal quantities.
His argument against such observations involved concocting a figure of merit, which he called the “X factor,” so designed as to exhibit large increases in response to small temperature changes and thereby give the impression that high ECS values would imply implausibly large system changes. As can be seen at time stamp 21:45 et seq. in the video of his July 2019 speech to the Heartland Institute’s Thirteenth International Conference on Climate Change, the X factor was the basis of his response to Dr. Spencer’s above-mentioned question. But the “Apples to Oranges” section of “The Power of Obscure Language” refutes that response, showing that it’s similar to the type of meaningless comparison that the new slide’s third row exemplifies.
Recap
The central claim of the forgotten-sunshine theory is a purported mathematical proof, based on feedback theory, that ECS is low. But the actual calculations apply the erroneous law that a feedback system’s output must be linearly proportional to what it would have been without feedback. And, although he denies that this is the law he’s applying, his various verbal formulations don’t rule out high ECS values if they’re interpreted in any other way. So the central theory fails.
An ancillary argument is that climate modelers’ feedback calculations don’t take sunshine into account. As we saw, though, the paper he most relies on for that proposition specifically discusses evaporation and albedo feedback at the emission temperature. That hardly amounts to forgetting sunshine.
Another argument is that high ECS values are inconsistent with IPCC statements of near-invariance. But we’ve seen elsewhere that he reaches such a conclusion only by interpreting those statements as dealing with changes in large-signal quantities, over a global-average-surface-temperature range much wider than humans have encountered or are likely to. And no justification was provided for adopting such an extraordinary interpretation.
Finally, he attempted to bolster the latter argument by using calculations like those in the new slide’s third row to give the impression that high ECS values would necessitate implausibly abrupt changes in other climate parameters. But working through such calculations reveals that they compare apples to oranges and have no logical connection to the proposition that high ECS values are inconsistent with feedback theory.
Conclusion
This all becomes apparent to critical thinkers who work through the math and logic. But not all readers have the time and inclination for such an exercise. Those who don’t may want to consider the following.
If modelers really had made so fundamental an error as failing to take the sun into account, Lord Monckton’s theory would be a scientific kill shot. Wouldn’t heavyweights like Richard Lindzen, William Happer, John Christy, and Roy Spencer therefore have embraced it? Wouldn’t the CO2 Coalition’s Web site have featured Lord Monckton’s theory? Wouldn’t Dr. Spencer have championed it on his blog?
But they haven’t. In fact, Dr. Spencer has instead written a rebuttal. The theory that feedback law rules out high ECS values is like the theory that there’s no greenhouse effect: although its conclusion is attractive, the theory itself is clearly wrong.
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Monckton is yet basically right, though for reasons he might not know about. I think I have well illustrated the problem here..
https://greenhousedefect.com/about-the-physical-impossibility-of-feedbacks
The graph depicts different planets (including Ceres) and moons of our solar system. We have the distance from the sun in AUs on the x-scale, and the reported temperatures on the y-scale. Temperatures were taken from wikipedia and are certainly not all totally correct. The drawn line represents black body temperatures (excluding albedo!) at the respective from the sun.
As we can see the celestial bodies follow this line very strictly, with the exception of Venus. That is why I added the light blue dots. I should note the “surface” of gas giants is arbitrarilly defined as the pressure level of 1 bar, like Earth. So the surface of Venus is at 92 bar, that of Jupiter at only 1 bar. To make it more comparable, the light blue dots give the temperature of Venus at 1 bar, and that of Jupiter and Saturn at 92 bar. I think the problem is quite obvious..
Anyhow, the interesting question is how Earth would behave, if it was moved closer to, or further from the sun. Would it stick to the blue line, or not? If the were no feedbacks, the answer would be yes. The blue line is just representing the forced temperature. If you say there were feedbacks multiplying that forcing only a factor of 2, you get the red line. Then Earth would turn much colder than other celestial bodies more distant from the sun, if you would move into their respective positions. Or hotter than Mercury, on the other extreme.
However such a small feedback would not get it even close to the heat of Venus. So the question is essentially if Venus is the benchmark, or all other celestial bodies. Given what I provided above, there is already an answer around the corner. The massive GHE of Venus is obviously depending on the mass of its atmosphere.
Theoretically it is thinkable that Earth runs so hot, that the oceans evaporate and provide Earth with a similar massive atmosphere, mainly consisting of H2O. For anything like it to happen, for even a moderate feedback, we would need to see a mass increase of the atmosphere. Or growing air pressure respectively, and substantially so. To my knowledge that is not happening..
Of course there is further knowledge confirming the insights above. WV feedback has been calculated excluding overlaps, giving some 1.8W/m2. Allowing for overlaps, and accurate surface emissivity, this figure drops to about 0.65W/m2. Effectively this is less than negative “lapse rate feedback”, meaning WV is actually a negative feedback as a whole. Also other assumed feedbacks, like albedo or cloud feedback are full of flaws and speculation. It is safe to say the feedback narrative is politically, not evidence driven.
Excellent post. Mass and emissivity are crucial. Movement of mass creates pressure differences that give rise to temperature changes. The magnitude of the temperature change depends on the total mass and its emissivity.
Eshaffer. Good post. I forgot to add this link on importance of mass with air movement. By Erl Happ.
Lots of chapters led to this summary.
https://reality348.wordpress.com/2021/10/26/new-book-the-movement-of-the-atmosphere/
That is practically another approach to come to the same conclusion as N&Z that TSI and atmospheric mass are setting basic temperature of celestial bodies.
It would be particular appealing as it explains, if true, temperatures independent of “weather” phenomena and annual variations on each celestial body.
The math of N&Z might be curve overfitting but the data points into the direction that this relation could be true and CO2 concentrations completely irrelevant to the climate.
I wish I’d know what “N&Z” is..
It refers to Nikolov and Zeller who published a paper under fake names:
“Emergent Model for Predicting the Average Surface Temperature of Rocky Planets with Diverse Atmospheres”
The paper was withdrawn when their use of fake names was revealed.
Oh yes, I remember this one. I am afraid what they published is bull*#/+. For any specific gas there is a strict relation between pressure, density and temperature. Just because you can calculate temperature based on pressure and density, does not mean you have explained WHY it has a certain temperature.
In fact it is not only atmospheric pressure that determines the magnitude of a GHE. There are other factors in play, as I pointed out in the article. With large, “runaway” GHEs however, pressure is indeed the most significant factor by far.
Also I would not say CO2 is completely irrelevant. It plays a role and in fact is the most significant GHG, rather than vapor. Yet the “science” hugely overstates it.
They found practically a similar correlation that – whatever the exact mechanism may be – would put TSI and atmospheric mass in the center and diminish the importance of atmosphere composition to a degree it plays only a minor role as different gases have different masses at same pressure per volume as they have same density.
I came to a similar conclusion from reading Monckton v. Spencer and so forth and so on. Monckton is close to correct, but not quite.
I didn’t understand a lot of this, Born is disagreeing with Monckton’s methodology. I don’t know who is right what I do know is that the climate models have not matched observations. Monckton believes the modelers assign too much of an affect from a doubling of CO2. Born disagrees with Monckton’s thinking but doesn’t refute that the models don’t match observations. So if he thinks Monckton is wrong then what is the reason? My understanding is that CO2 in and of itself does not raise average global temperatures but the feedback from the added CO2 is responsible. I think the modellers have figured for the positive feedback but not the negative feedback. I think their models are worthless until they are properly configured. I have no idea where Born stands on the issue except against Monckton. That is not helpful.
I find long winded “proofs” in math unconvincing. If the math is wrong a few lines is all it takes to show this. 100 scientists signed a letter saying relativity was wrong. Einstein’s reply, “if I’m wrong it only takes 1”
I looked at the math behind this some years ago and concluded monckton had a point.
Feedback in a steering wheel for example is not relative to the current position of the steering wheel. It is relative to the “hands off” zero feedback position.
Climate science has the wrong definition for feedback.
Monckton does have a point. Hopefully, sometime he will nail it really well.
The problem is ECS. It is relative to a doubling of CO2. This is a nonsense because there are an infinite number of doubling between 0 ppm CO2 and current CO2. So ECS is thus mathematically undefined.
The ECS curve is a nonsense because
There must be a discontinuity around 0 C, when CO2 concentrations permit liquid water. Where is this?
The no ghg temp is -18. Current temp is 15. 33 C diff. How is this possible? Water has near zero GHG effect at -18 because it is ice. How did CO2 get us from -18 to 0? . How many doublings of CO2 is this?
Divide 18 C by number of doublings from 0 to 280 ppm and you have min ECS. how many times do you have to double 0 to get 18?
Here is a “simple” feedback device
This device powers the trim tab on the rudder of a boat. It converts positive feedback to negative feedback with gain, allowing a small autohelm to steer a 40 foot 12 ton sailboat offshore.
I designed and built the device and sailed 10s of thousands of miles offshore using the device.
My experiences driving this device was what convinced me climate science has feedback wrong.
Points awarded for dragging your 40ft sailboat into the fray. We sail a Sparkman & Stephens designed Hughes 40 Ketch on Lake Michigan and the long full length keel leads to sluggish turns, so much so that impatient helmsmen will keep increasing rudder deflection to increase the turn rate right up until they stall the rudder, at which point you get an emergent phenomenon – the boat no longer goes where you want it to go.
That is the same as saying there in no GOD. Of course there is a GHE. It is a deeply held religious belief that has nothing ti do with Earth’s energy balance.
All this nonsense started with Manabe making silly atmospheric models that linked CO2 to surface warming. They are unrelated to what occurs on Earth’s surface.
Atmospheric CO2 CANNOT change the freezing point of sea ice. Therefore the insulating property of sea ice remains. The water below never gets colder than -1.8C.
Likewise CO2 cannot alter the point in the atmosphere where a level of free convection forms and deep convection sets in to prevent open ocean surface sustaining more than 30C. This process limits further heat uptake.
CO2 would have to be selective in whether it cools, warms and does not alter surface temperature – explain that if you think there is a GHE involved in Earth’s energy balance? The fact is there is NO GLOBAL warming. Some regions are warming, some cooling and some steady.
Any climate model that shows the Southern Ocean warming in this century are WRONG. They are ALL WRONG.
Could it kill you to learn to write clearly with actual structure? Nobody has. F-ing clue what argument you’re trying to make until the final paragraph. This is terrible writing.
Still have not seen a clear statement of what would happen if the atmosphere did not have water vapor and other green house gasses in it. The fact we have an atmosphere should change the base temperature of the planet, as the atmosphere would have no way, other than black body radiation, to lose energy. How much energy would the atmosphere gain from conduction and convection from the earths surface at near equilibrium? What temperature would that leave the near surface atmosphere, and would that temperature increase or decrease the surface temperature of the planet?
Which then leads to, adding greenhouse gases to the atmosphere leads to the atmosphere gaining a path to expelling energy it did not have previously. I personally think the Greenhouse gases are a wash in determining temperature. Not a gain.
Without any IR active gasses in it the atmosphere would heat/cool by contact with the ground surface, and would be stirred into convection when warmed. But without those IR active gasses the atmosphere would be exceptionally transparent to IR radiation, and the surface would lose heat constantly to space directly. You would have a situation where radiation and gasses would present different temperatures.
A few facts that may help.
The Troposphere is heated by the Earth’s surface through convection, conduction and latent heat.
All IR radiation entering the Troposphere leaves the Troposphere either to space or back to the surface. It does not heat the Troposphere.
The fraction of the radiation returning to the surface adds heats to the surface which then adds heat to the Troposphere through the process mentioned above.
So the atmosphere does not heat the surface GHGs do not add a path to expel energy. They limit existing paths.
Many here are missing the Viscount’s main point, which is that in all real-world cases where amplifying control circuits are used, there are TWO power sources – (1) VCC, and (2) the input signal. The DC power supply (VCC) is practically infinite when compared to the variable input signal to be amplified. To make a simple amplifier, you bias the transistor midway between zero and the supply voltage so that power flows through the transistor. The transistor is chosen to produce a large change in current for a small change in voltage (the input signal voltage) at the quiescent point. The large current change is then forced through a resistor to produce a large change in voltage – viola, amplification. This used to be a freshman electrical engineering lab assignment. The Viscount merely points out that solar insolation is the wattage (VCC) that balances the atmospheric circuit and sets the quiescent point, and that wattage and resulting temperature must be measured from zero (Kelvin for temps). He then stipulates to CO2 providing a few more watts of feedback, and then asks the question, “how are these last few watts of forcing any different than all of the watts that came before?” His answer is of course, there is no difference, a watt is watt. Ergo, the old watts (insolation) must also be affected by feedback the same as the new watts (CO2 forcing).
And for any who want to argue the importance that the response is non-linear, don’t bother. Even for strongly non-linear circuit responses, the forcing wattage is such a small percentage of solar insolation that the response is effectively linear. For the atmosphere, the input signal is the sum of Solar Insolation (340 watts) + CO2 forcing (3 watts?), which is +/- 1%. Pick any non-linear function like y=x^4, and vary x by +/- 1% and see how much y changes. It’s pretty linear. Those of us who did that freshman lab know this to be true.
“The Viscount merely points out that solar insolation is the wattage (VCC) that balances the atmospheric circuit and sets the quiescent point, and that wattage and resulting temperature must be measured from zero (Kelvin for temps). “
Yes, it sets the quiescent point. And so it is not part of the signal. It doesn’t change. And as you say, the power involved in VCC is far greater than the signal.
“For the atmosphere, the input signal is the sum of Solar Insolation (340 watts) + CO2 forcing (3 watts?”
No, it isn’t. Solar insolation is the VCC; the constant power source. CO2 is the signal. The problem is that by including part of a steady VCC component in the signal, he is treating it as if that DC is an amplitude. IOW, as if it swung from that value through zero (which is why he has to extrapolate down to 0K, obviously unphysical). Then his algebra goes that there is only a relatively small response to this hugely inflated input, so the sensitivity must be small.
You have no idea of what you are talking about. Why do you think a DC coupled amplifier only responds to a small signal? There is nothing in this system to “block” a “DC” signal, therefore an amplifier would respond to any DC at its input, whether it is insolation or feedback, with a corresponding output.
As I pointed out above, you also need to tell everyone where the power from “C” comes from. As TE pointed out. The power for the amplifier comes from the insolation. “C” does not have an independent power source. It is derived from “S”, consequently you have S-C as the input. When you add [(S-C)+C, what do you get “S” alone. Therefore you can’t just add them together.
Likewise, the feedback doesn’t have its own power source. It must come from “E”. Therefore, the output is actually “E-F”, and when you add “F” back in, what do you get? “E”
This is truly what is wrong with the feedback theory. Basic feedback needs some kind of an amplifier with a separate power supply to work. There is no amplifier in the earth’s system.
Using a three terminal device you can’t draw a system with no GHG’s (where radiation in equals radiation out) that has both an input and a power supply of the sun’s energy unless you tie the Vcc node directly to the input or output.
You literally can’t draw a passive circuit where feedback can add energy without a separate source of energy separate from the sun. Any feedback subtracts from the output and when connected to the input results in the output remaining the same, i.e., (S+F) = E.
Stronger solar wind states in the 1970’s drove colder ocean phases, which increased low cloud cover and reduced sunshine hours. Weaker solar wind states since 1995 drove warmer ocean phases, which reduced low cloud cover and increased sunshine hours. An amplified negative feedback with considerable overshoot.
“However,” Christopher Monckton said of such papers’ authors, “they can’t absolutely prove that they are right. We think that what we’ve done here is to absolutely prove that we are right.”
there are few clues i look for in ascertaining whether a sceptical argument or discussion will be worth my while or possibly shed light on some unsolved problem in science
on, or skim the text for humor. nothing substantive will follow
2 appearence of the word PROVE. skeptics never understandthe concept of proof
it is up to sceptics to demonstrate that they understand the meaning of proof.
despite these two red flags i kept reading and ran across more red flags
and talk some nonsense. you see its human nature to find one word you understand and see every conversation through that word.
2 mentions of ecs and gcms. two clear red flags that sceptic nonsense lies ahead.
theres nothing more annoying than people who dont understand a theory debating finer points which are in contentionbetween people who do understand the theory.within the science there is plenty of debate about ECS. sceptics who join that debate, like nic lewis gain power and shape the course of science. people who dont understand the concept. waste eeryones time with silly debates.
so sceptics need to prove they understand the concept of ecs and that they understand how and why gcms are used before they ever TRY to argue about them. reading online gcm code is a good start.
t
Reading FORTRAN spaghetti is a good use of someone’s time?
Finding drive-by nonsense is real easy to find: the post is written by Steven M Mosher.
It is mathematicians who have no idea what the meaning of proof is in physical science. Physical science requires that a hypothesis be completed with a physical functional relationship defined in mathematical terms such that the relationship of variables provides an accurate prediction of what will occur in a system. This functional relationship can be tested and measured for accuracy. THAT IS SCIENTIFIC PROOF.
A correlation may result in a hypothesis, BUT IT IS NOT PROOF. Thus far all I have seen from you and climate science is correlation.
Of course we will DESCEND.
Why do you think we spent hours in class and labs working on that very subject of physical science?
Why do you think we spent hours in class learning about complex feedback systems in control theory?
How many hours have you spent in class time learning the ins and outs of complex feedback problems?
How many analog computers have you built to verify your mathematics for climate? Do you think analog computer components for adding, subtracting, integrating, with non-linear response weren’t built before digital computers even existed?
Basically you haven’t learned yet that you don’t even know what you don’t know.
Actually I can think of at least one thing considerably more annoying.
There is something more annoying: Condescension coming from a source that has no right to push it.
Isn’t this all a bit academic? CO2 concentration is growing at about 2 ppm per year. At that rate it will take 200 years to double the concentration.
[[The theory that feedback law rules out high ECS values is like the theory that there’s no greenhouse effect: although its conclusion is attractive, the theory itself is clearly wrong.]]
Um, you’re wrong. The U.N. IPCC’s greenhouse warming theory is forever “clearly” disproved by the profound observation that Earth’s atmosphere isn’t a black body radiator like the surfaces of the Sun and Earth, and it’s all a category mistake. If you need a primer on sweet pure thermal physics unfettered by IPCC hijacking then click the following link:
http://www.historyscoper.com/whyaregreenhousegastheoriesdeadwrong.html
Or see this cool Quora article I wrote recently:
(505) TL Winslow’s answer to Why do we say ‘no net heat flow between two objects of different temperatures’ but not ‘no heat flow’? – Quora
The very first sentence says it all. With ECS from CO2, you might as well be talking about Jabberwockies.
In the head posting here, the author says that,
“It is widely accepted that if there were no feedback the equilibrium-temperature increase caused by doubling carbon-dioxide concentration would be modest; Lord Monckton’s new slide calls it 1.05 K, which he refers to as the “reference climate sensitivity,” or “RCS.”
The author then goes on through a discussion, illustrated by several similar temperature feedback response graphs (or iterative trend graphs) as to how Monckton’s way of doing things could amount to an underestimate or what the “true” ECS (or CO2 doubling) sensitivity might be. That section of the head article then ends with the statement,
“In short, his correction imposes a linear-proportionality requirement that true feedback theory does not.”
Now look, what we are actually talking about here amounts to asking whether some sort of reasonable “Monckton-like” piecewise linear graph could be a good approach to estimating how much feedback amplification to expect in the more or less short term future? It’s a question of how much can we expect a 1.05K CO2 connected “at first estimate” delta-T to be multiplied by feedback, over, say, the next 60 or 70 years, or whatever?
One thing that I think tends to get lost in all the theorizing over how to derive a “whole signal” approach to feedback is that the exact nature of this overall, presumably nonlinear, temperature feedback may *not* matter as much as having a perceptive outlook on what short term implications might be, across many reasonable scenarios.
If the feedback “grand picture’ is at least something that lends itself to a generally consistent function, then ‘piecewise linear’ ought to be a helpful idea, given that the temperature ranges of concern are of only a few degrees, and are much less than the absolute ‘Kelvins’ numbers involved (i.e. ‘255 K’ or higher).
Just thinking in a relatively short term linear way, people tend to say that the average surface temperature has warmed just one degree C since year 1850 (and how that even gets attributed to human activity is a bit of a mind bender, but never mind). If we think about the ratio between 400 ppm CO2 today and 280 ppm back in 1850, that’s the square root of two, essentially, so in logarithmic terms, that’s half a doubling, for the CO2 concentration, that has taken place. Even if all the temp rise were occurring due to CO2 as advertised, we would then have to say that only about half a degree would be due to “at first estimate of conventional theory”. After that, just one more nice doubling (due to feedback as such) would get us to the 1 degree C rise that’s been estimated as empirical (more or less). So the linear implication then, is that it’s just “times two” for any pragmatic feedback implication, in ‘current’ time — and it would seem to be about that much of a boost for feedback almost no matter what we assume for the general nonlinear function.
If things aren’t so strange that we get an unaccountable acceleration in effects, isn’t it then reasonable to think that we are right now effectively on a temperature slope up or ‘boosting’ effect that will persist for at least a little while in the big picture of things? If you forecast another half doubling (or square root of 2 ratio increase) of CO2 over the next 60 years, say, and our little “piece” of piecewise linear feedback functioning goes on, what you’ll get in that time frame is {0.5 degree times “2” for the ongoing feedback enhancement} or just another 1 degree Celsius, then. Alarmists will have to scratch mighty hard for arbitrary tipping point alarms to make much of *this*, surely!
Now where I do have some sympathy for the writer of this current article is that for sure, trying to understand the big picture of atmosphere feedback is apt to result in some very fussy or complicated ways of considering things! My perception of the big picture theorizing is that Monckton himself tries to “get” the big picture as simply as possible, while at the same time, our current article writer likes to fuss over all that and redo it all in some way. But, what I would ask is both whether the conventional premises of how to boost the earth’s temperature are sound, and even if they are, how do we even know then what variety of amplification or signal boosting is the truly correct one for a really good take on temp feedback as such, ‘big picture’ wise?
Mathematically, many things are possible for the big picture here, including scenarios where *negative* feedbacks in fluctuating temperatures would naturally *combine* in some way, to make a build up or boost up in the overall steady state or median temperature. In addition there is the chance that conventional climate theorists have been wrong all along to think that there is any significant temperature enhancing effect related to feedback in the first place, there’s always *that*.
A long post but a good question. All of this is basically trying to find an hypothesis that might be plausible. Hard to do with no more data than we have. What I see is an extremely complicated waveform and trying to extract intermod components from straight harmonics to fundamental oscillations is going to require much more information than we currently have. We don’t even know what we don’t know yet.
So far the models are nothing more that game playing and give about the same unreal answers as any game “virtual” environment would. Monckton’s basic assumption is that he doesn’t believe the feedback theory, people forget this. His argument is that even when accepting the premise it is easy to show how wrong it is. I agree with him. An amplifier needs an external power source to provide the energy for amplification. Feedback in a non-amplifier (gain <= 1) can only use energy that is extracted from the output which is the same or less than the input. Consequently, there is no way to absolutely increase the output.
The other problem is that we are dealing with power here, not infinite impedances where no power is lost when using feedback. We are discussing power gain, not just voltage or current gain. Any power gain has to be supplied from somewhere.
Another way to frame this is to ask:
What is the transfer function from solar irradiance to surface temperature?
Cli Sci calls irrradiance “forcing” but doesn’t quite state how E changes into T.
I think the transfer function relating the Sun’s irradiance to surface temperature is the Stefan Boltzmann Law.
Does this go the wrong direction? Note that I specified solar irradiance.
You can’t really use T, both because it has a 4th power, but it doesn’t add directly, it adds via power, i.e. through flux.
I just put a diagram up that uses power splitters/combiners. It’s rough and doesn’t include everything that goes on, but is shows that there is only one source and everything must derive from that source!
S-B says E o= T^4, but the T is on Earth, it cannot control the Sun. At any given moment there is a wide range of T on Earth, so the transfer function can’t be simple.
The splitter/combiner has to be a better way of modeling, although I confess to not understanding what the individual letters mean. S is Sun and F is feedback, I presume, but don’t know what the others are. Why are S and C added prior to the summing node?
S is sun and C is CO2, then F is a feedback loop. CO2 doesn’t create its own energy so I used a splitter to show that S is split into (S – C) and C, then combined back together.
I have no idea what you mean by go in the wrong direction. Nobody thinks the Earth heats the Sun.
It is not difficult to understand what energy heats the surface of the Earth. Obviously the electromagnet energy from the Sun and energy radiated by the surface that is returned to the surface by the action of the greenhouse gasses. The temperature of the surface is not limited by the Sun’s irradiance. In this sense there is a second source of power, namely the GHGs, that is independent of the power from the Sun.
There are many variables that would greatly complicate an exact calculation of the surface temperature everywhere on the planet but determining averages seems to be doing pretty well..
The transfer function is from solar irradiance (E) to surface temperature on Earth, and you replied that is the S-B equation. This does not work because E is a function of T in the S-B equation, so it cannot be a transfer function.
No, E is not a function of T in the S-B equation. E = 1360 w/m^2 and is radiation from the Sun measured outside the planets atmosphere thus having no relationship to the surface temperature.
Sorry, but without the sun’s energy the temperature would fall drastically, so there is a relationship. Whether the temp is determinate via the S-B equation is another question. The basic question is can temps be used in a “feedback” solution. I would postulate that they can not until a better power to temperature functional relationship can be developed, and that doesn’t include the S-B equation as a transfer equation.
The Sun’s energy reaching the Earth above the atmosphere is a constant independent of the temperature of the Earth. The surface temperature due to that energy can be approximated using the S_B relationship modified by considering the effects of rotation and reflection.. The temperature derived from the incident radiation from the Sun is of course not the correct temperature because the energy returned to the surface as a result of the GHGs is not included.
Can temperature be used in a feedback solution. The temperature to power relationship is given by Plank’s equation. If you integrate over the radiated spectrum of a body at some temperature you determine the radiated power from that body at that temperature. You can even determine how much power is radiated at each frequency.
I would say that temperature itself can’t be used because temperatures cant be added or subtracted but powers derived from temperature can be added or subtracted.
Are we on the same page or are we talking past each other?
Emissivities, specific heats, convection, albedo, and latent heat screw up temperature calculations.
Fluxes can be added directly. Plus temperatures don’t cause other temperatures other than through convection/conduction.
Did you mean to exclude radiation from the last sentence?
I left it out because S-B deals only with radiation and not the other things.
You can’t use S-B as a temperature proxy in the earth’s internal climate system. If you want to deal with radiation only, like the “feedback” using Bode, you must use power, and not temperature. One must also realize that S-B does not adequately express the “monochromatic” flux that molecules radiate.
The S-B equation assumes that the entire black body radiation curve is radiated and that determines the flux. The emissivity can be used to modulate this, but one must know what emissivity to use for each molecule under varying pressure, temperature, etc.
Look, I don’t agree with this whole Bode feedback process at all. I think any attempt to use it is wrongheaded and we end up arguing about angels. We are talking heat transfer of all kinds, conduction, convection, radiation, and all of that is modulated by all kinds of periodic processes in the ocean, the surface of the earth, and by atmospheric processes.
One must understand Planck’s heat transfer theories by radiation and how to deal with gradients of temperature due to too many things to list. If we can’t develop timely and accurate gradients for all this, it will never be solved. I along with many others don’t feel CO2 can have the effects being attributed to it. H2O has so many fingers that it is the obvious culprit for temperature control of the atmosphere.
The mere display of a theory that CO2 causes temperature is misplaced. There is evidence otherwise and little to NO EVIDENCE that CO2 causes temperature.
I believe I can explain how a physicist might explain the relation between temperature and CO2. First they define temperature as the amount of kinetic energy within the body. This involves all the atoms, molecules lattice structures, whatever all vibrating around. At absolute zero all vibration stops. Energy is released as a photon when KE is reduced by some collision. The photon energy corresponds to the change in KE resulting from the collision. Likewise when a photon is absorbed by some atom the KE and thus temperature is increased.
A photon released from a body at say 15 microns will strongly interact with a CO2 molecule giving it KE in the form of vibration or rotation. Within a bout 5 microseconds the molecule releases an equivalent photon. If that photon strikes the originating body it will add KE increasing the temperature.
I’m not going to educate you. S-B is built on black bodies. CO2 is not a black body, it only absorbs a portion of the S-B calculated calculation. Same with H2O, CH4, etc. Absorptivity/emissivity factors let you calculate it. But is feedback calculable via temperature alone for different molecules? Also, remember that thermalization is involved. Ultimately it needs to all be converted to a power basis to preserve the energy relationships.
Feel free to use temps if that’s what you want. It won’t come out in the end, I assure you.
With anything involving the GHE in the atmosphere the question is not is CO2 gas a black body it is does it act like a black body and follow the temperature vs radiation intensity that characterizes a black body for the frequency band of interest . Every analysis I have seen says it follows that relationship.
But good luck with you attempt to show that H2O controls the temperature of the atmosphere. Heating the atmosphere is not done by the GHE which only results in heating the surface of the planet. That is LW radiation from the surface does not heat the atmosphere.
This irradiance has no effect on surface temperature?
From wikipedia:
Recall that it was you who stated that the S-B equation was the transfer function. Here is what you wrote:
Which is it?
S-B works regardless of which variable is chosen as the independent variable. Choose T as a constant independent variable and you can calculate the outgoing radiated power flux. Or choose the incoming flux as the constant independent variable and calculate the temperature. Most formulas work that way.
All I was saying is that the Sun’s radiance arriving at the Earth’s atmosphere is a constant. The surface temperature could be 1000C warmer and the arriving radiance would still be 1360w/m^2.
However if you want to know how that radiance will effect the Earth’s temperature given no other sources of energy flux then use the S-B relationship. It relates how the energy transfers into temperature.
OK, I’m done. Please learn what a transfer function is.
You can use S-B in an isolated system where no other bodies or processes exist and the involved bodies are considered black bodies.
You do realize a transfer function is an equation that takes an input signal and tells you what the output signal is.
S-B doesn’t do that.
In an electronic scenario one would input a “step function” and analyze the output to determine the individual components that exist in it. In the frequency domain a Fourier or wavelet analysis would be used. Hard to do with the earth.
What is the physical mechanism that sees an increment of temperature as different to the prevailing temperature in its feedback effect? Let’s deal with that before getting into ECS suppositions. Geoff S
In my readings, it would seem that climate theorists ever since the year 1900 or so have been looking to water, H2O, as such, to create a “mutual reaction of the physical quantities”, i.e., an enhanced feedback, or “positive” feedback of some sort. In these terms, they look to the watery Earth system to do something that they would never expect on some really different planetary surface, like the surface of Titan say. On Titan, we’ve got lakes, but they aren’t made of water, so ‘presto’, no feedback there, I guess!
As one alternative to making water feedback an essential in everyone’s favourite theory, it occurs to me that planet Earth as such is *materially* at least roughly a closed system, despite the flow through of energy. So maybe something like Le Chatelier’s Principle (or the Equilibrium Law) could apply here, as in the following link, say,https://www.thoughtco.com/definition-of-le-chateliers-principle-605297
To quote the above, under “Temperature” heading, it says.
“In other words, the system compensates for the reduction in temperature by favouring the reaction that generates heat.”
Note that the reference above does not appear to be saying that a system would be generating heat from nothing indefinitely. The point is that the system responds with enough heat to limit the imposed change in temperature to the extent possible.
Then, by the same kind of process, such an equilibrium system would respond to an *increase* in temperature by attempting to *limit*the temperature *rise* as well!
If Le Chatelier holds true, it would seem that there’s no good reason why a presumed temperature forcing would be enhanced, boosted, exaggerated, positive feedbacked, etc.? I mean, all effects ought to be folded into the initial temperature estimate in the first place, and no fair doing an extra step of “mutual reaction of quantities” to boost that up?
We can just view the paleoclimate record and see thar CO2 at levels far higher than today has never induced any “runaway” temperature response, and that 10 times as much as is in the atmosphere now could not prevent climate from plunging from “hot house” to “ice house” conditions that lasted MILLIONS of years to establish (1) CO2 doesn’t “drive” temperature; and (2) “ECS” of CO2 increases is indistinguishable from ZERO.
There is a complication to the feedback issue with CO2 doubling that you might appreciate. There is a saturation effect with increasing CO2 concentration. In essence every CO2 molecule added to the atmosphere has less heating effect than the previous molecule.
This means there is a time factor that should be considered during the concentration doubling. Assuming the concentration is increasing uniformly, a change of say 100ppm at the start of the doubling will result in a greater change in climate forcing than the same change in concentration at the end of the doubling. Therefore the temperature change as the CO2 concentration increases will not be linear in time and neither will any feedback resulting from the change.
David, you have some interesting thoughts there, to which I’ll make two comments.
The first is that while Monckton does try to get the big picture simply, he made a mistake in assuming that one of his parameters was constant enough for a small change over time not to matter, and I showed that because of his large scale Kelvin outlook, a very small change made a significant change to sensitivity. Please see the link I posted in my comment a few minutes ago.
The second is about non-linearity. I looked into this in 2018 and found that it was important to concentrate on radiative fluxes, which can be added, rather than temperatures, which cannot. This led me to a 4th degree (so non-linear, and because of Stefan’s law) implicit equation for temperature, and a sensitivity dependent on the gradient of water-associated (ice cover, vapour) feedbacks over time. I was able to use data from a paper by Ramanathan & Inamdar to estimate that feedback, and arrived at sensitivity ~ 2.1K. In the end, the (in my view admirable) non-linear theory leads to an estimate which does just depend on local linearity.
However, 3 journals have rejected my paper : – (. I have been doing other stuff and not looked at it for 6 months.
Rich
As far as saying we should just add radiative fluxes, or radiative power flow, and never add temperatures, that might make some sense, if we were really adding significant power to the *total* earth system, from outside. So there’d be more radiant power coming into cloud tops, oceans, land surfaces and all — you’d add some real power in, and try to see what comes out of that. Turn up the sun, someone!
At the same time, if the sun as such is more or less constant, and we are looking at temperature adjustments within the earth system, it is not obvious to me why temperatures as such shouldn’t be added, or adjusted up and down, subtracted where appropriate, etc? Maybe energy conservation would tend to flatten or attenuate any feedback adjustments, since there’s a limited flow of energy to work with, but that’s not the same as saying that the appropriate functions would fall down and not work, so somehow failing to add any certain temperature?
FWIW, as far as the CO2 doubling sensitivity you mention, that’s pretty compatible with the easy calculation for the next ’60 to 70 years’ that I roughed out earlier.
I basically guessed at a doubling of CO2 occurring in the time frame 1850 to year 2090 or so, and your number of 2.1 degrees C for the result of that is quite close to the 2 degrees total that I roughly estimated there. That’s all hypothetically guessing that CO2 is the ‘valve’ for temperature that traditional climatists claim it to be, of course.
Continuing on here a bit, someone remind me why, even if conventional theory were right, there seems to be this fear that the CO2 fraction would double suddenly, with some tremendous fuel burning release, to double or even just “partially” double the CO2 fraction, within a short enough time period for this to pose an unmanageable threat? This would clearly take a lot of input (input that the earth system would then somehow refuse to absorb to any extent) to make an alarm, or even make a dent in the inertia of the whole situation.
I suppose that maybe it’s just too much fun to make up stories about accelerations, feedbacks and tipping points — storytelling about doomsday is just so good..
“it is not obvious to me why temperatures as such shouldn’t be added, or adjusted up and down, subtracted where appropriate, etc?”
Temperatures don’t really add. They really don’t tell you much about heat flow since they are only one piece of the puzzle. Using temps as a proxy for heat flow is really not very accurate or appropriate. The old PV = nrT depends on more than just T. Specific heat and mass are just as important as T.
Temperature doesn’t tell you much about latent heat either but it is an important part of the engine that is the biosphere.
“Attribution can mean a merely mental act, an act that has no physical consequence.”
— I almost stopped reading after this bit of nonsense.
Hi Joe, please note that I was probably the first on WUWT to refute Monckton’s theory, using his own mathematics rather than anything independent, in 2018 – see https://wattsupwiththat.com/2018/08/21/temperature-tampering-temper-tantrums/#comment-2440661 and some other comments by me downthread of that.
Rich
Yes, that did seem to go to the heart of the matter. But it does seem to me that readers saw the problem back when WUWT first started promoting Lord Monckton’s theory. Reader Frank comes to mind, but I know there were others.
Oh, I should also mention that just over a week after the comment you just cited I submitted a proposed head post employing graphs like those above to refute Lord Monckton’s theory, but WUWT wouldn’t run it.
Well that’s a shame (and I know the feeling). But at least WUWT published it this time! And it’s good to keep that coffin nailed down, to keep climate sceptics on the high moral and scientific ground.
Re Frank’s refutation, it is admirable, but open to LM saying “that’s all very well but it doesn’t refute my mathematics”. It took me a while to spot the flaw in those, but I did, using only his own maths. For new readers, a summary is that LM claimed that a parameter was near constant and that a small variation would not matter. That would have been true if he had been working in a small range of numbers, but by working over a large range the multiplier of that small variation became very significant, increasing sensitivity from 1.1K to around 1.7K.
As sort of a coda to the discussion I’ll make a comment about the length of the head post. I’ll set aside the fact that it’s shorter than the one in which Lord Monckton introduced his theory, and I’ll focus on the following comment by Mr. Blenkinsop, which gets things backwards.
No, I didn’t “redo” it at all; I quoted Lord Monckton’s exact words and calculations.
Yes, the rule that Lord Monckton’s “corrections” actually apply, i.e., ECS = RCS × E/R, is simple. But the head post is long (although, again, not as long as Lord Monckton’s) because it deals with the many ways in which Lord Monckton has attempted to evade that simplicity. He needs to evade the fact that he is indeed applying that simple rule, because his “proof” is based on the contention feedback theory requires his corrections, whereas it actually imposes no such rule.
He says that, unlike others who have concluded that ECS is low, he can actually prove it. The proof, he says, is based on a feedback law obtained from control-systems theory. The “corrections” by which he’s illustrated the application of that law always take the following form:
ECS = RCS × E/R,
where RCS is the equilibrium-temperature change that doubling carbon-dioxide concentration would cause if there were no feedback, E is the absolute equilibrium temperature under the conditions that prevailed in, say, 1850, and R is what that temperature would have been in the absence of feedback. Since according to Lord Monckton E/R doesn’t greatly exceed unity, ECS doesn’t greatly exceed the RCS value, which by all accounts is modest: feedback law requires ECS to be low.
In other words the “correction” he performs imposes the requirement that the ratio of temperature change to what it would have been without feedback equal the ratio of the absolute temperature to what it would have been without feedback:
ECS/RCS = E/R.
What is the purported feedback law that requires such a “correction”? Well, Lord Monckton looks upon R and E as the equilibrium stimulus and response of a feedback system whose open-loop gain is unity: the “stimulus” is what the response would have been in the absence of feedback. This means that RCS becomes a stimulus change ΔR, ECS becomes the resultant response change ΔE, and the ratio of response change to stimulus change must equal the ratio of entire response to entire stimulus.
But that relationship prevails in general only if the ratio is a constant k independent of E and R, i.e., only if
E = kR.
In other words, the purported feedback law would appear to be that in a feedback system the response E must be linearly proportional to the stimulus R. Given that in Lord Monckton’s framework the “stimulus” is what the response would have been without feedback, the law becomes the requirement that the response be linearly proportional to what it would have been without feedback.
Logically, that’s the essence of Lord Monckton’s purported proof: feedback law requires that the response of a unity-open-loop-gain feedback system must be linearly proportional to what it would have without feedback, so ECS = RCS × E/R. And, since RCS is modest and E/R doesn’t much exceed unity, ECS has to be low. QED.
The problem is that there’s no such feedback law, and the head post is long because it deals with four years of Lord Monckton’s attempts to evade the logical consequences of that fact.