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Radiative Balance, Feedback, and Runaway Warming
Posted on 26 February 2012 by Chris ColoseSkeptical Science has previously discussed the topic of feedbacks and why the existence of positive feedbacks (i.e., those feedbacks that amplify a forcing) do not necessarily lead to runaway warming, or even to an inherently "unstable" climate system. I also wrote on it at RealClimate (and Pt. 2). This was brought up again in Lord Christopher Monckton's response to SkepticalScience, where he asserted:
"First, precisely because the climate has proven temperature-stable, we may legitimately infer that major amplifications or attenuations caused by feedbacks have simply not been occurring...A climate subject to the very strongly net-positive feedbacks imagined by the IPCC simply would not have remained as stable as it has."
I wanted to revisit the subject in order to take a different approach on the subject of positive feedbacks. This involves the relationship between Earth's surface temperature and outgoing infrared radiation (the energy Earth emits to space). Determining how the outgoing longwave radiation (OLR) depends on surface temperature and greenhouse content is a fundamental determinant to any planetary climate.
I'll begin with very trivial, ideal cases, and then slightly build up in complexity in order to relate the problem to climate sensitivity. By the end, it should be clear why positive feedbacks can exist that inflate climate sensitivity but do not necessarily call for a runaway warming case. We'll also see a scenario, commonly discussed by planetary scientists, in which it does lead to a runaway.
First, we begin with the simplest case in which the Earth has no atmosphere and essentially acts as a perfect radiator. In this case, the outgoing radiation is given by the Stefan-Boltzmann equation OLR=σT4. T is temperature. σ is a constant, so the equation means that the outgoing radiation grows rapidly with temperature, (to the power of four) as shown below.
Figure 1: Plot of OLR vs. Surface temperature for a perfect blackbody
In the next case, suppose that we add some CO2 to the atmosphere (400 ppm). The atmosphere here is completely dry (and therefore no water vapor feedback). In this example, the addition of CO2 will reduce the OLR for any given temperature, since the atmosphere absorbs some of the exiting energy. This is displayed with the red curve in Figure 2 (the black curve is from above for reference).
Figure 2: Relationship between OLR and surface temperature for a blackbody (black curve) and with 400 ppm CO2 (red curve). The horizontal line is the absorbed solar radiation.
Also plotted in Figure 2 is a horizontal line at 240 W/m2, which corresponds to the amount of solar energy that Earth absorbs. In equilibrium, the Earth receives as much solar energy as it does emit infrared radiation. Therefore, in the above plot, the points at which the horizontal line intersect the black/red lines will correspond to the equilibrium climates in this model. Note that the red line makes this intersection at a higher surface temperature, which is the greenhouse effect.
Now let's step up the complexity a bit. We'll throw in some water vapor into the model, but not just a fixed amount of water vapor. This time, we'll also let the water vapor concentration increase as temperature increases. Water vapor is a good greenhouse gas, so now the infrared absorption grows with temperature. This is the water vapor feedback. The blue line in the next figure is the OLR for a planet with the same 400 ppm CO2, in addition to this operating feedback.
Figure 3: Relationship between OLR and surface temperature, as above, but with a constant relative humidity atmosphere (blue line, implying increasing water vapor with temperature)
In this figure, we see that the OLR does not depend very much on the water vapor at low temperatures. This makes sense, because at temperatures this cold (such as during a snowball Earth), there is so little water vapor in the air. However, at temperatures similar to the modern global mean and warmer, the OLR drops tremendously and the the T4 dependence instead becomes much flatter. We'll get a more clear picture of that means for climate sensitivity in the next diagram.
In the next diagram, I've removed the red curve for convenience. But I've added two horizontal lines this time. You can think of this as two possible values for the incoming solar radiation.
Figure 4: OLR vs. surface temperature for a blackbody (black curve) and an atmosphere with CO2 and a water vapor feedback (blue curve). The horizontal lines give two values for the absorbed incoming solar radiation, and the colored shapes give possible equilibrium points. On the trajectory where water vapor exists, sensitivity is enhanced because the temperature difference between the two red circles (as sunlight goes up) is greater than the difference between the two blue squares.
To interpret Figure 4, suppose that we increase the amount of sunlight that the Earth gets, which means we jump from the red to the green line in the above figure. If the Earth were a blackbody (black curve) then the temperature change that results from this would just be the difference between the values at the two blue squares. However, in a world with a water vapor feedback, the temperature difference is given by the distance between the two red circles. We can infer from this that water vapor has increased climate sensitivity, yet it did not cause a runaway warming effect.
Now let's consider one more case. Notice in the previous diagram that at very high temperatures, the OLR starts to flatten out, and indeed eventually can become almost flat. This is due to the rapid increase in water vapor (and infrared absorption) as temperature goes up. But suppose we pump up the amount of sunlight that the Earth gets to much higher values than in the last figure. This new value is shown by the horizontal green line in the figure below.
Figure 5: As above, but the green line corresponds to higher incoming solar radiation.
Once again, if we follow the black curve (with no atmosphere), then we get an expected increase in temperature as the amount of sunlight goes up. But if we follow the blue curve (the system with an operating water vapor feedback), then something strange happens.
At some point the OLR becomes so flat, that it can never increase enough to match the incoming sunlight. In this case, it actually becomes impossible to establish a radiative equilibrium scenario, and the result is a runaway greenhouse. This is the same phenomenon planetary scientists talk about in connection with the possible evolution of Venus or exoplanets outside our solar system. The system will only be able to come back to radiative equilibrium once the rapid increase of water vapor mass with temperature ceases, which in extreme cases may not be until the whole ocean is evaporated.
From these figures, we can readily see the fallacy in "positive feedbacks imply instability" type arguments. There is in fact a negative feedback that always tends to win out in the modern climate. This is the increase in planetary radiation emitted to space as temperature goes up. Positive longwave radiation feedbacks only weaken the efficiency at which that restoring effect operates. Instead of the OLR depending on T4, it might depend on T3.9, or maybe even T3 at higher temperatures; eventually the OLR becomes independent of the surface temperature altogether. I haven't discussed shortwave feedbacks, such as the decrease in albedo as sea ice retreats. That only raises the position of the horizontal lines slightly, allowing for a warmer equilibrium point, but in no way compromises the argument.
In fact, the same sort of argument can be applied if we let the albedo vary with temperature (and so the absorbed solar radiation is no longer given by a horizontal line). The opposite extreme, a snowball Earth, can then be thought of as a competition between the decreased longwave radiation to space as the planet cools, and the increased reflection as the planet brightens (when the ice line is advancing toward the equator). As with a runaway greenhouse, it's not inevitable that this occurs, as is evident from times in Earth's history when ice advanced but did not reach the equator.
As a final note, it's worth mentioning that it is virtually impossible to trigger a true runaway greenhouse in the modern day by any practical means, at least in the sense that planetary scientists use the word to describe the loss of any liquid water on a planet. The most realistic fate for Earth entering a runaway is to wait a couple billion years for the sun to increase its brightness enough, such that Earth receives more sunlight than the aforementioned outgoing radiation limit that occurs in moist atmospheres. None of this means that climate sensitivity cannot be relatively high however.
Note: Except for the first graph, all computations here were done using the NCAR CCM radiation module embedded within the Python Interface for Ray Pierrehumbert's supplementary online material to the textbook "Principles of Planetary Climate." The lapse rate feedback is included as an adjustment to the moist adiabat. I've assumed near-saturated conditions are maintained (constant 100% relative humidity) with temperature, although the argument is qualitatively similar with lesser RH values.
This post has been adapted into the Advanced rebuttal to "Positive feedback means runaway warming"
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The browser didn't show me #83 until after submitting #84 (in rep to #82).
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It seems the webserver garbled the < I had used in comment #84.
I'll repeat a large paragraph near the top:
I accepted the hindcasting was horrible before 1850. My comment was that no attempt was made to find a "trend line" going back beyond 1850. The model states essentially 1850 < t < 2000 and 2000 < t < 2100 iirc. To hindcast further is interesting but void. The trends are clearly very important to approaching the actual temperature values and were not done. Reusing the linear trend (or had you used the linear and quadratic) as you do is interesting but void. The true older trends likely represent very long term cycles or no real "cycles" at all. [If the analysis were to be extended further, you would probably want to use a large basis set (sinusoids and maybe even polynomials, wavelets, etc) and not just two "trend" curves.] Anyway, without the longer analysis, the short-cycle analysis doesn't become void, but, yes, further back hindcasting will almost surely fail.
Now, the short-cycle ....
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Can the Scafetta comments (#82-#86 and this one) be moved over with a link back to this thread for reference purposes?
I really wasn't interested in analyzing that topic here (or now) and apparently neither is KR.
FWIW, I like the gist of this comment http://www.skepticalscience.com/news.php?n=1293#75633 and found KR's http://www.skepticalscience.com/news.php?n=1293#75634 informative.
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Jose_X - I have replied here.
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I noticed a piece at the beginning of #66 was snipped. "Ricardo, (-snip-)". It's probably a good thing that was snipped although no insult was intended.
Here is a translation of what I had written.
"Ricardo, I was going to state at the top of that comment that Huffman appears to have a lot of anger towards the climate science community."
The intention of that line above would have been to warn anyone who went to read that link not to get distracted with the snide remarks (and outright insults) against climate science that pepper the website; however, I did opt not to forewarn anyone when I provided the link, and then Ricardo apparently found the link offensive and made it clear he did not like/trust the person.
Of course, I was not asking anyone to like or trust the person. As I already explained, I had offered the link for reference purposes to the question I had about the GHE on Venus.
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Ricardo 67>> In the real case, use the adiabatic lapse rate, the emission altitude from the effective radiation temperature and extrapolate back to the surface.
I do thank you for the advice even though in this case I already knew what you stated, but the problem is that if we are going to test GHE vs no such effect I don't think measuring the lapse rate is acceptable since we only have one Venus like planet to measure (so we can't measure the w/GHE and also the w/o GHE cases).
The idea would be to derive the lapse rate for the GHE and for the non-GHE cases and compare those two to each other (and while we are at it, compare the GHE case to Venus measurements).
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Jose_X
we already talked about the no-GHE case and you replied that it was not your interest ("My second scenario is not 100% N2 (which is this simple case you answered)").
Keeping in mind that we're talking about a rather crude aproximation, if you have a not too low absorbtion the lapse rate is not determined by the exact amount of greenhouse gas absorption, it's determined by specific heat and gravity. Where absorption matters is in the optical thickness as function of height needed to determine where to start extrapolating backward to the surface.
You may easily understand that it's not by chance or other weird reasons that the temperatures in Venus and Earth atmospheres are similar for equivalent pressure levels. It's not that "it seems to cast some doubt to what all of that CO2 is doing."
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GC - why would you give time to such astrology when there is perfectly good physical explanation for climate? Scafetta has another problem - how to explain why the known physical properties of GHGs do NOT affect climate, given the observed effects on DLR.
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Ricardo, currently a moderator (JH) believes I am "meandering". I asked for clearer guidelines on what to comment and what not to comment, eg, so I can avoid this "meandering". http://www.skepticalscience.com/news.php?n=1293#76064 I did not major in communications, that's for sure. And it does bother me not to come through clearly.
To keep this fairly short, thanks for your information (the optical thickness part). I still think there is an apparent coincidence not yet covered on the temperature-pressure near matchup. [I would have to calculate optical thickness height to the lower .7 albedo flux at TOA and verify that this Venus lapse rate line sort of overlaps the similar slope line on earth by the time the pressures line up.]
And the "non-GHE" case was not of 100% N2 with absolutely no ghg (I should have been clearer) but of using very low ghg % such as we find on earth. The 0 GHE case is trivial, as you pointed out. Sorry for the confusion.
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@ Jose_X #68
I try to give some answers.
1) Atmosphere 100%N2
The atmosphere is perfectly transparent and so isothermal: that’s, Ts = Tt = Tef where ‘s’ is surface, ‘t’ is TOA and ‘ef’ is effective.
2)Let’s add CO2 as 300 ppm as for Earth
The balance of radiative power is (missing the constants)
xTt^4 + (1-x)Ts^4 = Tef^4
Tt/Ts = (Pt/Ps)^(R/Cp)
Ht = (Ts-Tt)Cp/g
where ‘x’ is the % of radiation in the CO2 bandwidth, ‘(1-x)’ the remaining radiation in all the spectrum, ‘P’, ‘R’, ‘Cp’ are well known by thermodynamics, ‘Ht’ is the eighth above the ground where P = 0.2 bar, ‘g’ is the gravity.
The troposphere, cooled at the top and warmed at the bottom, becomes adiatically convective. Given x, the system is closed. If x << 1, then is Ts = (1+x/4)Tef, Tt/Ts = (0.2/90)^(299/1043) = 0.287, Ht = (1+x/4)(1-0.287)(1043/8.87)Tef/1000 = 0.0838(1-x/4)Tef kilometers.
Assuming x=0.04, you have Ts = 1.01Tef, Tt = 0.29Tef, Ht = 0.082Tef. Notice that the mean temp passes from Tef to (Ts+Tt)/2 = 0.65Tef.
If Tef = 240 K, then Ts = 242.4 K, Tt = 69.6 K, Ht = 15.6 Km, all more smaller than the real ones.
So, adding CO2 you get a small GH effect at the ground and a strong cooling for the whole troposphere. The sole CO2 isn’t enough.
3) Clouds
If there is a cloud layer at height Hc = aHt, with 0 ≤ a ≤ 1, then, the system above becomes
xTt^4 + (1-x)Tc^4 = Tef^4
Tt/Ts = (Pt/Ps)^(R/Cp)
Tc = Ts-a(Ts-Tt)
Ht = (Ts-Tt)Cp/g
Also, given x and a, the system is closed. Assuming the same values than above, you get
Tc = 242.4
Ts = 242.4/(1-0.713a)
Tt = 0.287Ts
If a = 0.94, then, Ts = 735 K, Tt = 211 K, Ht = 61.6 Km. Very close to real values.
Thus, the surface temperature is affected by the lapse rate caused by the CO2 and especially by the height of balance of the clouds liquid droplets, where their weight equals the viscosity of upwelling flow.
It's all a team effort between fluid dynamics and radiative transfer.
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@Michele #94, thanks for the details. I'll look at it carefully later.
@Chris and anyone else, I want to address the observations I posted @#41 contrasting feedback in engineering systems with climate feedback analysis. I have now had time to read over half of Roe09 and key parts of a feedback/controls book I have. This update will partially clarify and/or correct some of my earlier comments (mostly comments #30 and 36). If double-checked, the contents of this comment may be useful to a new article addressing misconceptions an engineer might have.
Engineering view: The main idea is to cheaply add feedback to improve the response of an existing plant/process without having to remake the costly plant itself. The main plant/process block is sampled to see how far a signal lies from the reference value ("negative" feedback describes this difference calculation.. the "how far") and have this difference define the driving force (eg, the amount of current applied to a heating coil in the plant depends on how far the measured signal is from the desired value).
Isolated blocks: I had wondered if the climate system analysis relied on *isolated* blocks, which is a principle justifying the (Laplace Transform based) transfer function math used in traditional feedback analysis. The answer is that this isolation can be created through careful modeling used to describe each block, including the existence of a buffering mechanism across adjacent blocks; an engineer/scientist can use transfer function analysis incorrectly if on a model that couples across blocks strongly or instead correctly if on one that allows the blocks to be accurately treated independently. Although Roe09 (up to page 11) did not detail any model frequently used as a feedback block, it's not too hard to imagine that a computer model subblock would rely on one or more inputs, like sampled temperature values, to arrive at an effect/output (like increase in temperature or increase in radiative forcing value) that are passed on without any immediate "back-coupling" effect, affecting the next pass through that same block and its equations only indirectly via the well-defined high-level input mechanism in a subsequent algorithmic cycle. For example, the engineer deals with automatic sensors that measure temperature or other signals in the main block without destroying or changing such signals. Meanwhile, the climate scientists also deals with similar measurements (if at different time scales and using manual intervention) that themselves also don't impact the measured condition of the climate to any significant extent and can then be used to derive an accurate result in another submodule (eg, in an ocean effects model). So there is no problem here. Yes, a series of climate equations that would link together tightly all the earth components cannot be spliced down the middle arbitrarily for analysis, but a model based on submodules designed to hopefully fairly accurately model parts of the climate and then combine the results into a whole coherently and accurately can in fact be analyzed across those module points. Again, the climate scenario poses no inherent problems here.
Engineers and climate scientists use different diagram structures and meanings of terms (explaining negative/positive feedback and runaway confusion):
A) The engineering system's "negative feedback" describes a key block model junction in the block diagram and represents the subtraction of the reference signal minus the result of a sensor measurement (after this measurement has been translated into a form compatible with the reference signal). This is where the "negative" comes from. This difference is then modified to suitable form and size and used to drive the plant's related controlled parameter. We note specifically that (a) a negative feedback value can lead to (b) a same sign (or opposite sign) driving force whose size likely has been diminished (or potentially augmented if the system is unstable) and can certainly be a positive value (eg, the new slightly lower "positive" current passing through heating coils). The differencing is highlighted as "negative feedback" while the sign and other features of the applied plant signal are not thus highlighted. This highlight makes sense for the primary engineering problem at hand, to tame a plant parameter in order to give improved performance of some sort (and avoiding instabilities). Smaller positive feedbacks might exist elsewhere in the diagram. What you generally don't want is for this primary differencing to instead end up being effectively an addition or otherwise leading to unstable runaway conditions.
B) In the climate system, the focus is reversed. The differencing against the reference signal does essentially occur but is transparent and implicit inside most (or all) feedback submodules (ie, is not a focal point of the analysis) while the sign value of the net changes made to the main signal (eg, temperature or radiative forcing increase or decrease) is the focus and defines the "positive" or "negative" feedback attribute. To repeat, we have this same exact negative effect and corresponding potentially positive driving value we see in engineered systems, but the differencing is not modeled at a key block junction while the focus shifts instead to the sign of the contribution the feedback path makes to the reference module/parameter.
One example of the hidden differencing in climate analysis would be the subtraction within a submodule's heat equation calculations on two temperature values (a delta step).
Three examples of the unimportance (to the engineer) of the final sign of the contribution made from a particular feedback path to the driving signal in the engineering problem are (a) a heating coil works the same regardless of the direction of electron flow, (b) alotting piecemeal contributions from different feedback paths may be impossible to do accurately given the time scales in effect and lack of measurement capabilities, and (c) the systems are purposely engineered to specs that adhere decently to understood models so there are usually more interesting and important questions than details of transient responses already understood well from derived model solutions.
So, the engineer and climate scientists are usually talking about different "positive" and "negative" feedback effects. When Roe09 says on page 6, "note also that the not-uncommon misconception that a positive feedback automatically implies a runaway feedback is not true," he is sort of comparing apples to oranges to the extent the "misconception" comes from engineers' discussion of negative vs positive feedback effects. The engineers would be having a different discussion than the positive/negative feedback discussion two climate scientists might have. Of course, this isn't to say two engineers might not at times find it worthwhile to analyze the same sort of positive/negative feedback effect climate scientists discuss (the sign of the contribution to the signal), but that would not be where the "misconception" comes from. [In my opinion.. based on my recent "study" of this point. blah blah.]
A few more notes:
Diagrams would have made this discussion easier to follow.. sorry.
on runaway: Many process/plant reference blocks likely already model an automatic regulating mechanism that, akin to Stefan-Boltzmann, naturally counters rises in the signal (temperature) and fights runaway to some extent; however, for (eg) electronic circuits (effects can happen very fast), this natural counter effect (like resistance) might be very weak and can possibly be overpowered rather easily and quickly by the driving forces (like transistors). Meanwhile, digital circuits (which function as perfect mathematics abstractions) may not even have a natural block against runaway effect unless added explicitly as digital "code".
on frequency/Laplace: This model doesn't appear to be used by climate modelers since the main questions are different than what an engineer faces. The "transfer functions" I saw on Roe09 were mostly just gain values: (a) they did not have a lag/lead component as you'd see with frequency analysis or specify the gains as a function of frequency; (b) multiplication in frequency domain is not needed, as the convolution in time domain is effectively performed within each submodules; and (c) the combination of submodule transfer functions include only real-valued gains independent of "s", so I believe the math works out fine. [may think about this last point more later]
Climate view: Obviously (today), the main difference between the climate system and an engineering system is that we are merely analyzing the climate and not trying to both analyze it and then significantly engineer an improved system response (eg, by purposely regulating up/down CO2 levels). Roe09 explains that different analyses might consider different reference systems, but probably almost always the reference system will include the no atmosphere earth Stefan-Boltzmann reaction.
..vs engineered system: The time scales are rather different. Our confidence in the models are also rather different. Manual and automatic roles are rather different.
Sorry this comment may be hard to understand, but it might help some determined soul.. who might be able to leverage parts of it to help others struggling with the feedback issue.
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Michele #94, it took me a while to read enough wikipedia thermodynamics to acquire a fair amount of (first approximation) confidence in your 3 primary equations; however, there were details I could not accept (as covered below). This comment is only on part 2 (no clouds).
First, I'll briefly note my interpretation of the 3 equations.
>> xTt^4 + (1-x)Ts^4 = Tef^4
The power .jkljkljkljk [I'll finish this answer later]
>> Tt/Ts = (Pt/Ps)^(R/Cp)
Assumption: the temperature up and down the atmosphere is the result we'd get if there was no vertical convection. I think this is the hydrostatic equilibrium, which can be described (I think) as: the temperature at all points exactly match the potential temperature of a single reference temperature, so I think this means the entire atmosphere in this region would be at the same temperature if we factor out the lapse rate ... or at least that is the assumption for the two points "surface" and "toa".
>> Ht = (Ts-Tt)Cp/g
Assumption: The hydrostatic equilibrium applies. This is just an application of the lapse rate.
>> P=.2 bar
Why? I'll assume for the moment that it is because the atmosphere above this point (@300ppm,Ht,Pt) absorbs radiation below some threshold value. Clearer insight into this would be welcomed. I expected appeal to data (like Hottel CO2 absorption) or to Beer Lambert.
>> xTt^4 + (1-x)Ts^4 = Tef^4
>> ‘x’ is the % of radiation in the CO2 bandwidth, ‘(1-x)’ the remaining radiation in all the spectrum
>> x=.04
What is x? Why .04? Doesn't CO2 absorb a much larger part of the spectrum?
I would think x, as you define it (but not as used in the Stefan-Boltzmann based equation) is closer to .2 based on Hottel measurements and probably/hopefully agreeing with analysis of line spectra for CO2.
And I heard that satellites measurements indicate that close to half of the IR radiation from the planet reaching the satellites is in the CO2 range, suggesting that maybe that x value should be closer to .5 as used in the equation.
In any case, where is the derivation of x or where does its measurement come from?
>> Tt/Ts = (0.2/90)^(299/1043) = 0.287
That math comes to something different: 0.1735 .. as can be easily verified by copy/pasting into google search bar. The 299, 1043, and 90 are in the right ball park (and I already wondered about the .2).
>> If x << 1, then is Ts = (1+x/4)Tef
Can you give me more insight into this simplification (we are dealing with almost insignificant digits perhaps, but I am curious where the approximation comes from)?
I don't see why we need an approximation since we have 2 equations and 2 unknowns (Tt, Ts), and one equation is linear so one variable can easily be eliminated for substitution.
Given Pt=.2, Ps=90, R=299, Cp=1043, and using your Tt/Ts=...=.287 which might be wrong, we get for the first equation:
x(.287*Ts)^4 + (1-x)Ts^4 = Tef^4
or, after substituting x=.04 and Tef=240:
Ts = (240^4/(.04*.287^4+.96))^.25 = 242.4 (as you got).
So using your .287 (instead of .1735), I get the same thing you got but without having to invoke the alleged approximation.
>> Ht = (1+x/4)(1-0.287)(1043/8.87)Tef/1000 = 0.0838(1-x/4)Tef kilometers.
You did not pass on the (1+x/4) .. you changed it to (1-x/4).
Ht = 0.0838(1+x/4)Tef
>> Ht = 0.082Tef
With the above fix, we get
Ht = 0.0846Tef
>> Ht = 0.082Tef ..= 15.6 Km
240 * .082 = 19.68 Km
However, after the fix to the equation,
Ht = 0.0846Tef = 20.31 Km
This is the same thing we get without having to use the approximation.
Ht= (Ts-Tt)*Cp/g = (242.4-69.6)*1043/8.87 = 20.32 Km
although this does rely on the .287 ratio that might be wrong.
All of the above rely on the x=.04 which appears wrong based on how I interpret your definition and/or use in the equation.
If you get back to this thread, can you try to answer some of the above, as I think the model is probably decent but there appear to be mistakes?
Thanks again for the detailed candidate solution to Venus with 300ppm CO2 (and presumably the rest of the atmosphere along similar percentages as Earth).
I won't deal with "3) Clouds" right now since you reused x=.04; however, the model you used there is also interesting, so I will study it even if you don't return to the thread.
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Chris,
Nice hypotheical explanation, but ultimately in the real climate you can't arbitarily separate the water vapor feedback from that of clouds and the latent heat of evaporation. All three of these physical processes are interconnected, and act together in a highly dynamic manner to maintain the current energy balance from the forcing of the Sun.
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Hi Chris-
It's a very illuminating post, but a very simplified model compared to the earth.
Methane has chemical reducing effects as well as greenhouse effects. According to Isaksen, these chemical effects (which can be very strongly non-linear) can lead to very strong positive feedback, from the production of ozone, secondary CO2, stratospheric water vapor, and increased atmospheric lifetime of methane due to exhaustion of the hydroxyl radical oxidation mechanism.
It would be interesting (and probably necessary) to apply your modeling to Isaksen's atmospheric chemistry change results, to come to any conclusions about true runaway greenhouse effects, I think.
I think Isaksen and his team have uncovered the explanation for the severity of some past mass extinction events - the atmospheric chemistry effects of methane. These chemical effects change the chemical composition of the atmosphere, in the direction of a primordial reducing atmosphere, with a stronger greenhouse effect.
One such probable severe near runaway greenhouse event, a mere 250 million years ago (only a few percent of the age of the earth), the End Permian, killed on the order of 90% of species then existing. And the sun, according to the standard model of stellar evolution, is a couple of percent hotter now.
Strong atmospheric chemistry feedback to climate warming from Arctic methane emissions
The magnitude and feedbacks of future methane release from the Arctic region are unknown. Despite limited documentation of potential future releases associated with
thawing permafrost and degassing methane hydrates, the large potential for future methane releases calls for improved understanding of the interaction of a changing climate with processes in the Arctic and chemical feedbacks in the atmosphere. Here we apply a “state of the art” atmospheric chemistry transport model to show that large emissions of CH4 would likely have an unexpectedly large impact on the chemical composition of the atmosphere and on radiative forcing (RF). The indirect contribution to RF of additional methane emission is particularly important. It is shown that if global methane emissions were to increase by factors of 2.5 and 5.2 above current emissions, the indirect contributions to RF would be about 250% and 400%, respectively, of the RF that can be attributed to directly emitted methane alone. Assuming several hypothetical scenarios of CH4 release associated with permafrost thaw, shallow marine hydrate degassing, and submarine landslides, we find a strong positive feedback on RF through atmospheric chemistry. In particular, the impact of CH4 is enhanced through increase of its lifetime, and of atmospheric abundances of ozone, stratospheric water vapor, and CO2 as a result of atmospheric chemical processes. Despite uncertainties in emission scenarios, our results provide a better understanding of the feedbacks in the atmospheric chemistry that would amplify climate warming.
Hansen's runaway greenhouse still seems plausible to me. If there had not been past mass extinctions apparently due to massive releases of methane from the hydrates, a true runaway greenhouse would look unlikely.
As it is, with methane release from the hydrates (and probable atmospheric chemistry effects) looking like a plausible explanation for several past mass extinction events, a true runaway greenhouse still looks quite possible to me.
The sun is hotter, now.
Let your modelling approach the complexity of the major feedbacks present in the actual atmosphere of the earth, and I'll admit that you are entitled to make conclusions based on your modelling. At a minimum, you need curves for ozone and nitrous oxide, I think. Keep in mind that the reducing effects of methane on the oceans could plausibly produce large amounts of nitrous oxide.
As it is, you've left out the atmospheric (and oceanic) chemistry effects of methane. The atmospheric chemistry effects of methane are very likely important, and its oceanic chemistry effects may be important.
You could do us all a service by using Isaksen's paper as a guide, and including his stuff in your modelling.
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Radiative balance is on the title, yet, nothing about it in the post. This is where IPCC is blatantly wrong: on Earth, there has to be radiative imbalance, because there is life.
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[DB] Inflammatory snipped.
[DB] Imputations of impropriety and fraud snipped. Please pay more than a passing nod to the Comments Policy of this site.
[DB] "The IPCC models suffer from confirmation bias because they assume that CO2 is responsible for most of the recent warming while ignoring the evidence that 50-80% is attributable to natural causes."
Unsupported assertion. It is incumbent upon you to now provide links to peer-reviewed articles published in reputable journals that document that the evidence you mentions both exists and that the IPCC has ignored it.
You will be held accountable for the above statement.