Guest Post by Willis Eschenbach
Well, for my sins I’ve been working on a paper with the hope of getting it published in a journal. Now that it’s nearly done, I realized that I have the worlds’ best peer-reviewers available on WUWT. So before seeing if I can get this published, I thought I’d take advantage of you good folks for some “peer preview”, to point out to me any problems you might see with the title, format, style, data, conclusions, or any other part of the following paper. All of the graphics are in grayscale because that’s what the journals want.
Many thanks for any and all contributions.
w.
The Emergent Thermostat
Abstract
The current paradigm of climate science is that the long-term change in global temperature is given by a constant called “climate sensitivity” times the change in downwelling radiation, called “radiative forcing”. However, despite over forty years of investigation, the uncertainty of the value of climate sensitivity has only increased.1 This lack of any progress in determining the most central value in the current paradigm strongly suggests that the paradigm itself is incorrect, that it is not an accurate description of reality. Here I propose a different climate paradigm, which is that a variety of emergent climate phenomena act in concert to keep the surface temperature within tight limits. This explains the unusual thermal stability of the climate system.
Overview
Several authors have analyzed the climate system as a heat engine. Here is Reis and Bejan’s description
The earth with its solar heat input, heat rejection, and wheels of atmo- spheric and oceanic circulation, is a heat engine without shaft: its maximized (but not ideal) mechanical power output cannot be delivered to an extraterrestrial system. Instead, the earth engine is destined to dissipate through air and water friction and other irreversibilities (e.g., heat leaks across finite ∆T) all the mechanical power that it produces. It does so by ‘‘spinning in its brake’’ the fastest that it can (hence the winds and the ocean currents, which proceed along easiest routes).2
When viewed as a heat engine, one of the most unusual and generally unremarked aspects is its astounding stability. Over the 20th Century, the global average surface temperature varied by less than one kelvin. This is a variation of ± 0.2%. Given that the system rejects a variable amount of incoming energy, with the variations mostly controlled by nothing more solid than clouds, this is a most surprising degree of stability.
This in turn strongly argues for some global thermoregulatory mechanism. The stability cannot be from simple thermal inertia, because the hemispheric land temperatures vary by ~ 20K over the year, and hemispheric sea temperatures vary by ~ 5K.
Emergence
There is no generally accepted definition of emergence. In 1874 Lewes proposed the following definition: “Emergence: Theory according to which the combination of entities of a given level gives rise to a higher level entity whose properties are entirely new”.3
For the purposes of this article, I will define emergent climate phenomena functionally and by example.
Emergent climate phenomena arise spontaneously, often upon passing some thermal or other threshold. Consider the daily development of the tropical cumulus cloud field. Upon passing a temperature threshold, out of a clear sky hundreds of individual cumulus clouds can appear in a short time.
They have a time of emergence and a limited lifespan. Dust devils form spontaneously at a certain moment, persist for a while, and then dissipate and disappear.
They form a separate whole, distinct from the surroundings. Tropical thunderstorms are surrounded by clear air.
They are often mobile and move in unpredictable ways. As a result, tropical cyclones have “prediction cones” for where they might possibly go next, rather than being accurately predictable.
They are often associated with phase changes in the relevant fluids. Convective cloud emergence involves a phase change of water.
Once in existence, they can persist below the threshold necessary for their emergence. Rayleigh-Benard circulation requires a certain temperature difference to emerge, but once in existence, the circulation can persist at a smaller temperature difference.
They are flow systems far from equilibrium. As such, in accordance with the Constructal Law4, they must evolve and mutate to survive.
They are not naively predictable, as they have entirely different properties than the substrate from which they emerge. If you lived somewhere that there were never clouds, you likely would not predict that a giant white object might suddenly appear hundreds of meters above your head.
Examples of natural emergent phenomena with which we are familiar include the behavior of flocks of birds, vortices of all kinds, termite mounds, consciousness, and indeed, life itself. Familiar emergent climate phenomena include thunderstorms, tornadoes, Rayleigh-Bénard circulation of the atmosphere and ocean, clouds, cyclones, El Ninos, and dust devils.
A Simple Example
To explain how emergent phenomena thermoregulate the earth’s surface temperature, consider the lowly “dust devil”. As the sun heats a field in the summer, the change in temperature is some fairly linear function of the “forcing”, the downwelling solar radiation. This is in accord with the current paradigm. But when the hottest part of the field reaches a certain temperature with respect to the overlying atmospheric temperature, out of the clear sky a dust devil emerges. This cools the surface in several ways. First, it moves warm surface air upwards into the lower troposphere. Second, it increases sensible heat transfer, which is a roughly linear function of the air velocity over the surface. Third, it increases evaporation, which again is a roughly linear function of the surface air velocity.
At this point, the current paradigm that the change in temperature is a linear function of the change in forcing has broken down entirely. As the sunshine further irradiates the surface, instead of getting more temperature we get more dust devils. This puts a cap on the surface temperature. Note that this cap is not a function of forcing. The threshold is temperature-based, not forcing-based. As a result, it will not be affected by things like changing amounts of sunshine or variations in greenhouse gases.
A Complete Example
The heavy lifting of the thermoregulatory system, however, is not done by dust devils. It is achieved through variations in the timing and strength of the daily emergence of tropical cumulus fields and the ensuing tropical thunderstorms, particularly over the ocean. This involves the interaction of several different emergent phenomena
Here is the evolution of the day and night in the tropical ocean. The tropical ocean is where the majority of the sun’s energy enters the huge heat engine we call the climate. As a result, it is also where the major thermostatic mechanisms are located.
Figure 1. Daily emergent phenomena of the tropical ocean.
As seen in Panel “Early Morning”, at dawn, the atmosphere is stratified, with the coolest air nearest the surface. The nocturnal emergent Rayleigh-Bénard overturning of the ocean is coming to an end. The sun is free to heat the ocean. The air near the surface eddies randomly.
As the sun continues to heat the ocean, around ten or eleven o’clock in the morning a new circulation pattern emerges to replace the random atmospheric eddying. As soon as a critical temperature threshold is passed, local Rayleigh-Bénard-type circulation cells emerge everywhere. This is the first emergent transition, from random circulation to Rayleigh-Bénard circulation. These cells transport both heat and water vapor upwards.
By late morning, the Rayleigh-Bénard circulation is typically strong enough to raise the water vapor to the local lifting condensation level (LCL). At that altitude, the water vapor condenses into clouds as shown in Panel “Late Morning”.
This area-wide shift to an organized circulation pattern is not a change in feedback, nor is it related to forcing. It is a self-organized emergent phenomenon. It is threshold-based, meaning that it emerges spontaneously when a certain threshold is passed. In the wet tropics there’s plenty of water vapor, so the major variable in the threshold is the temperature. In addition, note that there are actually two distinct emergent phenomena in Panel 2—the Rayleigh-Bénard circulation which emerges prior to the cumulus formation, and which is enhanced and strengthened by the totally separate emergence of the clouds. We now have two changes of state involved as well, with evaporation from the surface and condensation and re-evaporation at altitude.
Under this new late-morning cumulus circulation regime, much less surface warming goes on. Part of the sunlight is reflected back to space, so less energy makes it into the system to begin with. Then the increasing surface wind due to the cumulus-based circulation pattern increases the evaporation, reducing the surface warming even more by moving latent heat up to the lifting condensation level.
The crucial issues here are the timing and strength of the emergence. If the ocean is a bit warmer, the new circulation regime starts earlier in the morning and it cuts down the total daily warming. On the other hand, if the ocean is cooler than usual, clear morning skies last later into the day, allowing increased warming. The system temperature is thus regulated both from overheating and excessive cooling by the time of onset of the regime change.
Consider the idea of “climate sensitivity” in this system, which is the sensitivity of surface temperature to forcing. The solar forcing is constantly increasing as the sun rises higher in the sky. In the morning before the onset of cumulus circulation, the sun comes through the clear atmosphere and rapidly warms the surface. So the thermal response is large, and the climate sensitivity is high.
After the onset of the cumulus regime, however, much of the sunlight is reflected back to space. Less sunlight remains to warm the ocean. In addition to reduced sunlight, there is increased evaporative cooling. Compared to the morning, the climate sensitivity is much lower.
So here we have two situations with very different climate sensitivities. In the early morning, climate sensitivity is high, and the temperature rises quickly with the increasing solar insolation. In the late morning, a regime change occurs to a situation with much lower climate sensitivity. Adding extra solar energy doesn’t raise the temperature anywhere near as fast as it did earlier.
At some point in the afternoon, there is a good chance that the cumulus circulation pattern is not enough to stop the continued surface temperature increase. If the temperature exceeds a certain higher threshold, as shown in Panel “Late Afternoon”, another complete regime shift takes place. The regime shift involves the spontaneous emergence of independently mobile heat engines called thunderstorms.
Thunderstorms are dual-fuel heat engines. They run on low-density air. That air rises and condenses out the moisture. The condensation releases heat that re-warms the air, which rises deep into the troposphere.
There are two ways the thunderstorms get low-density air. One is to heat the air. This is how a thunderstorm gets started, as a solar-driven phenomenon emerging from strong cumulus clouds. The sun plus GHG radiation combine to heat the surface, which then warms the air. The low-density air rises. When that circulation gets strong enough, thunderstorms start to form. Once the thunderstorm is started, the second fuel is added — water vapor. The more water vapor there is in the air, the lighter it becomes. The thunderstorm generates strong winds around its base. Evaporation is proportional to wind speed, so this greatly increases the local evaporation. This makes the air lighter and makes the air rise faster, which makes the thunderstorm stronger, which in turn increases the wind speed around the thunderstorm base. A thunderstorm is a regenerative system, much like a fire where part of the energy is used to power a bellows to make the fire burn even hotter. Once it is started, it is much harder to stop. This gives thunderstorms a unique ability that is not represented in any of the climate models. A thunderstorm is capable of driving the surface temperature well below the initiation temperature that was needed to get the thunderstorm started. It can run on into the evening, and often well into the night, on its combination of thermal and evaporation energy sources.
Thunderstorms function as heat pipes that transport warm air rapidly from the surface to the lifting condensation level where the moisture turns into clouds and rain, and from there to the upper atmosphere without interacting with the intervening greenhouse gases. The air and the energy it contains are moved to the upper troposphere hidden inside the cloud-shrouded thunderstorm tower, without being absorbed or hindered by GHGs on the way. Thunderstorms also cool the surface in a host of other ways, utilizing a combination of a standard refrigeration cycle with water as the working fluid, plus cold water returned from above, clear surrounding air allowing greater upwelling surface radiation, wind-driven evaporation, spray increasing evaporation area, albedo changes, and cold downwelling entrained air.
As with the onset of the cumulus circulation, the onset of thunderstorms occurs earlier on days when it is warmer, and it occurs later (and sometimes not at all) on days that are cooler than usual. Again, there is no way to assign an average climate sensitivity. The warmer it gets, the less each additional watt per meter warms the surface.
Once the sun sets, first the cumulus and then the thunderstorms decay and dissipate. In Panel 4, a final and again different regime emerges. The main feature of this regime is that during this time, the ocean radiates the general amount of energy that was absorbed during all of the other parts of the day.
During the nighttime, the surface is still receiving energy from the greenhouse gases. This has the effect of delaying the onset of oceanic overturning, and of reducing the rate of cooling. Note that the oceanic overturning is once again the emergent Rayleigh-Bénard circulation. Because there are fewer clouds, the ocean can radiate to space more freely. In addition, the overturning of the ocean constantly brings new water to the surface to radiate and cool. This increases the heat transfer across the interface. As with the previous thresholds, the timing of this final transition is temperature-dependent. Once a critical threshold is passed, oceanic overturning emerges. Stratification is replaced by circulation, bringing new water to radiate, cool, and sink. In this way, heat is removed, not just from the surface as during the day, but from the entire body of the upper layer of the ocean.
Predictions
A theory is only as good as its predictions. From the above theoretical considerations we can predict the following:
Prediction 1. In warm areas of the ocean, clouds will act to cool the surface, and in cold areas they will act to warm the surface. This will be most pronounced above a temperature threshold at the warmest temperatures.
Evidence validating the first prediction.
Figure 2. Scatterplot, sea surface temperature (SST) versus surface cloud radiative effect. The more negative the data the greater the cooling.
As predicted, the clouds warm the surface when it is cold and cool it when it is warm, with the effect very pronounced above about 26°C – 27°C.
Prediction 2. In the tropical ocean, again above a certain temperature threshold, thunderstorms will increase very rapidly with increasing temperature.
Evidence validating the second prediction.
Since there is always plenty of water over the tropical ocean, and plenty of sunshine to drive them, thermally driven tropical thunderstorms will be a function of little more than temperature.
Figure 3. Cloud top altitude as a proxy for deep convective thunderstorms versus sea surface temperature.
As with clouds in general, there is a clear temperature threshold at about 26°C – 27°C, with a nearly vertical increase in thunderstorms above that threshold. This puts a very strong cap on increasing temperatures.
Prediction 3. Transient decreases in solar forcing such as those from eruptions will be counteracted by increased sunshine from tropical cumulus forming later in the day and less frequently. This means that after an initial decrease, incoming solar will go above the pre-eruption baseline until the status quo ante is re-established.
Evidence validating the third prediction.
Regarding the third prediction, my theory solves the following Pinatubo puzzle from Soden et al.5
“Beginning in 1994, additional anomalies in the satellite-observations of top-of-atmosphere absorbed solar radiation become evident, which are unrelated to the Mount Pinatubo eruption and therefore not reproduced in the model simulations. These anomalies are believed to stem from decadal-scale changes in the tropical circulation over the mid to late 1990’s [see J. Chenet al., Science 295, 838 (2002); and B.A. Wielicki et al., Science 295, 841 (2002], but their veracity remains the subject of debate. If real, their absence in the model simulations implies that discrepancies between the observed and model-simulated temperature anomalies, delayed 1 to 2 years by the climate system’s thermal inertia, may occur by the mid-1990s.”
Figure 4. Soden Figure 1, with original caption
However, this is a predictable result of the emergent thermostat theory. Here is the change in lower atmospheric temperature along with the ERBS data from Soden:
Figure 5. ERBE absorbed solar energy (top panel in Figure 4) and UAH lower tropospheric temperature (TLT). Both datasets include a lowess smoothing.
As predicted by the theory, the absorbed solar energy goes above the baseline until the lower troposphere temperature returns to its pre-eruption value. At that point, the increased intake of solar energy ceases and the system is back in its steady-state condition.
Prediction 4. The “climate sensitivity”, far from being a constant, will be found to be a function of temperature.
Evidence validating the fourth prediction.
Figure 6 below shows the 1° latitude by 1° longitude gridcell by gridcell relationship between net downwelling radiation at the surface and the surface temperature.
Figure 6. Scatterplot, CERES net downwelling surface radiation (net shortwave plus longwave) versus Berkeley Earth global surface temperature. The slope of the lowess smooth at any point is the “climate sensitivity” at that temperature, in °C per watt per square metre (W/M2)
The tight correlation between the surface temperature and the downwelling radiation confirms that this is a valid long-term relationship. This is especially true given that the two variables considered are from entirely different and unrelated datasets.
Note that the “climate sensitivity” is indeed a function of temperature, and that the climate sensitivity goes negative at the highest temperatures. It is also worth noting that almost nowhere on the planet does the long-term average temperature go above 30°C. This is further evidence of the existence of strong thermoregulatory mechanisms putting an effective cap on how hot the surface gets on average.
Prediction 5. In some areas, rather than the temperature being controlled by the downwelling surface radiation, the surface radiation will be found to be controlled by the temperature.
Evidence validating the fifth prediction.
Figure 7 below shows the correlation between net downwelling surface radiation (net shortwave plus longwave) and surface temperature. As expected, over most of the land masses the correlation is positive—as the downwelling radiation increases, so does the surface temperature.
Figure 7. Correlation between monthly surface temperatures and monthly surface downwelling radiation. Seasonal variations have been removed from both datasets.
However, over large areas of the tropical ocean, the temperature and downwelling surface radiation are negatively correlated. Since decreasing downwelling radiation cannot increase the surface temperature, the only possible conclusion is that in these areas, the increasing temperature modifies the number and nature of the overlying clouds in such a way to decrease the downwelling radiation.
CONCLUSIONS
1) The current climate paradigm, which is that in the long run, changes in global surface temperature are a simple linear function of changes in forcing (downwelling radiation), is incorrect. This is indicated by the inability of researchers to narrow the uncertainty of the central value of the paradigm, “climate sensitivity”, despite forty years of investigations, millions of dollars, billions of computer cycles, and millions of work-hours being thrown at the problem. It is also demonstrated by the graphs above which show that far from being a constant, the “climate sensitivity” is a function of temperature.
2) A most curious aspect of the climate system is its astounding stability. Despite being supported at tens of degrees warmer than the moon by nothing more stable than evanescent clouds, despite volcanic eruptions, despite changes in CO2 and other GHG forcings, despite great variations in aerosols and black carbon, over the 20th Century the temperature varied by only ±0.2%.
3) This amazing stability implies and indeed requires the existence of a very strong thermoregulation system.
4) My theory is that the thermoregulation is provided by a host of interacting emergent phenomena. These include Rayleigh-Benard circulation of the ocean and the atmosphere; dust devils; tropical thermally-driven cumulus cloud fields; thunderstorms; squall lines; cyclones; tornadoes; the La Nina pump moving tropical warm water to the poles and exposing cool underlying water; and the great changes in ocean circulation involved with the Pacific Decadal Oscillation, the North Atlantic Oscillation, and other oceanic cycles.
5) This implies that temperatures are unlikely to vary greatly from their current state because of variations in CO2, volcanoes, or other changing forcings. The thresholds for the various phenomena are temperature-based, not forcing-based. So variations in forcing will not affect them much. However, it also opens up a new question—what causes slow thermal drift in thermoregulated systems?
REFERENCES
1 Knutti, R., Rugenstein, M. & Hegerl, G. Beyond equilibrium climate sensitivity. Nature Geosci 10, 727–736 (2017). https://doi.org/10.1038/ngeo3017
2 Lewes, G. H. (1874) in Emergence, Dictionnaire de la langue philosophique, Foulquié.
3 Reis, A. H., Bejan, A, Constructal theory of global circulation and climate, International Journal of Heat and Mass Transfer, Volume 49, Issues 11–12, 2006, Pages 1857-1875, https://doi.org/10.1016
4 Bejan, A, Reis, A. Heitor, Thermodynamic optimization of global circulation and climate, International Journal of Energy Research, Vol. 29, Is. 4, https://doi.org/10.1002/er.1058
5 Brian J. Soden et al., Global Cooling After the Eruption of Mount Pinatubo: A Test of Climate Feedback by Water Vapor,Science 26 Apr 2002, Vol. 296, Issue 5568, pp. 727-730, DOI: 10.1126/science.296.5568.727
Anyhow, that’s what I have to date. There are few references, because AFAIK nobody else is considering the idea that emergent phenomena act as a global thermostat. Anyone who knows of other references that might be relevant, please mention them.
Finally, any suggestions as to which journal might be willing to publish such a heretical view of climate science would be much appreciated.
My best to all, the beat goes on,
w.
As Always: I can defend my own words, but I can’t defend your interpretation of them. So if you comment, please quote the exact words you are discussing so we can all understand what you are referring to.
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4) My theory is that the thermoregulation ….
perhaps the less subjective
“Proposed hypothesis is that the thermoregulation ….”
Thanks, vuk, done.
w.
excellent.
cheers
Good read, a few thoughts to consider:
1) The emergent phenomenon you describe applies mostly to large bodies of water – landscapes may lack the necessary water or have significant interfering mountains that complicate the system you describe.
2) “As the sun continues to heat the ocean, around ten or eleven o’clock in the morning a new circulation pattern emerges to replace the random atmospheric eddying. As soon as a critical temperature threshold is passed, local Rayleigh-Bénard-type circulation cells emerge everywhere.”
I was under the impression that large-scale cloud formations occurred mostly in bands over the oceans, so again a complication that isn’t addressed. (or I am wrong)
3) There is no mention of angle of incidence other then the Sun “rising” from morning to noon – latitude also plays a big part. It seems to me that the angle that the Sunlight hits clouds (especially ice particles) would play a part in the amount of light reflected to Earth below.
4) The ocean serves to buffer temperature changes in other ways – in the morning it takes up heat and starting around noon to evening it releases extra heat. This buffering of heat is seldom ever mentioned but helps result in a more moderate climate. Rocks and soil do the same – this can lengthen the amount of time that water is being used to transport heat high up.
–
Maybe all of this is tangential to the purpose of your paper, but it would show that you considered such ideas rather than didn’t think of them.
Conclusion number five (5), specifically where you say ” or other changing forcings” is flat out wrong. You ask the question: “what causes slow thermal drift in thermoregulated systems?” which has already been answered by Milankovitch: https://earthobservatory.nasa.gov/features/Milankovitch You can see the effect in the ice core record due to the minuscule change in radiative forcing of ~0.45 W/m2
In other words Willis, you hypothesis fails to regulate the climatic effect of very small changes in TSI due to orbital variations.
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You also need a different word than “emergent” because the subject phenomena of your hypothesis have been around for millions of years, and have failed to prevent the advance and retreat of glaciers. If they “regulate” the climate, they don’t do a very good job of it.
Small changes in TSI may cause shifts in storm tracks. Over time, all that is needed is a small place (like in northern Quebec) to accumulate a few more inches of winter snow than melt in the summer. 5 inches of ice per year? Over 1000 years, you now have an expanding region of 1/2 mile high ice, which will now accumulate ice year round – because it has a surface elevation of 2000 ft, which can then more quickly reach 10,000 feet, the pressure of which spreads the ice out and south. I would argue that it would take a major emergent phenomena to melt all this, causing our brief interglacials.
Most Milankovitch cycles don’t rely on change in TSI, but in insolation due to orbital and rotational mechanics.
Jut to be clear, it is the change in orbit that causes the TSI to change.
Where did you come up with that crap, Taguchi? The total solar insolation at 65° N (where all the land is) varies from 450 W/m^2 to 550 W/m^2 over the course of the Milankovitch cycles.
And tell us Mr. Meab, when 65N increases, doesn’t 65S decrease?
Hai Taguchi-san, but it is the 450 to 550 north of 65° that causes ice formation north of 65°.
Maybe. I would argue that it is the increased local precipitation more than the subtle change in insolation which causes the ice to build up. It would not have to be much, because we are talking thousands of years to accumulate.
Fred, Very good point. There was a theory published in the 1970s that posited an ice free Arctic ocean would cause more precipitation on land, and the gradual accumulation of snow, which would eventually become glaciers.
No, Taguchi. When the orbital eccentricity elongates, the Earth spends more time near aphelion and less time at perihelion (Kepler figured this out 400 years ago). Winters in one hemisphere will be much longer and much colder and summers will be much hotter but also much *shorter*. The percent change in insolation is about 4 * eccentricity. Presently, eccentricity is about .017 so the Earth receives about 6.8% more insolation during the Southern Hemisphere summer (because the Earth is closer to the Sun during SH summer at present). The Earth’s eccentricity gets as high as .0679 so the difference between the hemisphere’s insolation will rise to about 27%. That’s huge.
The hemispheres will still be out of phase BUT insolation over land areas counts the most in warming the Earth. 2/3 of the Earth’s land area is in the Northern Hemisphere – that’s why the global average temperature actually goes up in present times during the NH summer despite the fact that the Earth is closest to the sun during the SH summer. So, when the Earth’s axial precession puts NH winter at perihelion at a time with maximum orbital eccentricity, the whole Earth cools dramatically – enough for a global glacial advance as opposed to just a NH glaciation which can happen during other Milankovitch cycle conditions.
Taguchi, the impact of the Milankovitch cycles does NOT result from the tiny change in radiative forcing that you falsely alluded to.
You are wrong Meab. When the orbit elongates, the TIME spent at the DISTANT aphelion increases. Total energy drops because it is TSI times time. The TSI increases at perihelion, but since the time drops, the amount of energy decreases. It is an unbalanced difference.
That’s what I wrote, learn to read. Quoting ” When the orbital eccentricity elongates, the Earth spends more time near aphelion and less time at perihelion (Kepler figured this out 400 years ago).”
You are pulling stuff out of your nether regions. It’s NOT the global TSI that creates glaciation, it’s the TSI over land. You know, where grounded glaciers grow. Sheesh.
WRONG
.
You post: “The total solar insolation at 65° N (where all the land is) varies from 450 W/m^2 to 550 W/m^2 over the course of the Milankovitch cycles.”
.
Ignoring what happens in the Southern Hemisphere where MORE ocean area with a lower albedo than land areas.
Let me note that Roger Taguchi is up to his usual trick here. He takes some minor point and he spins it into endless disagreement. In this case, he has people spending loads of mental energy debating minor issues regarding Milankovich, which is only very tangentially related to the subject of the post.
Let me STRONGLY recommend that you do not feed the trolls, and Roger is assuredly one of them. Me, I’ve given up answering him directly. It’s an endless, joyless mudpit.
w.
I certainly root for this to be published in the most distinguished journals in existence. Failing that, how about aiming for popularity, in household magazines, trade journals, hobby mags etcetera? THEY will not easily give this exposure, but the battle is for the heart and mind of the “common man”, so publish where the “common man” reads.
One caveat; the graphs may need some more, er, colloquial captioning for such an audience, but the information as is should be comprehensible to most folk, given a little more background. (How does a model work, and how that ‘senstivity’ thing fits into it. One or two paragraphs?)
For this particular audience, this is near perfect, far’s my limited opinion matters.
P.S. Colour them pics, then make’em move. Apparently that is how today’s kids ‘read’.
Hi Willis – Great article – my suggestions are grammatical/clarity related only
You say “They are not naively predictable, as they have entirely different properties than the substrate from which they emerge. If you lived somewhere that there were never clouds,” – I suggest you say “If you lived somewhere where clouds did not exist — “
You say “The sun plus GHG radiation combine to heat the surface, which then warms the air. The low-density air rises.” – I suggest you define GHG here – then you don’t have to do it again
You say, “Thunderstorms function as heat pipes that transport warm air rapidly from the surface to the lifting condensation level where the moisture turns into clouds and rain, and from there to the upper atmosphere without interacting with the intervening greenhouse gases.” — here you say greenhouse gasses – if you defined GHG earlier it is proper to here just say GHG. Nitpicky stuff but ——
You say “Prediction 4. The “climate sensitivity”, far from being a constant, will be found to be a function of temperature.” I suggest you change to say “The “climate sensitivity”, far from being a constant, will be a function of temperature.”
You say “Prediction 5. In some areas, rather than the temperature being controlled by the downwelling surface radiation, the surface radiation will be found to be controlled by the temperature.” – same suggestion as above – recommend rewriting to say, “In some areas, rather than the temperature being controlled by the downwelling surface radiation, the surface radiation will be controlled by the temperature.”
Roger, wilco.
w.
Refreshing to see old fashioned predictions.
I heartily approve of your effort to publish, and I think that I understand what you have written. It is refreshing to see a reasonable hypothesis and theory for this complex system.
Along the lines of the Terry Pratchett character, however, to call me a peer is to call for more sawdust on the floor. In my sordid past, I have done engineering technical writing and editing, and have some suggestions along those lines not suited to this comment format.
My suggestions may not be appropriate for where and how you may intend to publish. Let me know, here, if and/or how I should send these to you, and correspond with you in a different way.
Willis, as one of your biggest fans, I hate to sound brutal on this, but believe me, the reviewers will be even more brutal, and forget Nature, even if you submit as Eschen Willisbach. Those immature, phony-scientists are still trying to get out of their political short pants since leaving university. I wish I had more time to work on this as I know I can help. In fact, this month I, and my colleagues, just had two papers accepted in seriously good journals after some fairly healthy reviewer critiques. I think the content is great but it’s just not written in Journal style and, as such, makes it a bit difficult (for me) to follow.
I just picked a paper that I thought was well written (when I first read it), for PNAS, that you could use as a template, whether or not you agree with the content: Feldman et al. (2014).
https://www.pnas.org/content/pnas/111/46/16297.full.pdf
I think if you rewrote the paper in that style, it would look fantastic.
If you’re not pissed off at me, I could help further, just not this week.
Pissed off at you? Why on earth would I be pissed? Brutal is honest, and honesty is what is needed in this situation. I’m not looking for kudos.
I had a “Brief Communications Arising” peer-reviewed (3 reviewers) by Nature, so I’m aware of their style …
Thanks for the example, looks good. I’ll study it when I finally work my way through the 100+ comments here.
w.
I knew you wouldn’t be but, you know, how beautiful one’s baby is can sometimes be a sensitive subject. I actually do get pissed off at some reviewer’s comments if they’ve obviously been a bit lazy.
Overall, an excellent paper. But there is one nit to pick:
[QUOTE FROM PAPER]”Note that the “climate sensitivity” is indeed a function of temperature, and that the climate sensitivity goes negative at the highest temperatures. It is also worth noting that almost nowhere on the planet does the long-term average temperature go above 30°C. This is further evidence of the existence of strong thermoregulatory mechanisms putting an effective cap on how hot the surface gets on average.”[END QUOTE]
Since most of the paper deals with the formation of thunderstorms over tropical oceans, which tend to prevent them from becoming too hot, the statement about “long-term average temperatures” never going above 30 C should be limited to areas over or near oceans, not anywhere “on the planet”, which can include some desert areas (Sahara or parts of southwestern USA) where average daily temperatures can exceed 30 C. Even over some bodies of water nearly surrounded by land, such as the Mediterranean Sea or Gulf of Mexico, average daily temperatures can exceed 30 C in summer.
Also, what is meant by a “long-term” average temperature? A diurnal average? A monthly average? A yearly average? The time period of the average should be specified.
In this case, “long-term average” means the 20 years Mar 2000 – Feb 2020. However, the result is the same for the last fifty or the last 100 years. And you’re right, I should have specified the time period, I’ll change that.
And over that 20-year period only 0.22% of the world’s surface averaged over 30°, tiny spots in inland Africa south of the Sahara.
It strikes me that an interesting analysis would be just how much of the globe is over 30°C, year by year. So many drummers … so little time.
w.
Maybe a nit pick – on dust devils – “First, it moves warm surface air upwards into the lower troposphere.” The surface air is already in the lower troposphere isn’t it? So “in” instead of “into”.
Figure 5. label vertical dashed line “Pinatubo”.
Thanks, Rick. Changed. Please note when I say “changed”, I’m changing the original not the blog post.
w.
Well for starters I think that most climate scientists would disagree with the first statement that
The current paradigm of climate science is that the long-term change in global temperature is given by a constant called “climate sensitivity” times the change in downwelling radiation, called “radiative forcing”.
The parameter or climate sensitivity is something that emerges from different climate models as a simple number that allows people to hide all the messy details. For example in your model there is still a climate sensitivity parameter only you are claiming that it is zero.
Secondly you appear to be confusing global and local effects. The climate sensitivity parameter as used is an average over the entire globe. So your discussion after prediction 4 is missing the point entirely. At best you would need to average your climate sensitivity at each grid cell to come up with an average climate sensitivity for the globe and then look to see if that global average varied with average global temperate.
In addition to which climate scientists already know that climate sensitivity varies with temperature. For example in Roe’s “Feedbacks, Timescales and Seeing Red” the climate
sensitivity parameter ignoring feedbacks is just the derivative of the Stefan-Boltzmann law with respect to temperature giving (his Eq. 3) 1/(sigma T^3).
There are also fairly fundamental issues regarding your model. Firstly the question arises as to timescales over which your emergent effects work. You describe a series of events such as thunderstorms, dust devils etc all of which emerge over the course of a day and so can only operate on timescales of 24 hours. Thus they should work to stop seasonal changes — your model clearly predicts that seasons shouldn’t happen since your thermo-regulatory system would act to counteract the reduction in forcing. But clearly seasons happen and result in local temperature variations of more than 0.2%. Hence the question would be why can your emergent effects stop global variations of more than 0.2% but not local seasonal changes.
Your model is also incomplete. It only discusses how energy is moved around the climate system. It does not say anything about how energy enters or more importantly leaves the earth. I could just as easily say that your model explains why global warming is more pronounced at the poles since all the thermoregulatory systems you describe take energy from the equator and shift it polewards. This would explain the fact that the arctic is warming faster than the equator, keep all of the mechanisms you discuss intact and allow for significant global warming. If you want to claim that you thermoregulatory system actually cools the earth then you need to couple it to a model of radiation and discuss the greenhouse effect in detail since that is the only way for energy to leave.
Also you do not show any evidence that the mechanisms you discuss are not already included in current climate models. Clearly they are not explicitly in them due to the size of the grid cells but if a modeller were to claim that such feedbacks are implicitly included as parameterised values for convection and cloud feedback or something similar and therefore there is nothing new in your model since it is already in current simulations how would you disprove them? You need to create a mathematical model for your feedbacks so that you can estimate the size of them and then compare them to the size of various parameters in the climate models.
Your final sentence shows that the entire premise is wrong. You ask
“what causes slow thermal drift in thermoregulated systems?”
to which the answer many people would give might be the rise in greenhouse gases. Nothing you describe stops an increase in greenhouse gases from producing a slow thermal drift. Dr. Spencer’s satellite measurements show a temperature rise of 0.13 degree rise per decade. How do you know this is not caused by an increase in CO2? You also make the misleading claim that temperatures have varied by less than one degree Kelvin. Most people would say instead that temperatures have risen by about one degree Kelvin. This difference is crucial to whether or not your mechanism is working. If there is a slow steady rise over a century then clearly your thermoregulatory mechanisms are not doing their job. If the temperature on the other hand has gone up and down over the past century while remaining roughly constant then your mechanisms might be working but then you have to explain how effects that only last a day work to slow temperature changes over a 50 year period but not any faster.
“Climate sensitivity is something that emerges from different climate models as a simple number that allows people to hide all the messy details.”
To hide messy details, it has to be built in – not to emerge from the same messy details.
Izaak,
I don’t believe that the emergent phenomena as described by Willis would have anything to do with seasonal suppression. The primary region for this proposed effect is the ITCZ. Thunderstorm formation anywhere outside of this is typically not due to the temperature reaching a high point, but rather lifting mechanisms: fronts, orographic lifting, advection, etc. Sure, there is some, but not the overwhelming majority. The transport of this excess energy from the tropics toward the poles via humidity or enso or whatever will increase the rate of energy leaving the system as a whole. Now, you can argue that the rate of energy transport from these emergent phenomena does not exactly equal the energy change radiated from earth, and I’ll listen.
You say “If there is a slow steady rise over a century then clearly your thermoregulatory mechanisms are not doing their job.” Or it could be that they are. These are not mutually exclusive. The mechanisms are primarily describing what happens in the tropics, and that region has not warmed.
Finally, I didn’t catch that part where Willis claimed that the rise in CO2 didn’t cause the rise in temperature, but I was reading it fast. I’ll read it more carefully now.
Thanks, Izaak. You say:
The problem is that nobody can agree on the value of the simple number. But it’s worse than simple disagreement. As I pointed out in “Dr. Kiehl’s Paradox”:
So this “simple number” as you put it, differs by a factor of 2 to 3 but they still get the right answer? Really? And you find nothing at all curious about that, to you that makes sense? Because to me, it says something is wrong with the theory.
Next, you say:
Nope. I said very clearly that there is a climate sensitivity, but it is a function of temperature, and sometimes is less than zero.
You say:
Per S-B, the change in temperature corresponding to a doubling of CO2 (3.7 W/m2) is 0.8°C at 0°C, and 0.6°C at 30°C. So you are correct, and I do need to clarify that statement. But no one uses those figures.
On the other hand, my own figures show that the change in temperature corresponding to a doubling of CO2 (3.7 W/m3) is ~0.5°C at 0°C, and by the time you get to 30°C, it’s gone negative. So clearly, we’re talking about different things.
Note that at the point where the emergent thermostat really kicks in, which is at about 26-27°C, the temperature sensitivity falls off a cliff.
You say:
First, the cloud radiative effects include the clouds sending energy directly back out of the system via reflection. Next, thunderstorms transport energy from the surface to high in the troposphere without it interacting with greenhouse gases. For the transport up to the thunderstorm base its in the form of latent heat, so not radiating. Once it hits the lifting condensation level, it is transported inside the thunderstorm tower with little interaction with any GHGs outside the tower. And at the top it is released in an area nearly free of CO2 and H2O so it is free to radiate to space … and that is how it “more importantly leaves the earth” as you say.
So your claim that “all the thermoregulatory systems you describe take energy from the equator and shift it polewards” is simply not true. In fact, most of them move energy from the surface upwards, not polewards. And every metre that the energy moves vertically, it has less and less CO2 and more importantly water vapor between it and space.
Next, you say:
First, none of the emergent thermoregulatory phenomena are 100% effective. Clouds and thunderstorms keep tropical temperatures from overheating or over cooling by the timing and strength of their emergence. But some days are still hotter than others, due to differences in overlying atmosphere characteristics, wind, and other variables.
Second, the emergent thermoregulatory phenomena are not always present at all locations and at all times.
Now when I started thinking about this question, like you I thought “what could keep the temperature stable within a percent over a century or more”. So I was looking at all kinds of slow, long-term phenomena, like the long-term interaction between rain, mountain rock, and CO2.
I was living in Fiji at that time, and one late morning I was sitting on the beach looking at the cumulus field forming, and I thought “I’m looking through the wrong end of the telescope”.
What I realized what that if there were a phenomenon that could keep most days from getting too hot or too cold, it would also keep a week from getting too hot or too cold … and a month, year, or a century from getting too hot or too cold.
And I was looking at an important part of that phenomenon. On cold days, the cumulus field formed later, allowing in more heat. On warm days, the field forms earlier, reflecting sunshine back out to space. And since half of the incoming sunlight hits the tropics, controlling tropical albedo is the same as the gas pedal in your car—it controls the amount of energy entering the engine.
So yes, controlling temperatures in the short term, even imperfectly, can indeed control temperatures in the long term.
Finally, you say:
Not true. Here’s the key. The tropical cumulus field forms when a certain temperature is exceeded. It doesn’t form when the sunshine gets to a certain strength. The threshold is temperature-based, not forcing-based. And as a result, if GHG forcing increases AND that increases the temperature, all that happens is that the clouds form earlier in the day.
And in the tropics, total downwelling noon radiation is about a kilowatt. Increasing GHGs since 1900 may have changed that by a couple watts, less than half a percent … so an imperceptible change in the timing of the emergence of the cumulus field would be enough to totally counteract that change.
My thanks to you for your detailed objections, they make me think and will definitely focus and improve my paper.
w.
Willis,
If your feedback mechanisms are not 100% effective then they do not work as you claim they do and still leave room for a small change in temperature over the course of a century to be due to greenhouse effects. You state that the temperature has changed by about 0.2% since 1900 and similarly the forcing at the tropics has changed by less than half a pecent over the same time period. So an imperceptible change in the timing of the cumulus field would just as easily be changed by the forcing resulting in the temperature rise.
And again unless you can put some numbers into your model it will just get ignored. Since you can easily still be right and for CO2 to be driving the climate. Suppose for example the global temperature is given by:
T(t) = T0+ A cos(b*t) Exp(-c*t)
where T0 is the set point, A the magnitude of some perturbation and c is a decay term. Your paper only says that c is positive while leaving open the question of what determines the set point T0. All a climate scientist has to do is say that once you average over suitably long time scales the value of A, b and c are irrelevant and the only equations of interest are those for T0 which is determined by things like the amount of CO2 in the atmosphere, the ellipticity of the orbit, solar intensity etc.
Willis’s emergent mechanisms are not described as eliminating climate variations, including seasons and decadal (or longer) climate changes, but in moderating them—-and most importantly, putting bounds on them.
Those bounds mean No Tipping Point from CO2 forcing lies ahead. This is just the opposite of the claims of climate alarmists, whose models forecast runaway warming from the course of rising CO2 we are on.
This is an enormously important point. The Western world is getting ready to commit unnecessary economic suicide based on the models Willis’s theory contradicts.
kwinterkorn,
It is very hard to see how emergent mechanisms such as Willis describes operates on a decadal timescale. His model involves things like thunderstorms or tropical clouds that naturally have a periodicity of about 24 hours (i.e. the water heats up during the day causing clouds to form in the afternoon). Thus any such mechanisms react almost instantly and on a timescale of hours to days to a change in temperature. Therefore if they exist and they work they should stop it getting colder in winter so the fact that in most places it gets colder in winter shows that such mechanisms are of very limited strength.
Nor do Willis’ mechanisms put any useful bound on global temperatures. Tropical temperatures might be limited to 30 degrees but the average temperature of the planet is only 15 degrees or so and hence there is still a maximum of 15 degrees of global warming possible until Willis’ mechanisms operate globally. So there is still room for catastrophic global warming even if Willis’ theory is correct.
How can it be catastrophic? This mechanism is already in full affect in the tropics, and all kinds of creatures inhabit the tropics, in fact the biodiversity and/or concentrations of living organisms on this planet is likely highest in the tropics. If anything, a whole lot of warming on this planet would just make bigger tropics. And if that worries you, relax, this planet has been there before as well, and still supports life just fine. If anything, global warming would make life a beach everywhere!
I like the description of thunderstorms as heat pipes that cool the ground, partly by way of cool rain hitting the ground. Of course the raindrops themselves at whatever temperature have heat content, caloric content, so the falling rain represents a downward component of heat related energy. This all seems to me very much in contrast to simple depictions of greenhouse theory, where virtually the only downward power components are held to be either solar input or else downwelling IR, with seemingly no special attention to a regulatory cooling effect overall.
Willis thanks for a very interesting article! I think there is an additional related phenomen that perhaps should be checked in the future. When a thunderstorm forms large amounts of water is condensed into microscopic droplets with zero CO2 content at a high altitude and thus low temperature with an extremely large surface area. My view is that the thunder storm efficiently locally removes CO2 from the atmosphere thus increasing radiating heat loss over the sea. Over land the CO2 is released close to the ground when the water evaporates.
Perhaps something to look into in the future.
To me the mechanisms you describe feel very plausible.
Willis, a suggestion concerning Tstorm mechanism discussion, which you may wish to add. You note clouds cool by increasing albedo. But some don’t—high wispy ice cirrus warms because transparent to incoming SWR but opaque to outgoing LWR—part of Lindzens adaptive iris.
IMO there is a second and arguably more important Tstorm thermoregulatory mechanism. The condensation at altitude in a thunderhead releases the heat of evaporation in large part above the greenhouse radiative altitude threshhold, radiatively cooling directly. For sure this is true for hail and grauppel. The condensation falling as rain lowers troposphere specific humidity, reducing the water vapor feedback. That cools indirectly by lowering the positive WVF.
I studied this second issue back when writing The Arts of Truth (climate chapter) and then Blowing Smoke (eassys Humidity is Still Wet, and Cloudy Clouds). In both CMIP3 (AR4) and CMIP5 (AR5) the amount of modeled ocean rainfall is about half that which can now be ‘known’ directly from the ARGO near surface ocean salinity measurements. Means two things. First, you have second and third Tstorm cooling mechanisms at least as powerful as reduced insolation. And second, observational proof that Tstorms are incorrectly parameterized. See my above comment for the more powerful statement you ‘prove’ by showing they cannot be parametrized at at all since vary over the day and season. In the conventional climate model sense, parameters are the ‘constants’ in some larger climate function. See my post here some years ago ‘The Trouble with Climate Models’ for details.
“releases the heat of evaporation in large part above the greenhouse radiative altitude threshhold, radiatively cooling directly.
N2 and O2 cannot cool radiatively, but liquid or solid water can. I wonder if models take it into account.
They do, but incorrectly by assuming constant relative humidity, observationally proven false.
Rud and Willis,
I’ve wondered about this. All the energy of evaporation or sublimation is converted into latent energy, and yes this cools the surface, but then an equal amount must then be released on condensation or precipitation. During condensation or precipitation, I have always assumed that the bulk of this energy is then thermalized, but I always wondered what fraction of it is radiated. Do you have a handle on what % of the energy released on condensation is radiated? Or, is it that all energy is transferred to the surrounding molecules, warming them, and then it is radiated?
Curious.
If the release is above the radiative layer, it all goes to space. The equivalent radiative layer, determined by CO2, is a function of CO2 concentration and altitude. Is why CO2 never saturates.
I would think that needs to be an exaggeration, on at least two counts:
It’s all thermalized, transferred to the surrounding molecules.
The warm air radiates at a rate related to its temperature. (It also absorbs longwave radiation from below and above.)
The efficiency of radiative heat transfer from the air increases at higher altitudes, as the atmosphere above becomes more “optically thin.”
But, there is no point at which all added heat is instantly and magically whisked away by being radiated to space.
Some of the heat is eventually returned to the surface, as convective circulation transports air to higher latitudes where it returns to the surface.
See also my comment to Rud.
Could you unpack or cite what evidence you’re referring to? (I don’t have any assumptions about this either way; just curious.)
“N2 and O2 cannot cool radiatively,”
Is that actually a true statement?
Just because they do not radiate in the LWIR doesn’t everything radiate away it’s energy if it is above 0k.
In the case of N2 and O2 it is in the microwave frequencies.
First, yes, N2 and O2 can cool radiatively, but the effect is trivially small.
Next, all solids radiate. But monatomic gases (e.g. argon) don’t.
w.
“The condensation falling as rain lowers troposphere specific humidity, reducing the water vapor feedback. That cools indirectly by lowering the positive WVF.”
I can see that specific humidity would be lower in the upper troposphere, where the condensation occurs, but there must be a lot of evaporation from raindrops as they fall and warm. This should cool the surviving droplets but increase humidity (as compared with before the rain) at that lower altitude.
Thanks, Rud. Elsewhere I’ve listed the following:
In addition to reflecting sunlight from their top surface as cumulus clouds do, and transporting heat to the upper troposphere where it radiates easily to space, thunderstorms cool the surface in a variety of other ways, particularly over the ocean.
1. Wind driven evaporative cooling. Once the thunderstorm starts, it creates its own wind around the base. This self-generated wind increases evaporation in several ways, particularly over the ocean.
a) Evaporation rises linearly with wind speed. At a typical squall wind speed of 10 mps (20 knots), evaporation is about ten times higher than at “calm” conditions (conventionally taken as 1 mps).
b) The wind increases evaporation by creating spray and foam, and by blowing water off of trees and leaves. These greatly increase the evaporative surface area, because the total surface area of the millions of droplets is evaporating as well as the actual surface itself.
c) To a lesser extent, surface area is also increased by wind-created waves (a wavy surface has larger evaporative area than a flat surface).
d) Wind created waves in turn greatly increase turbulence in the atmospheric boundary layer. This increases evaporation by mixing dry air down to the surface and moist air upwards.
e) As spray rapidly warms to air temperature, which in the tropics is often warmer than ocean temperature, evaporation also rises above the sea surface evaporation rate.
2. Wind driven albedo increase. The white spray, foam, spindrift, changing angles of incidence, and white breaking wave tops greatly increase the albedo of the sea surface. This reduces the energy absorbed by the ocean.
3. Cold rain and cold wind. As the moist air rises inside the thunderstorm’s heat pipe, water condenses and falls. Since the water is originating from condensing or freezing temperatures aloft, it cools the lower atmosphere it falls through, and it cools the surface when it hits. In addition, the falling rain entrains a cold wind. This cold wind blows radially outwards from the center of the falling rain, cooling the surrounding area.
4. Increased reflective area. White fluffy cumulus clouds are not tall, so basically they only reflect from the tops. On the other hand, the vertical pipe of the thunderstorm reflects sunlight along its entire length. This means that thunderstorms shade an area of the ocean out of proportion to their footprint, particularly in the late afternoon.
5. Modification of upper tropospheric ice crystal cloud amounts (Linden 2001, Spencer 2007) . These clouds form from the tiny ice particles that come out of the smokestack of the thunderstorm heat engines. It appears that the regulation of these clouds has a large effect, as they are thought to warm (through IR absorption) more than they cool (through reflection).
6. Enhanced night-time radiation. Unlike long-lived stratus clouds, cumulus and cumulonimbus often die out and vanish as the night cools, leading to the typically clear skies at dawn. This allows greatly increased nighttime surface radiative cooling to space.
7. Delivery of dry air to the surface. The air being sucked from the surface and lifted to altitude is counterbalanced by a descending flow of replacement air emitted from the top of the thunderstorm. This descending air has had the majority of the water vapor stripped out of it inside the thunderstorm, so it is relatively dry. The dryer the air, the more moisture it can pick up for the next trip to the sky. This increases the evaporative cooling of the surface.
8. Increased radiation from less water vapor. The dry air surrounding the thunderstorm allows for more upwelling surface longwave radiation to make it to space.
So yes, lots of ways that thunderstorms cool … but I couldn’t justify going through all of that in the paper.
Charles said it really should be about five different papers … might be right.
As always,
w.
You wrote:
“3. Cold rain and cold wind. As the moist air rises inside the thunderstorm’s heat pipe, water condenses and falls. Since the water is originating from condensing or freezing temperatures aloft, it cools the lower atmosphere it falls through, and it cools the surface when it hits. In addition, the falling rain entrains a cold wind. This cold wind blows radially outwards from the center of the falling rain, cooling the surrounding area.”
Yes, I distinctly experienced such a cold wind one time back in the mid 1990’s here in Saskatchewan. From my tractor at the time, I could see a really big lenticular shaped cloud formation above the hills to the northeast of me, maybe 10 miles away, or maybe more like 15 miles to the center of this thing. When I stopped my machine to step off for a bit, the wind coming direct from there felt very cool indeed.
Later when I got in my car and drove through that area, there were steel bins strewn all around. Also I saw one old farmhouse ripped in half, and another newer house sitting intact in an otherwise completely obliterated farmyard. “Plough wind” damage, they called it.
I will give it a closer look later, but I want to say from the start the opening statement is very strong. The fact that decades of new and better data have failed to improve the uncertainty in our estimates of climate sensitivity is proof that the underlying model is wrong. This is a basic principle of science. Just as the very precise observations of Tycho Brahe failed to improve the uncertainty about the size of the orbit of Mars, until the underlying model was changed from a circle to an ellipse by Kepler, our estimate of climate sensitivity will not become more precise until the underlying model is similarly rectified. This is the central issue.
Willis, I really wish more journal articles read as easily as your writing, but sadly, that is not the case. There seems to be a stylistic bias requiring more turgid and less easily comprehensible writing style. An example from this article is your statement “doesn’t raise the temperature anywhere near as fast”, from which you could remove the “anywhere near” making it more in accord with scientific journals, but less interesting. There are many such stylistic adjustments that might be made, to make this important work read more in the way to which journal editors are accustomed. I have never been the lead author on a journal article, so I am perhaps a poor judge, but others on WUWT might agree with me here that such stylistic changes may improve the likelihood of publication.
Also, the consensus elite (?) scientists will no doubt be looking for every nit to pick, so the way you have used “climate sensitivity” in the context of the processes in a single day will be an easy target. I understand why you have done so, in that climate is simply weather writ large, yet being content to call it temperature sensitivity may be a safer option. Again, the thoughts of someone having been published in a lot of journals would carry more weight than mine.
Willis,
Lowess fitting provides an aesthetically-pleasing representation of the general trend of data. However, it has a disadvantage of not being particularly useful for interpolation or short-range extrapolation. That is, it all has to be done manually with the graphics. Furthermore, it does not provide a quantitative estimate of the goodness-of-fit for purposes of comparing models or supporting any claims of utility.
Therefore, I’d suggest adding, as appropriate, function fits, from a statistics package, to your figures. Either fit all the data, or your Lowess fit. That way, you can claim how well your hypothesis is explained by your independent variables. For example, you might get by with a 3rd-order polynomial fit for Fig. 2, and Fig. 6 looks like it might be fit well with a logarithmic or 2nd-order polynomial.
Obvious but important point.
The predictions are supported by evidence. But you do not discuss the counter-evidence.
Even if the discussion is a single sentence of “As yet there are no observations that contradict this interpretation”, there ought to be some consideration of the alternative.
This is a discussion of the issue not an article intended to sway opinion.
Great effort, Willis. My only contribution from experience is to eliminate any qualitative descriptors and ensure that you have a ‘complete’ literature search.
I think LOWESS (LOcally WEighted Scatter-plot Smoother) should be caps like CERES.
Willis, don’t feel bad if you paper doesn’t make Nature. They cater to the university academia Ph.D track who have spent such big taxpayer $ on test gear that they essentially HAVE to publish in Nature. There are many good journals in the meteorological realm.
Global warming is mostly about polar amplification.
So it seems global warming or cooling is mostly the tilt of Earth’s axis.
And since our axis tilt is reducing, long term, we heading towards, global cooling.
So we have recovered or are recovering from Little Ice Age and within few centuries or
less, we could expect a return to something like the Little Ice Age.
And a continuation of our 5000 year tread of cooling.
I agree. Global warming during Ice Age Terminations is extremely rapid compared with cooling during Ice Age onset. I believe this is due to the exponential growth of melt ponds at high northern latitudes when absorption of solar radiation by water surfaces exceeds a specific threshold determined by solar elevation angle. It is a good predictor, see: http://blackjay.net.au/wp-content/uploads/2020/04/IceAges-1.pdf
High rates of precipitation occur at any time over the warm pools. They are triggered by convective instability and that is not linked to daily cycle. It takes about 30 hours to recharge the CAPE.
Attached was observed at the moored buoy at 0N 156E when it was in a warm pool. The heaviest rainfall occurred on the evening of day 3. Also heavy falls early morning on day 7.
Willis has the advantage of having lived in the tropics, as did my father who suggested that in Singapore you could set your watch by the timing of the afternoon thunderstorms. Obviously, this is a general statement and there are a variety of features that can create heavy rain in the tropics.
Also of note, is that precipitation rates in tropical systems like hurricanes often increase overnight. Curious.
Land is a different situation to open water. The land is much more responsive to sunlight and clouds than the ocean.
You can go and look at the buoy data yourself to see the big downpours occur at any time. It is reasonably well known in the literature as well.
True, Rick. In the warm pool there are lots of thunderstorms that occur on a much more random basis than occurs in much of the rest of the tropics.
w.
Willis,
Not bad, but can you explain why you mixed CERES with Berkeley, when CERES has its own temperature (skin_temp, adj_skin_temp)?
Hey, Zoe, good to hear from you. I used the Berkeley Earth and Reynolds OI data because the CERES surface data is not part of the EBAF 4.1 dataset, which is stated to be “suitable for analysis of variability at the intra-seasonal, inter-annual, and longer time scales”.
The datasets you reference are from:
or
Neither of these say that they are suitable for the kind of comparisons I’m making. One is for “regional and diurnal process studies”, and the other is for “comparison with other same orbit sensors.”
My best regards to you,
w.
Oh, this dataset has skin_temp:
https://opendap.larc.nasa.gov/opendap/hyrax/CERES/SYN1deg-Month/Terra-Aqua-MODIS_Edition4A/
This is actually EBAF4.2, I think.
Thanks, Zoe, but AFAIK that’s actually part of the SYN dataset I referenced above. Also, I’ve not seen anything about and EBAF4.2. Link?
w.
w. ==> Figures 2 and 3 both scatter-plots, show classic signs of non-linearity — with fractal-like banding. There are two potential causes of this: 1) The physical phenomena themselves are non-linear and have fractal-like expressions in the real world or 2) the fractal-like numerical results are a outgrowth of the non-linear mathematical expressions.
Some explanation has to be advanced for this obvious feature in the plots.
Kip,
Possibly rounding of values contributes some pattern (if they are actually rounded). I do not know, just theorising. Geoff S
Geoff and Kip, from what I’ve seen the banding is a function of the fact that these are averaged into 1° latitude and longitude bands. Particularly with latitude, the variables being measured are often changing rapidly N/S and slowly E/W, and thus form individual line-like patterns in the scatterplots.
Likely something worth mentioning somewhere in the paper.
w.
w. ==> Lat/Long might produce a regular banding, but I think not the distinctive “strange attractor-like” patterned banding showing in your two figures. I’m going to try to find and read Rud’s fractal productivity paper in which he finds the “same result”.
Kip, what makes the pattern is that the variables are generally changing very rapidly with latitude and very slowly with longitude. This leads to “chains” of results with the patterns you see. Consider a simplified example:
I’ve used gridcell area because it’s a proxy for the cosine of the latitude. The banding is vertical because, for a given latitude, the gridcell area is the same at every point of longitude.
Now, consider using a variable in place of gridcell area which changes slowly with longitude, and then returns to its original value. Those vertical lines will become the curious looping patterns you see in my graphs.
Best regards,
w.
Kip, a comment from someone who actually published major peer reviewed on fractal implications long ago. See https/doi.org/10/002/smj.4250130705/
or search Istvan, fractal productivity. Same result.
Rud ==> I’d love to read it but none of my usual ten ways of finding an paper that is “in hiding” have turned it up, including a doi search. If you have a direct link, can you please post it here?
Rud ==> I haven’t been able to locate your paper, but I suspect that “same result” in your comment implies that there are some fractal-like non-linearities in the real world function being measured?
I have seen this fracticality time and again in the oddest natural phenomena — larval instars in flour beetles, cloud production, etc.
Germaine, I suppose, but small potatoes:
1) “Here is Reis and Bejan’s description” This should be followed by a colon.
2) “I will define emergent climate phenomena functionally and by example.” Needs a colon there instead of a period; and, would be better as “…climate functionally (in bold) and by example:”
Very best wishes to you on this!
Done.
w.