Guest Post by Willis Eschenbach (@weschenbach on X, personal blog at Skating Under The Ice)
Here’s a science joke about the dangers of oversimplified models.
A dairy farmer with low milk production asks a physicist for help. After some months, the physicist eventually reports back: “I have found out how to solve the problem.”
“About time!”, said the farmer, “What is it?”
The physicist replies, “First, assume a spherical cow in a vacuum.”
In 2023 I wrote post entitled Testing a Constructal Climate Model, where I took a first cut at making a computer implementation of Adrian Bejan’s ideas about a Constructal model of the climate.
For those who missed my earlier post, the Constructal Law is the most recently discovered fundamental law of thermodynamics. It was first described by Adrian Bejan in 1996. He’s the JA Jones Distinguished Professor of Mechanical Engineering at Duke University, and his writings have over 100,000 citations.
The Constructal Law says that flow systems far from equilibrium evolve to maximize access to flow. Rivers don’t meander randomly—they organize to maximize water transport. Animal circulatory systems don’t just happen—they evolve to maximize nutrient flow. And according to Adrian Bejan, the climate should organize itself to maximize heat flow from the hot tropics to the cold poles.
Now, that sounded reasonable enough … but does it actually work? Can you build a working climate model based on that principle?
Turns out you can. And as my post above showed, it’s a very simple model.
In any case, after writing that post, I got invited to present my work in November at the 15th Constructal Law Conference, hosted by the Florida International University College of Engineering and Computing in Miami.
I went in part because I wanted to meet Adrian Bejan, who was slated to be in attendance. I have a number of scientific heroes, and he’s one of them. I introduced myself to him, and he said Oh, you’re Willis Eschenbach. I’ve seen your work. It’s very impressive!
Zowie, sez I. A win for the reformed cowboy!
There were many interesting presentations at the Constructal Conference, but that interaction alone was worth the ticket to Miami … however, I digress.
Originally, my plan for the conference was to just present the work shown in my post linked above. But then I realized that was a lazy copout — that model was two years old. I had to take it further forward. So I did more research and analysis, which is what this post is about. Basically, it’s an expanded version of my presentation at the conference.
The model I’m about to show you treats the Earth as a smooth sphere—no land, no ocean, no mountains, no ice sheets, nothing but a ball heated by the sun. It divides this ball into two zones: a hot equatorial zone and cold polar zones. That’s it. Two zones. And from those two zones, using the Constructal Law to maximize heat flow between them, the model reproduces the actual Earth’s temperature, circulation patterns, and year-to-year variations with remarkable accuracy.
Let me show you how it works, and then we’ll look at what it tells us about climate sensitivity. Spoiler alert: the news is good if you’re worried about catastrophic warming.
The Basic Setup
Figure 1 shows the concept. We divide Earth into a hot zone,extending from the equator to some latitude θ, and two cold zones, poleward of θ. Heat flows from hot to cold, driven by the temperature difference.
Figure 1. The spherical cow … er, spherical Earth model. There is a hot equatorial zone of area A_H with an average temperature T_H. There are two cold polar zones of total area A_L with an average temperature T_L). Heat flow q moves from hot to cold.
Now, before anyone objects that this is ridiculously oversimplified, let me show you what the real Earth looks like in terms of energy balance:
Figure 2a. The actual Earth’s hot and cold zones, as determined by the gridded top-of-atmosphere radiation balance from CERES satellite data. The tropics export energy (red), and the polar regions import it (blue). Note that the deserts—Sahara, Arabia, Australia, Gobi—are actually in the cold zone despite being hot. They radiate more energy than they absorb.
The similarity is striking. The real Earth organizes itself into these zones naturally. The model just captures this organization mathematically. And the division into these zones is surprisingly stable over time.
Figure 2b. Annual average hot and cold zones, 2001 to 2024
Note how the Sahara, Arabia, and Gobi deserts protrude down into the hot zone. This leads to some offsets in the results, as discussed below.
The Energy Balance
Being a simple fellow, I started with Bejan’s simple energy balance equations. The hot zone receives solar energy based on its projected area, reduced by its albedo (the fraction of incoming solar radiation reflected by the planet, “albedo_H”):
Energy in = (projected area) × (1 − albedo_H) × (solar constant) [Equation 1]
The hot zone radiates energy to space, reduced by the greenhouse fraction “greenhouse_H”. This is the percentage of upwelling thermal radiation from the surface that is absorbed by the clouds, water vapor, and the radiatively active gases.
Energy out = (area) × (1 − greenhouse_H) × σ × T_H^4 [Equation 2]
where σ is the Stefan-Boltzmann constant and greenhouse_H is the fraction of surface radiation absorbed by the atmosphere.
The same things are true for the cold zones. They absorb solar radiation mediated by albedo and emit thermal radiation to space, regulated by the greenhouse fraction.
The difference between incoming and outgoing power in each zone must equal the heat flow q between the zones. Energy is conserved—it has to go somewhere.
So far, nothing fancy. Just bookkeeping.
The Heat Transport
Here’s where it gets interesting. How much heat flows from the hot zone to the cold zone? Bejan and Reis showed that for buoyancy-driven atmospheric circulation, the heat flow should vary as:
q = C × (T_H − T_L)(3/2) [Equation 3]
where q is the heat flow and C is a thermal conductance factor representing how easily the heat is conducted from the hot to the cold zones.
According to Bejan, the 3/2 power law comes from the physics of convection. Warmer air rises, cooler air sinks, and the flow rate depends on the temperature difference in a very specific way. The constant C depends on atmospheric properties and circulation patterns.
Now we have five unknowns (T_H, T_L, q, the fraction x of Earth’s surface in the hot zone, and the conductance factor C), and three equations. How do we close the system?
Enter the Constructal Law
Here’s where Bejan’s insight comes in. The system evolves to maximize the heat flow q. Why? Because the climate is a heat engine, with the tropics as the hot reservoir and the poles as the cold reservoir. But unlike a car engine that delivers power to the wheels, Earth’s climate engine is permanently coupled to its “brake”—all the power it generates gets dissipated immediately through friction in winds and ocean currents.
For such a system—an engine hard-wired to its brake—maximum power production equals maximum dissipation, which means maximum heat flow. The atmosphere and ocean organize themselves to achieve this.
So the fourth equation is simply:
dq/dx = 0 [Equation 4]
Making It Work
I implemented this as a nested optimization problem in R. For any given value of x, I first solve for the values of T_H, T_L, and q that satisfy the three energy balance equations. Then I vary x to find the value that maximizes q. Finally, I optimize the value of C, the conductance, to agree with the distance between T_H and T_L. (T_H minus T_L) It’s optimization within optimization.
The original Bejan/Reis model used global average values for albedo and greenhouse effect. I improved this by using separate values for each zone, derived from CERES satellite data. Tropical regions have lower albedo (less ice and snow) and higher greenhouse effect (more water vapor) than polar regions. This matters.
I also added one more refinement. As you can see in my previous model analysis linked to above, the original model had a slight drift in temperatures over time.
Figure 3a. Results of my previous model incarnation, which shows an anomalous trend in the modeled temperatures
After too much investigation, I realized that this is because my model neglected the heat absorbed by the oceans. This flow was also not included in the Bejan model shown in Figure 1 above. I added this as a small tunable parameter for each zone.
So how many parameters does this model have? Let’s count:
- Albedo in hot zone (measured from CERES data)
- Albedo in cold zone (measured from CERES data)
- Greenhouse fraction in hot zone (measured from CERES data)
- Greenhouse fraction in cold zone (measured from CERES data)
- Conductance C^(3/2) (tuned parameter)
- Ocean heat absorption, hot zone (tuned)
- Ocean heat absorption, cold zone (tuned)
That’s four measured parameters and three tuned ones. Compare that to the thousands of parameters in comprehensive climate models. It’s a spherical cow.
The Results: Temperatures
OK, enough theory. Does it work? Figure 3b shows 24 years of data (2001-2024) comparing CERES satellite surface temperature observations to the Constructal model emulation. This is the corrected version of Figure 3a above.
Figure 3b. Annual mean temperatures. Blue/cyan: CERES satellite observations. Red/orange: Constructal model predictions. Top: hot zone temperature T_H. Bottom: cold zone temperature T_L.
The agreement with the actual real-world temperatures of the hot and cold zones is remarkable, given that nowhere is the model tuned to produce them. At this scale, they are so close that you can only see the difference between reality and the model around 2010.The model gets the absolute temperatures right within 0.1°C on average. It also tracks the year-to-year variations. It captures the slight warming trend. And remember—this is a model of a featureless sphere with no continents, no oceans, no mountains, no ice sheets, nothing.
Next, here’s a close-up of the hot zone temperatures shown in Figure 3b above:
Figure 4. Detailed view of hot zone temperatures. CERES data (blue) and model (red). Root mean square error: 0.20°C. Correlation of interannual variations: r = 0.56, p < 0.001.
The main difference between the model and reality is that the swings in the modeled temperature are somewhat larger than the swings in the real world. I suspect this is because the model assumes that the losses are all temperature-controlled, and also, in the model, there’s no atmospheric absorption of the sunlight. Both of these omissions increase the size of the swings.
Next, the cold zone results:
Figure 5. Cold zone temperatures. CERES data (cyan) and model (orange). RMSE: 0.13°C. Correlation: r = 0.71, p < 0.001.
The fit in the cold zone is better than in the hot zone, although again the swings are exaggerated in the model.
This shows that the model isn’t just matching the average temperatures—it’s capturing the dynamic annual changes in temperature as well.
The Hot Zone Boundary
The model predicts that the boundary between hot and cold zones should be at about 36° North and South latitude. The actual boundary, based on where top-of-atmosphere radiation balance crosses zero, is at around 34°. The model is off by about 2°, or about 220 kilometers.
Not bad for a model that doesn’t know about Hadley cells, polar cells, El Nino/La Nina, jet streams, Gulf Streams, or any of the detailed atmospheric and oceanic circulation patterns. Those patterns emerge naturally from maximizing heat transport.
Figure 6 shows how the boundaries compare by year:
Figure 6. Boundaries of Earth’s hot zone. Blue: CERES observations. Red: Model predictions. The model boundary is about 2.4° wider than observed.
The model tracks the variations well. The offset in the boundaries exists because in the real Earth, the major deserts (Sahara, Arabia, Australia, Gobi) are in the cold zone—they radiate more than they absorb. See Figures 2a and 2b above. But in the smooth-sphere model, those latitudes are in the hot zone. This makes the model’s hot zone larger than reality.
Despite this, the model captures the year-to-year changes quite well. Figure 7 shows the anomalies (variations around the mean) of the latitude of the boundary between hot and cold:
Figure 7. Anomalies in hot zone area. Blue: CERES. Red: Model. When you remove the offset, the model tracks the variations quite well.
This is doing a workmanlike job of calculating both the annual variations in the size of the hot zone and the overall trend of hot zone size over the period of record.
And to close the circle on this part of the analysis, here’s Figure 2 with the Constructal model hot zone boundaries overlaid on it.
Figure 8. As in Figure 2, but with the modeled boundaries overlaid on it (yellow/gray dotted lines).
Here you can see why the actual earth’s total hot zone area is slightly smaller than that of the model—the areas in green which are cold zone intruding into the model-simulated hot zone.
Heat Flow
Now for the crucial test. The Constructal Law says the system maximizes heat flow. Does the model get the heat flow right?
Figure 9 shows the total poleward heat transport:
Figure 9. Annual heat flow from tropics to poles, in petawatts (PW = 10^15 watts, left scale) and the equivalent global heat flow (petawatts divided by global surface area, W/m2, right scale). Blue: CERES. Red: Model.
The model shows a significantly higher heat flow than observed (14.9 PW modeled vs. 12.3 PW observed). This is for the same reason the area of the hot zone is larger as discussed above—those deserts that are in the cold zone in the real world but in the hot zone in the model. This means the model is absorbing more solar power than the real world in the hot zones and transferring it to the poles. So the total flow is too large, by a globally averaged value of ~ 5 W/m2. But look at the heat flow anomalies below:
Figure 10. Heat flow anomalies. Blue: CERES. Red: Model. RMSE: 0.04 PW. The model captures year-to-year variations almost perfectly.
That RMSE of 0.04 PW is tiny compared to the year-to-year variations. The model is faithfully capturing the dynamics of heat transport using only annually updated albedo and greenhouse parameters as input. That validates that we are seeing the Constructal Law at work.
Climate Sensitivity
Finally, what does this model tell us about climate sensitivity—how much warming would we get from doubling atmospheric CO₂?
To determine that, I ran the model with a uniform increase in downwelling radiation of 3.7 W/m², the IPCC standard assumed forcing from doubled CO₂. The model predicts:
- Hot zone warms by 1.09°C
- Cold zone warms by 1.12°C
- Global average warms by 1.10°C
So the equilibrium climate sensitivity is about 1.1°C per doubling of CO₂.
But wait, there’s more. And this is important. This value is a maximum estimate because the model doesn’t include negative feedbacks from a host of emergent climate phenomena like thunderstorm responses, El Nino/La Nina events, tornadoes, and other phenomena which I’ve written about extensively in my thunderstorm thermostat posts. Those feedbacks all oppose surface warming by transferring heat from the surface to the atmosphere. As a result, the real climate sensitivity is likely lower than shown above.
In addition, total known fossil fuel reserves contain about 4,780 gigatonnes of CO2. This is not total proven reserves, those we know we can get to within budget. This is everything we know about, whether or not it actually is economically recoverable with today’s technology.
At 17.4 Gt CO2 added per each ppmv increase, that will increase the atmospheric CO2 by 275 ppmv … and since we have ~ 420 ppmv of CO2, it’s unlikely that we’ll ever see a doubling of CO2 from here.
And with a sensitivity of 1.1°C from doubling, this implies a maximum temperature increase on the order of log2((275 + 420) / 420) * 1.1 = 0.8°C … Thermageddon™ cancelled, sorry, no refunds.
Is this sensitivity believable? The IPCC’s range for climate sensitivity is 1.5°C to 4.5°C per doubling. The Constructal model puts it at 1.1°C, below the IPCC’s lower bound. However, this is in the same range of observational estimates from Lewis and Curry and others who’ve analyzed the actual warming we’ve seen.
For comparison, here’s the history of climate sensitivity estimates:
Figure 11. Historical estimates of equilibrium climate sensitivity. The range of the estimates has actually gotten wider over time. That tells you something about how well we understand the climate.
Climate sensitivity is a, perhaps the, biggest unknown in climate science. Note that the uncertainty of the climate sensitivity has increased, despite hundreds of thousands of hours of computer time and human research. That’s not how science is supposed to work. To me, it strongly suggests our current climate models have been barking up the wrong tree.
What This Tells Us
The success of this ultra-simple spherical cow model reveals some profound things about how climate works:
1. Optimization trumps complexity. You don’t need to simulate every cloud, every ocean eddy, every rainstorm to understand the big picture. The climate organizes itself according to simple principles—it maximizes heat transport, subject to radiative constraints.
2. The ocean’s role is simpler than we thought. The model treats Earth as a uniform sphere—no explicit ocean, no currents, no thermohaline circulation. Yet it works, and works very well. This suggests the ocean’s main climate role is facilitating heat transport (captured in that conductance parameter C), not creating fundamentally new dynamics that require detailed representation.
3. Circulation patterns emerge. The model predicts a hot/cold boundary near 34°N/S—where the Hadley cell meets the Ferrel cell in the real atmosphere. The model doesn’t know about these circulation cells. They emerge from the optimization. The atmosphere organizes itself into Hadley and polar cells because that configuration maximizes heat transport.
4. Less is more. This model has seven parameters (four measured, three tuned). Comprehensive climate models have hundreds. Yet this simple model matches observations as well as or better than the complex ones for these fundamental variables of hot and cold zone temperatures, hot zone area, and heat flow. Occam’s razor suggests we should pay attention to that.
5. It demonstrates and validates the importance of the albedo and the poorly-named “greenhouse effect”. Clearly, those two variables alone have an overwhelming importance in the way that the climate organizes itself.
6. It makes intuitive sense. Albedo and the greenhouse fraction respectively control the amount of energy entering and leaving the system. And from basic physics, this makes sense—we’d expect the global temperature to be a function of the energy entering the system minus energy leaving the system. However, it is not a simple function of those two values. Instead, following the Constructal Law, the system constantly rearranges itself to maximize the energy flow given those two values.
7. Current climate models are going down the wrong path. This model clearly shows the underlying Constructal structure and action of the climate, a structure that is not emulated by the current generation of climate models.
Limitations
Now, I’m not claiming this model can do everything. It can’t. It has obvious limitations:
- Only two zones, so no gradients within zones and no longitudinal (east-west) variations
- Annual averages only, so no seasonal or daily cycles
- Simplified transport physics lumped into one parameter
- No ocean, no land. If nothing else, the thermal conductance factor C will be different in those two regimes.
- No explicit clouds, water vapor changes, ice-albedo feedback, or vegetation
- Simple greenhouse treatment
Future work should address these. A multi-zone model with finer resolution. Adding seasonal cycles. Explicitly modeling thunderstorm convection and ocean circulation. Including the desert areas as part of the cold zones. Coupling to detailed radiative transfer models.
But the point is, it works now despite its simplicity. That tells us something important about nature’s organizing principles.
Not Maximum Entropy Production
Some folks confuse the Constructal Law with Maximum Entropy Production (MEP). They’re related but different.
MEP says systems evolve to maximize entropy generation—maximum dissipation. For Earth’s climate, that’s sort of true. But Bejan’s Constructal Law is more general. It says flow systems evolve to maximize flow access, not necessarily dissipation. For an engine that can deliver power externally (like your car), Constructal Law predicts minimum dissipation. For an engine coupled to its brake (like Earth), it predicts maximum dissipation.
Earth just happens to be the second case. The Constructal Law explains both. MEP only explains the Earth. The success of this model validates the more general Constructal principle.
Where We Stand
Let me summarize what we’ve got here:
- A computational climate model based on Constructal optimization of heat flow
- Validated against 24 years of CERES satellite data
- Matches absolute temperatures within 0.1°C average (RMSE 0.13-0.20 K)
- Matches hot zone area within 2° latitude
- Captures interannual temperature variability and trends of the two zones (correlations 0.56-0.74)
- Predicts heat flux variations with RMSE of 0.04 PW
- Uses minimal parameterization—four measured quantities plus three tuned parameters
- Predicts climate sensitivity of 1.1°C per doubling of CO₂ as an emergent property, not a tuned value
This ultra-simple smooth sphere model, with no ocean or land or topography, successfully reproduces observed temperatures, circulation patterns, and power flow with unprecedented accuracy. I don’t know of any comprehensive climate model that achieves this level of skill, regardless of its level of complexity.
And it shows that every once in a while … an über-simplified model of a spherical cow in a vacuum actually does work …
CODA:
The Constructal climate model has two input variables—greenhouse fraction and albedo. It’s worth noting that the albedo and the greenhouse fraction are both functions inter alia of thunderstorms and clouds.
The surface is constantly emitting thermal radiation upwards (“upwelling radiation”). Some of this upwelling radiation is absorbed by the clouds and the “greenhouse gases”. The greenhouse fraction is the percentage of the upwelling radiation that is absorbed in the atmosphere. Figure 12 below shows how that differs around the world.
Figure 12. Average greenhouse fraction, CERES data.
As you can see, the areas of largest absorption enclosed by the 45% greenhouse fraction contour line are the great band of thunderstorms that stretches around the world at the Inter-Tropical Convergence Zone (ITCZ) just north of the equator.
Next, here is a map of the albedo, overlaid with the 45% greenhouse fraction contour line.
Figure 13. Average albedo, CERES data
Note that the areas of high albedo line up with the areas of high greenhouse fraction.
And to verify that this is indeed related to thunderstorms, here is the rainfall from the Tropical Rainfall Measuring Mission satellite observation.
Figure 14. Average monthly rainfall as measured by the TRMM
And that’s all I have for now, dear friends … tomorrow is a new day, always more to learn.
Here on our Northern California coastal hillside, we had rain yesterday—blessed rain after a dry spell. The weather systems that brought it organized themselves according to the same principles this model uses: maximize heat and moisture transport from where there’s an excess to where there’s a deficit. It’s beautiful to see the same physics working at scales from individual storms to the global circulation.
My warmest regards to all, my thanks to Adrian Bejan for illuminating conversations about Constructal theory, and to Umit Gunes and Pezhman Manipour for organizing the conference.
w.
As Is My Custom: When you comment, please quote the exact words you’re discussing, so we can all be clear on the exact topic under discussion.
References and Data
CERES data are from NASA Langley Research Center (https://ceres.larc.nasa.gov/). Key papers:
- Bejan & Reis (2005), “Thermodynamic optimization of global circulation and climate,” Int. J. Energy Res.
- Reis & Bejan (2006), “Constructal theory of global circulation and climate,” Int. J. Heat Mass Transfer
- Loeb et al. (2018), “Clouds and the Earth’s Radiant Energy System (CERES) EBAF data product,” J. Climate
I seem to recall that beyond a certain concentration more CO2 makes no difference because the spectrum is saturated. Is that correct? Does it change any of the calculations in this model?
For info on the saturation effect, see:
“The Saturation of the Infrared Absorption by Carbon Dioxide in the Atmosphere” by Dieter Schildknecht.
URL: https://arixiv.org/pdf/2004.00708vi
URL: https://arxiv.org/labs/2004.00708
From the Heartland Institute: https://climateatglance/carbon-dioxide-saturation-the-atmospere.
Shown in the chart (See below) are plots of the annual seasonal temperatures and
a plot of the average annual temperatures at the Furnace Creek weather station in Death Valley from 1922 to 2001. In 1922 the concentration of CO2 in dry air was ca. 303 ppmv (0.60 g of CO2/cu. m. of air) and by 2001, it had increased to 371 ppmv
( 0.73 g CO2/cu. m of air), but there was no corresponding in the air temperature at this remote desert. The simple explanation is that there is too little CO2 in the air to absorb out-going long wavelength IR light emanating from surface of this arid desert.
The real reason there was there was no increase in desert air temperature is that at concentration of 303 ppmv ,the absorption of IR by CO2 is saturated i.e. adding more CO2 to the air will not cause any more warming. The threshold for the saturation effect for CO2 is 300 ppmv in air which occurred in 1920.
At the Mauna Loa Obs. in Hawaii, the concentration of CO2 in dry air is 426 ppmv. One cubic meter of this air contains 0.84 g of CO2, a 15% increase from 2001.
The chart was obtained from the late John Daly’s website:
“Still Waiting For Greenhouse” available at: http://www.john-daly.com. From the home page, go to the end and click on: Station Temperature Data”. On the: “World Map”, click on
“NA”, and the page down to U.S.A.-Pacific. Finally, scroll down and click on
“Death Valley”. John Daly found over 200 weather stations located around the world that showed no warming up to 2002.
NB: If you click on the chart, it will expand and become clear. Click on the “X” in the circle to contract the chart and return to: Comments.
This might be true but I think the more general statement would be “the climate should organize itself to maximize heat flow from the earth to space”
Reality is (probably) that in order to achieve maximising heat flow from earth to space, climate needs to maximise heat flow to the poles but I dont think its a given truth by itself.
Excellent point. Earth and its climate is not a closed system. It’s just a part of a much larger entity.
The earth is a closed system because it does not exchange mass with its surrounding outer space. Actually earth gains small amounts of mass from meteors and the solar wind.
Unless you agree that e=mc2, of course.
It is a potential equivalence that only happens under special circumstances. To the best of my knowledge, it plays no role in climatological considerations.
The engineering (wiki) definition is
So honestrus meant in terms of energy flow. The earth is not bound to have its energy flow from equator to poles in any way because it can flow straight to space.
Harold The Organic Chemist Says:
In classical thermodynamics, the example of a closed system is a cylinder with a moveable piston. The gas inside cylinder is the system. The piston has a fitted pressure gauge and a port for a thermocouple for measurement of the gas temperature. The apparatus sits in liquid or gas bath whose temperature can be changed by using a heater or a cooling coil. The system can only exchange heat energy with its surroundings.
I’m not sure how that helps understanding the issue. Willis said
And (IMO) that flow is from the earth to space. He’s focussing on the internal flows and I dont think that’s entirely valid, although its not necessarily wrong either.
Thanks, Tim. The flow to space is basically constant to within a percent or so. Hard to optimize output when the input is basically constant to within a percent or so.
w.
The whole of AGW fits into that 1% or so. I think its the time aspect. In a general sense, the longer the energy stays, the warmer the planet gets. A more efficient flow to space cools the planet.
If you’re genuinely writing a paper on this then expect criticism around this idea because it’s not clear to me where constructual law regarding flow to space, fits.
It doesn’t really matter, does it? The planet has demonstrably cooled notwithstanding four and a half billion years of continuous sunlight.
Maybe you meant to say “cools faster”, rather than “cools”? Willis believes slower cooling results in heating! Cooling is cooling. The Earth loses around 44 TW, and sunlight is irrelevant due to the Sun’s energy in being precisely balanced by the Sun’s energy out.
And a body continuously losing even 1 W is, wait for it, cooling,
Not getting hotter, cooling. Losing more energy than it gains. Willis doesn’t accept this, nor do his ignorant and gullible supporters, but it happens to be a fact.
What do you think?
“The Earth loses around 44 TW, and sunlight is irrelevant due to the Sun’s energy in being precisely balanced by the Sun’s energy out.”
‘The Earth’ you refer to is the core and about half of the 47 TW heat transfer to the surface is the result of radioactive decay, this is less than 0.03% of the surface energy budget. The energy balance with solar input occurs at the Top of the Atmosphere (ToA) so changes in the troposphere can lead to changes in surface temperature.
No, you are either delusional, or your powers of comprehension are sadly lacking.
As Fourier said “All the heat the Earth receives from the Sun is lost to space, plus a little of the Earth’s internal heat.”
You may not accept that the Earth has cooled over the past four and a half billion years, but it’s true.
It is your choice to be ignorant and gullible, so don’t blame me. It won’t do you any good at all.
Fourier introduced the concept of the greenhouse effect, he said: “the temperature [of the Earth] can be augmented by the interposition of the atmosphere, because heat in the state of light finds less resistance in penetrating the air, than in repassing into the air when converted into non-luminous heat”.
Fourier, .I. (1824) Remarques générales sur les temperatures du globe terrestre et des espaces planétaires, Ann. Chim. Phys.(Paris) 2nd ser., 27, 136-167. This essay was reprinted, with slight changes, as Fourier, J. (1827) Mémoire sur les temperatures du globe terrestre et des espaces planétaires, Mém. Acad. Sci., 2nd ser., 7, 569-604. The English translation of Fourier’ s 1824 article, by Ebeneser
Burgess, was published in 1837 in the Amer: J. Sci. 32, l-20
.
Read the rest.
Particularly where Fourier writes –
You see, Fourier (and Tyndall etc) realised that without an atmosphere, the surface temperatures would drop to levels which would not sustain plant life, and man would die.
They also realised that daytime temperatures would exceed boiling point, but assumed that this would be self evident.
Now, where Fourier says
he describes the effect observed in a solar pond, where temperatures of around 90 C may be achieved. The “mass of air thus become solid”, (at least more solid than air).
Fourier was smarter than an ignorant and gullible person like you, and even calculated the rate at which the Earth is cooling, based on
So heat continuously being lost – cooling, not heating.
You need to appeal to an authority which supports you, not me.
“You need to appeal to an authority which supports you, not me.”
I wasn’t appealing to authority, I was pointing out that the ‘authority’ you quoted was the originator of the greenhouse effect, something you deny exists!
Gavin Schmidt believes that adding CO2 to air makes thermometers hotter! He is obviously ignorant and gullible, but at least not as ignorant and gullible as you.
It could be worse – you could have appealed to the authority of a faker, fraud, scofflaw and deadbeat like Michael Mann. I admit I don’t know whether he is more ignorant and gullible than Gavin Schmidt. Of the two, who do you think is dumber?
I was referring to Fourier (your source), nothing to do with Schmidt or Mann!
Fourier didn’t mention a “Greenhouse Effect”.
Fantasists like Schmidt and Mann did.
“Fourier didn’t mention a “Greenhouse Effect”.”
He certainly did as I quoted from his 1824 paper (citation above).
Fascinating, WE — its the best model I’ve seen (not that I’m any kind of expert on the subject).
Just the fact you used absolute Ts and not anomalies speaks volumes.
Complete and utter nonsense. The Earth is a large rotating blob of mostly glowing matter, slowly cooling because it is about 150,000 km from the Sun.
No “climate engine”, no “power”. A solid object on the surface heats up in sunlight, cools in its absence. As Fourier said, the Earth gives up all the energy it receives from the Sun to outer space, plus a little internal heat – currently about 44 TW, having diminished greatly over the past four and a half billion years.
Willis is too ignorant and gullible to accept reality, and still believes that adding CO2 to air makes thermometers hotter.
Like many others.
The Moon is cooler than the Earth because it has no atmosphere.
The nature of the atmospheric blanket does make a difference.
The questions, “How much of a difference?”
The question is not, “Does spectroscopy work?”
You are wrong.
And also hotter. Up to 127C or so.
Earth extremes are roughly -90 C to +90 C. The Moon, about 127 C to -133 C.
Didn’t you know that?
No, I’m not.
“Earth extremes are roughly -90 C to +90 C. The Moon, about 127 C to -133 C.”
The coldest temperature on the Moon is about -253ºC.
“The Moon is cooler than the Earth because it has no atmosphere.”
Also the time between sunset and sunrise at the Moon’s equator is about 13.5 times longer than on the Earth so the Moon’s surface is cooling in the absence of solar radiation for about 13.5 Earth days.
So?
We have already gone over your obsession with those 44 TW, or ~100 milli-Watts per square metre, of “the Earth cooling over 4.5 billion years” heat flow when compared to the solar input to the Earth’s surface “energy equation”, but let’s go through it again for any newcomers to the “argument”.
Davies & Davies (2010) summarised the “Earth surface heat flow” in Table 7 of that paper :
One of the authors then provided a map, in Figure 7 of Davies (2013), showing the concentration of that flow along the ocean floor dorsal ridges, with a maximum value of just under 1.25 W/m² :
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Tables of numbers are often useful, but I am a “visual” person that usually (though not always) requires things to be presented in a graphical format before I really “get” them.
The following shows the various “internal layers” of a 6° segment of a cross-section of planet Earth.
“Clearly” a zoomed-in version was required so that I could see what the heat flows were at the surface level. The result I ended up with, after adjusting line widths to the correct proportions, was …
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You remain laser-focused on the (constant) ~0.1 W/m² of internal heat loss flowing through the Earth’s surface, while insisting that the (annual average) ~160 W/m² from the sun should be completely ignored.
I have no idea why.
Willis,
A very nice piece of work.
Minor peeve:Gobi deserts protrude down into the hot zone. China surely?
Have you looked at the work of Don Hitchcock? His Ice Age maps with their icecap topographic data are a possible way forward for futher applications of your model, based on the hypothesis that its all about topography.
Thanks, Philip. If it’s “all about topography”, why would it work so well on a smooth sphere as in this model?
And you’re right, it’s not just the Gobi, it’s part of China as well.
w.
I suppose I’ll pluck a few things at random, and point out some problems, The above quote starts off with Willis claiming to be a simple fellow. I agree, and add that he is also ignorant and gullible.
Now, all of the surface receives solar energy based on its area, inclination to the Sun, and time of the year – not just the “hot zone”, which may or may not be hot at any given time. The fraction of solar radiation received is reduced by atmospheric attenuation. Willis goes on to say –
Well, maybe it’s news to Willis, but all of the Earth’s surface radiates energy to space – no “greenhouse fraction”.
Willis hasn’t the faintest idea what he’s talking about here. The Earth is roughly spherical, and the surface radiates in all directions – like all matter above absolute zero. Yes, downwards even. It doesn’t matter, any radiation from the surface proceeding towards a warmer interior simply has no effect. Just like the radiation from a block of ice won’t warm water.
The surface warms in sunlight, cools its absence. Overall, the Earth has cooled over the past four and half billion years – losing energy to space in the process.
None, as heat does not “flow” around a sphere. Radiation moves in straight lines – any radiation which starts off parallel to the surface does not follow it.
Willis is either ignorant, gullible, and delusional – or quite detached from reality. He obviously believes that adding to CO2 to air makes thermometers hotter.
Definitely a strange chap.
When attempting to “persuade” not just the person you are directly responding to but also third-party “silent watchers” that your arguments are worth thoughtful consideration, it is a (very) good idea to actively avoid limiting yourself to the “Name Calling (and/or Abuse)” level of Paul Graham’s “Debate Pyramid”.
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May I also suggest that you (re- ?) read the WUWT “Policy” webpage, which starts with the paragraph
and includes the following bullet-point, which has always resonated with me in my visits here.
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PS
No he doesn’t.
Neither do any of the other 8 billion people on the planet.
I’m not attempting to persuade anyone.
Of course he does. So does every climate scientist. I assume that you don’t, and accept the reality that the “greenhouse effect” is a myth.
Feel free to provide evidence that Willis and others who believe that adding CO2 to air makes thermometers hotter are not, in fact, ignorant and gullible.
“the reality that the “greenhouse effect” is a myth.”
Hardly, see this graph showing the difference between the ToA and the Earth’s surface, the greenhouse effect!
So the “Greenhouse Effect” is now a graph, is it?
A couple of points.
Your graph appears to show the presence of the Sun. The Sun doesn’t shine at night. Second, in any case, your graph shows that precisely no (no) energy is prevented from reaching outer space, after being emitted by the surface.
This graph was obviously prepared by an ignorant and gullible illusionist, for consumption by those more ignorant and gullible than himself.
“Your graph appears to show the presence of the Sun.”
No it does not.
“Second, in any case, your graph shows that precisely no (no) energy is prevented from reaching outer space, after being emitted by the surface.”
On the contrary, the pink curve shows the IR emissions that leave the surface and the blue curve shows the radiation that leaves the TOA. The difference between the curves is those surface emissions which are prevented from leaving by the atmosphere.
The graph was prepared by someone who understands physics and is clearly annotated, apparently you are unable to understand it!
So why is the surface emitting those frequencies? Due to magic, perhaps?
That would be the slightly bewildered mathematician, Gavin Schmidt, would it? The same Gavin Schmidt who authored the fairytale “Atmospheric CO2: Principal Control Knob Governing Earth’s Temperature”, I presume.
All of the energy emitted by the surface escapes to space. That’s why the surface cools each night, and also why the surface is no longer molten. You’re even more ignorant and gullible than Gavin Schmidt!
Think for yourself. Adding CO2 to air doesn’t make thermometers hotter, no matter what fantasies occupy Gavin Schmidt’s imagination.
No, the graph posted by “Phil” did not include “the presence of the Sun”.
A graph showing the equivalent (/ theoretical) black-body surface emissions from both the Earth and the Sun would be a variant of the attached image.
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Primarily because the Earth’s surface is heated by an annual average net heat flow of ~160 W/m² by the Sun.
What would be the equivalent “black-body surface emission curve” for an Earth whose (global average) surface temperature was determined only by the ~0.1 W/m² of internal heat loss ?
How do you explain the “notches” in the ToA curve that was measured by satellites posted by “Phil” ?
Mark, as you say
which was rather my point. Of course, the deceptive Gavin Schmidt somehow forgot to mention that.
You seriously don’t know? In any case “the notches” are meaningless, as the surface cools every night. No “heat” prevented from escaping to space. That’s why the Earth has cooled over the past four billion years or so, and continues to do so, as Fourier said.
Well, no, there is no “net heat flow” from the Sun. The Earth loses all the heat it receives from the Sun to outer space.
And adding CO2 to air doesn’t make thermometers hotter, which makes your belief in the mythical Greenhouse Effect look pretty ignorant and gullible, doesn’t it?
We are not attempting to determine whether (or not) ***I*** can “explain” the “notches” in the graph but whether the person who insists on calling everyone with an opinion they disagree with “ignorant and gullible” has an explanation for them.
You pointedly avoided actually answering the question(s) I asked.
The only “reasonable” conclusion to draw is that you are incapable of doing so.
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That specific point, at least, is correct.
Why should I? You pointedly avoided supplying any good reason for doing so.
Thank you for your worthless opinion. Your drawing abilities need improving.
Good, we seem to agree then, that the GHE which you can’t describe doesn’t depend on CO2 making thermometers hotter.
“So why is the surface emitting those frequencies? Due to magic, perhaps?”
It’s called Blackbody radiation, Stefan-Boltzmann and Wien’s law apply.
That graph is not from Gavin Schmidt but he has produced similar ones.
“All of the energy emitted by the surface escapes to space.”
As shown in the graph not all the surface emission escapes to space, some of it is recycled, causing the surface temperature to increase until the emission to space equals the incoming solar radiation.
What a load of rubbish! All the surface Sun-sourced emission escapes to space each night. That’s why the surface cools. Not only that, the surface continuously loses 44 TW – even while the Sun is shining.
No solar radiation at night, you pillock. Go on, show me one of your “graphs”.
Adding CO2 to air does not make thermometers hotter. Accept reality, Phil.
“All the surface Sun-sourced emission escapes to space each night. That’s why the surface cools. Not only that, the surface continuously loses 44 TW – even while the Sun is shining.”
Not all the energy from the sun ‘escapes to space’ at night, some of it is stored mostly in the oceans (~89%). Also the blackbody radiation from the surface continues while the sun is shining (order 100,000 TW).
You’re right. As Fourier said, the influence of the Sun may be felt up to about 10 m below the ground surface. All the energy from the Sun is lost to space, eventually.
I should have said that no energy in photons emitted by the surface is prevented from being lost to outer space by the atmosphere. The surface cools at night, you ninny!
Even the sea surface, which leads to the deep bottom waters being at their maximum density. You are probably too ignorant and gullible to comprehend the reason.
Do you still believe that adding CO2 to air makes thermometers hotter?[chuckles]
“You’re right. As Fourier said, the influence of the Sun may be felt up to about 10 m below the ground surface. All the energy from the Sun is lost to space, eventually.”
Only once the sun stops shining!
“I should have said that no energy in photons emitted by the surface is prevented from being lost to outer space by the atmosphere.”
And you’d still be wrong. Photons in the 15μm band will be intercepted by CO2 molecules, other frequencies intercepted by water and ozone, take a look at the graph I provided.
“Only once the sun stops shining!”
No, the earth loses heat it receives from the sun even during daylight. As the temperature goes up linearly during the day the heat loss goes up by T^x (where x = 4 for a blackbody). The higher the daytime temp goes the faster the earth loses heat than it gains it. It’s a boundary condition on Tmax. Once Tout = T^x equals Tin you have reached equilibrium even during the day. It’s why the daytime temp curve bends over like a sine wave instead of just linearly increasing.
““Only once the sun stops shining!”
No, the earth loses heat it receives from the sun even during daylight.”
Of course it does, I’ve posted that too.
What I was responding to was:
“All the energy from the Sun is lost to space, eventually.”
Which as I said would only be true once the sun stops shining (not nighttime).
This is the piece that leaves me wondering.
If the recycled emissions cause the surface temperature to increase, then the surface must radiate more. If the surface radiates more, then more must be radiated backward which warms the earth further. Which then cause the surface to radiate more, and then more to be radiated backward, and so on and so on. When does this process cease? What causes it to cease?
You know you won’t get an answer, right?
Planck specifically says that *reflected* heat gets immediately resent by new rays from a black body, it does not say that the temperature of the black body goes UP. What happens is the heat loss from the internals of the black body goes down – i.e. the black body cools at a slower rate.
Heat is is a time function. A black body does not stay at the same temperature over time unless there is a heat source in equilibrium with it. A heat reflector is not a heat source so the black body will continue to cool in the presence of a heat reflector. The rate at which the cooling happens will be dependent on how much heat is reflected. If CO2 is a heat reflector then increasing the reflection coefficient will only cause the earth to cool at a slower rate. It will not increase the internal temperature of the earth and thus will not increase the flux into space.
E_space(t) = E_reflected(t) + E_internal(t)
E_interal(t) = E_space(t) – E_reflected(t)
Unless E_reflected(t) = E_space(t), E_internal(t) will remain positive, i.e. cooling.
Tim Gorman
Reply to
Jim Gorman
December 23, 2025 9:01 am
I just gave him the answer. It’s basic stuff.
w.
As with any positive feedback which is less than one, it will not go on forever. The final equilibrium value will be 1/f, where f is the feedback factor.
So for example if half the signal is fed back, the final value will be 1/0.5 = 2 times the original signal.
w.
Ummmm…. 1/f implies several questions which need to be answered.
“So for example if half the signal is fed back, the final value will be 1/0.5 = 2 times the original signal.”
The input from the sun doesn’t change so how does the output become greater than the input? If you had full feedback (f = 1) your equation would say the output equals the input (1/1). So how does the output get greater when the feedback is less than 1?
Almost all feedback analyses I’ve seen for the “greenhouse” never say where the extra power comes from in a passive circuit like the biosphere that can make the output greater than the input.
Meaningless word salad. Phil has no understanding of physics – he even believes that adding CO2 to air makes thermometers hotter!
Would you expect any sense from such a delusional person?
Welcome to Flynn’s “ignorant and gullible” club Willis!
Well, maybe it’s news to Willis, but all of the Earth’s surface radiates energy to space – no “greenhouse fraction”.”
Willis’s ‘greenhouse fraction’ includes clouds, no clouds on your planet Flynn?
“The Earth is roughly spherical, and the surface radiates in all directions – like all matter above absolute zero. Yes, downwards even.”
Radiation downwards into the soil? No, that flow is conduction!
None, as heat does not “flow” around a sphere. Radiation moves in straight lines – any radiation which starts off parallel to the surface does not follow it.”
Willis referred to ‘buoyancy-driven atmospheric circulation’ in other words convection, so yes heat does flow around a sphere which has an atmosphere!
Willis is talking about the real Earth not the one in your head Flynn, a molten one which has no atmosphere!
This one?
Maybe you are confused, as well as ignorant and gullible.
No, I’m talking about the Earth upon which we live. If you don’t want to believe the Earth is >99% glowing hot, you don’t have to.
“If you don’t want to believe the Earth is >99% glowing hot, you don’t have to.”
It certainly doesn’t glow hot anywhere near where I’ve lived!
And that proves precisely what?
That you don’t know what you’re talking about!
Maybe you should move to Hawaii, Iceland, or any place where glowing magma from the interior can be observed. The Earth consists of more than 99% glowing matter.
Luckily, most of the surface is no longer that hot, after four and a half billion years.
Yes which is why the heat from ‘glowing magma’ is an irrelevancy when considering the heat balance of the Earth.
I see we are once again blessed with the presence of the charming, kind, compassionate Michael Flynn, the man who never lets an ugly, meaningless, petty ad hominem insult go unspoken … his latest example is “Willis is either ignorant, gullible, and delusional – or quite detached from reality.”
Sigh …
Folks, my best advice is, never bother him with those actual scientific “fact” thingies.
You know, those weird beliefs like the idea that heat flows from the warm equator to the cold poles. He’ll get angry, scream at you, call you names, and tell you with a straight face that “heat does not ‘flow’ around a sphere.”
Michael does have one amazing ability—he can ignore any amount of reality, no matter how large.
So let me suggest that we all let him rave in solitude, and that we leave him, unanswered, to his fitful dreams of worlds where heat doesn’t flow from warm to cold. It seems such curious fantasies soothe his soul, and who are we to gainsay that?
I do wish we could bring him to his scientific senses, but I’ve tried, and sadly I found that, as the Doctor in Macbeth says, “This disease is beyond my practice.”
My best to all, including Michael,
w.
Thank you so much, Willis.
You forgot to mention my modesty, which is only exceeded by my humility, but I’ll let you catch up next time.
Unfortunately, your “best” is somewhat less than many other people’s “worst”, so I’ll pass if you don’t mind.
Hi Willis, it’s great to see a simple climate model that actually works. My experience (40+ years modelling) has been that if you can’t get a reasonable match with a simple model then making it more complex won’t make it any better, just harder to interpret. But here’s the stumper: what causes climate change? Not the piddly recent warming your simple model can explain, but the 6 ºC increase in global temperature that happened between 17 and 14,000 years ago at the end of the last ice age. It wasn’t GHG so something quickly changed Earth’s albedo before temperatures changed, I.e. your work indicates something melted the ice sheets before temperatures rose. Well done.
Strictly speaking, albedo is the relative retro-reflectance of a diffuse reflector, which reaches a maximum for an astronomical body when the observer is in line with the central rays of the light source. Whereas, what is needed for net energy modeling is all the EM energy leaving the surface of the Earth, 71% of which is covered by water, a specular reflector. Thus, most measurements of albedo only result in a lower-bound for energy leaving the Earth system except for nadir-viewing geometries. Even thermal IR measurements only actually measure a small solid-angle of exiting thermal energy. The net cooling loss of energy is composed of 1) diffuse retro-reflectance (albedo), 2) diffuse reflectance outside the cone of observation (always a solid angle much less than 2X an angle of incidence of 45 deg), 3) specular reflectance measurable from the nadir viewing geometry, 4) specular reflectance that is reflected forward and is only measurable looking towards the source (sun), and thermal IR emitted in a hemispherical radius in equal amounts for viewable points. The total energy cannot be measured directly and must be derived by integration from a bi-directional reflectance distribution function (BRDF). The important point is that all reflectors vary with the angle of observation, but specular reflectors especially.
https://wattsupwiththat.com/2016/09/12/why-albedo-is-the-wrong-measure-of-reflectivity-for-modeling-climate/
I think we can all agree that a pregnant cow would make more realistic climate predictions than most current “climate models”
Well done Willis; I love that it comes from a man up a mountain, not an ivory tower.
This needs a wider audience than just WUWT; please publish & get it mainstream.
Thanks, 1save. Working on it.
w.
Hi Willis
I think you might have to wait until you’ve departed this reality before you find fame, like Alfred Wegener, Ignaz Semmelweis, Gregor Mendel, Copernicus, Kepler, and Avagadro. Some accepted beliefs are difficult to replace.
and possibility until Hell freezes over? He believes that adding CO2 to air makes thermometers hotter! And you?
Nice article. I appreciate the implementation of KISS. Current GCM’s just aren’t amenable to a global view for a number of reasons. Attempting to globalize a temperature database derived from such a large number of stations all lumped into a single average is doomed from the beginning.
GCM’s should become RCM’s, regional climate models. If you can’t model and predict regions, the whole will never be correct. The entirety of a system is a sum of its parts. KISS means minimizing the parts, as you have done. Whether yours turns out correct, or at least a good approximation, only time will tell. I think it is a good start.
“So the equilibrium climate sensitivity is about 1.1°C per doubling of CO₂.
But wait, there’s more. And this is important. This value is a maximum estimate because the model doesn’t include negative feedbacks from a host of emergent climate phenomena like thunderstorm responses, El Nino/La Nina events, tornadoes, and other phenomena which I’ve written about extensively in my thunderstorm thermostat posts. Those feedbacks all oppose surface warming by transferring heat from the surface to the atmosphere. As a result, the real climate sensitivity is likely lower than shown above.”
Might not the albedo also change following a change in CO₂? I am thinking especially of induced changes in cloud cover.
As well as a ‘greening’ effect as documented by NASA, which shows the CO2 is acting as a stimulus for plant growth and probably marine photo-synthesizers as well.
Yup all these “sensitivity” numbers are is a ceiling incorporating the assumption “all other things held equal.”
Which they have never been, are not now, and never will be. Once the clearly negative, offsetting feedbacks occur, the actual, as opposed to hypothetical, “effect” of atmospheric CO2 is indistinguishable from zero.
As confirmed by the Earth’s climate history. Glaciation with ten times today’s atmospheric CO2 doesn’t happen if atmospheric CO2 is a “climate driver.” Nor do repeated episodes of reverse correlation between atmospheric CO2 and temperature.
Good work, Willis!
I appreciate your interest driven effort in discovery.
Doing a cursory reading of this article reminds me of just how much my skepticism of everything NASA/Climate connected has increased over the years. For instance, looking at your Figure 12, we see that NASA has a specialized satellite called CERES, that can determine just how much the percentage of upwelling thermal, longwave IR, radiation is absorbed in the atmosphere for various points around the globe? So, somehow, the satellite can get right down on the ground, figure out how much upwelling thermal IR is there, and then move higher up and figure out how much of that has not been ‘disappeared’ somehow, to continue on up into space from the top of the atmosphere as such? Notwithstanding a nice graphical map there in the figure, I for one might have thought that a satellite could *only* detect what is actually arriving in outer space where the satellite is located!
Having said that, I hope you will excuse my lack of knowledge, if I am missing some key info as to earth monitoring satellites actually work. I just continue to see more confusion than enlightenment in all the various things that conventional climate theory claims must be true! Say, talking about spherical cows, for instance, does the CERES satellite also separate out how many tens or hundreds of times more IR absorption is done by a typical methane ‘cow burp’ molecule versus a regular old CO2? Does water vapor count — or, maybe in this model, such often mentioned details really don’t matter?
David, perhaps instead of doing “cursory reading” you might do some actual research before uncapping your electronic pen. All of these types of questions are answered in the CERES documentation.
For example, you could start by reading pages 12-13 of this document. It describes the details of the calculation of the SARB (Surface and Atmosphere Radiation Budget).
Best regards,
w.
Thanks for that rather impressive looking 20 page document. This paper is titled “Clouds and the Earth’s Radiant Energy System (CERES) Algorithm Theoretical Basis Document: CERES Algorithm Overview”. I see bad things along with perhaps some good things there. Never mind pages 12 and 13 to start with, how about the “scientific objectives” statement” near the top of this paper (page 3) where the number one bullet point says “Changes in the radiative energy balance of the Earth-atmosphere system can cause long-term climate changes (including a carbon dioxide induced “global warming”).” Now, this is expressly presented as the top “scientific justification” for the whole CERES project as such? I mean, no fooling, the intro to the three bullet points clearly states that “the scientific justification for the CERES measurements can be summarized by three assertions:”, etc, with the idea of making the assertion that CO2 induces global warming as the top priority!
Well, what’s wrong with that, you may ask? We all know that that august Nobel Prize winner Arrhenius got this correct all the way back at the start of the twentieth century, right? So if someone is willing to build a gigabuck satellite system, supercomputer algorithms, etc, expressly to prove this some more, why that’s not bias or anything, it’s just sensible really?
For contrast, take a look at the current issue of the Heartland Institute Climate Change Weekly, i.e., the issue # 566 just lately posted, and particularly, note the section titled “An Alternative Causal Mechanism for Climate Change Proposed”. The point of this article is effectively to flatly contradict the ‘CO2 boosts climate warming’ idea, by way of building upon the evidence that pre-existing warming trends cause CO2 to rise *later*, *after* the warming has already happened! This is seemingly notwithstanding any molecular IR related concepts that seem to point the direction of cause and effect to the conventional ‘CO2 rise causes warming’ way.
Now, getting down to your page 12 in the CERES article reference, I see a **lot** of jargon there, and I mean all kinds of algorithmic considerations to do with folding existing surface data in with cloud imaging picked up by the CERES satellites, etc. Now, a certain amount of ‘hard for any novice to digest’ jargon is to be expected, and I don’t want to be the kind of ‘alternative thinker’ who would critique from a lack of understanding. Unfortunately, one of the basic problems here is that if the technicalities are really all *working to a certain conclusion*, it then becomes really difficult to scrape away the verbal specialist fog? How do we have any sense of confidence that we are not just getting the fulfillment of the mission statement set out at the beginning?
If I go back to page 4 of the CERES paper, here is a little snippet of the sort of wording that we get in this document:
”
Angular Sampling
• ERBE used empirical anisotropic models which were only a function of cloud amount and four surface types (Wielicki and Green 1989). This caused significant rms and bias errors in TOA fluxes (ATBD subsystem 0, Suttles et al. 1992).
• CERES will fly a new rotating azimuth plane (RAP) scanner to sample radiation across the
entire hemisphere of scattered and emitted broadband radiation. The CERES RAP scanner data will be merged with coincident cloud imager derived cloud physical and radiative properties to develop a more complete set of models of the radiative anisotropy of shortwave (SW) and long-wave (LW) radiation. Greatly improved TOA fluxes will be obtained
”
So, that not only tells you something about what they are doing with this, it also happens that there is a key word that jumps out a couple times here.
The word is model. Yes, it is undoubtedly, really true that when you do graphs of most of the CERES results, you are *not* doing graphs of basic data, like surface temperatures inferred from IR spectrum detected, or something as basic as that. What you are doing is plotting the final output of the grand CERES algorithm, or model. Some people call this data, but is it really just data?
Perhaps it would help if something like Figure 12 in the head posting here were clearly labelled “Plot of CERES Model Outputs”, say, or something else with the word ‘model’ expressly in the title as such, or maybe even in the graph’s lower caption?
As it stands, the figure’s starting title is ‘Average Greenhouse Factor’, etc., with no mention that it’s really just a computer model output. Lower down, the caption states ‘DATA: CERES EBAF 4.2’, etc.
So, it is good, solid, measured ‘data’, but, is it really?
https://wattsupwiththat.com/2023/03/06/the-misguided-crusade-to-reduce-anthropogenic-methane-emissions/
Thanks for that. In my initial post here yesterday, one of my skeptical concerns was the methane crusade, something so persistently promoted by many, but perhaps not all (?), of the conventional climate theory makers.
dq/dx = 0 [Equation 4]
This means dq=0 and dx <> 0. Why is q invariant? Why is x always changing?
Wouldn’t dx go thru zero to reverse direction? That would result in infinities would it not?
At the peak of any curve, the differential goes to zero.
w.
Willis, looking at the math you wrote:
So the fourth equation is simply:
=========
However, Equation 4 is true if and only if dq is 0 and dx is not zero. All other values are forbidden. However if dq=0 then q cannot change and the model cannot adjust the flow and if dx can never be zero then the fraction of the earth in the hot zone must always be increasing or decreasing, it can never reverse direction because to do so dx must pass thru zero which would leave the model undefined. And if x is always increasing there is no cold zone and if x is always decreasing there is no hot zone. Which leads to problems decreasing x beyond 0% and increasing x beyond 100%
I don’t understand your claim. Any curve that increases to a peak and then decreases has a first derivative dq/dx of zero at the peak. However, that does not mean that “q cannot change”. It’s just the derivative at that point. Below that, the derivative is positive; above that, the derivative is negative.
Regards,
w.