Guest Post by Willis Eschenbach
I ponder curious things. I got to thinking about available solar energy. That’s the amount of solar energy that remains after reflection losses.
Just under a third (~ 30%) of the incoming sunshine is reflected back into space by a combination of the clouds, the aerosols in the atmosphere, and the surface. What’s left is the solar energy that actually makes it in to warm up and power our entire planet. In this post, for shorthand I’ll call that the “available energy”, because … well, because that’s basically all of the energy we have available to run the entire circus.
Now, I don’t agree with the widely-held idea that the planetary temperature is a linear function of the “radiative forcing” or simply “forcing”, which is the amount of downwelling radiation headed to the surface from both the sun and from atmospheric CO2 and other greenhouse gases. Oh, the radiation itself is real … but it doesn’t set the surface temperature
My theory of how the climate operates is that the globe is kept from overheating by a variety of emergent phenomena. These phenomena emerge when some local temperature threshold is exceeded. Among the most powerful of these emergent phenomena are thunderstorms. In the tropics, thunderstorms emerge when the sea surface temperature (SST) is above about 27°C (80°F) or so. Here’s a movie I made of how the thunderstorms follow the sea surface temperature, month after month.
Figure 1. Tropical thunderstorms are characterized by tall cloud towers. The average altitude of the cloud tops is therefore a measure of the number and strength of the thunderstorms in the area. Colors show average cloud top altitude, with the red areas having the most and largest thunderstorms, and the blue areas almost none. The gray contour lines show sea surface temperatures (SSTs) of 27°, 28°, and 29°C, with the inner ring being the hottest.
Thunderstorms cool the surface in a variety of ways. They waste little energy in the process because they emerge to cool the surface only where it will do the most good—the hottest part of the system.
Among the ways thunderstorms cool the surface is via an increase in the local albedo. Albedo is the percentage of energy reflected back to space. The increase in this reflection (increasing albedo) occurs because the thunderstorm clouds both cover a larger area and are taller than the cumulus clouds that they replace. Their height and area provide more reflective surfaces to reject solar energy back to space.
In addition, the thunderstorm generated winds increase the local sea surface reflectivity by creating reflective white foam, spume, and spray over large areas of the ocean. And finally, a rough ocean with thunderstorm-generated waves reflects about two times what a calm ocean reflects (albedo ~ 8% rough vs ~ 4% smooth). That change in sea surface roughness alone equates to about 15 W/m2 less available energy.
Now generally, we’d expect that additional solar energy would be correlated with warmer temperatures. It’s logical that the relationship should go like this:
More available solar energy –> more energy absorbed by the surface –> higher temperatures.
We’d expect, therefore, that both the available energy and the temperature should be “positively correlated”, meaning that they increase or decrease together. And in general, that’s true. Here’s the available solar energy, which is the sunshine that makes it past all of the reflective surfaces, the sunlight that is the one true source of all of the energy that heats, agitates, and powers the climate.
Figure 2. Available solar energy after all reflection from clouds, atmosphere, and the planet’s surface. The numbers are 24/7 averages.
As you can see, the poles are cold because they only get fifty watts per square metre (W/m2) or so from the sun. And the tropics get up to 360 watts per square metre (W/m2), so they are hot. The tropics are the main area where energy enters the system, and they’re also the hottest.
So far, what we see agrees with what we’d expect—available energy and temperature are correlated, going up and down together.
Now, my theory is that emergent phenomena act to constrain the maximum temperature. So an indication that my theory is valid would be if the amount of available solar energy were to not only stop increasing at high surface temperatures, but would actually go down with increasing temperature when the SST gets over about 27°C.
To see if this is the case, I turned once again to the CERES data, available here. I’m using the EBAF 4.0 dataset, with data from March 2000 to February 2019. The CERES satellite data has month-by-month information on the size of the incoming and reflected solar energy flows. The information is presented on a 1° latitude by 1° longitude gridcell basis.
According to the CERES data, incoming solar energy at the top of the atmosphere (TOA) is ~ 340 W/m2. The total reflected is ~ 100 W/m2. That leaves 240 W/m2 of available energy to warm the world. (Numbers are 24/7 global averages.)
To investigate the relationship between the surface temperature and the available energy, I looked at just the liquid ocean (not including sea ice). I do this for several reasons. The ocean is 70% of the planet. It is all at the same elevation, with no mountains to complicate matters. There’s no vegetation sticking up to impede the winds. It is a ways from human cities. All of this reduces the noise in the data, and makes it possible to compare different locations.
What I’ve done is to make a “scatterplot” of available energy versus sea surface temperature (SST). Each blue dot in the scatterplot below shows the available solar energy versus the sea surface temperature (SST) of a single 1°x1° gridcell.
Then I’ve used a Gaussian average (yellow & red with black outline) to see what the data is doing overall. (In this dataset, it turns out that the Gaussian average is basically indistinguishable from averaging the data in bins of a tenth of a degree (not shown). This lends support to the validity of the line.) The yellow/red line outlined in black shows the 160-point full-width-half-maximum (FWHM) Gaussian average of the data. The red area simply highlights the part above 27°C.
Figure 3. Scatterplot of available solar energy versus liquid sea surface temperature. Blue dots show the results for each 1° latitude by 1° longitude gridcell. Yellow/red line is 160-point full-width-half-maximum (FWHM) Gaussian average. The part of the data where the average SST above 27°C is highlighted in red
In Figure 3 we see that above ~ 27°C, the thunderstorm initiation temperature, the available solar energy stops rising, takes a ninety-degree turn, and starts dropping. You’ve heard of things being “non-linear”? This graph could serve as the poster child of non-linearity …
It’s worth noting that at temperatures from about 3°C to 27°C, the temperature is indeed a linear function of the available solar energy. So the common misunderstanding is … well … understandable. In that temperature range the sea surface is going up about 0.1°C per additional W/m2, which is the same as ~0.4° C per doubling of CO2 … but of course, that ignores the area in red, where the relationship is totally reversed and energy goes down as temperature goes up.
This is strong support for my theory that emergent phenomena actively regulate the global temperature and constrains the maximum temperature. It is also evidence against the current theory of how climate works, which is that the temperature slavishly follows the available energy in a linear fashion … as I noted, this is as non-linear as you can get..
In the areas where the sea surface temperature is over ~ 27°C there is less and less energy available with each additional degree C of surface warming. The size of the decrease is large—6.6 W/m2 less energy is available when the surface temperature has risen by each additional 1°C.
Figure 4 shows the location of these areas (shown in blue/green with white borders) where available solar energy goes down when the temperature goes up (negative correlation).
Figure 4. Gridcell by gridcell correlation of available solar energy and surface temperature. Blue box show the tropical area discussed below (130°E – 90°W longitude, 10°N/S latitude).
Investigating the energy flows further, loss of incoming energy via increased albedo is only one way thunderstorms cool the surface. It is an important method of thermoregulation because it acts just like the gas pedal in your car—the thunderstorms are controlling the amount of energy entering the planetary-scale heat engine we call the climate. And above a sea surface temperature of ~ 27°C, they are cutting the incoming energy down.
The thunderstorms which are cutting down the total available solar energy are also cooling the surface in a host of other ways. First among these is evaporation. Thunderstorms make rain, and it takes solar energy to evaporate the rain. That energy is then not available to heat the surface.
Figure 5 Scatterplot of the sea surface temperature versus the rainfall in the equatorial Pacific area shown by the blue box above (130°E – 90°W, 10°N/S). The blue dots show results from the TAO moored buoys in the blue box. The red dots show gridcell results from the Tropical Rainfall Measuring Mission (TRMM) satellite rainfall data and Reynolds OI sea surface temperatures. Graphic from my post Drying The Sky
Figure 5 above has SST data from two separate datasets, Tao buoys and the Reynolds OISST dataset. It also has rainfall data from two separate datasets, the TRMM data and TAO buoys. They agree very well, giving support to the relationships displayed.
And once again, it is highly non-linear …
Because the tropical oceanic thunderstorms are temperature related, so is the rain. Above 27°C, every single 1°x1° gridcell (red dot) and every TAO buoy (blue dot) in the equatorial Pacific area outlined in blue in Figure 4 above has rain.
In addition, by the time the open ocean temperature reaches its maximum value of 30°C, almost every gridcell has nearly three meters (ten feet, or 120″) of rain. At high sea surface temperatures, rain is not optional. This is clear evidence of the thermal nature of the thresholds involved.
It’s an important point. The thresholds for all of these emergent temperature-regulating climate phenomena (e.g. dust devils, cumulus fields, thunderstorms, squall lines) are temperature-based. They are not based on how much radiation the area is receiving. They are not affected by either CO2 levels or sunshine amounts. When the tropical ocean temperature gets above a certain level, the system kicks into gear, cumulus clouds mutate into thunderstorms, albedo goes straight up, and rain starts falling … no matter what the CO2 levels might be. Temperature-based, not forcing-based. It’s an important point.
And below is the rainfall data from 40° North to 40° South, expressed as the amount of energy needed to evaporate the rain.
Figure 6. Scatterplot of 1° x 1° gridcell annual average ocean-only thunderstorm evaporative cooling on the vertical axis, in watts per square metre (W/m2) versus 1° x 1° gridcell annual average sea surface temperature on the horizontal axis. Evaporative cooling amount is calculated from the rainfall—it takes ~ 80 W/m2 for one year to evaporate a metre of rainfall. Graphic from my post, How Thunderstorms Beat The Heat
As I write this, I think hmm … I could use the relationship shown in red above, between tropical sea surface temperature and evaporative cooling. Then I could add that TRMM data to the solar availability data to see how much is available after albedo and evaporation. Hmm … I’m off to write a another bunch of code in the computer language simply called “R”.
(Best computer language ever, by the way, and R was something like the tenth computer language I’ve learned. It’s free, cross platform, free, killer free user interface “RStudio”, free packages to do almost anything, good help files, and did I mention free? I owe Steve McIntyre an unpayable debt for convincing me to learn to code in R. But I digress, I’m off to write R code …)
…
OK, here’s the result. The scatterplot as above, scale about the same, but this time showing what’s left after removing both albedo reflections and the energy used for evaporation. This covers the area where rainfall was measured by the TRMM, from 40° N latitude to 40° S latitude.
Figure 7. Scatterplot, available solar energy minus evaporative cooling, versus sea surface temperature from 40°N latitude to 40°S latitude. Because it is only the middle latitudes the ocean doesn’t get much cooler than 15°C.
I note that when we include evaporative cooling, the drop in available energy starts at a slightly lower temperature, 26°C vs 27°. And it is decreasing much faster and further than just the 6.6 W/m2 decrease per degree of degree warming from albedo alone as shown in Fig. 3 above.
Figure 7 shows that there is 44 W/m2 less available energy per additional degree of warming above 26°C. So it is decreasing about seven times as fast as from albedo alone. On average there is less energy left over for warming at 30°C than at 15°C … go figure.
And finally, here’s the distribution of the solar energy once we’ve subtracted the reflected energy and the energy used for evaporation. What remains is the energy available to heat the planet and to fuel plant growth.
Figure 8. Available solar energy after albedo and evaporation losses. TRMM data only covers from 40° N to 40°S latitude.
Note that there are some areas of the oceans where any additional solar forcing goes into increasing clouds, increasing thunderstorms, and increasing evaporation, with little to nothing left over to heat the area …
Now, remember that my hypothesis is that the widely-believed claim that there is a linear relationship between forcing and temperature is not correct.
Instead, I say emergent phenomena come into existence when a temperature threshold is passed, and that they act to oppose further heating.
My main conclusions out of all of this? It supports my hypothesis regarding emergent phenomena regulating the temperature, and this is clear evidence that temperature is NOT a linear function of forcing.
And on a side note, the US passed a sad milestone today—the number of COVID pandemic deaths (a once-off phenomenon) finally equaled two-thirds of the annual number of deaths from obesity. In the face of this hidden gustatory emergency of 300,000 US obesity deaths per year, I recommend mandatory gastric banding of the entire populace and fine-enforced social distancing from donuts …
My best regards to everyone, end all lockdowns, the emergency is over. Let’s get back to work, school, and play,
w.
The Small Print: When you comment please quote the exact words you are discussing, so we can all be in on the secret subject of your ideas.
-Very interesting…….the total amount of energy that tropical thunderstorms represent in a single day probably compares with some no. of nuclear weapons energy. Will Scientific American publish this paper? The vast oceans are a main reason Mars and Venus are not comparable to earth when comparing climate. Maybe these observations are finally the CO2 killer?
Wow. This one’s a keeper. Thank you Willis.
I agree, very excellent post Willis!
“The thunderstorms which are cutting down the total available solar energy are also cooling the surface in a host of other ways. First among these is evaporation. Thunderstorms make rain, and it takes solar energy to evaporate the rain. That energy is then not available to heat the surface.”
They ( the thunderstorms) are cooling the surface in a way not mentioned. They are greatly reducing SW insolation into AND below the ocean surface, where said energy has a very long residence time, and us lost to the surface for up to 1000 years!
So, in a magical world, even if there were no clouds, the ocean warming would not follow the surface warming of land, as a percentage of the increased incoming W/SQm would go below the surface and not affect the surface air T, except to stabilise it and raise the mean T over time.
Super article–but it seems to me you are doing the work that should have been done by all the “climate scientists”.
Thanks.
There are climatologists, and there are climate “scientists”. The two sets are disjoint.
When I was in engineering school in the 1970s, I saw a poster in the “operations research” department (data science modeling) that I still remember.
It showed Snoopy dancing gleefully (a popular meme back then) with a caption that said, “Happiness is assuming linearity!”
Willis — you are going to make the modelers sad!
Ed Bo,
The idea of approximate linearity around the mean between T and W/m^2 seemed to originated with Schlesinger back in the 80’s when he was trying to fix Hansen’s erroneous feedback paper (1984) in order to shoe horn Bode’s LINEAR feedback amplifier analysis to the climate system, which at the time was the holy grail they needed to make a sensitivity large enough to justify the creation of the IPCC seem plausible.
One of the only 2 preconditions for using Bode’s analysis is linearity across all possible inputs and outputs which approximate linearity around the mean doesn’t satisfy anyway, but people can be fooled into thinking that it does.
The other precondition is an implicit source of Joules to provide the output power, that is, input power is not consumed to contribute to the output power which originates from an implicit power supply. Schlesinger tried to claim that the average not accounted for by the incremental analysis was the power supply, but once more, this doesn’t actually satisfy the precondition; moreover; it assumes non linearity!
Two wrongs don’t make a right, but far too many are easily fooled into thinking that it does.
This admirable comment by co2isnotevil is one sound way of telling why the orthodox Hansen–Schlesinger “forcing and feedback” formalism is nonsense. But there are also other sound and cogent ways. The Bode theory assumes that the driver input is an external factor entirely independent of factors internal to the system. This Bode assumption is violated in the Hansen–Schlesinger “forcing and feedback” formalism, in which the “forcing”, its hybrid version of the “driver”, is derived from the CO2 level along with factors internal to the system, that depend on system temperature, the prime internal variable. The physical reason for Bode’s assumption is that it expresses that the Bode model obeys and exhibits causality. Because the Hansen–Schlesinger formalism doesn’t obey the Bode assumption, it doesn’t obey causality, and consequently is unphysical, or nonsensical. I do not understand why this is not more widely recognised.
No, mad….
As in insane……
Sad indeed for lineal models, as this thunderstorm activity also greatly shortens the residence time of TSI. When you accelerate the hydrological cycle you require massive amounts of energy that is NOT converted to heat, but to moving mass/energy within the system, and towards the exit from the system; aloft and poleward!
( So it is not just the Albedo increase that decreases incoming radiative energy residence time, but an accelerated hydrological cycle also decreases the conductive and convective residence time of energy within the atmosphere.)
Measuring temperature does not indicate the level of energy with any precision without knowing precise absolute humidity levels. Measured temperature changes wildly at a given level of energy because energy changes forms through condensation and vaporization.
I might think that thermodynamic models of thunder storms are pretty well understood. It is merely a matter of looking up the common humidity levels contained in tropical atmospheres when the sea level temperature is near or above 27 °C. When at saturation all that is required is a minor drop in air pressure or air temperature caused by rising circulation patterns and voila.
The measures of enthalpy for air has been well understood since the steam age.
Even 150 years hence it was required curriculum when I was in school. How exactly do you think nuclear energy turns a turbine? Steam is steam is steam.
Definitely was in the curriculum when I was doing my Mech Eng degree. Dry steam being the preferred form 😀
The thermodynamic models of thunder storms might be understood – but the problem is likely that the minimum grid sizes in the climate models preclude the addition of transient phenomena like clouds and thunderstorms.
Or put another way: the climate models are Newtonian when climate is really quantum (an analogy, not literally).
Mario:
You are correct with regard to atmospheric temperatures — we really ought to be using “moist enthalpy” instead.
But the temperatures Willis is using in this post are the surface temperatures of the liquid ocean, not the atmosphere.
Willis is above my pay grade with analysis and presentation of data, and explanations of complex physics. I get caught up in the parts that I do understand – and – that make it hard for me to accept data and then to use it to form conclusions. Willis’ is amazing at doing it for us all to think about.
I get so fixated on the idea that climate and temperature are so linked in our conversations when really, temperature is not the (complete) thing that tells us how much energy there is accumulating or waning from the planet. It’s just a convenient way to measure part of the answer to a question.
It’s surrounds a story I tell people… it’s way more likely that drought causes high temperature, rather that high temperature causes drought.
This seems an appropriate thread to pose a question which has been puzzling be for a while now.
Albedo , is basically reflection of solar energy into space. Snow and ice have a high albedo, and reflect more energy than open water. Fine so far. But in the polar winter there is no solar radiation to reflect so all any energy lost into space is by Radiative Cooling from sea, ice,snow or atmosphere. So the question is more energy lost by Radiative Cooling in winter than is reflected as a result of the albedo of snow and ice.
How is this handled in climate models?
“How is this handled in climate models?”
Depends on what you want the climate model to conclude.
(Whatever the result, it will “worse than we thought” 🙂 )
Mr
Worse than we thought is so 2019
2020 is Even worse than worse than we thought!
Unprecedented is the word you are looking for I believe
It sounds like the accountant who, when asked by his client how much profit he had made, answers ‘how much do you want it to be?’
On a side note, the BBC is already starting to get worked up about COP26. I dread to think what the next 12 months evangelising will be like.
“How is this handled in climate models?”
Incorrectly.
The effect of melting ice is also misrepresented where since 2/3 of the planet is covered by clouds, which reflect about the same as ice and snow, only 1/3 of the newly exposed land has an influence on the albedo and only during summer months as it’s still would be covered by snow in the winter.
If the Earth was completely devoid of ice and snow 12 months of the year and the incremental solar input is amortized across the planet, the W/m^2 available are still not enough to offset the extra 3 W/m^2 or so of emissions claimed to be caused by 1 W/m^2 of forcing, above and beyond the average 1.62 W/m^2 of surface emissions per W/m^2 of forcing which is erroneously referred to as the ‘before feedback’ sensitivity. The actual before feedback sensitivity is 1 W/m^2 of surface emissions per W/m^2 of forcing characteristic of an ideal black body and is about 0.2C per W/m^2 at the average temperature of the surface. The total feedback power is 620 mw per W/m^2 of forcing resulting in a post feedback sensitivity of 1.62 W/m^2 (0.3C) per W/m^2 of forcing.
The 3 W/m^2 is in the noise. Error is at least 4 W/m^2.
Fascinating analysis, Willis. So the addition of forcing elements, like the evil CO2, into the atmosphere will have their effect mitigated by a non-linear response? The zone of maximum thunderstorm formation might expand in latitude, but the moderation process will save the earth? I know for sure when I am on vacation in the Caribbean it is not as hot as many places at higher latitudes. Now if those pesky travel restrictions are tamed down I’m off again. Thanks.
Indeed, Ron, I came up with my hypothesis watching the daily thunderstorms form in Fiji … have fun in the Caribe. At present you can still go to the American Virgin Islands …
w.
Where there are no virgins….
Dont forget latent heat loss, I read a hurricane, because of wind, can make the sea give up 1000 Wm^-2.
I was on a sailboat off Beef Island, BVI in May in a squall and was shivering. Did not have a raincoat and was at the helm. The rest of the crew were down below letting me be the goat. Tropical squalls in fact do cool things down substantially.
BTW, BVI’s announced they are back open December 1, in time for the winter tourist season.
I hope your first name isn’t “Roger”
Because I had a chuckle at that old seafarers’ joke –
Captain to first mate: “go below and fetch my charts, and Roger the cabin boy”
First Mate : “aye, aye Sir. Which do you want me to do first?”
30% is the average albedo, more or less.
And it is very high in the polar regions and low around the equator.
http://www.climatedata.info figure 1.
And according to figure 2 around 0.25 in the winter with snow cover and as low as 0.15 in the summer w/o.
http://www.climatedata.info/forcing/albedo/
And since the albedo is zero on the dark side it would have to be 60% on the lit.
And by reducing the ISR the albedo cools the earth.
One may well say that all weather is emergent, from the local thunderstorms to the expansive synoptic weather systems. They are all a product of the temperature gradients and baroclinicity of the atmosphere. The greater the temperature gradient the more unstable the atmosphere becomes on all scales and in both the horizontal and vertical, and will act to dissipate this instability through various sized storms.
Very nice piece. Very plausible. There has to be something that stops warming becoming runaway. There has to have been something that stopped the MWP turning us into Venusians. This seems like a very promising hypothesis of what it could be.
We will eventually come to the end of this great popular madness. But I’m afraid there is a heap more which will still be fermenting away under the blankets.
“On the road to Mandalay
Where the flying fishes play
And the sun comes up like thunder
Rolling out across the bay”
……(sung with passion)…
Being almost as mature as Willis, I can hark back to a childhood in WWII and the dusk of Empire. The BBC broadcast musichall style programmes Sunday evenings, the above verse from a very popular song, has stayed with me. Willis’ chart of the ‘thunder belt’ going right through that part of the globe explains the analogy.
What I’m taking away from this is that it could be the possible cause of the ice ages. Precipitation increases with the temperature increase, meaning more snow in the extreme north and south. Eventually, albedo increases to the point where so much sunlight is reflected that the snow/ice coverage dominates climate. Am I simplifying too much here?
“Am I simplfying to much here.”
I think so, as the WV in the atmosphere rapidly precipitates out as the atmosphere cools, thus the feedbacks the other way increase and counterbalance us achieved.
Willis concludes: “My main conclusions out of all of this? It supports my hypothesis regarding emergent phenomena regulating the temperature, and this is clear evidence that temperature is NOT a linear function of forcing.”
Bravo!
Stay safe and healthy, all.
Regards,
Bob
Another thunderstorm related thermoregulatory mechanism is Lindzen’s “adaptive infrared iris”. Some years ago Judith Curry and I posted back to back on it. She interviewed Lindzen for the backstory, I covered his paper and the then new results of a GCM that specially incorporated it. IIRC, lowered the model ECS from 3.2 to 2.3 with just that one change.
Thanks, Rud. Do you have links to those documents? I’d be most interested in all three.
w.
Just checked. Go to Climate Etc, type adaptive iris into the search box. My post comes up first; it has a link to Lindzen’s paper. Judy’s complementary post comes up second.
Regards, and kudos on a great analysis.
Thanks, Rud, will do.
w.
Great informative article Willis.
Don’t answer this if you don’t want to, but I have to ask –
as such a dedicated researcher and prolific technical documenter, how do you find the time?
I’m wondering if, like prolific author Stephen King, you are insomniac?
Mr., I do my best to get to bed before 3AM, and am generally successful. And I get up when I wake up, usually between seven and eight hours later.
When I was working at my last full-time job, I went to sleep every night at midnight after researching/writing/programming/etc for as many hours as I could pack in. And I got up at 6AM every day to be at work at seven, the CFO has to be there before anyone else. At least when I’m CFO.
But now, at 73 I’m in what I call my “late youth”, and I’m retired. So it’s my dream world. I can work early or late, long as I keep my “honeydew list” down to a reasonable length.
The beauty part is that I’ve never made a dime off of my climate work. Oh, I got an honorarium, I think it was $500 from memory, for speaking at the Heartland Climate Conference for a couple years. But my work is totally unfunded.
For a mad scientist like myself, it’s the best of worlds … I now have fiber optic cable direct to my home office, one gig upload and download. I have access to all of the world’s datasets, and the time and freedom to explore them in any way that I choose. What’s not to like?
I can only wish this for you and for every scientist and researcher around the planet …
w.
Willis, I’m your age and you make me jealous of your vocation for fact-finding and disclosure.
Your time management skills also obviously contribute a lot to your productivity.
I hope you have many more productive years left practicing your passion, from which we all benefit, particularly because of the debates your posts usually initiate.
Oh, but it’s also so disedifying that you have the gall to disclose here that you really are a fossil fuel industry lackey, what with your $500 ‘cash for comment’ payment from the Heartland Climate Conference. What is wrong with you? David Suzuki doesn’t get out of bed for less than $30k even just to do a boilerplate enviro talk to schoolkids. Why can’t you emulate David’s passion for unbridled capitalism? 🙂
Are you suggesting a weather (water) related negative feedback that will tend to limit climate extremes?
If so, this theory is quite boring compared with the current water vapor positive feedback theory, tripling the effect of CO2 alone, causing runaway warming, ending all life on Earth, except microbes, ants and mother in laws, unless we act radically to limit CO2 emissions in the next 23 years.
Love the list of survivors …
w.
Wouldn’t that be “in the next 23.4783 years”?
23.478FOUR years, because G Newsome got rid of ICE in cars.
The signature tropical tropospheric temperature predictions of that water vapor positive feedback theory fail spectacularly when tested against independent data of radiosonde temperatures, satellite temperature, and reanalysis temperature. “Only” off by 2.5X to 7X! Eschenbach’s emergent feedback theory has a lot better likelihood of being accurate. See review post:
Ross McKitrick “New confirmation that climate models overstate atmospheric warming” at Climate Etc. re
Mitchell et al. (2020) “The vertical profile of recent tropical temperature trends: Persistent model biases in the context of internal variability” Environmental Research Letters,
https://iopscience.iop.org/article/10.1088/1748-9326/ab9af7
and
McKitrick and Christy (2020) “Pervasive warming bias in CMIP6 tropospheric layers” Earth and Space Science.
https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020EA001281
Willis….My G you are old!!! ;>) I am 73 as well and healthy but holy S%^$, I sure can’t match your energy. Two questions:
1. Are you training an acolyte/ successor to take your great work into posterity?
2. I really enjoy your writings on emergent phenomenon. Is anyone in the “legitimate” academia working to replicate your work. (if there are any left who can afford to be heretics)
Thanks for the kind words, Joe.
1. I wish I had an acolyte/successor to take over, but I fear it’s just me in my home. What I really nead are minions. Every world-dominating evil overlord has minions, where are mine?
2. While there are some mainstream sciencefolk who think I’m not entirely crazy regarding emergent phenomena, none appear to be overly enthusiastic about it … being heretical, my ideas are generally anathema to the center of the road.
w.
PS—Don’t tell anyone, but the secret to my eternal youth is here …
Willis What are the qualifications to be a minion?
Emergent phenomenon arising from chaotic behavior certainly plays a role in how the atmosphere self organizes, but the goal doesn’t appear to be maintaining the surface temperature, but to maintain a constant ratio between the BB emissions of the surface consequential to its temperature and the emissions at TOA above that surface. The data clearly shows how this ratio wants to be remarkably constant at about 620 mw of emissions at TOA for each W/m^2 RADIATED by the surface. Averages of nearly every point on the surface converges to within a few percent of this ratio within a month or so and gets even closer as the averaging increases. The common factor preventing this ratio from emerging is the lack of chaotic variability from clouds.
While you may think that the value of this ratio must just be a coincidence, it would need to be the same coincidence occurring at all points of the surface at all times. This is very unlikely. The fact that 0.62 is 1/g, where g is the golden ratio, doesn’t seem to be a coincidence either, as relatively simple math can readily show how this ratio is very likely to emerge from a chaotically self organized system, where what’s chaotically varying is this ratio and the instantaneous value of this ratio is highly dependent on the instantaneous cloud coverage which is chaotically varying.
http://www.palisad.com/co2/goldenwarming.pdf
Yes, it seems to me that the asymptotic approach of sea surface temperatures to about 300K is the result of incremental solar energy evaporating so much water that the latent heat released is enough to prevent any additional temperature rise. This same asymptotic behavior is seen in atmospheric water content. This is not so much an emergent property, as it is a causal effect related to the rate of evaporation as a function of temperature.
http://www.palisad.com/co2/sens/st_wc.png
co2isnotevil September 23, 2020 at 11:42 am
Mmmm … sounds unlikely. The world usually isn’t that neat. Good news is, I can answer the question. Here’s a grapic I just made using the CERES data.
[Hat tip to Wim R who notified me that it should say “%” where it says “W/m2”. He’s right. I dashed it off, and the function that I wrote that creates my world maps defaults to units of watts per square metre … anyhow, take too long to redo it, just gonna leave this note.]
[Second and larger H/T to Wim who fixed the graphic, well done, thanks.]
As you can see, it’s absolutely not true that “every point on the surface converges to within a few percent of” the 61% you mention. In fact, the ratio goes from a low of 42% to a high of 104% … how does 104% happen, you say?
It’s because of the additional heat transported by the atmosphere to the poles. Like the surface, the atmosphere is emitting longwave radiation, so the total at the top of the atmosphere can be larger than just the surface LW radiation alone.
While your claim isn’t true about the surface, there’s an interesting oddity about the graph you might have noticed … despite wildly differing surface conditions in terms of percentage of land and land at the poles, the northern and southern hemispheres are within one percent of each other … hang on, haven’t I written about this before? With over a thousand posts it’s hard to remember … OK, see On The Stability and Symmetry Of The Climate System
I think that this symmetry is a consequence of the various thermoregulatory emergent phenomena affecting the system, and other explanations are welcome.
w.
Willis,
“The world usually isn’t that neat. ”
But the laws of physics are and math is, so clearly, the climate must be observing these. This is basically how an ideal gray body radiator must behave, that is a constant emissivity, independent of the temperature. The fact that this behavior is observed shouldn’t be surprising.
I’ve done the averaging across 2.5 degree slices of latitude and more consistently arrive at that average, try integrating across slices of latitude and see what you get. I also see deviations in Antarctica and parts of equatorial oceans. As I said, what prevents that average from occurring locally is the lack of suitable chaos, but even globally this fraction still emerges from the math. Think of it as fractal like where the same math and physics applies locally and globally.
Consider that 1/g +/- 5% varies from .589 to .649, so according to your plot, most of the globe falls into this range and the hemisphere averages of .611 and .621 are within about 1% of 1/g, while the global average of .612 is within 0.3% of 1/g. If this is just a coincidence, why are the two hemispheres so similar? Try plotting the ratio as a function of monthly averages and see how constant it will be.
Antarctica suffers from the lack of chaotic variability, but this is offset elsewhere across the planet. My point is that the system tries, even locally, to achieve that average ratio and the more time and space the average is calculated across, the better the self organization becomes at achieving the desired goal. Across large parts of the planet, this average ratio emerges rather quickly.
co2isnotevil September 23, 2020 at 1:57 pm
I almost didn’t answer you for fear this would happen, because I’ve interacted with you before. Let me review the bidding. You’d said:
That seemed unlikely, so I said so. Then I looked it up. In the graph I just posted, it shows that far from being true, your claim was total bullshit. Of course, I was too polite to say that. I just pointed out that the 19-year-average of the points ranged from 42% to 104%.
And in response, you tell me that I should try looking at zonal averages … say what? It’s my fault because I didn’t do the analysis right? I didn’t appreciate your genius because of something about Antarctica, it’s nothing to do with your claim being bovine exrement?
How about “Gee, Willis, I was totally wrong and your unaided intuition beat my research.”?
I have an iron-clad rule—if I’m wrong, I say so loud and clear, and I have no interest in discussing things with someone who doesn’t do the same.
There’re not enough hours in the day for me to waste another minute on you.
Sadly,
w.
Willis,
‘”There’re not enough hours in the day for me to waste another minute on you.”
Then you’re missing out on crucial knowledge. The fact that this ratio is so constant has the power to bring down the IPCC, especially since I can now explain why it has the value it does and why it’s not likely to be anything else. I’m assuming you read the link to the math, if not, you should as both of these assertions are explained. You’ve even noticed how constant this ratio seems to be at larger scales. No mention of this being so constant is in any IPCC report and for good reason.
Keep in mind that the math and the model is specific to the bulk radiant behavior of the entire atmosphere and puts an immutable limit on the sensitivity of about 0.3C per W/m^2. Despite it being a global model, it’s exceptionally good per hemisphere and is still a very close approximation locally, PROVIDING THERE”S SUFFICIENT CHAOTIC VARIABILITY. One thing about slices of latitude is that they will have more of this kind of variability.
You’re right that the transfer of energy from the equator to the poles has something to do with it, but this has more to do with the direction the ratio goes when there’s insufficient cloud variability since the effect of the transfer of energy from the equator to the poles is mostly accounted for by its effect on the local surface temperature while the ratio of surface emissions to TOA emissions is largely independent of the surface temperature. Cloud emissions arising from transferred energy are likely responsible for most of the small deviations from golden and is likely a major contributer in Antarctica.
The lack of sufficient variability occurs when there are either way too many clouds or no clouds at all and the theory predicts that under these circumstances the ratio can be arbitrary, so the fact that the outliers vary by so much is expected. It only converges to golden locally when there’s sufficient chaotic variability. Globally and over large areas, this ratio still emerges, despite local variability, and does so very quickly as long as the region the averages are calculated across has sufficient cloud variability, and that’s the crucial point I’m trying to make.
I wasn’t fully aware of how much local deviation was being compensated for globally and across slices of latitude, since the data I used was much coarser, but it was of no real concern, because it was readily explained and not only consistent with the theory, reinforces it since even more local variability has to be compensated for elsewhere in order for the ‘coincidence’ to be realized. I just didn’t expect that explaining it, rather than giving you kudo’s for noticing it would upset you so much.
You will also notice when you calculate shorter term averages, instead of a 20 year average, the distribution of ratios across the surface will not vary by a whole lot, supporting the fact that this ratio is converged to very quickly and the per hemisphere and global averages will vary by even less.
In no way am I inferring that any thing is your fault by suggesting other experiments you could try to further validate this hypothesis. Isn’t this what proper science is supposed to be about?
Willis,
That this ratio is the most consistent variable between hemispheres is something I noticed a long time ago and I’ve also noticed that it’s also most quickly converged variable as well. Interestingly enough, this ratio is highly dependent on the average cloud cover and yet the average cloud coverage per hemispheres is quite different, as are average temperatures, albedo and solar input, all attributed to the varying ratio of land to ocean. It’s the variability in the average cloud coverage that seems to compensate for other differences so that this constant ratio can emerge.
That this emissions ratio is so constant and independent of so much is something I’ve been trying to figure out for a long time. How the math I discovered (I haven’t seen anything like it anywhere else) so elegantly aligns with the radiant transfer function of the bulk atmosphere is almost too good to be true. None the less, when globally, the CERES data shows a result within 0.3% of the prediction and the ISCCP data I used was within 0.5% of the prediction (I had to derive the TOA flux from other data), I would call this a validation of repeatable science.
The question I’ll pose to you, is given how independent this ratio is of everything else, what else would cause it to change?
Where this would be most useful is as a sanity check on GCM’s to make sure that this ratio isn’t bumbling around all over the place.
Willis I encourage you to compare the cloud top altitude of your first graph at the beginning, with the top of atmosphere longwelling as ratio of surface longwelling. Visually there seems to be a negative correlation.
e.g. See the Pacific with the highest cloud top altitude (8 km) compared with the lowest (0.45) atmospheric longwelling ratio to surface longwelling. That has promise as how to predict top of tropospheric tropical temperature from surface temperature. Then be able to test that prediction against independent radiosonde, satellite and reanalysis temperatures. Potentially far more accurately than IPCC’s tropospheric temperature model predictions.
David,
The sentence after the one Willis complained about explains the ITC behavior. Both local and global convergence to the golden ratio requires sufficient chaotic variability. Without sufficient variability, this ratio can be anything, as the math clearly predicts.
In simple terms, if G is the amplification of solar W/m^2 to surface emissions and 1/G is the attenuation of surface emissions to emissions at TOA, there are an infinite number of transformations for any possible G from 0 to 1. However; owing to the unique numerical properties of the golden ratio, for each possible transformation resulting in an arbitrary G, there are an infinite squared number of possible transformations resulting in a golden g. Given that the transformation is chaotically varying as clouds vary, the most likely value of G is a golden g.
Chaotic variability arises from clouds and in the ITC, the cloud coverage is nearly absolute. Sufficient cloud coverage variability doesn’t exist and the same is true in Antarctica which has too few clouds.
Think about how clouds affect this ratio. More clouds decreases the average of this ratio, less clouds increases it while average clouds drive the system to its converged ratio. The ITC has too many clouds and the ratio is lower, while Antartica has too few clouds and the ratio increases.
None the less, the planet has sufficient global chaotic variability in cloud coverage to insure that this ratio emerges globally and the data is unambiguously clear that it does, exactly as the math predicts. The math also predicts how and why expected local deviations will occur and why such deviations have no effect on the global convergence to this ratio.
As a further test of the golden warming hypothesis, when averages are calculated across shorter periods of time, they will vary very little from the 20 year average in Willis’s plot and this is what I meant by quickly converges. Also note that even in Willis’s plot, the vast majority of the planet has sufficient cloud variability and maintains local ratios centered on and within 5% of the golden ratio as it maintains a nearly invariant global ratio within a tiny fraction of a percent of golden.
Note as well that the IPCC’s nominal sensitivity requires incremental surface emissions of 4.4 W/m^2 per W/m^2 at TOA, that is, the increase in surface emissions from the next W/m^2 of forcing will require a ratio of 1/4.4 = 0.23 which would mean each of the next 4.4 W/m^2 of surface emissions arising from the next W/m^2 of forcing only results in 0.23 W/m^2 of emissions at TOA. Obviously, this can’t be true as the next W/m^2 is no different than the average W/m^2 relative to the work done maintaining the surface temperature and replacing emissions is the only work required.
The fact that the average ratio is so constant confirms that a gray body with an emissivity of 1/g quantifies the bulk behavior of the plant better than anything else as it limits the ECS to 1.62 W/m^2 of incremental surface emissions (0.3C) per W/m^2 of forcing. This demonstrable truth paves the way to undermining the IPCC and its false consensus. There is no other way.
I would not necessarily call it an “emergent” phenomenon, but the smoke cloud from the recent fires cooled surface temps by 20°F. The forecast temp was in the 80’s, the actual on the ground temp was in the 60’s, for a week. When the smoke finally cleared and the sun went from red to yellow, it warmed up considerably.
Albedo has a huge effect. The failure of GCM’s to correctly predict/model clouds is their greatest failing. Well, one of them.
As a resident of the Bay Area I can confirm the dramatic impact of the smoke on temperatures.
I will also note that a neighbor reported his solar output was 2% of normal.
NOAA has a Smoke Plume Map on one of their websites and it shows the Left Coast fires’ smoke reaches all the way to the UK! That’s a hell of a lot of albedo, above 20 degrees N, and we just entered Autumn. So, How could this “emergent phenomenon,” impact the temperatures for Winter 20-21?
1783 and1816….The years without a summer.
Now add 2020…brutal tough winter??
Great post!
Re: “My theory of how the climate operates is that the globe is kept from overheating by a variety of emergent phenomena.” Does this statement reveal a bias around heating? Who is to say it is overheating or overcooling? Weather is local. Or does this mean that these local effects are what are preventing heating that would result from increasing atmospheric CO2 if the hypothesis of AGW were true?
Scissor September 23, 2020 at 11:48 am
Choice B, “these local effects are what are preventing heating that would result from increasing atmospheric CO2 if the hypothesis of AGW were true”.
When I got interested in climate a couple decades ago I was obsessed by one question—why is the global temperature so dang stable, over centuries and millennia? I’ve dealt with heat engines before, and a temperature variation of plus or minus half a degree C over the 20th century is a variation of less than ± 0.2%. Even the variation over the entire Holocene is less than one percent, and that is an amazingly stable heat engine.
I spent a lot of time thinking about slow-acting long-term phenomena that might exert control over millennial timescales, like the weathering of rocks removing CO2 from the atmosphere.
I was living in Fiji at the time, and one day I was watching the usual tropical weather show—clear in the morning, cumulus field forms late morning, thunderstorms in the afternoon. I thought “Wait a minute. I’m looking at and living in and under the answer”.
I realized that the thunderstorms had huge cooling effects on the surface. Further, I realized that the daily timing and strength of the emergence of thunderstorms actively controlled the temperature.
And finally, I realized that any phenomenon that can keep each day from overheating will also keep each week, month, year, decade, century, and millennium from overheating …
So your speculation, that local events prevent overheating, is 100% correct.
w.
An excellent article Willis!
I can confirm your postulate with direct observation. I live in South Florida. And our “rainy” season starts when ocean temp reaches 80F, and ends when it falls below. (May to November)
During this time, we typically get almost daily pop up thunderstorms in the afternoon, which serve to cool things down. These are not to be trifled with – tropical downpours of 4” per hour are the norm, and you must slow down when driving as suddenly visibility can drop to less than the hood of your car. (bonnet for Brits)
These storms can form in minutes, and usually form either east of the coast (where the Gulf Stream is only a mile or two off the east coast here), or at a convergence zone of onshore and offshore winds.
This year has “felt” hotter than normal, but this sense has nothing to do with trace gases. Rather it is because we have had a dearth of the daily storms, so haven’t had this natural cooling effect as much.
I certainly cannot match your maths skills, but can muster some basic “self checking” of an hypothesis on this notion.
The following is a “back of the envelope” cross check on the notion Tropical Thunderstorms provide a net cooling effect on the planet. It’s not comprehensive, but is based on real typical pop up thunderstorm parameters here in the sub tropics.
Actual Values used:
Solar Input with Clear Sky = 835 W/m²
Duration of Thunderstorm = 20 minutes (1200 seconds)
Area of Thunderstorm/Rainfall = 1 km² (1,000,000 m²)
Rain Rate = 4” /hr (0.1016 m/hr)
Mean Altitude of the CB (Cumulo Nimbus) = 20,000 ft (6400 m)
Water Mass = 1,000 kg/m³
water evaporation energy = 2,430 kJ/kg @30C
Downdraft Velocity = 27 m/s
Downdraft Gust Duration = 100 seconds
Lightning Energy = 6 GJ per strike
Lightning strikes = 33
Now this is not a comprehensive analysis of thunderstorm physics, but just takes the most easily obtained facts about these typical almost daily storms here in southern Florida. And uses physics principles to calculate the energy output of this storm as a heat engine.
Thunderstorm as heat engine output energy:
Water: 1,000,000 m² area x 0.1016 m rain depth/hr x 0.33 hrs = 33,867 cubic meters of water fell as rain. This is 33,866,667 kg of water.
Evaporation Energy = 33,866,667 kg x 2,430 kJ/kg = 82 GJ
Raising that mass of water to the mean altitude required 33,866,667 kg x 6100 m x 9.8 N/kg = 2,025 GJ
The downdraft gust entails 27,000,000 m³ of air* which is 32,400,000 kg x 27^2 m/s x 0.5 x 100 seconds = 1,181 GJ of energy.
And 33 lightning strikes at 6 GJ per strike is 165 GJ
*(each second, the downdraft encompasses 27 m high x 1,000,000 square meters area and kinetic energy is 1/2mv^2)
So we have a total output energy of 3,453 GJ from this 20 minute tropical thunderstorm.
Now Solar input in a clear sky, is on average (daylight only, not the silly 24hr average) is 835 W/m² at this latitude. 20 minutes of this over 1,000,000 square meters is 1,002 GJ.
So either the storm took 69 minutes of solar input to form, or it formed faster (which does occur here) and drew in warm moist air from a far larger area of the ocean surface to satisfy conservation law.
Either way the net effect of the thunderstorm as heat engine is it converts heat to useful work which is then not available for heating the planet via the solar energy input.
This “cross check” does not account for the increased albedo of the CB, or the fact that heat from the ocean or ground is transported to high altitudes and released there by convection and water phase changes. (when it condenses it releases heat – and this causes the runaway rise in the cumulus clouds – otherwise it should only condense at the dewpoint temp which is at the cloud base) Nor does it account for how much cold air from high altitudes are brought down by the rain entraining downdraft.
Willis’ postulate that thunderstorms are a cooling mechanism is correct. And they do in fact self generate as soon as the ocean temp reaches 80F in the spring and continues until it drops below 80F in the fall. Thus they are a form of self regulation of climate.
The thunderstorm not only converts the solar heating input to useful work, thus that energy cannot heat the planet, but it transports surface heat to high altitudes where it can more easily be radiated to space. And it brings cold air from high altitudes down to ground level as well as rain that is significantly cooler than ground level temps.
You could say that tropical thunderstorms are nature’s thermostats!
And just for Schist and Giggles, assume the IPCC value for CO2 heating is correct at 1.8 W/m². If we use the storm’s area and duration, the demon carbon molecule adds just a hair over 2 GJ compared to the thunderstorm dissipating 3,453 GJ. Put another way, each 20 minute tropical thunderstorm dissipates as much energy as carbon dioxide adds over 48 days. i.e. Water is the earth’s thermostat, not CO2!
Since energy is not lost in the evaporative cooling, where does it end up in the system? This long term
balancing act would fail as there would be all the water in the atmosphere.
So it is definitely a local cooling, but how can it later cause greater radiation?
Timo, the latent heat is released into the upper troposphere when the water vapor condenses in the clouds. It then radiates to space and the water returns to the surface. There is no accumulation of water vapor in the atmosphere.
And the radiation into space is facilitated greatly by the CO2 in the upper atmosphere (where there is little to no water).
Timo Soren
September 23, 2020 at 11:51 am
What you asking for, has an answer.
But you will never get to understand that answer unless first you understand that the main point of this particular post is not about the RF being non existent.
Once you get to understand this very simplicity, maybe you get a chance to see that your question as put is a fallacy.
You see, Willis is not claiming that RF is non existent.
Simply pointing out that the variation of the radiation potential does not seem to effect it… even in short term.
Before one can destroy, one has to build.
Unless understanding how it builds up, no chance of figuring out how it is squared off.
(my understanding and position is that Willis doing a great work)
cheers
Worth repeating.
Excellent point.
The emergent “negative feedback” phenomena limiting tthe upside if ocean temperatures seems almost like a no brainer once you have explained it. Embarrassing for “climate scientists”, if they were capable of embarrassment.
One issue: among the thunderstorm-related coolings in addition to the albedo and rain/evaporation effects, I have thought that updrafts within towering thunderstorm clouds transports heat from the surface to high enough in the atmosphere to be far more readily radiated into space.
Indeed, once transported to an altitude above most of the H2O in the atmosphere, the “greenhouse gas” effect now would hinder the return of heat energy to the surface. This would be like heat being above a blanket lying on you—-the blanket would keep you cooler by keeping the heat away.
And, if the heat is regularly carried well above most CO2 in the air, any rise in CO2 level would have, if anything, a slight cooling effect in the thunderstorm region.
Hi Willis! Thank you for your effort to get the science right. The energy budget of the Earth could be the final brik to stop the AGW theory, although there already seems to be so many falsifications to that theory, that it should have been put back into the history of science. Does the average energy model even comply? As you mention 70% of the surface of the Earth is water not soil, most of the energy of the Sun is received near equator, the energy from the equator region is transfered north or south through strong wind systems with high kinetic energy – as I find it even not reflected in the official IPCC energy budgets based on IR radiation forcing of CO2. I would so much encourage all of you bright scientific guys to join effort to finally come up with a scientific and bullet poof evidence that the AWG is wrong. We use too much money and energy on what seems to be a false theory.
kind regards SteenR
In fact, the transfer is such that the temperature of the tropics away from the equator is warmer than at the equator itself. link
I agree Willis. I believe we live in a world that has a nonlinear chaotic climate. Good luck trying to come up with computer model for that. It’s why they can’t simulate cloud formation or pressure system’s in the atmosphere.
Excellent Article, Willis. I always look forward to your essays as they are always very enlightening as well as enjoyable reading. I agree with you that the climate self-regulates generally in the manor that you put forth but I have to play devils advocate for a minute and ask a question that may be posed by alarmists and luke-warmers alike. Assuming the general tenant of AGW and the greenhouse hypothesis in general, and that the temperature in the tropics have essentially a max temperature limited by the atmospheric water cycle as you propose, wouldn’t increased greenhouse gasses just push the max temperature into higher latitudes, thereby increasing the global average temperature?
Dewenter
Electrical Engineer
Nice job Willis. Compelling to say the least.
I suspect this will play an integral role in the development of CMIP Phase 200 at centuries end, as the modelers will be scared stiff to consider your analysis for decades to come 😉