Emergent Climate Phenomena

Guest Post by Willis Eschenbach

In a recent post, I described how the El Nino/La Nina alteration operates as a giant pump. Whenever the Pacific Ocean gets too warm across its surface, the Nino/Nina pump kicks in and removes the warm water from the Pacific, pumping it first west and thence poleward. I also wrote about dolphins in a piece called “Here There Be Dragons“.

Fulfilling an obligation I incurred in the latter paper by saying I would write about emergence and climate, let me take a larger overview of the situation by noting that both the El Nino pump and the dolphins are examples of a special class of things that are called “emergent” phenomena.

emergence 2

Figure 1. Hands emerging from the paper …

Emergence is a very important concept. Systems with emergent phenomena operate under radically different rules than those without. Today I want to talk about emergent systems, and why they need to be analyzed in different ways than systems which do not contain emergent phenomena.

Examples of natural emergent phenomena with which we are familiar include sand dunes, the behavior of flocks of birds, vortexes of all kinds, termite mounds, consciousness, and indeed, life itself. Familiar emergent climate phenomena include thunderstorms, tornadoes, clouds, cyclones, El Ninos, and dust devils.

Generally speaking, we recognize emergent phenomena because they surprise us. By that, I mean emergent phenomena are those which are not readily predictable from the underlying configuration and physics of the situation. Looking at a termite, if you didn’t know about their mounds there’s no way you’d say “I bet these bugs build highly complex structures a thousand times taller than they are, with special air passages designed to keep them cool”. You wouldn’t predict mounds from looking at termites, no way. They are an emergent phenomenon.

The El Nino phenomenon is another excellent example of emergent phenomena. Looking at a basin of water like the Pacific, there’s no way you would say “Hey, I’ll bet that ocean has this complex natural system that kicks in whenever the ocean overheats, and it pumps warm water up to the poles.” You wouldn’t predict the existence of the El Nino from the existence of the Pacific Ocean. It also is an emergent phenomenon.

In addition to their surprising emergence from the background, what other characteristics do emergent phenomena possess to allow us to tell them from other non-emergent phenomena?

One common property of emergent phenomena is that they are flow systems which are far from equilibrium. As a result, they need to evolve and change in order to survive. They are mobile and mutable, not fixed and unchanging. And locally (but of course not globally) they can reverse entropy (organize the local environment). Indeed, another name for emergent phenomena is “self-organized phenomena”.

Another key to recognizing emergent phenomena is that they arise spontaneously when conditions are right. They don’t have to be artificially generated. They create themselves in response to external stimuli.

Next, they often have a lifespan. By a “lifespan”, I mean that they come into existence at a certain time and place, often when some natural threshold is exceeded. Thereafter they are in continuous existence for a certain length of time, and at the end of that time, they dissipate or disappear.

Another characteristic of emergent phenomena is that they are not cyclical, or are at best pseudo-cyclical. They do not repeat or move in any regular or ordered or repetitive fashion. Often they can move about independently, and when they can do so, their movements can be very hard to predict.

Another feature of emergent phenomena is that they are often threshold-based. By that I mean that they rarely emerge below that threshold, but above it their numbers increase rapidly.

Another attribute of emergent systems is that they are often associated with phase changes in the relevant fluids, e.g. clouds occur because of a phase change of water.

One final attribute of threshold-based emergent systems is crucial to this discussion—they exhibit “overshoot” or hysteresis. In the Rayleigh-Bénard circulation shown below, it takes a certain threshold temperature difference from top to bottom to cause the emergence of the circulation pattern. But once that circulation is established, it will persist even though you turn the heat down far below the initiation threshold temperature.

So those are some of the characteristic features of emergent phenomena. They are flow systems far from equilibrium which arise spontaneously, often upon crossing a critical threshold. They are not obviously predictable from the underlying conditions. They move and act unpredictably, they are often associated with phase changes, and they exhibit “overshoot” (hysteresis).

However, not all emergent systems are created equal. Some of them are what might be termed “field-wide”. An example of this is the spontaneous emergence of “Rayleigh-Bénard” natural circulation in a fluid heated from the bottom and cooled from the top.

rayleigh-benard circulationFigure 2. Rayleigh-Bénard circulation. Curiously, the time reads first down the right column then down the left. At the end an organized series of rising and falling areas is emerging. It is characterized by narrower rapidly upwelling sections, separated by larger, slower-moving downwelling sections. Original Caption: Onset and development of thermal convection cells in Rayleigh-Benard convection. Note the regularity of initial “bubbles” and their coalescence to form larger loops. SOURCE

Another, more complex type of emergent systems are what might be called “independent”. Examples of these in the climate world are thunderstorms and dust devils. Unlike the field-wide emergent phenomena, these are free to roam about the landscape. Like all flow systems far from equilibrium, they are constantly adjusting and evolving to meet the physical constraints. For example, thunderstorms move preferentially across the surface to warmer areas.

As I said above, I want to highlight the difference between the analysis of systems that do and do not contain emergent phenomena. My thesis is that systems with emergent phenomena cannot be analyzed in the same manner as systems without emergent phenomena. The corollary is that climate models are appropriate only for systems without emergent phenomena. Let me give an example of each kind of system so you can see the difference.

For the first system, let me consider a flat slab of iron that is warmed by the sun or some other heat source in a vacuum. As the heat source varies, the temperature of the slab of iron varies as well. This variation in temperature with energy input is quite regular and predictable. If we graph the changes, we’d see that there are no sharp bends in the graph. In addition, the more energy that the iron is receiving, the hotter it gets, with an unchanging mathematical relationship between downwelling radiation and the temperature of the iron slab. So we could approximate it by a straight line.

Now, let’s replace the flat slab of iron with a flat slab of cool water, and we’ll add the possibility of clouds and thunderstorms as the emergent phenomena. Starting with cool water, at first, we’d see basically the same thing as with the iron slab—the more energy we add, the warmer the water gets. Everything is all nicely proportional, the water is acting just like the iron. (Yes, there are a million details, but work with me here. It’s a thought experiment.)

But at a certain point, a curious and surprising thing happens. A threshold is passed, and clouds form.And when they do, it reflects some of the incoming energy back to space. So we get a “knuckle” in the graph of incoming energy versus temperature. We’re no longer warming as fast as we were.

exemplar temperature curves

If the incoming energy continues to rise, however, a more surprising thing happens. Another threshold is passed, and thunderstorms begin to form. These cool the surface in a host of ways, most importantly by piping the warm surface air through the middle of the thunderstorm up to high altitudes. This avoids almost all of the greenhouse gases (H2O and CO2) in the lower troposphere and allows for free radiation of huge amounts of thermal energy to space. Not only that, but thunderstorms are radically different from a feedback because they cool the surface down to well below the thunderstorm initiation threshold temperature. This means that they can not only slow down a temperature increase, they can stop it in its tracks.

And at that point, when thunderstorms start forming, the water basically stops warming. Further increases in incoming energy are simply equaled by further increases in thunderstorms and changes in their orientation such that the surface temperature hardly warms after that.

Now, one of the claims of the AGW supporters is that there is a linear relationship between downwelling energy and temperature. They say that any increase in incoming energy must be matched by an increase in surface temperature. Despite the known non-linearity of the system, the claim is made that over a narrow interval, a linear approximation of the relationship between energy and temperature is a very reasonable approximation to the reality.

But in the thunderstorm part of the tropical thermal regime, it is important to note that not only is the relationship between incoming energy and temperature non-linear, but in fact, there is no relationship between incoming energy and temperature. So you cannot even approximate it with a linear relationship. In that regime, increases in incoming energy are generally balanced out by increases in thunderstorm numbers and associated increased evaporation and convection, leaving only small residual temperature changes.

So one reason you can’t simply map a linear approximation to a non-linear relationship is that in the thunderstorm regime, there is almost no relationship, non-linear or otherwise, between incoming energy and temperature. Given the number of phase changes of water that are involved in the thunderstorm system, this should be no surprise at all—the same exact situation occurs when water is boiling. The temperature of the boiling water can no longer be even approximated by looking at how much energy is going into the water. The boiling water system simply moves energy through it at a faster rate, it doesn’t run any hotter. The exact same thing is going on in the thunderstorm regime. If you increase the solar radiation, all you get is more thunderstorms moving faster. The surface doesn’t get hotter, the energy and the water just circulate faster.

There is a second reason that you can’t just take an average, note that the average doesn’t move much, and assume linearity. The problem is that in the tropics, the climate sensitivity is very different depending on the time of day. Here’s why. First, without reference to anything else, climate sensitivity is an inversely proportional function of temperature for several reasons.

• Radiation is a function of T^4.

• Parasitic losses increase with temperature.

• Emergent cooling mechanisms (thunderstorms, dust devils, rain) are temperature based with high numbers appearing once the local system goes above some threshold of emergence.

So clearly, climate sensitivity is inversely proportional to temperature, falling as temperature rises. It is not a constant in any sense of the word.

Next, climate sensitivity varies over both space and time. In the early morning in the all-critical tropics where the energy enters the planet-sized heat engine we call “climate”, the temperature rises rapidly because of the lack of clouds—a high change in temperature per change in watts (high sensitivity). In the late morning, the watts are still rising but the clouds greatly reduce the temperature rise—smaller change in temperature per change in watts (low sensitivity). And indeed, certain areas at certain times can show negative sensitivity, and some areas of the planet are not sensitive to the forcing at all.

Now, the global average climate sensitivity, the one that people take as a constant, is no more than the average of these highly varying sensitivities. But the average is greatly misleading because it is taken as constant or semi-constant. In the real world, however, climate sensitivity not constant in any sense. It is both inversely proportional to temperature and highly non-linear.

For example, in Figure 3 above, the “climate sensitivity” is taken as the average slope of the linear trend line relating temperature and incoming radiation. As you can see, if the earth were like an iron slab with no emergent phenomena, a straight light approximates the curve extremely well at every temperature. But in the real world with water and clouds, the trend line is meaningless—it doesn’t represent the actual climate sensitivity at any temperature.

As a result, you can’t just say that because the global average surface temperature doesn’t vary much, we can treat it as a constant. The average is not real, it is a mathematical chimera. In the real world, we don’t see an average temperature. If the “average temperature” goes up by one degree, and it happens to be evenly spread out, let’s say the morning temperature goes from say 7°C to 8°C, while the afternoon goes from 22°C to 23°C.

But both the climate sensitivity, and the change in climate sensitivity with temperature, are very, very different in the two temperature regimes of morning and afternoon. It takes much, much more energy to go from 22°C to 23°C than it does to go from 7°C to 8°C. So while the average temperature doesn’t change much, that is highly deceptive. In reality, the dependence of sensitivity on temperature makes a huge difference in how the system actually reacts to changes in forcing.

To explain this in detail, I’m going to shamelessly steal, re-heat, and re-forge a section from my earlier post called “It’s Not About Feedback” because it is highly relevant to the questions I’m discussing. To understand why emergent phenomena are critical to understanding the climate, here is the evolution of the day and night in the tropical ocean. The tropical ocean is where the majority of the sun’s energy enters the huge heat engine we call the climate. So naturally, it is also where the major homeostatic mechanisms are located.

At dawn, the atmosphere is stratified, with the coolest air nearest the surface. The nocturnal overturning of the ocean is coming to an end. The sun is free to heat the ocean. The air near the surface eddies randomly.

Figure 4. Average conditions over the tropical ocean shortly after dawn.

As you can see, there are no emergent phenomena in this regime. Looking at this peaceful scene, you wouldn’t guess that you could be struck by lightning in a few hours … emergence roolz. As the sun continues to heat the ocean, around ten or eleven o’clock in the morning there is a sudden regime shift. A new circulation pattern replaces the random eddying. As soon as a critical temperature/humidity threshold is passed, local Rayleigh-Bénard-type circulation cells spring up everywhere. These cells transport water vapor upwards to the local lifting condensation level. At that level, the water vapor condenses into clouds as shown in Figure 3.

Figure 5.  Average conditions over the tropical ocean when cumulus threshold is passed.

Note that this area-wide shift to an organized circulation pattern is not a change in feedback. It has nothing to do with feedback. It is a self-organized emergent phenomenon. It is threshold-based, meaning that it emerges spontaneously when a certain threshold is passed. In the “wet” deep tropics there’s plenty of water vapor, so the major variable in the threshold is the temperature. In addition, note that there are actually two distinct emergent phenomena in the drawing, the Rayleigh-Bénard circulation which emerges prior to the cumulus formation, and which is enhanced and strengthened by the emergence of the clouds.

Note also that we now have several changes of state involved as well, with evaporation from the surface and condensation and re-evaporation at altitude.

Under this new late-morning cumulus circulation regime, much less surface warming goes on. Part of the sunlight is reflected back to space, so less energy makes it into the system to begin with. Then the increasing surface wind due to the cumulus-based circulation pattern increases the evaporation, reducing the surface warming even more by moving latent energy up to the lifting condensation level.

Note that the system is self-controlling. If the ocean is a bit warmer, the new circulation regime starts earlier in the morning and it cuts down the total daily warming. On the other hand, if the ocean is cooler than usual, clear morning skies last later into the day, allowing increased warming. The system is regulated by the time of onset of the regime change.

Let’s stop at this point in our examination of the tropical day and consider the idea of “climate sensitivity”. The solar forcing is constantly increasing as the sun rises higher in the sky. In the morning before the onset of cumulus circulation, the sun comes through the clear atmosphere and rapidly warms the surface. So the thermal response is large, and the climate sensitivity is high.

After the onset of the cumulus regime, on the other hand, much of the sunlight is reflected back to space. Less sunlight remains to warm the ocean. In addition to reduced sunlight, there is enhanced evaporative cooling. Compared to the morning, the climate sensitivity is much lower. The heating of the surface slows down.

So here we have two situations with very different climate sensitivities. In the early morning, climate sensitivity is high, and the temperature rises quickly with the increasing solar insolation. In the late morning, a regime change occurs to a situation with much lower climate sensitivity. Adding extra solar energy doesn’t raise the temperature anywhere near as fast as it did earlier.

Moving along through the day, at some point in the afternoon there is a good chance that the cumulus circulation pattern is not enough to stop the continued surface temperature increase. When the temperature exceeds a certain higher threshold, another complete regime shift takes place. Some of the innocent cumulus clouds suddenly mutate and grow rapidly into towering monsters. The regime shift involves the spontaneous generation of those magical, independently mobile heat engines called thunderstorms.

Thunderstorms are dual-fuel heat engines. They run on low-density air. That air rises and condenses out the moisture. The condensation releases heat that re-warms the air, which rises deep into the troposphere.

Figure 6. Afternoon thunderstorm circulation over the tropical ocean.

There are a couple of ways to get low-density air. One is to heat the air. This is how a thunderstorm gets started, as a strong cumulus cloud. The sun plus GHG radiation combine to heat the surface, warming the air. The low-density air rises. When that gets strong enough, a thunderstorm starts to form.

Once the thunderstorm is started, the second fuel is added to the fire — water vapor. Counter-intuitively, the more water vapor there is in the air, the lighter it becomes. The thunderstorm generates strong winds around its base. Evaporation is proportional to wind speed, so this greatly increases the local evaporation.

This, of course, makes the air lighter, and makes the air rise faster, which makes the thunderstorm stronger, which in turn increases the wind speed around the thunderstorm base, which increases the evaporation even more … a thunderstorm is a regenerative system, much like a fire where part of the energy is used to run a bellows to make the fire burn even hotter. Once it is started, it is much harder to stop.

This gives thunderstorms a unique ability that, as far as I know, is not represented in any of the climate models. A thunderstorm is capable of driving the surface temperature well below the initiation temperature that was needed to get the thunderstorm started. It can run on into the evening, and often well into the night, on its combination of thermal and evaporation energy sources.

Thunderstorms can be thought of as local leakages that transport heat rapidly from the surface to the upper atmosphere. They cool the surface in a host of ways, utilizing a combination of cold water, shade, wind, spray, evaporation, albedo changes and cold air.

And just like the onset of the cumulus circulation, the onset of thunderstorms occurs earlier on days when it is warmer, and it occurs later (and sometimes not at all) on days that are cooler than usual.

So again, we see that there is no way to assign an average climate sensitivity. The warmer it gets, the less each additional watt per metre actually warms the surface.

Finally, once all of the fireworks of the daytime changes are over, first the cumulus and then the thunderstorms decay and dissipate. A final and again different regime ensues. The main feature of this regime is that during this time, the ocean radiates about the amount of the energy that it absorbed during all of the previously described regimes. How does it do this? Another emergent phenomenon …

Figure 8. Conditions prevailing after the night-time dissipation of the daytime clouds.

During the nighttime, the surface is still receiving energy from the GHGs. This has the effect of delaying the onset of oceanic overturning, and of reducing the rate of cooling. Note that the oceanic overturning is once again the emergent Rayleigh-Bénard circulation. Because there are no clouds, the ocean can radiate to space more freely. In addition, the overturning of the ocean constantly brings new water to the surface, to radiate and to cool. This increases the heat transfer across the interface.

As with the previous thresholds, the timing of this final transition is temperature dependent. Once a critical threshold is passed, oceanic overturning kicks in. Stratification is replaced by circulation, bringing new water to radiate, cool, and sink. In this way, heat is removed, not just from the surface as during the day, but from the entire body of the upper layer of the ocean.

There are a few things worth pointing out about this whole system.

First, this is what occurs in the tropics, which is where the energy enters the hot end of the great heat engine we call the climate.

Next, sometimes increases in incoming energy are turned mostly into temperature. Other times, incoming energy increases are turned mostly into physical work (the circulation of the ocean and atmosphere that transports energy to the poles). And other times, increasing energy is mostly just moved from the tropics to the poles.

Next, note that this whole series of changes is totally and completely dependent on temperature threshold based emergent phenomena. It is a mistake to think of these as being feedback. It’s more a drunk walking on a narrow walkway. The guardrails are not feedback—they are a place where the rules change. The various thresholds in the climate system are like that—when you cross them, everything changes. The ocean before and after the onset of overturning are very different places.

And this, in turn, all points to one of the most important control features of the climate—time of onset. How much energy the ocean loses overnight depends critically on what time the overturning starts. The temperature of the tropical afternoon depends on what time the cumulus kick in, and what time the thunderstorms start

Finally, look at the difficulty in analyzing or modeling this kind of situation. You have a grid box that is far larger than any cloud or thunderstorm. And all you have to go on, the only things in your model, are the average statistics of that gridbox. And the main control system is the timing of the initiation of threshold-based phenomena that are far below your model’s gridcell size …

Think about say the average humidity of the tropical Pacific where there are thunderstorms. As soon as the thunderstorms kick in, they start discharging dry air up high. This dry air cools and descends in the area between the thunderstorms. So if you were to average the relative humidity of the bulk of the atmosphere across say one gridcell of a climate model, a hundred miles square or so, you’d see humidity falling as thunderstorms develop.

But this bulk drying of the downwelling air masks what is really happening. Under the thunderstorms, the storm-driven winds kick the evaporation into overdrive. The dry surrounding air is drawn in, loaded to the brim with moisture via the increased evaporation, and shot skyward at rates up to 10 m/sec. In a few minutes, it has moved up to the LCL, the “lifting condensation level”, where it condenses as clouds and rain.

As a result, despite the fact that the bulk atmosphere is drying, huge amounts of moisture are being moved vertically through the system. So simple averages are useless. The system is moving more water but the average relative humidity of the bulk atmosphere has dropped.

As this shows, increasing energy input may only increase the throughput, rather than increasing the temperature. Not all of the energy that hits the tropical ocean is immediately radiated back to space. A large amount of it is moved, via the ocean and the atmosphere, towards the polar regions before finally returning to space. This means that one of the crucial determinants of the temperature of the tropical regions, as well as of the polar regions, is the rate of energy throughput—how much energy is moved from the tropics to the poles. Once the system is into the thunderstorm regime, almost all of the incoming energy goes to simply turning the wheel faster, moving more energy from the surface to the upper troposphere, moving more air and water from the tropics to the polar regions. So instead of warming up the surface, the energy is moved skywards and polewards.

Again, however, these changes in throughput make the situation difficult to analyze. The dang system won’t ever stand still, it responds to everything that happens. How can one accurately measure how much energy is being moved and transformed by a thunderstorm? It can be done but it’s not easy.

An allied difficulty is with the size of the phenomena. Thunderstorms are one of the most common natural emergent heat engines on the surface of the planet. But they are way, way below the typical grid size of a climate model. As a result, they simply cannot be simulated in modern global climate models. This means that they must be “parametrized”, which as near as I can tell comes from the Latin and means “made up to fit the programmer’s preconceptions”. But while parametrizing a simple system is not difficult, parametrizing a system containing emergent phenomena is a very hard thing to do well.

In part, this problem arises from the very thing causing the need to parameterize—the small size of the thunderstorms. The problem is that those small thunderstorms cool down small hot spots before they ever get large. I have seen, for example, a single solitary thunderstorm in the morning, sitting over some warm spot in the ocean, with not another cloud in the sky. It was feeding off of some very local hotspot which had persisted through the night, and as long as it was hot, the thunderstorm stayed and cooled it down.

How on earth can one parametrize such an instantaneous response to excess warmth? Thunderstorms spring up over hot spots and cool them down to below the initiation temperature of the thunderstorm. And that kind of quick proactive response containing overshoot is not easily put into parameters.

And given that all you have are grid box averages, how will you model the critical changes in the time of onset of the various emergent phenomena? If the cumulus doesn’t appear until an hour later, or shows up an hour earlier, it makes a huge difference. And of course, the clouds and thunderstorms never shows up off-time, it emerges only as and when required, because its appearance is set by the immutable laws of wind and water and evaporation and condensation. It can’t occur late or early, it’s always right on time. But in the models, there are no thunderstorms …

As I mentioned above, there are a range of emergent climate phenomena. In general, they work together to maintain the temperature of the planet within fairly narrow bounds. The most important one of these is the tropical thunderstorm system described above. And there is something very critical about this system, something you may not have noticed so let me repeat it. A main control on the temperature is exerted by the timing and strength of the emergent phenomena, particularly clouds and thunderstorms. Now, here’s the important part. The time of day when a cloud forms is a function of the physics ruling the winds and the waves and the water and evaporation and condensation and the air and how they react to temperature.

Here’s why that statement is important. It is important because of what is missing—there is no mention of CO2 because CO2 doesn’t exert any direct effect on when clouds form. Clouds form in response to temperature and pressure and the like, not CO2.

So if there is a bit of additional forcing and the surface is a bit warm, the clouds simply form earlier, and the thunderstorms form earlier, and the nightly overturning of the ocean starts earlier … and that balances out the additional forcing, just like it has done for millions of years.

Nor is this just theory. I’ve shown that at the TAO buoys, days that start out colder than average end up warmer than average, and days that start out warmer than average end up colder … just as this theory predicts. See here and here for further discussion of the effect of emergent systems as seen in the TAO buoy records.

Now, note that I didn’t say that this kind of system containing emergent temperature control systems was impossible to model … just that it is hard. I’ve done a lot of computer modeling myself, both iterative and non-iterative models, and so I’ve both written and used physics-based models, economic models, models using neural nets, machine learning algorithms, computerized evolution models, tidal models, I’ve played the game a lot in a lot of fields and a lot of ways. It could be done. But it can’t be done the way that they are doing it because their way doesn’t account for the emergent phenomena. See my post entitled “The Details Are In The Devil” for a discussion of this difficulty in modeling systems dominated by emergent phenomena.

The emergence of clouds and thunderstorms radically cooling the surface, plus the increase in convection and evaporation with temperature, plus the thermal radiation going up as the fourth power of the temperature, all combine to put a serious barrier in the way of any increases in temperature. As near as I can tell, the climate models have no such barrier. In the model world, going up six degrees or even ten degrees seems to be no big deal, model runs achieve that without breaking a sweat.

But in the real world, of course, Murphy conspires with nature to make sure that every single additional degree is harder and harder to achieve … and emergent phenomena not only stop warming, they actively cool the surface down. Until both the theory and the models robustly embrace the emergent phenomena, the models will continue to be a funhouse-mirror version of reality … you can recognize it as some kind of climate but with all the distortions, you can’t use that as a guide for anything.

One last question—how would I recognize a good climate model? Well, in a good model all of the emergent phenomena we know about would actually emerge, not be parametrized … because the free actions of those emergent phenomena, the variations and changes in their times and locations of appearance are what control the temperature, not the CO2 “control knob”. So when the forcing from CO2 increases a watt or two, in an accurate model the clouds will emerge a few minutes earlier on average across the tropics, and the balance will be restored. This system of control by emergent phenomena has worked very well for billions of years, and it handles large swings in radiation every single day—it won’t be altered by a few watts of extra forcing from CO2.



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” This system of control by emergent phenomena has worked very well for billions of years, and it handles large swings in radiation every single day—it won’t be altered by a few watts of extra forcing from CO2″
Climate science is way way behind you Willis. Their ‘model’ of radiative balance is not real, in that it is a static model. I was amazed to see a professor giving this stilted view of the world to university students. I had to laugh, as it was just plain silly. The world is not only dynamic, but within bounds it is chaotic. You do a great job of describing its essential features.

Tobias Ostien

“Nor is this just theory. I’ve shown that at the TAO buoys, days that start out colder than average end up warmer than average, and days that start out colder end up warmer … just as this theory predicts.”
Did you mean the inverse warmer/colder during the second part of the statement?
Oh, and there’s also hurricanes… One giant thunderstorm is more efficient than a thousand tiny ones.

Dr T G Watkins

Yet another great article. I look forward to a detailed rebuttal from ‘the team’.


While I certainly couldn’t have written this paper, I can grasp its broad points. I have felt all along that the complexity of the climate was being grossly underestimated (or more probably under reported) by the CAGW crowd.
Anytime you see simple (especially linear) relationships being insisted on to describe complex, chaotic systems you should be suspicious of the person trying to sell them.
I don’t think that the destruction of our complex society will be accomplished by evil people (although they do exist) but primarily by stupid people that demand easy answers to very hard questions.
Science (as an quasi-institution) has lost its way, preferring to sell its soul for more grant money in return for the simplistic solutions stupid people want and need rather than insisting that having an opinion on some issues (such as climate) requires a lot of study and thought.
Thanks for trying to educate those of us that really want to understand (even if we never quite get it).


“Human being says: “It never rains but it pours.” This is not very apt, for it frequently does rain without pouring. The rabbits proverb is better expressed. They say, “One cloud feels lonely”: and indeed it is true that the appearance of a single cloud often means that the sky will soon be overcast. However that may be, the very next day provided a dramatic second opportunity to put Hazel’s idea into practice”
Watership Down, Richard Adams

Theo Goodwin

This essay is the most brilliant, interesting, and important essay in climate science that I have seen in years. Willis does not directly address scientific method but you can see it at work throughout his essay. The best thing about this essay is that it teaches the proper humility that must be shown by anyone who would make claims about climate sensitivity and who would anchor those claims in the facts, the myriad natural processes, that determine earth’s responses to the sun’s radiation.

Thanks, Willis, for yet another great article on the workings of the World. I wonder if any member of the Warmistas will read it and understand the significance of it.


Just fantastic Willis!
You are so right on the spot here, and the lack of this kind of basic observtiions and basic logic reasoning is what caused the CAGW pseudo science to go off the rails! You do science Willis!!.

Richard of NZ

Nicely put, Willis. I have frequently had severe doubts about the use of averages and this clarifies my thinking. It is rather like taking the average speed of the piston in a pump and saying that because the average speed is zero then the pump cannot work. Finer detail is needed than the gross averages used in the GCMs to tease any useful information out of them.
p.s. How do the climate investigators relate energy to temperature i.e. x downwelling watts gives y temperature change, when every substance has its own specific heat. Change the substance slightly (such as the absolute humidity of the air) and the specific heat also changes. Dry air temperature rises more rapidly for a change in incoming energy than does moist air temperature.
p.p.s. Regarding adjusted (homogenised etc.) data. When I was at school many centuries ago data was what was observed. When any manipulation was done to the data it ceased to be data and become either information or a result. For example, when a solution of NaOH was standardised against potassium hydrogen pthalate the data points were:
1.. the mass of potassium hydrogen pthalate measured (i.e. observed accurately) with a balance.
2.. the volume of NaOH solution measured in a burette.
After the necessary calculations were performed one had a result (the concentration of the solution of NAOH) which was useful information for further analyses.

Yes! I have been saying this for years, including in IPCC Review comments which have been ignored.
A recent example is my post at January 15, 2013 at 4:11 am in the WUWT thread at
where I wrote

… the models do not emulate ENSO which is an emergent property of the climate system. Therefore, if ENSO is a significant climatic effect then the failure of the models to emulate it demonstrates the models do not emulate the climate system of the real Earth. In other words, the models are useless for ‘projecting’ the climate of the real Earth.

Please keep saying it because people take notice of you.


Dr T G Watkins says:
Yet another great article. I look forward to a detailed rebuttal from ‘the team’.
Once they understand it, is say 5-10 years time !!! 🙂
ps.. nice work Willis.. but….
at one point you say “The dry surrounding air is drawn in, loaded to the brim with moisture via the increased evaporation, and shot skyward at rates up to 10 m/sec”
Moist air will not generally travel upward at 10m/sec, probably about half that. (gravity/specific heat)
However, approximately the same amount of energy is moved upwards.

That was ridiculously informative, Willis. Thank you.

Outstanding science writing. Well done.
One aspect of thunderstorms that you don’t cover is that in the humid tropics, once they develop they often persist overnight and into the next day. In Singapore, they are called Sumatras, as they originate over the island of Sumatra and typically reach Singapore late in the night to around dawn.
My experience of Singapore and the Riau islands (within 100km of the equator) is that it rains at all hours of the day and night and there is no noticeable late afternoon rainfall peak. I tried to find a reference but couldn’t. Presumably no one has studied this. I’ll suggest the regime you describe occurs where humidity levels are somewhat lower than the high humidity levels close to the equator.


Have you evere thought about collating your essays into, say, a Kindle book? I believe it would sell well.


Despite being pretty familiar with emergent behavior(and thus enjoyed the article immensely) I am mot sure I follow exactly the argument here. You refer to climate sensitivity becomes higher or lower based on the emergent cloud cover. Presumably the sensitivity you are referring to is changes in the incoming solar radiation that was heating the oceans. How though does this apply to sensitivity with respect to CO2 as a GHG? I am not sure we can just correlate the two here.
Despite that discrepancy, anyone who understands non-linear dynamic systems and complexity theory would appreciate that talking about global averages or predicting behavior based on tweaking a variable like CO2 is talking out their ass. All they have to go on is the data, and the data don’t fit.


Thank you – very nice.

Arno Arrak

Well done, Willis, except for the El Nino you do not understand. I learnt a lot. We all knew their models were no good and now we know some more of the reasons for it. And your “Here Be Dragons” is a masterpiece. It should be in some print medium. By the way, once I put you on a cc list for stuff I sent out but that email address from the islands does not work. Arno

wayne Job

Thank you Willis, harmony from chaos rules, well done

Gary Hladik

“And of course, the clouds and thunderstorms never shows up off-time, it emerges only as and when required, because its appearance is set by the immutable laws of wind and water and evaporation and condensation. It can’t occur late or early, it’s always right on time.”
Frodo: “You’re late.”
Gandalf: “A wizard is never late, Frodo Baggins. Nor is he early. He arrives precisely when he means to.”
— “The Fellowship of the Ring”
Also the answer to the riddle, “Why is a wizard like a thunderstorm?” 🙂
Nice article, Willis. Keep ’em coming.


Like your posts Willis, but 3 paragraphs in, I come upon this:
“Today I want to take about emergent ……..”
It is not the typo, it is the break in the flow it causes.


Thank you for another informative post. I really like how you can coalesce the various concepts into a cohesive clear essay.


Emergent line of dolphins? Phooey denier! For starters our time lapse camera at LatitudeX Longtitude Y on Beebopaloola atoll clearly shows sea monsters regularly on the horizon and they’re getting more prolific and threaten to overwhelm us all folks. This network of carefully selected time lapse cameras backs up past proxy sightings from a plethora of interviewed witch doctors that the Royal Society of Sea Monster Watchers have fed so diligently into our computer models. The science is settled and don’t pander to these unqualified cranks and dreamers.

The other Phil

Nice work, as usual.


I have a feeling that the CAGW modellers would simply claim that all of the emergent activity would “eventually” cancel out, thus leaving their cherished delusions intact.


Great article, Willis.
M. C. Escher may have had emergent phenomena in mind when he drew Waterfall:
Of course, perpetual motion machines are not viable but this example certainly makes you think.


The Willis I know, did not write this post, so who did ?

Gary Pearse

A climate E=mc^2 moment!! This is the most compelling presentation of what is really going on in climate and it doesn’t match anything we are getting from climate scientists. From the contrast, I imagine choice of climate science as a discipline has, to a large number of the experts, been through a belief that it is simple work – linear stuff attracts linear thinkers. You have shown that a highly complex goings-on can be explained convincingly by a real master thinker-educator. I’m proud to say I was here for this. The engineer in me says this is what its all about. Unfortunately instead of being heaped with prizes and honors, you should prepare for abuse – you are a lightning and lightening rod.

Pat Heuvel

Thank you Willis. Would it be correct, then, to summarise by saying: “the system should never experience runaway variation (be it warming or cooling) because emergent climate events will take place to regulate it”?

Gary Pearse

One thing I intended to add: from your explanation, when the warmth of summer moves up into the temperate zones, what do we get? Thunderstorms, water spouts, dust devils….when things warm up enough!

Great again Willis.Should be required reading.
BTW I am so glad that my God is not an “emergent”.
just saying………think about it

Beth Cooper

Oh so cool, Willis.
Modellers in cloud towers
Whiling away the tenured hours
Cannot model emergent phenomena
Like clouds and thunder-storm behavior.
Peut etre imagining it’s no problemo?


You scare the crap outta me


u.k.(us) says:
February 7, 2013 at 3:44 pm
The Willis I know, did not write this post, so who did ?
Never read (only skimmed) past the 3rd paragraph, Willis might have sent it, but he didn’t write it.
It has no “flair”, it reads like a tech seminar.
Writing has style, this has none.

Pat Heuvel:
At February 7, 2013 at 3:48 pm you ask Willis

Thank you Willis. Would it be correct, then, to summarise by saying: “the system should never experience runaway variation (be it warming or cooling) because emergent climate events will take place to regulate it”?

With respect, your question by implication – which your earlier post shows is unintentional – puts words in Willis’ mouth.
So, perhaps you will allow me to provide my answer to your question.
The climate system is chaotic and displays bistability (i.e. it seems to be stable in either glacial or interglacial conditions, and it ‘switches’ between these two conditions). Such behaviour is typical of chaotic systems with strange attractors. The emergent properties of the system are probably what holds the system close to either of its two apparently stable states.

Sanjay Punjab

Would not an intellectually curious person start with the question of why are we about 33C warmer than we should be?

Gene Selkov

It gave me a chuckle to note that we are unlikely to see an avalanche of comments on this article today or on any other day. And so be it; such things are better appreciated in peace in quiet, which I will only break for a moment to give my thanks.
It is an absolutely awesome piece of work, on many levels. To talk about a subject so big without losing track or getting drowned in details, and to arrive at any sort of conclusion in such a short time, having sufficiently covered all the essentials, is a remarkable feat. I see echoes of Prigogine and friends in your observations, but none of those guys were as eloquent and as focused as you are (although I fully admit I may have been too stupid to enjoy wrapping my brain around their philosophy and formalism).
While none of what you write about is new to me, I walk away from reading your work with an enhanced clarity of thought — thank you very much!

Excellent Willis.
Yet another proof that climate models don’t model climate reality!

Great work – thanks.
Also, as Philip Bradley says, bit different in the humid tropics, so it is also ‘work in progress’ ?


Great essay, Willis.
Wasn’t it Lindzen who said that most dynamic systems are self-regulating, as those that have a tendency to be self-reenforcing would have spun out of control long ago..or something like that..?
A very interesting topic with a lot of food for thought.

Bookmarked it, in my Thermostat Hypothesis folder: “Willis frames thermostat hypothesis as Emergent Climate Phenomenon”

I always felt thunderstorms would cool an “overheated” earth. However I also imagined that was why a “hot spot” had to be created high up in the troposphere in the tropics, in order for the models to alarm. Such hot air aloft would prevent the formation of thunderstorms, and keep thunderstorms from cooling the tropics. As soon as reality failed to show any tropical “hot spot,” Alarmism sprang a major leak and started sinking.
Thunderstorms are like a safety valve. When they fail to occur, (as in the case of the major “heat high” that caused the Dust Bowl,) you get your most murderous heat and worst drought.

AndyG55 says:
February 7, 2013 at 1:45 pm

Dr T G Watkins says:
at one point you say “The dry surrounding air is drawn in, loaded to the brim with moisture via the increased evaporation, and shot skyward at rates up to 10 m/sec”
Moist air will not generally travel upward at 10m/sec, probably about half that. (gravity/specific heat) However, approximately the same amount of energy is moved upwards.

I’m no glider pilot, so I don’t have a good understanding of life under a thunderstorm (which is the context of the 10 m/sec).
Once in a thunderstorm, updrafts can be much greater than that, witness hail formation. In 1960 Lt Col William Rankin became one of the first people to ride a parachute through a thunderstorm did it the hard way – by ejecting from a powerless F8U at 47,000 feet, above a thunderstorm. While there aren’t estimates of wind speed in the storm, he spent at least 25 minutes in the air and endured accelerations that must have led to velocity changes at least 10 m/sec.

Beautifully put. This is what they should be teaching in schools.

Stephen Wilde

A very well written article but overlaps with a lot of points that I and others have been saying for some time, notably:
i) That his thunderstorm hypothesis is sound but needs to be extended to the entire globe which is what he has now started to do..
ii) That as per my suggestion from some time ago ENSO occurs because the ITCZ is on average north of the equator which introduces an imbalance in solar input to the oceans either side of the equator. That imbalance builds up over time and periodically discharges into the northern oceans in El Nino pulses of warm water.
iii) He says this:
“The boiling water system simply moves energy through it at a faster rate, it doesn’t run any hotter”
Which is the analogy I have used several times in the past and have linked the boiling point of water to surface pressure which leads naturally on to the ideas of me and tallbloke concerning the effect of surface pressure on ocean temperatues and energy content.
In the past Willis has been very abrasive about so called ‘pressure heads’ but here he is close to conceding the point.
iv) “So increasing input may only increase the throughput, rather than increasing the temperature”
Exactly as I have been proposing but the faster throughput does involve a global circulation change as in the speed of my adiabatic loop.
v) “So when the forcing from CO2 increases a watt or two, in an accurate model the clouds will emerge a few minutes earlier on average across the tropics, and the balance will be restored. This system of control by emergent phenomena has worked very well for billions of years, and it handles large swings in radiation every single day—it won’t be altered by a few watts of extra forcing from CO2″
Been telling everyone that for 6 years but referring to the entire global circulation rather than just the diurnal timing of regional events.

Ric Werme,
Here is a damn interesting report on Col. Rankin’s adventure:


Great work as usual…
Living here in Panama, right under the ITCZ for much of the year, my reaction to first reading your thermostat theory was, well of course that is how it works. How else could you explain that the temperature where we live is virtually constant morning, noon and night all year. Thanks for fleshing out the story.
Here is a bit of a testimonial: We live at 1200 meters (4200 ft.) about 40km from both the Pacific and Caribbean coasts. During the rainy season, we sit right under the ITCZ and watch the thunderstorms rolling up the mountain from the Pacific. Here are the rainy season average temps for last year:
May 67.5
June 67.6
July 69
Aug 67.2
Sep 67.6
Oct 66.2
Nov 67.6
Dec 67.3
The min and max temps also fall consistently between about 58F and 81F. Glancing a the data,
If that isn’t the action of a thermostat, I don’t know what else to call it. Rainfall varies wildly (24″ in May, 1″ in Dec), but temps never vary. Our house has neither heating nor air conditioning and not once in five years have I put on a long sleeved shirt in the house or felt uncomfortably hot.
Keep at it Willis – it took Alfred Wegener a very long time and a lot of derision before his ideas about continental drift were accepted – and today, we look at the Earth and say, “Duh, well of course that’s how it works.”

Alan S. Blue

Dredge up links and references and shop this to computer modelling journals.
There are directly testable hypothesis stated here. For starters, carpet-bombing a single tropical oceanic gridcell with extensive temperature/pressure/wind/sunlight/humidity monitoring would be interesting.
The term “Climate Sensitivity” I’d mostly replace with something that highlights the local-and-instantaneous nature that you’re referring to though.


There’s that fish again.

Ken Stewart

Excellent and very compelling article. I hesitate to mention a couple of points which still puzzle me: During the Wet season (with high humidity and upper and lower atmosphere instability) clouds pop up and begin mushrooming very soon after dawn, and thunderstorms can occur at any time of the day or night. Perhaps time of day is not so important as energy available and conditions encouraging stronger convection? The energy in the atmosphere presumably is being stored in the humidity and only a little (relatively) extra energy (from the sun or from convergence from a local or regional upper level low pressure) will generate thunderstorms. However the high humidity and the resulting cloud development generally keeps the surface temperature much lower and fairly stable over many days. Can your idea be generalised to cover time spans longer than daily e.g. many days for the life of a tropical cyclone, or the active phase of the monsoon?
And re a previous comment doubting that humid air can rise at 10m per second- too right it can, and much more too. Don’t deliberately fly into a thunderstorm.


I’m glad to see something I had been positing for years articulated so well