Guest Post by Willis Eschenbach

There’s an old saying about models—“All models are wrong, but some models are useful.”

It’s often used to justify the existence of climate models. However, the obvious corollary to the old saying is “All models are wrong, and some models are useless.”

I’ve been told several times that it’s not enough for me to put together my theory that a variety of often-overlapping emergent phenomena act to govern the temperature of the planet. I also need to show that this is not already included in mainstream climate theory and expressed in climate models. And it’s true, I do need to do that. Hence, this post.

Let me digress for a moment to explain my theory. When I began seriously studying the climate 25 years ago now, everyone was looking at why and how much the global average surface temperature was rising. But because of my experience with a variety of heat engines, I was struck by something completely different. I looked at the earth as a gigantic heat engine. Like all heat engines, it has a hot end (the tropics) where the energy enters the system. It then transports the energy to the cold end of the heat engine (the poles), where it is rejected. In the process it converts some of the energy into physical work, driving the endless motion of the atmosphere and the oceans.

Now, when you analyze a heat engine, say to determine its efficiency or any other reason, you have to use the Kelvin temperature scale. That’s the scale that starts at absolute zero (-273.15°C, or -459.67°F). The units of the Kelvin scale are called “kelvins” (not “degrees kelvin”), and one kelvin is the same size as one degree Celsius, which is also called one degree Centigrade. The kelvin is abbreviated “K”.

With that as a prologue, here is the oddity that attracted my attention. Over the entire 20th century, the temperature of the planet varied by less than 1°C, which is to say, less than 1K. And with the surface temperature of the planet being about 288K, that represents a variation of about a third of one measly percent … I found this stability to be quite amazing. The cruise control on your car can’t keep your car speed within that small a variation, well under 1% peak to peak.

Note that this stability is not due to thermal mass, even the thermal mass of the ocean. At 45°N in the mid-Pacific, the sea surface temperature sometimes changes up to 5K (5°C, 9°F) in a single month. And the land changes temperature even faster than the ocean.

So I started thinking about what kind of governing mechanism could keep the temperature so stable over an entire century full of El Nino events and volcanic eruptions and all kinds of things you’d expect to disturb the temperature. Because I was looking for something that would lead to long-term stability, I spent a long time contemplating slow processes like the gradual weathering of the mountain rocks changing the CO2 content of the atmosphere, and the buffering of the CO2 content of the ocean via calcium carbonate precipitation.

During this time I was living in Fiji … hey, the waves aren’t going to surf themselves, someone has to do it. And hanging out outdoors a lot in the tropics, I got to noticing the repeating daily weather pattern. I realized that I was looking at the hour-by-hour emergence of various phenomena that put a cap on how hot it could get. And I realized that if there are emergent phenomena that prevent a day from overheating, they will also prevent a week, a year, or a millennium from overheating

Let me borrow an explanation of what I saw from a previous post of mine.

At dawn, the tropical 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 1. 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. This is the first transition, from random circulation to organized circulating cells that characterize Rayleigh-Bénard circulation.

These cells transport both heat and water vapor upwards. By late morning, the Rayleigh-Bénard circulation is typically strong enough to raise the water vapor to the local lifting condensation level (LCL). At that altitude, the water vapor condenses into clouds as shown in Figure 3.

Figure 2.  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 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 totally separate emergence of the clouds that mark the upwelling columns of air in the circulation.

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. Due to the increasing clouds, the earth’s albedo (reflectivity) increases, so more of the sunlight is reflected back to space. As a result, 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 sensitivity of surface temperature to radiative forcing from either the sun or from CO2. 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 3. 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, which then warms the air. The low-density air rises. When that Rayleigh-Benard circulation gets strong enough, thunderstorms start to form.

Once the thunderstorm is started, the second fuel is added to the fire—that fuel is 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 some part of the fire’s energy is used to power a bellows to make the fire burn even hotter. Once it is started, it is much harder to stop.

This gives thunderstorms a unique ability that, 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, heat pipes that transport warm air rapidly from the surface to the lifting condensation level where the moisture turns into clouds and rain, and from there to the upper atmosphere without interacting with the intervening greenhouse gases. The air and the energy it contains is moved to the upper troposphere hidden inside the cloud-shrouded thunderstorm tower, without being absorbed or hindered by GHGs on the way.

Thunderstorms 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 meter 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 energy that is absorbed during all of the previously described regimes. How does it do this? Another emergent phenomenon … oceanic overturning.

Figure 4. 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 “mixed” 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 largest amount of 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 like a drunk walking on a narrow elevated walkway. The guardrails are not feedback—they are a place where the rules change. The various thresholds in the climate system are like that—if you go over them, everything changes. As one example of many, the ocean before and after the onset of nocturnal 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

With the idea of emergent thunderstorms and cumulus fields in hand, let me note that we can determine where this phenomenon is happening. In areas in the tropics, the warmer it gets, the more clouds appear—first the cumulus fields, then the tropical thunderstorms. As a result, the warmer it gets, the higher the tropical albedo gets, and the more energy is reflected back to space instead of warming the surface. In other words, in the tropics, the albedo and the temperature are positively correlated.

Outside of the tropics, the opposite goes on. The colder it gets, the more we get storms, ice, and snow. As a result, the colder it gets, the higher the albedo gets. Outside the tropics, the albedo and the temperature are negatively correlated.

And this is clearly revealed in the CERES satellite dataset, as shown in Figure 5 below.

Figure 5. Correlation of albedo and surface temperature. Perfect correlation, where both variables move in total unison, has a correlation value of 1.0. Perfect anti-correlation, where one variable increases whenever the other decreases, has a correlation value of -1.0. A correlation of zero means no relationship between the two variables, albedo and temperature.

Some things of note about Figure 5. As predicted by my theory, in much of the tropical ocean the albedo is positively correlated with the temperature, but this is true only in a few isolated areas outside of the tropics. The arctic and antarctic are strongly anti-correlated (negative correlation), with a correlation of ~ -0.6. In the tropics, on the other hand, the average correlation is zero. Land overall has a strong negative correlation, ~ -0.5.

The tropical correlation of zero is of interest because this is what we would expect if the tropics are regulating the temperature—the earth would warm until a slight increase in temperature pushes the albedo/temperature correlation positive, whereupon the earth would tend to cool.

And that brings us to the question of how useful the models are. I went and got the historical runs of the MIROC-ESM model, which covers the period from 1850 to 2005. To compare with the CERES data, I looked at four separate 21-year periods, the same time span as the CERES data. Here is the first of those periods, 1850 – 1870, showing the results in model-world. I’ve included the real-world data (left graphic) for comparison.

Figure 6. As in Figure 5, but using data from the MIROC-ESM climate model

The most obvious difference is that in model-world, the polar and sub-polar regions both have some areas of positive correlation that do not occur in real-world. There is also much less positive correlation in the tropics, model-world correlation of -0.15, versus a real-world tropical correlation of 0.0.

Another way to look at the differences is by averaging the correlation by latitude. Figure 7 shows that result.

Figure 7. Average correlation of albedo and surface temperature, by degree of latitude, CERES and MIROC data.

As you can see, model-world is very, very different from real-world.

My next question was, just how stable over time is this correlation between albedo and temperature, both in the real world and in model-world. To investigate this, here are the first and second halves of the CERES dataset.

Figure 8. Correlation of temperature and albedo, first and second halves of the CERES dataset.

Note that all of the correlations of different geographical areas, and of land and sea, are within 0.01 or so of each other. So this is a very stable relationship. Next, here are four different 21-year periods from the start to the end of the MIROC model output.

Figure 9. Correlation of temperature and albedo, four 21-year periods of the CERES dataset.

As with the CERES data, these are all very close. Here are the average correlations by latitude of the four MIROC model results and the two CERES results.

Figure 10. Correlation between albedo and temperature by latitude, four 21-year periods from the MIROC model results (1850-1870, 1900-1920, 1950-1970, and 1985-2005) and two 10-year periods from the CERES satellite data (2000-2009, and 2010-2019).

The relationship between albedo and temperature in both real-world and model-world is very stable, even over a period as short as 10 years, indicating that this relationship between albedo and temperature provides a meaningful insight into how the climate system actually works. And all of the model results are very different from the CERES satellite data.

Conclusions:

• My theory that the temperature control of tropical albedo via emergent phenomena exerts a thermoregulatory effect is supported by these findings.

• The gridcell size of current climate models is far too large to simulate individual thunderstorms. For this among other reasons, it is unlikely that the models incorporate realistic representations of the thermoregulatory effects of tropical thunderstorms.

• At least in the case of the MIROC-ESM model, the model representation of the correlation of temperature and albedo is quite unlike what happens in the real world.

• The geographic stability of the correlations over time, in both the real world and in model-world, indicates that this is a persistent diagnostic feature of the climate.

w.

MY USUAL: I can defend my own words and am happy to do so. I cannot defend your understanding of my words, so please, when you comment quote the exact words you are referring to.