The Details Are In The Devil

Guest Post by Willis Eschenbach

I love thought experiments. They allow us to understand complex systems that don’t fit into the laboratory. They have been an invaluable tool in the scientific inventory for centuries.

Here’s my thought experiment for today. Imagine a room. In a room dirt collects, as you might imagine. In my household I’m responsible for keeping the dirt down, so I get out my vacuum cleaner to clean up.

But suppose I had a magic way to handle that dirt. Suppose there was a class of beings such that whenever there was a concentration of dirt in some small part of the room, one of these beings would pop into existence, clean up the dirt, and then disappear. We’ll say this being is a rare relative of the Tasmanian Devil, call it a “Tasmanian Dirt Devil” (TDD).

Figure 1. One of the few authenticated photos of the elusive Tasmanian Dirt Devil (TDD) cleaning a floor in its natural habitat. PHOTO SOURCE: Annals of Cryptozoology, Vol. 6, 1954

After observing the room for a while, we realize that the the TDD only appears when there is some small area of the floor with more than a certain concentration of dirt. However, we see that the TDD does not limit itself to that small concentration of dirt. It moves around and cleans out any other smaller concentrations of dirt around it as well. Once the area is cleaned to a certain level, the TDD vanishes, leaving the room somewhat cleaner. We also see that on days when traffic is heavy, often there are a number of Tasmanian Dirt Devils working on the room at once. No single TDD cleans the whole floor, but the floor is never dirty anywhere for long.

Now, here’s the question for our thought experiment: can we use a computer to model the effect of the TDDs, for example to calculate the rate at which dirt is being added to the floor, based on the average amount of dirt on the floor?

I say we cannot model it adequately if our only input to the model is the average level of dirt on the floor. Here’s two circumstances to explain part of why the problem is ugly.

1. Someone spills a very small bit of dirt on one corner of the floor. Because the dirt is concentrated in one area, a TDD materializes, cleans up the dirt and the surrounding area, and vanishes.

2. Four people simultaneously spill a very small bit of dirt in all four corners of the floor. Four TDDs materialize, clean up the dirt and the surrounding areas, and vanish.

If all we have is the average dirtiness of the floor, a few bits of dirt which are rapidly cleaned up will make little difference in a daily average of floor conditions. Despite those small fluctuations, in one case there is four times as much dirt being added to the system as in the other case.

So I think we can agree that in our thought experiment, the average dirt level of the floor is not linearly related to amount of dirt being added to the system. If we want to model what’s going on, it is very difficult to do it based on the average dirt level. We need much more detailed information in both time and space.

Here’s an illustration of a different problem. Again, two conditions.

1. Someone spills a very small bit of dirt on one corner of the floor. Because the dirt is concentrated in one area, a TDD materializes, cleans up the dirt and the surrounding area, and vanishes. Average dirt level on the floor ends up slightly below where it started.

2. Someone spills a very small bit of dirt evenly all over the floor. There is no concentration of dirt above the threshold level, so no TTD appear.  Average dirt level on the floor ends up slightly above where it started.

Again, as you can see, average dirt levels and amount of dirt added show no correlation.

So what do Tasmanian Dirt Devils have to do with the climate? If we saw something like a TDD in our kitchens, we’d be amazed. However something just as amazing exists in the climate. We’re not astounded by it all purely because are so familiar with it. However, let me take a small digression on the way to explaining the relationship between climate and Tasmanian Dirt Devils.

Emergent phenomena are a special class of things. They can be recognized by certain traits that they have in common. In general, emergent phenomena arise spontaneously at a certain time and place. Typically they exist for a definite duration, and eventually dissipate at another time and place. Their appearance is often associated with some natural variable exceeding a threshold. Often they can move about somewhat independently. If so, although they have general tendencies, their specific actions are usually very difficult to predict.

One clear characteristic of emergent phenomena is that the properties of emergent phenomena are not apparent in the underlying stratum from which they arise.

Examples of natural emergent phenomena with which we are familiar include sand dunes, the behaviour of flocks of birds, vortexes of all kinds, termite mounds, consciousness, and indeed, life itself.

Regarding climate, there is one particularly important class of natural emergent phenomena. These are the natural “heat engines”. Heat engines are able to turn heat into work. Examples of these natural emergent heat engines include hurricanes, thunderstorms, dust devils, tornadoes, and the Hadley Circulation itself.

The most common and most important of these heat engines are thunderstorms. Thunderstorms do two kinds of mechanical work. First, they power the deep tropical convection that is the driving force for the circulation of the entire ocean and atmosphere.

 

Second, thunderstorms drive what can be thought of as a sophisticated air conditioner, using a variation of the standard refrigeration method. This method, used in your home air conditioner, uses ambient heat to evaporate a liquid. This removes the heat from the area where the evaporation is taking place.

Then you move the evaporated liquid (and the latent heat it contains) to another location. In the new location, you condense the liquid, releasing the latent heat of condensation. The heat is then transferred to the surroundings, and the condensed liquid is returned to start the cycle over.

In the natural Hadley air conditioner we call a thunderstorm, the same process takes place. Water is evaporated at the surface, cooling the surface. The water vapor rises to the clouds. There it is condensed. The latent heat it contained is released, rises, and is radiated out to space.

Meanwhile, in addition to losing latent heat through evaporation, the surface is further cooled by the fall of cold rain from the thunderstorm. This is accompanied by an entrained cold wind, which assists in the cooling.

In both cases (Hadley circulation and refrigeration) the net effect of a thunderstorm is to remove energy from the surface and move it up into the troposphere.

Having digressed, I return to what climate has to do with Tasmanian Dirt Devils.

Consider our thought experiment. If you replace TDDs with thunderstorms, and replace the room with a climate model gridcell of the tropical ocean, and replace dirt with energy, you have an excellent description of the action of the climate system at the hot end of the climate heat engine, the Tropics.

Whenever there is a “hot spot” on the tropical ocean or land, if it is hot enough, a thunderstorm springs up and starts pushing huge amounts of energy vertically. As the thunderstorm moves across the surface, it moves towards the warmest area in its path. This preferentially cools the warmest areas. In addition, it continues to do so until the local surface temperature is a few degrees below the initiation temperature.

There are some conclusions that we can draw from this thought experiment:

1. Increasing the rate at which dirt is added does not commensurately increase the average dirtiness of the floor. Similarly, increasing the rate at which energy is added to the Tropics does not commensurately increase the surface temperature.

2. Attempting to model our thought experiment using room-wide averages won’t work because Tasmanian Dirt Devils are driven by local conditions, not average conditions. Similarly, attempting to model our climate using gridcell-based averages won’t work because thunderstorms are driven by local conditions, not average conditions.

3. Modeling a system which contains simple linear feedback is not too difficult. In that case, average changes in the response variable are linearly related to changes in the forcings. Modeling a system with an active governor, like TDDs or thunderstorms, requires a much different type of model. As I showed above, in that case the response variable is not linearly related to the forcing.

4. Thunderstorms preferentially cool the warmest areas. Although the average temperatures might be the same, this has a different effect than a gridcell-wide uniform cooling. Again, this makes the modelling of the system more complex.

Let me be clear about what I am saying about models. I’m not saying that we can’t model the climate. I think we can, although it won’t be easy. But we have to model it the way it really is.

It is not a system with a linear relationship between forcing and temperature as conventional theory claims. It is a dynamic governed system with a complex, nuanced, non-linear response to forcing. Yes, we can model that. But as I show above, we can’t do it under the assumptions made by the climate models.

Could we model it parametrically, without having to model individual thunderstorms? Probably … but the model has to be designed to do that. And the current climate models either are not designed to do it, or are not doing it successfully.

How do I know that they are not doing it successfully? Drift. Consider the room with the Tasmanian Dirt Devils. If there is no change in the amount of dirt being added per day, the system will rapidly take up a steady-state condition.

The models are subjected to a very similar test. In this test, called a “control run”, every one of the forcings of the model is held exactly steady. Then the models are run for a number of model years. Figure 2 shows the results from the Coupled Model Intercomparison Project (CMIP) control runs. We would expect the models to rapidly take up a steady-state condition.

Figure 2. Results of control runs for 16 coupled atmosphere-ocean climate models. SOURCE

Notice the drift in the surface air temperature in a number of the runs over the 80-year simulation. The CERFACS model is the worst, but even a mainstream model like the NASA GISS model of James Hansen and Gavin Schmidt shows drift over the 80 years.

How much drift? Well, the trend in the NASA GISS model control run is a warming of about 0.7°C per century. This is about the same as the IPCC estimate of the warming over the last century, which is 0.6°C.

Now, you could look on that GISS model 0.7°C per century inherent warming drift with no forcing change as a bug. I prefer to think of it as a feature. After all, it lets Hansen and Schmidt simulate the warming of the 20th century without the slightest change in the forcings at all, and how many models can do that?

However, that drift does strongly suggest that they are not modelling the climate correctly …

As always, the quest for understanding continues. My best regards to all,

w.

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incervisiaveritas

Brilliant analogy! Thank-you.

Scott Brim

See http://climateaudit.org/2010/12/11/remember-gavins-taunts-about-steig-et-al-2009/#comment-248841
In that CA thread, I quoted from a post made by Bender, in which he offered his own translation of Realclimate’s criticisms of the various CA and Air Vent analyses of the Steig 2009 Antarctic warming paper, as follows: “ ……. Because once we figure out what regulates natural climatic variability we’ll be in a much better position to estimate GHG contributions to warming, which are pretty uncertain ..….”
I asked the following question of the CA readership:
Focusing on the phrase “what regulates natural climatic variability”, is it possible to state that within some range of temperature values, apparent changes in the earth’s global mean temperature could be the result of system drift from the current long-term GMT trend, drift which has no identifiable driving mechanism whatsoever?
If this is so, if a long-term trend in GMT can drift within certain temperature ranges, but with no identifiable driving mechanism whatsoever being present to cause that drift, is it possible to state with any reasonable assurance what the temperature range of the system’s inherent drift might be?
On that CA thread, I also remarked that perhaps this is a question Dr. Koutsoyiannis might be interested in discussing, if he is following that particular CA thread.
So far, as of December 13th, there has been no response from anyone on CA in response my question. Willis, perhaps you would like to take a stab at it.

Geoff Sherrington

Party pooper. I was working upon a sequence of posts on Judith Curry’s blog to say much the same thing. You’ve sprung my trap.
The TD, the native Sarcophilus harrisii , you might note, starts with sarc on.

John F. Hultquist

Willis,
Are you on a warm island in a hammock sipping on something? Whatever it is, I want some.
This post is like a shaggy dog story. http://en.wikipedia.org/wiki/Shaggy_dog_story
You went a long and circuitous route to the punch line, which is very good. I trust it will hold up under the withering attack of warmest scolds.

Baa Humbug

Willis likes thought experiments.
I like Willeses articles, from which I get thought experiments. 2 for the price of 1. I win.

Mike Jowsey

How can I trade in my super-turbo-self-cleaning vacume cleaner for a bunch of those TTD’s? I’m guessing I’m gonna have to trade a bunch of carbon credits to make up the difference. I hope the CCX can assist.

TimTheToolMan

Stop it with these these theories about how the climate works!
You ‘ll get much more palatable “AGW Style” results if you’re more dispassionate about the data and apply analysis that ignores any semblence of reality.

Very interesting, a good job of making it so. I strikes me that nature of these thought games is more then slightly associated with the nature of deterministic models of dynamic systems. Interesting and more fiction then reality.

Dave F

I was hoping you would carry the thought experiment to left field and suggest that the TDDs somehow add more dirt to the average using the dirt that already exists. Excellent analogy Willis!

Malaga View

Wonderful posting… music to my ears.
I prefer to think of it as a feature.
Unfortunately I think you are totally correct here… my guess is that this temperature drift has a non-linear forcing relationship that drives budget drift exponentially upwards… and when this pool of excess monetary resources reaches a critical point the system spontaneously generates The Warming And Terrifying Scientists that converts the budget surplus into a hot air feedback that drives the temperature drift ever higher.

Dave F

My own post reminds me of this from George Carlin:
“A crumb is a magical thing. It’s the only thing on Earth that when you split it in half, you don’t have two half-crumbs, you have two crumbs.”

John_in_Oz

Are these local conditions high local temperatures, or local high temperature gradients?
(Or some mixture, of course…) The first condition implies Global Warming is self-limiting.
As I understand it, the Climate models forecast greater temperature increases at the Poles, from which I infer a reduced temperature gradient across the globe. Consequently, in the second case there is more heat/dirt before a thunderstorm/tdd, not less.
The above question seems to me to be important. On it’s answer depends either a negative feedback or a positive one. Unless the question is too simplistic, of course.

Malaga View

The SOURCE also shows that GISS has an upward precipitation drift of 0.1 mm per day over 80 years… which, according to my maths, equates to an additional 45 mm of precipitation per year after 100 years… but I guess this precipitation must be composed of magic water © that doesn’t cool the planet but manages to accumulate in the oceans and drift sea levels ever higher.
http://www-pcmdi.llnl.gov/projects/cmip/overview_ms/control_tseries.pdf

Doug in Seattle

So it would seem that what appear to be random, chaotic events at the climate model grid scale are in fact predictable phenomena when examined at the proper scale.

FWIW, it looks like some folks have found ENSO to be an ’emergent behaviour’ in a computer model. No external events need apply. Just a natural instability.
http://chiefio.wordpress.com/2010/12/13/enso-a-natural-oscillation/

Grumpy old Man

Dear Willis. Brilliant analogy, Have you considered developing it into a short educational cartoon?
“Vortex” has a Latin root. The plural is “vortices”, not “vortexes”

charles nelson

Well done Sir.
May I add something I think might be relevant to your piece, it’s a simple thought experiment and it stumps most Warmists…they get that ‘look’.
I ask them to recall the last time they took a commercial jet flight.
To picture themselves coming up through the clouds, rising above them – to cruising altitude.
I ask them if the Captain at any point mentioned the temperaturere…” we’re flying at 29,000 feet and the temperature is….” or if perhaps there was a Temperature Display in the cabin (I’ve seen this on several airlines.)
I then ask them if they remembered the outside temperature at cruising altitude.
(At this point I am amazed by the percentage of people who ardently defend the ‘science’ of the greenhouse theory but have no idea of this fairly simple fact.)
A few know the temperature range I am discussing and we proceed.
We establish quickly that there is a vast resevoir of thin cold air just above our heads, every time we look up and see a contrail we are looking at frigid air.
I then ask, “What does hot air do, in nature?”.
“Rises.” can be the only only answer.
So imagine yourself looking out of the window of your plane…on the display it says minus 30 degrees. Down below are clouds…some are flat but some are high, in fact some are towering magnificently into the chilled atmosphere – indeed the Captain has told you to strap your seatbelts because of turbulence caused by high altitude air currents.
Now given that hot things rise, and hotter things rise higher/faster- if….if for some reason our planet was to become ‘over heated’ surely all the clouds would just rise a few metres higher and lose, through radiation whatever excess heat carried them there.
I conclude by asking them if they can honestly argue, given the vast resevoir of coldness that begins a mere five miles above our heads and extends upwards towards the void, that the earth could ever lose its ability to shed its heat into space?

OT

Thank you for the illustrative thunder/refrigeration cycle comparison, never thought it that way before.
But for the models, in my view 80 years (cycles) do not yet prove that models are bad (that they leak energy), but leave possibility that modelled system has multiple solutions beweeen which it oscillates, or have bad initial conditions and very long time constant (are these atmosphere only?). They should run models long enough to have them settle, and with more than one set of forcings.
Multiple degree offset discrepancy between models begs explanation.

AusieDan

I like he explanation of how storms take heat away from the earth and allow it to be expelled to space. That neatly explains why raising CO2 levels do not cause the temperature to rise.
I am not quite as comfortable with the idea of drift.
The climate generally and temperature & rainfall in particular are chaotic systems.
Drift in a chaotic system infers high Hurst numbers (above 0.5 – Brownian randomness). Such systems are auto correlated (eg the stock market) and tend to drift up or down untill Hurst’s “Joker” suddenly intervenes, the system is reset and goes off in a completely new direction.
Both rainfall and temperature in a number of Australian locations have extremely low Hurst numbers (Sydney Observatory Hill approximately 0.02). Such systems have a strong tendency to revert to the mean and are trendless if left to themselves.
The only interference that I have found is UHI. It’s commencement can be clearly identified in both Sydney and Adelaide temperatures for example.
In each case I have positively identified the massive change in the built environment the allowed UHI to begin to raise the temperature. (Rainfall is imune so it is the ideal control for UHI).
So I can’t see that random drift is the answer.
At least in many well dispersed locations of Australia.

hotrod ( Larry L )

John_in_Oz says:
December 13, 2010 at 11:04 pm
Are these local conditions high local temperatures, or local high temperature gradients?
(Or some mixture, of course…) The first condition implies Global Warming is self-limiting.

In the case of thunderstorms, it is more than temperature. For example you don’t have many thunder storms in the Sahara. You also need humidity, and an atmospheric profile that creates instability, along with some mechanism to initiate lifting of the air mass to start the process.
Instability is created when a mass of warm moist air is over laid by dryer air. This creates a situation that if a parcel of that warm moist air is forced to rise due to any one of several causes it will continue to rise due to it being lighter than the surrounding air. Lift can be due to such things as being pushed over rising terrain by winds, or convergence where two directions of flow collide forcing the air upward where they meet. A frontal passage (rapid changes in barometric pressure) is often a trigger to initiate lift, or in cases of severe instability, just random motions generate the upward movement which becomes self reinforcing.
As the warm moist air rises, it cools more slowly than the dryer air above and around it due to its higher heat capacity, so the higher it gets lifted, the more it buoyant the parcel becomes. At some point the moisture begins to condense releasing latent heat of condensation. This extra heat then drives the upward motion ever faster creating the strong updraft that builds the convective column of the thunder storm.
You need heating, moisture and the proper air temperature profile, and usually some trigger to initiate lift, with the proper local wind flow (shear) .
The local winds need to be such that the updraft is fed more warm moist air as the updraft forms, without the local winds being too strong. If too strong, they can tear the convection apart and re-mix the rising parcel with dryer surrounding air killing the convection.
Some of these variables are captured in indices like.
LI – (Lifted index)
CAPE – (convective available potential energy)
dew point (humidity) vs local air temperature and air temperature at higher levels.
Skew T profiles (plots of the atmospheric conditions at different altitudes.
Storm watchers pay more attention to these variables than they do just temperature.
At certain combinations of LI and CAPE thunderstorm development is almost guaranteed, as long as there are not competing effects like unfavorable winds (very high winds) or a lack of lift to initiate the development of the storm.
http://en.wikipedia.org/wiki/Lifted_index
http://en.wikipedia.org/wiki/Convective_available_potential_energy
http://airsnrt.jpl.nasa.gov/SkewT_info.html
Larry

Ian H

If you believe feedback (eg from water vapour) is positive the you are asserting that the climate is inherently unstable. Any model built with these assumptions is going to drift in the absence of any forcing. Indeed drift is too mild a term as the behavior of such a system could be quite wild; massive oscillations, aymptotes, all bets are off in an unstable chaotic system with positive feedback.
It has always puzzled me that the rhetoric of climate change is all about nicely predictable linear responses to forcing. This much reduction of CO_2 needed to reduce that much warming, and so forth. Whereas the assumption of positive feedback which is needed to get alarming results posits an unstable climate where the response to forcing is likely to be highly non-linear and indeed where the climate may well behave chaotically even in the complete absence of forcing.
Without positive feedback the temperature change caused by increased CO_2 is too small to be a problem. With positive feedback the temperature response might indeed be alarming, however there would be no point in trying to control CO_2 emissions because such a system is inherently so unstable that nothing we could do would ensure climate stablity.

wayne Job

Thank you Willis, stick to the heat pump it is the only valid and measurable system that makes sense. Chaos tending always to simplicity and beauty in a non linear system, even vortices are perfection and beauty.

oldseadog

But….. but….. there is only one graph.
What happened?
Run out of graph papar?
Very good, though.

Willis.
Follow the drift into the attribution studies.
AR4 chapter 9. Attribution studies. Supplmental material. page 9.5
FAQ 9.2
only 14 models are selected for attribution studies. Those with drift of .2C per century or lower.
Question: when trying to do an attribution study, they select models with small drift.
Small drift means tighter CIs. Tighter CIs on the models means you have an easier time rejecting the null. On the other hand when projecting the future they select all the models, including those with higher drift. Higher drift means wider CIs. Wider CIs on the forecast means lower probability of conflciting with Obs.
I’ve be bugged by this for a couple years. have a look.

Mike McMillan

Given the scarcity of TDD’s, the solution to global warming would then be maid service.

Robbo

@ Grumpy
The Latin plural of vortex is vortices, but illis writes in English, so “vortexes” is good.
@ Ian H
It is the net feedback which governs the system, not any one component. It seeems to me bleeding obvious that the net feedback on the warming side is strongly negative, since the climate has been bouncing around for millions of years under an upper bound a few degrees higher than todays. On the cooling side, again there must be negative feedback, or we would slide into the ‘snowball earth’ stable solution, but the Ice Ages show us that the lower bound on temperature is a lot lower than today’s temps, and given the long ‘dwell time’ in Ice Ages, the feedback seems to be weaker near the lower bound than near the upper bound. For me the challenge is not to develop more precise models based on assumptions about feedbacks, but to elucidate the cause-and-effect relationships, which will allow the feedbacks to be estimated / calculated, rather than assumed.

Brian H

charles n.;
Not tea bags!
But it’s “reservoir”, not “resevoir”. And yes, that 2nd ‘r’ IS pronounced.

Stefan

So here’s what “settled” means: “we stopped thinking”.

Brian H

Robbo;
unfortunately, you’re correct. Either is acceptable. But “mouses” is NOT! >:(
About the bounds and feedbacks:

Blog: Science
Researcher: Basic Greenhouse Equations “Totally Wrong”
Michael Asher (Blog) – March 6, 2008 11:02 AM \

New derivation of equations governing the greenhouse effect reveals “runaway warming” impossible
Miklós Zágoni isn’t just a physicist and environmental researcher. He is also a global warming activist and Hungary’s most outspoken supporter of the Kyoto Protocol. Or was.
That was until he learned the details of a new theory of the greenhouse effect, one that not only gave far more accurate climate predictions here on Earth, but Mars too. The theory was developed by another Hungarian scientist, Ferenc Miskolczi, an atmospheric physicist with 30 years of experience and a former researcher with NASA’s Langley Research Center.
After studying it, Zágoni stopped calling global warming a crisis, and has instead focused on presenting the new theory to other climatologists. The data fit extremely well. “I fell in love,” he stated at the International Climate Change Conference this week.
“Runaway greenhouse theories contradict energy balance equations,” Miskolczi states. Just as the theory of relativity sets an upper limit on velocity, his theory sets an upper limit on the greenhouse effect, a limit which prevents it from warming the Earth more than a certain amount.
How did modern researchers make such a mistake? They relied upon equations derived over 80 years ago, equations which left off one term from the final solution.
Miskolczi’s story reads like a book. Looking at a series of differential equations for the greenhouse effect, he noticed the solution — originally done in 1922 by Arthur Milne, but still used by climate researchers today — ignored boundary conditions by assuming an “infinitely thick” atmosphere. Similar assumptions are common when solving differential equations; they simplify the calculations and often result in a result that still very closely matches reality. But not always.
So Miskolczi re-derived the solution, this time using the proper boundary conditions for an atmosphere that is not infinite. His result included a new term, which acts as a negative feedback to counter the positive forcing. At low levels, the new term means a small difference … but as greenhouse gases rise, the negative feedback predominates, forcing values back down.
NASA refused to release the results. Miskolczi believes their motivation is simple. “Money”, he tells DailyTech. Research that contradicts the view of an impending crisis jeopardizes funding, not only for his own atmosphere-monitoring project, but all climate-change research. Currently, funding for climate research tops $5 billion per year.
Miskolczi resigned in protest, stating in his resignation letter, “Unfortunately my working relationship with my NASA supervisors eroded to a level that I am not able to tolerate. My idea of the freedom of science cannot coexist with the recent NASA practice of handling new climate change related scientific results.”
His theory was eventually published in a peer-reviewed scientific journal in his home country of Hungary.
The conclusions are supported by research published in the Journal of Geophysical Research last year from Steven Schwartz of Brookhaven National Labs, who gave statistical evidence that the Earth’s response to carbon dioxide was grossly overstated. It also helps to explain why current global climate models continually predict more warming than actually measured.
The equations also answer thorny problems raised by current theory, which doesn’t explain why “runaway” greenhouse warming hasn’t happened in the Earth’s past. The new theory predicts that greenhouse gas increases should result in small, but very rapid temperature spikes, followed by much longer, slower periods of cooling — exactly what the paleoclimatic record demonstrates.
However, not everyone is convinced. Dr. Stephen Garner, with the NOAA’s Geophysical Fluid Dynamics Laboratory (GFDL), says such negative feedback effects are “not very plausible”. Reto Ruedy of NASA’s Goddard Institute for Space Studies says greenhouse theory is “200 year old science” and doubts the possibility of dramatic changes to the basic theory.
Miskowlczi has used his theory to model not only Earth, but the Martian atmosphere as well, showing what he claims is an extremely good fit with observational results.

David Socrates

Willis Eschenbach, ably assisted by Charles Nelson (December 13, 2010 at 11:48 pm), have between them most entertainingly put this global warming conundrum to bed.
Sensible skeptics start from the twin observations that:
(1) Contrary to uninformed doom mongering over the past 30 years, at only 0.5degC or so per century the Earth’s temperature is steadfastly failing to rise in correspondence with the sharp (~30%) post-WW2 upturn in anthropogenic GHGs.
(2) The straightforward physics of CO2 indicates that an increase in its atmospheric concentration should have a significant and potentially worrying warming effect.
Consequently, we reason that there must be something else holding the temperature down. What is it?
As I have blogged many times both here and elsewhere, my best thought experiment is my 40kW house central heating system which keeps the temperature inside my house in the winter very close to 21degC simply because of the strong feedback effect provided by its thermostat, which constantly measures the house temperature against a fixed physical set point.
Suppose I then turn on the 3kW electric fan heater that I keep only for occasional use and emergencies. Surprisingly (to some people), my house does not increase in temperature from its 21degC set point. Why is this? It is because any additional heating effect from the 3kW heater is exactly offset by the house thermostat which shuts down the central heating boiler commensurately.
The CO2 warming effect has no (efficient) thermostat. The hydrological cycle, via convection, thunderstorms, cloud formation, etc., has a very effective one. Therefore the CO2 warming effect is completely enclosed within the highly regulated hydrological feedback loop, in exactly the same way that the warming effect of my unregulated fan heater is completely enclosed within the warming effect of my highly regulated central heating system.
Warmists can’t seem to get this idea of one warming effect being enclosed within another and therefore being entirely neutralised.
If only they were control system engineers!
End of story.

As usual, Willis takes an initially reasonable analogy – and misuses it. His details are the devil. In this case, his “thought experiment” does not give the result he wants it to. One could indeed successfully model “the rate at which dirt is being added to the floor, based on the average amount of dirt on the floor”. I don’t “agree that in our thought experiment, the average dirt level of the floor is not linearly related to amount of dirt being added to the system”, because it is. Contrary to his claim that “average dirt levels and amount of dirt added show no correlation”, they will indeed be correlated, with the specific correlation dependent on the algorithm employed by the dust devils. The correlation is certainly not perfect, and the linear relationship is not the only relevant phenomenon, because, as he points out, the actual ratio depends on the local distribution of dirt; but, for typical scenarios in which the average manner in which dirt is deposited is fairly consistent, a kitchen-wide (“global”) linear model is likely to work pretty well, as a predictor of the overall dirtiness of the kitchen. I’d actually be quite surprised if the manufacturers of dust devils (which are now starting to appear on the market in reality) don’t use some such computer model.
The reason that Willis’s thunderstorm thermostat doesn’t do what he thinks it should is that there are still underlying broadly linear (or at least monotonic) dependencies on temperature and insolation that the local feedback from his “governor” does not eliminate. For example, thunderstorms are driven by a temperature difference between surface and stratosphere, not the absolute temperature; and there is evidently a variable latitude, or range of latitudes, by which the tropical mechanism ceases to operate. He’s had this pointed out to him several times before, but prefers to ignore it.

Alex the skeptic

Great post and analogy Willis, which reminds me: I’ve been meaning to say the following for some time now:
On negative/positive feedbacks:
Place a small sphere inside a smooth round bowl and give it a small kick. This will roll up and down the sides and through the centre of the bowl until the sphere stops to rest at the centre, bottom of the bowl, where it finds its stable natural position inside the bowl after the energy is dissipated. The oscillation will be repeated when the sphere is acted upon by another force. This is analogous to negative feedback.
Now turn the bowl over and rest the small sphere on the vertex of the smooth bowl and let it go free. The sphere will hockey-stick down, never to be able to go up again to the top of the bowl. This is positive feedback.
If the earth’s climate had positive feedback due to anything, there would not be any life on earth, me thinks. Consider the quantity and magnitude of all the forcings that our planet has gone through during its billionial (can I say this word? My first language is not English, so pardon me) life.
Now, the IPCC wants us to spend hundreds of billions of dollars/euros and put back society a hundred years back in time so as to keep the sphere inside the bowl 2mm above its natural stable position.
Meanwhile millions of people are suffering in Haiti, Africa, Asia, but what the heck? Who cares/ As long as we save the planet from 2C warming.

Alex the skeptic says:
December 14, 2010 at 2:05 am
“If the earth’s climate had positive feedback due to anything, there would not be any life on earth, me thinks.”
There are both negative and positive feedbacks in the Earth’s climate. Note that even a net positive feedback does not necessarily imply that a system is unstable – it may simply amplify fluctuations by a finite but sustainable factor.Conversely, even with net negative feedback, a system can still be destroyed if you hit it hard enough or find a resonance (the ball will still jump out of the bowl if you jiggle the bowl sufficiently violently or at the right frequency).

Stefan

@Paul Birch: “for typical scenarios in which the average manner in which dirt is deposited is fairly consistent”
I don’t understand. What typical scenarios are you assuming where the dirt is deposited consistently? My kitchen has many local regions. By the door, a lot of dirt comes in from outside in big amounts at certain times of day. Meanwhile under the furniture, in quiet spots, dirt can accumulate very slowly over a long period of time. Some of it comes from the door so it also depends on how quickly the door area was cleaned up. If the door area was subjected to lots of dirt suddenly (muddy say) then it gets cleaned up immediately. If it is a dry day, then the dust can accumulate a bit and spread to the rest of the kitchen. So I don’t understand what you’re assuming? And I don’t understand what you’re assuming about the planet?

Steve Allen

Willis,
Very interesting article.
You said: “Meanwhile, in addition to losing latent heat through evaporation, the surface is further cooled by the fall of cold rain from the thunderstorm. This is accompanied by an entrained cold wind, which assists in the cooling.”
This localized cooling from the cold rain water dosen’t change the earth’s heat content, as the heat is just moved from one place within the biosphere to another (not radiated to space), right? Also, by simple observation, it appears “visually” to me that many of the control run models show no drift. True?

Alex the skeptic

Paul Birch says:
December 14, 2010 at 2:40 am
Alex the skeptic says:
December 14, 2010 at 2:05 am
“If the earth’s climate had positive feedback due to anything, there would not be any life on earth, me thinks.”
There are both negative and positive feedbacks in the Earth’s climate. Note that even a net positive feedback does not necessarily imply that a system is unstable – it may simply amplify fluctuations by a finite but sustainable factor.Conversely, even with net negative feedback, a system can still be destroyed if you hit it hard enough or find a resonance (the ball will still jump out of the bowl if you jiggle the bowl sufficiently violently or at the right frequency).
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
It was expected that someone would come up with the ‘kick hard enouhg to throw the sphere out of the bowl”, but as I said in my original comment:
“Consider the quantity and magnitude of all the forcings that our planet has gone through during its billionial life.” Fact is that our planet has never experienced such a kick during its geological histroy, not due to CO2 increases, solar forcings, not even the catastrophic direct hit that presumably killed the dinosaurs. The planet still managed to find its equilibrium following this global devastating event. The climate bowl must be very very deep, so deep that not even a celestial direct hit could manage to throw the ball out of the bowl.

I think it would be interesting to see Figure 2 presented as departures from some reference period. The entire time period, or the first 20 or 30 years.

wayne Job

Any extraneous gases in an unbounded heat pump using H2O as a refrigerant will make three fifths of five eighths of sweet FA of a difference to the null set of the thermostat. The only possible variation to the thermostat is the heat input, this is obviously varied by solar and cosmic influences beyond our control. Internal upsets such as extra heat from internal sources or particulate heat blocking from volcanic activity or industry and forest fires, are the only other variables. This is predicated on the hope various large rocks from the cosmos do not feel an urge to upset our peaceful existance, for they also tend to upset our thermostat. Those who believe we can control the thermostat by living in bark huts and caves are delusional.
90% of the time for the last odd million years our thermostat has been set on deep freeze, this setting is not particularly conducive to the life style we have come to enjoy.
It is not global warming that will cause us pain, it is cooling that will see suffering and death. I therefore ask those of scientific bent on this site to forget the nonsense of warming and investigate the reasons why in the past our thermostat was set to deep freeze for most of the time. Huge quantities of research and information are out there, they may have been distorted to prove a fallacy but they remain as information.

charles nelson

Brian thanks for the spelling tip…I did actually know that-honest.
And Socrates dear boy, we definitely need more practical engineers on here
I tire of voodoo physics.
I’ve got another one for you, shorter.
One evening after a great a dinner party I was confronted by a mellow wall of friends, all comfortably off and in senior positions who tut tutted my ardently skeptical position on the subject of climate change. (This is a few years back, obviously.)
And one of them took the lead with talk of uv spectra and infra red absorption, tropospheric warming, increased hurricanes, droughts, icecaps melting, feedback
loops….I let him go on a bit.
Eventually and in a good natured way he explained that he had looked at the science and had come down on the side of the warmists, he believed what they had to say. I chose to believe ‘other’ sources of information. I knew what he meant by other but I let it go. I waited a moment and then asked him.
‘Do you know how your fridge works?’
I saw a flicker in his eye, his composure was gone.
‘What’s that got to do with it?.’ He laughed and everyone formed a little protesting chorus behind him.
‘Come on surely somebody knows how a fridge works – that one in the corner, that kept this beer cold?’ One by one their glares were an admission of ignorance.
‘That’s below the belt.’ I heard someone mutter.
” So you would, discuss, spectra, parts per million, infra red, uncle tom cobbly and all with me? You would explain the workings of the planetary climate system with relaxed confidence but have no knowledge of the inner workings of a ubiquitous household object which uses gases and presures to keep things cool….
My missus gave me one of her looks. Something had changed in the atmosphere…and it wasn’t CO2 levels.

Willis Eschenbach

Paul Birch says:
December 14, 2010 at 2:01 am

As usual, Willis takes an initially reasonable analogy – and misuses it. His details are the devil. In this case, his “thought experiment” does not give the result he wants it to. One could indeed successfully model “the rate at which dirt is being added to the floor, based on the average amount of dirt on the floor”. I don’t “agree that in our thought experiment, the average dirt level of the floor is not linearly related to amount of dirt being added to the system”, because it is.

If we can add dirt and end up with more dirt, and we can also add the exact same amount of dirt and end up with less dirt, no, it’s not linear. If we can add three piles of dirt and end up with the same floor conditions as when we add one pile of dirt … no, it’s not linear.

Contrary to his claim that “average dirt levels and amount of dirt added show no correlation”, they will indeed be correlated, with the specific correlation dependent on the algorithm employed by the dust devils.

In a system with linear feedback, there is a one-to-one relationship between dirt added and dirt levels. But in a system with a governor, there is a many to one relationship between dirt added and dirt levels. We get the same result if we add three units of dirt and three TDDs clean it up, or if we add one unit of dirt and one TDD cleans it up.
Mathematically, this kind of system is termed to be not “invertible”. An average, for example, is not invertible. Knowing the algorithm, we can say that the average of three and five is four. However, if we know the average is four, we can’t determine what the two numbers were that made up the average. Could be six and two, or seven and one. This is the “many-to-one” relationship that we get in a system with a governor.
Which is why I said that we can’t calculate the rate at which dirt is added from the average amount of dirt on the floor.
And as you point out, to go the other way and predict floor conditions requires a knowledge of the dirt devils’ algorithm. But it requires something more than that. It requires that we know the distribution of the dirt that’s being added. But in a climate model, we don’t know that, because we are working both from and to gridcell averages. So even if we know the algorithm, it won’t help much if we don’t know the distribution, we can only get a crude picture.

The correlation is certainly not perfect, and the linear relationship is not the only relevant phenomenon, because, as he points out, the actual ratio depends on the local distribution of dirt; but, for typical scenarios in which the average manner in which dirt is deposited is fairly consistent, a kitchen-wide (“global”) linear model is likely to work pretty well, as a predictor of the overall dirtiness of the kitchen. I’d actually be quite surprised if the manufacturers of dust devils (which are now starting to appear on the market in reality) don’t use some such computer model.

Huh? That’s what I said in my head post.

Let me be clear about what I am saying about models. I’m not saying that we can’t model the climate. I think we can, although it won’t be easy. But we have to model it the way it really is.
It is not a system with a linear relationship between forcing and temperature as conventional theory claims. It is a dynamic governed system with a complex, nuanced, non-linear response to forcing. Yes, we can model that. But as I show above, we can’t do it under the assumptions made by the climate models.
Could we model it parametrically, without having to model individual thunderstorms? Probably … but the model has to be designed to do that.

Now, that’s what I said. So why are you acting like I said it couldn’t possibly be modeled? My point is that the current crop of models aren’t designed to model that kind of system. They’re designed to model a linear one-to-one system, not a governed system.

The reason that Willis’s thunderstorm thermostat doesn’t do what he thinks it should is that there are still underlying broadly linear (or at least monotonic) dependencies on temperature and insolation that the local feedback from his “governor” does not eliminate. For example, thunderstorms are driven by a temperature difference between surface and stratosphere, not the absolute temperature; and there is evidently a variable latitude, or range of latitudes, by which the tropical mechanism ceases to operate.

I’m afraid I’m not following you here. You speak of:

underlying broadly linear (or at least monotonic) dependencies on temperature and insolation that the local feedback from his “governor” does not eliminate.

That’s not clear. Seems like you’re saying that thunderstorm formation depends on other temperature and insolation factors. Your example is that “thunderstorms are driven by a temperature difference between surface and stratosphere, not the absolute temperature.” Well, kinda. You are correct that there are a host of factors that affect thunderstorm formation. And? Exactly which of my claims does that somehow negate?
As to your claim that there are places where a “tropical mechanism ceases to operate”, well, yeah, that’s called the extra-tropics. Again I’m not following your argument. How does that negate something I’ve said?

He’s had this pointed out to him several times before, but prefers to ignore it.

And you were doing so well, too, but then you decided to blow all your gains by getting nasty. So it goes. It’s useful to know, though. I find that kind of unwarranted anti-social behavior to be a pretty reliable gauge of a man’s inner belief in the strength of his arguments …
Now, you may be right, it might have been pointed out to me before. But if they did it the way you just did, by mumbling something unintelligible about the “broadly linear (or at least monotonic) dependencies” of something that you disdain to name “on temperature and insolation”, I didn’t “ignore it”. I simply didn’t understand it. What is it that you are referring to, that is dependent on insolation? Where did I say that the thunderstorm governing system was supposed to eliminate that mystery dependency? What are you on about?
Paul, here is a primer on how to tear my work to shreds.
1. Quote my exact words that you are disagreeing with, and cite where they came from. Most important. Quote what you think is wrong.
2. Explain as clearly as you can exactly which parts of that statement of mine you think are incorrect. Be as specific as you can be. Saying “it’s wrong” is meaningless. You need to say something more along the lines of “Your estimate of the value of X is three times the real value” or “Your claim of the evolutionary descent of monopoles from monotremes is highly improbable” or “You have made a mathematical error in the third step, E is actually equal to MC squared, not unequal”. That way, we both know exactly where you think I went off the rails.
3. Explain as clearly as you can exactly why you think what I said is incorrect. Again, be specific. Include citations and details. You want to say something along the lines of “Your estimate is high because you have neglected the first order vestigial discriminant factor” or “Higgbotham (1977) showed that monopoles have very different genetic makeup from monotremes”. Bring out the big guns, show precisely how my facts are wrong or my math sucks, post links to support for your ideas, then we’ll know exactly why you think my ideas are hokum …
If you do that, you’ll get some traction with your ideas and your claims. But just making vague assertions about some unknown dependencies that someone is supposed to have told me about sometime or other , and then leaving with an insult?
Not so much …

Chris Edwards

Why do the warmist lot get the high paying jobs and will it stop? I am a lowly engineer, just employed to fix practical things, in the real world, I have a memory and can read, this stopped me believing in AGW from the start I saw it was a scam. Also the “fix” sending all the wests money and jobs to China seemed ineffectual and unlikely to have any effect that was good so tell me why do the liars get the good wages?
This ming game was good but I went there many years ago, we need to become a powerful group, worldwide with a voice, the trouble is Im a lot busy right now coping with the green taxes to keep my family warm and fed, maybe thats the real plan.

R. Farr

It is a nonlinear chaotic system and thus can not be predicted. Your only hope is to work out the major bifurcation modes and prepare responses for those conditions based on their probability.
Then comes the once-in-a-century “perfect storm”….oh well.

Dr. John Ware

Excellent article; thanks, Willis!
An English point: The possessive of it is its. “It’s” means “It is” or “It has.” (One would never write hi’s meaning “belonging to him.”) No pronoun, regardless of case, has an apostrophe; the apostrophe, if present, means a contraction (i.e., two words expressed as one).

David Socrates says:
December 14, 2010 at 1:54 am
Willis Eschenbach, ably assisted by Charles Nelson (December 13, 2010 at 11:48 pm), have between them most entertainingly put this global warming conundrum to bed.
Sensible skeptics start from the twin observations that:
(1) Contrary to uninformed doom mongering over the past 30 years, at only 0.5degC or so per century the Earth’s temperature is steadfastly failing to rise in correspondence with the sharp (~30%) post-WW2 upturn in anthropogenic GHGs.
(2) The straightforward physics of CO2 indicates that an increase in its atmospheric concentration should have a significant and potentially worrying warming effect.
########
A. you’d have to net out negative forcings ( like volcanoes ) to get the isolated impact of GHGs
B. Time lag. The response to C02 addition is not instananeous. Its not like a blanket despite stupid metaphors to that effect

What if the nature of those “dirt devils” is electrical?, “a la Vukcevic”, and those pesky Solar storms, outside the “room” where those devils work, affect its behavior, as Piers Corbyn contends, and worse, if those are “She devils” then they are affected too by the Moon cycles, and every 28 days, they have an irritating character…. 🙂

Tony

The modified warmist position, best I can tell, is that increased warming leads to more unstable weather. This thought experiment seems to lead to the same conclusion. I don’t think the two claims are quite the same, but I’m not clear on the differences. Would someone care to help clear that up?

Gary

So it requires dropping the gridcell concept in order to liberate the models from their constraints. So simple, yet so difficult. The supercomputers ought to have enough horsepower to handle it now.

Willis Eschenbach says:
December 14, 2010 at 3:43 am
“If we can add dirt and end up with more dirt, and we can also add the exact same amount of dirt and end up with less dirt, no, it’s not linear. If we can add three piles of dirt and end up with the same floor conditions as when we add one pile of dirt … no, it’s not linear.”
Sorry, but this does not follow. If adding dirt in a particular distribution increases or decreases the overall amount of dirt in approximate proportion to the added amount – or even leaves it the same – that is a linear relationship.
“In a system with linear feedback, there is a one-to-one relationship between dirt added and dirt levels.”
No, this does not follow, because there can be other things (like noise) going on at the same time. A one-to-one relationship is not required for there to be a correlation. Quite the opposite. We use correlations to link varibables precisely when there isn’t a one-to one relationship.
“But in a system with a governor, there is a many to one relationship between dirt added and dirt levels.”
There may or may not be. It depends on the system. A simple AGC is a governor, with non-linear feedback, having an asymptotically limited output that is monotonic and in one-to-one-relationship with the input. A thermostat with hysteresis, on the other hand, does not have a one-to-one relationship of input and output; but in general there will still be a linear relationship between the average room temperature and the external temperature, the radiator temperature and the heating power. Contrary to popular belief, thermostats seldom if ever prevent room temperatures from varying with external conditions – they merely reduce the impact of such changes (in some cases with a change of sign).
“We get the same result if we add three units of dirt and three TDDs clean it up, or if we add one unit of dirt and one TDD cleans it up.”
Not in general. A similar result, very probably. But exactly the same? Almost certainly not.
“Mathematically, this kind of system is termed to be not “invertible”.”
This is nothing to do with the governor or feedback mechanism. It is a simple consequence of the fact that the single output is derived from multiple inputs; there is insufficient information to separate out the inputs, given only the output figure. However, this does not debar one from measuring the sensitivity of the output to each of those inputs in turn. And in a well-behaved physical system, those dependencies will be linear, for small changes about a norm.
“Which is why I said that we can’t calculate the rate at which dirt is added from the average amount of dirt on the floor.”
And you’re wrong. We can. It will only be an estimate, subject to various fluctuations and errors, but on average it will be correct (assuming that the deposition mechanism has not altered significantly since the observations upon which the model is based).
“And as you point out, to go the other way and predict floor conditions requires a knowledge of the dirt devils’ algorithm.”
No, it doesn’t. The details of the algorithm will indeed change the correlation, but it is not necessary to understand the algorithm in order to measure the correlation. An empirical relationship can be obtained and used as a predictor (in either direction), whether or not one understands the physical mechanism.
“Let me be clear about what I am saying about models. I’m not saying that we can’t model the climate. I think we can, although it won’t be easy. But we have to model it the way it really is.”
No, we really don’t. We can empirically or analytically model those parts of the system and those mathematical relationships that interest us, without bothering with all the complexities that we’re not interested in, or don’t know much about, or can’t predict.
“They’re designed to model a linear one-to-one system, not a governed system.”
They’re designed to model the linear dependencies that exist in any well-behaved system, including “governed” ones (whether with linear or non-linear feedback).
“Seems like you’re saying that thunderstorm formation depends on other temperature and insolation factors. Your example is that “thunderstorms are driven by a temperature difference between surface and stratosphere, not the absolute temperature.” Well, kinda. You are correct that there are a host of factors that affect thunderstorm formation. And? Exactly which of my claims does that somehow negate?”
A thermostat that measures or regulates the difference in temperature between two rooms cannot set the temperature for the whole house.
“As to your claim that there are places where a “tropical mechanism ceases to operate”, well, yeah, that’s called the extra-tropics. Again I’m not following your argument. How does that negate something I’ve said?”
Because a thermostat that regulates the temperature in a variable fraction of a room cannot regulate the temperature of the whole house. The latitude band over which the thunderstorm mechanism operates itself depends on external conditions (such as insolation, greenhouse warming, non-tropical albedo, etc.) in an essentially linear fashion (to first order or for reasonably small changes). So even if the thunderstorms were a perfect regulator (which of course they’re not), their effect on the global average would still be such a linear one, within the scope of a simple semi-empirical model.
“I find that kind of unwarranted anti-social behavior to be a pretty reliable gauge of a man’s inner belief in the strength of his arguments … ”
Yes, that’s why I’m afraid I have to consider you a cowardly poster – you seem to respond readily enough to the ignoramuses who don’t understand basic physics, but if ever someone comes up with a cogent criticism, then as soon as you realise you can’t answer it, you ignore them and pretend it wasn’t said. You have done this to me more than once. For example, I demonstrated conclusively on a previous thread why your claim that a one-shell greenhouse cannot produce enough warming was false; I supplied not one but three distinct mechanisms capable of generating unlimited warming. You ignored the comment completely. I have also seen you do the same to other commenters, who have shown you quite explicitly how your thermostat model breaks down. You didn’t ask them for clarification; you just ducked out of the discussion. If this was merely inadvertance on your part, then I apologise.

Stefan says:
December 14, 2010 at 3:10 am
@Paul Birch: for typical scenarios in which the average manner in which dirt is deposited is fairly consistent
“I don’t understand. What typical scenarios are you assuming where the dirt is deposited consistently? ”
On whatever timescale you’re interested in observing the average dirtiness of the kitchen, that’s the timescale on which the deposition mechanism has to be reasonably consistent (for a simple empirical model). The kitchen “climate” rather than its “weather”. It might be a day, or a week, or a year. Obviously, the more you know about the specifics of how the dust devils operate, and how dust accumulates in the kitchen, the better the handle you can get on the “weather” too.

Alex the skeptic says:
December 14, 2010 at 3:24 am
“… ‘kick hard enouhg to throw the sphere out of the bowl”, but as I said in my original comment:
“Consider the quantity and magnitude of all the forcings that our planet has gone through during its billionial life.” Fact is that our planet has never experienced such a kick during its geological histroy, not due to CO2 increases, solar forcings, not even the catastrophic direct hit that presumably killed the dinosaurs. ”
This is somewhat debatable, since mass extinctions arguably should count as “sphere out of bowl” (even if it subsequently found its way back in). However, my point was that this does not tell you whether or not you have net positive or negative feedback. The Earth could have survived with the former – or suffered catastrophe with the latter.