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 any room dirt collects, as you might imagine. In my household I’m somewhat responsible for keeping the dirt down, so I get out the 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 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 in order 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 are 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 the 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 appears. The 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, even as to sign.
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. Many times they involve a change of state of a variable (e.g. condensation of water vapor). Often they can move about somewhat independently. If so, although they have general tendencies, their specific movements 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 behavior 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 that 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 contains 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, 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. In our thought experiment, 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 that 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 modeling 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? Perhaps … 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 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 at 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 modeling the climate correctly …
As always, the quest for understanding continues. My best regards to all,
w.
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@ur momisugly Grumpy
The Latin plural of vortex is vortices, but illis writes in English, so “vortexes” is good.
@ur momisugly 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.
charles n.;
Not tea bags!
But it’s “reservoir”, not “resevoir”. And yes, that 2nd ‘r’ IS pronounced.
So here’s what “settled” means: “we stopped thinking”.
Robbo;
unfortunately, you’re correct. Either is acceptable. But “mouses” is NOT! >:(
About the bounds and feedbacks:
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.
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).
@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?
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?
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.
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.
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.
Paul Birch says:
December 14, 2010 at 2:01 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.
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.
Huh? That’s what I said in my head post.
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.
I’m afraid I’m not following you here. You speak of:
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?
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 …
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.
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.
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…. 🙂
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?
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.