Guest Post by Willis Eschenbach
David Rose has posted this , from the unreleased IPCC Fifth Assessment Report (AR5):
‘ECS is likely in the range 1.5C to 4.5C… The lower limit of the assessed likely range is thus less than the 2C in the [2007 report], reflecting the evidence from new studies.’ SOURCE
I cracked up when I read that … despite the IPCC’s claim of even greater certainty, it’s a step backwards.
You see, back around 1980, about 33 years ago, we got the first estimate from the computer models of the “equilibrium climate sensitivity” (ECS). This is the estimate of how much the world will warm if CO2 doubles. At that time, the range was said to be from 1.5° to 4.5°.
However, that was reduced in the Fourth Assessment Report, to a narrower, presumably more accurate range of from 2°C to 4.5°C. Now, however, they’ve backed away from that, and retreated to their previous estimate.
Now consider: the first estimate was done in 1980, using a simple computer and a simple model. Since then, there has been a huge, almost unimaginable increase in computer power. There has been a correspondingly huge increase in computer speed. The number of gridcells in the models has gone up by a couple orders of magnitude. Separate ocean and atmosphere models have been combined into one to reduce errors. And the size of the models has gone from a few thousand lines of code to millions of lines of code.
And the estimates of climate sensitivity have not gotten even the slightest bit more accurate.
Can anyone name any other scientific field that has made so little progress in the last third of a century? Anyone? Because I can’t.
So … what is the most plausible explanation for this ludicrous, abysmal failure to improve a simple estimate in a third of a century?
I can give you my answer. The models are on the wrong path. And when you’re on the wrong path, it doesn’t matter how big you are or how complex you are or how fast you are—you won’t get the right answer.
And what is the wrong path?
The wrong path is the ludicrous idea that the change in global temperature is a simple function of the change in the “forcings”, which is climatespeak for the amount of downward radiation at the top of the atmosphere. The canonical (incorrect) equation is:
∆T = lambda ∆F
where T is temperature, F is forcing, lambda is the climate sensitivity, and ∆ means “the change in”.
I have shown, in a variety of posts, that the temperature of the earth is not a function of the change in forcings. Instead, the climate is a governed system. As an example of another governed system, consider a car. In general, other things being equal, we can say that the change in speed of a car is a linear function of the change in the amount of gas. Mathematically, this would be:
∆S = lambda ∆G
where S is speed, G is gas, and lambda is the coefficient relating the two.
But suppose we turn on the governor, which in a car is called the cruise control. At that point, the relationship between speed and gas consumption disappears entirely—gas consumption goes up and down, but the speed basically doesn’t change.
Note that this is NOT a feedback, which would just change the coefficient “lambda” giving the linear relationship between the change in speed ∆S and the change in gas ∆G. The addition of a governor completely wipes out that linear relationship, de-coupling the changes in gas consumption from the speed changes entirely.
The exact same thing is going on with the climate. It is governed by a variety of emergent climate phenomena such as thunderstorms, the El Nino/La Nina warm water pump, and the PDO. And as a result, the change in global temperature is totally decoupled from the changes in forcings. This is why it is so hard to find traces of e.g. solar and volcano forcings in the temperature record. We know that both of those change the forcings … but the temperatures do not change correspondingly.
To me, that’s the Occam’s Razor explanation of why, after thirty years, millions of dollars, millions of man-hours, and millions of lines of code, the computer models have not improved the estimation of “climate sensitivity” in the slightest. They do not contain or model any of the emergent phenomena that govern the climate, the phenomena that decouple the temperature from the forcing and render the entire idea of “climate sensitivity” meaningless.
PS—I have also shown that despite their huge complexity, the global temperature output of the models can be emulated to a 98% accuracy by a simple one-line equation. This means that their estimate of the “climate sensitivity” is entirely a function of their choice of forcings … meaning, of course, that even on a good day with a following wind they can tell us nothing about the climate sensitivity.