Freeman Dyson is not saying that the "fudge factors" were chosen as a linear approximation around an operating point, based on scientific conclusions regarding their value. He is plainly saying that they were chosen as a linear approximations that makes the models fit the observed data.
Either the values are based on some good understanding of what is to be modeled, or they are not. If they are not, then they amount to a curve-fit, even if the method being used is more sophisticated than a crude fitting of points on the curve. As Dyson says.
The good news is that we are at last putting serious effort and money into local observations. Local observations are laborious and slow, but they are essential if we are ever to have an accurate picture of climate. The bad news is that the climate models on which so much effort is expended are unreliable because they still use fudge-factors rather than physics to represent important things like evaporation and convection, clouds and rainfall. Besides the general prevalence of fudge-factors, the latest and biggest climate models have other defects that make them unreliable. With one exception, they do not predict the existence of El Niño. Since El Niño is a major feature of the observed climate, any model that fails to predict it is clearly deficient. The bad news does not mean that climate models are worthless. They are, as Manabe said thirty years ago, essential tools for understanding climate. They are not yet adequate tools for predicting climate.[14]
en.wikipedia.org
BTW, I think you have an extraordinary nerve to call Freeman Dyson a "prattler" who doesn't understand models. |
