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Politics : New FADG. -- Ignore unavailable to you. Want to Upgrade?

To: neolib who wrote (1624)	6/11/2007 12:23:21 PM
From: Nadine Carroll	Read Replies (1) \| Respond to of 4152

There are two things a real model must do: 1) Produce outputs which fit known results when given known inputs, i.e. validation, and 2) the model equations must also match known science. #2 gets rid of a model which is simply a curve not based on science. You seem to be deliberately avoiding Freeman Dyson's point, which is that the current models produce outputs that match observed data NOT because of their underlying theory of greenhouse gases, but because their outputs have been made to fit with all kinds of "fudge factors" which are supposed to represent cloud formation, vegetation growth, snow melt, etc, etc. If you run the model without the fudge factors, the outputs do NOT match observed data. Will the fudge factors continue to match the data going forward? Who knows? You fail to understand which sciences were more advanced 100 years ago. Math, physics, and chemistry were doing significantly better 100 years ago than biology/medicine compared to current knowledge. No surprises there. What kind of a red herring is this? Whether any branch of science has advanced significantly in the last 100 years is besides the point. The point being, were the claims that were advanced by a large consensus of scientists, activists and politicians scientifically sound? Or were they found to be scientifically lacking? You must remember that scientists and activists will be most tempted to run ahead of the evidence in the case where the underlying science is incomplete - especially if they fear (whether genuinely or for some other reason) a disaster that must be acted upon to be avoided. One could very justly compare the state of social science a hundred years ago to the state of climatology today. In both cases, the scientists know they are on to something important. And in both cases, they have barely begun to get a handle on an insanely complicated subject - dynamic, chaotic, nonlinear and tightly coupled.