It should not need to be said that a model is not evidence of anything. A model is a hypothesis. Like any scientific hypothesis, it is confirmed or refuted by observation. A model that is refuted by observation is worthless. And yet, these models, which have repeatedly been shown to be wrong, are the basis for enormously destructive policies that have been adopted across much of the western world.It is, because pushing frightening things, whether it's body odor, a lack of sex appeal, or The End of The World As We Know It, pays off, until it doesn't. Perhaps after fifty to sixty years of this sort of doomsaying, while the Worst Case Scenarios of a quarter century ago have not transpired, enough of us have accumulated sufficient evidence to undermine the doomsayers with mockery.
Someone pointed out with respect to these data–I would credit him, but I can’t now find the reference–that if it were simply a matter of mathematical errors or inconsistencies, one would expect some models to err on the “hot side” and others on the “cold side” of actual observations. But that isn’t the case: all of the models run hot. That suggest that global warming alarmism is a political, not a scientific, movement.
31.1.24
SHOULDN'T FORECAST ERRORS BE POSITIVE OR NEGATIVE?
Extrapolation models built to push policies, whether with respect to climate or to contagion, are useless. How much more evidence must John Hinderaker offer before advocates of extrapolation models shut up?
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2 comments:
Reminds me of when we talked about modeling in Econometrics Class. Less complex models are usually inaccurate because they don’t capture the complexity of the Economy but as you attempt to build a more complex model it’s also likely to be not very accurate because there are some many variables that no one can properly weight them all properly. It’s a a Fool’s errand.
With statistical inference, there's always a degrees of freedom problem, and even the best programs run into conditioning and rounding problems as the number of parameters to be estimated increases.
By definition, you cannot capture all the details of a complex system with a small set of equations. You can, however, capture the essential elements.
Those extrapolation models the climate and epidemic types use face a different problem, there isn't enough computing power to simulate the behavior of small parcels (of atmosphere or the population) and about the best you can do with the long term forecasts is suggest there will be a tornado somewhere in Iowa in May.
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