When a system is well understood, a well-constructed mathematical model of that system can make realistic predictions based on the data sets fed into it. However, when a system is not well-understood, but one insists on making a mathematical of it, anyway, the holes in the database and the gaps in our knowledge must, necessarily, be filled with assumptions and estimates, instead of established principles and actual data.
The poorer our understanding of the system, the greater the impact of those simplifying assumptions and arbitrary estimates on the modeled results.
Today, realistic predictions from current climate models are simply not an option for two very simple reasons. First of all, Earth’s climate is a mind-bogglingly complex, chaotic, natural system, the governing principles of which we have only a rudimentary understanding. Secondly, because only a small fraction of the Earth’s surface (considerably less than 25%) is covered by weather stations, there are nowhere near enough actual data points to feed into a GCM to compute any realistic predictions.
Unfortunately, whenever we insist on reducing a poorly understood system to a set of mathematical equations, we invariably fool ourselves (and others) into thinking that we understand that system much better than we actually do. And, when those equations are programmed into a computer, we (and others) are even more impressed with the results, even though such models reflect our ignorance more than anything else.
One of my favorite old jokes describes the difference between a neurotic, a psychotic, and a psychiatrist as follows::a neurotic builds castles in the sky; a psychotic lives in them; and a psychiatrist collects the rent. Whenever I think of this joke, I cannot help but think of mathematical models in general and general climate models (GCMs) in particular.
In this analogy, the flawed climate models are the “castles in the sky”; the climate modelers are the “psychiatrists”; and the true believers in the lay public are either the “neurotics” or the “psychotics”, depending on how high is their tolerance for implausible nonsense.
The GCMs used by the United Nation’s International Panel on Climate Change (IPCC) are even worse than they have to be for the simple reason that they are not even designed to explore how the Earth’s natural climate system actually works. Rather, they are designed to (1) largely ignore all natural determinants of climate change, (2) assume that atmospheric CO2, rather than the Sun, is the primary forcer of Earth’s climate, and (3) generate “scenarios” of climate change based on those programmed omissions and assumptions.
In other words, the IPCC’s GCMs are being used not as instruments of scientific investigation but as tools of political propaganda.
Not surprisingly, then, virtually all of the predictions made by the IPCC’s GCMs have so far proven to be completely false. The only thing that is surprising is that so many people’s faith in these models apparently remains unshaken.
On Mathematical Models
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