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Document Page 69 The objective of the most basic physics is a complete description of what happens. In principle and apparently in practice, quantum mechanics gives a complete account of what goes on inside, say, a hydrogen atom. But most things we want to analyze, even in physical science, cannot be dealt with at that level of completeness. The only exact model of the global weather system is that system itself. Any smaller-scale model of that system is therefore to some degree a falsification: it leaves out many aspects of reality. How, then, does the meteorological researcher decide what to put into his model? And how does he decide whether his model is a good one? The answer to the first question is that the choice of model represents a mixture of judgment and compromise. The model must be something you know how to make that is, you are constrained by your modeling techniques. And the model must be something you can construct given your resources time, money, and patience are not unlimited. There may be a wide variety of models possible given those constraints; which one or ones you choose actually to build depends on educated guessing. And how do you know that the model is good? It will never be right in the way that quantum electrodynamics is right. At a certain point you may be good enough at predicting that your results can be put to repeated practical use, like the giant weather-forecasting models that run on today's supercomputers; in that case predictive success can be measured in terms of dollars and cents, and the improvement of models becomes a quantifiable matter. In the early stages of a complex science, however, the criterion for a good model is more subjective: it is a good model if it file:///D|/Export2/www.netlibrary.com/nlreader/nlreader.dll@bookid=409&filename=page_69.html [4/18/2007 10:30:29 AM]
Document succeeds in explaining or rationalizing some of what you see in the world in a way that you might not have expected. Notice that I have not specified exactly what I mean by a model. You may think that I must mean a mathematical model, perhaps a computer simulation. And indeed that's mostly what we have to work with in economics. But a model can equally well be a physical one, and I'd like to describe briefly an example from the pre-computer era of meteorological research: Fultz's dishpan. 1 Page 70 Dave Fultz was a researcher at the University of Chicago in the early postwar years, who sought an answer to what might seem a very hard question: what factors are essential to generating the intricacy and variability of world weather? Is it a process that depends on the full complexity of the world the interaction of ocean currents and the atmosphere, the location of mountain ranges, the alternation of the seasons, and so on or does the basic pattern of weather, for all its complexity, have simple roots? He was able to show the essential simplicity of the weather's causes with a "model" that consisted of a dishpan filled with water, placed on a slowly rotating turntable, with an electric heating element bent around the outside of the pan. Aluminum flakes and dye were suspended in the water, so that a camera perched overhead and rotating with the pan could take pictures of the pattern of flow. The setup was designed to reproduce two features of the global weather system: the temperature differential between the poles and the equator, and the Coriolis force that results from the earth's spin. Everything else all the rich detail of the actual planet was suppressed. And yet the dishpan exhibited steady flows near the rim that clearly corresponded to the tropical trade winds, great eddies that file:///D|/Export2/www.netlibrary.com/nlreader/nlreader.dll@bookid=409&filename=page_70.html [4/18/2007 10:30:29 AM]
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