Science & Technology
Statistics and climatology
Aug 16th 2007
From The Economist print edition
Modelling the Earth's climate mathematically is hard already. Now a new difficulty is emerging
“SCIENCE” is a recently coined word. When the Royal Society, the world's oldest academy of the discipline, was founded in London in 1660, the subject was referred to as natural philosophy. In the 19th century, though, nature and philosophy went their separate ways as the natural philosophers grew in number, power and influence.
Nevertheless, the link between the fields lingers on in the name of one of the Royal Society's journals, Philosophical Transactions. And appropriately, the latest edition of that publication, which is devoted to the science of climate modelling, is in part a discussion of the understanding and misunderstanding of the ideas of one particular 18th-century English philosopher, Thomas Bayes.
Pascal's way of looking at the world was that of the gambler: each throw of the dice is independent of the previous one. Bayes's allows for the accumulation of experience, and its incorporation into a statistical model in the form of prior assumptions that can vary with circumstances. A good prior assumption about tomorrow's weather, for example, is that it will be similar to today's. Assumptions about the weather the day after tomorrow, though, will be modified by what actually happens tomorrow.
Psychologically, people tend to be Bayesian—to the extent of often making false connections. And that risk of false connection is why scientists like Pascal's version of the world. It appears to be objective. But when models are built, it is almost impossible to avoid including Bayesian-style prior assumptions in them. By failing to acknowledge that, model builders risk making serious mistakes.
In one sense it is obvious that assumptions will affect outcomes—another reason Bayes is not properly acknowledged. That obviousness, though, buries deeper subtleties. In one of the papers in Philosophical Transactions David Stainforth of Oxford University points out a pertinent example.