Climate change uncertainty is no reason for inaction since we can't rule out risk

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Courtesy of guardian.co.uk

Climate change is sometimes presented in simple black and white terms. You either believe it or you don't. Perhaps after the recent controversies over email leaks and melting Himalayan glaciers, some may have decided to change camp.

But this is a false dichotomy. Indeed the notion of "belief" plays no role at all in science, whether about climate change or anything else. The Royal Society, the UK's national academy of science, was founded 350 years ago on this very basis, with the motto Nullius in verba, or "take nobody's word for it". The founders took nothing for granted and chose to investigate observations and search for the conclusions that best fit them. The notion that these conclusions can never be considered certain and immutable, underpinned both their actions and those that came after them. As James Gleick wrote about the great 20th century theoretical physicist Richard Feynman; he believed in the primacy of doubt, not as a blemish on our ability to know, but as the essence of knowing.

Modern day weather prediction is inherently uncertain. Every day, weather forecast centres will generate an ensemble, typically of 50 individual weather predictions, in order to assess uncertainty in the weather up to a week or more ahead. The individual predictions have very slightly different starting conditions, reflecting the fact that the weather observations which generate a forecast's initial state are neither complete nor wholly accurate. When the atmosphere is in a predictable state, all 50 predictions are more or less identical for the coming week and the forecaster can say with great confidence what the weather will be like. On the other hand, when the atmosphere is in a chaotic state, the best the forecaster can talk about are probabilities of different outcomes.

Some, perhaps those without scientific training, may see probabilistic predictions as an evasion of responsibility. However, in reality, probabilistic predictions embody the scientific method. In any case, what is better for decision making, a forecast with some realistic measure of uncertainty, or some grossly overconfident prediction with no hint of uncertainty?

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email leak, global warming, weather forecasting