Taking climate change by storm – what does the butterfly effect, actually affect?
Chaos theory is the idea that small changes in initial conditions result in vast differences in the final outcome. For instance, a butterfly flapping its wings could result in a hurricane forming several weeks later. Weather can be considered to be ‘chaotic’ as small fluctuations in atmospheric conditions can build up into large weather effects over time. This makes it impossible to predict more than a few weeks in advance, and for weather forecasting to be unreliable.
So how is it that climate change, which is essentially how average weather changes over time, can be predicted 50 years or so into the future when weather can barely be predicted 5 weeks? If they are so closely linked, how is our ability to predict each so radically different?
Although weather is chaotic, climate is not. In the same sense that although we are unable to predict the age at which a specific man will die, we can make reasonably accurate predictions as to the average age at which 100 or so men will die, and how this will change over time if we look at statistics on eating habits and changes in public health. We can measure many of the factors that affect climate change, most significantly the atmospheric conditions, and how these are likely to change over time, and are therefore able to make predictions into the future.
Yet chaos still does not mean randomness. Seemingly chaotic systems can show recurring patterns emerging, a famous one being the golden ratio. In flower petals, pine cones, shells, hurricanes and even spiral galaxies, these seemingly random formations show this Fibonacci sequence. Even at a microscopic level, the DNA molecule measures 34 angstroms long by 21 angstroms wide for each full cycle of the double helix spiral. These two numbers are in the Fibonacci sequence, with their ratio closely approximating Phi (the golden ratio).