Our lives tend to run smoothly and predictably most of the time, but they are also prone to intermittent instability with devastating consequences. Can we do more to predict these periods and even intervene to prevent them? A BBC article discusses it.
Getting stuck in a rut
For many of us, life seems to progress smoothly and predictably for much of the time. Indeed, it seems one of our biggest concerns appears to be getting stuck in a rut. But then, seemingly out of nowhere, our world is turned upside down. A global pandemic strikes us down, killing millions of people and forcing entire countries into lockdown. Then inflation takes off and economic downturn threatens our livelihoods. Where on Earth did all that come from?
There’s a generic reason for these sudden unforeseen catastrophes. It’s something commonly found in many “nonlinear systems” in the physical, biological and social sciences: intermittent instability. That is to say, after long periods of boring and predictable behaviour, these systems suddenly become wildly unpredictable, exhibiting extreme fluctuations.
A nonlinear system
What is a nonlinear system? It’s one whose outputs are not in direct proportion to inputs. We humans are nonlinear systems: if we win $1m (or £1m if you prefer) in the lottery, we will likely be very happy indeed. But if we were to win $4m/£4m, we would likely not be four times as happy. Put more viscerally, if doubling our wealth in the lottery would make us happy, losing our wealth through some stupid gamble would not just make us sad, it would devastate us.
Nonlinearity is a key ingredient behind the phenomenon of chaos – the process underpinning the famous butterfly effect – how a small uncertainty can grow and make the whole system unpredictable. However, in chaotic systems, the butterfly effect is not fully at play all the time. Sometimes a chaotic system can be predictable for quite a long period into the future. On other occasions, near an intermittent instability, the flap of a butterfly’s wings can destroy predictability over a very short period of time. It’s all a consequence of nonlinearity.
The weather is a nonlinear chaotic system. It’s rather boring and predictable for most of the time but occasionally becomes wildly unpredictable and extreme. In October 1987, BBC weather forecaster Michael Fish told viewers not to worry about strong winds that turned out to be the worst storm southern England had experienced in 300 years, just the day before it happened. Meteorologists learned from this experience.
It was realised that the evolution of what has become known in some circles as the “Fish storm” was exceptionally sensitive to the butterfly effect – much more so than normal. And so, nowadays, when trying to predict the weather, forecast centres run ensembles of 50 simulations, each differing slightly in their initial conditions (by flaps of meteorological butterfly wings).
Unstable atmosphere!
When the atmosphere is very unstable, as it was in October 1987, then the assorted forecasts within the ensemble will differ dramatically from one another: some will show hurricane-strength extreme weather, others will show much more benign weather. All a forecaster can do in such a situation is estimate some probability, or likelihood, that the extreme event will occur.
But forecasting a significant probability for an extreme event is much better than forecasting nothing significant, as happened in 1987. And ensemble weather prediction is today revolutionising the way humanitarian and disaster relief agencies send emergency food, shelter, medicine and even finance to regions at risk of extreme weather. Such anticipatory action is taken when the ensemble-based probabilities for extreme weather exceed a pre-determined threshold.
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Source: BBC
