Predicting natural events
Box 1 | Defining thresholds
Scientists predict weather and climate using mathematical models. The underlying processes – involving sunshine, winds, heat, moisture, clouds, ocean currents and vegetation on land – are described by mathematical equations and solved on a computer. One of the difficulties faced by scientists who predict weather and climate in this way is that many aspects of the weather, such as rainfall, are not smooth but behave in an erratic or 'spiky' fashion. The yearly average of rain may occur in one or two heavy falls, with very little rain between major downpours. Such erratic events are difficult to predict.
Thresholds and pattern dynamics focuses on what happens at the upper and lower limits representing rare events. With enough data and understanding, patterns emerge, the threshold can be identified and predictions of the likelihood and behaviour of extreme events can be made.
Resilience is another feature of systems that have thresholds. Resilience is the amount of disturbance that a system – such as climate – can tolerate before it crosses the threshold and moves to a different state. Analysis of systems that have thresholds, and are well understood, shows that the rate of progress towards the tipping point may be gradual or rapid. Once the threshold or boundary has been met, the change from one state to the next may be quite sudden.
Thresholds can be altered or influenced by human activities. They are often created when humans introduce a problem to an otherwise stable system by trying to control it or utilise the resource, such as water. Some thresholds are reversible, so a system will return to the same state it was in before crossing the threshold after a recovery period. Examples of reversible thresholds are lake eutrophication, overgrazing of vegetation and predator regulation of prey. Other thresholds, such as dryland salinity and extreme coral bleaching, are difficult or impossible to reverse. The reversal may involve 'hysteresis', in which a system that has crossed a threshold must be reversed a long way beyond the threshold point before it flips back to its original, pre-threshold state. An example is lake eutrophication caused by excessive nutrient input which generate massive algal blooms. The nutrients often take the form of nitrogen and phosphorus in runoff from farmland or urban areas. A lake may turn eutrophic when the nutrient level exceeds some threshold, but will only revert to its original non-eutrophic state when the nutrient input is reduced to a very much lower level. This illustrates the importance of having good predictive tools to minimise the possibility of causing an irreversible negative change to the environment.
Posted September 2005.