Predicting the impact of climate change requires studying changes in the long-term averages of daily weather patterns and many other factors, and can be a tricky business.
Scientists use climate models that simulate the possible impact of variables like radiation, moisture content, and the movement of air and temperature over a given period of time to help project what could happen.
To make forecasting the possible impact of climate change as comprehensive as possible, and make the connection between current events and future consequences clearer, scientists and academics have been expanding the list of variables such as sea level rise and even food price increases and malnutrition statistics.
"The lesson is to understand what models do," said Peter Walker, director of the FeinsteinInternational Centre at Tufts University in the US. "They show you a very simplified picture of what may happen under very tightly proscribed conditions. They do not predict the future!"
|They [models] show you a very simplified picture of what may happen under very tightly proscribed conditions|
Models show "what will happen if the variables looked at behave as expected - i.e., all other things being equal, and our predictions over the changes in variables being right - this is what will happen," he explained.
"Where models fall down is if the accrual variables affecting the future turn out to be ones they [scientists] have not mapped. So, what if conflict triggered by climate changes turns out to be a big issue [in future]? What if the relationships between the variables change as a different future evolves?" Walker commented.
"So, for instance, models that 30 years ago were used to predict savings rates in the US are now useless because the relationship between what people earn, what they want to buy, and what they saved has been radically changed by the introduction of credit cards. Pre-credit card models don't work," he pointed out.
"Finally, it is an irritating reality that much change in history has not been driven by the predictable events, but by the unpredicted - the big, unexpected events. This is referred to as the 'Black Swan Theory'."
The theory was described by Nassim Nicholas Taleb, an epistemologist in his 2007 book, The Black Swan, where he referred to it as the Black Swan Events.
Swans were assumed to be always white, until the discovery of black swans in Australia. "By definition we do not know what black swans will come along to render our predictive models useless," he said, nevertheless, modelling was still a "good tool for demonstrating that there is no business as usual!"
Walker recently used various models to project the likely rise in humanitarian spending over the next 20 years as the frequency and intensity of natural disasters increased.