The Future of Climate Projections

Freya Roberts

Projecting future climates is an inexact science. But changes to the way scientists make their predictions could put us on a path to greater certainty.

Predicting future climate

The Intergovernmental Panel on Climate Change is the most comprehensive assessment of the science of climate change in existance. Its job is consider the field of climate change science, synthesise conclusions about how the climate is behaving from the scientific literature, and then try and determine what the effects will be on our planet. Finally, the IPCC process tries to assess what the impacts of these changes will be, and suggests how we can adapt to them.

It’s a big, all-encompassing project to try and ‘sum-up’ climate change, but the process can be broken down into some fundamental bits:

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The current approach for projecting climate change. Source: Moss et al., 2010

As a first step, scientists work out what human factors are driving emissions, and how they are likely to change in the future. With this information, they can estimate how emissions might increase.

This is the idea behind ’emissions scenarios’, but the challenge is that elements of uncertainty at this early stage can have a knock-on effect on the accuracy of the overall projections.

Making emissions scenarios

An emissions scenario is designed to give plausible broad-brush picture of what greenhouse gas emissions might do in the future. To form them, scientists make assumptions about the main factors driving emissions – things like changes in population, advances in technology, and social and economic development. They make informed guesses about how these drivers will change over time, and by mapping all these changes together, they calculate total emissions at a stage in the future.

But human behaviour is the main thing which will affect future emissions – and since it’s uncertain how humans will act in the future, it’s very difficult to know how emissions will change.

So the IPCC produce a number of scenarios , varying the assumed changes slightly in each, to give a number of plausible future outcomes. None of these scenarios is expected to be ‘the one’ – the aim is to demonstrate a range.

But there are problems with doing it like this

This way of projecting climate change is useful, but limited by a number of factors.

One of the biggest limitations lies at the heart of projecting future emissions. For example, one tool the IPCC use is a pretty simple equation called the ‘Kaya Identity’, which goes like this:

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The Kaya Identity , one of the framing tools used by the IPCC see page 105 of SRES )

This equation can be widely and easily applied, but it assumes each driver has a similar effect on greenhouse gas emissions, when in practice, some things make more of a difference than others.

Population is one example. A new review in Nature Climate Change demonstrates this well: for a long time researchers have proposed that a growing population brings greater environmental stress (aka more emissions). The idea holds that emissions rise in tandem with population.

But actually, that doesn’t appear to be the case. The emissions of a growing population increase at a faster rate than the number of people, according to anempirical study. It sampled a number of countries over the period of 1960 – 2005 and found that at national level, an increase in population size of 10% made greenhouse gas emissions rise by between 12.7% and 18.6%

The practical upshot of this finding is that simple equations like the Kaya Identity probably underestimate the effect of population growth on emissions, and such errors are then passed on into the calculated emissions totals, and the projected climate impacts that are based on them.

The whole process is also very slow – from start to finish it takes about 10 years to create scenarios and map them through to impacts studies. And the uncertainty increases with each step.

Doing something new

These issues are probably why, in advance of its Fifth Assessment Report (AR5), the IPCC has been reevaluating the way it projects future emissions.

Instead of starting with a socio-economic story about the future and calculating the amount of greenhouse emissions it gives rise to, it will start by specifying some likely concentrations of greenhouse gases in the atmosphere over the near future, and then working out how the climate will respond. By taking humans out of equation, the idea goes, the uncertainties of working out physical changes to the climate system will be reduced.

These emissions concentration levels will be called ‘representative concentration pathways’ (RCPs), and they can be used to look forwards, using earth-system models to work out what physical changes in the climate system may result from these greenhouse gas concentrations, and also to look backwards: using socio-economic models to see how our actions might lead to certain concentrations of greenhouse gases.

Essentially, rather than making assumptions about how driving forces will change, the new process will make assumptions about how greenhouse gas concentrations will change. The greenhouse gases will now be the starting point, rather than a middle stage. In theory this will make climate projections more reliable and more useful for policy makers when they are trying to decide the best measures for adaptation.

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