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Understanding the potential impacts of climate change is dependent on how ambitious our climate policy will be in future. However, climate and energy models do not adequately address the question of how society will respond to climate change.
Although the connections between technology, society and climate change are complicated, they are not impossible. In a paper published in Nature, my co-authors and I identify the factors that influence climate policy – from an individual to the global scale – and use them to simulate future emissions.
Some of the most important factors include the public’s perception of climate change through their experience of weather; the future cost and effectiveness of mitigation technologies; and the responsiveness of political institutions.
Our overall finding that the world is likely to experience warming of between 2-3C by 2100 is strikingly similar to studies that project emissions based on countries’ pledges to the Paris Agreement.
These all suggest that, although society has moved away form high-emissions pathways where global warming of 4-5C may be possible, the Paris Agreement goals remain largely unattainable on our current trajectory.
Complex society
To understand the long-term impacts of climate change, it is important to know how ambitious and effective a climate policy will be. This is because global temperature will be determined by the evolution of greenhouse gases emissions. The range of warming in 2100 across different emission pathways is greater than variation due to uncertainty in the climate system and natural variability.
However, almost all ClimateAnd energy-system models fail to represent the complex reality of human behaviour and social systems, even though they are a key driver of Earth’s future climate.
Global climate models simulate climate under different emissions futures, while energy systems models optimise the technology mix for a particular condition, such as limiting global temperatures to 2C. Climate models cannot predict the outcomes of different emission pathways and can only show alternate stories about economic growth, population growth, and climate policy.
For example, just as there is the potential for “Tipping points” in the climate system, similar tipping point-style behaviour can In the energy or social systems, emerge – for example, by the desire to conform to social norms or by learning-by-doing feedbacks that accelerate installation of new energy technologies. Policy changes can also be used to either support or resist further changes.
It is not possible to include complex behaviours in climate models for two main reasons. First, as a scientific question, leaving one of the single most important drivers of the climate system – namely future climate policy – unexamined and unmodelled is somewhat unsatisfying.
Second, it is difficult for adaptation planners to present climate impacts under different emissions pathways without a formal assessment of their relative probabilities. They know the probabilities for different impacts.
Modelling social systems
The pace of decarbonisation required to meet the 1.5C and 2C temperature targets under the Paris Agreement is far greater than any other historical record at the global level.
On the other side, there are specific cases of energy systems changing rapidly, such as the Rapid fall in coal generation in UK electricity mixNorway’s electric vehicle sales are dominated by Norway.
We can also draw on the social and politically-oriented sciences to understand the likelihood and evolution for the kinds of changes that are required to combat climate change.
My co-authors, and I, present a model in our paper that includes fundamental social, political, and technical processes as factors that directly drive climate policies and emissions pathways.
The figure below shows the six major components and the scales of each process.
The emissions component (orange icon) models the reduction in emissions compared to a no-policy baseline scenario (“RCP7.0”). The climate component (red Icon) converts global greenhouse gas emission into a change of global average temperature using a simple carbon cycle model with three boxes (atmosphere (upper ocean and lower ocean)) and a two-box temperature model with (atmosphere (and ocean).
The model tracks public opinion shifts on climate policy (blue icons) and pro-climate behaviour fractions (purple icons). Public opinion can be affected by people’s direct perception of climate change through their experience of weather (cognition component, yellow icon). The policy component is used to filter public opinion (for example, a carbon subsidy or tax; green icon).
Eight key feedback mechanisms are identified that link the various components of the model. These processes were drawn from a variety of literature including psychology, law, and engineering. Emissions can have an impact on the climate, which in turn can affect the weather people experience. This could affect their perception of climate change evidence and, consequently, their support for climate policies. We allow for feedbacks from climate system to public opinion via the cognition component.
Emissions drivers
The model simulates 100,000 possible future policies and emissions trajectories. The vast majority of these models produce global temperatures in 2100 which are lower than the 3.9C. pre-industrial levelsreached in the business as usual case, without any climate policies
The most important factors in determining emissions pathways, and therefore warming over the 21st Century, are public perception of climate change, and their experience with weather; future cost and effectiveness mitigation technologies; and the responsiveness to political institutions.
More than 90% of our simulations result in warming of between 1.8C & 3.0C by 20100. Our most common cluster of results, which we term the “Modal Pathway”, contains 48% of runs and produces warming of 2.3C by 2100.
These emissions are strikingly similar to those in the previous pathway. Previous work that estimated the impact of countries’ pledges under the Paris Agreement for emissions in 2030 and 2050. This is especially notable because we don’t use data from these commitments when designing or calibrating our model.
Our overall finding that there is a high chance of warming between 2-3C and pre-industrial temperatures by 2100 matches the findings of a NumberOf RecentPapers that employ different approaches.
These numbers collectively suggest that the world has moved decisively away form a business as usual emissions path. It is increasingly unlikely that we will see a warming trend of between 4-5C and 2100, but that the Paris Agreement temperature targets are still largely unattainable given our current trajectory.
Moving forward
Our paper demonstrates the possibility of integrating political and social theories with climate and energy systems modeling to better understand climate futures.
However, there are important caveats to our findings. First, we only use one climate model and do not account for uncertainty in climate systems. Uncertainty is Climate SensitivityAnd Carbon-cycle feedbacksCould increase uncertainty in 2100 warming both at the high-end and low-ends of our projected range.
The second caveat is the fact that our model doesn’t include the possibility of Negative emissions techniquesTo extract CO2 from the atmosphere and to bury it under ground or in the sea for the long-term. This means that emissions and temperatures could be much lower than we imagine if technology advances significantly over the next few years.
Another challenge with general models like the one we use is the difficulty of obtaining the data necessary to calibrate the model. We would love to be able to match long-term data from countries around the globe on public opinion, policy, and behaviour change, but unfortunately, this data is not available.
We instead perform two limited calibrations. One is based upon a Time-series of public opinionsClimate change and carbon-price data from The World Bank. The second is based upon A recent studyOn the impact of Swedish carbon price on emissions
Our approach should not be seen as a means to an end, but rather as a beginning of a multidisciplinary research agenda. Future work will be focused on improving the representation of politics, political economy, and calibrating mitigation rates to more detailed energy-system models. It will also focus on better representing strategic interactions between countries and policy spillovers.
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