MANET · Climate economic policies: assessing values and costs of uncertainty in energy scenarios

Climate economic policies: assessing values and costs of uncertainty in energy scenarios

Climate change, a consistently variation of weather patterns beyond natural variability, is being affecting life on earth at different levels of severity and magnitude across the world. The global mean temperature has already grown by one degree Celsius compared to pre-industrial times, but the worst forecasts announce that a staggering increase by nearly 4°C could be reached. Global warming, the main cause of climate change, is due to the accumulation of greenhouse gases at higher rates compared to the pre-industrial times. The Intergovernmental Panel on Climate Change (IPCC) has demonstrated a causal link between global warming, higher rates of anthropogenic emissions, and a growing energy demand from the society and industries. Integrated Assessment Models (IAMs) are key tools used in the research community informing the IPCC on the nexus between climate modelling, social science, and energy systems. Despite IAMs are powerful tools, they are subjected to concerns in the way they are used and in the way their outputs are interpreted, since they must deal with complex systems and projections over hundreds of years. Uncertainty of the long-term energy futures means that broad ranges of projections are obtained from IAMs. For instance, the uptake of key decarbonisation technologies such as renewables, carbon capture and storage (CCS), electric vehicles, vary hugely among the IAMs outputs, as they are displayed in emissions scenarios ensembles. Uncertainty in the scenarios showing possible ranges of intervention to reduce emissions, has resulted in a lack of constructive political initiatives for the promotion of the investments needed to face climate change and its consequences. If on the one side, policy makers are not cohesively joint to tackle climate change with robust political, economic, and social decisions, on the other side, the effects of climate change are more and more visible in everyday life. Long-term strategies for mitigation and adaptation should make the backbone of national and international policies. To solve the problem of uncertainties in scenarios which have been paralysing the development of coherent policy frameworks, this fellowship project has contributed to increasing the awareness of the uncertainty implications in the use of ensembles of IAMs outputs for informing policies on mitigation and adaptation. To do so, the fellowship has focused on characterising the source of these uncertainties from linking the outputs with the inputs of IAMs. The diversity in the response from IAMs could be either coming from assumptions on data inputs (parametric uncertainty) or features of the model (structural uncertainty). Specifically, the focus was on defining what triggers the most the differential response in the IAMs projections. This has been achieved building semi-quantitative and quantitative methods.

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