Abstract
Probabilistic projections of baseline (with no additional mitigation policies) future carbon emissions are important for sound climate risk assessments. Deep uncertainty surrounds many drivers of projected emissions. Here, we use a simple integrated assessment model, calibrated to century-scale data and expert assessments of baseline emissions, global economic growth, and population growth, to make probabilistic projections of carbon emissions through 2100. Under a variety of assumptions about fossil fuel resource levels and decarbonization rates, our projections largely agree with several emissions projections under current policy conditions. Our global sensitivity analysis identifies several key economic drivers of uncertainty in future emissions and shows important higher-level interactions between economic and technological parameters, while population uncertainties are less important. Our analysis also projects relatively low global economic growth rates over the remainder of the century. This illustrates the importance of additional research into economic growth dynamics for climate risk assessment, especially if pledged and future climate mitigation policies are weakened or have delayed implementations. These results showcase the power of using a simple, transparent, and calibrated model. While the simple model structure has several advantages, it also creates caveats for our results which are related to important areas for further research.
Highlights
What is a sound approach to projecting future climate change and its impacts? This is a critical question for understanding the impact of adaptation and mitigation strategies
One approach, adopted in the reports of the Intergovernmental Panel on Climate Change, or IPCC (IPCC 2014), to handling the deep uncertainty associated with future emissions and the associated radiative forcing is to use scenarios which cover an appropriate range of plausible futures
We focus on projecting baseline CO2 emissions for the remainder of the twenty-first century, only incorporating the effects of those mitigation policies which have had sufficient effect to be reflected in the calibration data
Summary
What is a sound approach to projecting future climate change and its impacts? This is a critical question for understanding the impact of adaptation and mitigation strategies. These scenarios are useful for creating a set of harmonized assumptions for modeling and impacts studies As they are not intended to be interpreted as predictions of future socioeconomic, emissions, or climate trajectories, they are explicitly provided without probabilities or likelihoods (van Vuuren et al 2011). Another approach is the use of a Bayesian statistical model calibrated using historical data (e.g., Raftery et al 2017; Liu and Raftery 2021) These models can be run many times, allowing them to fully resolve the tails of the projective distributions, and are flexible enough to capture historical dynamics while representing different future scenarios and potential trend breaks.
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