Leveraging open-source tools for collaborative macro-energy system modeling efforts
Published in Joule , 2020
Recommended citation: DeCarolis, J. F., Jaramillo, P., Johnson, J. X., McCollum, D. L., Trutnevyte, E., Daniels, D. C., Akın-Olçum, G., Bergerson, J., Joon-Choi, S., Craig, M.T., de Queiroz, A.R., et al. (2020). Leveraging open-source tools for collaborative macro-energy system modeling efforts. Joule, 4(12), 2523-2526 https://doi.org/10.1016/j.joule.2020.11.002
Many nations have committed to mitigating climate change by designing and implementing policy solutions that enable deep decarbonization of their energy systems. Due to global reliance on fossil fuels, appropriate action requires fundamental and coordinated changes in the way societies generate and use energy. Policy makers face the monumental challenge of crafting effective energy and climate policy in the face of a highly uncertain future. The stakes are high because energy infrastructure often involves large, up-front investments in long-lived assets. Macro-energy system models, which are distinguished from other energy models by their energetic, temporal, and spatial scales, provide a systematic way to examine future decarbonization pathways, evaluate technology choices, test the effects and consequences of proposed policies, and explore decisions under future uncertainty. Analyses using these models yield critical insights that inform energy and climate policymaking around the world and underpin influential reports, including the World Energy Outlook by the International Energy Agency, the Annual Energy Outlook by the US Energy Information Administration, the Special Report on Global Warming of 1.5°C by the Intergovernmental Panel on Climate Change, and many others.
It is an ongoing challenge for macro-energy system modeling teams to meet the universal and unprecedented policy needs associated with climate change mitigation. We envision a paradigm shift in the process of conducting model-based analysis from single-institution modeling teams to distributed, collaborative teams, allowing access to a much wider array of disciplinary and domain expertise to inform a given analysis. While some European efforts are already moving in this direction, the potential for collaborative, model-based analysis has yet to be realized.