Overcoming the disconnect between energy system and climate modeling
Craig, Michael; Wohland, Jan; Stoop, L.P.; Kies, Alex; Pickering, Bryn; Bloomfield, Hannah; Browell, J.; De Felice, Matteo; Dent, Chris; Deroubaix, Adrien; Frischmuth, Felix; Gonzalez, Paula; Grochowicz, Aleksander; Gruber, Katharina; Härtel, Philip; Kittel, Martin; Kotzur, Leander; Labuhn, Inga; Lundquist, Julie K.; Pflugradt, Noah; van der Wiel, Karin; Zeyringer, Marianne; Brayshaw, David J.
(2022) Joule, volume 6, issue 7, pp. 1405 - 1417
(Article)
Abstract
Energy system models underpin decisions by energy system planners and operators. Energy system modeling faces a transformation: accounting for changing meteorological conditions imposed by climate change. To enable that transformation, a community of practice in energy-climate modeling has started to form that aims to better integrate energy system models with
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weather and climate models. Here, we evaluate the disconnects between the energy system and climate modeling communities, then lay out a research agenda to bridge those disconnects. In the near-term, we propose interdisciplinary activities for expediting uptake of future climate data in energy system modeling. In the long-term, we propose a transdisciplinary approach to enable development of (1) energy-system-tailored climate datasets for historical and future meteorological conditions and (2) energy system models that can effectively leverage those datasets. This agenda increases the odds of meeting ambitious climate mitigation goals by systematically capturing and mitigating climate risk in energy sector decision-making.
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Keywords: Taverne
ISSN: 2542-4351
Publisher: Cell Press
Note: Funding Information: The hosting of the NextGenEC workshops—which led to the initiation and progression of this paper—was enabled with the kind support of the University of Reading and the National Centre for Atmospheric Science (e.g. through access to conferencing software), and the initial workshop concept was developed during the PRIMAVERA project (which received funding from the European Union's Horizon 2020 Research and Innovation Program under grant agreement no. 641727). The authors would like to acknowledge the following sources of funding. During large parts of this work, J.W. was funded through an ETH Postdoctoral Fellowship and acknowledges support from the ETH and Uniscientia foundations. B.P. was funded by the Swiss Federal Office of Energy (SFOE) under grant number SI/502229. L.P.S. received funding from the Netherlands Organisation for Scientific Research (NWO) under grant number 647.003.005 and is part of the IS-ENES3 project that has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement no. 824084. C.J.D. is part of the projects “Managing Uncertainty in Government Modeling” (sponsored by the Alan Turing Institute) and “Decision support under climate uncertainty for energy security and net zero” (sponsored by the Alan Turing Institute and EPSRC). A.G. acknowledges UiO:Energi Thematic Research Group Spatial-Temporal Uncertainty in Energy Systems (SPATUS). K.G. is funded through the reFUEL project, an ERC grant with no. ERC2017-STG 758149. P.H. is part of the PROGRESS project funded by the Federal Ministry for Economic Affairs and Energy (BMWi.IIC5, funding ref. 03EI1027). J.K.L. has funding provided by the US Department of Energy Office of Energy Efficiency and Renewable Energy Wind Energy Technologies Office. This work was authored in part by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the US Department of Energy (DOE) under contract no. DE-AC36-08GO28308. D.J.B. was a co-principal investigator on the EU H2020 PRIMAVERA project (grant number 641727) and is the lead-convenor of the Next Generation Challenges in Energy Climate Modeling workshops from which this perspective was developed. Conceptualization, D.J.B. J.W. M.T.C. and L.P.S.; original draft, J.W. M.T.C. and L.P.S.; revision, review, and editing core group, D.J.B. M.T.C. A.K. B.P. L.P.S. and J.W.; revision and review, all authors. All authors (except L.K.) were present at the Next Generation Energy Climate Modeling 2021 workshop that led to the conceptualization of this paper and was organized by D.J.B. The ordering of the first two authors was decided by a coin toss; these co-first authors can prioritize their names as first authors when adding this paper's reference to their résumés. The authors declare no competing interests. Funding Information: The hosting of the NextGenEC workshops—which led to the initiation and progression of this paper—was enabled with the kind support of the University of Reading and the National Centre for Atmospheric Science (e.g., through access to conferencing software), and the initial workshop concept was developed during the PRIMAVERA project (which received funding from the European Union’s Horizon 2020 Research and Innovation Program under grant agreement no. 641727 ). The authors would like to acknowledge the following sources of funding. During large parts of this work, J.W. was funded through an ETH Postdoctoral Fellowship and acknowledges support from the ETH and Uniscientia foundations . B.P. was funded by the Swiss Federal Office of Energy (SFOE) under grant number SI/502229 . L.P.S. received funding from the Netherlands Organisation for Scientific Research (NWO) under grant number 647.003.005 and is part of the IS-ENES3 project that has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 824084 . C.J.D. is part of the projects “Managing Uncertainty in Government Modeling” (sponsored by the Alan Turing Institute ) and “Decision support under climate uncertainty for energy security and net zero” (sponsored by the Alan Turing Institute and EPSRC ). A.G. acknowledges UiO:Energi Thematic Research Group Spatial-Temporal Uncertainty in Energy Systems (SPATUS). K.G. is funded through the reFUEL project, an ERC grant with no. ERC2017-STG 758149 . P.H. is part of the PROGRESS project funded by the Federal Ministry for Economic Affairs and Energy (BMWi.IIC5, funding ref. 03EI1027 ). J.K.L. has funding provided by the US Department of Energy Office of Energy Efficiency and Renewable Energy Wind Energy Technologies Office . This work was authored in part by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the US Department of Energy (DOE) under contract no. DE-AC36-08GO28308 . D.J.B. was a co-principal investigator on the EU H2020 PRIMAVERA project (grant number 641727 ) and is the lead-convenor of the Next Generation Challenges in Energy Climate Modeling workshops from which this perspective was developed. Publisher Copyright: © 2022 Elsevier Inc.
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