Identifying energy model fingerprints in mitigation scenarios

Mark M. Dekker (), Vassilis Daioglou, Robert Pietzcker, Renato Rodrigues, Harmen-Sytze Boer, Francesco Dalla Longa, Laurent Drouet, Johannes Emmerling, Amir Fattahi, Theofano Fotiou, Panagiotis Fragkos, Oliver Fricko, Ema Gusheva, Mathijs Harmsen, Daniel Huppmann, Maria Kannavou, Volker Krey, Francesco Lombardi, Gunnar Luderer, Stefan Pfenninger, Ioannis Tsiropoulos, Behnam Zakeri, Bob Zwaan, Will Usher and Detlef Vuuren
Additional contact information
Mark M. Dekker: PBL Netherlands Environmental Assessment Agency
Vassilis Daioglou: PBL Netherlands Environmental Assessment Agency
Robert Pietzcker: Potsdam Institute for Climate Impact Research
Renato Rodrigues: Potsdam Institute for Climate Impact Research
Harmen-Sytze Boer: PBL Netherlands Environmental Assessment Agency
Francesco Dalla Longa: TNO Energy and Materials Transition
Laurent Drouet: Centro Euro‐Mediterraneo sui Cambiamenti Climatici
Johannes Emmerling: Centro Euro‐Mediterraneo sui Cambiamenti Climatici
Amir Fattahi: TNO Energy and Materials Transition
Theofano Fotiou: E3-Modelling SA
Panagiotis Fragkos: E3-Modelling SA
Oliver Fricko: International Institute for Applied Systems Analysis (IIASA)
Ema Gusheva: Delft University of Technology
Mathijs Harmsen: PBL Netherlands Environmental Assessment Agency
Daniel Huppmann: International Institute for Applied Systems Analysis (IIASA)
Maria Kannavou: E3-Modelling SA
Volker Krey: International Institute for Applied Systems Analysis (IIASA)
Francesco Lombardi: Delft University of Technology
Gunnar Luderer: Potsdam Institute for Climate Impact Research
Stefan Pfenninger: Delft University of Technology
Ioannis Tsiropoulos: E3-Modelling SA
Behnam Zakeri: International Institute for Applied Systems Analysis (IIASA)
Bob Zwaan: TNO Energy and Materials Transition
Will Usher: KTH Royal Institute of Technology
Detlef Vuuren: PBL Netherlands Environmental Assessment Agency

Nature Energy, 2023, vol. 8, issue 12, 1395-1404

Abstract: Abstract Energy models are used to study emissions mitigation pathways, such as those compatible with the Paris Agreement goals. These models vary in structure, objectives, parameterization and level of detail, yielding differences in the computed energy and climate policy scenarios. To study model differences, diagnostic indicators are common practice in many academic fields, for example, in the physical climate sciences. However, they have not yet been applied systematically in mitigation literature, beyond addressing individual model dimensions. Here we address this gap by quantifying energy model typology along five dimensions: responsiveness, mitigation strategies, energy supply, energy demand and mitigation costs and effort, each expressed through several diagnostic indicators. The framework is applied to a diagnostic experiment with eight energy models in which we explore ten scenarios focusing on Europe. Comparing indicators to the ensemble yields comprehensive ‘energy model fingerprints’, which describe systematic model behaviour and contextualize model differences for future multi-model comparison studies.

Date: 2023
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DOI: 10.1038/s41560-023-01399-1

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