Identifying energy model fingerprints in mitigation scenarios
Mark M. Dekker (Universiteit Utrecht, Planbureau voor de Leefomgeving)
Vassilis Daioglou (Universiteit Utrecht, Planbureau voor de Leefomgeving)
Robert Pietzcker (Potsdam-Institut für Klimafolgenforschung)
Renato Rodrigues (Potsdam-Institut für Klimafolgenforschung)
Harmen Sytze de Boer (Planbureau voor de Leefomgeving)
Francesco Dalla Longa (TNO)
Laurent Drouet (Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici)
Johannes Emmerling (Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici)
Amir Fattahi (TNO)
Theofano Fotiou (E3-Modelling)
Panagiotis Fragkos (E3-Modelling)
Oliver Fricko (International Institute for Applied Systems Analysis)
Ema Gusheva (TU Delft - Energy and Industry)
Mathijs Harmsen (Universiteit Utrecht, Planbureau voor de Leefomgeving)
Daniel Huppmann (International Institute for Applied Systems Analysis)
Maria Kannavou (E3-Modelling)
Volker Krey (International Institute for Applied Systems Analysis)
Francesco Lombardi (TU Delft - Energy and Industry)
Gunnar Luderer (Potsdam-Institut für Klimafolgenforschung, Technical University of Berlin)
Stefan Pfenninger (TU Delft - Energy and Industry)
Ioannis Tsiropoulos (E3-Modelling)
Behnam Zakeri (International Institute for Applied Systems Analysis)
Bob van der Zwaan (Universiteit van Amsterdam, Johns Hopkins School of Advanced International Studies European campus, TNO)
Will Usher (KTH Royal Institute of Technology)
Detlef van Vuuren (Planbureau voor de Leefomgeving, Universiteit Utrecht)
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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.
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