TY - JOUR
T1 - Identifying energy model fingerprints in mitigation scenarios
AU - Dekker, Mark M.
AU - Daioglou, Vassilis
AU - Pietzcker, Robert
AU - Rodrigues, Renato
AU - de Boer, Harmen Sytze
AU - Dalla Longa, Francesco
AU - Drouet, Laurent
AU - Emmerling, Johannes
AU - Fattahi, Amir
AU - Fotiou, Theofano
AU - Fragkos, Panagiotis
AU - Fricko, Oliver
AU - Gusheva, Ema
AU - Harmsen, Mathijs
AU - Huppmann, Daniel
AU - Kannavou, Maria
AU - Krey, Volker
AU - Lombardi, Francesco
AU - Luderer, Gunnar
AU - Pfenninger, Stefan
AU - Tsiropoulos, Ioannis
AU - Zakeri, Behnam
AU - van der Zwaan, Bob
AU - Usher, Will
AU - van Vuuren, Detlef
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85175806970&partnerID=8YFLogxK
U2 - 10.1038/s41560-023-01399-1
DO - 10.1038/s41560-023-01399-1
M3 - Article
AN - SCOPUS:85175806970
SN - 2058-7546
VL - 8
SP - 1395
EP - 1404
JO - Nature Energy
JF - Nature Energy
IS - 12
ER -