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  Identifying energy model fingerprints in mitigation scenarios

Dekker, M. M., Daioglou, V., Pietzcker, R. C., Rodrigues, R., de Boer, H.-S., Dalla Longa, F., Drouet, L., Emmerling, J., Fattahi, A., Fotio, T., Fragkos, P., Fricko, O., Gusheva, E., Harmsen, M., Huppmann, D., Kannavou, M., Krey, V., Lombardi, F., Luderer, G., Pfenninger, S., Tsiropoulos, I., Zakeri, B., van der Zwaan, B., Usher, W., van Vuuren, D. (2023): Identifying energy model fingerprints in mitigation scenarios. - Nature Energy, 8, 1395-1404.
https://doi.org/10.1038/s41560-023-01399-1

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externe Referenz:
https://doi.org/10.5281/zenodo.8220166 (Ergänzendes Material)
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This repository is linked to a scientific paper on identifying model fingerprints in mitigation scenario data (https://doi.org/10.1038/s41560-023-01399-1).

Urheber

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 Urheber:
Dekker, Mark M.1, Autor
Daioglou, Vassilis1, Autor
Pietzcker, Robert C.2, Autor              
Rodrigues, Renato2, Autor              
de Boer, Harmen-Sytze1, Autor
Dalla Longa, Francesco1, Autor
Drouet, Laurent1, Autor
Emmerling, Johannes1, Autor
Fattahi, Amir1, Autor
Fotio, Theofano1, Autor
Fragkos, Panagiotis1, Autor
Fricko, Oliver1, Autor
Gusheva, Ema1, Autor
Harmsen, Mathijs1, Autor
Huppmann, Daniel1, Autor
Kannavou, Maria1, Autor
Krey, Volker1, Autor
Lombardi, Francesco1, Autor
Luderer, Gunnar2, Autor              
Pfenninger, Stefan1, Autor
Tsiropoulos, Ioannis1, AutorZakeri, Behnam1, Autorvan der Zwaan, Bob1, AutorUsher, Will1, Autorvan Vuuren, Detlef1, Autor mehr..
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

Inhalt

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Schlagwörter: -
 Zusammenfassung: 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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Sprache(n): eng - Englisch
 Datum: 2023-02-282023-10-052023-11-062023-12-01
 Publikationsstatus: Final veröffentlicht
 Seiten: 10
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1038/s41560-023-01399-1
MDB-ID: No MDB - stored outside PIK (see DOI)
Working Group: Energy Systems
Organisational keyword: RD3 - Transformation Pathways
PIKDOMAIN: RD3 - Transformation Pathways
Model / method: Model Intercomparison
Model / method: Quantitative Methods
Model / method: REMIND
Regional keyword: Europe
Research topic keyword: Climate Policy
Research topic keyword: Energy
Research topic keyword: Carbon Pricing
Research topic keyword: 1.5/2°C limit
Research topic keyword: Decarbonization
Research topic keyword: Economics
OATYPE: Hybrid Open Access
 Art des Abschluß: -

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Projektname : ECEMF
Grant ID : 101022622
Förderprogramm : Horizon 2020 (H2020)
Förderorganisation : European Commission (EC)

Quelle 1

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Titel: Nature Energy
Genre der Quelle: Zeitschrift, SCI, Scopus
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 8 Artikelnummer: - Start- / Endseite: 1395 - 1404 Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/nature-energy
Publisher: Nature