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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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https://doi.org/10.5281/zenodo.8220166 (Supplementary 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).

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

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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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Language(s): eng - English
 Dates: 2023-02-282023-10-052023-11-062023-12-01
 Publication Status: Finally published
 Pages: 10
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: 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
 Degree: -

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Project name : ECEMF
Grant ID : 101022622
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

Source 1

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Title: Nature Energy
Source Genre: Journal, SCI, Scopus
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Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 8 Sequence Number: - Start / End Page: 1395 - 1404 Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/nature-energy
Publisher: Nature