Using large ensembles of climate change mitigation scenarios for robust insights

Céline Guivarch; Thomas Le Gallic; Nico Bauer; Panagiotis Fragkos; Daniel Huppmann; Marc Jaxa-Rozen; Ilkka Keppo; Elmar Kriegler; Tamás Krisztin; Giacomo Marangoni; Steve Pye; Keywan Riahi; Roberto Schaeffer; Massimo Tavoni; Evelina Trutnevyte; Detlef van Vuuren; Fabian Wagner

doi:10.1038/s41558-022-01349-x

Using large ensembles of climate change mitigation scenarios for robust insights

Céline Guivarch^*
, Thomas Le Gallic
, Nico Bauer
, Panagiotis Fragkos
, Daniel Huppmann
, Marc Jaxa-Rozen
, Ilkka Keppo
, Elmar Kriegler
, Tamás Krisztin
, Giacomo Marangoni
, Steve Pye
, Keywan Riahi
, Roberto Schaeffer
, Massimo Tavoni
, Evelina Trutnevyte
, Detlef van Vuuren
, Fabian Wagner

^*Corresponding author for this work

Research output: Contribution to journal › Review article › peer-review

Abstract

As they gain new users, climate change mitigation scenarios are playing an increasing role in transitions to net zero. One promising practice is the analysis of scenario ensembles. Here we argue that this practice has the potential to bring new and more robust insights compared with the use of single scenarios. However, several important aspects have to be addressed. We identify key methodological challenges and the existing methods and applications that have been or can be used to address these challenges within a three-step approach: (1) pre-processing the ensemble; (2) selecting a few scenarios or analysing the full ensemble; and (3) providing users with efficient access to the information.

Original language	English
Pages (from-to)	428-435
Number of pages	8
Journal	Nature Climate Change
Volume	12
Issue number	5
DOIs	https://doi.org/10.1038/s41558-022-01349-x
Publication status	Published - May 2022

Bibliographical note

Funding Information:
This work received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 821124 (NAVIGATE). R.S. also acknowledges funding received from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil, grant no. 310992/2020-6, and from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 821471 (ENGAGE). P.F. acknowledges funding from the CAMPAIGNers H2020 research project (grant agreement 101003815).

Publisher Copyright:
© 2022, Springer Nature Limited.

Funding

This work received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 821124 (NAVIGATE). R.S. also acknowledges funding received from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil, grant no. 310992/2020-6, and from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 821471 (ENGAGE). P.F. acknowledges funding from the CAMPAIGNers H2020 research project (grant agreement 101003815).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1038/s41558-022-01349-x

s41558-022-01349-xFinal published version, 1.3 MBLicence: Taverne

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Guivarch, C., Le Gallic, T., Bauer, N., Fragkos, P., Huppmann, D., Jaxa-Rozen, M., Keppo, I., Kriegler, E., Krisztin, T., Marangoni, G., Pye, S., Riahi, K., Schaeffer, R., Tavoni, M., Trutnevyte, E., van Vuuren, D., & Wagner, F. (2022). Using large ensembles of climate change mitigation scenarios for robust insights. Nature Climate Change, 12(5), 428-435. https://doi.org/10.1038/s41558-022-01349-x

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abstract = "As they gain new users, climate change mitigation scenarios are playing an increasing role in transitions to net zero. One promising practice is the analysis of scenario ensembles. Here we argue that this practice has the potential to bring new and more robust insights compared with the use of single scenarios. However, several important aspects have to be addressed. We identify key methodological challenges and the existing methods and applications that have been or can be used to address these challenges within a three-step approach: (1) pre-processing the ensemble; (2) selecting a few scenarios or analysing the full ensemble; and (3) providing users with efficient access to the information.",

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note = "Funding Information: This work received funding from the European Union{\textquoteright}s Horizon 2020 research and innovation programme under grant agreement no. 821124 (NAVIGATE). R.S. also acknowledges funding received from Conselho Nacional de Desenvolvimento Cient{\'i}fico e Tecnol{\'o}gico (CNPq), Brazil, grant no. 310992/2020-6, and from the European Union{\textquoteright}s Horizon 2020 research and innovation programme under grant agreement no. 821471 (ENGAGE). P.F. acknowledges funding from the CAMPAIGNers H2020 research project (grant agreement 101003815). Publisher Copyright: {\textcopyright} 2022, Springer Nature Limited.",

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doi = "10.1038/s41558-022-01349-x",

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Guivarch, C, Le Gallic, T, Bauer, N, Fragkos, P, Huppmann, D, Jaxa-Rozen, M, Keppo, I, Kriegler, E, Krisztin, T, Marangoni, G, Pye, S, Riahi, K, Schaeffer, R, Tavoni, M, Trutnevyte, E, van Vuuren, D & Wagner, F 2022, 'Using large ensembles of climate change mitigation scenarios for robust insights', Nature Climate Change, vol. 12, no. 5, pp. 428-435. https://doi.org/10.1038/s41558-022-01349-x

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AU - Bauer, Nico

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AU - Jaxa-Rozen, Marc

AU - Keppo, Ilkka

AU - Kriegler, Elmar

AU - Krisztin, Tamás

AU - Marangoni, Giacomo

AU - Pye, Steve

AU - Riahi, Keywan

AU - Schaeffer, Roberto

AU - Tavoni, Massimo

AU - Trutnevyte, Evelina

AU - van Vuuren, Detlef

AU - Wagner, Fabian

N1 - Funding Information: This work received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 821124 (NAVIGATE). R.S. also acknowledges funding received from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil, grant no. 310992/2020-6, and from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 821471 (ENGAGE). P.F. acknowledges funding from the CAMPAIGNers H2020 research project (grant agreement 101003815). Publisher Copyright: © 2022, Springer Nature Limited.

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N2 - As they gain new users, climate change mitigation scenarios are playing an increasing role in transitions to net zero. One promising practice is the analysis of scenario ensembles. Here we argue that this practice has the potential to bring new and more robust insights compared with the use of single scenarios. However, several important aspects have to be addressed. We identify key methodological challenges and the existing methods and applications that have been or can be used to address these challenges within a three-step approach: (1) pre-processing the ensemble; (2) selecting a few scenarios or analysing the full ensemble; and (3) providing users with efficient access to the information.

AB - As they gain new users, climate change mitigation scenarios are playing an increasing role in transitions to net zero. One promising practice is the analysis of scenario ensembles. Here we argue that this practice has the potential to bring new and more robust insights compared with the use of single scenarios. However, several important aspects have to be addressed. We identify key methodological challenges and the existing methods and applications that have been or can be used to address these challenges within a three-step approach: (1) pre-processing the ensemble; (2) selecting a few scenarios or analysing the full ensemble; and (3) providing users with efficient access to the information.

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Using large ensembles of climate change mitigation scenarios for robust insights

Abstract

Bibliographical note

Funding

UN SDGs

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