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  Recommendations for producing knowledge syntheses to inform climate change assessments

Ford, J. D., Biesbroek, R., Ford, L. B., Creutzig, F., Haddaway, N., Harper, S., Minx, J. C., New, M., Sietsma, A. J., Zavaleta-Cortijo, C., Callaghan, M. (2025): Recommendations for producing knowledge syntheses to inform climate change assessments. - Nature Climate Change, 15, 698-708.
https://doi.org/10.1038/s41558-025-02354-6

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 Creators:
Ford, James D.1, Author
Biesbroek, Robbert1, Author
Ford, Lea Berrang1, Author
Creutzig, Felix2, Author                 
Haddaway, Neal1, Author
Harper, Sherilee1, Author
Minx, Jan C.2, Author                 
New, Mark1, Author
Sietsma, Anne J.1, Author
Zavaleta-Cortijo, Carol1, Author
Callaghan, Max2, Author                 
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1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, Potsdam, ou_persistent13              

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 Abstract: Climate change assessments (CCAs) play a critical role in taking stock of the available science and other forms of knowledge and informing policy processes. As the underlying evidence base increases exponentially, the complexity also increases and challenges CCA author teams to capture all the relevant knowledge. Therefore, CCAs will need to transition from predominantly assessing primary research to focusing on the assessment and critical appraisal of knowledge syntheses of such work, alongside capturing knowledges held outside traditional scientific sources. To support this, a stronger knowledge synthesis culture is needed, and we propose key recommendations and offer guidance for producing robust, transparent, reproducible, inclusive and timely syntheses that can inform CCAs across scales.

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Language(s): eng - English
 Dates: 2024-08-072025-05-022025-06-102025-07-01
 Publication Status: Finally published
 Pages: 11
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1038/s41558-025-02354-6
PIKDOMAIN: RD5 - Climate Economics and Policy - MCC Berlin
Organisational keyword: RD5 - Climate Economics and Policy - MCC Berlin
Working Group: Evidence for Climate Solutions
Working Group: Cities: Data Science and Sustainable Planning
Model / method: Machine Learning
MDB-ID: No data to archive
 Degree: -

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Project name : GENIE
Grant ID : 951542
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

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Title: Nature Climate Change
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 15 Sequence Number: - Start / End Page: 698 - 708 Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/140414
Publisher: Nature