Articles | Volume 9, issue 1
https://doi.org/10.5194/esd-9-15-2018
https://doi.org/10.5194/esd-9-15-2018
Research article
 | 
15 Jan 2018
Research article |  | 15 Jan 2018

Systematic Correlation Matrix Evaluation (SCoMaE) – a bottom–up, science-led approach to identifying indicators

Nadine Mengis, David P. Keller, and Andreas Oschlies

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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to minor revisions (review by editor) (16 Nov 2017) by Ben Kravitz
AR by Nadine Mengis on behalf of the Authors (20 Nov 2017)  Author's response   Manuscript 
ED: Publish subject to minor revisions (review by editor) (21 Nov 2017) by Ben Kravitz
AR by Nadine Mengis on behalf of the Authors (24 Nov 2017)  Author's response   Manuscript 
ED: Publish as is (28 Nov 2017) by Ben Kravitz
AR by Nadine Mengis on behalf of the Authors (28 Nov 2017)
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Short summary
The Systematic Correlation Matrix Evaluation (SCoMaE) method applies statistical information to systematically select, transparent, nonredundant indicators for a comprehensive assessment of the Earth system state. We show that due to changing climate forcing, such as anthropogenic climate change, the ad hoc assessment indicators might need to be reevaluated. Within an iterative process, this method would allow us to select scientifically consistent and societally relevant assessment indicators.
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