Articles | Volume 17, issue 1
https://doi.org/10.5194/essd-17-221-2025
https://doi.org/10.5194/essd-17-221-2025
Data description paper
 | 
27 Jan 2025
Data description paper |  | 27 Jan 2025

Imputation of missing land carbon sequestration data in the AR6 Scenarios Database

Ruben Prütz, Sabine Fuss, and Joeri Rogelj

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Short summary
The AR6 Scenarios Database lacks data on carbon dioxide removal (CDR) via land sinks for many pathways, hindering secondary scenario analyses. We tested and compared regression models, identifying k-nearest neighbors regression as most effective to predict missing CDR data. We provide an imputation dataset for incomplete global scenarios (n = 404) and for regional scenario variants (n = 2358) and discuss the caveats of our study, its use cases, and how our dataset compares to other approaches.
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