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

Data sets

Imputation of missing land carbon sequestration data in the AR6 Scenario Database Ruben Prütz et al. https://doi.org/10.5281/zenodo.13373539

Model code and software

Imputation of missing land carbon sequestration data in the AR6 Scenario Database Ruben Prütz et al. https://doi.org/10.5281/zenodo.13373539

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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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