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

This repository is linked to the following research paper:

Prütz, R., Fuss, S., and Rogelj, J.: Imputation of missing land carbon sequestration data in the AR6 Scenarios Database, Earth Syst. Sci. Data, 2025. https://doi.org/10.5194/essd-17-221-2025 

This repository includes: 

An imputation dataset for missing land carbon sequestation data of the AR6 Scenarios Database for global scenarios and R10 scenario variants

Code to test, compare and visualize the performance of regression models to predict missing land removal data

Code to compare and visualize available AR6 land removal data and existing AR6 data reanalyses

The following two datasets are required to replicate the analysis:

Byers, E., Krey, V., Kriegler, E., Riahi, K., Schaeffer, R., Kikstra, J., Lamboll, R., Nicholls, Z., Sandstad, M., Smith, C., van der Wijst, K., Al -Khourdajie, A., Lecocq, F., Portugal-Pereira, J., Saheb, Y., Stromman, A., Winkler, H., Auer, C., Brutschin, E., … van Vuuren, D. (2022). AR6 Scenarios Database [Data set]. In Climate Change 2022: Mitigation of Climate Change (1.1). Intergovernmental Panel on Climate Change. https://doi.org/10.5281/zenodo.7197970

Gidden, M., Gasser, T., Grassi, G., Forsell, N., Janssens, I., Lamb, W. F., Minx, J., Nicholls, Z., Steinhauser, J., & Riahi, K. (2023). Dataset for Gidden et.al. 2023 Updated AR6 Mitigation Benchmarks using National Emissions Inventories (Version v2) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10158920

The variable imputation is based on the dataset by Byers et al. (2022). The dataset by Gidden et al. (2023) is used for variable comparison.