Global Carbon Budget
|Fachgebiet: Klimatologie, Modellierung, Vegetationsgeographie
Projektleitung: Prof. Dr. Julia Pongratz
Projektwissenschaftler: M.Sc. Selma Bultan, Dr. Wolfgang A. Obermeier, Prof. Dr. Julia Pongratz
Laufzeit: 04/2018 - 12/2025
The key aim of the project is to quantify the sinks and sources of CO2 related to human activity and to enhance our understanding of the underlying physical and biogeochemical processes. This supports the monitoring of the progress of climate policies and management of land that reduces emissions and enhances CO2 uptake. To this end, we contribute regularly to the annual global carbon budgets of the Global Carbon Project by providing dynamic global vegetation model simulations as part of the TRENDY exercise and bookkeeping estimates of land-use fluxes. Further, Julia Pongratz coordinates the land-use emissions estimates. Global assessments are increasingly brought to the regional (Bastos et al. 2020 in Global Biogeochem. Cycles) and country-level.
Land-use emissions are the most uncertain term in the global carbon budget and we put a special focus on quantifying and reducing these uncertainties, by investigating uncertainty of historical land-use reconstructions (Hartung et al. 2021 in Earth System Dynamics), analyzing relevance of modeling choices (Bastos et al. 2021 in Earth System Dynamics) and reconciling different modeling approaches (Obermeier et al. 2021 in Earth System Dynamics).
We also investigate the persistence of the natural terrestrial sink. Responding favorably to atmospheric CO2 increases (Walker et al. 2020 in New Phytologist) and other environmental changes, managed and unmanaged vegetation together remove about one third of all (fossil and land-use) anthropogenic CO2 emissions from the atmosphere. However, the natural terrestrial sink has been highly susceptible to recent droughts (Bastos et al. 2020 in Philos. Trans. R. Soc. B and Bastos et al. 2020 in Sci. Adv.).
Recent activities relate to identifying the natural variability of the carbon budget terms using the MPI Grand Ensemble.