Articles | Volume 12, issue 4
https://doi.org/10.5194/esd-12-1191-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-12-1191-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Nov 2021
Research article |
| 23 Nov 2021
| 23 Nov 2021
Parameter uncertainty dominates C-cycle forecast errors over most of Brazil for the 21st century
Thomas Luke Smallman
CORRESPONDING AUTHOR
School of GeoSciences, University of Edinburgh, Edinburgh, UK
National Centre for Earth Observations, University of Edinburgh, Edinburgh, UK
David Thomas Milodowski
School of GeoSciences, University of Edinburgh, Edinburgh, UK
National Centre for Earth Observations, University of Edinburgh, Edinburgh, UK
Eráclito Sousa Neto
INPE, São José dos Campos, Brazil
Gerbrand Koren
Meteorology and Air Quality, Wageningen University, Wageningen, the Netherlands
Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, the Netherlands
Jean Ometto
INPE, São José dos Campos, Brazil
Mathew Williams
School of GeoSciences, University of Edinburgh, Edinburgh, UK
National Centre for Earth Observations, University of Edinburgh, Edinburgh, UK
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Cited
14 citations as recorded by crossref.
- Global Carbon Budget 2023 P. Friedlingstein et al. 10.5194/essd-15-5301-2023
- Remote sensing-based assessment of land degradation and drought impacts over terrestrial ecosystems in Northeastern Brazil M. de Oliveira et al. 10.1016/j.scitotenv.2022.155490
- Evaluating carbon and water fluxes and stocks in Brazil under changing climate and refined regional scenarios for changes in land use A. Castro et al. 10.3389/fclim.2022.941900
- Improved process representation of leaf phenology significantly shifts climate sensitivity of ecosystem carbon balance A. Norton et al. 10.5194/bg-20-2455-2023
- Flexible Foliar Stoichiometry Reduces the Magnitude of the Global Land Carbon Sink E. Hauser et al. 10.1029/2023GL105493
- Atmospheric CO2 inversion reveals the Amazon as a minor carbon source caused by fire emissions, with forest uptake offsetting about half of these emissions L. Basso et al. 10.5194/acp-23-9685-2023
- Global Carbon Budget 2024 P. Friedlingstein et al. 10.5194/essd-17-965-2025
- Scale variance in the carbon dynamics of fragmented, mixed-use landscapes estimated using model–data fusion D. Milodowski et al. 10.5194/bg-20-3301-2023
- Simulating the land carbon sink: Progresses and challenges of terrestrial ecosystem models W. Yuan et al. 10.1016/j.agrformet.2024.110264
- Defining model complexity: An ecological perspective C. Malmborg et al. 10.1002/met.2202
- CARDAMOM-FluxVal version 1.0: a FLUXNET-based validation system for CARDAMOM carbon and water flux estimates Y. Yang et al. 10.5194/gmd-15-1789-2022
- From Ecosystem Observation to Environmental Decision-Making: Model-Data Fusion as an Operational Tool T. Smallman et al. 10.3389/ffgc.2021.818661
- Isolating the effects of land use and functional variation on Yucatán's forest biomass under global change S. George-Chacon et al. 10.3389/ffgc.2023.1204596
- Evaluation of the Terrestrial Ecosystem Model Biome-BGCMuSo for Modelling Soil Organic Carbon under Different Land Uses M. Ostrogović Sever et al. 10.3390/land10090968
11 citations as recorded by crossref.
- Global Carbon Budget 2023 P. Friedlingstein et al. 10.5194/essd-15-5301-2023
- Remote sensing-based assessment of land degradation and drought impacts over terrestrial ecosystems in Northeastern Brazil M. de Oliveira et al. 10.1016/j.scitotenv.2022.155490
- Evaluating carbon and water fluxes and stocks in Brazil under changing climate and refined regional scenarios for changes in land use A. Castro et al. 10.3389/fclim.2022.941900
- Improved process representation of leaf phenology significantly shifts climate sensitivity of ecosystem carbon balance A. Norton et al. 10.5194/bg-20-2455-2023
- Flexible Foliar Stoichiometry Reduces the Magnitude of the Global Land Carbon Sink E. Hauser et al. 10.1029/2023GL105493
- Atmospheric CO2 inversion reveals the Amazon as a minor carbon source caused by fire emissions, with forest uptake offsetting about half of these emissions L. Basso et al. 10.5194/acp-23-9685-2023
- Global Carbon Budget 2024 P. Friedlingstein et al. 10.5194/essd-17-965-2025
- Scale variance in the carbon dynamics of fragmented, mixed-use landscapes estimated using model–data fusion D. Milodowski et al. 10.5194/bg-20-3301-2023
- Simulating the land carbon sink: Progresses and challenges of terrestrial ecosystem models W. Yuan et al. 10.1016/j.agrformet.2024.110264
- Defining model complexity: An ecological perspective C. Malmborg et al. 10.1002/met.2202
- CARDAMOM-FluxVal version 1.0: a FLUXNET-based validation system for CARDAMOM carbon and water flux estimates Y. Yang et al. 10.5194/gmd-15-1789-2022
3 citations as recorded by crossref.
- From Ecosystem Observation to Environmental Decision-Making: Model-Data Fusion as an Operational Tool T. Smallman et al. 10.3389/ffgc.2021.818661
- Isolating the effects of land use and functional variation on Yucatán's forest biomass under global change S. George-Chacon et al. 10.3389/ffgc.2023.1204596
- Evaluation of the Terrestrial Ecosystem Model Biome-BGCMuSo for Modelling Soil Organic Carbon under Different Land Uses M. Ostrogović Sever et al. 10.3390/land10090968
Latest update: 01 Apr 2025
Short summary
Our study provides a novel assessment of model parameter, structure and climate change scenario uncertainty contribution to future predictions of the Brazilian terrestrial carbon stocks to 2100. We calibrated (2001–2017) five models of the terrestrial C cycle of varied structure. The calibrated models were then projected to 2100 under multiple climate change scenarios. Parameter uncertainty dominates overall uncertainty, being ~ 40 times that of either model structure or climate change scenario.
Our study provides a novel assessment of model parameter, structure and climate change scenario...
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