Articles | Volume 9, issue 1
https://doi.org/10.5194/esd-9-153-2018
© Author(s) 2018. 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-9-153-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Feb 2018
Research article |
| 21 Feb 2018
| 21 Feb 2018
Reliability ensemble averaging of 21st century projections of terrestrial net primary productivity reduces global and regional uncertainties
Jean-François Exbrayat
CORRESPONDING AUTHOR
School of GeoSciences and National Centre for Earth
Observation, University of Edinburgh, Edinburgh, EH9 3FF, UK
A. Anthony Bloom
Jet Propulsion Laboratory, California Institute of
Technology, Pasadena, California, USA
Pete Falloon
Met Office Hadley Centre, Fitzroy Road, Exeter, EX1 3PB, UK
Akihiko Ito
National Institute for Environmental Studies, Tsukuba,
Japan
T. Luke Smallman
School of GeoSciences and National Centre for Earth
Observation, University of Edinburgh, Edinburgh, EH9 3FF, UK
Mathew Williams
School of GeoSciences and National Centre for Earth
Observation, University of Edinburgh, Edinburgh, EH9 3FF, UK
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- Optimizing Carbon Cycle Parameters Drastically Improves Terrestrial Biosphere Model Underestimates of Dryland Mean Net CO2 Flux and its Inter‐Annual Variability K. Mahmud et al. 10.1029/2021JG006400
- Ignoring previous water conditions underestimates global terrestrial ecosystem productivity in severely arid vegetation regions J. Zeng et al. 10.1016/j.gloplacha.2025.104799
- Root mass carbon costs to acquire nitrogen are determined by nitrogen and light availability in two species with different nitrogen acquisition strategies E. Perkowski et al. 10.1093/jxb/erab253
- Simulated response of soil organic carbon density to climate change in the Northern Tibet permafrost region D. Zhao et al. 10.1016/j.geoderma.2021.115455
- Reliability ensemble averaging reduces surface wind speed projection uncertainties in the 21st century over China Z. Zhang & C. Xu 10.1016/j.accre.2024.01.011
- Evaluating two land surface models for Brazil using a full carbon cycle benchmark with uncertainties A. Caen et al. 10.1002/cli2.10
- Multi-model ensemble successfully predicted atmospheric methane consumption in soils across the complex landscape M. Glagolev et al. 10.18822/edgcc625761
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- Evaluation of terrestrial pan-Arctic carbon cycling using a data-assimilation system E. López-Blanco et al. 10.5194/esd-10-233-2019
- Weighting climate models for hydrological projections: effects on contrasting hydroclimatic regions M. Castaneda-Gonzalez et al. 10.1007/s10584-023-03643-9
- Evolution and Mechanism Analysis of Terrestrial Ecosystems in China with Respect to Gross Primary Productivity H. Sun et al. 10.3390/land13091346
- The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space S. Quegan et al. 10.1016/j.rse.2019.03.032
- Understanding the Land Carbon Cycle with Space Data: Current Status and Prospects J. Exbrayat et al. 10.1007/s10712-019-09506-2
24 citations as recorded by crossref.
- Parameter uncertainty dominates C-cycle forecast errors over most of Brazil for the 21st century T. Smallman et al. 10.5194/esd-12-1191-2021
- CO2 fertilization plays a minor role in long-term carbon accumulation patterns in temperate pine forests in the southwestern Pyrenees Y. Lo et al. 10.1016/j.ecolmodel.2019.108737
- Uncertainties of gross primary productivity of Chinese grasslands based on multi-source estimation P. He et al. 10.3389/fenvs.2022.928351
- MATHEMATICAL MODELS OF METHANE CONSUMPTION BY SOILS: A REVIEW M. Glagolev et al. 10.18822/edgcc622937
- Applying ensemble ecosystem model projections to future-proof marine conservation planning in the Northwest Atlantic Ocean A. Bryndum-Buchholz et al. 10.1139/facets-2023-0024
- A Bayesian ensemble data assimilation to constrain model parameters and land-use carbon emissions S. Lienert & F. Joos 10.5194/bg-15-2909-2018
- From Ecosystem Observation to Environmental Decision-Making: Model-Data Fusion as an Operational Tool T. Smallman et al. 10.3389/ffgc.2021.818661
- Changing Pattern of Intensity–Duration–Frequency Relationship of Precipitation due to Climate Change S. Maity & R. Maity 10.1007/s11269-022-03313-y
- Modeling the Carbon Cycle of a Subtropical Chinese Fir Plantation Using a Multi-Source Data Fusion Approach L. Hu et al. 10.3390/f11040369
- Changes in leaf and root carbon allocation of global vegetation simulated by the optimally integrated ecosystem models Z. Duanmu et al. 10.1016/j.agrformet.2024.110366
- Optimizing Carbon Cycle Parameters Drastically Improves Terrestrial Biosphere Model Underestimates of Dryland Mean Net CO2 Flux and its Inter‐Annual Variability K. Mahmud et al. 10.1029/2021JG006400
- Ignoring previous water conditions underestimates global terrestrial ecosystem productivity in severely arid vegetation regions J. Zeng et al. 10.1016/j.gloplacha.2025.104799
- Root mass carbon costs to acquire nitrogen are determined by nitrogen and light availability in two species with different nitrogen acquisition strategies E. Perkowski et al. 10.1093/jxb/erab253
- Simulated response of soil organic carbon density to climate change in the Northern Tibet permafrost region D. Zhao et al. 10.1016/j.geoderma.2021.115455
- Reliability ensemble averaging reduces surface wind speed projection uncertainties in the 21st century over China Z. Zhang & C. Xu 10.1016/j.accre.2024.01.011
- Evaluating two land surface models for Brazil using a full carbon cycle benchmark with uncertainties A. Caen et al. 10.1002/cli2.10
- Multi-model ensemble successfully predicted atmospheric methane consumption in soils across the complex landscape M. Glagolev et al. 10.18822/edgcc625761
- Resolving temperature limitation on spring productivity in an evergreen conifer forest using a model–data fusion framework S. Stettz et al. 10.5194/bg-19-541-2022
- Comparison of Flood Scenarios in the Cunas River Under the Influence of Climate Change C. Torres-Mercado et al. 10.3390/hydrology12050117
- Evaluation of terrestrial pan-Arctic carbon cycling using a data-assimilation system E. López-Blanco et al. 10.5194/esd-10-233-2019
- Weighting climate models for hydrological projections: effects on contrasting hydroclimatic regions M. Castaneda-Gonzalez et al. 10.1007/s10584-023-03643-9
- Evolution and Mechanism Analysis of Terrestrial Ecosystems in China with Respect to Gross Primary Productivity H. Sun et al. 10.3390/land13091346
- The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space S. Quegan et al. 10.1016/j.rse.2019.03.032
- Understanding the Land Carbon Cycle with Space Data: Current Status and Prospects J. Exbrayat et al. 10.1007/s10712-019-09506-2
Discussed (preprint)
Latest update: 08 Jul 2025
Short summary
We use global observations of current terrestrial net primary productivity (NPP) to constrain the uncertainty in large ensemble 21st century projections of NPP under a "business as usual" scenario using a skill-based multi-model averaging technique. Our results show that this procedure helps greatly reduce the uncertainty in global projections of NPP. We also identify regions where uncertainties in models and observations remain too large to confidently conclude a sign of the change of NPP.
We use global observations of current terrestrial net primary productivity (NPP) to constrain...
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