Articles | Volume 18, issue 20
https://doi.org/10.5194/bg-18-5639-2021
© 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/bg-18-5639-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
20 Oct 2021
Research article | Highlight paper |
| 20 Oct 2021
| 20 Oct 2021
Assessing the representation of the Australian carbon cycle in global vegetation models
ARC Centre of Excellence for Climate Extremes, Sydney, NSW, Australia
Climate Change Research Centre, University of New South Wales, Sydney, NSW, Australia
Martin G. De Kauwe
School of Biological Sciences, University of Bristol, Bristol, BS8 1TQ, UK
ARC Centre of Excellence for Climate Extremes, Sydney, NSW, Australia
Climate Change Research Centre, University of New South Wales, Sydney, NSW, Australia
Andrew J. Pitman
ARC Centre of Excellence for Climate Extremes, Sydney, NSW, Australia
Climate Change Research Centre, University of New South Wales, Sydney, NSW, Australia
Daniel S. Goll
Université Paris Saclay, CEA-CNRS-UVSQ, LSCE/IPSL, Gif sur Yvette, France
Vanessa Haverd
CSIRO Oceans and Atmosphere, G.P.O. Box 1700, Canberra, ACT 2601, Australia
deceased, 19 January 2021
Atul K. Jain
Department of Atmospheric Sciences, University of Illinois, Urbana, IL 61821, USA
Emilie Joetzjer
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France
Etsushi Kato
Institute of Applied Energy (IAE), Minato-ku, Tokyo 105-0003, Japan
Sebastian Lienert
Climate and Environmental Physics, Physics Institute and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Danica Lombardozzi
Terrestrial Sciences Section, Climate and Global Dynamics, National Center for Atmospheric Research, Boulder, CO 80305, USA
Patrick C. McGuire
Department of Meteorology, Department of Geography and Environmental Science, National Centre for Atmospheric Science, University of Reading, Reading, UK
Joe R. Melton
Climate Research Division, Environment and Climate Change Canada, Victoria, BC, Canada
Julia E. M. S. Nabel
Max Planck Institute for Meteorology, Hamburg, Germany
Max Planck Institute for Biogeochemistry, P.O. Box 600164, Hans-Knöll-Str. 10, 07745 Jena, Germany
Julia Pongratz
Max Planck Institute for Meteorology, Hamburg, Germany
Department of Geography, LMU, Munich, Germany
Stephen Sitch
College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4RJ, UK
Anthony P. Walker
Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
Sönke Zaehle
Max Planck Institute for Biogeochemistry, P.O. Box 600164, Hans-Knöll-Str. 10, 07745 Jena, Germany
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- Dynamic global vegetation models may not capture the dynamics of the leaf area index in the tropical rainforests: A data-model intercomparison L. Zou et al. 10.1016/j.agrformet.2023.109562
- Exploring quantification and analyzing driving force for spatial and temporal differentiation characteristics of vegetation net primary productivity in Shandong Province, China Z. Lu et al. 10.1016/j.ecolind.2023.110471
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- Inappropriateness of space-for-time and variability-for-time approaches to infer future dryland productivity changes W. Zhan et al. 10.3389/fenvs.2022.1010269
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- Modelling changes in vegetation productivity and carbon balance under future climate scenarios in southeastern Australia B. Wang et al. 10.1016/j.scitotenv.2024.171748
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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
23 citations as recorded by crossref.
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- Tracking 21st century anthropogenic and natural carbon fluxes through model-data integration S. Bultan et al. 10.1038/s41467-022-32456-0
- Soil respiration–driven CO 2 pulses dominate Australia’s flux variability E. Metz et al. 10.1126/science.add7833
- Using phenology to unravel differential soil water use and productivity in a semiarid savanna B. Steiner et al. 10.1002/ecs2.4762
- Deep Learning Surrogate Models of JULES-INFERNO for Wildfire Prediction on a Global Scale S. Cheng et al. 10.1109/TETCI.2024.3445450
- A Process‐Model Perspective on Recent Changes in the Carbon Cycle of North America G. Murray‐Tortarolo et al. 10.1029/2022JG006904
- Interannual variability of spring and summer monsoon growing season carbon exchange at a semiarid savanna over nearly two decades R. Scott et al. 10.1016/j.agrformet.2023.109584
- Precipitation–fire functional interactions control biomass stocks and carbon exchanges across the world's largest savanna M. Williams et al. 10.5194/bg-22-1597-2025
- Dryland productivity under a changing climate L. Wang et al. 10.1038/s41558-022-01499-y
- Evaluating the Performance of the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) Tailored to the Pan‐Canadian Domain S. Curasi et al. 10.1029/2022MS003480
- Opening Pandora's box: reducing global circulation model uncertainty in Australian simulations of the carbon cycle L. Teckentrup et al. 10.5194/esd-14-549-2023
- Towards species‐level forecasts of drought‐induced tree mortality risk M. De Kauwe et al. 10.1111/nph.18129
- Does maximization of net carbon profit enable the prediction of vegetation behaviour in savanna sites along a precipitation gradient? R. Nijzink et al. 10.5194/hess-26-525-2022
- Thirty-eight years of CO2 fertilization has outpaced growing aridity to drive greening of Australian woody ecosystems S. Rifai et al. 10.5194/bg-19-491-2022
- Dynamic global vegetation models may not capture the dynamics of the leaf area index in the tropical rainforests: A data-model intercomparison L. Zou et al. 10.1016/j.agrformet.2023.109562
- Exploring quantification and analyzing driving force for spatial and temporal differentiation characteristics of vegetation net primary productivity in Shandong Province, China Z. Lu et al. 10.1016/j.ecolind.2023.110471
- A Comprehensive Assessment of Anthropogenic and Natural Sources and Sinks of Australasia's Carbon Budget Y. Villalobos et al. 10.1029/2023GB007845
- Are Plant Functional Types Fit for Purpose? J. Cranko Page et al. 10.1029/2023GL104962
- Inappropriateness of space-for-time and variability-for-time approaches to infer future dryland productivity changes W. Zhan et al. 10.3389/fenvs.2022.1010269
- Explaining the contrast responses of evergreen needle-leaved forest and grassland carbon fluxes during the growing season droughts over the North Temperate Zone X. Li et al. 10.1016/j.ecolind.2025.114016
- Modelling changes in vegetation productivity and carbon balance under future climate scenarios in southeastern Australia B. Wang et al. 10.1016/j.scitotenv.2024.171748
- Climate Change and CO2 Fertilization Have Played Important Roles in the Recent Decadal Vegetation Greening Trend on the Chinese Loess Plateau Z. Niu et al. 10.3390/rs15051233
- Revisiting the role of mean annual precipitation in shaping functional trait distributions at a continental scale I. Towers et al. 10.1111/nph.19478
Latest update: 30 Oct 2025
Short summary
The Australian continent is included in global assessments of the carbon cycle such as the global carbon budget, yet the performance of dynamic global vegetation models (DGVMs) over Australia has rarely been evaluated. We assessed simulations by an ensemble of dynamic global vegetation models over Australia and highlighted a number of key areas that lead to model divergence on both short (inter-annual) and long (decadal) timescales.
The Australian continent is included in global assessments of the carbon cycle such as the...
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