Articles | Volume 20, issue 23
https://doi.org/10.5194/bg-20-4795-2023
© Author(s) 2023. 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-20-4795-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Dec 2023
Research article |
| 06 Dec 2023
| 06 Dec 2023
Temporal variability of observed and simulated gross primary productivity, modulated by vegetation state and hydrometeorological drivers
Department of Meteorological and Climatological Research, Royal Meteorological Institute, Brussels, Belgium
Sebastian Wieneke
Remote Sensing Centre for Earth System Research, University of Leipzig, Leipzig, Germany
Ana Bastos
Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
José Miguel Barrios
Department of Meteorological and Climatological Research, Royal Meteorological Institute, Brussels, Belgium
Liyang Liu
Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
Philippe Ciais
Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
Alirio Arboleda
Department of Meteorological and Climatological Research, Royal Meteorological Institute, Brussels, Belgium
Rafiq Hamdi
Department of Meteorological and Climatological Research, Royal Meteorological Institute, Brussels, Belgium
Maral Maleki
Department of Biology, University of Antwerp, Antwerp, Belgium
Fabienne Maignan
Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
Françoise Gellens-Meulenberghs
Department of Meteorological and Climatological Research, Royal Meteorological Institute, Brussels, Belgium
Ivan Janssens
Department of Biology, University of Antwerp, Antwerp, Belgium
Manuela Balzarolo
Department of Biology, University of Antwerp, Antwerp, Belgium
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Cited
10 citations as recorded by crossref.
- Forest carbon uptake as influenced by snowpack and length of photosynthesis season in seasonally snow-covered forests of North America J. Yang et al. https://doi.org/10.1016/j.agrformet.2024.110054
- Monitoring and modeling seasonally varying anthropogenic and biogenic CO2 over a large tropical metropolitan area R. Alberti et al. https://doi.org/10.5194/acp-25-9803-2025
- Comparing the performance of vegetation indices for improving urban vegetation GPP estimation via eddy covariance flux data and Landsat 5/7 data Q. Zeng et al. https://doi.org/10.1016/j.ecoinf.2025.103023
- Global Photovoltaic Cool Island Effect Modulated by Dual Pathways of Evapotranspiration Suppression and Photovoltaic Conversion J. Guo et al. https://doi.org/10.1021/acs.est.5c17772
- Hydrothermal integration and synergy regulate carbon exchange in forest ecosystems of eastern China Y. Wang et al. https://doi.org/10.1016/j.agrformet.2025.110888
- Divergent responses of photosynthesis and respiration underlie the nonlinear response of carbon use efficiency to temperature in sub-frigid forest in China Q. Lei et al. https://doi.org/10.1093/jpe/rtaf162
- Sim2DSphere: A novel modelling tool for the study of land surface interactions G. Petropoulos et al. https://doi.org/10.1016/j.envsoft.2024.106086
- Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe C. Poppe Terán et al. https://doi.org/10.5194/gmd-18-287-2025
- Modelling decadal trends and the impact of extreme events on carbon fluxes in a temperate deciduous forest using a terrestrial biosphere model T. Thum et al. https://doi.org/10.5194/bg-22-1781-2025
- The Increased Effect of Spring Leaf Unfolding on Autumn Senescence in the Northern and Southern Hemispheres D. Tang et al. https://doi.org/10.1111/geb.70180
10 citations as recorded by crossref.
- Forest carbon uptake as influenced by snowpack and length of photosynthesis season in seasonally snow-covered forests of North America J. Yang et al. https://doi.org/10.1016/j.agrformet.2024.110054
- Monitoring and modeling seasonally varying anthropogenic and biogenic CO2 over a large tropical metropolitan area R. Alberti et al. https://doi.org/10.5194/acp-25-9803-2025
- Comparing the performance of vegetation indices for improving urban vegetation GPP estimation via eddy covariance flux data and Landsat 5/7 data Q. Zeng et al. https://doi.org/10.1016/j.ecoinf.2025.103023
- Global Photovoltaic Cool Island Effect Modulated by Dual Pathways of Evapotranspiration Suppression and Photovoltaic Conversion J. Guo et al. https://doi.org/10.1021/acs.est.5c17772
- Hydrothermal integration and synergy regulate carbon exchange in forest ecosystems of eastern China Y. Wang et al. https://doi.org/10.1016/j.agrformet.2025.110888
- Divergent responses of photosynthesis and respiration underlie the nonlinear response of carbon use efficiency to temperature in sub-frigid forest in China Q. Lei et al. https://doi.org/10.1093/jpe/rtaf162
- Sim2DSphere: A novel modelling tool for the study of land surface interactions G. Petropoulos et al. https://doi.org/10.1016/j.envsoft.2024.106086
- Systematic underestimation of type-specific ecosystem process variability in the Community Land Model v5 over Europe C. Poppe Terán et al. https://doi.org/10.5194/gmd-18-287-2025
- Modelling decadal trends and the impact of extreme events on carbon fluxes in a temperate deciduous forest using a terrestrial biosphere model T. Thum et al. https://doi.org/10.5194/bg-22-1781-2025
- The Increased Effect of Spring Leaf Unfolding on Autumn Senescence in the Northern and Southern Hemispheres D. Tang et al. https://doi.org/10.1111/geb.70180
Saved (final revised paper)
Latest update: 26 Jul 2026
Short summary
The gross primary production (GPP) of the terrestrial biosphere is a key source of variability in the global carbon cycle. To estimate this flux, models can rely on remote sensing data (RS-driven), meteorological data (meteo-driven) or a combination of both (hybrid). An intercomparison of 11 models demonstrated that RS-driven models lack the sensitivity to short-term anomalies. Conversely, the simulation of soil moisture dynamics and stress response remains a challenge in meteo-driven models.
The gross primary production (GPP) of the terrestrial biosphere is a key source of variability...
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