Articles | Volume 20, issue 23
https://doi.org/10.5194/bg-20-4795-2023
https://doi.org/10.5194/bg-20-4795-2023
Research article
 | 
06 Dec 2023
Research article |  | 06 Dec 2023

Temporal variability of observed and simulated gross primary productivity, modulated by vegetation state and hydrometeorological drivers

Jan De Pue, Sebastian Wieneke, Ana Bastos, José Miguel Barrios, Liyang Liu, Philippe Ciais, Alirio Arboleda, Rafiq Hamdi, Maral Maleki, Fabienne Maignan, Françoise Gellens-Meulenberghs, Ivan Janssens, and Manuela Balzarolo

Viewed

Total article views: 1,874 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,556 266 52 1,874 46 60 62
  • HTML: 1,556
  • PDF: 266
  • XML: 52
  • Total: 1,874
  • Supplement: 46
  • BibTeX: 60
  • EndNote: 62
Views and downloads (calculated since 12 Jun 2023)
Cumulative views and downloads (calculated since 12 Jun 2023)

Viewed (geographical distribution)

Total article views: 1,874 (including HTML, PDF, and XML) Thereof 1,836 with geography defined and 38 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 13 Mar 2025
Download
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.
Share
Altmetrics
Final-revised paper
Preprint