Articles | Volume 20, issue 23
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


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-994', Anonymous Referee #1, 18 Jul 2023
    • AC1: 'Reply on RC1', Jan De Pue, 03 Oct 2023
  • RC2: 'Comment on egusphere-2023-994', Anonymous Referee #2, 02 Sep 2023
    • AC2: 'Reply on RC2', Jan De Pue, 03 Oct 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Publish subject to minor revisions (review by editor) (07 Oct 2023) by Paul Stoy
AR by Jan De Pue on behalf of the Authors (09 Oct 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (16 Oct 2023) by Paul Stoy
AR by Jan De Pue on behalf of the Authors (20 Oct 2023)
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.
Final-revised paper