Articles | Volume 15, issue 17
Development and technical paper
02 Sep 2022
Development and technical paper |  | 02 Sep 2022

Pixel-level parameter optimization of a terrestrial biosphere model for improving estimation of carbon fluxes with an efficient model–data fusion method and satellite-derived LAI and GPP data

Rui Ma, Jingfeng Xiao, Shunlin Liang, Han Ma, Tao He, Da Guo, Xiaobang Liu, and Haibo Lu


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2022-96', Anonymous Referee #1, 01 Jun 2022
    • AC1: 'Reply on RC1', Rui Ma, 08 Jun 2022
  • RC2: 'Comment on gmd-2022-96', Anonymous Referee #2, 05 Jun 2022
    • AC2: 'Reply on RC2', Rui Ma, 16 Jul 2022
    • AC4: 'Reply on RC2', Rui Ma, 18 Jul 2022
    • AC5: 'Reply on RC2', Rui Ma, 01 Aug 2022
  • CEC1: 'Comment on gmd-2022-96', Juan Antonio Añel, 15 Jun 2022
    • AC3: 'Reply on CEC1', Rui Ma, 16 Jul 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Rui Ma on behalf of the Authors (01 Aug 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (02 Aug 2022) by Tomomichi Kato
AR by Rui Ma on behalf of the Authors (05 Aug 2022)  Author's response   Manuscript 

Post-review adjustments

AA: Author's adjustment | EA: Editor approval
AA by Rui Ma on behalf of the Authors (30 Aug 2022)   Author's adjustment   Manuscript
EA: Adjustments approved (30 Aug 2022) by Tomomichi Kato
Short summary
Parameter optimization can improve the accuracy of modeled carbon fluxes. Few studies conducted pixel-level parameterization because it requires a high computational cost. Our paper used high-quality spatial products to optimize parameters at the pixel level, and also used the machine learning method to improve the speed of optimization. The results showed that there was significant spatial variability of parameters and we also improved the spatial pattern of carbon fluxes.