Articles | Volume 16, issue 6
https://doi.org/10.5194/essd-16-2789-2024
https://doi.org/10.5194/essd-16-2789-2024
Data description paper
 | 
14 Jun 2024
Data description paper |  | 14 Jun 2024

TCSIF: a temporally consistent global Global Ozone Monitoring Experiment-2A (GOME-2A) solar-induced chlorophyll fluorescence dataset with the correction of sensor degradation

Chu Zou, Shanshan Du, Xinjie Liu, and Liangyun Liu

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2023-329', Anonymous Referee #1, 10 Dec 2023
    • AC1: 'Reply on RC1', Chu Zou, 29 Jan 2024
  • RC2: 'Comment on essd-2023-329', Anonymous Referee #2, 19 Dec 2023
    • AC2: 'Reply on RC2', Chu Zou, 29 Jan 2024

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Chu Zou on behalf of the Authors (29 Jan 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (04 Mar 2024) by Chaoqun Lu
RR by Anonymous Referee #2 (17 Mar 2024)
RR by Anonymous Referee #1 (25 Mar 2024)
ED: Publish subject to minor revisions (review by editor) (02 Apr 2024) by Chaoqun Lu
AR by Chu Zou on behalf of the Authors (10 Apr 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Publish subject to minor revisions (review by editor) (24 Apr 2024) by Chaoqun Lu
AR by Chu Zou on behalf of the Authors (25 Apr 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (26 Apr 2024) by Chaoqun Lu
AR by Chu Zou on behalf of the Authors (26 Apr 2024)  Manuscript 
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Short summary
To obtain a temporally consistent satellite solar-induced chlorophyll fluorescence
(SIF) product (TCSIF), we corrected for time degradation of GOME-2A using a pseudo-invariant method. After the correction, the global SIF grew by 0.70 % per year from 2007 to 2021, and 62.91 % of vegetated regions underwent an increase in SIF. The dataset is a promising tool for monitoring global vegetation variation and will advance our understanding of vegetation's photosynthetic activities at a global scale.
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