Articles | Volume 16, issue 6
https://doi.org/10.5194/essd-16-2789-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-2789-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
14 Jun 2024
Data description paper |
| 14 Jun 2024
| 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
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, 100094 Beijing, China
College of Resources and Environment, University of Chinese Academy of Sciences, 100049 Beijing, China
International Research Center of Big Data for Sustainable Development Goals, 100094 Beijing, China
Shanshan Du
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, 100094 Beijing, China
International Research Center of Big Data for Sustainable Development Goals, 100094 Beijing, China
Xinjie Liu
CORRESPONDING AUTHOR
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, 100094 Beijing, China
International Research Center of Big Data for Sustainable Development Goals, 100094 Beijing, China
Liangyun Liu
Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, 100094 Beijing, China
College of Resources and Environment, University of Chinese Academy of Sciences, 100049 Beijing, China
International Research Center of Big Data for Sustainable Development Goals, 100094 Beijing, China
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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.
(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.
To obtain a temporally consistent satellite solar-induced chlorophyll fluorescence
(SIF) product...
(SIF) product...
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Final-revised paper
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