Articles | Volume 17, issue 8
https://doi.org/10.5194/essd-17-3835-2025
https://doi.org/10.5194/essd-17-3835-2025
Data description paper
 | 
08 Aug 2025
Data description paper |  | 08 Aug 2025

A benchmark dataset for global evapotranspiration estimation based on FLUXNET2015 from 2000 to 2022

Wangyipu Li, Zhaoyuan Yao, Yifan Qu, Hanbo Yang, Yang Song, Lisheng Song, Lifeng Wu, and Yaokui Cui

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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-2024-460', Anonymous Referee #1, 24 Jan 2025
    • AC1: 'Reply on RC1', Yaokui Cui, 28 Apr 2025
  • RC2: 'Comment on essd-2024-460', Anonymous Referee #2, 17 Apr 2025
    • AC2: 'Reply on RC2', Yaokui Cui, 28 Apr 2025

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Yaokui Cui on behalf of the Authors (28 Apr 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Publish subject to minor revisions (review by editor) (29 Apr 2025) by Peng Zhu
ED: Publish as is (04 May 2025) by Peng Zhu
AR by Yaokui Cui on behalf of the Authors (10 May 2025)

Post-review adjustments

AA: Author's adjustment | EA: Editor approval
AA by Yaokui Cui on behalf of the Authors (28 Jul 2025)   Author's adjustment   Manuscript
EA: Adjustments approved (05 Aug 2025) by Peng Zhu
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Short summary
Due to shortcomings such as extensive data gaps and limited observation durations in current ground-based latent heat flux (LE) datasets, we developed a novel gap-filling and prolongation framework for ground-based LE observations, establishing a benchmark dataset for global evapotranspiration (ET) estimation from 2000 to 2022 across 64 sites at various timescales. This comprehensive dataset can strongly support ET modeling, water–carbon cycle monitoring, and long-term climate change analysis.
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