Articles | Volume 24, issue 2
Hydrol. Earth Syst. Sci., 24, 1011–1030, 2020
https://doi.org/10.5194/hess-24-1011-2020
Hydrol. Earth Syst. Sci., 24, 1011–1030, 2020
https://doi.org/10.5194/hess-24-1011-2020

Research article 03 Mar 2020

Research article | 03 Mar 2020

Comparison of probabilistic post-processing approaches for improving numerical weather prediction-based daily and weekly reference evapotranspiration forecasts

Hanoi Medina and Di Tian

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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to minor revisions (further review by editor) (02 Dec 2019) by Albrecht Weerts
AR by Svenja Lange on behalf of the Authors (17 Dec 2019)  Author's response    Manuscript
ED: Publish subject to technical corrections (22 Jan 2020) by Albrecht Weerts
AR by Di Tian on behalf of the Authors (29 Jan 2020)  Author's response    Manuscript
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Short summary
Reference evapotranspiration (ET0) forecasts play an important role in agricultural, environmental, and water management. This study evaluated probabilistic post-processing approaches for improving daily and weekly ensemble ET0 forecasting based on single or multiple numerical weather predictions. The three approaches used consistently improved the skill and reliability of the ET0 forecasts compared with the conventional method, due to the adjustment in the spread of the ensemble forecast.