Articles | Volume 24, issue 2
https://doi.org/10.5194/hess-24-1011-2020
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

Data sets

Post-processed crop reference evapotranspiration forecasts H. Medina and D. Tian https://doi.org/10.17605/OSF.IO/NG6WA

Model code and software

Post-processed crop reference evapotranspiration forecasts H. Medina and D. Tian https://doi.org/10.17605/OSF.IO/NG6WA

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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.