Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 24, issue 2
Articles | Volume 24, issue 2
https://doi.org/10.5194/hess-24-1011-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-1011-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 24, issue 2
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

Viewed

Total article views: 3,685 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,703 894 88 3,685 104 132
  • HTML: 2,703
  • PDF: 894
  • XML: 88
  • Total: 3,685
  • BibTeX: 104
  • EndNote: 132
Views and downloads (calculated since 12 Aug 2019)
Cumulative views and downloads (calculated since 12 Aug 2019)

Viewed (geographical distribution)

Total article views: 3,685 (including HTML, PDF, and XML) Thereof 3,384 with geography defined and 301 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 29 Nov 2025
Download
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.
Read more
Share