Articles | Volume 22, issue 1
https://doi.org/10.5194/hess-22-265-2018
https://doi.org/10.5194/hess-22-265-2018
Research article
 | 
12 Jan 2018
Research article |  | 12 Jan 2018

An adaptive two-stage analog/regression model for probabilistic prediction of small-scale precipitation in France

Jérémy Chardon, Benoit Hingray, and Anne-Catherine Favre

Viewed

Total article views: 2,619 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,532 1,002 85 2,619 356 76 99
  • HTML: 1,532
  • PDF: 1,002
  • XML: 85
  • Total: 2,619
  • Supplement: 356
  • BibTeX: 76
  • EndNote: 99
Views and downloads (calculated since 15 Feb 2017)
Cumulative views and downloads (calculated since 15 Feb 2017)

Viewed (geographical distribution)

Total article views: 2,619 (including HTML, PDF, and XML) Thereof 2,512 with geography defined and 107 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 17 Jun 2024
Download
Short summary
We present a two-stage statistical downscaling model for the probabilistic prediction of local precipitation, where the downscaling statistical link is estimated from atmospheric circulation analogs of the current prediction day. The model allows for a day-to-day adaptive and tailored downscaling. It can reveal specific predictors for peculiar and non-frequent weather configurations. This approach noticeably improves the skill of the prediction for both precipitation occurrence and quantity.