Articles | Volume 20, issue 5
https://doi.org/10.5194/nhess-20-1369-2020
https://doi.org/10.5194/nhess-20-1369-2020
Research article
 | 
20 May 2020
Research article |  | 20 May 2020

Systematic error analysis of heavy-precipitation-event prediction using a 30-year hindcast dataset

Matteo Ponzano, Bruno Joly, Laurent Descamps, and Philippe Arbogast

Viewed

Total article views: 2,069 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,514 498 57 2,069 57 48
  • HTML: 1,514
  • PDF: 498
  • XML: 57
  • Total: 2,069
  • BibTeX: 57
  • EndNote: 48
Views and downloads (calculated since 25 Sep 2019)
Cumulative views and downloads (calculated since 25 Sep 2019)

Viewed (geographical distribution)

Total article views: 2,069 (including HTML, PDF, and XML) Thereof 1,807 with geography defined and 262 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 16 Apr 2024
Download
Short summary
We assess a methodology to evaluate and improve intense precipitation forecasting in the southeastern French region. This methodology is based on the use of a 30-year dataset of past forecasts which are analysed using a spatial verification approach. We found that precipitation forecasting is qualitatively driven by the deep-convection parametrization. Locally the model is able to reproduce the distribution of spatially integrated rainfall patterns of the most intense precipitation.
Altmetrics
Final-revised paper
Preprint