Natural Hazards and Earth System Sciences
Natural Hazards and Earth System Sciences
NHESS
Articles | Volume 20, issue 5
Articles | Volume 20, issue 5
https://doi.org/10.5194/nhess-20-1369-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-20-1369-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 20, issue 5
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: 2,081 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,521 500 60 2,081 57 49
  • HTML: 1,521
  • PDF: 500
  • XML: 60
  • Total: 2,081
  • BibTeX: 57
  • EndNote: 49
Views and downloads (calculated since 25 Sep 2019)
Cumulative views and downloads (calculated since 25 Sep 2019)

Viewed (geographical distribution)

Total article views: 2,081 (including HTML, PDF, and XML) Thereof 1,819 with geography defined and 262 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 25 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.
Read more
Altmetrics
Final-revised paper
Preprint