Articles | Volume 28, issue 3
https://doi.org/10.5194/npg-28-467-2021
https://doi.org/10.5194/npg-28-467-2021
Research article
 | 
16 Sep 2021
Research article |  | 16 Sep 2021

Calibrated ensemble forecasts of the height of new snow using quantile regression forests and ensemble model output statistics

Guillaume Evin, Matthieu Lafaysse, Maxime Taillardat, and Michaël Zamo

Viewed

Total article views: 3,183 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,414 701 68 3,183 45 40
  • HTML: 2,414
  • PDF: 701
  • XML: 68
  • Total: 3,183
  • BibTeX: 45
  • EndNote: 40
Views and downloads (calculated since 28 Apr 2021)
Cumulative views and downloads (calculated since 28 Apr 2021)

Viewed (geographical distribution)

Total article views: 3,183 (including HTML, PDF, and XML) Thereof 3,019 with geography defined and 164 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 30 Mar 2025
Download
Short summary
Forecasting the height of new snow is essential for avalanche hazard surveys, road and ski resort management, tourism attractiveness, etc. Météo-France operates a probabilistic forecasting system using a numerical weather prediction system and a snowpack model. It provides better forecasts than direct diagnostics but exhibits significant biases. Post-processing methods can be applied to provide automatic forecasting products from this system.
Share