Articles | Volume 5, issue 1
https://doi.org/10.5194/ascmo-5-1-2019
https://doi.org/10.5194/ascmo-5-1-2019
04 Feb 2019
 | 04 Feb 2019

NWP-based lightning prediction using flexible count data regression

Thorsten Simon, Georg J. Mayr, Nikolaus Umlauf, and Achim Zeileis

Viewed

Total article views: 7,520 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
6,720 693 107 7,520 103 97
  • HTML: 6,720
  • PDF: 693
  • XML: 107
  • Total: 7,520
  • BibTeX: 103
  • EndNote: 97
Views and downloads (calculated since 04 Feb 2019)
Cumulative views and downloads (calculated since 04 Feb 2019)

Viewed (geographical distribution)

Total article views: 6,053 (including HTML, PDF, and XML) Thereof 5,874 with geography defined and 179 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 30 Mar 2025
Download
Short summary
Lightning in Alpine regions is associated with events such as thunderstorms, extreme precipitation, high wind gusts, flash floods, and debris flows. We present a statistical approach to predict lightning counts based on numerical weather predictions. Lightning counts are considered on a grid with 18 km mesh size. Skilful prediction is obtained for a forecast horizon of 5 days over complex terrain.
Share