Advances in Statistical Climatology, Meteorology and Oceanography
Advances in Statistical Climatology, Meteorology and Oceanography
ASCMO
Articles | Volume 5, issue 1
Articles | Volume 5, issue 1
https://doi.org/10.5194/ascmo-5-1-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ascmo-5-1-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 5, issue 1
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

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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.
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