Articles | Volume 23, issue 12
https://doi.org/10.5194/nhess-23-3651-2023
https://doi.org/10.5194/nhess-23-3651-2023
Research article
 | 
29 Nov 2023
Research article |  | 29 Nov 2023

Forecasting large hail and lightning using additive logistic regression models and the ECMWF reforecasts

Francesco Battaglioli, Pieter Groenemeijer, Ivan Tsonevsky, and Tomàš Púčik

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Latest update: 08 Nov 2024
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Short summary
Probabilistic models for lightning and large hail were developed across Europe using lightning observations and hail reports. These models accurately predict the occurrence of lightning and large hail several days in advance. In addition, the hail model was shown to perform significantly better than the state-of-the-art forecasting methods. These results suggest that the models developed in this study may help improve forecasting of convective hazards and eventually limit the associated risks.
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