Natural Hazards and Earth System Sciences
Natural Hazards and Earth System Sciences
NHESS
Articles | Volume 22, issue 2
Articles | Volume 22, issue 2
https://doi.org/10.5194/nhess-22-577-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-22-577-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 22, issue 2
Research article
 | 
25 Feb 2022
Research article |  | 25 Feb 2022

Nowcasting thunderstorm hazards using machine learning: the impact of data sources on performance

Jussi Leinonen, Ulrich Hamann, Urs Germann, and John R. Mecikalski

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Short summary
We evaluate the usefulness of different data sources and variables to the short-term prediction (nowcasting) of severe thunderstorms using machine learning. Machine-learning models are trained with data from weather radars, satellite images, lightning detection and weather forecasts and with terrain elevation data. We analyze the benefits provided by each of the data sources to predicting hazards (heavy precipitation, lightning and hail) caused by the thunderstorms.
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