Articles | Volume 21, issue 12
https://doi.org/10.5194/nhess-21-3679-2021
https://doi.org/10.5194/nhess-21-3679-2021
Research article
 | 
03 Dec 2021
Research article |  | 03 Dec 2021

Applying machine learning for drought prediction in a perfect model framework using data from a large ensemble of climate simulations

Elizaveta Felsche and Ralf Ludwig

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Latest update: 23 May 2024
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Short summary
This study applies artificial neural networks to predict drought occurrence in Munich and Lisbon, with a lead time of 1 month. An analysis of the variables that have the highest impact on the prediction is performed. The study shows that the North Atlantic Oscillation index and air pressure 1 month before the event have the highest importance for the prediction. Moreover, it shows that seasonality strongly influences the goodness of prediction for the Lisbon domain.
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