Articles | Volume 21, issue 12
Nat. Hazards Earth Syst. Sci., 21, 3679–3691, 2021
https://doi.org/10.5194/nhess-21-3679-2021

Special issue: Recent advances in drought and water scarcity monitoring,...

Nat. Hazards Earth Syst. Sci., 21, 3679–3691, 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

Data sets

The Canadian Earth System Model Large Ensembles Environment and Climate Change Canada https://open.canada.ca/data/en/dataset/aa7b6823-fd1e-49ff-a6fb-68076a4a477c

CRCM5-LE ClimEx project https://climex-data.srv.lrz.de/Public/

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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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