Articles | Volume 21, issue 12
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

CRCM5-LE ClimEx project

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.
Final-revised paper