AI4Drought: AI for SCIENCE - Multi-Hazards, Compounds and


There is a clear and urgent need to deepen our understanding on the occurrence and the cascading effects of droughts. This project considers seasonal climate predictions in the Iberian peninsula (Spain and Portugal) that are projected to move towards a drier climate (Vicente-Serrano et al. 2014, Donelly et al. 2017). Using the Iberian peninsula as a case study provides an ideal opportunity for testing our ability to improve drought-related phenomena predictions and to measure their impacts.

AI4Drought provides a comprehensive approach that combines AI techniques, dynamic SPS and multiple EO-products that are appropriate for studying societal impacts (e.g., soil moisture, NDVI, lake levels or burned area) to improve our prediction capabilities and to enrich our understanding of the causes, evolution and consequences of droughts at seasonal time-scales.