Use of AI and ML can drive new knowledge about how the Earth system works

Three recently published articles involving Digital Futures Faculty members Georgia Destouni, Zahra Kalantari and Carla Ferreira show how AI and Machine Learning use can drive new knowledge about how the Earth system works and how climate extremes (in these cases, drought) can be predicted around Sweden and the world.

ChatGPT in Hydrology and Earth Sciences: Opportunities, Prospects and Concerns, Foroumandi E, Moradkhani H, Sanchez-Vila X, Singha K, Castelletti A, Destouni G, Water Resources Research, 2023 (in press). https://doi.org/10.1029/2023WR036288

 

 

Predicting agricultural drought indicators: ML approaches across wide-ranging climate and land use conditions, Kan J-C, Ferreira CSS, Destouni G, Haozhi P, Vieira Passos M, Barquet K, Kalantari Z, Ecological Indicators, 154, 110524, 2023. https://doi.org/10.1016/j.ecolind.2023.110524

 

 

Contrasting drought propagation into the terrestrial water cycle between dry and wet regions, Li W., Reichstein M., O, S., May C., Destouni G., Migliavacca M., Kraft B., Weber U., Orth R., Earth’s Future, 11, e2022EF003441, 2023. https://doi.org/10.1029/2022EF003441

 

 

 

 

Find out more in this article on One Earth – Global patterns in water flux partitioning: Irrigated and rainfed agriculture drives asymmetrical flux to vegetation over runoff Graphical