Artificial intelligence for modeling and understanding extreme weather and climate events

In recent years, artificial intelligence (AI) has deeply impacted various fields, including Earth system sciences, by improving weather forecasting, model emulation, parameter estimation, and the prediction of extreme events. The latter comes with specific challenges, such as developing accurate pre...

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Vydané v:Nature communications Ročník 16; číslo 1; s. 1919 - 14
Hlavní autori: Camps-Valls, Gustau, Fernández-Torres, Miguel-Ángel, Cohrs, Kai-Hendrik, Höhl, Adrian, Castelletti, Andrea, Pacal, Aytac, Robin, Claire, Martinuzzi, Francesco, Papoutsis, Ioannis, Prapas, Ioannis, Pérez-Aracil, Jorge, Weigel, Katja, Gonzalez-Calabuig, Maria, Reichstein, Markus, Rabel, Martin, Giuliani, Matteo, Mahecha, Miguel D., Popescu, Oana-Iuliana, Pellicer-Valero, Oscar J., Ouala, Said, Salcedo-Sanz, Sancho, Sippel, Sebastian, Kondylatos, Spyros, Happé, Tamara, Williams, Tristan
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London Nature Publishing Group UK 24.02.2025
Nature Publishing Group
Nature Portfolio
Predmet:
704/106
704/4111
Annotations
Artificial intelligence
Disaster management
Disasters
Drought
Emergency preparedness
Extreme weather
Floods
Heat waves
Humanities and Social Sciences
multidisciplinary
Parameter estimation
Real time
Review
Review Article
Risk management
Risk reduction
Science
Science (multidisciplinary)
Time integration
Trustworthiness
Weather
Weather forecasting
Wildfires
ISSN:2041-1723, 2041-1723
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Popis
Shrnutí:In recent years, artificial intelligence (AI) has deeply impacted various fields, including Earth system sciences, by improving weather forecasting, model emulation, parameter estimation, and the prediction of extreme events. The latter comes with specific challenges, such as developing accurate predictors from noisy, heterogeneous, small sample sizes and data with limited annotations. This paper reviews how AI is being used to analyze extreme climate events (like floods, droughts, wildfires, and heatwaves), highlighting the importance of creating accurate, transparent, and reliable AI models. We discuss the hurdles of dealing with limited data, integrating real-time information, and deploying understandable models, all crucial steps for gaining stakeholder trust and meeting regulatory needs. We provide an overview of how AI can help identify and explain extreme events more effectively, improving disaster response and communication. We emphasize the need for collaboration across different fields to create AI solutions that are practical, understandable, and trustworthy to enhance disaster readiness and risk reduction. Artificial Intelligence is transforming the study of extreme climate events like floods, droughts, and wildfires, helping to overcome challenges such as limited data and real-time integration. This review article highlights the need for transparent, reliable AI models to improve disaster response, risk communication and stakeholder trust.
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ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-025-56573-8