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Artificial intelligence for modeling and understanding extreme weather and climate events

Author

Listed:
  • Gustau Camps-Valls

    (Universitat de València)

  • Miguel-Ángel Fernández-Torres

    (Universitat de València)

  • Kai-Hendrik Cohrs

    (Universitat de València)

  • Adrian Höhl

    (Technical University of Munich)

  • Andrea Castelletti

    (Politecnico di Milano
    Centro Euro-Mediterraneo sui Cambiamenti Climatici)

  • Aytac Pacal

    (Institut für Physik der Atmosphäre
    Institute of Environmental Physics (IUP))

  • Claire Robin

    (Max Planck Institute of Biogeochemistry
    ELLIS Unit Jena)

  • Francesco Martinuzzi

    (Leipzig University
    Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI))

  • Ioannis Papoutsis

    (National Technical University of Athens
    National Observatory of Athens
    Archimedes/Athena Research Center)

  • Ioannis Prapas

    (Universitat de València
    National Technical University of Athens
    National Observatory of Athens)

  • Jorge Pérez-Aracil

    (Universidad de Alcalá)

  • Katja Weigel

    (Institut für Physik der Atmosphäre
    Institute of Environmental Physics (IUP))

  • Maria Gonzalez-Calabuig

    (Universitat de València)

  • Markus Reichstein

    (Max Planck Institute of Biogeochemistry
    ELLIS Unit Jena)

  • Martin Rabel

    (Institute for Data Science)

  • Matteo Giuliani

    (Politecnico di Milano)

  • Miguel D. Mahecha

    (Leipzig University
    Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI))

  • Oana-Iuliana Popescu

    (Institute for Data Science)

  • Oscar J. Pellicer-Valero

    (Universitat de València)

  • Said Ouala

    (UMR CNRS 6285 & INRIA team odyssey)

  • Sancho Salcedo-Sanz

    (Universidad de Alcalá)

  • Sebastian Sippel

    (Leipzig University)

  • Spyros Kondylatos

    (Universitat de València
    National Technical University of Athens
    National Observatory of Athens)

  • Tamara Happé

    (VU Amsterdam)

  • Tristan Williams

    (Universitat de València)

Abstract

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.

Suggested Citation

  • Gustau Camps-Valls & Miguel-Ángel Fernández-Torres & Kai-Hendrik Cohrs & Adrian Höhl & Andrea Castelletti & Aytac Pacal & Claire Robin & Francesco Martinuzzi & Ioannis Papoutsis & Ioannis Prapas & Jor, 2025. "Artificial intelligence for modeling and understanding extreme weather and climate events," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-56573-8
    DOI: 10.1038/s41467-025-56573-8
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    References listed on IDEAS

    as
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