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<p>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.</p>

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Artificial intelligence for modeling and understanding extreme weather and climate events

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年2月24日

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  • Gustau Camps-Valls,
  • Miguel-Ángel Fernández-Torres,
  • Kai-Hendrik Cohrs,
  • Adrian Höhl,
  • Andrea Castelletti,
  • Aytac Pacal,
  • Claire Robin,
  • Francesco Martinuzzi,
  • Ioannis Papoutsis,
  • Ioannis Prapas,
  • Jorge Pérez-Aracil,
  • Katja Weigel,
  • Maria Gonzalez-Calabuig,
  • Markus Reichstein,
  • Martin Rabel,
  • Matteo Giuliani,
  • Miguel D. Mahecha,
  • Oana-Iuliana Popescu,
  • Oscar J. Pellicer-Valero,
  • Said Ouala,
  • Sancho Salcedo-Sanz,
  • Sebastian Sippel,
  • Spyros Kondylatos,
  • Tamara Happé,
  • Tristan Williams

摘要

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.