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复杂的气候风险的早期预警与集成的人工智能
Markus Reichstein1,2,3, Vitus Benson4,5,6, Jan Blunk7
1Amazon Web Services, Seattle and Santa Clara, WA and CA, USA. mreichstein@bgc-jena.mpg.de.
Nature communications
|March 16, 2025
概括
有效的预警系统 (EWS) 对于适应气候变化至关重要. 综合人工智能 (AI) 建模为多危险的EWS提供了变革性的潜力,增强了灾害风险降低和弹性.
科学领域:
- 气候科学 气候科学
- 人工智能的人工智能
- 灾害风险管理 灾害风险管理
背景情况:
- 加快气候变化增加了灾难的风险和社会压力.
- 有效的预警系统 (EWS) 对抗性和可持续发展至关重要.
- 目前的EWS在危险预测,风险沟通和决策方面面临挑战.
研究的目的:
- 探索整合人工智能 (AI) 建模的潜力,以增强EWS.
- 提出一个框架,用于开发使用AI的多危险EWS.
- 在EWS中倡导负责任的AI实践和以用户为中心的设计.
主要方法:
- 整合气象和地理空间基础模型 (FMs) 进行影响预测.
- 利用因果AI模型来提高预测准确度并避免虚假的相关性.
- 利用气候组合和生成方法进行长期的,空间解决的预测.
主要成果:
- 人工智能可以显著提高多危险EWS的能力.
- 以用户为中心的方法通过直观的界面和社区反来改善危机管理.
- 负责任的AI原则 (FATES) 对于公平和值得信赖的EWS至关重要.
结论:
- 集成的人工智能建模为开发先进的,多种危险的EWS提供了一种变革性的方法.
- 由人工智能启用的十年EWS可以支持积极的气候适应.
- 伦理考虑和社区参与对于有效的人工智能驱动的EWS至关重要.
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