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人工智能用于建模和理解极端天气和气候事件
Gustau Camps-Valls1, Miguel-Ángel Fernández-Torres2, Kai-Hendrik Cohrs2
1Image Processing Laboratory, Universitat de València, València, Spain. gustau.camps@uv.es.
Nature communications
|February 24, 2025
概括
人工智能 (AI) 增强了地球系统科学,用于预测极端气候事件. 应对数据挑战是开发可靠的人工智能的关键,以应对灾害准备和降低风险.
科学领域:
- 地球系统科学 地球系统科学
- 气候科学 气候科学
- 人工智能应用程序 人工智能应用程序
背景情况:
- 人工智能 (AI) 越来越多地被用于地球系统科学,改善了天气预报和极端事件预测等领域.
- 预测极端气候事件带来了挑战,包括杂的数据,小样本大小和有限的注释.
研究的目的:
- 审查AI在分析洪水,干旱,野火和热浪等极端气候事件中的应用.
- 突出在气候科学中需要准确,透明和可靠的AI模型.
主要方法:
- 对当前应用于极端气候事件分析的AI方法的审查.
- 讨论人工智能模型开发中的挑战,包括数据限制和实时集成.
主要成果:
- 人工智能为识别和解释极端气候事件提供了改进的能力.
- 克服数据稀缺性和确保模型可解释性对于人工智能部署至关重要.
结论:
- 开发值得信赖和可理解的AI模型对于利益相关者的采用和监管合规性至关重要.
- 跨学科的合作对于在灾难准备和风险降低方面提供实际AI解决方案至关重要.
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