系统性风险:跨学科和跨学科科学的机会,以提高社会性
Jana Sillmann1,2, Alessio Ciullo3, Christian L E Franzke4,5
1Research Unit for Sustainability and Climate Risks, University of Hamburg, Hamburg, Germany.
iScience
|January 16, 2026
概括
全球变暖通过气候冲击扩大了系统性风险. 跨学科的协作和先进的建模,包括人工智能,对于理解和管理这些复杂的,跨系统的级联影响至关重要.
科学领域:
- 环境科学 环境科学
- 风险管理 风险管理
- 跨学科研究 跨学科研究
背景情况:
- 全球变暖通过气候相关冲击加剧了系统性风险.
- 极端天气事件会在各个部门引发级联和复合影响.
- 了解和管理系统性风险需要采用综合方法.
研究的目的:
- 总结系统风险及其驱动因素建模方面的科学进展.
- 为风险管理展示跨学科和跨学科的合作.
- 为风险评估提供利用多种数据源的例子.
主要方法:
- 审查对系统风险建模的聚焦集合的科学贡献.
- 整合当地知识,部门数据和人工智能的例子.
- 对理解气候相关系统性风险的建模方法的分析.
主要成果:
- 介绍了建模系统风险驱动因素的科学进展.
- 强调了跨学科和跨学科合作的有效策略.
- 展示使用当地知识,部门数据和人工智能可以提高风险理解.
结论:
- 跨学科和跨学科的合作对于管理扩大系统性风险至关重要.
- 采用各种数据的先进建模技术,提高了对系统风险的理解.
- 需要积极的管理策略来应对气候驱动的系统性风险.
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