对具有多变量输出的综合评估模型的全球敏感性分析
Leonardo Chiani1,2,3, Emanuele Borgonovo4, Elmar Plischke5
1Department of Management, Economics and Industrial Engineering, Politecnico di Milano, Milan, Italy.
Risk analysis : an official publication of the Society for Risk Analysis
|February 22, 2025
概括
本研究引入了一种分析复杂气候经济模型的新方法,改进了对排放途径的不确定性量化和灵敏度分析. 调查结果揭示了不同气候政策下不确定性的关键驱动因素.
科学领域:
- 气候科学是气候科学.
- 环境经济学环境经济学
- 计算建模计算建模
背景情况:
- 量化模型对于复杂系统的风险评估至关重要,但它们的复杂性和不确定性需要强有力的分析.
- 传统的灵敏度分析方法与这些模型中常见的多变量输出作斗争.
研究的目的:
- 在具有多变量输出的风险评估模型中开发一个结构化方法来量化不确定性和进行全球敏感性分析.
- 将这种方法应用于气候经济模型 (RICE50+),用于分析各种政策情景下的排放路径.
主要方法:
- 基于最佳运输理论的新型灵敏度测量.
- 对RICE50+模型的应用,更新了输入分布和长期预测.
- 在成本效益和成本效益 (巴黎协定) 政策架构下探讨敏感性.
主要成果:
- 在成本效益情景中确定了关键的不确定性驱动因素:排放强度和减排成本.
- 在"巴黎协定"情景中确定的主要驱动因素:气候系统的敏感性和碳强度.
- 提供了对多变量模型输出和输入重要性区域/时间变化的洞察力.
结论:
- 提出的方法有效地处理不确定性量化和综合灵敏度分析复杂的模型与多变量输出.
- 了解不同政策框架的投入的重要性对于有效的气候变化减缓和风险管理至关重要.
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