Uncertainty Analysis in Multi‐Sector Systems: Considerations for Risk Analysis, Projection, and Planning for Complex Systems
Uncertainty Analysis in Multi‐Sector Systems: Considerations for Risk Analysis, Projection, and Planning for Complex Systems
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多部门系统中的不确定性分析：复杂系统风险分析、预测和规划的考虑因素
DOI：
10.1029/2021ef002644
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
B. Lee
中科院分区：
文献类型：
--
作者：
Vivek Srikrishnan;David C. Lafferty;T. Wong;J. Lamontagne;J. Quinn;Sanjib Sharma;Nusrat Molla;J. Herman;R. Sriver;Jennifer Morris;B. Lee
多部门系统的模拟模型越来越多地用于了解社会对气候和经济冲击和变化的适应能力。然而，多部门系统也受到许多不确定性的影响，这些不确定性阻碍了直接应用模拟模型进行预测和规划，特别是在将过去的行为外推到非平稳的未来时。最近的研究开发了一系列方法来描述、属性和量化单部门和多部门系统的这些不确定性。在这里，我们回顾了充分量化多部门模型中所有不确定性及其在不同分析阶段出现的与政策设计的相互作用的理想目标的挑战和复杂性：(a)推理和模型校准；(b)预测未来的结果；(c)风险机制的情景发现和识别。我们还确定了潜在的方法和研究机会，以帮助导航复杂系统的不确定性分析中固有的权衡。在本次讨论中，我们提供了不确定性类型的分类，并讨论了模型耦合框架，以支持多部门动力学（MSD）研究的跨学科合作。最后，我们总结了最佳实践的建议，以确保MSD研究可以适当地考虑潜在的不确定性。
Simulation models of multi‐sector systems are increasingly used to understand societal resilience to climate and economic shocks and change. However, multi‐sector systems are also subject to numerous uncertainties that prevent the direct application of simulation models for prediction and planning, particularly when extrapolating past behavior to a nonstationary future. Recent studies have developed a combination of methods to characterize, attribute, and quantify these uncertainties for both single‐ and multi‐sector systems. Here, we review challenges and complications to the idealized goal of fully quantifying all uncertainties in a multi‐sector model and their interactions with policy design as they emerge at different stages of analysis: (a) inference and model calibration; (b) projecting future outcomes; and (c) scenario discovery and identification of risk regimes. We also identify potential methods and research opportunities to help navigate the tradeoffs inherent in uncertainty analyses for complex systems. During this discussion, we provide a classification of uncertainty types and discuss model coupling frameworks to support interdisciplinary collaboration on multi‐sector dynamics (MSD) research. Finally, we conclude with recommendations for best practices to ensure that MSD research can be properly contextualized with respect to the underlying uncertainties.
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DOI：
10.1029/2020ef001970
发表时间：
2021-08
期刊：
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影响因子：
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作者：
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影响因子：
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发表时间：
2003-08
期刊：
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影响因子：
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作者：
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