Updates on Model Hierarchies for Understanding and Simulating the Climate System: A Focus on Data‐Informed Methods and Climate Change Impacts
Updates on Model Hierarchies for Understanding and Simulating the Climate System: A Focus on Data‐Informed Methods and Climate Change Impacts
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DOI：
10.1029/2023ms003715
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发表时间：
2023-10
影响因子：
6.8
通讯作者：
Laura A. Mansfield;Aman Gupta;A. Burnett;B. Green;C. Wilka;Aditi Sheshadri
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文献类型：
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作者：
Laura A. Mansfield;Aman Gupta;A. Burnett;B. Green;C. Wilka;Aditi Sheshadri
气候模型体系包括沿不同轴的不同复杂性的模型，从优雅地描述孤立机制的理想化模型到渴望提供可用的气候预测的完全耦合的地球系统模型。在2022年举行的第二次模型层次研讨会的基础上，我们提出了自2016年第一次模型层次研讨会以来该领域的发展情况。在此期间，我们目睹了(A)在气候建模中使用机器学习和(B)在气候变化下评估风险和影响决策的气候模型的使用急剧增加。在这里，我们讨论这些不断增长的研究领域的含义，以及我们如何将它们整合到模型层次结构框架中。
The climate model hierarchy encompasses models of varying complexity along different axes, ranging from idealized models that elegantly describe isolated mechanisms to fully coupled Earth system models that aspire to provide useable climate projections. Based on the second Model Hierarchies Workshop, which took place in 2022, we present perspectives on how this field has evolved since the first Model Hierarchies Workshop in 2016. In this period, we have witnessed a dramatic increase in the use of (a) machine learning in climate modeling and (b) climate models to estimate risks and influence decision making under climate change. Here, we discuss the implications of these growing areas of research and how we expect them to become integrated into the model hierarchies framework.