Insights from Earth system model initial-condition large ensembles and future prospects
Insights from Earth system model initial-condition large ensembles and future prospects
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DOI：
10.1038/s41558-020-0731-2
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发表时间：
2020-03-30
影响因子：
30.7
通讯作者：
Ting, M.
中科院分区：
文献类型：
--
作者：
Deser, C.;Lehner, F.;Ting, M.
气候系统的内部变率使人为引起的气候变化的评估难以进行，并对气候变化预测的准确性，特别是在区域和十年尺度上的预测的准确性造成了不可缩小的限制。一个新的收集的初始条件大合奏（LE）产生的七个地球系统模型下的历史和未来的辐射强迫情景提供了新的见解的不确定性，由于内部的变化与模型的差异。这些数据加强了对气候变化风险，包括极端事件的评估，并为新方法提供了一个强有力的试验平台，旨在将强迫信号与观测记录中的内部变异分离开来。未来LEs的设计和传播所面临的机遇和挑战，包括增加空间分辨率和模式的复杂性，以及新兴的地球系统applications.Climate变化检测混淆内部的变化，但最近的初始条件大型合奏（LEs）已经开始解决这个问题。这个观点讨论了多模式LE的价值，提供它们的挑战和它们在未来气候变化研究中的作用。
Internal variability in the climate system confounds assessment of human-induced climate change and imposes irreducible limits on the accuracy of climate change projections, especially at regional and decadal scales. A new collection of initial-condition large ensembles (LEs) generated with seven Earth system models under historical and future radiative forcing scenarios provides new insights into uncertainties due to internal variability versus model differences. These data enhance the assessment of climate change risks, including extreme events, and offer a powerful testbed for new methodologies aimed at separating forced signals from internal variability in the observational record. Opportunities and challenges confronting the design and dissemination of future LEs, including increased spatial resolution and model complexity alongside emerging Earth system applications, are discussed.Climate change detection is confounded by internal variability, but recent initial-condition large ensembles (LEs) have begun addressing this issue. This Perspective discusses the value of multi-model LEs, the challenges of providing them and their role in future climate change research.