期刊
NATURE CLIMATE CHANGE
卷 10, 期 4, 页码 277-+出版社
NATURE RESEARCH
DOI: 10.1038/s41558-020-0731-2
关键词
-
资金
- US National Science Foundation
- National Oceanic and Atmospheric Administration
- National Aeronautics and Space Administration
- Department of Energy
- National Center for Atmospheric Research
- National Science Foundation [1852977]
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据