文章基本信息

标题：Decadal predictability without ocean dynamics
本地全文：下载
作者：Abhishekh Srivastava ; Timothy DelSole
期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2017
卷号：114
期号：9
页码：2177-2182
DOI：10.1073/pnas.1614085114
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：This paper shows that the most predictable components of internal variability in coupled atmosphere–ocean models are remarkably similar to the most predictable components of climate models without interactive ocean dynamics (i.e., models whose ocean is represented by a 50-m-deep slab ocean mixed layer with no interactive currents). Furthermore, a linear regression model derived solely from dynamical model output can skillfully predict observed anomalies in these components at least a year or two in advance, indicating that these model-derived components and associated linear dynamics are realistic. These results suggest that interactive ocean circulation is not essential for the existence of multiyear predictability previously identified in coupled models and observations.
关键词：decadal prediction ; decadal predictability ; average predictability time ; CMIP