DOI: 10.1007/s00382-017-3939-8
Scopus记录号: 2-s2.0-85031430080
论文题名: Predictability in a changing climate
作者: DelSole T. ; Tippett M.K.
刊名: Climate Dynamics
ISSN: 9307575
出版年: 2018
卷: 51, 期: 2018-01-02 起始页码: 531
结束页码: 545
语种: 英语
英文关键词: Information theory
; Predictability
Scopus关键词: climate change
; climate prediction
; climatology
; conceptual framework
; observational method
; theoretical study
英文摘要: The standard framework of predictability defines a variable to be unpredictable from a set of observations if it is independent of those observations. This definition requires comparing two distributions: a forecast distribution that is conditioned on observations, and a climatological distribution that is not. However, if the system is non-stationary because of externally forced climate changes, or is characterized by a climatological distribution that is much broader than the distribution of states over the recent past, then a rigorous application of this framework gives unsatisfying answers to reasonable questions about weather and climate predictability. This paper proposes generalizations of this framework that resolves these limitations and is consistent with the definition of independence. The first generalization, which was proposed effectively by Lorenz and Leith, is to distinguish initial-value predictability from forced predictability, where the latter is defined by time variations in the climatological distribution. This paper goes a step further by introducing a new measure, called total climate predictability, that can be decomposed into a sum of previously known measures of forced and initial-value predictability, namely relative entropy and mutual information. The second generalization, called generalized predictability, provides a new approach to filtering in such a way that processes with long time scales do not contribute to predictability. This generalization is important when the system’s climatological distribution is much broader than the range of climates experienced in the recent past. These concepts are illustrated using a simple model in which all aspects of predictability can be solved exactly. © 2017, The Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/109210
Appears in Collections: 影响、适应和脆弱性 气候变化事实与影响
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作者单位: Department of Atmospheric, Oceanic, and Earth Sciences, George Mason University, Fairfax, United States; Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY, United States; Department of Meteorology, Center of Excellence for Climate Change Research, King Abdulaziz University, Jeddah, Saudi Arabia
Recommended Citation:
DelSole T.,Tippett M.K.. Predictability in a changing climate[J]. Climate Dynamics,2018-01-01,51(2018-01-02)