气候变化领域集成服务门户(CCPortal): Linear dynamical modes as new variables for data-driven ENSO forecast

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DOI	10.1007/s00382-018-4255-7
	Linear dynamical modes as new variables for data-driven ENSO forecast
	Gavrilov A.; Seleznev A.; Mukhin D.; Loskutov E.; Feigin A.; Kurths J.
发表日期	2019
ISSN	0930-7575
起始页码	2199
结束页码	2216
卷号	52 期号:2020-03-04
英文摘要	A new data-driven model for analysis and prediction of spatially distributed time series is proposed. The model is based on a linear dynamical mode (LDM) decomposition of the observed data which is derived from a recently developed nonlinear dimensionality reduction approach. The key point of this approach is its ability to take into account simple dynamical properties of the observed system by means of revealing the system’s dominant time scales. The LDMs are used as new variables for empirical construction of a nonlinear stochastic evolution operator. The method is applied to the sea surface temperature anomaly field in the tropical belt where the El Nino Southern Oscillation (ENSO) is the main mode of variability. The advantage of LDMs versus traditionally used empirical orthogonal function decomposition is demonstrated for this data. Specifically, it is shown that the new model has a competitive ENSO forecast skill in comparison with the other existing ENSO models. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.
英文关键词	Data dimensionality reduction; Empirical modeling; ENSO forecast; Nonlinear stochastic modeling
语种	英语
scopus关键词	climate modeling; El Nino-Southern Oscillation; empirical analysis; forecasting method; numerical model; stochasticity
来源期刊	Climate Dynamics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/146537
作者单位	Institute of Applied Physics of RAS, 46 Ul’yanov Str., Nizhny Novgorod, 603950, Russian Federation; Potsdam Institute for Climate Impact Research, Telegraphenberg A31, Potsdam, 14473, Germany
推荐引用方式 GB/T 7714	Gavrilov A.,Seleznev A.,Mukhin D.,et al. Linear dynamical modes as new variables for data-driven ENSO forecast[J],2019,52(2020-03-04).
APA	Gavrilov A.,Seleznev A.,Mukhin D.,Loskutov E.,Feigin A.,&Kurths J..(2019).Linear dynamical modes as new variables for data-driven ENSO forecast.Climate Dynamics,52(2020-03-04).
MLA	Gavrilov A.,et al."Linear dynamical modes as new variables for data-driven ENSO forecast".Climate Dynamics 52.2020-03-04(2019).