Stochastic modeling of decadal variability in ocean gyres

被引:46
|
作者
Kondrashov, D. [1 ,2 ]
Berloff, P. [3 ]
机构
[1] Univ Calif Los Angeles, Dept Atmospher & Ocean Sci, Los Angeles, CA 90095 USA
[2] Univ Calif Los Angeles, Inst Geophys & Planetary Phys, Los Angeles, CA 90024 USA
[3] Univ London Imperial Coll Sci Technol & Med, Dept Math, London, England
基金
美国国家科学基金会;
关键词
low-order inverse modeling; large-scale oceanic variability; multilayer stochastic closure; stochastic parameterization; small scales; empirical model reduction; LOW-FREQUENCY VARIABILITY; NONLINEAR-REGRESSION MODELS; SINGULAR-SPECTRUM ANALYSIS; MADDEN-JULIAN OSCILLATION; SEA-SURFACE TEMPERATURE; LARGE-SCALE; KUROSHIO EXTENSION; MESOSCALE EDDIES; SOUTHERN-OCEAN; TIME-SERIES;
D O I
10.1002/2014GL062871
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Decadal large-scale low-frequency variability of the ocean circulation due to its nonlinear dynamics remains a big challenge for theoretical understanding and practical ocean modeling. This paper presents a novel fully data driven approach that addresses this challenge. Proposed is non-Markovian low-order methodology with stochastic closure and use of mode decomposition by multichannel Singular Spectrum Analysis. The multilayer stochastic linear model is obtained from the coarse-grained eddy-resolving ocean model solution, and with high accuracy it reproduces the main statistical properties of the decadal variability. The proposed methodology does not depend on the governing fluid dynamics equations and geometry of the problem, and it can be extended to other ocean models and ultimately to the real data.
引用
收藏
页码:1543 / 1553
页数:11
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