Stochastic modeling of decadal variability in ocean gyres. Issue 5 (4th March 2015)

• Record Type: Journal Article
• Authors: Kondrashov, D.; Berloff, P.
• Is Part Of: Geophysical research letters. Volume 42:Issue 5(2015:Mar.)
• Page Start: 1543
• Page End: 1553
• Publication Date: 2015-03-04
• Subjects: low‐order inverse modeling -- large‐scale oceanic variability -- multilayer stochastic closure -- stochastic parameterization -- small scales -- empirical model reduction; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1002/2014GL062871
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: 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. Key Points: Data‐adaptive time‐lagged basis to extract LFV modes Small scales are parameterized by memory effects and stochastic forcing Time‐lagged basis suffices for linear stochastic closure