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Dynamical analysis of a reduced model for the North Atlantic Oscillation

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Quinn, C ORCID: 0000-0001-5298-5233, Harries, D and O'Kane, TJ 2021 , 'Dynamical analysis of a reduced model for the North Atlantic Oscillation' , Journal of the Atmospheric Sciences, vol. 78, no. 5 , 1647–1671 , doi: 10.1175/JAS-D-20-0282.1.

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Abstract

The dynamics of the North Atlantic Oscillation (NAO) are analyzed through a data-driven model obtained from atmospheric reanalysis data. We apply a regularized vector autoregressive clustering technique to identify recurrent and persistent states of atmospheric circulation patterns in the North Atlantic sector (20°–90°N, 110°W–0°). To analyze the dynamics associated with the resulting cluster-based models, we define a time-dependent linear delayed map with a switching sequence set a priori by the cluster affiliations at each time step. Using a method for computing the covariant Lyapunov vectors (CLVs) over various time windows, we produce sets of mixed singular vectors (for short windows) and approximate the asymptotic CLVs (for longer windows). The growth rates and alignment of the resulting time-dependent vectors are then analyzed. We find that the window chosen to compute the vectors acts as a filter on the dynamics. For short windows, the alignment and changes in growth rates are indicative of individual transitions between persistent states. For long windows, we observe an emergent annual signal manifest in the alignment of the CLVs characteristic of the observed seasonality in the NAO index. Analysis of the average finite-time dimension reveals the NAO− as the most unstable state relative to the NAO+, with persistent AR states largely stable. Our results agree with other recent theoretical and empirical studies that have shown blocking events to have less predictability than periods of enhanced zonal flow.

Item Type: Article
Authors/Creators:Quinn, C and Harries, D and O'Kane, TJ
Keywords: North Atlantic Oscillation, Lyapunov vectors, pattern detection
Journal or Publication Title: Journal of the Atmospheric Sciences
Publisher: Amer Meteorological Soc
ISSN: 0022-4928
DOI / ID Number: 10.1175/JAS-D-20-0282.1
Copyright Information:

© Copyright 2021 American Meteorological Society (AMS). For permission to reuse any portion of this Work, please contact permissions@ametsoc.org. Any use of material in this Work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act (17 U.S. Code § 107) or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC § 108) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a website or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. All AMS journals and monograph publications are registered with the Copyright Clearance Center (https://www.copyright.com). Additional details are provided in the AMS Copyright Policy statement, available on the AMS website (https://www.ametsoc.org/PUBSCopyrightPolicy).

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