A dynamical systems characterization of atmospheric jet regimes

Messori, Gabriele; Harnik, Nili; Madonna, Erica; Lachmy, Orli; Faranda, Davide

doi:10.5194/esd-12-233-2021

Cited by 18 publications

(14 citation statements)

References 57 publications

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“…These metrics are related to the intrinsic predictability of the atmosphere and therefore to the stability (here in the context of atmospheric variability) of the flow: a highly persistent (low θ ), low‐dimensional (low d ) state will be more stable than a low‐persistence (high θ ), high‐dimensional (high d ) one (Messori et al., 2017). This approach has been applied to various atmospheric fields (e.g., Faranda et al., 2019a; Messori et al., 2021). Indeed, it has been shown that d and θ can offer a dynamical characterization of synoptic systems over several geographical regions (Faranda, Alvarez‐Castro, et al., 2017; Hochman et al., 2019; Hochman, Alpert, et al., 2020).…”

Section: Introductionmentioning

confidence: 99%

Do Atlantic‐European Weather Regimes Physically Exist?

Hochman

Messori

Quinting

et al. 2021

Geophysical Research Letters

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The subseasonal atmospheric variability in the extratropics is a key research topic within atmospheric science and of broad socioeconomic relevance (White et al., 2017). A far-reaching paradigm is that a small number of states, termed "weather regimes," can describe this variability. These are defined as recurrent or quasi-stationary states of the large-scale circulation (Hannachi et al., 2017). Weather regimes have implications for extended-range weather forecasting and in the understanding of climate variability (Merryfield et al., 2020).The concept of weather regimes was first introduced by weather forecasters in the late 1940s (Levick, 1949). A corresponding theory was developed by Charney and DeVore (1979), who hypothesized that the largescale circulation transitions between multiple equilibria states, based on a spectral model. The multiple equilibria viewpoint has been later authenticated for the barotropic case (Legras & Ghil, 1985), and in two-layer models (Yoden, 1983), yet was criticized using models with higher spectral resolution (Cehelsky & Tung, 1987). Faranda et al. (2016) argued for linking blocked regimes to unstable fixed points rather than stable equilibria. Nowadays, there is little doubt that weather regimes emerge from different statistical classifications applied to long archives (Hannachi et al., 2017). However, it is a source of debate whether these regimes represent metastable states of the atmosphere (Majda et al., 2006), or are merely useful statistical categorizations lacking physical grounding (Fereday, 2017).A variety of procedures has been used to classify weather regimes (Hannachi et al., 2017). They typically seek to define a low-dimensional phase-space reflecting the key aspects of the atmosphere's variability. A common choice is to compute the Empirical Orthogonal Functions (EOF) of the data. Clustering algorithms

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Section: Introductionmentioning

confidence: 99%

Do Atlantic‐European Weather Regimes Physically Exist?

Hochman

Messori

Quinting

et al. 2021

Geophysical Research Letters

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“…The persistence of individual states together with the local attractor dimension can be used as a dynamical proxy of the general circulation. This approach has already successfully been applied to dynamical features of the atmosphere (Faranda et al, 2017;Messori et al, 2021)), but never, to the best of our knowledge, to thermodynamic features.…”

Section: Discussionmentioning

confidence: 99%

Meridional energy transport extremes and the general circulation of NH mid-latitudes: dominant weather regimes and preferred zonal wavenumbers

Lembo

Fabiano

Gálfi

et al. 2022

Preprint

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Abstract. The extratropical meridional energy transport in the atmosphere is fundamentally intermittent in nature, having extremes large enough to affect the net seasonal transport. Here, we investigate how these extreme transports are associated with the dynamics of the atmosphere at multiple scales, from planetary to synoptic. We use ERA5 reanalysis data to perform a wavenumber decomposition of meridional energy transport in the Northern Hemisphere mid-latitudes during winter and summer. We then relate extreme transport events to atmospheric circulation anomalies and dominant weather regimes, identified by clustering 500 hPa geopotential height fields. In general, planetary-scale waves determine the strength and meridional position of the synoptic-scale baroclinic activity with their phase and amplitude, but important differences emerge between seasons. During winter, large wavenumbers (k = 2 − 3) are key drivers of the meridional energy transport extremes, and planetary and synoptic-scale transport extremes virtually never co-occur. In summer, extremes are associated with higher wavenumbers (k = 4 − 6), identified as synoptic-scale motions. We link these waves and the transport extremes to recent results on exceptionally strong and persistent co-occurring summertime heat waves across the Northern Hemisphere mid-latitudes. We show that these events are typical, in terms of dominant regime patterns associated with extremely strong meridional energy transports.

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“…Here, u and σ are parameters of the distribution which depend on the chosen ζ x , while ϑ is the extremal index: the standard measure of clustering in extreme value theory (Moloney et al, 2019). We estimate the latter using the Süveges maximum likelihood estimator (Süveges, 2007).…”

Section: Theoretical Underpinnings Of the Dynamical Systems Frameworkmentioning

confidence: 99%

“…The code to compute the three dynamical systems indicators used in this study is made freely available through the cloud storage of the Centre National de la Recherche Scientifique (CNRS) under a CC BY-NC 3.0 license: https://mycore. core-cloud.net/index.php/s/pLJw5XSYhe2ZmnZ (Faranda, 2021).…”

Section: Appendix A: Additional Figuresmentioning

confidence: 99%

Technical note: Characterising and comparing different palaeoclimates with dynamical systems theory

Messori

Faranda

2021

Clim. Past

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Abstract. Numerical climate simulations produce vast amounts of high-resolution data. This poses new challenges to the palaeoclimate community – and indeed to the broader climate community – in how to efficiently process and interpret model output. The palaeoclimate community also faces the additional challenge of having to characterise and compare a much broader range of climates than encountered in other subfields of climate science. Here we propose an analysis framework, grounded in dynamical systems theory, which may contribute to overcoming these challenges. The framework enables the characterisation of the dynamics of a given climate through a small number of metrics. These may be applied to individual climate variables or to several variables at once, and they can diagnose properties such as persistence, active number of degrees of freedom and coupling. Crucially, the metrics provide information on instantaneous states of the chosen variable(s). To illustrate the framework's applicability, we analyse three numerical simulations of mid-Holocene climates over North Africa under different boundary conditions. We find that the three simulations produce climate systems with different dynamical properties, such as persistence of the spatial precipitation patterns and coupling between precipitation and large-scale sea level pressure patterns, which are reflected in the dynamical systems metrics. We conclude that the dynamical systems framework holds significant potential for analysing palaeoclimate simulations. At the same time, an appraisal of the framework's limitations suggests that it should be viewed as a complement to more conventional analyses, rather than as a wholesale substitute.

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A dynamical systems characterization of atmospheric jet regimes

Cited by 18 publications

References 57 publications

Do Atlantic‐European Weather Regimes Physically Exist?

Do Atlantic‐European Weather Regimes Physically Exist?

Meridional energy transport extremes and the general circulation of NH mid-latitudes: dominant weather regimes and preferred zonal wavenumbers

Technical note: Characterising and comparing different palaeoclimates with dynamical systems theory

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