Abstract

Abstract. Atmospheric dynamics are described by a set of partial differential equations yielding an infinite-dimensional phase space. However, the actual trajectories followed by the system appear to be constrained to a finite-dimensional phase space, i.e. a strange attractor. The dynamical properties of this attractor are difficult to determine due to the complex nature of atmospheric motions. A first step to simplify the problem is to focus on observables which affect – or are linked to phenomena which affect – human welfare and activities, such as sea-level pressure, 2 m temperature, and precipitation frequency. We make use of recent advances in dynamical systems theory to estimate two instantaneous dynamical properties of the above fields for the Northern Hemisphere: local dimension and persistence. We then use these metrics to characterize the seasonality of the different fields and their interplay. We further analyse the large-scale anomaly patterns corresponding to phase-space extremes – namely time steps at which the fields display extremes in their instantaneous dynamical properties. The analysis is based on the NCEP/NCAR reanalysis data, over the period 1948–2013. The results show that (i) despite the high dimensionality of atmospheric dynamics, the Northern Hemisphere sea-level pressure and temperature fields can on average be described by roughly 20 degrees of freedom; (ii) the precipitation field has a higher dimensionality; and (iii) the seasonal forcing modulates the variability of the dynamical indicators and affects the occurrence of phase-space extremes. We further identify a number of robust correlations between the dynamical properties of the different variables.

Highlights

  • Atmospheric motions are governed by a web of complex interactions among the different components of the earth system (Charney, 1947)

  • In this study we present a novel analysis based on d and θ computed for the whole Northern Hemisphere (NH)

  • The attractor of a dynamical system is a geometrical object defined in the space hosting all the possible states of the system (Milnor, 1985)

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Summary

Introduction

Atmospheric motions are governed by a web of complex interactions among the different components of the earth system (Charney, 1947). In a few words (see “Methodology and data” for the details), the recurrences of a state ζ of a chaotic dynamical system of arbitrary dimension have a universal asymptotic distribution in the limit of infinite recurrences The parameters of this distribution are linked to the instantaneous dimension d(ζ ) and to another important dynamical quantity, namely the inverse of the average persistence time of the trajectory around ζ (Freitas et al, 2012). Estimating these parameters via Poincaré recurrences is easier than with the box counting algorithms because the method avoids altogether computations in scale space.

Methodology and data
Local dimensions
Local persistence
Dynamical properties of individual observables
Cross-analysis of the dynamical properties
Conclusions
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