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Nonlinear Dynamics and Chaos: Applications in Meteorology and Atmospheric Physics

  • Amujuri Mary SelvamEmail author
Chapter
Part of the Springer Atmospheric Sciences book series (SPRINGERATMO)

Abstract

Atmospheric flows, an example of turbulent fluid flows, exhibit fractal fluctuations of all space-time scales ranging from turbulence scale of mm-sec to climate scales of thousands of kilometres/years and may be visualized as a nested continuum of weather cycles or periodicities, the smaller cycles existing as intrinsic fine structure of the larger cycles. The power spectra of fractal fluctuations exhibit inverse power-law form signifying long-range correlations identified as self-organized criticality and are ubiquitous to dynamical systems in nature and is manifested as sensitive dependence on initial condition or ‘deterministic chaos’ in finite precision computer realizations of nonlinear mathematical models of real-world dynamical systems such as atmospheric flows. Though the self-similar nature of atmospheric flows have been widely documented and discussed during the last three to four decades, the exact physical mechanism is not yet identified. There now exists an urgent need to develop and incorporate basic physical concepts of nonlinear dynamics and chaos into classical meteorological theory for more realistic simulation and prediction of weather and climate. A historical review of nonlinear dynamics and chaos in meteorology and atmospheric physics is summarized in this chapter.

Keywords

Nonlinear dynamics and chaos Weather and climate prediction Fractals Self-organized criticality Long-range correlations Inverse power law 

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© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Ministry of Earth Sciences, Government of IndiaRetired from IITMPuneIndia

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