Abstract
Atmospheric flows, a representative example of turbulent fluid flows, exhibit long-range spatiotemporal correlations manifested as the fractal geometry to the global cloud cover pattern concomitant with inverse power law form for spectra of temporal fluctuations. Such nonlocal connections are ubiquitous to dynamical systems in nature and are identified as signatures of self-organized criticality. Mathematical models for simulation and prediction of dynamical systems are nonlinear so that analytical solutions are not available. Finite precision computed solutions are sensitively dependent on initial conditions and give chaotic solutions, identified as deterministic chaos. Realistic mathematical modeling for simulation and prediction of atmospheric flows requires alternative theoretical concepts and analytical or error-free numerical computational techniques and therefore comes under the field of ‘General Systems research’. General systems theory for atmospheric flows visualizes the hierarchical growth of larger scale eddies from space–time integration of smaller scale eddies resulting in an atmospheric eddy continuum manifested in the self-similar fractal fluctuations of meteorological parameters. The model shows that the observed long-range spatiotemporal correlations are intrinsic to quantum-like mechanics governing fluid flows. The model concepts are independent of intrinsic characteristics of the dynamical system such as chemical, physical, electrical, etc., and gives scale-free governing equations for fluid flow characteristics.
Published Version
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