  The apparantly irregular (unpredictable) space-time fluctuations in
atmospheric flows ranging from climate (thousands of kilometers - years) to
turbulence (millimeters - seconds) exhibit the universal symmetry of
self-similarity. Self-similarity or scale invariance implies long-range
spatiotemporal correlations and is manifested in atmospheric flows as the
fractal geometry to spatial pattern concomitant with inverse power-law form for
power spectra of temporal fluctuations. Long-range spatiotemporal correlations
are ubiquitous to dynamical systems in nature and are identified as signatures
of self-organized criticality. Standard meteorological theory cannot explain
satisfactorily the observed self-organized criticality. Numerical models for
simulation and prediction of atmospheric flows are subject to deterministic
chaos and give unrealistic solutions. Deterministic chaos is a direct
consequence of round-off error growth in iterative computations. Round-off
error of finite precision computations doubles on an average at each step of
iterative computations. Round-off error will propagate to the mainstream
computation and give unrealistic solutions in numerical weather prediction
(NWP) and climate models which incorporate thousands of iterative computations
in long-term numerical integration schemes. A recently developed
non-deterministic cell dynamical system model for atmospheric flows predicts
the observed self-organized criticality as intrinsic to quantumlike mechanics
governing flow dynamics.
