Identification of Self-Organized Criticality in Atmospheric Low Frequency Variability

Joshi, Ranjan; Selvam, A. M.

doi:10.1142/s0218348x99000414

Cited by 16 publications

(4 citation statements)

References 9 publications

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“…LogT 50 also represents the mean value for the r. m. s. eddy fluctuations and is consistent with the concept of the mean level represented by r. m. s. eddy fluctuations. Spectra of time series of meteorological parameters when plotted as cumulative percentage contribution to total variance versus normalized deviation t have been shown to follow closely the model predicted universal spectrum (Selvam and Fadnavis, 1998;Joshi and Selvam, 1999) which is identified as a signature of quantum-like chaos. The model predicted T 50 is obtained from Eq.…”

Section: Logarithmic Spiral Pattern Underlying Fractal Fluctuationsmentioning

confidence: 63%

Universal Inverse Power-Law Distribution for Fractal Fluctuations in Dynamical Systems: Applications for Predictability of Inter-Annual Variability of Indian and USA Region Rainfall

Selvam

2016

Pure Appl. Geophys.

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Dynamical systems in nature exhibit self-similar fractal space-time fluctuations on all scales indicating long-range correlations and therefore the statistical normal distribution with implicit assumption of independence, fixed mean and standard deviation cannot be used for description and quantification of fractal data sets. The author has developed a general systems theory based on classical statistical physics for fractal fluctuations which predicts the following. (i) The fractal fluctuations signify an underlying eddy continuum, the larger eddies being the integrated mean of enclosed smaller-scale fluctuations. (ii) The probability distribution of eddy amplitudes and the variance (square of eddy amplitude) spectrum of fractal fluctuations follow the universal Boltzmann inverse power law expressed as a function of the golden mean. (iii) Fractal fluctuations are signatures of quantum-like chaos since the additive amplitudes of eddies when squared represent probability densities analogous to the subatomic dynamics of quantum systems such as the photon or electron. (iv) The model predicted distribution is very close to statistical normal distribution for moderate events within two standard deviations from the mean but exhibits a fat long tail that are associated with hazardous extreme events. Continuous periodogram power spectral analyses of available GHCN annual total rainfall time series for the period 1900 to 2008 for Indian and USA stations show that the power spectra and the corresponding probability distributions follow model predicted universal inverse power law form signifying an eddy continuum structure underlying the observed inter-annual variability of rainfall. Global warming related atmospheric energy input will result in intensification of fluctuations of all scales and can be seen immediately in high frequency (shortterm) fluctuations such as devastating floods/droughts resulting from excess/deficit annual, quasi-biennial and other shorter period (years) rainfall cycles.

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Section: Logarithmic Spiral Pattern Underlying Fractal Fluctuationsmentioning

confidence: 63%

Universal Inverse Power-Law Distribution for Fractal Fluctuations in Dynamical Systems: Applications for Predictability of Inter-Annual Variability of Indian and USA Region Rainfall

Selvam

2016

Pure Appl. Geophys.

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“…eddy fluctuations. Spectra of time series of meteorological parameters when plotted as cumulative percentage contribution to total variance versus t have been shown to follow the model predicted universal spectrum (Selvam, 1987;1990;Selvam and Radhamani, 1995;Selvam and Joshi, 1995;Selvam et al, 1996;Selvam and Fadnavis, 1998;1999;Joshi and Selvam, 1999) which is identified as a signature of quantumlike chaos.…”

Section: Model Predictionsmentioning

confidence: 82%

Self-organized Criticality: A Signature of Quantum-like Chaos in Atmospheric Flows

Selvam

2017

Springer Atmospheric Sciences

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Atmospheric flows exhibit long-range spatiotemporal correlations manifested as the fractal geometry to the global cloud cover pattern concomitant with inverse power law form for power spectra of temporal fluctuations on all spacetime scales ranging from turbulence (centimetres-seconds) to climate (kilometres-years). Long-range spatiotemporal correlations are ubiquitous to dynamical systems in nature and are identified as signatures of self-organized criticality. Standard models in meteorological theory cannot explain satisfactorily the observed self-organized criticality in atmospheric flows. Mathematical models for simulation and prediction of atmospheric flows are nonlinear and do not possess analytical solutions. Finite precision computer realizations of nonlinear models give unrealistic solutions because of deterministic chaos, a direct consequence of round-off error growth in iterative numerical computations. Recent studies show that round-off error doubles on an average for each iteration of iterative computations. Round-off error propagates to the mainstream computation and gives unrealistic solutions in numerical weather prediction (NWP) and climate models, which incorporate thousands of iterative computations in longterm numerical integration schemes. An alternative non-deterministic cell dynamical system model for atmospheric flows developed by the author predicts the observed self-organized criticality as intrinsic to quantumlike mechanics governing flow dynamics. The model provides universal quantification for self-organized criticality in terms of the statistical normal distribution. Model predictions are in agreement with a majority of observed spectra of time series of several standard climatological data sets representative of disparate climatic regimes. Universal spectrum for natural climate variability rules out linear trends. Man-made greenhouse gas related atmospheric warming would result in intensification of natural climate variability, seen immediately in high frequency fluctuations such as QBO and ENSO and even shorter timescales. Model concepts and results of analyses are discussed with reference to possible prediction of climate change. Model concepts, if correct, rule out unambiguously, linear trends in climate. Climate change will only be manifested as increase or decrease in the natural variability. However, more stringent tests of model concepts and predictions are required before applications to such an important issue as climate change. The cell dynamical system model for atmospheric flows is a general systems theory applicable in general to all dynamical systems in other fields of science, such as, number theory, biology, physics and botany.

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“…But with their help one succeeds in making finer, although qualitative prognostic conclusions. For example, large Herst coefficient values (H~0.7-0.8) indicate that externally random wind speed changes are far from being random and are obviously a regular manifestation of the dynamic chaos in the turbulent atmosphere [16,19] and part of more long-term global processes of the air mass transport. The wavelet analysis data demonstrate periodic events in the wind speed changes.…”

Section: Resultsmentioning

confidence: 99%

The analysis of long-term wind speed characteristics in the Chernobyl NPP region and possible prediction of radioactive aerosol release from the Ukrytie object

Skorbun

Ogorodnikov

2010

Russ. Meteorol. Hydrol.

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Three-hour and daily mean measurements of the module of an average speed and wind gusts were analyzed over 2001-2006 in the Chernobyl NPP region using wavelet analysis and the method of the Herst normalized range. Diurnal and seasonal fluctuations are revealed, the periodicity of 8, 16, and 60 days is not well-pronounced. The derived Herst high-value coefficients (~0.7-0.8) against the background of well-pronounced seasonal and other fluctuations of an average wind speed are indicative of the fact that its temporal variability is far from being random. The analysis is performed to predict the concentration of radioactive aerosols released from the Ukrytie object (the damaged unit 4 of the ChNPP), whose changes correlate with the wind speed.

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Identification of Self-Organized Criticality in Atmospheric Low Frequency Variability

Cited by 16 publications

References 9 publications

Universal Inverse Power-Law Distribution for Fractal Fluctuations in Dynamical Systems: Applications for Predictability of Inter-Annual Variability of Indian and USA Region Rainfall

Universal Inverse Power-Law Distribution for Fractal Fluctuations in Dynamical Systems: Applications for Predictability of Inter-Annual Variability of Indian and USA Region Rainfall

Self-organized Criticality: A Signature of Quantum-like Chaos in Atmospheric Flows

The analysis of long-term wind speed characteristics in the Chernobyl NPP region and possible prediction of radioactive aerosol release from the Ukrytie object

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