Signatures of a Universal Spectrum for Atmospheric Interannual Variability in Coads Surface Pressure Time Series

Abstract

Annual and seasonal mean global surface pressure time series for the 25 years 1964-1988 obtained from the Comprehensive Ocean Atmosphere Data Set (COADS) were subjected to quasi-continuous periodogram spectral analysis. Periodogram estimates are summarized in the following: (i) the atmospheric interannual variability exhibits a broadband (eddy continuum) structure; (ii) the spectra follow the universal inverse power-law form of the statistical normal distribution; (ii) periodicities up to 5 years contribute to as much as 50 per cent of the total variance; (v) the high-and low-frequency El Niiio-Southern Oscillation (ENSO) cycles of respective periodicities 3-4 years and 4-8 years and interdecadal oscillations are present in all the data sets.The inverse power-law form for power spectra is ubiquitous to real-world dynamical systems and is identified as a signature of self-organized criticality or deterministic chaos.The above results are consistent with a recently developed cell dynamical system model for atmospheric flows, which predicts self-organized criticality as intrinsic to quantum-like mechanics governing atmospheric flow dynamics. Identification of selforganized criticality in annual and seasonal mean surface pressure fluctuations and its unique quantification implies predictability of the total pattern of fluctuations. A universal spectrum for interannual variability rules out linear trends in atmospheric surface pressure patterns.

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

“…8) consistent with model prediction of quantum-like chaos, i.e., variance or square of eddy amplitude represents the probability distribution, a signature of quantum systems. Universal spectrum for inter-annual variability have been reported in the following meteorological parameters: (i) rainfall time series over the Indian Region (Selvam et al, 1992) (ii) rainfall time series over India and the United Kingdom (iii) COADS global air and sea surface temperatures (Selvam and Joshi, 1995) (iv) interannual variability in COADS surface pressure time series (Selvam et al, 1996) (v) interannual variability in some disparate climatic regimes (Selvam and Fadnavis, 1998) (vi) global mean monthly temperature anomalies (Selvam, 2010. The model predicted and observed universal spectrum for inter-annual variability rules out linear secular trends in annual rainfall over Indian and USA regions. Atmospheric energy input related to global warming results in intensification of fluctuations of all scales and is manifested immediately in high frequency fluctuations such as the increase in frequency of occurrence heavy rainfall/drought.…”