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SIGNATURES OF A UNIVERSAL SPECTRUM FOR ATMOSPHERIC INTERANNUAL VARIABILITY IN COADS SURFACE PRESSURE TIME SERIES

✍ Scribed by SELVAM, A. M.; PETHKAR, J. S.; KULKARNI, M. K.; VIJAYAKUMAR, R.


Publisher
John Wiley and Sons
Year
1996
Tongue
English
Weight
701 KB
Volume
16
Category
Article
ISSN
0899-8418

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✦ Synopsis


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.


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Universal spectrum for interannual varia
✍ A. Mary Selvam; R. R. Joshi 📂 Article 📅 1995 🏛 John Wiley and Sons 🌐 English ⚖ 648 KB

## Abstract Continuous periodogram spectral analyses of 28 years (1961–1988) of seasonal (September‐November) mean COADS global surface (air and sea) temperature time‐series show that the power spectra follow the universal inverse power law form of the statistical normal distribution. An inverse po