Signatures of A universal spectrum for atmospheric interannual variability in rainfall time series over the Indian region

Abstract

AbstractA recently developed non‐deterministic cell dynamic system model for atmospheric flows is summarized in this paper. The model predicts quantum‐like mechanics for atmospheric flows with inherent long‐range spatiotemporal correlations, now identified as signatures of self‐organized criticality or deterministic chaos. The model enables quantification of the power spectrum of temporal fluctuations of atmospheric flows in terms of the universal and unique characteristics of the statistical normal distribution. The model predictions are in agreement with continuous periodogram analysis of three sets each of 30 years (1871–1900, 1901–1930, 1956–1985) and one set of 25 years (1931–1955) summer monsoon rainfall time series for 29 meteorological subdivisions in the Indian region. The important results of the present study are as follows. (i) The power spectrum of the temporal fluctuations of rainfall follows the universal inverse power law form of the statistical normal distribution, with the square of the eddy amplitude representing the eddy probability density corresponding to the normalized standard deviation t equal to (logλlogλ50)‐1; where λ is the period length in years and λ50 the period up to which the cumulative percentage contribution to total variance is equal to 50 and t=0. (ii) Periodicities in rainfall up to 3–4 years contribute to as much as 50 per cent of the total variance.A universal spectrum for interannual variability in summer monsoon rainfall indicates predictability of the overall pattern of rainfall fluctuations. A relatively recent and short period rainfall time series, such as the 30‐year period 1956–1985 in this study, enables identification of the universal structure of atmospheric variability. Further, short period fluctuations that are major contributors to interannual variability can be identified accurately in the 30‐year data sets and provide means for estimating the near future (up to 4 years) rainfall variation.