A study of the impact of a total solar eclipse (TSE) on surface atmospheric electricity was made using observations of surface electrical potential gradient, conductivity, and boundary layer parameters recorded during the TSE of February 16, 1980, and on a control day at Raichur. The study showed that with the progressing of the eclipse, as a consequence of inhibited convection, the responses of turbulent mixing in the boundary layer near the ground exhibited diminution and subsequent restoration, respectively. During the next 45 min after the totality, when the surface layer remained stably stratified, the diminution in the potential gradient and the increase in the conductivity was maximum; this was about 60% and 200%, respectively, of their corresponding control day values. This result is in very good agreement with most earlier studies of solar eclipses. The study of the impact of the TSE during 3–4 hours of posteclipse showed significant cooling (∼3°C) of the entire surface air layer and a considerable drop in wind speed over the stretch (1130 km×120 km) of the totality‐occupied land region. This significant and systematic phenomenon was responsible for setting up a land‐sea breezelike circulation, that is, subsidence/downward air motion over the totality‐occupied land region and upward over the noneclipsed land across the totality stretch. This resulted in a considerable aerosol‐induced reduction in conductivity and about 5 to 8 times increase in potential gradient during the 3–4 hours of posteclipse. This response of the atmospheric electricity parameters was unlike that observed on the normal days.

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A 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 19561985) and one set of 25 years 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 (log I/log &) -1; where 1 is the period length in years and I,, the period up to which the cumulative percentage contribution to total variance is equal to 50 and t = O .(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 19561985 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. KEY WORDS Self-organized criticality Deterministic chaos Universal spectrum for rainfall variability Interannual variability of rainfall

Land-ocean contrasts in the lightning activity over Indian land and two surrounding oceanic regions viz. Arabian Sea and Bay of Bengal have been studied. Satellite-based lightning flash data for 5-year (1998-2002) period have been used. The study revealed that lightning activity over Bay of Bengal was three times higher than that over Arabian Sea and 9.3 times lower than that over land. The bimodal distribution is seen over Arabian Sea (peaks in April and November), and land (peaks in May and September). A unimodal distribution is observed over Bay of Bengal with peak in May. The maximum activity over Bay of Bengal occurs more at northern latitudes (28-30°N) compared with Arabian Sea (12-14°N). The land-ocean contrast is dominated by monsoon season. Comparison of lightning activity in the El Nino (2002) and La Nina year (1998)(1999)(2000)(2001) shows that the lightning activity is increased by nearly 18% over the land region and it maybe attributed to in the increase in surface air temperature during the warm phase of El Nino, land sea breeze circulations and difference in the continental and the oceanic convection.

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 Niño–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 criticali ty as intrinsic to quantum‐like mechanics governing atmospheric flow dynamics. Identification of self‐organized 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.