Abstract
The aim of this work was to use an Iterative Regression Analysis Method for the determination of periodicities in geophysical time series. This method gives, for every identified sine function, its three parameters and their standard deviation due to measurement errors and to the presence of adjustment residues. This feature allows to select the most important periodicities with higher amplitude/deviation ratio. The method described was applied to the analysis of the main periodicities in time series of atmospheric cosmonuclides (atmospheric carbon 14 and beryllium 10 of ice cores from Greenland and Antarctica), mean surface temperatures and indicators of atmospheric volcanic dust. During the time interval of these series, the periodicities found were compared from the point of view of possible causal associations between such phenomena as solar activity, cosmonuclide concentrations in the terrestrial atmosphere, atmospheric circulation, temperatures of the air and volcanic dust in the atmosphere.
Published Version
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