Highlights Most geophysical processes, including electric discharges, influence Schumann Resonance. Statistical fitting process applied to five years of Schumann Resonance data. Patterns on the classification of the Schumann Resonance compared with thunderstorm hotspots. Links established between lightning activity and statistical classification.

    Abstract The Schumann resonance is an electromagnetic phenomenon, a product of lightning activity inside the earth-ionosphere cavity. Five years of Schumann resonance records are analyzed by a novel methodology that segments the records into time intervals and finds the probability distribution that best describes each segment. Then patterns are extracted from the resulting time series and compared against known patterns of global lightning activity to further test the power of the methodology under study. The Quality of Fit indices show how over 95% of the segments analyzed are properly described by the distribution that fit them best. The relationship between global lightning activity and the number of segments identified as Gaussian emerges clearly. A link between Laplacian segments and local lightning activity is explored as well. This presents transient statistical fitting as an alternative for characterizing complex phenomena by identifying different segments with a probability distribution, then identifying circumstances that segments with the same distributions have in common. This study further validates the chosen analysis tool, showing its capacity to offer information on the activity of thunderstorms in the time segments analyzed from the Schumann resonance data. It presents an additional source of information that complements the usual techniques used to study the signal in the frequency domain.


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    Title :

    Study of the statistical footprint of lightning activity on the Schumann Resonance



    Published in:

    Advances in Space Research ; 73 , 5 ; 2387-2403


    Publication date :

    2023-11-29


    Size :

    17 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English