The monitoring of natural electromagnetic activity in the extremely low frequency range is considered as a means of obtaining global information on the lightning activity and other parameters concerning the state of the Earth's atmosphere. In this sense, the possible application of the study of Schumann resonances (SRs) to environmental monitoring systems has already been proposed in the recent past. However, the usual lack of details existing in the literature concerning the process of extracting SR parameters hinders the development of global networks intended for environmental purposes. In this paper, the methodology used to extract SR information from data measured at the Sierra Nevada extremely low frequency station, Spain, is described in detail. The process is split in three main parts: the determination of the amplitude spectrum from the low-amplitude noisy signal measured, the anthropogenic noise elimination and, finally, the calculation of an analytical function to fit the filtered amplitude spectrum from which SR parameters can be precisely defined. Some different options in the method are considered, and their effect on the SR results has been quantified. Significant differences in the final results have been observed in some of the options considered. As a conclusion of this work, it becomes clear that, if data from different research groups are to be shared and quantitatively compared, a standardization of the process is required or, at least, some details on the station and this process should be provided together with the SR results.

We present a study of the Schumann resonance (SR) regular variations (March 2013–February 2017) using the ground‐based magnetometers from the Sierra Nevada station, Spain (37°02′N, 3°19′W). The study is based on the fitting parameters obtained by the Lorentzian fit, calculated for each 10‐min interval record, namely, peak amplitudes, peak frequencies, width of the resonances, and the power spectrum integral for the first three SR modes. We consider three time‐scales in the study: seasonal, monthly, and daily variations. The processed data collected by the Sierra Nevada station are also made public with this work. The general characteristics of the long‐term evolution of the SR are confirmed, but discrepancies appear that require further study comparing recent measurements from different stations. Signatures of the influences of the El Niño phenomenon and the solar cycle to SR have been found.

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