Synthesis of natural electric and magnetic Time‐series using Inter‐station transfer functions and time‐series from a Neighboring site (STIN): Applications for processing MT data

Abstract

AbstractSynthesis of natural electric and magnetic Time series using Interstation transfer functions and time series from a Neighboring site (STIN) is a new approach for recovering natural electric and magnetic fields and reduce the influence of anthropogenic noise. The proposed approach modifies the windows of the local electric and magnetic time series that are affected by noise with time series resulted from modifying the spectra of the magnetic time series from a neighboring site with the interstation transfer functions between the local and neighboring sites. The STIN method was tested with artificially contaminated electric and magnetic time series. Comparison between STIN‐corrected time series and original noncontaminated time series shows high similarity, both in the time and frequency domains. Differences were quantified using the normalized root‐mean‐square error, the correlation coefficient, and the signal‐to‐noise ratio. The STIN method was also applied to two sites affected by unconstrained anthropogenic noise, thus demonstrating the ability and accuracy of STIN in synthesizing natural electric and magnetic fields and reducing the influence of anthropogenic noise. The synthesized time series provided by STIN show the method to be valuable for magnetotelluric (MT) geophysical applications, by increasing the reliability when constrains the MT impedance tensor and by reducing the scatter of data points when the time series are affected by noise, particularly for longer periods. As STIN is based on interstation transfer functions, the electric and magnetic time series can be treated independently, enabling computation of the MT impedance tensor even when the electric and magnetic time series of the local site were recorded at different times.