Abstract
AbstractGalvanic distortions complicate magnetotelluric (MT) soundings. In this research, we use lightning network data to identify specific sferics in MT measurements and analyse these events on the basis of the lightning source location. Without source information, identification and removal of galvanic distortion is a fundamentally ill-posed problem, unless data are statistically decomposed into determinable and indeterminable parts. We use realistic assumptions of the earth-ionosphere waveguide propagation velocity to accurately predict the time of arrival, azimuth and amplitude for every significant sferic in our time-series data. For each sferic with large amplitude, we calculate the rotation of the electric field from the measured to the predicted arrival azimuth. This rotation of the electric field is a primary parameter of distortion. Our results demonstrate that a rudimentary model for near-surface galvanic distortion consistently fits observed electric field rotations. When local features rotate regional electric fields, then counter-rotating data to predicted arrival azimuths should correct the directional dependence of static shift. Although we used amplitude thresholds to simplify statistical processing, future developments should incorporate both signal-to-noise improvements and multisite decompositions. Lower amplitude signal may also be useful after the appropriate signal processing for noise reduction. We anticipate our approach will be useful for further work on MT distortion.
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