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| | Abstract | | Magnetotelluric (MT) method is used for visualizing subsurface resistivity structure and recently used for monitoring of subsurface struture. For the monitoring by MT method, the evaluation of ionospheric current condition is required because the topical ionospheric current causes false changes of MT responses. Conventional methods are based on geomagnetic transfer functions (TFs) using magnetic field data at several sites (by using the remote reference processing). However, if the reference data are affected by inherent noise or topical ionospheric current the evaluation becomes impractical. In this study, we developed Multi-Channel Non-negative Matrix Factorization (MC-NMF), which can extract common factors in multiple spectrograms. MC-NMF is applied to six synthetic geomagnetic field data with inherent noise, then we tested the MC-NMF performance to evaluate the inherent components (i.e., noises) and common components (i.e., signals) included in geomagnetic field data. As a result, we can extract magnetic field data and time step with large noise. Before remote reference processing, using our new method, the evaluation of ionospheric current condition is expected more appropriately. |
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