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Magnetotelluric and geomagnetic depth-sounding surveys were made in the Harz Mountains, Germany, to investigate the conductivity structure across its northern edge as well as the extension of crystalline intrusions inside the mountains. Magnetic and electric pulsations were recorded along a north-south-profile of 80km length. Because the statioins were recording simultaneously, transfer functions for anomalous horizontal and vertical magnetic variations could be obtained with the north end station defined as normal. Their amplitude and phase indicate a large-scale discontinuity in conductivity.This model explains well the smooth behaviour of the magnetic transfer functions but not the telluric impedances and their distinct changes from site to site. For this reason a special study of the effects of local anomalous conductivity zones on the telluric field was carried out. The impedances found there are influenced by strong direct-current distortions. Furthermore, a vertical electric field was detected inside the uppermost layer. Because it is also associated with a local anomaly, it can be used to determine the orientation and magnitude of that anomaly.

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Spectral analysis of the time-varying horizontal magnetic and electric field components yields the magnetotelluric (MT) impedance tensor. This frequency dependent 2x2 complex tensor can be examined for details which axe diagnostic of the electrical conductivity distribution in the Eaxth within the relevant (frequency dependent) inductive scale length of the surface observation point. As such, precise and accurate determination of this tensor from the electromagnetic time series is fundamental to successful interpretation of the derived responses. In this paper, several analysis techniques are applied to the same data set from one of the EMSLAB Lincoln Line sites.Two subsets of the complete data set were selected, on the basis of geomagnetic activity, to test the methods in the presence of differing signal-to-noise ratios for varying signals and noises.Illustrated by this comparison are the effects of both statistical and bias errors on the estimates from the diverse methods. It is concluded that robust processing methods should become adopted for the analysis of MT data, and that whenever possible remote reference fields should be used to avoid bias due to runcorrelated noise contributions.

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