Geology topics

Andrei Swidinsky

Publications and source records attributed to Andrei Swidinsky.

3 recordsLinked to original sources

USGS2018

Geoelectric hazard assessment: the differences of geoelectric responses during magnetic storms within common physiographic zones

Geomagnetic field data obtained through the INTERMAGNET program are convolved with with magnetotelluric surface impedance from four EarthScope USArray sites to estimate the geoelectric variations throughout the duration of a magnetic storm. A duration of time from June 22, 2016, to June 25, 2016, is considered which encompasses a magnetic storm of moderate size recorded at the Brandon, Manitoba and Fredericksburg, Virginia magnetic observatories over 3 days. Two impedance sites were chosen in each case which represent different responses while being within close geographic proximity and within the same physiographic zone. This study produces estimated time series of the geoelectric field throughout the duration of a magnetic storm, providing an understanding of how the geoelectric field differs across small geographic distances within the same physiographic zone. This study shows that the geoelectric response of two sites within 200 km of one another can differ by up to two orders of magnitude (4484 mV/km at one site and 41 mV/km at another site 125 km away). This study demonstrates that the application of uniform 1-dimensional conductivity models of the subsurface to wide geographic regions is insufficient to predict the geoelectric hazard at a given site. This necessitates that an evaluation of the 3-dimensional conductivity distribution at a given location is necessary to produce a reliable estimation of how the geoelectric field evolves over the course of a magnetic storm.

Earth, Planets and Space↗

USGS2015

Observatory geoelectric fields induced in a two-layer lithosphere during magnetic storms

We report on the development and validation of an algorithm for estimating geoelectric fields induced in the lithosphere beneath an observatory during a magnetic storm. To accommodate induction in three-dimensional lithospheric electrical conductivity, we analyze a simple nine-parameter model: two horizontal layers, each with uniform electrical conductivity properties given by independent distortion tensors. With Laplace transformation of the induction equations into the complex frequency domain, we obtain a transfer function describing induction of observatory geoelectric fields having frequency-dependent polarization. Upon inverse transformation back to the time domain, the convolution of the corresponding impulse-response function with a geomagnetic time series yields an estimated geoelectric time series. We obtain an optimized set of conductivity parameters using 1-s resolution geomagnetic and geoelectric field data collected at the Kakioka, Japan, observatory for five different intense magnetic storms, including the October 2003 Halloween storm; our estimated geoelectric field accounts for 93% of that measured during the Halloween storm. This work demonstrates the need for detailed modeling of the Earth’s lithospheric conductivity structure and the utility of co-located geomagnetic and geoelectric monitoring.

Kakioka↗

USGS2014

Time causal operational estimation of electric fields induced in the Earth's lithosphere during magnetic storms

In support of projects for monitoring geomagnetic hazards for electric power grids, we develop a simple mathematical formalism, consistent with the time causality of deterministic physics, for estimating electric fields that are induced in the Earth's lithosphere during magnetic storms. For an idealized model of the lithosphere, an infinite half‐space having uniform electrical conductivity properties described by a galvanic tensor, we work in the Laplace‐transformed frequency domain to obtain a transfer function which, when convolved with measured magnetic field time series, gives an estimated electric field time series. Using data collected at the Kakioka, Japan observatory, we optimize lithospheric conductivity parameters by minimizing the discrepancy between model‐estimated electric field variation and that actually measured. With our simple model, we can estimate 87% of the variance in storm time Kakioka electric field data; a more complicated model of lithospheric conductivity would be required to estimate the remaining 13% of the variance. We discuss how our estimation formalism might be implemented for geographically coordinated real‐time monitoring of geoelectric fields.

Geophysical Research Letters↗