Geoelectric power spectra over oceanic distances

Fujii, Ikuko; Lanzerotti, L. J.; Utada, Hisashi; Kinoshita, Hajimu; Kasahara, Junzo; Medford, L. V.; Maclennan, C. G.

doi:10.1029/94gl03282

Cited by 17 publications

(9 citation statements)

References 21 publications

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“…In recent decades, the SP method has been becoming an important component in geophysical surveys on the areas of groundwater flow (Jardani et al, 2006;Mao et al, 2015;Sill, 1983), dam seepage monitoring (Al-Saigh et al, 1994;Ikard et al, 2014;Panthulu et al, 2001), volcanic monitoring (Aizawa et al, 2005;Corwin & Hoover, 1979;Kuwano et al, 2015), and earthquake precursor (Chen & Chen, 2016;Chen et al, 2017;Corwin & Morrison, 1977;Ramirez-Rojas et al, 2004). However, the SP signals are sensitive to anthropogenic factors, such as electric trains, factories, and power pipelines (Fraser-Smith & Coates, 1978;Harada et al, 2004;Ishikawa et al, 2007;Oettinger et al, 2001;Saito et al, 2011;Takahashi et al, 2007;Viljanen & Pirjola, 1994), and to natural factors, such as solar-terrestrial interactions, groundwater flows, and ocean tides (Fujii et al, 1995;Huang & Liu, 2006;Jardani et al, 2006;Lanzerotti et al, 2000). Hence, understanding the SP background noises is critical and helpful to improve the data quality.…”

Section: Introductionmentioning

confidence: 99%

Self‐Potential Ambient Noise and Spectral Relationship With Urbanization, Seismicity, and Strain Rate Revealed via the Taiwan Geoelectric Monitoring Network

Chen

Chiu

et al. 2020

JGR Solid Earth

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Geoelectric self-potential (SP) signals are sensitive to natural and anthropogenic factors. The SP spectral characteristics under the different factors in Taiwan were investigated, and the SP spectral scalings were correlated with urbanization level, seismicity, and crustal deformation. The ambient SP noise models were first established by estimating the probability density functions of the spectrograms at each frequency. The effects of the natural and anthropogenic factors on the SP signals are understood by comparing the SP noise models under various conditions, such as precipitation, urbanization, and electric trains. Results show that the SP signals in areas of high industrialization and human activity and areas close to train stations behave as white noises and exhibit a distinct spectral ripple at frequencies around 1 Hz. On the other hand, the SP spectral power law parameters, Gutenberg-Richter b values, and dilation strain rates were estimated by using the SP, earthquake catalog, and GPS data, respectively, during 2012-2017. By investigating the correlations of the SP spectral parameters with the Gutenberg-Richter b value, dilation strain rates, and urbanization level, the SP optimal frequency band is found between 0.006 and 1 Hz due to the high correlation between the SP and seismicity data and between the SP and dilation data and the low correlation between the SP and urbanization data. Hence, this study may help the filtering and screening of the SP data and facilitate the understanding of the mechano-electric behavior in the crust.Plain Language Summary Self-potential is a naturally electric potential difference beneath the Earth's surface, measured between any two points on the ground or in boreholes. The selfpotential signals are sensitive to natural factors, such as ionospheric disturbance, solar wind, and tidal forces, and to artificial factors, such as electric trains, factories, and power pipelines. Hence, the investigation of the background noises is critical. The self-potential noise models were established by estimating the probability density functions of the daily power spectral densities. We compared the noise models under several conditions, such as urbanization, electric trains, and rainfalls. We found that the noise models behave as white noises in areas of high industrialization and human activity. Furthermore, we also estimated the self-potential power law parameters, seismic b values, and dilation strain rates. We then studied correlations of the self-potential power law parameters with the urbanization levels, b values, and dilation strain rates. We found out the frequency-dependent correlations of the spectral scalings with the other parameters and determined the self-potential signals with a high signal-to-noise ratio in the frequency band of 0.006-1 Hz. Understanding such correlations may understand the feature of the mechano-electric behavior in the crust and facilitate the development of a seismic-electric theory.Key Points:• Self-potential (SP) signals show white noises or spe...

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Section: Introductionmentioning

confidence: 99%

Self‐Potential Ambient Noise and Spectral Relationship With Urbanization, Seismicity, and Strain Rate Revealed via the Taiwan Geoelectric Monitoring Network

Chen

Chiu

et al. 2020

JGR Solid Earth

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“…Despite the mentioned difficulties, oceanic EM signals can be very useful in monitoring the ocean. Many studies have inferred oceanic transports from in situ measurements, such as seafloor voltage cables [e.g., Larsen, 1991;Fujii et al, 1995]. With the launch of the new satellite mission Swarm [Friis-Christensen et al, 2006;Olsen et al, 2007], and with the deployment of new terrestrial EM stations, smaller oceanographic features are Geophysical Research Letters 10.1002/2017GL073683 extractable for current research.…”

Section: Introductionmentioning

confidence: 99%

Impact of oceanic warming on electromagnetic oceanic tidal signals: A CMIP5 climate model‐based sensitivity study

Saynisch

Petereit

Irrgang

et al. 2017

Geophysical Research Letters

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In contrast to ocean circulation signals, ocean tides are already well detectable by electromagnetic measurements. Oceanic electric conductivities from the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate simulations are combined with tidal currents of M2 and O1 to estimate electromagnetic tidal signals and their sensitivity to global warming. Ninety‐four years of global warming leads to differences of ±0.3 nT in tidal magnetic amplitudes and ±0.1 mV/km in the tidal electric amplitudes at sea level. Locally, the climate‐induced changes can be much higher, e.g., +1 nT in the North Atlantic. In general, all studied electromagnetic tidal amplitudes show large‐scale climate‐induced anomalies that are strongest in the Northern Hemisphere and amount to 30% of their actual values. Consequently, changes in oceanic electromagnetic tidal amplitudes should be detectable in electromagnetic records. Electric and magnetic signals, as well as tides of different frequencies, contain complementary regional information.

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“…In oceanic environment, the distance can vary from a few meters to many thousands of kilometers. Longer electrode separation generally enables us to detect signals of larger spatial extent that are useful for exploring the ionospheric current of oceanic scales [1], the mantle structure [2,3,4] and signals from the core [5,6,7] and for monitoring global ocean circulation [8] and ocean tides [9]. Submarine cables in the Pacific Ocean retired from telecommunications services have been used for such purposes since middle 1990's ( Fig.…”

Section: Reuse Of Telecommunications Cablesmentioning

confidence: 99%

Ocean bottom measurements of the Earth's electric field using long cable installed by ROV

Utada

Baba

Shimizu

et al. 2013

2013 IEEE International Underwater Technology Symposium (UT)

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The materials in Earth's crust and mantle are classified as semiconductor in terms of electrical property. Therefore essential information to understand various kinds of geodynamic processes can be provided from measurements of the electric field of the Earth as well as the measurements of the magnetic field. Recently, we have developed a geophysical instrument for accurate measurement of Earth's electric field, named as EFOS (Earth's electric field observation system), which is installed by using ROV (remotely operated underwater vehicle). It is shown by recent experiments to provide data of much higher quality than conventional instrument, OBEM (ocean bottom electro-magnetometer).

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Geoelectric power spectra over oceanic distances

Cited by 17 publications

References 21 publications

Self‐Potential Ambient Noise and Spectral Relationship With Urbanization, Seismicity, and Strain Rate Revealed via the Taiwan Geoelectric Monitoring Network

Self‐Potential Ambient Noise and Spectral Relationship With Urbanization, Seismicity, and Strain Rate Revealed via the Taiwan Geoelectric Monitoring Network

Impact of oceanic warming on electromagnetic oceanic tidal signals: A CMIP5 climate model‐based sensitivity study

Ocean bottom measurements of the Earth's electric field using long cable installed by ROV

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