Earthquake precursory electric field signatures

Although data acquisition and relevant signal processing abilities have rapidly developed, forecast of earthquake remains one of the major scientific challenges. Besides having some knowledge of common features of fault mechanisms, regional complexity and relatively weak observability of the upper lithosphere make the forecast more problematic. Analysis of low frequency (DC to ELF) electric field changes appears as a usable indication to determine earthquake precursory structural variations. It has been observed that there is a correlation between the signatures constructed by time series of measured electric field data and the related nearby fault systems. Effect of regional change in dielectric constant (permittivity) of the upper crust on surface electric fields due to probable structural deformations has been investigated in this study. A method developed to determine structural changes in time by using specially developed stationary measurement device as well as in space by using mobile version of the system is described here. In this method, one part of the sensor mechanism is the Earth's upper crust that couples to the monopolar electrode through the air. Theoretically, maximum electric field strength occurs at the surface of any sphere that is loaded by a voltage source and the electric field decreases inverse-square proportional to the distance from the surface of the sphere. This is also valid for the Earth as a globe since the upper atmosphere keeps negative ions. Change in charge induction at the probe is expected to be related to the change in regional resultant stress as an electric potential source or change of permittivity due to structural variations in time or space. Although there also exist atmospherically electric field changes as noise, they can be filtered since the frequency range and the signal patterns are different from the change in upper crust coupling. It has been observed that each region has Electrocardiogram-like typical electrostatic field patterns and the deviation of spectral density in time is correlated to seismic events. This is the main reason that directs us towards the evaluation of electric field signatures for forecasting the earthquakes.