Preseismic electromagnetic signals in terms of complexity

Area of Science:

• Geophysics
• Nonlinear Dynamics
• Time Series Analysis

Background:

• Catastrophic events in physical systems are often preceded by organizational changes.
• Pre-earthquake electromagnetic (EM) time series data may contain characteristic signatures of impending seismic events.

Purpose of the Study:

• To investigate if complexity measures in EM time series can identify precatastrophic states before earthquakes.
• To validate findings using both linear and nonlinear analytical approaches.

Main Methods:

• Analysis of electromagnetic time series data using T-complexity and approximate entropy to quantify complexity.
• Linear fractal spectral analysis was employed for independent verification.
• Comparison of complexity measures during normal and precatastrophic states.

Main Results:

• A significant decrease in T-complexity and approximate entropy was observed in EM time series during the precatastrophic phase.
• Increased signal persistence was detected in the tail of preseismic EM emissions.
• Convergence of nonlinear (T-complexity, approximate entropy) and linear (fractal spectral analysis) methods confirmed findings.

Conclusions:

• Reduced complexity and increased persistence in EM time series are reliable indicators of the final stage of earthquake preparation.
• These complexity changes can potentially be used as diagnostic tools for predicting crustal failure and earthquakes.
• The study supports the principle that system organization changes precede catastrophic events.