Methods of Multivariable Earthquake Precursor Analysis and a Proposed Prototype Earthquake Early Warning System

Abstract

Significant advances are being made in earthquake prediction theory; however, a reliable method for forecasting the occurrence of earthquakes from space and/or ground based technologies remains limited to no more than a few minutes before the event happens. Several claims of earthquake precursors have been put forward, such as ionospheric changes, electromagnetic effects, and ground heating, though the science behind these is far from complete and the successful application of these precursors is highly regionally variable. Existing and planned dedicated space missions for monitoring earthquake precursors are insufficient for resolving the precursor issue. Their performance does not satisfy the requirements of an earthquake early warning system in terms of spatial and temporal coverage. To achieve statistically significant validation of precursors for early warning delivery, precursor data must be obtained from simultaneous repeated monitoring of several precursors in focus regions over a long period of time and then integrated and processed. Data sources include historical data, data from ground-based units, airborne systems, and space-based systems. This paper describes methods of systematic evaluation of regionally specific, multivariable precursor data needed for the identification of the expected time, magnitude and the position of the epicentre. This data set forms the basis for a proposed operational early warning system developed at the International Space University and which is built in partnership with local and national governments as well as international organizations.