Foundations for an Operational Earthquake Prediction System - Angelo De Santis; Gianfranco Cianchini; Loredana Perrone; Maurizio Soldani; Habib Rahimi; Homayoon Alimoradi (Geosciences)
Earthquake prediction is one of the most challenging enterprises of science. Any prediction system must be based on the search for a precursor appearing during the preparation phase of an earthquake in the ground, atmosphere, or ionosphere that can anticipate its occurrence. We present methods to detect potential pre-earthquake anomalies. In particular, we show the analysis of lithospheric, atmospheric, and ionospheric data and the detection of anomalies under specific criteria. When we apply these methods retrospectively, we find that their accuracy goes from 69% to 83%. The combination of two or more methods is expected to improve the accuracy.