Guest
Short term (days to hours) earthquake forecasting is a hard scientific problem. Monitoring electromagnetic (EM) rather than mechanical/seismic activity may provide a breakthrough in this research. Many reports of anomalous EM phenomena preceding earthquakes exist, but controversy persists about their validity. Claims typically split into anecdotal and statistical. Criticisms of anecdotal studies include lack of reproducible observations, and non-uniqueness of the anomalies when data are examined over the long term. Acquiring a dataset with the spatial and temporal coverage for rigorous statistical analysis of EM fields near earthquake epicenters is difficult because large seismic events are relatively rare. In the early 2000s a private effort (QuakeFinder) was established to address the deficiency of data and to build out a dataset appropriate for statistical analysis. Three-component induction magnetometers were deployed at more than 100 stations running primarily along the San Andreas Fault. More than 300,000 station days have been acquired with many stations nearby to significant earthquakes. The goal was to determine if there is a natural signal prior to moderate to large (greater than M4) earthquakes within range (less than 40 km) of the magnetometer instruments. Two major peer-reviewed statistical analyses have come out of this dataset. Both studies indicated rejection at the 95% confidence level of the null hypothesis (that there is not an electromagnetic precursor to earthquakes) as a baseline result with minimal treatment of noise. In both studies the confidence level rises above 3-sigma (99.7%) rejection of the null hypothesis when crude noise compensation measures are applied - in the first case via exclusion of noisy sites and in the second case by a bulk correction for solar geomagnetic noise. These statistical studies form the basis of further investigations to move the technology towards an operational, short term (days not seconds), earthquake early warning system.
