Investigation of ionospheric electron content variations before earthquakes in southern California, 2003–2004Thomas Dautermann
Department of Physics, Purdue University, West Lafayette, Indiana, USA
Eric Calais
Department of Earth and Atmospheric Sciences, Purdue University, West Lafayette,
Indiana, USA
Jennifer Haase
Department of Earth and Atmospheric Sciences, Purdue University, West Lafayette,
Indiana, USA
James Garrison
School of Aeronautics and Astronautics, Purdue University, West Lafayette, Indiana,
USA
AbstractIt has been proposed that earthquakes are preceded by electromagnetic signals
detectable from ground- and space-based measurements. Ionospheric anomalies,
such as variations in the electron density a few days before earthquakes, are one of
the precursory signals proposed. Since Global Positioning System (GPS) data can be
used to measure the ionospheric total electron content (TEC), the technique has
received attention as a potential tool to detect ionospheric perturbations related to
earthquakes. Here, we analyze 2 years (2003–2004) of data from the Southern
California Integrated GPS Network (SCIGN), a dense network of 265 continuous
GPS stations centered on the Los Angeles basin, for possible precursors. This time
period encompasses the December 2003, M6.6, San Simeon and September 2004,
M6.0, Parkfield earthquakes. We produce TEC time series at all SCIGN sites and
apply three different statistical tests to detect anomalous TEC signals preceding
earthquakes. We find anomalous TEC signals but no statistically significant
correlation, in time or in space, between these TEC anomalies and the occurrence of
earthquakes in southern California for the 2003–2004 period. This result does not
disprove the possibility of precursory phenomena but show the signal-to-noise ratio
of a hypothetical TEC precursor signature is too low to be detected by the analysis
techniques employed here. Precursors may still be revealed for future large
earthquakes in well instrumented areas such as California and Japan, if the tests can
be developed into techniques that can better separate external influences from the
actual TEC signal.
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