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of extreme events in self-potential data and earthquakes, both modelled as stochastic point processes. This
method gives objective results, robust to the presence of nonstationarities that often affect observational time series.
Furthermore, the NWCCF identifies the timescales involved in the cross-correlated behaviour between two point processes. In particular, we analyzed the cross-correlation between the sequence of extreme events in selfpotential data measured at the monitoring station Tito, located in a seismic area of Southern Italy, and the series of earthquakes which occurred in the same area during 2001. To evaluate the influence of rain on the dynamics
of geoelectrical variations, we applied the same approach between the selected extreme values and the rain data.
We find that the anomalous geoelectrical values seem to cross-correlate with the rain at short and intermediate timescales (t< 500 h), while they significantly cross-correlate only with earthquakes (M = 2.5) at long timescales (t> 500 h).
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