The present invention introduces an innovative data mining technique to identify precursory signals associated with earthquakes. It involves a multistrategy approach that employs one-dimensional wavelet transformations to identify singularities in data, and analyzes the continuity of wavelet maxima in time and space to determine the singularities that could be precursory signals. Surface Latent Heat Flux (SLHF) data may be used. A single prominent SLHF anomaly may be found to be associated some days prior to a main earthquake event.