Long Term RST Analyses of TIR Satellite Radiances in Different Geotectonic Contexts: Results and Implications for a Time‐Dependent Assessment of Seismic Hazard (t‐DASH)

Tuesday, 16 December 2014: 8:45 AM
Valerio Tramutoli1,2, Barbara Armandi1, Irina Coviello3, Alexander Eleftheriou4, Carolina Filizzola3, Nicola Genzano1, Teodosio Lacava3, Mariano Lisi1, Rossana Paciello3, Nicola Pergola1,3, Valeria Satriano1 and Filippos Vallianatos4, (1)University of Basilicata, Potenza, Italy, (2)International Space Science Institute, Bern, Switzerland, (3)IMAA/CNR, Tito Scalo (Pz), Italy, (4)Technological Educational Institute of Crete, Chania, Greece
A large scientific documentation is to-date available about the appearance of anomalous space-time patterns of geophysical parameters measured from days to week before earthquakes occurrence. Nevertheless up to now no one measurable parameter, no one observational methodology has demonstrated to be sufficiently reliable and effective for the implementation of an operational earthquake prediction system.

In this context PRE-EARTHQUAKES EU-FP7 project (www.pre-earthquakes.org), investigated to which extent the combined use of different observations/parameters together with the refinement of data analysis methods, can reduce false alarm rates and improve reliability and precision (in the space-time domain) of predictions.

Among the different parameters/methodologies proposed to provide useful information in the earthquake prediction system, since 2001 a statistical approach named RST (Robust Satellite Technique) has been used to identify the space-time fluctuations of Earth’s emitted Thermal Infrared (TIR) radiation observed from satellite in seismically active regions.

In this paper RST-based long‐term analysis of TIR satellite record collected by MSG/SEVIRI over European (Italy and Greece) and by GOES/IMAGER over American (California) regions will be presented. Its enhanced potential, when applied in the framework of time-Dependent Assessment of Seismic Hazard (t-DASH) system continuously integrating independent observations, will be moreover discussed.