Real-time integration of multi-parametric observations is expected to accelerate the process toward improved, and operationally more effective, systems for time-Dependent Assessment of Seismic Hazard (t-DASH) and earthquake short-term (from days to weeks) forecast. However, a very preliminary step in this direction is the identification of those parameters (chemical, physical, biological, etc.) whose anomalous variations can be, to some extent, associated with the complex process of preparation for major earthquakes. In this paper one of these parameters (the Earth’s emitted radiation in the Thermal InfraRed spectral region) is considered for its possible correlation withM ≥ 4 earthquakes occurred in Greece in between 2004 and 2013. The Robust Satellite Technique (RST) data analysis approach and Robust Estimator of TIR Anomalies (RETIRA) index were used to preliminarily define, and then to identify, significant sequences of TIR anomalies (SSTAs) in 10 years (2004–2013) of daily TIR images acquired by the Spinning Enhanced Visible and Infrared Imager on board the Meteosat Second Generation satellite. Taking into account the physical models proposed for justifying the existence of a correlation among TIR anomalies and earthquake occurrences, specific validation rules (in line with the ones used by the Collaboratory for the Study of Earthquake Predictability—CSEP—Project) have been defined to drive a retrospective correlation analysis process. The analysis shows that more than 93 % of all identified SSTAs occur in the prefixed space–time window around (M ≥ 4) earthquake's time and location of occurrence with a false positive rate smaller than 7 %. Molchan error diagram analysis shows that such a correlation is far to be achievable by chance notwithstanding the huge amount of missed events due to frequent space/time data gaps produced by the presence of clouds over the scene. Achieved results, and particularly the very low rate of false positives registered on a so long testing period, seems already sufficient (at least) to qualify TIR anomalies (identified by RST approach and RETIRA index) among the parameters to be considered in the framework of a multi-parametric approach to t-DASH.

Space-time fluctuations of Earth's emitted Thermal Infrared (TIR) radiation have been observed from satellite months to weeks before earthquakes occurrence. The general RST approach has been proposed in order to discriminate normal (i.e. related to the change of natural factor and/or observation conditions) TIR signal fluctuations from anomalous signal transient possibly associated to earthquake occurrence. In this work RST approach is applied to the Abruzzo 6 April 2009 event (M_L=5.8) by using for the first time MSG-SEVIRI (Meteosat Second Generation -Spinning Enhanced Visible and Infrared Imager) thermal infrared observations. A validation/confutation analysis has been performed in order to verify the presence/absence of anomalous space-time TIR transients in the presence/absence of significant seismic activity. March–April 2009 has been analyzed for validation purposes. Relatively unperturbed periods (no earthquakes with M_L≥5) have been taken for confutation. A specific TIR anomalies space-time persistence analysis as well as a cloud coverage distribution test have been introduced in order to eliminate artifacts and outliers both in the validation and confutation phases. Preliminary results show clear differences in TIR anomalies occurrence during the periods used for validation and confutation purposes. Quite clear TIR anomalies appear also to mark main tectonic lines related to the preparatory phases of others, low magnitude (M_L~4) earthquakes, occurred in the area.

The European Plate Observing System (EPOS) is a long-term initiative aimed at integrating research infrastructures for solid Earth science in Europe. EPOS provides a sustainable, multidisciplinary user-oriented platform - the EPOS Data Portal - that facilitates data integration, access, use, and re-use, while adhering to the FAIR principles. The paper describes the key governance, community building, and technical aspects for achieving multidisciplinary data integration through the portal. It also outlines the key portal features for aggregating approximately 250 data sources from more than ten different scientific communities. The main architectural concepts underpinning the portal, namely the rich-metadata, the service-driven data provision, and the usage of semantics, are outlined. The paper discusses the challenges encountered during the creation of the portal, describes the community engagement process, and highlights the benefits to the scientific community and society. Future work includes expanding portal functionalities to include data analysis, processing, and visualization and releasing the portal as an open-source software package.