## 8 Conclusions  
The results of this study have shown that a multiparametric approach may provide an important contribution for better interpreting the actual origin of ionospheric anomalies. This contribution may be particularly valuable when ionospheric disturbances are investigated as possible indicators of impending earthquakes (e.g., [100; 101; 102; 103; 104; 105; 106; 107; 108]). Indeed, the integration of independent observations is nowadays expected to be a major improvement in short-term seismic hazard forecast. The possibility of moving to the operational use of this information, independently obtained by well-established data analysis methodologies (e.g., [61; 109; 110; 111] and references herein), strongly relies on our present capability in discriminating anomalous transients, possibly related to an impending earthquake, from those related to other natural, and in general nonseismic, sources. This paper, other than confirming the significant impacts on the ionosphere of volcanic eruptions and dust outbreaks, also demonstrates the importance of a multiparametric approach in identifying and removing false-positives in seismic hazard forecast applications. This way, by reducing false alarm rates, the identification of anomalous transients related to volcanic eruptions and/or to dust events could significantly improve the reliability of forecasts based on measurements of single and/or multiple parameters.  
Finally, the multiparametric approach used in this study could also have a positive impact on observations from missions such as Swarm, a European Space Agency (ESA) three-satellite constellation enabling the investigation of electric currents flowing in the magnetosphere and ionosphere [112], and the China Seismo-Electromagnetic Satellite (CSES). The latter is a Chinese-Italian space mission for the monitoring of the electromagnetic field and wave, plasma, and particle perturbations of the atmosphere, ionosphere, and magnetosphere induced by natural sources and anthropocentric emitters [113].  
V.T.: writing, coordination, and revision; F.M.: writing and AVHRR/SEVIRI data analyses; A.F.: SEVIRI data analysis and SW development; C.F.: SEVIRI data provision and analysis; N.G.: thermal anomalies and RST products analyses; K.H.: data analyses; M.L.: thermal anomalies and RST products analyses; J.Y.L.: writing and TEC data analyses; D.O.: writing and OLR data analyses; M.P.: writing and DEMETER data analyses; N.P.: writing and RST dust/ash products analyses; S.P.: writing and ACP data analyses.  
The work was partially funded by the SMART BASILICATA project funded by MIUR under the \"Smart Cities and Communities and Social Innovation\" Call, MIUR Announcement n.84/Ric 2012, PON 2007 - 2013 of 2 nd March 2012.  
DEMETER was a satellite launched by the Centre National d'Etudes Spatiales. This work is based on observations with the electric field instrument ICE, and the density experiments ISL and IAP aboard DEMETER. The authors thank [PERSON], the PI of ICE and IAP, and [PERSON], the PI of ISL for the use of the data. The authors thank ISSI (Bern) for the support of the team \"Multi-instrument Space-Borne Observations and Validation of the Physical Model of the Lithosphere-Atmosphere-Ionosphere-Magnetosphere Coupling\". The authors thank the NOAA's Climate Prediction Center and NASA's Goddard Global Modeling and Assimilation Office (GMAO) for providing satellite data products. The MSG-SEVIRI data used in this study followed the EUMETSAT data policy and were made available through the license released by the Meteorological Service of the Italian Military Aeronautics. The authors thank the referees for constructive comments devoted to improve the quality of the paper.  
**Conflicts of Interest**: The authors declare no conflict of interest.