Phd in INFRASTRUCTURES AND TRANSPORT

Thesis title: An innovative approach for real-time GNSS Ionospheric Seismology: assessment, potentialities, applications and issues

GNSS Ionospheric Seismology employs the GNSS signal to study the ionospheric response to earthquakes and tsunamis. These events generate acoustic and gravity waves able to propagate up to the ionosphere, perturbing its natural total electron content (TEC) and causing the so-called Traveling Ionospheric Disturbances (TIDs). In this background, the VARION (Variometric Approach for Real-Time Ionosphere Observation) algorithm, able to estimate the TEC variations in real-time using a standalone GNSS receiver and standard GNSS broadcast products, was developed. The main aim of this thesis is to investigate the innovative applications of VARION algorithm, in order to establish a reliable real-time tool for ionospheric monitoring and natural hazards/man-made TIDs detection, with a specific focus on the augmentation of tsunami early warning systems. One of the first new VARION extensions is the inclusion of the observations coming from geostationary (GEO) satellites in the processing. In this context, the joint use of GEOs and MEOs (Medium Earth Orbit) within VARION is applied to analyse the TIDs connected to the 2018 New Caledonia earthquake and tsunami. Despite few GNSS stations tracking the GEO satellites, their advantages are clear. Among them, the possibility to provide continuous time series, to remove all the geometry effects and to keep the observation noise level as constant as possible is the most important. Therefore, these features could really mark an improvement in the effectiveness of TIDs detection enabling continuous monitoring of ionospheric activity. Furthermore, an analysis of ionospheric data from a Xiaomi Mi8 dual-frequency smartphone is carried out. Indeed, thanks to the opportunity for Android 7.0 (and higher) smartphones to access GNSS raw measurements, it is possible to process this data with the VARION algorithm. Despite the high level of noise in the measurements, the application of a moving median filtering technique allows for noise reduction, making it comparable to what is achievable with geodetic class receivers. The promising results of this first study aim at paving the way for the use of smartphones to increase the amount of available data. The basic principle of VARION, i.e the single time differences of geometry-free combination, also permits to leverage observations coming from moving receivers. As a matter of fact, the receiver motion does not affect the TEC estimation process. For this reason, we demonstrate the feasibility of using VARION for detecting TIDs from ship-based GNSS receivers. In detail, two GNSS receivers installed on a ship moving near Kauai Island in the Hawaiian archipelago are used to detect the TIDs connected to the 2010 Maule earthquake and tsunami. In this sense, using the GNSS receivers already onboard the ships represent a cost-effective tool (it doesn't require the installation of complex infrastructures in the open sea) that can improve already existing tsunami early warning systems as well as densify ionospheric monitoring. Moreover, one of the fundamental applications of our work is the coupling between VARION and VADASE (Variometric Approach for Displacements Analysis Standalone Engine), constituting the so-called Total Variometric Approach (TVA). Starting from the same variometric principle, the two algorithms allow for the simultaneous estimation of ground shaking, coseismic displacements and ionospheric TEC disturbances, using the same real-time GNSS data stream. The 2015 Illapel earthquake is analysed to prove the feasibility and reliability of TVA to support classic method for tsunami warning systems. On the other side, the application of TVA to the 2019 Ridgecrest earthquake sequences aims at a better understanding of the coupling Earth-atmosphere-ionosphere for strike-slip earthquakes. Similarly, VARION is employed to elaborate a methodology to estimate Hion (i.e., the height at which the whole ionospheric electron contribution is approximated), that represents one of the long-standing issues in GNSS ionospheric sounding. Nominally, the study of TIDs propagation allows to investigate the physical properties of the ionosphere. The 2011 Tohoku-Oki earthquake and tsunami is used as a case study, since it triggered very well-defined TIDs detected by a particularly dense GPS network. Finally, the future of GNSS Ionospheric Seismology is questioned. To this end, it is impossible not to mention the leading role of machine learning in TIDs detection. The huge amount of data available allows to develop a VARION based machine learning approach to detect tsunami induced TIDs. Our first promising outcomes related to the 2012 Haida Gwaii earthquake and tsunami give the scientific community the possibility to have an additional tool to detect TIDs and, hence, to enhance tsunami early warning systems. In conclusion, the feasibility and reliability of VARION in estimating TEC variations in real time, leveraging multi-constellations, multi-devices, multi-algorithms data is proven. These studies aim, hence, at making VARION an established tool in GNSS Ionospheric Seismology for the ionospheric monitoring, TIDs detection and the augmentation of tsunami early warning systems.