# Monitoring of Ionospheric Anomalies Using GNSS Observations to Detect Earthquake Precursors
## 1 Introduction  
The ionosphere is a shell of ionized gas in the Earth's atmosphere which interacts with the Sun's fully ionized zone and the Earth's neutral region in a complex manner. It is a highly variable propagation medium capable of substantially influencing (i) radio communications [1], (ii) navigation [2, 3], and (iii) remote sensing [4, 5] technologies and applications, as well as playing an important role in space weather monitoring and forecasting [6, 7]. The ionosphere impacts the technologies of GNSS communications in at least two ways, as (i) positioning and navigation applications are heavily affected by time delay errors induced by its charged particles and (ii), conversely, GNSS observations madeby Continuously Operating Reference Stations (CORSs) allow for the monitoring of the so-called ionospheric Total Electron Content (TEC) both spatially and temporally. Ionospheric models have been developed to predict such errors. From the Klobuchar model, developed to support survey with single frequency receivers [8], to models used for precise real-time navigation and positioning applications with different satellite constellations [9; 10], strategies have been set up for the Precise Point Positioning (PPP) of GNSS observations with the aim of mitigating the effects of ionospheric errors, especially in the estimation of GNSS ambiguities [11; 12]. Conversely, from the point of view of space weather monitoring, it is important to detect ionosphere perturbations which can affect space-to-Earth radio communications, particularly for precise GNSS positioning and navigation applications and in situations where radio communications play a significant role in Safety of Life (SoL). Perturbations can be produced by geomagnetic storms strictly connected to the solar activity or due to local phenomena like earthquakes, volcanic ash emissions, huge desert storms, nuclear accidents, or tests. In the first case, they can be subdivided on the basis of their intensity into (i) large-scale storms, during which the enhancement of the solar wind energy generates perturbations at high latitudes that can influence the ionosphere globally and have high TEC variations (more than 200%); (ii) medium-scale Traveling Ionospheric Disturbances (TIDs) corresponding to TEC variations of a few TEC units (TECUs), for which the sources have not yet been comprehensively identified; and (iii) small-scale ionospheric perturbations correlated with steep TEC gradients [13]. Although ionosphere maps have been produced for many years both in post-processing [14; 15] and in Near Real-Time (NRT) [16; 17; 18] applications, other projects and approaches have been developed focusing on monitoring and forecasting ionosphere perturbations. The Royal Observatory of Belgium uses a GNSS to produce the Vertical Total Electron Content (VTEC) in NRT for Europe, generating maps which are published every 15 minutes [19]. The processing strategy is based on L1 and L2 GNSS observations (from a network of permanent stations) used to retrieve the Slant TEC (STEC) from a geometry-free combination of phase-smoothed code observables. STEC values are biased by the Differential Code Bias (DCB) of satellites (\(DCB^{*}\)) and receivers (\(DCB_{r}\)) [20; 21]: \(DCB^{*}\) are provided as products from International GNSS Service (IGS) Analysis Centers, while \(DCB_{r}\) are estimated using the a priori CODE [22] IONEX ionospheric model and RINEX data from the European Permanent Network (EPN) [23]. Monitoring space weather is crucial both for precision and for SoL GNSS applications. To improve the reliability of the results, processing strategies based on the estimation of spatial and temporal variations in TEC have been proposed and implemented.