Near-Real-Time Classification of Traveling Ionospheric Disturbances of Natural Hazards and Space Weather by GNSS data

Global Navigation Satellite System (GNSS) is a powerful tool for the analysis of traveling ionospheric disturbances (TIDs) since it is characterized by a wide spread network of receivers and, hence, provides almost global coverage. We developed novel methods that enable to automatically detect TIDs in series of ionospheric total electron content (TEC) and, then, to determine their spatio-temporal characteristics (velocity and azimuth of propagation, spectral components, localisation of a disturbance) in Near-Real Time (NRT), i.e., less than several minutes after the first detection of the disturbance. Our methods are based on the Rate of TEC (ROT) approach. Therefore, they are mostly suitable for detection of TIDs characterized by a high rate of TEC change (earthquakes, volcanic eruptions, tornadoes, explosions, rocket launches, and solar flares). We collected the database of such events (more than 90,000 time series for 33 events) and found that their instantaneous ROT signatures are quite diverse. The analysis of characteristics of TIDs generated by different geophysical and man-made events allowed to summarize the criteria to identify the origin of TIDs in NRT. For the discrimination of the source, we propose to use these spatio-temporal characteristics: the distance between the first estimated instantaneous velocity/center of the disturbance and the further instantaneous velocities/centers; the dominated frequencies in the ROT time series; the instantaneous velocities. Based on the differences of these characteristics, we show how to classify TIDs of different origins by using our newly developed methods and the collected database in NRT.