Detecting volcanic plume signatures on GNSS signal, Based on the 2014 Sakurajima Eruption

Detection of volcanic hazards are important for public health and aircraft safety. In this study, we investigate the ability to detect volcanic plume using a simple analytic approach based on Global Navigate Satellite System (GNSS) observations, numerical weather model (NWM) fields and ground-based automatic weather stations. The GNSS data obtained from the network located around the Sakurajima volcano in Japan was used to estimate zenith tropospheric delays (ZTD) in October 2014, when the volcano showed an increase in activity. For our analysis, the ZTDs reconstructed in the ray tracing approach were applied to ERA5 reanalysis, and then compared with the ZTDs estimated by the Natural Resources Canada web GNSS processing software. Four analytical techniques were employed: target, space, time, and eventually, time and space differentiation. Meteorological data from nearby weather stations, as well as ERA5 reanalysis, helped separate the ZTD increments connected to weather conditions and volcanic activity. The results revealed that our approach correctly demonstrates Sakurajima activity in four cases out of five. We also noted a correlation between the results of our calculations and plume spreading direction data in 25% of cases.