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.

检测火山危害对公共健康和飞机安全很重要。在这项研究中，我们使用基于全球导航卫星系统 (GNSS) 观测、数值天气模型 (NWM) 场和地面自动气象站的简单分析方法研究了检测火山羽流的能力。从位于日本樱岛火山周围的网络获得的 GNSS 数据用于估计 2014 年 10 月火山活动增加时的天顶对流层延迟 (ZTD)。在我们的分析中，将射线追踪方法重建的 ZTD 应用于 ERA5 再分析，然后与加拿大自然资源部网络 GNSS 处理软件估计的 ZTD 进行比较。使用了四种分析技术：目标、空间、时间，以及最终的时间和空间区分。来自附近气象站的气象数据以及 ERA5 再分析有助于区分与天气条件和火山活动相关的 ZTD 增量。结果表明，我们的方法在五分之四的情况下正确地证明了樱岛活动。我们还注意到在 25% 的情况下，我们的计算结果与羽流扩散方向数据之间存在相关性。