09:30 〜 09:45
[G04-3-05] Estimates of vertical velocity errors for IGS ITRF2014 stations by applying the improved singular spectrum analysis method and environmental loading models
An accurate removal of the seasonal signals from the Global Positioning System (GPS) position time series is beneficial for the accuracy of the derived velocities. In this research, we propose a two-stage solution of the problem of reliable subtraction of seasonal changes. Firstly, we employ the environmental loading models (atmospheric, hydrologic and ocean non-tidal) and study the seasonal signal (annual and semi-annual) estimates that changes over time using the Improved Singular Spectrum Analysis (ISSA) approach. Then, this model is subtracted from GPS position time series. We studied data from 376 permanent IGS (International GNSS Service) stations, derived as the official contribution to ITRF2014 (International Terrestrial Reference Frame) to measure the influence of applying environmental loading models on the estimated vertical velocity. These loading models show a dominant annual signal and their superpositon reveals amplitudes of up to 12 mm. Having removed the environmental loadings directly from ITRF2014 position time series we noticed the evident change in the power spectrum of GPS time series for frequencies between 4 and 80 cpy. Therefore, we modeled the seasonal signal using the ISSA approach in environmental models and subtracted it from GPS position time series. Finally, we estimated the Dilution of Precision (DP) of the vertical velocities of the ITRF2014 series. For a total number of 298 out of the 376 stations analyzed, the DP was lower than 1. This indicates that when the ISSA-derived curve was removed from the GPS data, the error of velocity becomes lower than it was before.