Automamatic detection of discontinuities in the station position time series of the reprocessed global GNSS network using Bernese GNSS Software

For over 25 years, the International GNSS Service (IGS) has been processing observational data from the Global Navigation Satellite Systems (GNSSs). Hence, long time series of station coordinates are available, however, they are burdened with discontinuities, station velocity changes, and gross errors. Discontinuities and periodic variations are caused by equipment changes at stations, earthquakes, geophysical processes, data problems, as well as local environmental changes. As a result, many approaches have been identified that identify and remove discontinuities in the GNSS coordinate time series. One of them is the program Finding Outliers and Discontinuities In Time Series (FODITS) implemented in the Bernese GNSS Software environment (Dach et al., 2015), developed by the Astronomical Institute, University of Bern. The program is designed for the automatic analysis of time series, in which the functional model is adapted to the time series of coordinates depending on the adopted parameters. This study presents the analysis of long-term GNSS coordinate time series reprocessed in the framework of the realization of the International Terrestrial Reference Frame 2014 (ITRF2014) using the FODITS program. The results show that the optimum confidence level for the autonomous detection of station discontinuities in FODITS is 99 % and 98 %, for 7-day and 3-day GNSS solutions, respectively, when compared to the manual discontinuity detection from ITRF2014. However, the manual analysis unsupported by statistical tests as conducted in ITRF2014 may contain errors over which further elaboration is indispensable. On the other hand, routine interpretation of GNSS coordinate time series in a fully autonomous manner, although much faster, is not free from drawbacks, in particular in detecting appropriate epochs of discontinuities and changes in station velocities. ARTICLE INFO