Abstract
In this research, we focus on determining the quasi-annual changes in GNSS-derived 3-dimensional time series. We use the daily time series from PPP solution obtained by JPL (Jet Propulsion Laboratory) from more than 300 globally distributed IGS stations. Each of the topocentric time series were stacked into data sets according to year (from January to December) and then decomposed and approximated with a Meyer wavelet. This approach allowed investigating changes of the amplitudes in time. An observed quasi-annual signal for a set of European stations prompted us to divide the stations into different sub-networks called clusters. For Up component seven clusters were established. The signals were then averaged within each cluster and median quasi-annual signal was revealed. The vast majority of the GNSS time series is characterized by vertical changes of 3 mm with their maximum in Summer. The maximum vertical amplitude was at the level of 14 mm with the minimum equal to −13 mm, giving the peak-to-peak position changes up to 27 mm.
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Acknowledgments
This research was financed by the Military University of Technology, Faculty of Civil Engineering and Geodesy Young Scientists Development funds, grant No. 739/2015.
JPL repro2011b time series accessed from ftp://sideshow.jpl.nasa.gov/pub/JPL_GPS_203_Timeseries/repro2011b/raw on 2014-11-10.
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Bogusz, J., Gruszczynska, M., Klos, A., Gruszczynski, M. (2015). Non-parametric Estimation of Seasonal Variations in GPS-Derived Time Series. In: van Dam, T. (eds) REFAG 2014. International Association of Geodesy Symposia, vol 146. Springer, Cham. https://doi.org/10.1007/1345_2015_191
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DOI: https://doi.org/10.1007/1345_2015_191
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