Global navigation satellite systems (GNSS) data are a fundamental source of information for achieving a better understanding of geophysical and climate-related phenomena. However, discontinuities in the coordinate time series might be a severe limiting factor for the reliable estimate of long-term trends. A methodological approach has been adapted from Rodionov (Geophys Res Lett 31:L09204, 2004 ; Geophys Res Lett 31:L12707, 2006) and from Rodionov and Overland (J Marine Sci 62:328-332, 2005) to identify both the epoch of occurrence and the magnitude of jumps corrupting GNSS data sets without any a priori information on these quantities. The procedure is based on the Sequential t test Analysis of Regime Shifts (STARS) (Rodionov in Geophys Res Lett 31:L09204, 2004). The method has been tested against a synthetic data set characterized by typical features exhibited by real GNSS time series, such as linear trend, seasonal cycle, jumps, missing epochs and a combination of white and flicker noise. The results show that the offsets identified by the algorithm are split into 48 % of true-positive, 28 % of false-positive and 24 % of false-negative events. The procedure has then been applied to GPS coordinate time series of stations located in the southeastern Po Plain, in Italy. The series span more than 15 years and are affected by offsets of different nature. The methodology proves to be effective, as confirmed by the comparison between the corrected GPS time series and those obtained by other observation techniques.

Detecting discontinuities in GNSS coordinate time series with STARS: case study, the Bologna and Medicina GPS sites

BRUNI, SARA;ZERBINI, SUSANNA;ERRICO, MADDALENA;SANTI, EFISIO
2014

Abstract

Global navigation satellite systems (GNSS) data are a fundamental source of information for achieving a better understanding of geophysical and climate-related phenomena. However, discontinuities in the coordinate time series might be a severe limiting factor for the reliable estimate of long-term trends. A methodological approach has been adapted from Rodionov (Geophys Res Lett 31:L09204, 2004 ; Geophys Res Lett 31:L12707, 2006) and from Rodionov and Overland (J Marine Sci 62:328-332, 2005) to identify both the epoch of occurrence and the magnitude of jumps corrupting GNSS data sets without any a priori information on these quantities. The procedure is based on the Sequential t test Analysis of Regime Shifts (STARS) (Rodionov in Geophys Res Lett 31:L09204, 2004). The method has been tested against a synthetic data set characterized by typical features exhibited by real GNSS time series, such as linear trend, seasonal cycle, jumps, missing epochs and a combination of white and flicker noise. The results show that the offsets identified by the algorithm are split into 48 % of true-positive, 28 % of false-positive and 24 % of false-negative events. The procedure has then been applied to GPS coordinate time series of stations located in the southeastern Po Plain, in Italy. The series span more than 15 years and are affected by offsets of different nature. The methodology proves to be effective, as confirmed by the comparison between the corrected GPS time series and those obtained by other observation techniques.
Bruni S.; Zerbini S.; Raicih F.; Errico M.; Santi E.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/395117
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