Detecting offsets in GPS time series: First results from the detection of offsets in GPS experiment

The accuracy of Global Positioning System (GPS) time series is degraded by the presence of offsets. To assess the effectiveness of methods that detect and remove these offsets, we designed and managed the Detection of Offsets in GPS Experiment. We simulated time series that mimicked realistic GPS data consisting of a velocity component, offsets, white and flicker noises (1/f spectrum noises) composed in an additive model. The data set was made available to the GPS analysis community without revealing the offsets, and several groups conducted blind tests with a range of detection approaches. The results show that, at present, manual methods (where offsets are hand picked) almost always give better results than automated or semiautomated methods (two automated methods give quite similar velocity bias as the best manual solutions). For instance, the fifth percentile range (5% to 95%) in velocity bias for automated approaches is equal to 4.2mm/year (most commonly 0.4mm/yr from the truth), whereas it is equal to 1.8mm/yr for the manual solutions (most commonly 0.2mm/yr from the truth). The magnitude of offsets detectable by manual solutions is smaller than for automated solutions, with the smallest detectable offset for the best manual and automatic solutions equal to 5mm and 8mm, respectively. Assuming the simulated time series noise levels are representative of real GPS time series, robust geophysical interpretation of individual site velocities lower than 0.2-0.4mm/yr is therefore certainly not robust, although a limit of nearer 1mm/yr would be a more conservative choice. Further work to improve offset detection in GPS coordinates time series is required before we can routinely interpret submm/yr velocities for single GPS stations. Key Points Manual and automatic GPS offset detection methods are testedManual approaches yield smaller velocity biasesCare must be taken when interpreting single-site velocities <1mm/yr