On the combined effect of periodic signals and colored noise on velocity uncertainties

Kłos, Anna; Olivares, Germán; Teferle, Felix Norman; Hunegnaw, Addisu; Bogusz, Janusz

doi:10.1007/s10291-017-0674-x

Cited by 79 publications

(40 citation statements)

References 64 publications

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“…After the common annual seasonal curve was modelled with MSSA and removed from the GPS position time series, the residual station-specific annual curve was removed with LSE, as it may affect the character of stochastic part of the GPS data Bogusz and Klos 2016;Klos et al 2018b). We showed that the amplitudes of residual oscillations do not exceed 2 mm at maximum.…”

Section: Discussionmentioning

confidence: 92%

Multichannel Singular Spectrum Analysis in the Estimates of Common Environmental Effects Affecting GPS Observations

Gruszczyńska

Rosat

Kłos

et al. 2018

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We described a spatio-temporal analysis of environmental loading models: atmospheric, continental hydrology, and non-tidal ocean changes, based on multichannel singular spectrum analysis (MSSA). We extracted the common annual signal for 16 different sections related to climate zones: equatorial, arid, warm, snow, polar and continents. We used the loading models estimated for a set of 229 ITRF2014 (International Terrestrial Reference Frame) International GNSS Service (IGS) stations and discussed the amount of variance explained by individual modes, proving that the common annual signal accounts for 16, 24 and 68% of the total variance of non-tidal ocean, atmospheric and hydrological loading models, respectively. Having removed the common environmental MSSA seasonal curve from the corresponding GPS position time series, we found that the residual station-specific annual curve modelled with the least-squares estimation has the amplitude of maximum 2 mm. This means that the environmental loading models underestimate the seasonalities observed by the GPS system. The remaining signal present in the seasonal frequency band arises from the systematic errors which are not of common environmental or geophysical origin. Using common mode error (CME) estimates, we showed that the direct removal of environmental loading models from the GPS series causes an artificial loss in the CME power spectra between 10 and 80 cycles per year. When environmental effect is removed from GPS series with MSSA curves, no influence on the character of spectra of CME estimates was noticed.

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Section: Discussionmentioning

confidence: 92%

Multichannel Singular Spectrum Analysis in the Estimates of Common Environmental Effects Affecting GPS Observations

Gruszczyńska

Rosat

Kłos

et al. 2018

Pageoph Topical Volumes

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“…As was previously shown, the assumption on white-noise-only leads to an underestimation of velocity uncertainty of several times [32,54], as the covariance matrix of observations is created based on the amplitude of white-noise-only a and the identity matrix I, as in:…”

Section: Methodsmentioning

confidence: 99%

“…Bos et al [31] considered this problem further and proved that adding a white plus power-law noise model causes the accuracy of the linear trend to decrease. Recently, Klos et al [32] demonstrated that this decrease is directly related to the type of power-law noise added, which can be nicely summarized that any of the time series components which have been un-or mis-modelled will influence the value of velocity along with its uncertainty.…”

Section: Introductionmentioning

confidence: 98%

Optimal Strategy of a GPS Position Time Series Analysis for Post-Glacial Rebound Investigation in Europe

2019

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We describe a comprehensive analysis of the 469 European Global Positioning System (GPS) vertical position time series. The assumptions we present should be employed to perform the post-glacial rebound (PGR)-oriented comparison. We prove that the proper treatment of either deterministic or stochastic components of the time series is indispensable to obtain reliable vertical velocities along with their uncertainties. The statistical significance of the vertical velocities is examined; due to their small vertical rates, 172 velocities from central and western Europe are found to fall below their uncertainties and excluded from analyses. The GPS vertical velocities reach the maximum values for Scandinavia with the maximal uplift equal to 11.0 mm/yr. Moreover, a comparison between the GPS-derived rates and the present-day motion predicted by the newest Glacial Isostatic Adjustment (GIA) ICE-6G_C (VM5a) model is provided. We prove that these rates agree at a 0.5 mm/yr level on average; the Sweden area with the most significant uplift observed agrees within 0.2 mm/yr. The largest discrepancies between GIA-predicted uplift and the GPS vertical rates are found for Svalbard; the difference is equal to 6.7 mm/yr and arises mainly from the present-day ice melting. The GPS-derived vertical rates estimated for the southern coast of the Baltic Sea are systematically underestimated by the GIA prediction by up to 2 mm/yr. The northern British Isles vertical rates are overestimated by the GIA model by about 0.5 mm/yr. The area of the Netherlands and the coastal area of Belgium are both subsiding faster than it is predicted by the GIA model of around 1 mm/yr. The inland part of Belgium, Luxemburg and the western part of Germany show strong positive velocities when compared to the GIA model. Most of these stations uplift of more than 1 mm/yr. It may be caused by present-day elastic deformation due to terrestrial hydrology, especially for Rhein basin, or non-tidal atmospheric loading, for Belgium and Luxembourg.

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“…The Crustal Movement Observation Network of China (CMONOC) is an important scientific infrastructure in China, which initially contained 27 Continuous Global Positioning System (GPS) stations in 1999 and then was extended to 260 GPS stations since 2011. CMONOC has provided useful datasets to facilitate the investigations of various geophysical phenomena, such as global plate motion [1], regional tectonic deformation [2], uplift of the Tibetan Plateau [3], land subsidence of Furthermore, periodic signals contribute to the temporal noise in GPS position time series [35,36] and both of them can be affected by CMC filtering. Therefore, CMC filtering has a further effect on velocity estimates and their uncertainties.…”

Section: Introductionmentioning

confidence: 99%

Effects of Spatiotemporal Filtering on the Periodic Signals and Noise in the GPS Position Time Series of the Crustal Movement Observation Network of China

et al. 2018

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Analysis of Global Positioning System (GPS) position time series and its common mode components (CMC) is very important for the investigation of GPS technique error, the evaluation of environmental loading effects, and the estimation of a realistic and unbiased GPS velocity field for geodynamic applications. In this paper, we homogeneously processed the daily observations of 231 Crustal Movement Observation Network of China (CMONOC) Continuous GPS stations to obtain their position time series. Then, we filtered out the CMC and evaluated its effects on the periodic signals and noise for the CMONOC time series. Results show that, with CMC filtering, peaks in the stacked power spectra can be reduced at draconitic harmonics up to the 14th, supporting the point that the draconitic signal is spatially correlated. With the colored noise suppressed by CMC filtering, the velocity uncertainty estimates for both of the two subnetworks, CMONOC-I (≈16.5 years) and CMONOC-II (≈4.6 years), are reduced significantly. However, the CMONOC-II stations obtain greater reduction ratios in velocity uncertainty estimates with average values of 33%, 38%, and 54% for the north, east, and up components. These results indicate that CMC filtering can suppress the colored noise amplitudes and improve the precision of velocity estimates. Therefore, a unified, realistic, and three-dimensional CMONOC GPS velocity field estimated with the consideration of colored noise is given. Furthermore, contributions of environmental loading to the vertical CMC are also investigated and discussed. We find that the vertical CMC are reduced at 224 of the 231 CMONOC stations and 170 of them are with a root mean square (RMS) reduction ratio of CMC larger than 10%, confirming that environmental loading is one of the sources of CMC for the CMONOC height time series.

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On the combined effect of periodic signals and colored noise on velocity uncertainties

Cited by 79 publications

References 64 publications

Multichannel Singular Spectrum Analysis in the Estimates of Common Environmental Effects Affecting GPS Observations

Multichannel Singular Spectrum Analysis in the Estimates of Common Environmental Effects Affecting GPS Observations

Optimal Strategy of a GPS Position Time Series Analysis for Post-Glacial Rebound Investigation in Europe

Effects of Spatiotemporal Filtering on the Periodic Signals and Noise in the GPS Position Time Series of the Crustal Movement Observation Network of China

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