Deriving common seasonal signals in GPS position time series: by using multichannel singular spectrum analysis

Gruszczyńska, M

doi:10.13168/agg.2017.0010

Cited by 13 publications

(12 citation statements)

References 57 publications

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“…Zhu et al (2016) used the MSSA approach to investigate the inter-annual oscillations in glacier mass change estimated from gravity recovery and climate experiment (GRACE) data in Central Asia. Gruszczynska et al (2017) compared the MSSA-, SSA-and least-squares estimationderived seasonal signals. They showed that the seasonal signals detected by MSSA are not affected by noise as much as the SSA-derived oscillations.…”

Section: Introductionmentioning

confidence: 99%

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

Gruszczyńska

Rosat

Kłos

et al. 2018

Pure Appl. Geophys.

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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: Introductionmentioning

confidence: 99%

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

Gruszczyńska

Rosat

Kłos

et al. 2018

Pure Appl. Geophys.

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“…Depending on the basic capability of decomposition, SSA can be applied in gross errors detection, interpolation and denoising of gravity data (Guo et al 2018a, b;Yu et al 2018). The main calculation steps of SSA are given below according to the research of Golyandina and Zhigljavsky (2013).…”

Section: Singular Spectrum Analysismentioning

confidence: 99%

“…Selection of the proper window length depends on the problem in hand, and on preliminary information about the time series. In the general case no universal rules can be given for the selection of the window length (Golyandina et al 2001). But there is a recommendation that the windows length is generally chosen as the common multiple of the known periods (Kondrashov et al 2010;Wang et al 2019).…”

Section: Singular Spectrum Analysismentioning

confidence: 99%

Gravity tides extracted from SSA-denoised superconducting gravity data with the harmonic analysis: a case study at Wuhan station, China

et al. 2020

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Superconducting gravimetry is one main technique to determine the gravity tides. In superconducting gravimeter (SG) measurement, the gravity tides is affected by the gross errors (including spikes and severe deviations and mainly caused by instrument problems and earthquakes) and noise (caused due to the internal structure of SG instrument and measurement environment) in SG data. The singular spectrum analysis (SSA) method was proposed to correct and denoise SG data. Then the harmonic analysis method is used to precisely extract the gravity tides from SSA-denoised SG data. The SG data at Wuhan station of China are used in the case study. The results show that the accuracies of tidal amplitude factors, phase differences and amplitudes of most wave groups determined from SSA-denoised SG data by the harmonic analysis were improved significantly. The standard deviation of residuals between the synthetic gravity tides obtained by harmonic analysis of SSA-denoised SG data and theoretical gravity tides is 0.0096 μGal (1 μGal = 10 −8 m s −2 ), and is 0.1772 μGal while replacing the SSA-denoised SG data from the un-denoised SG data. The Akaike's Bayesian Information Criterion value of harmonic analysis on SSAdenoised SG data is better than that from un-denoised SG data, which indicates that SSA denoising on SG data can improve the accuracy of harmonic analysis results. The root mean square of gravity residuals obtained by harmonic analysis of SSA-denoised SG data is 0.0019 μGal, and is 0.2275 μGal when replacing the SSA-denoised SG data from the un-denoised SG data. The result shows that SSA can effectively eliminate most of gross errors and noise existing in the SG data, and improve accuracy of the gravity tides with the harmonic analysis.

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“…Accordingly, this periodic signal is almost offset at annual speeds. Periodic signals arise under the influence of various factors (Dong et al, 2002;Gruszczynska et al, 2017;Tretyak et al, 2015). As periodic oscillations are practically constant, they do not appear at the average velocities of vertical movements determined on the basis of long-term data processing, but the accuracy of velocity determination is different.…”

Section: The Purpose and The Task Of The Researchmentioning

confidence: 99%

The research of interrelation between seismic activity and modern vertical movements of the European permanent GNNS-stations

Tretyak¹

2018

Acta Geodynamica Et Geomaterialia

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Based on experimental studies using the "integral velocity index of the vertical displacement of the territory" and criterion of generalized seismicity, a close functional relationship was found between two parameters of different physical nature: seismic activity and altitude displacements of the Earth's surface in Europe. The mathematical correlation between the generalized parameters of the velocity altitude displacements on the territory and seismic activity is established according to seismic and GNSS stations for the period from 2000-2011 for the areas in Europe with close correlation between seismicity and velocity of vertical movements of the Earth's surface. ARTICLE INFO

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Deriving common seasonal signals in GPS position time series: by using multichannel singular spectrum analysis

Cited by 13 publications

References 57 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

Gravity tides extracted from SSA-denoised superconducting gravity data with the harmonic analysis: a case study at Wuhan station, China

The research of interrelation between seismic activity and modern vertical movements of the European permanent GNNS-stations

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