Ground surface elevation changes estimated using multiple GNSS signal-to-noise ratio observations over permafrost area

2020 ◽  
Author(s):  
Yufeng Hu
Keyword(s):  
Time Series ◽  
Signal To Noise Ratio ◽  
Model Fitting ◽  
Ground Surface ◽  
Composite Model ◽  
Surface Elevation ◽  
Signal To Noise ◽  
Frozen Ground ◽  
Elevation Changes ◽  
Noise Ratio

<p>The ground surface over permafrost area subsides and uplifts annually due to the seasonal thawing and freezing of active layer. GPS Interferometric Reflectometry (GPS-IR) has been successfully applied to the signal-to-noise ratio (SNR) observations to retrieve elevation changes of frozen ground surface at Barrow, Alaska. In this study, the method is extended to include GLONASS and Galileo SNR observations. Based on the multiple SNR observations collected by SG27 in Barrow, the multiple GNSS-IR time series of ground surface elevation changes during snow-free days from late June to middle October in year 2018 are obtained at daily intervals. All the three time series show a similar pattern that the ground subsided in thaw season followed by uplifts in freezing season, which is well characterized by the previous composite physical model using thermal indexes. Fitted with the composite model, the amplitude of the GPS-derived elevation changes during the snow-free days is suggested to be 3.3 ± 0.2 cm. However, the time series of GLONASS-IR and Galileo-IR measurements are much noisier than that of GPS-IR due to their inconsistent daily satellite tracks. Applied with a specific strategy in the composite model fitting, the amplitudes of GLONASS- and Galileo-derived elevation changes are estimated to be 4.0 ± 0.3 cm and 3.9 ± 0.5 cm, respectively. Then, GLONASS-IR and Galileo-IR time series are reconstructed in turn with the fitting coefficients. Moreover, the occurrences of the short-term variations in time series of GNSS-IR measurements are found to coincidence with the precipitation events, indicating the hydrologic control on the movements of frozen ground surface. The results presented in this study show the feasibility to combine multiple GNSS to densely monitor frozen ground surface deformations, and provide an insight to understand the impacts of both thermal and hydrologic forces on the frozen ground dynamics.</p>

scholarly journals Decadal changes of surface elevation over permafrost area estimated using reflected GPS signals

2017 ◽  
Author(s):  
Lin Liu ◽  
Kristine M. Larson
Keyword(s):  
Signal To Noise Ratio ◽  
Ground Surface ◽  
Temporal Variations ◽  
Surface Elevation ◽  
Frozen Ground ◽  
Near Surface ◽  
Ratio Data ◽  
Long Time ◽  
Elevation Changes ◽  
Continuous Gps

Abstract. Conventional benchmark-based surveys and Global Positioning System (GPS) have been used to measure surface elevation changes over permafrost areas, usually once or a few times a year. Here we introduce a new method that uses reflected GPS signals to measure temporal changes of ground surface elevation due to dynamics of the active layer and near-surface permafrost. Applying the GPS interferometric reflectometry technique to the signal-to-noise-ratio data collected by a continuous GPS receiver mounted deep in permafrost in Barrow, Alaska, we can retrieve the vertical distance between the antenna and surface reflector under the antenna. Using this unique kind of observables, we obtain daily changes of surface elevation during July and August from 2004 to 2015. Our results show distinct temporal variations at three timescales: regular thaw settlement within each summer, strong inter-annual variability that is characterized by a sub-decadal subsidence trend followed by a brief uplift trend, and a secular subsidence trend of 0.26 ± 0.02 cm/year during 2004 and 2015. This method provides a new way to fully utilize data from continuous GPS sites in cold regions for studying dynamics of the frozen ground consistently and sustainably over a long time.

scholarly journals Decadal changes of surface elevation over permafrost area estimated using reflected GPS signals

2018 ◽  
Vol 12 (2) ◽  
pp. 477-489 ◽  
Author(s):  
Lin Liu ◽  
Kristine M. Larson
Keyword(s):  
Signal To Noise Ratio ◽  
Ground Surface ◽  
Temporal Variations ◽  
Surface Elevation ◽  
Frozen Ground ◽  
Near Surface ◽  
Long Time ◽  
Elevation Changes ◽  
Multipath Signal ◽  
Reflecting Surface

Abstract. Conventional benchmark-based survey and Global Positioning System (GPS) have been used to measure surface elevation changes over permafrost areas, usually once or a few times a year. Here we use reflected GPS signals to measure temporal changes of ground surface elevation due to dynamics of the active layer and near-surface permafrost. Applying the GPS interferometric reflectometry technique to the multipath signal-to-noise ratio data collected by a continuously operating GPS receiver mounted deep in permafrost in Barrow, Alaska, we can retrieve the vertical distance between the antenna and reflecting surface. Using this unique kind of observables, we obtain daily changes of surface elevation during July and August from 2004 to 2015. Our results show distinct temporal variations at three timescales: regular thaw settlement within each summer, strong interannual variability that is characterized by a sub-decadal subsidence trend followed by a brief uplift trend, and a secular subsidence trend of 0.26 ± 0.02 cm year−1 during 2004 and 2015. This method provides a new way to fully utilize data from continuously operating GPS sites in cold regions for studying dynamics of the frozen ground consistently and sustainably over a long time.

On the Signal-to-Noise Ratio in Real-Life Emotional Time Series

2021 ◽  
pp. 131-152
Author(s):  
Egon Dejonckheere ◽  
Merijn Mestdagh
Keyword(s):  
Time Series ◽  
Signal To Noise Ratio ◽  
Real Life ◽  
Signal To Noise ◽  
Noise Ratio

Brain activity detection by estimating the signal-to-noise ratio of fMRI time series using dynamic linear models

2015 ◽  
Vol 47 ◽  
pp. 205-211
Author(s):  
Alicia Quirós ◽  
Simon P. Wilson ◽  
Raquel Montes Diez ◽  
Ana Beatriz Solana ◽  
Juan Antonio Hernández Tamames
Keyword(s):  
Time Series ◽  
Linear Models ◽  
Signal To Noise Ratio ◽  
Brain Activity ◽  
Activity Detection ◽  
Signal To Noise ◽  
Dynamic Linear Models ◽  
Fmri Time Series ◽  
Noise Ratio

scholarly journals Temporal Behavior of Solar P-Modes from Gong and Golf Experiments

1998 ◽  
Vol 185 ◽  
pp. 227-228
Author(s):  
V.G. Gavryusev ◽  
E.A. Gavryuseva
Keyword(s):  
Time Series ◽  
Signal To Noise Ratio ◽  
Temporal Behavior ◽  
The Sun ◽  
Solar Oscillations ◽  
Signal To Noise ◽  
Data Set ◽  
Noise Ratio

We used the measurements of solar oscillations taken by GONG and GOLF experiments. The first set of data are the integrated images obtained from the complex GONG observations taken from June 10 of 1995 to January 7 of 1997, 578 days in total, referenced below as ts0 time series. Radial, dipole and quadrupole modes are well visible in this time series. The second data set is the GOLF time series obtained on-board SOHO mission from April 11, 1996 to June 22, 1997. GOLF observes the “Sun as a star”. This time series is similar to ts0 of GONG but of a better quality (better signal-to-noise ratio; uniform, practically uninterrupted data). Both experiments are significantly overlapped in time. Because of this the direct comparison between them is possible, and the effects visible in both observations support each other.

scholarly journals Estimations of uncertainties of frequencies

2015 ◽  
Vol 11 (A29A) ◽  
pp. 201-201
Author(s):  
Laurent Eyer ◽  
Jean-Marc Nicoletti ◽  
Stephan Morgenthaler
Keyword(s):  
Time Series ◽  
Light Curve ◽  
Frequency Estimation ◽  
Signal To Noise Ratio ◽  
Simulated Data ◽  
Signal To Noise ◽  
Periodic Signals ◽  
Noise Ratio ◽  
The Universe

AbstractDiverse variable phenomena in the Universe are periodic. Astonishingly many of the periodic signals present in stars have timescales coinciding with human ones (from minutes to years). The periods of signals often have to be deduced from time series which are irregularly sampled and sparse, furthermore correlations between the brightness measurements and their estimated uncertainties are common. The uncertainty on the frequency estimation is reviewed. We explore the astronomical and statistical literature, in both cases of regular and irregular samplings. The frequency uncertainty is depending on signal to noise ratio, the frequency, the observational timespan. The shape of the light curve should also intervene, since sharp features such as exoplanet transits, stellar eclipses, raising branches of pulsation stars give stringent constraints. We propose several procedures (parametric and nonparametric) to estimate the uncertainty on the frequency which are subsequently tested against simulated data to assess their performances.

scholarly journals GPS Interferometric Reflectometry measurements of ground surface elevation changes in permafrost areas in northern Canada

2019 ◽  
Author(s):  
Jiahua Zhang ◽  
Lin Liu ◽  
Yufeng Hu
Keyword(s):  
Surface Deformation ◽  
Surface Condition ◽  
Ground Surface ◽  
Surface Elevation ◽  
Frozen Ground ◽  
Northern Canada ◽  
Elevation Changes ◽  
Baker Lake ◽  
Resolute Bay ◽  
Broad Region

Abstract. Global Positioning System Interferometric Reflectometry (GPS-IR) is a relatively new technique which uses reflected GPS signals to measure surface elevation changes to study frozen ground dynamics. At present, more than 200 GPS stations are in continuous operation in the Northern Hemisphere permafrost areas. They were originally designed and maintained for tectonic and ionospheric studies. However, only one site in Barrow, Alaska has so far been used to study permafrost by GPS-IR. Moreover, GPS-IR has high requirements on ground surface condition, which needs to be open, flat, and homogeneous. In this study, we screen 3 major GPS networks in Canada and identify 12 out of 38 stations located in permafrost areas as useful ones where reliable reflectometry measurements can be obtained. We narrow our focus to 5 Canadian Active Control System stations and obtain their daily GPS-IR estimated surface elevation changes. We find that the ground surface subsided in Alert and Resolute Bay respectively by 0.79 ± 0.04 cm yr−1 (2012–2017) and 0.70 ± 0.02 cm yr−1 (2003–2014), but uplifted in Iqaluit by 0.35 ± 0.04 cm yr−1 (2010–2017). At the other two sites respectively in Repulse Bay and Baker Lake, the trends are not statistically significant. The linear trends of deformation were negatively correlated with those of the thaw indices in Alert, Resolute Bay, and Iqaluit. Furthermore, in Resolute Bay, we also find that the end-of-thaw elevations during 2003–2012 were highly negatively correlated with the square root of thaw indices. This study highlights multiple useful GPS stations in northern Canada, where multi-year, continuous, and daily GPS-IR estimated surface deformation can be obtained and used to study frozen ground dynamics at various temporal scales and across a broad region.

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