scholarly journals Analysis and Discussion on the Optimal Noise Model of Global GNSS Long-Term Coordinate Series Considering Hydrological Loading

2021 ◽  
Vol 13 (3) ◽  
pp. 431
Author(s):  
Yuefan He ◽  
Guigen Nie ◽  
Shuguang Wu ◽  
Haiyang Li
Keyword(s):  
White Noise ◽  
Flicker Noise ◽  
Noise Analysis ◽  
Vertical Direction ◽  
Noise Model ◽  
Series Data ◽  
Noise Power ◽  
The Impact ◽  
Noise Models

The displacement of Global Navigation Satellite System (GNSS) station contains the information of surface elastic deformation caused by the variation of land water reserves. This paper selects the long-term coordinate series data of 671 International GNSS Service (IGS) reference stations distributed globally under the framework of World Geodetic System 1984 (WGS84) from 2000 to 2021. Different noise model combinations are used for noise analysis, and the optimal noise model for each station before and after hydrologic loading correction is calculated. The results show that the noise models of global IGS reference stations are diverse, and each component has different optimal noise model characteristics, mainly white noise + flicker noise (WN+FN), generalized Gauss–Markov noise (GGM) and white noise + power law noise (WN+PL). Through specific analysis between the optimal noise model and the time series velocity of the station, it is found that the maximum influence value of the vertical velocity can reach 1.8 mm when hydrological loading is considered. Different complex noise models also have a certain influence on the linear velocity and velocity uncertainty of the station. Among them, the influence of white noise + random walking noise is relatively obvious, and its maximum influence value in the elevation direction can reach over 2 mm/year. When studying the impact of hydrological loading correction on the periodicity of the coordinate series, it is concluded whether the hydrological loading is calculated or not, and the GNSS long-term coordinate series has obvious annual and semi-annual amplitude changes, which are most obvious in the vertical direction, up to 16.48 mm.

scholarly journals Noise behavior in CGPS position time series: the eastern North America case study

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
M. A. Goudarzi ◽  
M. Cocard ◽  
R. Santerre
Keyword(s):  
Time Series ◽  
Random Walk ◽  
North America ◽  
White Noise ◽  
Flicker Noise ◽  
Noise Model ◽  
Eastern North America ◽  
Position Time Series ◽  
White Noise Model ◽  
Noise Models

AbstractWe analyzed the noise characteristics of 112 continuously operating GPS stations in eastern North America using the Spectral Analysis and the Maximum Likelihood Estimation (MLE) methods. Results of both methods show that the combination ofwhite plus flicker noise is the best model for describing the stochastic part of the position time series. We explored this further using the MLE in the time domain by testing noise models of (a) powerlaw, (b)white, (c)white plus flicker, (d)white plus randomwalk, and (e) white plus flicker plus random-walk. The results show that amplitudes of all noise models are smallest in the north direction and largest in the vertical direction. While amplitudes of white noise model in (c–e) are almost equal across the study area, they are prevailed by the flicker and Random-walk noise for all directions. Assuming flicker noise model increases uncertainties of the estimated velocities by a factor of 5–38 compared to the white noise model.

scholarly journals Spatiotemporal Filtering and Noise Analysis for Regional GNSS Network in Antarctica Using Independent Component Analysis

2019 ◽  
Vol 11 (4) ◽  
pp. 386 ◽  
Author(s):  
Wenhao Li ◽  
Fei Li ◽  
Shengkai Zhang ◽  
Jintao Lei ◽  
Qingchuan Zhang ◽  
...  
Keyword(s):  
Time Series ◽  
Independent Component Analysis ◽  
White Noise ◽  
Flicker Noise ◽  
Component Analysis ◽  
Independent Component ◽  
Noise Model ◽  
Residual Time ◽  
Noise Characteristics ◽  
Noise Models

The common mode error (CME) and optimal noise model are the two most important factors affecting the accuracy of time series in regional Global Navigation Satellite System (GNSS) networks. Removing the CME and selecting the optimal noise model can effectively improve the accuracy of GNSS coordinate time series. The CME, a major source of error, is related to the spatiotemporal distribution; hence, its detrimental effects on time series can be effectively reduced through spatial filtering. Independent component analysis (ICA) is used to filter the time series recorded by 79 GPS stations in Antarctica from 2010 to 2018. After removing stations exhibiting strong local effects using their spatial responses, the filtering results of residual time series derived from principal component analysis (PCA) and ICA are compared and analyzed. The Akaike information criterion (AIC) is then used to determine the optimal noise model of the GPS time series before and after ICA/PCA filtering. The results show that ICA is superior to PCA regarding both the filter results and the consistency of the optimal noise model. In terms of the filtering results, ICA can extract multisource error signals. After ICA filtering, the root mean square (RMS) values of the residual time series are reduced by 14.45%, 8.97%, and 13.27% in the east (E), north (N), and vertical (U) components, respectively, and the associated speed uncertainties are reduced by 13.50%, 8.06% and 11.82%, respectively. Furthermore, different GNSS time series in Antarctica have different optimal noise models with different noise characteristics in different components. The main noise models are the white noise plus flicker noise (WN+FN) and white noise plus power law noise (WN+PN) models. Additionally, the spectrum index of most PN is close to that of FN. Finally, there are more stations with consistent optimal noise models after ICA filtering than there are after PCA filtering.

scholarly journals Common mode signals and vertical velocities in the great Alpine area from GNSS data

2021 ◽  
Author(s):  
Francesco Pintori ◽  
Enrico Serpelloni ◽  
Adriano Gualandi
Keyword(s):  
Time Series ◽  
White Noise ◽  
Vertical Direction ◽  
Noise Model ◽  
Tectonic Deformation ◽  
European Alps ◽  
Atmospheric Loading ◽  
Vertical Ground ◽  
The Impact ◽  
Ground Displacements

Abstract. We study time series of vertical ground displacements from continuous GNSS stations to investigate the spatial and temporal contribution of different geophysical processes to the time-varying displacements that are superimposed on vertical linear trends across the European Alps. We apply a multivariate statistics-based blind source separation algorithm to both GNSS displacement time series and to ground displacements associated with atmospheric and hydrological loading processes, as obtained from global reanalysis models. This allows us to associate each retrieved geodetic vertical deformation signal with a corresponding forcing process. Atmospheric loading is the most important one, reaching amplitudes larger than 2 cm. Besides atmospheric loading, seasonal displacements with amplitudes of about 1 cm are associated with temperature-related processes and with hydrological loading. We find that both temperature and hydrological loading cause peculiar spatial features of GNSS ground displacements. For example, temperature-related seasonal displacements show different behaviour at sites in the plains and in the mountains. Atmospheric and hydrological loading, besides the first-order spatially uniform feature, are associated also with NS and EW displacement gradients. We filter out signals associated with non-tectonic deformation from the raw time series to study their impact on both the estimated noise and linear rates in the vertical direction. While the impact on rates appears rather limited, given also the long-time span of the time-series considered in this work, the uncertainties estimated from filtered time-series assuming a power law + white noise model are significantly reduced, with an important increase in white noise contributions to the total noise budget. Finally, we present the filtered velocity field and show how vertical ground velocities are positively correlated with topographic features of the Alps.

scholarly journals Assessing Stream-Aquifer Connectivity in a Coastal California Watershed

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 416
Author(s):  
Bwalya Malama ◽  
Devin Pritchard-Peterson ◽  
John J. Jasbinsek ◽  
Christopher Surfleet
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Water Level ◽  
Time Series Data ◽  
Series Data ◽  
Low Permeability ◽  
Pumping Tests ◽  
Stream Flows ◽  
The Impact

We report the results of field and laboratory investigations of stream-aquifer interactions in a watershed along the California coast to assess the impact of groundwater pumping for irrigation on stream flows. The methods used include subsurface sediment sampling using direct-push drilling, laboratory permeability and particle size analyses of sediment, piezometer installation and instrumentation, stream discharge and stage monitoring, pumping tests for aquifer characterization, resistivity surveys, and long-term passive monitoring of stream stage and groundwater levels. Spectral analysis of long-term water level data was used to assess correlation between stream and groundwater level time series data. The investigations revealed the presence of a thin low permeability silt-clay aquitard unit between the main aquifer and the stream. This suggested a three layer conceptual model of the subsurface comprising unconfined and confined aquifers separated by an aquitard layer. This was broadly confirmed by resistivity surveys and pumping tests, the latter of which indicated the occurrence of leakage across the aquitard. The aquitard was determined to be 2–3 orders of magnitude less permeable than the aquifer, which is indicative of weak stream-aquifer connectivity and was confirmed by spectral analysis of stream-aquifer water level time series. The results illustrate the importance of site-specific investigations and suggest that even in systems where the stream is not in direct hydraulic contact with the producing aquifer, long-term stream depletion can occur due to leakage across low permeability units. This has implications for management of stream flows, groundwater abstraction, and water resources management during prolonged periods of drought.

scholarly journals Characterizing the γ-ray long-term variability of PKS 2155−304 with H.E.S.S. and Fermi-LAT

2017 ◽  
Vol 598 ◽  
pp. A39 ◽  
Author(s):  
◽  
H. Abdalla ◽  
A. Abramowski ◽  
F. Aharonian ◽  
F. Ait Benkhali ◽  
...  
Keyword(s):  
Flicker Noise ◽  
High Energy ◽  
Long Term Results ◽  
Noise Power ◽  
Quiescent State ◽  
Physical Processes ◽  
Bl Lac Objects ◽  
Power Spectral ◽  
Bl Lac

Studying the temporal variability of BL Lac objects at the highest energies provides unique insights into the extreme physical processes occurring in relativistic jets and in the vicinity of super-massive black holes. To this end, the long-term variability of the BL Lac object PKS 2155−304 is analyzed in the high (HE, 100 MeV < E < 300 GeV) and very high energy (VHE, E > 200 GeV) γ-ray domain. Over the course of ~9 yr of H.E.S.S. observations the VHE light curve in the quiescent state is consistent with a log-normal behavior. The VHE variability in this state is well described by flicker noise (power-spectral-density index βVHE = 1.10+0.10-0.13) on timescales larger than one day. An analysis of ~5.5 yr of HE Fermi-LAT data gives consistent results (βHE = 1.20+0.21-0.23, on timescales larger than 10 days) compatible with the VHE findings. The HE and VHE power spectral densities show a scale invariance across the probed time ranges. A direct linear correlation between the VHE and HE fluxes could neither be excluded nor firmly established. These long-term-variability properties are discussed and compared to the red noise behavior (β ~ 2) seen on shorter timescales during VHE-flaring states. The difference in power spectral noise behavior at VHE energies during quiescent and flaring states provides evidence that these states are influenced by different physical processes, while the compatibility of the HE and VHE long-term results is suggestive of a common physical link as it might be introduced by an underlying jet-disk connection.

Welfare Use in Japan: Trends and Determinants

2007 ◽  
pp. 88
Author(s):  
Wataru Suzuki ◽  
Yanfei Zhou
Keyword(s):  
Time Series ◽  
Longitudinal Data ◽  
Time Series Data ◽  
Positive Impact ◽  
Series Data ◽  
Negative Effects ◽  
Long Time ◽  
Welfare Use ◽  
The Impact

This article represents the first step in filling a large gap in knowledge concerning why Public Assistance (PA) use recently rose so fast in Japan. Specifically, we try to address this problem not only by performing a Blanchard and Quah decomposition on long-term monthly time series data (1960:04-2006:10), but also by estimating prefecturelevel longitudinal data. Two interesting findings emerge from the time series analysis. The first is that permanent shock imposes a continuously positive impact on the PA rate and is the main driving factor behind the recent increase in welfare use. The second finding is that the impact of temporary shock will last for a long time. The rate of the use of welfare is quite rigid because even if the PA rate rises due to temporary shocks, it takes about 8 or 9 years for it to regain its normal level. On the other hand, estimations of prefecture-level longitudinal data indicate that the Financial Capability Index (FCI) of the local government2 and minimum wage both impose negative effects on the PA rate. We also find that the rapid aging of Japan's population presents a permanent shock in practice, which makes it the most prominent contribution to surging welfare use.

Does Public Debt Service Expenditure Crowd-Out Economic Growth? Empirical Evidence from an African Developing Country

2019 ◽  
Vol 64 (3) ◽  
pp. 23-38
Author(s):  
Talknice Saungweme ◽  
Nicholas M. Odhiambo
Keyword(s):  
Economic Growth ◽  
Public Debt ◽  
Time Series Data ◽  
Policy Formulation ◽  
Debt Service ◽  
Series Data ◽  
Long Run ◽  
Short Run ◽  
The Impact

Abstract This paper contributes to the ongoing debate on the impact of public debt service on economic growth; and it provides an evidence-based approach to public policy formulation in Zimbabwe. The empirical analysis was performed by applying the autoregressive distributed lag (ARDL) technique to annual time-series data from 1970 to 2017. The study findings reveal that the impact of public debt service on economic growth in Zimbabwe is negative in the short run but positive in the long run. The results are suggestive of the existence of a crowding-out effect of public debt service in Zimbabwe in the short run and a crowding-in effect in the long run. In view of these findings, the government should consider fiscal and financial policies that promote a constant supply of long-term finance, long-term fixed investments, and extension of a government securities maturity structure so as to ensure sustainable short- and long-term public debt service expenditures. The study further recommends the strengthening of non-distortionary revenue mobilisation reforms to reduce market distortions and boost domestic investment.

scholarly journals The Impact of the COVID-19 Pandemic on Antibiotic Prescribing Trends in Outpatient Care: A Nationwide, Quasi-Experimental Approach

Antibiotics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1040
Author(s):  
Tânia Magalhães Silva ◽  
Marta Estrela ◽  
Eva Rebelo Gomes ◽  
Maria Piñeiro-Lamas ◽  
Adolfo Figueiras ◽  
...  
Keyword(s):  
Public Health ◽  
Outpatient Care ◽  
Experimental Approach ◽  
National Level ◽  
Series Data ◽  
Antibiotic Prescribing ◽  
Prescribing Trends ◽  
Quasi Experimental ◽  
The Impact

Coronavirus disease 2019 (COVID-19) has spread globally and is currently having a damaging impact on nearly all countries in the world. The implementation of stringent measures to stop COVID-19 dissemination had an influence on healthcare services and associated procedures, possibly causing antibiotic consumption fluctuations. This paper aims to evaluate the immediate and long-term impact of the COVID-19 pandemic on antibiotic prescribing trends in outpatient care of the Portuguese public health sector, including in primary healthcare centers and hospitals, as well as on specific antibiotic groups known to be closely associated with increased resistance. Segmented regression analysis with interrupted time series data was used to analyze whether the COVID-19 pandemic had an impact in antibiotic prescribing tendencies at a national level. The outcomes from this quasi-experimental approach demonstrate that, at the beginning of the pandemic, a significant, immediate decrease in the overall antibiotic prescribing trends was noticed in the context of outpatient care in Portugal, followed by a statistically non-significant fall over the long term. The data also showed a significant reduction in the prescription of particular antibiotic classes (antibiotics from the Watch group, 3rd-generation cephalosporins, fluoroquinolones, and clarithromycin) upon COVID-19 emergence. These findings revealed an important disruption in antibiotics prescribing caused by the current public health emergency.

scholarly journals The impact of bank-specific and macroeconomic variables on profitability of Islamic rural bank in Indonesia

2019 ◽  
Vol 5 (3) ◽  
Author(s):  
Muhammad Sanusi
Keyword(s):  
Banking Sector ◽  
Time Series Data ◽  
Series Data ◽  
Estimation Model ◽  
Policy Makers ◽  
Vector Error Correction ◽  
Macroeconomic Variables ◽  
Vector Error ◽  
The Impact

This paper investigates the impact of bank-specific and macroeconomic variables on the profitability of Islamic rural bank (BPRS) in Indonesia. Using monthly time series data from January 2010 - December 2018. The estimation model used is a vector error correction model to analyze the long-term and short-term relationships between bank-specific and macroeconomic variables on the profitability of Islamic rural bank. The results showed that CAR and LnTA had a significant positive relationship, while NPF, BOPO and IPI had a negative and significant relationship to the profitability of Islamic rural banks. But FDR and Inflation variables are not significantly related to the profitability of Islamic rural bank. The results leave implications for policy makers, investors and banking sector managers. Based on evidence that bank profitability is more influenced by internal banks (as specific as banks), this research can help Islamic rural banks to help them understand which factors are important to be analyzed to obtain higher profitability.

A Unified Explanation of gm/ID-Based Noise Analysis

2014 ◽  
Vol 24 (01) ◽  
pp. 1550010 ◽  
Author(s):  
Jack Ou ◽  
Pietro M. Ferreira
Keyword(s):  
Thermal Noise ◽  
Flicker Noise ◽  
Practical Implication ◽  
Noise Analysis ◽  
Drain Current ◽  
Corner Frequency ◽  
Noise Power ◽  
Noise Power Spectral Density ◽  
Power Spectral ◽  
The Relationship

We present an unified explanation of the transconductance-to-drain current (gm/ID)-based noise analysis in this paper. We show that both thermal noise coefficient (γ) and device noise corner frequency (f co ) are dependent on the gm/ID of a transistor. We derive expressions to demonstrate the relationship between the normalized noise power spectral density technique and the technique based on γ and f co . We conclude this letter with examples to demonstrate the practical implication of our study. Our results show that while both techniques discussed in this letter can be used to compute noise numerically, using γ and f co to separate thermal noise from flicker noise provides additional insight for optimizing noise.

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