References of "Bingley, Richard"
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See detailGNSS Meteorology in Luxembourg
Ahmed, Furqan UL; Teferle, Felix Norman UL; Bingley, Richard et al

in Cahier Scientifique - Revue Technique Luxembourgeoise (2012), (1), 16-22

Atmospheric water vapour is a primary greenhouse gas and plays an important role in weather forecasting and climate monitoring. Global Navigation Satellite System (GNSS) signals experience a propagation ... [more ▼]

Atmospheric water vapour is a primary greenhouse gas and plays an important role in weather forecasting and climate monitoring. Global Navigation Satellite System (GNSS) signals experience a propagation delay, which is related to the amount of water vapour in the lower atmosphere. Hence GNSS observations can be processed to estimate this delay with millimetre-level accuracy and together with meteorological data can be used to compute the amount of atmospheric water vapour on various temporal and spatial scales. [less ▲]

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See detailFirst Zenith Total Delay and Integrated Water Vapour Estimates from the Near Real-Time GNSS Data Processing Systems at the University of Luxembourg
Ahmed, Furqan UL; Teferle, Felix Norman UL; Bingley, Richard

Poster (2012, March 16)

Since June 2011, the University of Luxembourg has started in collaboration with the University of Nottingham a PhD project entitled “The Potential of Precipitable Water Vapour Measurements using Global ... [more ▼]

Since June 2011, the University of Luxembourg has started in collaboration with the University of Nottingham a PhD project entitled “The Potential of Precipitable Water Vapour Measurements using Global Navigation Satellite Systems in Luxembourg (PWVLUX)”, which is funded by the Fonds National de la Recherche (FNR) Luxembourg. The research objectives of the project are to study the potential for improvements in short-term weather forecasts and long-term climate variability for Luxembourg and the Greater Region by inclusion of the observations from Global Navigation Satellite Systems (GNSS) in the existing techniques. To achieve the research objectives, systems are being set up at the University of Luxembourg which process ground-based GNSS data for the provision of zenith total delay (ZTD) and integrated water vapour (IWV) estimates in real-time, near real-time and post-processing modes. Through collaboration with the Administration du cadastre et de la topographie (Luxembourg) and the Service public de Wallonie (Belgium), the coverage of the available GNSS permanent networks is improved over the primary project area, although also data from other European and global networks are processed. The meteorological analysis of the PWVLUX products is supported through collaborations with the Meteorological Service of the Administration de la navigation aérienne and the EUMETNET project E-GVAP. In this study we present the first ZTD and IWV estimates obtained from the near-real time processing systems in development at the University of Luxembourg. In a preliminary evaluation we compared their performance to some state-of-the-art systems already in operation and found that the ZTD estimates agree up to a few millimeters and the IWV estimates agree at the sub-millimeter level. [less ▲]

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See detailThe Effect of Processing Technique and Reference Frame Definition on Noise in CGPS Position Time Series
Teferle, Felix Norman UL; Williams, Simon; Kierulf, Halfdan et al

Poster (2005)

In this presentation we investigate the effects of GPS processing techniques and strategies, and the related reference frame realization, on the stochastic properties of continuous GPS (CGPS) position ... [more ▼]

In this presentation we investigate the effects of GPS processing techniques and strategies, and the related reference frame realization, on the stochastic properties of continuous GPS (CGPS) position time series. It was of particular interest to establish whether and how different GPS processing techniques and strategies, e.g. double differencing (DD) and precise point positioning (PPP), and the use of different orbit and clock products, and/or the definition of the reference frame (partly dependent on the applied strategy) affect the colored noise content of time series. We used CGPS position time series from 15 different solutions obtained from seven different analysis centers as part of the European Sea Level Service - Research Infrastructure project (ESEAS-RI) using the GIPSY OASIS II, GAMIT and Bernese GPS softwares. All time series analyzed have at least three years of data for the period between 2000 and 2005. Furthermore, a selected set of position time series was also analyzed using Empirical Orthogonal Function (EOF) analysis. The noise content of the first 15 modes, representing the solution-specific common mode time series for each of the selected solutions were then also investigated for colored noise. Using Maximum Likelihood Estimation (MLE) a white, a white plus flicker, a white plus power- law and a white plus first-order Gauss-Markov (FOGM) noise model were fitted to the position and EOF time series data. For both the position and EOF time series the parameter model included a constant, a rate and harmonic terms with annual, semi-annual, 4- monthly, 3-monthly, 2.4-monthly and 13.66 day periods. Position jumps were modeled at logged epochs or at visible discontinuities in the time series. The MLE showed that in most cases the best fitting noise model is a combination of white plus power-law noise with average spectral indices in the range between -0.5 and -1.4. This model is closely followed by the combination of white plus flicker and white plus FOGM noise. The noise properties of the EOF time series follow predominantly a white plus power-law character, with the first few modes indicating a white plus flicker noise behavior. In general, DD solutions contain less noise than PPP solutions and that regional reference frame definitions further reduce the amount of noise in the time series. [less ▲]

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