Estimates of the information provided by GPS slant data observed in Germany regarding tomographic applications

Bender, Michael A.; Dick, Galina; Wickert, Jens; Ramatschi, Markus; Ge, Maorong; Gendt, G.; Rothacher, M.; Raabe, Armin; Tetzlaff, G.

doi:10.1029/2008jd011008

Cited by 32 publications

(35 citation statements)

References 26 publications

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“…Five of the solutions used GPS and GLONASS observations and six solutions used GPS-only observations; five of them are based on DD observations and six of them are computed using zero-difference data in PPP analysis. More information about TUW solutions can be found in Möller et al (2016), about GFZ in Bender et al (2009 and Deng et al (2011) and about CNAM in Morel et al (2014). For ROB, TUO and WUE solutions we refer the reader to Dach et al (2015).…”

Section: Std Retrievals From Gnss Observationsmentioning

confidence: 99%

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Inter-technique validation of tropospheric slant total delays

et al. 2017

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Abstract. An extensive validation of line-of-sight tropospheric slant total delays (STD) from Global Navigation Satellite Systems (GNSS), ray tracing in numerical weather prediction model (NWM) fields and microwave water vapour radiometer (WVR) is presented. Ten GNSS reference stations, including collocated sites, and almost 2 months of data from 2013, including severe weather events were used for comparison. Seven institutions delivered their STDs based on GNSS observations processed using 5 software programs and 11 strategies enabling to compare rather different solutions and to assess the impact of several aspects of the processing strategy. STDs from NWM ray tracing came from three institutions using three different NWMs and ray-tracing software. Inter-techniques evaluations demonstrated a good mutual agreement of various GNSS STD solutions compared to NWM and WVR STDs. The mean bias among GNSS solutions not considering post-fit residuals in STDs was −0.6 mm for STDs scaled in the zenith direction and the mean standard deviation was 3.7 mm. Standard deviations of comparisons between GNSS and NWM ray-tracing solutions were typically 10 mm ± 2 mm (scaled in the zenith direction), depending on the NWM model and the GNSS station. Comparing GNSS versus WVR STDs reached standard deviations of 12 mm ± 2 mm also scaled in the zenith direction. Impacts of raw GNSS post-fit residuals and cleaned residuals on optimal reconstructing of GNSS STDs were evaluated at intertechnique comparison and for GNSS at collocated sites. The use of raw post-fit residuals is not generally recommended as they might contain strong systematic effects, as demonstrated in the case of station LDB0. Simplified STDs reconstructed only from estimated GNSS tropospheric parameters, i.e. without applying post-fit residuals, performed the best in all the comparisons; however, it obviously missed part of tropospheric signals due to non-linear temporal and spatial variations in the troposphere. Although the post-fit residuals cleaned of visible systematic errors generally showed a slightly worse performance, they contained significant tropospheric signal on top of the simplified model. They are thus recommended for the reconstruction of STDs, particularly during high variability in the troposphere. Cleaned residuals also showed a stable performance during ordinary days while containing promising information about the troposphere at low-elevation angles.

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Section: Std Retrievals From Gnss Observationsmentioning

confidence: 99%

“…The GNSS tomography technique aiming at the three-dimensional reconstruction of the water vapour field (Flores et al, 2001) uses STDs as input data as well. Obviously, the quality of the tomography depends on both the accuracy of the STDs (Bender et al, 2009) and the observation geometry .…”

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confidence: 99%

Inter-technique validation of tropospheric slant total delays

et al. 2017

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“…Rohm (2012) studied the error sources and their propagation in tomography solution, and the topology of cofactor matrix shows the most significant influence on the final solution uncertainty. Meanwhile, research about the distributions of signal slant paths and their intersection points (Bender et al, 2009) demonstrated that the density of slants is maximum in the boundary layer while the intersection points distribute the most sparsely, which leads to poor topology of coefficient matrix for the estimated parameters in corresponding tomography level. Therefore it is necessary to introduce the surface water vapor measurements to overcome aforementioned disadvantage.…”

Section: P Jiang Et Al: Long-term Experiments In Hong Kongmentioning

confidence: 99%

Near real-time water vapor tomography using ground-based GPS and meteorological data: long-term experiment in Hong Kong

Jiang

Liu

et al. 2014

Ann. Geophys.

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Abstract.Water vapor tomography is a promising technique for reconstructing the 4-D moisture field, which is important to the weather forecasting and nowcasting as well as to the numerical weather prediction. A near real-time 4-D water vapor tomographic system is developed in this study. GPS slant water vapor (SWV) observations are derived by a sliding time window strategy using double-difference model and predicted orbits. Besides GPS SWV, surface water vapor measurements are also assimilated as real time observations into the tomographic system in order to improve the distribution of observations in the lowest layers of tomographic grid. A 1-year term experiment in Hong Kong was carried out. The feasibility of the GPS data processing strategy is demonstrated by the good agreement between the time series of GPS-derived Precipitable Water Vapor (PWV) and radio-sounding-derived PWV with a bias of 0.04 mm and a root-mean-square error (RMSE) of 1.75 mm. Using surface humidity observations in the tomographic system, the bias and RMSE between tomography and radiosonde data are decreased by half in the ground level, but such improved effects weaken gradually with the rise of altitude until becoming adverse above 4000 m. The overall bias is decreased from 0.17 to 0.13 g m −3 and RMSE is reduced from 1.43 to 1.28 g m −3 . By taking the correlation coefficient and RMSE between tomography and radiosonde individual profile as the statistical measures, quality of individual profile is also improved as the success rate of tomographic solution is increased from 44.44 to 63.82 % while the failure rate is reduced from 55.56 to 36.18 %.

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“…The size and location of the rectangular cubes are determined based on the distribution of GNSS signals only on the top boundary of the tomographic field -the rectangular cube that best fits the top boundary is adopted (Bastin et al, 2005;Bender et al, 2009;Champollion et al, 2005;Ding et al, 2017;Gradinarsky and Jarlemark, 2004;Hoyle, 2005;Rohm et al, 2014;Seko et al, 2000;Troller et al, 2006;Xia et al, 2013;Ye et al, 2016). In fact, the field that GNSS signals cover has roughly the shape of an upside-down cone, meaning that in the part near the edge of the cube, especially in the lower part, none of the GNSS signals cross through.…”

Section: Introductionmentioning

confidence: 99%

A new approach for GNSS tomography from a few GNSS stations

Ding

Zhang

et al. 2018

Atmos. Meas. Tech.

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Abstract. The determination of the distribution of water vapor in the atmosphere plays an important role in the atmospheric monitoring. Global Navigation Satellite Systems (GNSS) tomography can be used to construct 3-D distribution of water vapor over the field covered by a GNSS network with high temporal and spatial resolutions. In current tomographic approaches, a pre-set fixed rectangular field that roughly covers the area of the distribution of the GNSS signals on the top plane of the tomographic field is commonly used for all tomographic epochs. Due to too many unknown parameters needing to be estimated, the accuracy of the tomographic solution degrades. Another issue of these approaches is their unsuitability for GNSS networks with a low number of stations, as the shape of the field covered by the GNSS signals is, in fact, roughly that of an upsidedown cone rather than the rectangular cube as the pre-set. In this study, a new approach for determination of tomographic fields fitting the real distribution of GNSS signals on different tomographic planes at different tomographic epochs and also for discretization of the tomographic fields based on the perimeter of the tomographic boundary on the plane and meshing techniques is proposed. The new approach was tested using three stations from the Hong Kong GNSS network and validated by comparing the tomographic results against radiosonde data from King's Park Meteorological Station (HKKP) during the one month period of May 2015. Results indicated that the new approach is feasible for a three-station GNSS network tomography. This is significant due to the fact that the conventional approaches cannot even solve a network tomography from a few stations.

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Estimates of the information provided by GPS slant data observed in Germany regarding tomographic applications

Cited by 32 publications

References 26 publications

Inter-technique validation of tropospheric slant total delays

Inter-technique validation of tropospheric slant total delays

Near real-time water vapor tomography using ground-based GPS and meteorological data: long-term experiment in Hong Kong

A new approach for GNSS tomography from a few GNSS stations

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