scholarly journals Assessment of the Accuracy of the Saastamoinen Model and VMF1/VMF3 Mapping Functions with Respect to Ray-Tracing from Radiosonde Data in the Framework of GNSS Meteorology

2020 ◽  
Vol 12 (20) ◽  
pp. 3337
Author(s):  
Peng Feng ◽  
Fei Li ◽  
Jianguo Yan ◽  
Fangzhao Zhang ◽  
Jean-Pierre Barriot

In this paper, we assess, in the framework of Global Navigation Satellite System (GNSS) meteorology, the accuracy of GNSS propagation delays corresponding to the Saastamoinen zenith hydrostatic delay (ZHD) model and the Vienna Mapping function VMF1/VMF3 (hydrostatic and wet), with reference to radiosonde ray-tracing delays over a three-year period on 28 globally distributed sites. The results show that the Saastamoinen ZHD estimates have a mean root mean square (RMS) error of 1.7 mm with respect to the radiosonde. We also detected some seasonal signatures in these Saastamoinen ZHD estimates. This indicates that the Saastamoinen model, based on the hydrostatic assumption and the ground pressure, is insufficient to capture the full variability of the ZHD estimates over time with the accuracy needed for GNSS meteorology. Furthermore, we found that VMF3 slant hydrostatic delay (SHD) estimates outperform the corresponding VMF1 SHD estimates (equivalent SHD RMS error of 4.8 mm for VMF3 versus 7.1 mm for VMF1 at 5° elevation angle), with respect to the radiosonde SHD estimates. Unexpectedly, the situation is opposite for the VMF3 slant wet delay (SWD) estimates compared to VMF1 SWD estimates (equivalent SWD RMS error of 11.4 mm for VMF3 versus 7.0 mm for VMF1 at 5° elevation angle). Our general conclusion is that the joint approach using ZHD models and mapping functions must be revisited, at least in the framework of GNSS meteorology.

2013 ◽  
Vol 48 (4) ◽  
pp. 171-189
Author(s):  
A.H. Souri ◽  
M.A. Sharifi

Abstract The aim of this paper is to compare the validity of six recent symmetric mapping functions. The mapping function models the elevation angle dependence of the tropospheric delay. Niell Mapping Function (NMF), Vienna Mapping Function (VMF1), University of New Brunswick- VMF1 (UNB-VMF1) mapping functions, Global Mapping Function (GMF) and Global Pressure and Temperature (GPT2)/GMF are evaluated by using ray tracing through 25 radiosonde stations covering different climatic regions in one year. The ray-traced measurements are regarded as “ground truth”. The ray-tracing approach is performed for diverse elevation angle starting at 5° to 15°. The results for both hydrostatic and non-hydrostatic components of mapping functions support the efficiency of online-mapping functions. The latitudinal dependence of standard deviation for 5° is also demonstrated. Although all the tested mapping functions can provide satisfactory results when used for elevation angles above 15°, for high precision geodetic measurements, it is highly recommended that the online-mapping functions (UNBs and VMF1) be used.The results suggest that UNB models, like VMF have strengths and weaknesses and do not stand out as being consistently better or worse than the VMF1. The GPT2/GMF provided better accuracy than GMF and NMF. Since all of them do not require site specific data; therefore GPT2/GMF can be useful as regards its ease of use.


2019 ◽  
Vol 50 ◽  
pp. 1-7
Author(s):  
Daniel Landskron ◽  
Johannes Böhm ◽  
Thomas Klügel ◽  
Torben Schüler

Abstract. During the Continuous Very Long Baseline Interferometry (VLBI) Campaign 2017 (CONT17), carried out from 28 November through 12 December 2017, an extensive data set of atmospheric observations was acquired at the Geodetic Observatory Wettzell. In addition to in situ measurements of temperature, humidity, pressure or wind speed at the surface, radiosonde ascents yielded meteorological parameters continually up to 25 km height, and integrated water vapor (IWV) was obtained at several elevations and azimuths from a water vapor radiometer. Troposphere delays estimated from Global Navigation Satellite Systems (GNSS) observations plus comparative values from two different Numerical Weather Models (NWMs) complete the abundance of data. In this presentation, we compare these data sets to parameters of the Vienna Mapping Functions 1 and 3 (VMF1 & VMF3), which are based on NWM data by the ECMWF, and to estimates of VLBI analysis using the Vienna VLBI and Satellite Software (VieVS). On the one hand, we contrast the variety of troposphere delays in zenith direction with each other, while on the other hand we utilize radiosonde data and meteorological observations at the site to create local mapping functions which can then be compared to VMF3 and VMF1 at Wettzell. In general, we thus received very good accordance between the different solutions. Also in terms of the mapping functions, the local radiosonde mapping function is in consistence with VMF1 and VMF3 with differences less than 5 mm at 5∘ elevation.


2021 ◽  
Vol 13 (15) ◽  
pp. 3014
Author(s):  
Feng Wang ◽  
Dongkai Yang ◽  
Guodong Zhang ◽  
Jin Xing ◽  
Bo Zhang ◽  
...  

Sea surface height can be measured with the delay between reflected and direct global navigation satellite system (GNSS) signals. The arrival time of a feature point, such as the waveform peak, the peak of the derivative waveform, and the fraction of the peak waveform is not the true arrival time of the specular signal; there is a bias between them. This paper aims to analyze and calibrate the bias to improve the accuracy of sea surface height measured by using the reflected signals of GPS CA, Galileo E1b and BeiDou B1I. First, the influencing factors of the delay bias, including the elevation angle, receiver height, wind speed, pseudorandom noise (PRN) code of GPS CA, Galileo E1b and BeiDou B1I, and the down-looking antenna pattern are explored based on the Z-V model. The results show that (1) with increasing elevation angle, receiver height, and wind speed, the delay bias tends to decrease; (2) the impact of the PRN code is uncoupled from the elevation angle, receiver height, and wind speed, so the delay biases of Galileo E1b and BeiDou B1I can be derived from that of GPS CA by multiplication by the constants 0.32 and 0.54, respectively; and (3) the influence of the down-looking antenna pattern on the delay bias is lower than 1 m, which is less than that of other factors; hence, the effect of the down-looking antenna pattern is ignored in this paper. Second, an analytical model and a neural network are proposed based on the assumption that the influence of all factors on the delay bias are uncoupled and coupled, respectively, to calibrate the delay bias. The results of the simulation and experiment show that compared to the meter-level bias before the calibration, the calibrated bias decreases the decimeter level. Based on the fact that the specular points of several satellites are visible to the down-looking antenna, the multi-observation method is proposed to calibrate the bias for the case of unknown wind speed, and the same calibration results can be obtained when the proper combination of satellites is selected.


2017 ◽  
Vol 11 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Sobhy Abdel-Monam Younes

Background:The author compares several methods to map the a priori wet tropospheric delay of GNSS signals in Egypt from the zenith direction to lower elevations.Methods and Materials:The author compared the following mapping techniques against ray-traced delays computed for radiosonde profiles under the assumption of spherical symmetry: Saastamoinen, Hopfield, Black, Chao, Ifadis, Herring, Niell, Moffett, Black and Eisner and UNBabc mapping functions. Radiosonde data were computed from radiosonde stations at the Egyptian stations; in the south of Egypt, near the Mediterranean Sea, and near the Red Sea over a period of 5 years (2000-2005), most of the stations launched radiosonde twice daily, every day of the year. Moreover, data is received from the Egyptian Meteorology Authority.Results and Conclusion:The results indicate that currently, the saastamoinen mapping function should be used for all geodetic applications in Egypt, and if necessary, the Chao and Moffett mapping functions can serve as an acceptable replacement without introducing a significant bias into the station position.


2019 ◽  
Vol 37 (3) ◽  
pp. 429-446 ◽  
Author(s):  
Michal Kačmařík ◽  
Jan Douša ◽  
Florian Zus ◽  
Pavel Václavovic ◽  
Kyriakos Balidakis ◽  
...  

Abstract. An analysis of processing settings impacts on estimated tropospheric gradients is presented. The study is based on the benchmark data set collected within the COST GNSS4SWEC action with observations from 430 Global Navigation Satellite Systems (GNSS) reference stations in central Europe for May and June 2013. Tropospheric gradients were estimated in eight different variants of GNSS data processing using precise point positioning (PPP) with the G-Nut/Tefnut software. The impacts of the gradient mapping function, elevation cut-off angle, GNSS constellation, observation elevation-dependent weighting and real-time versus post-processing mode were assessed by comparing the variants by each to other and by evaluating them with respect to tropospheric gradients derived from two numerical weather models (NWMs). Tropospheric gradients estimated in post-processing GNSS solutions using final products were in good agreement with NWM outputs. The quality of high-resolution gradients estimated in (near-)real-time PPP analysis still remains a challenging task due to the quality of the real-time orbit and clock corrections. Comparisons of GNSS and NWM gradients suggest the 3∘ elevation angle cut-off and GPS+GLONASS constellation for obtaining optimal gradient estimates provided precise models for antenna-phase centre offsets and variations, and tropospheric mapping functions are applied for low-elevation observations. Finally, systematic errors can affect the gradient components solely due to the use of different gradient mapping functions, and still depending on observation elevation-dependent weighting. A latitudinal tilting of the troposphere in a global scale causes a systematic difference of up to 0.3 mm in the north-gradient component, while large local gradients, usually pointing in a direction of increasing humidity, can cause differences of up to 1.0 mm (or even more in extreme cases) in any component depending on the actual direction of the gradient. Although the Bar-Sever gradient mapping function provided slightly better results in some aspects, it is not possible to give any strong recommendation on the gradient mapping function selection.


2019 ◽  
Vol 12 (1) ◽  
pp. 23-34 ◽  
Author(s):  
Gregor Möller ◽  
Daniel Landskron

Abstract. In Global Navigation Satellite System (GNSS) tomography, precise information about the tropospheric water vapor distribution is derived from integral measurements like ground-based GNSS slant wet delays (SWDs). Therefore, the functional relation between observations and unknowns, i.e., the signal paths through the atmosphere, have to be accurately known for each station–satellite pair involved. For GNSS signals observed above a 15∘ elevation angle, the signal path is well approximated by a straight line. However, since electromagnetic waves are prone to atmospheric bending effects, this assumption is not sufficient anymore for lower elevation angles. Thus, in the following, a mixed 2-D piecewise linear ray-tracing approach is introduced and possible error sources in the reconstruction of the bended signal paths are analyzed in more detail. Especially if low elevation observations are considered, unmodeled bending effects can introduce a systematic error of up to 10–20 ppm, on average 1–2 ppm, into the tomography solution. Thereby, not only the ray-tracing method but also the quality of the a priori field can have a significant impact on the reconstructed signal paths, if not reduced by iterative processing. In order to keep the processing time within acceptable limits, a bending model is applied for the upper part of the neutral atmosphere. It helps to reduce the number of processing steps by up to 85 % without significant degradation in accuracy. Therefore, the developed mixed ray-tracing approach allows not only for the correct treatment of low elevation observations but is also fast and applicable for near-real-time applications.


Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5578
Author(s):  
Fangzhao Zhang ◽  
Jean-Pierre Barriot ◽  
Guochang Xu ◽  
Marania Hopuare

Since Bevis first proposed Global Positioning System (GPS) meteorology in 1992, the precipitable water (PW) estimates retrieved from Global Navigation Satellite System (GNSS) networks with high accuracy have been widely used in many meteorological applications. The proper estimation of GNSS PW can be affected by the GNSS processing strategy as well as the local geographical properties of GNSS sites. To better understand the impact of these factors, we compare PW estimates from two nearby permanent GPS stations (THTI and FAA1) in the tropical Tahiti Island, a basalt shield volcano located in the South Pacific, with a mean slope of 8% and a diameter of 30 km. The altitude difference between the two stations is 86.14 m, and their horizontal distance difference is 2.56 km. In this paper, Bernese GNSS Software Version 5.2 with precise point positioning (PPP) and Vienna mapping function 1 (VMF1) was applied to estimate the zenith tropospheric delay (ZTD), which was compared with the International GNSS Service (IGS) Final products. The meteorological parameters sourced from the European Center for Medium-Range Weather Forecasts (ECMWF) and the local weighted mean temperature ( T m ) model were used to estimate the GPS PW for three years (May 2016 to April 2019). The results show that the differences of PW between two nearby GPS stations is nearly a constant with value 1.73 mm. In our case, this difference is mainly driven by insolation differences, the difference in altitude and the wind being only second factors.


Author(s):  
G. Gurbuz ◽  
K. S. Gormus ◽  
U. Altan

Air pollution is the most important environmental problem in Zonguldak city center. Since bituminous coal is used for domestic heating in houses and generating electricity in thermal power plants, particulate matter (PM<sub>10</sub>) is the leading air pollutant. Previous studies have shown that the water vapor in the troposphere is responsible for the tropospheric zenith delay in Global Navigation Satellite System (GNSS) measurements. In this study, data obtained from the ZONG GNSS station from Türkiye Ulusal Sabit GNSS Ağı (TUSAGA-Active network) in the central district of Zonguldak province, processed with GIPSY-OASIS II and GAMIT/GlobK software using the VMF1 mapping function, which is developed previously and considered to be the most accurate model. The resulting values were examined separately in terms of software. The meteorological parameters obtained from the Turkish State Meteorological Service and the air pollution values obtained from the Ministry of Environment and Urban Planning were analyzed and the zenith delay values were compared. When wet zenith delays of different days with different amounts of PM<sub>10</sub> concentrations were examined in succession and under the same meteorological conditions, differences in the range of 20&amp;ndash;40&amp;thinsp;mm on ZTD were observed.


2020 ◽  
Vol 12 (11) ◽  
pp. 1848 ◽  
Author(s):  
Wenyuan Zhang ◽  
Shubi Zhang ◽  
Nan Ding ◽  
Qingzhi Zhao

Global Navigation Satellite System (GNSS) tomography has developed into an efficient tool for sensing the high spatiotemporal variability of atmospheric water vapor. The integration of GNSS top signals and side rays for tropospheric tomography systems using a novel height factor model (HFM) is proposed and discussed in this paper. Within the HFM, the sectional slant wet delay (SWD) of inside signals (the part of the side signal inside the tomography area), which is considered a key factor for modeling side rays, is separated into isotropic and anisotropic components. Correspondingly, two height factors are defined to calculate the isotropic and anisotropic part of tropospheric delays in the HFM. In addition, the dynamic tomography top boundary is first analyzed and determined based on 30-year radiosonde data to reasonably divide signals into top and side rays. Four special experimental schemes based on different tomography regions of Hong Kong are performed to assess the proposed HFM method, the results of which show increases of 33.42% in the mean utilization of rays, as well as decreases of 0.46 g/m3 in the average root mean square error (RMSE), compared to the traditional approach, revealing the improvement of tomography solutions when the side signals are included in the modeling. Furthermore, compared with the existing correction model for modeling side rays, the water vapor profiles retrieved from the proposed improved model are closer to the radiosonde data, which highlights the advantages of the proposed HFM for optimizing the GNSS tomography model.


2020 ◽  
Vol 12 (4) ◽  
pp. 617
Author(s):  
Yuchen Wang ◽  
Nan Ding ◽  
Yu Zhang ◽  
Long Li ◽  
Xiaoyan Yang ◽  
...  

Global Navigation Satellite System (GNSS) tomography is a popular method for measuring and modelling water vapor in the troposphere. Presently, most studies use a cuboid-shaped tomographic region in their modelling, which represents the modelling region for all measurement epochs. This region is defined by the distribution of the GNSS signals skywards from a network of ground based GNSS stations for all epochs of measurements. However, in reality at each epoch the shape of the GNSS tomographic region is more likely to be an inverted cone. Unfortunately, this fixed conic tomographic region does not properly reflect the fact that the GNSS signal changes quickly over time. Therefore a dynamic or adaptive tomographic region is better suited. In this study, a new approach that adjusts the GNSS tomographic model to adapt the size of the GNSS network is proposed, which referred to as The High Flexibility GNSS Tomography (HFGT). Test data from different numbers of the GNSS stations are used and the results from HFGT are compared against that of radiosonde data (RS) to assess the accuracy of the HFGT approach. The results showed that the new approach is feasible for different numbers of the GNSS stations when a sufficient and uniformed distribution of GNSS signals is used. This is a novel approach for GNSS tomography.


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