Tomographic reconstruction of wet and total refractivity fields from GNSS receiver networks

One of the most attractive scientific issues in the use of GNSS (Global Navigation Satellite System) signals, from a meteorological point of view, is the retrieval of high resolution tropospheric water vapour maps. The real-time (or quasi real-time) knowledge of such distributions could be very useful for several applications, from operative meteorology to atmospheric modelling. Moreover, the exploitation of wet refractivity field reconstruction techniques can be used for atmospheric delay compensation purposes and, as a very promising activity, it could be applied for example to calibrate SAR or Interferometric-SAR (In-SAR) observations for land remote sensing. This is in fact one of the objectives of the European Space Agency project METAWAVE (Mitigation of Electromagnetic Transmission errors induced by Atmospheric Water vapour Effects), in which several techniques are investigated and results were compared to identify a strategy to remove the contribution of water vapour induced propagation delays in In-SAR products. Within this project, the tomographic reconstruction of three dimensional wet refractivity fields from tropospheric delays observed by a local GNSS network (9 dual frequency GPS receivers) deployed over Como area (Italy), during 12–18 October, 2008, was performed. Despite limitations due to the network design, internal consistency tests prove the efficiency of the adopted tomographic approach: the rms of the difference between reconstructed and GNSS observed Zenith Wet Delays (ZWD) are in the order of 4 mm. A good agreement is also observed between our ZWDs and corresponding delays obtained by vertically integrating independent wet refractivity fields, taken by co-located meteorological analysis. Finally, during the observing period, reconstructed vertical wet refractivity profiles evolution reveals water vapour variations induced by simple cloud covering. Even if our main goal was to demonstrate the effectiveness in adopting tomographic reconstruction procedures for the evaluation of propagation delays inside water vapour fields, the actual water vapour vertical variability and its evolution with time is well reproduced, demonstrating also the effectiveness of the inferred 3D wet refractivity fields.     

Improving the estimation of zenith dry tropospheric delays using regional surface meteorological data

Global Navigation Satellite Systems (GNSS) are emerging as possible tools for remote sensing high-resolution atmospheric water vapour that improves weather forecasting through numerical weather prediction models. Nowadays, the GNSS-derived tropospheric zenith total delay (ZTD), comprising zenith dry delay (ZDD) and zenith wet delay (ZWD), is achievable with sub-centimetre accuracy. However, if no representative near-site meteorological information is available, the quality of the ZDD derived from tropospheric models is degraded, leading to inaccurate estimation of the water vapour component ZWD as difference between ZTD and ZDD. On the basis of freely accessible regional surface meteorological data, this paper proposes a height-dependent linear correction model for a priori ZDD. By applying the ordinary least-squares estimation (OLSE), bootstrapping (BOOT), and leave-one-out cross-validation (CROS) methods, the model parameters are estimated and analysed with respect to outlier detection. The model validation is carried out using GNSS stations with near-site meteorological measurements. The results verify the efficiency of the proposed ZDD correction model, showing a significant reduction in the mean bias from several centimetres to about 5 mm. The OLSE method enables a fast computation, while the CROS procedure allows for outlier detection. All the three methods produce consistent results after outlier elimination, which improves the regression quality by about 20% and the model accuracy by up to 30%.     

Exploration and analysis of the factors influencing GNSS PWV for nowcasting applications

Precipitable water vapor (PWV) can be assimilated into a numerical weather model (NWM) to improve the prediction accuracy of numerical weather prediction. In this study, taking GNSS data for the Beijing Fangshan station (BJFS) as an example, based on the method of Pearson correlation coefficient combined with quantitative analysis, GNSS datasets are used to study the relationships between GNSS-derived PWV (GNSS PWV__Met) and its influencing factors, including the internal influencing factors zenith troposphere delay (ZTD), zenith hydrostatic delay (ZHD), zenith wet delay (ZWD), and surface temperature (T_s), and the external influencing factor haze (mainly PM_2.5). Firstly, based on the strong correlation between PWV__Met and ZTD hourly sequences from the International GNSS Service Network’s BJFS station for DOYS 182–212, 2015, the results of experiment prove that the reliability of GNSS ZTD is used to forecast PWV_Met in short-term forecasting. Secondly, based on hourly data of BJFS in 2016, the correlation between PWV__Met and ZTD, ZWD, ZHD, pressure (P) and T_s is analyzed, and then, with the rate of ZTD variation as the main factor, ZTD variation as auxiliary factor, the prediction success rate is 88.24% from hourly data of precipitation event for DOYs 183–213 in Beijing. The experiment indicates that ZTD can help forecast short-term precipitation. Thirdly, based on data from three hazy periods with relatively stable weather conditions, no heavy rainfall, and relatively continuous data in the past three years, the correlation between GNSS PWV_Met/ZTD and PM_2.5 hourly series is analyzed. The results of the experiments suggests that GNSS ZTD should be considered to assist in haze monitoring. So in the absence of radiosonde stations and meteorological elements, ZTDs on retrieval of GNSS stations have more application value in short-term forecast.     

Combination methods of tropospheric time series

In this article we present two methods for combination of different Global Navigation Satellite Systems (GNSS) Zenith Total Delay (ZTD) time-series for the same GNSS site, but from different producers or different processing setups. One method has been setup at ASI/CGS, the other at KNMI. Using Near Real-Time (NRT) ZTD data covering 1 year from the E-GVAP project, the performance of the two methods is inter-compared and validation is made against a combined ZTD solution from EUREF, based on post-processed ZTDs. Further, validation of the ASI combined solutions is made against independent ZTDs derived from radiosonde, Numerical Weather Prediction (NWP) model and Very Long Baseline Interferometry (VLBI) ZTD.     

DORIS and GPS monitoring of the Gavdos calibration site in Crete

Due to its specific geographical location as well as its geodetic equipment (DORIS, GNSS, microwave transponder and tide gauges), the Gavdos station in Crete, Greece is one of the very few sites around the world used for satellite altimetry calibration. To investigate the quality of the Gavdos geodetic coordinates and velocities, we analyzed and compared here DORIS and GPS-derived results obtained during several years of observations. The DORIS solution is the latest ignwd11 solution at IGN, expressed in ITRF2008, while the GPS solution was obtained using the GAMIT software package. Current results show that 1–2 mm/yr agreement can be obtained for 3-D velocity, showing a good agreement with current geophysical models. In particular, the agreement obtained for the vertical velocity is around 0.3–0.4 mm/yr, depending on the terrestrial reference frame. As a by-product of these geodetic GPS and DORIS results, Zenith Tropospheric Delays (ZTDs) estimations were also compared in 2010 between these two techniques, and compared to ECMWF values, showing a 6.6 mm agreement in dispersion without any significant difference between GPS and DORIS (with a 97.6% correlation), but with a 13–14 mm agreement in dispersion when comparing to ECMWF model (with only about 90% correlation for both techniques). These tropospheric delay estimations could also provide an external calibration of the tropospheric correction used for the geophysical data of satellite altimetry missions.     

VLBI observations to the APOD satellite

The APOD (Atmospheric density detection and Precise Orbit Determination) is the first LEO (Low Earth Orbit) satellite in orbit co-located with a dual-frequency GNSS (GPS/BD) receiver, an SLR reflector, and a VLBI X/S dual band beacon. From the overlap statistics between consecutive solution arcs and the independent validation by SLR measurements, the orbit position deviation was below 10?cm before the on-board GNSS receiver got partially operational. In this paper, the focus is on the VLBI observations to the LEO satellite from multiple geodetic VLBI radio telescopes, since this is the first implementation of a dedicated VLBI transmitter in low Earth orbit. The practical problems of tracking a fast moving spacecraft with current VLBI ground infrastructure were solved and strong interferometric fringes were obtained by cross-correlation of APOD carrier and DOR (Differential One-way Ranging) signals. The precision in X-band time delay derived from 0.1?s integration time of the correlator output is on the level of 0.1?ns. The APOD observations demonstrate encouraging prospects of co-location of multiple space geodetic techniques in space, as a first prototype.     

Improving dUT1 from VLBI intensive sessions with GRAD gradients and ray-traced delays

Exact knowledge of the angle of Earth rotation UT1 with respect to coordinated time UTC, dUT1, is essential for all space geodetic techniques. The only technique which is capable of determining dUT1 is Very Long Baseline Interferometry (VLBI). So-called Intensive VLBI sessions are performed on a daily basis in order to provide dUT1. Due to the reduced geometry of Intensive sessions, there is however no possibility to estimate tropospheric gradients from the observations, which limits the accuracy of the resulting dUT1 significantly. This paper deals with introducing the information on azimuthal asymmetry from external sources, thus attempting to improve the dUT1 estimates. We use the discrete horizontal gradients GRAD and the empirical horizontal gradients GPT3 as well as ray-traced delays from the VieVS ray-tracer for this purpose, which can all be downloaded from the VMF server of TU Wien (http://vmf.geo.tuwien.ac.at). The results show that this strategy indeed improves the dUT1 estimates when compared to reference values from multi-station VLBI stations, namely by up to 15%. When converted to length-of-day (LOD), the estimates can be compared to LODs from global analyses of Global Navigation Satellite Systems (GNSS). Here, the improvement amounts to up to 7% compared to neglecting a priori information on azimuthal asymmetry.     

Annual,seasonal and diurnal variations of integrated water vapor using GPS observations over Hyderabad,a tropical station

This paper presents annual, seasonal and diurnal variations of integrated water vapor (IWV) derived from Global Positioning System (GPS) measurements for a tropical site, Hyderabad (17.4° N, 78.46° E). The zenith wet delay (ZWD) due to the troposphere has been computed using GPS observations and collocated meteorological data. ZWD is converted to IWV with very little added uncertainty. Mean monthly IWV values show maximum in July (~50 kg m⁻²) and minimum in December (~15 kg m⁻²). Fast Fourier Transform (FFT) and Harmonic analyses methods have been adopted to extract amplitudes and phases of diurnal (24 h), semi-diurnal (12 h) and ter-diurnal (8 h) oscillations which yielded comparable results. Amplitude of the 24 h component is observed to be maximum in spring whereas 12 h and 8 h components maximize in summer. A cross-correlation study between available daily IWV values and corresponding surface temperatures over one year produced a good correlation coefficient (0.44). The correlation obtained for different seasons got reduced to 0.25, 0.02, −0.39 and 0.21 for winter, spring, summer and autumn seasons respectively. The correlation between IWV and rainfall is poor. The coefficients obtained for the whole year is 0.05 and −0.13 for the rainy season.     

Integer phase ambiguity estimation in next-generation geodetic Very Long Baseline Interferometry

Next-generation Very Long Baseline Interferometry (VLBI) system designs are aiming at 1 mm global position accuracy. In order to achieve this, it is not only necessary to deploy improved VLBI systems, but also to develop analysis strategies that take full advantage of the observations taken. Since the new systems are expected to incorporate four independent radio frequency bands, it should be feasible to resolve phase ambiguities directly from post-correlation data, providing roughly an order of magnitude improvement in precision of the delay observable. As the unknown ambiguities are of integer nature, it is discussed here how they the can be resolved analytically using algorithms which have been developed for Global Navigation Satellite System (GNSS) applications. Furthermore, it will be shown that ionosphere contribution and source structure effects, so-called core-shifts, can be solved simultaneously with the delay, which is the main geodetic observable for follow-on analysis. In order to verify the proposed algorithm, simulated observations were created using parameters from actual design studies. It is shown that, even in the case of low signal-to-noise ratio observations, reliable phase ambiguity resolution can be achieved and it is discussed how the integer ambiguity recovery depends on the number of observations and signal-to-noise ratio.     

The ground GNSS tomography – unconstrained approach

The GNSS signal along its more than 20,000 km line of sight is bended, attenuated and delayed. These effects are results of the Earth’s atmosphere, and Sun radiation. Amongst all mentioned effects the one considered in this paper is a signal phase delay in troposphere.     

Mechanism of error propagation from the subdaily Universal Time model into the celestial pole offsets estimated by VLBI

Within the analysis of space geodetic observations, errors of the applied subdaily Earth rotation model can induce systematic effects in different estimated parameters. In this paper, we focus on the impact of the subdaily Universal Time (UT1) model on the celestial pole offsets (CPO) estimated from very long baseline interferometry (VLBI) observations. We provide a mechanism that describes the error propagation from the subdaily UT1 into the daily CPO.In typical 24-h VLBI sessions the observed quasars are well distributed over the sky. But the observations, if looked at from the Earth-fixed frame, are not homogeneously distributed. The amount of observations performed in different terrestrial directions shows an irregularity which can be roughly compared to the case where the observations are collected in only one Earth-fixed direction. This peculiarity leads to artefacts in VLBI solutions, producing a correlation between the subdaily variations in UT1 and the position of the celestial pole. As a result errors in diurnal terms of the subdaily UT1 model are partly compensated by the estimated CPO. We compute for each 24-h VLBI session from 1990 until 2011 the theoretical response of the CPO to an error in the subdaily UT1 by setting up a least-squares adjustment model and using as input the coordinates of the observed quasars and observation epochs. Then real observed response of the estimated CPO derived from the VLBI session solutions is compared to the predicted one. A very good agreement between the CPO values estimated from VLBI and the predicted values was achieved. The presented model of error propagation from the subdaily UT1 into the daily CPO allows to predict and explain the behaviour of CPO estimates of VLBI solutions computed with different subdaily Earth rotation models, what can be helpful for testing the accuracy of different subdaily tidal models.     

面向绕月交会对接的同波束VLBI研究

针对"嫦娥5号"(CE-5)探测器间高精度相对测量需求,设计了我国深空干涉测量处理中心框架下的同波束VLBI处理算法,分析了X波段同波束VLBI相位解模糊条件和结果;通过引入群时延辅助的相位干涉技术,大幅抑制了干涉时延随机误差,为同波束VLBI中相位解模糊提供了先验条件;利用CE-5对接实测数据验证了本文工作的有效性,为CE-5任务同波束VLBI的实施奠定了基础。     

Development of a GNSS water vapour tomography system using algebraic reconstruction techniques

A GNSS water vapour tomography system developed to reconstruct spatially resolved humidity fields in the troposphere is described. The tomography system was designed to process the slant path delays of about 270 German GNSS stations in near real-time with a temporal resolution of 30 min, a horizontal resolution of 40 km and a vertical resolution of 500 m or better. After a short introduction to the GPS slant delay processing the framework of the GNSS tomography is described in detail. Different implementations of the iterative algebraic reconstruction techniques (ART) used to invert the linear inverse problem are discussed. It was found that the multiplicative techniques (MART) provide the best results with least processing time, i.e., a tomographic reconstruction of about 26,000 slant delays on a 8280 cell grid can be obtained in less than 10 min. Different iterative reconstruction techniques are compared with respect to their convergence behaviour and some numerical parameters. The inversion can be considerably stabilized by using additional non-GNSS observations and implementing various constraints. Different strategies for initialising the tomography and utilizing extra information are discussed. At last an example of a reconstructed field of the wet refractivity is presented and compared to the corresponding distribution of the integrated water vapour, an analysis of a numerical weather model (COSMO-DE) and some radiosonde profiles.     

The adjusted optical properties for Galileo/BeiDou-2/QZS-1 satellites and initial results on BeiDou-3e and QZS-2 satellites

Solar Radiation Pressure (SRP) is the dominant non-gravitational perturbation for GNSS (Global Navigation Satellite System) satellites. In the absence of precise surface models, the Empirical CODE Orbit Models (ECOM, ECOM2) are widely used in GNSS satellite orbit determination. Based on previous studies, the use of an a priori box-wing model enhances the ECOM model, especially if the spacecraft is a stretched body satellite. However, so far not all the GNSS system providers have published their metadata. To ensure a precise use of the a priori box-wing model, we estimate the optical parameters of all the Galileo, BeiDou-2, and QZS-1 (Quasi Zenith Satellite System) satellites based on the physical processes from SRP to acceleration. Validation using orbit prediction proves that the adjusted parameters of Galileo and QZS-1 satellites exhibit almost the same performance as the corresponding published and “best guess” values. Whereas, the estimated parameters of BeiDou-2 satellites demonstrate an improvement of more than 60% over the initial “guess” values. The resulting optical parameters of all the satellites are introduced into an a priori box-wing model, which is jointly used with ECOM and ECOM2 model in the orbit determination. Results show that the pure ECOM2 model exhibits better performance than the pure ECOM model for Galileo, BeiDou-2 GEO and QZS-1 orbits. Combined with the a priori box-wing model the ECOM model (ECOM+BW) results in the best Galileo, BeiDou-2 GEO and QZS-1 orbits. The standard deviation (STD) of satellite laser ranging residuals reduce by about 20% and 5% with respect to the pure ECOM2 model for Galileo and BeiDou-2 GEO orbits, while the reductions are about 40% and 60% for QZS-1 orbits in yaw-steering and orbit-normal mode respectively. BeiDou-2 IGSO and MEO satellite orbits do not benefit much from the a priori box-wing model. In summary, we suggest setting up a unified SRP model of ECOM+BW for Galileo, QZS-1, and BeiDou-2 orbits based on the adjusted metadata. In addition, we estimate the optical parameters of BeiDou-3e and QZS-2 satellites using a limited number of tracking stations. Results regarding the unified SRP model indicate the same advantages, the STD of satellite laser ranging residuals reduces by about 30% and 20% for QZS-2 and BeiDou-3e orbits respectively over orbit products without a priori model. The estimation procedure is effective and easy to apply to the new emerging satellites in the future.     

High temporal resolution global PWV dataset of 2005–2016 by using a neural network approach to determine the mean temperature of the atmosphere

Atmospheric water vapour plays an important role in phenomena related to the global hydrologic cycle and climate change. However, the rapid temporal–spatial variation in global tropospheric water vapour has not been well investigated due to a lack of long-term, high-temporal-resolution precipitable water vapour (PWV). Accordingly, this study generates an hourly PWV dataset for 272 ground-based International Global Navigation Satellite System (GNSS) Service (IGS) stations over the period of 2005–2016 using the zenith troposphere delay (ZTD) derived from global-scale GNSS observation. The root mean square (RMS) of the hourly ZTD obtained from the IGS tropospheric product is approximately 4 mm. A fifth-generation reanalysis dataset of the European Centre for Medium-range Weather Forecasting (ECMWF ERA5) is used to obtain hourly surface temperature (T) and pressure (P), which are first validated with GNSS synoptic station data and radiosonde data, respectively. Then, T and P are used to calculate the water vapour-weighted atmospheric mean temperature (Tm) and zenith hydrostatic delay (ZHD), respectively. T and P at the GNSS stations are obtained via an interpolation in the horizontal and vertical directions using the grid-based ERA5 reanalysis dataset. Here, Tm is calculated using a neural network model, whereas ZHD is obtained using an empirical Saastamoinen model. The RMS values of T and P at the collocated 693 radiosonde stations are 1.6 K and 3.1 hPa, respectively. Therefore, the theoretical error of PWV caused by the errors in ZTD, T and P is on the order of approximately 2.1 mm. A practical comparison experiment is performed using 97 collocated radiosonde stations and 23 GNSS stations equipped with meteorological sensors. The RMS and bias of the hourly PWV dataset are 2.87/?0.16 and 2.45/0.55 mm, respectively, when compared with radiosonde and GNSS stations equipped with meteorological sensors. Additionally, preliminary analysis of the hourly PWV dataset during the EI Niño event of 2014–2016 further indicates the capability of monitoring the daily changes in atmospheric water vapour. This finding is interesting and significant for further climate research.     

The impact of microwave absorber and radome geometries on GNSS measurements of station coordinates and atmospheric water vapour

We have used microwave absorbing material in different geometries around ground-based Global Navigation Satellite System (GNSS) antennas in order to mitigate multipath effects on the estimates of station coordinates and atmospheric water vapour. The influence of a hemispheric radome – of the same type as in the Swedish GPS network SWEPOS – was also investigated. Two GNSS stations at the Onsala Space Observatory were used forming a 12 m baseline. GPS data from October 2008 to November 2009 were analyzed by the GIPSY/OASIS II software using the Precise Point Positioning (PPP) processing strategy for five different elevation cutoff angles from 5° to 25°. We found that the use of the absorbing material decreases the offset in the estimated vertical component of the baseline from ∼27 mm to ∼4 mm when the elevation cutoff angle varies from 5° to 20°. The horizontal components are much less affected. The corresponding offset in the estimates of the atmospheric Integrated Water Vapour (IWV) decreases from ∼1.6 kg/m² to ∼0.3 kg/m². Changes less than 5 mm in the offsets in the vertical component of the baseline are seen for all five elevation cutoff angle solutions when the antenna was covered by a hemispheric radome. Using the radome affects the IWV estimates less than 0.4 kg/m² for all different solutions. IWV comparisons between a Water Vapour Radiometer (WVR) and the GPS data give consistent results.     

Deformation monitoring using GNSS-R technology

GNSS reflectometry (GNSS-R) has been widely studied in recent years for various applications, such as soil moisture monitoring, biomass analysis, and sea state monitoring. This paper presents the concept of a novel application of using GNSS-R technology for deformation monitoring. Instead of installing GNSS on the deformation body to sense the movement, GNSS-R deformation monitoring system estimates the deformation from receiving GNSS signal reflected by the deformation body remotely. A prototype of GNSS-R deformation monitoring system has been developed based on GNSS software receiver technology. A 3D geometrical model of GNSS signal reflection has been used to reveal the relationship between the change of carrier phase difference and deformation. After compensating the propagation path delay changes caused by satellite movement, the changes in the remaining carrier phase difference are linked to the deformation. Field tests have been carried using the GNSS-R system developed and the results show sub-centimeter level deformation can be observed with the new technology. Unlike other GNSS deformation monitoring methods, GNSS-R receivers are not installed on the slope which makes this new technology more attractive.     

Near real-time estimation of tropospheric water vapour content from ground based GNSS data and its potential contribution to weather now-casting in Austria

The importance of high resolution meteorological analysis of the atmosphere increased over the past years. A detailed analysis of the humidity field is an important precondition for a better monitoring of local and regional extreme precipitation events and for forecasts with improved spatial resolution. For this reason, the Austrian Meteorological Agency (ZAMG) is operating the spatial and temporal high resolution INCA system (Integrated Now-casting through Comprehensive Analysis) since begin of 2005. Errors in this analysis occur mainly in the areas of rapidly changing and hard to predict weather conditions or rugged topography with extreme differences in height such as the alpine area of Austria. The aim of this work is to provide GNSS based measurements of the tropospheric water vapour content with a temporal resolution of 1 h and a temporal delay of less than 1 h to assimilate these estimates into the INCA system. Additional requirement is an accuracy of better than 1 mm of the precipitable water (PW) estimates.     

Chang’E-1 precision orbit determination and lunar gravity field solution

In this paper we present results assessing the role of Very Long Baseline Interferometry (VLBI) tracking data through precision orbit determination (POD) during the check-out phase for Chang’E-1, and the lunar gravity field solution CEGM-01 based on the orbital tracking data acquired during the nominal phase of the mission. The POD of Chang’E-1 is performed using S-band two-way Range and Range Rate (R&RR) data, together with VLBI delay and delay rate observations. The role of the VLBI data in the POD of Chang’E-1 is analyzed, and the resulting orbital accuracies are estimated for different solution strategies. The final orbital accuracies proved that the VLBI tracking data can improve the Chang’E-1 POD significantly. Consequently, CEGM-01 based on six-month tracking data during Chang’E-1 nominal mission phase is presented, and the accuracy of the model is assessed by means of the gravity field power spectrum, admittance and coherence between gravity and topography, lunar surface gravity anomaly and POD for both Chang’E-1 and Lunar Prospector (LP). Our analysis indicates that CEGM-01 has significant improvements over a prior model (i.e. GLGM-2), and shows the potential of Chang’E-1 tracking data in high resolution lunar gravity field model solution by combining with SELENE and LP tracking data.     

用于太阳系天体VLBI观测的时延模型

VLBI观测技术可以用于对深空航天器的跟踪定位以及测速观测．这类近距离天体发出的射电信号波前是球面波．为此，本文提出了一个1ps精度下近距离射电天体地面VLBI观测时间延迟模型．