Effect of different tropospheric mapping functions on the TRF, CRF and position time-series estimated from VLBI

This paper compares estimated terrestrial reference frames (TRF) and celestial reference frames (CRF) as well as position time-series in terms of systematic differences, scale, annual signals and station position repeatabilities using four different tropospheric mapping functions (MF): The NMF (Niell Mapping Function) and the recently developed GMF (Global Mapping Function) consist of easy-to-handle stand-alone formulae, whereas the IMF (Isobaric Mapping Function) and the VMF1 (Vienna Mapping Function 1) are determined from numerical weather models. All computations were performed at the Deutsches Geodätisches Forschungsinstitut (DGFI) using the OCCAM 6.1 and DOGS-CS software packages for Very Long Baseline Interferometry (VLBI) data from 1984 until 2005. While it turned out that CRF estimates only slightly depend on the MF used, showing small systematic effects up to 0.025 mas, some station heights of the computed TRF change by up to 13 mm. The best agreement was achieved for the VMF1 and GMF results concerning the TRFs, and for the VMF1 and IMF results concerning scale variations and position time-series. The amplitudes of the annual periodical signals in the time-series of estimated heights differ by up to 5 mm. The best precision in terms of station height repeatability is found for the VMF1, which is 5–7% better than for the other MFs.     

Comparison of GMF/GPT with VMF1/ECMWF and implications for atmospheric loading

This paper compares estimates of station coordinates from global GPS solutions obtained by applying different troposphere models: the Global Mapping Function (GMF) and the Vienna Mapping Function 1 (VMF1) as well as a priori hydrostatic zenith delays derived from the Global Pressure and Temperature (GPT) model and from the European Centre for Medium-Range Weather Forecasts (ECMWF) numerical weather model data. The station height differences between terrestrial reference frames computed with GMF/GPT and with VMF1/ECMWF are in general below 1 mm, and the horizontal differences are even smaller. The differences of annual amplitudes in the station height can also reach up to 1 mm. Modeling hydrostatic zenith delays with mean (or slowly varying empirical) pressure values instead of the true pressure values results in a partial compensation of atmospheric loading. Therefore, station height time series based on the simple GPT model have a better repeatability than those based on more realistic ECMWF troposphere a priori delays if atmospheric loading corrections are not included. On the other hand, a priori delays from numerical weather models are essential to reveal the full atmospheric loading signal.     

VMF3/GPT3: refined discrete and empirical troposphere mapping functions

Incorrect modeling of troposphere delays is one of the major error sources for space geodetic techniques such as Global Navigation Satellite Systems (GNSS) or Very Long Baseline Interferometry (VLBI). Over the years, many approaches have been devised which aim at mapping the delay of radio waves from zenith direction down to the observed elevation angle, so-called mapping functions. This paper contains a new approach intended to refine the currently most important discrete mapping function, the Vienna Mapping Functions 1 (VMF1), which is successively referred to as Vienna Mapping Functions 3 (VMF3). It is designed in such a way as to eliminate shortcomings in the empirical coefficients b and c and in the tuning for the specific elevation angle of \(3^{\circ }\). Ray-traced delays of the ray-tracer RADIATE serve as the basis for the calculation of new mapping function coefficients. Comparisons of modeled slant delays demonstrate the ability of VMF3 to approximate the underlying ray-traced delays more accurately than VMF1 does, in particular at low elevation angles. In other words, when requiring highest precision, VMF3 is to be preferable to VMF1. Aside from revising the discrete form of mapping functions, we also present a new empirical model named Global Pressure and Temperature 3 (GPT3) on a \(5^{\circ }\times 5^{\circ }\) as well as a \(1^{\circ }\times 1^{\circ }\) global grid, which is generally based on the same data. Its main components are hydrostatic and wet empirical mapping function coefficients derived from special averaging techniques of the respective (discrete) VMF3 data. In addition, GPT3 also contains a set of meteorological quantities which are adopted as they stand from their predecessor, Global Pressure and Temperature 2 wet. Thus, GPT3 represents a very comprehensive troposphere model which can be used for a series of geodetic as well as meteorological and climatological purposes and is fully consistent with VMF3.     

Assessment of troposphere mapping functions using three-dimensional ray-tracing

The troposphere delay is an important source of error for precise GNSS positioning due to its high correlation with the station height parameter. It has been demonstrated that errors in mapping functions can cause sub-annual biases as well as affect the repeatability of GNSS solutions, which is a particular concern for geophysical studies. Three-dimensional ray-tracing through numerical weather models (NWM) is an excellent approach for capturing the directional and daily variation of the tropospheric delay. Due to computational complexity, its use for positioning purposes is limited, but it is an excellent tool for evaluating current state-of-the-art mapping functions used for geodetic positioning. Many mapping functions have been recommended in the past such as the Niell Mapping Function (NMF), Vienna Mapping Function 1 (VMF1), and the Global Mapping Function (GMF), which have been adopted by most IGS analysis centers. A new Global Pressure Temperature model (GPT2) has also been developed, which has been shown to improve upon the original atmospheric model used for the GMF. Although the mapping functions mentioned above use the same functional formulation, they vary in terms of their atmospheric source and calibration approach. A homogeneous data set of three-dimensional ray-traced delays is used to evaluate all components of the mapping functions, including their underlying functional formulation, calibration, and compression method. Additionally, an alternative representation of the VMF1 is generated using the same atmospheric source as the truth data set to evaluate the differences in ray-tracing methods and their effect on the end mapping function. The results of this investigation continue to support the use of the VMF1 as the mapping function of choice when geodetic parameters are of interest. Further support for the GPT2 and GMF as reliable back-ups when the VMF1 is not available was found due to their high consistency with the NWM-derived mapping function. Additionally, a small latitude-dependent bias in station height was found in the current mapping functions. This bias was identified to be due to the assumption of a constant radius of the earth and was largest at the poles and at the equator. Finally, an alternative version of the VMF1 is introduced, namely the UNB-VMF1 which provides users with an independent NWM-derived mapping function to support geodetic positioning.     

基于GPS非差技术近实时获取对流层延迟

本文提出一种近实时获取高精度对流层延迟(Zenith Tropospheric Delay,ZTD)的方法。该方法基于全球GPS参考站网络的非差观测值数据和IGU预报产品(卫星轨道和ERP),使用GPS非差技术和卡尔曼滤波近实时估计各参考站的高精度ZTD。将该方法应用于香港GPS参考站网得到的ZTD与基于事后技术计算的ZTD进行比较后发现,两者的平均偏差均优于5mm,RMS均优于6mm。     

Estimation and evaluation of hourly updated global GPS Zenith Total Delays over ten months

The EUMETNET EIG GNSS Water Vapour Programme (E-GVAP) is responsible for the coordination of near real time GPS Zenith Total Delay (ZTD) production in Europe and for aiding the development of ZTD assimilation into Numerical Weather Prediction (NWP) models. Since 2000, the Geodetic Observatory Pecný (GOP) has been routinely estimating regional ZTDs in near real time. In 2010, GOP developed a modified processing system in order to provide the first optimal and robust ZTD solution with a global scope and hourly upgrade, fulfilling the requirements for assimilation into operational NWP models. Since July 2010, the GOP global tropospheric product has consisted of about 90 sites and has contributed routinely in a testing mode into the E-GVAP database. Global near real time ZTDs generated over ten months have been evaluated with respect to IGS and EUREF routine post-processed ZTD products, ZTDs integrated from radiosonde profiles, and ZTDs calculated from the Met Office global NWP model. Comparison with the GNSS post-processed solutions gives standard deviations of 3–6 mm in ZTD and biases of 1–2 mm, which is comparable to GOP regional near real time solution, however, for some isolated or low data quality stations up to 20 % quality decrease can be found. Comparison with NWP shows a latitudinal trend in the standard deviation with values as low as 4 mm at high latitudes, increasing to almost 20 mm in the tropics, and a lack of variability in the model background ZTD in the tropics. The evaluation with global radiosondes gives ZTD standard deviation of 5–16 mm, which is comparable with previous studies in European scope. Since the 10-month comparison gave satisfactory results, GOP was asked by UK Met Office to disseminate the global product to the end users via the Global Telecommunications System. Since 10 October 2011, the GOP global ZTD product configuration has been extended to about 164 global stations and still processed within 10 min. However, in GOP routine contribution to E-GVAP, about 124 stations are available in general due to hourly data latency above 30 min or data gaps.     

单站地基GPS天顶延迟反演大气剖面研究

基于一定的大气折射率剖面模型和搜索方法,可以由GPS天顶延迟反演大气折射率剖面。利用上海气象站的探空数据和上海IGS站的GPS数据,对基于单站地基GPS天顶延迟的大气折射率剖面反演方法进行了验证。结果表明,根据目前处理得到的天顶延迟,反演剖面与实际剖面吻合较好。     

Ambiguity resolution in precise point positioning with hourly data

Precise point positioning (PPP) has become a powerful tool for the scientific analysis of Global Positioning System (GPS) measurements. Until recently, ambiguity resolution at a single station in PPP has been considered difficult, due to the receiver- and satellite-dependent uncalibrated hardware delays (UHD). However, recent studies show that if these UHD can be determined accurately in advance within a network of stations, then ambiguity resolution at a single station becomes possible. In this study, the method proposed by Ge et al. J Geod 82(7):389–399, 2007 is adopted with a refinement in which only one single-difference narrow-lane UHD between a pair of satellites is determined within each full pass over a regional network. This study uses the EUREF (European Reference Frame) Permanent Network (EPN) to determine the UHD from Day 245 to 251 in 2007. Then 12 International GNSS Service stations inside the EPN and 15 outside the EPN are used to conduct ambiguity resolution in hourly PPP. It is found that the mean positioning accuracy in all hourly solutions for the stations inside the EPN is improved from (3.8, 1.5, 2.8) centimeters to (0.5, 0.5, 1.4) centimeters for the East, North and Up components, respectively. For the stations outside the EPN, some of which are over 2,000 km away from the nearest EPN stations, the mean positioning accuracy in the East, North and Up directions still achieves (0.6, 0.6, 2.0) centimeters, respectively, when the EPN-based UHD are applied to these stations. These results demonstrate that ambiguity resolution at a single station can significantly improve the positioning accuracy in hourly PPP. Particularly, UHD can be even applied to a station which is up to thousands of kilometers from the UHD-determination network, potentially showing a great advantage over current network-based GPS augmentation systems. Therefore, it is feasible and beneficial for the operators of GPS regional networks and providers of PPP-based online services to provide these UHD estimates as an additional product.     

Assessment of ZTD derived from ECMWF/NCEP data with GPS ZTD over China

The accuracy and feasibility of computing the zenith tropospheric delays (ZTDs) from data of the European Center for Medium-Range Weather Forecasts (ECMWF) and the United States National Centers for Environmental Prediction (NCEP) are studied. The ZTDs are calculated from ECMWF/NCEP pressure-level data by integration and from the surface data with the Saastamoinen model method and then compared with the solutions measured from 28 global positioning system (GPS) stations of the Crustal Movement Observation Network of China (CMONOC) for 1 year. The results are as follows: (1) the error of the integration method is 1–3 cm less than that of the Saastamoinen model method. The agreement between the ECMWF ZTD and GPS ZTD is better than that between NCEP ZTD and GPS ZTD; (2) the bias and root mean square difference (RMSD), especially the latter, have a seasonal variation, and the RMSD decreases with increasing altitude while the variation with latitude is not obvious; and (3) when using the full horizontal resolution of 0.5° × 0.5° of the ECMWF meteorological data in place of a reduced 2.5° × 2.5° grid, the mean RMSD between GPS and ECMWF ZTD decreases by 4.5 mm. These results illuminated the accuracy and feasibility of computing the tropospheric delays and establishing the ZTD prediction model over China for navigation and positioning with ECMWF and NCEP data.     

BDS/GPS组合天顶对流层延迟的精度分析

在现有的精密轨道和钟差条件下,选取8个MGEX跟踪站2014年6—9月的观测数据,详细分析利用BDS/GPS组合PPP法在未固定跟踪站坐标和固定跟踪站坐标情况下估计ZTD的效果,并与IGS提供的对流层产品对比分析。实验分析表明,利用PPP法估计ZTD,BDS ZTD现阶段的STD优于34mm,GPS ZTD与BDS/GPS组合现阶段的STD相当,均优于14mm。与未固定跟踪站情形下估计的BDS ZTD相比,固定跟踪站坐标的方式虽然可以提高利用BDS估计ZTD的稳定性,但不能提高精度。     

Multi-technique comparison of troposphere zenith delays and gradients during CONT08

CONT08 was a 15 days campaign of continuous Very Long Baseline Interferometry (VLBI) sessions during the second half of August 2008 carried out by the International VLBI Service for Geodesy and Astrometry (IVS). In this study, VLBI estimates of troposphere zenith total delays (ZTD) and gradients during CONT08 were compared with those derived from observations with the Global Positioning System (GPS), Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS), and water vapor radiometers (WVR) co-located with the VLBI radio telescopes. Similar geophysical models were used for the analysis of the space geodetic data, whereas the parameterization for the least-squares adjustment of the space geodetic techniques was optimized for each technique. In addition to space geodetic techniques and WVR, ZTD and gradients from numerical weather models (NWM) were used from the European Centre for Medium-Range Weather Forecasts (ECMWF) (all sites), the Japan Meteorological Agency (JMA) and Cloud Resolving Storm Simulator (CReSS) (Tsukuba), and the High Resolution Limited Area Model (HIRLAM) (European sites). Biases, standard deviations, and correlation coefficients were computed between the troposphere estimates of the various techniques for all eleven CONT08 co-located sites. ZTD from space geodetic techniques generally agree at the sub-centimetre level during CONT08, and??as expected??the best agreement is found for intra-technique comparisons: between the Vienna VLBI Software and the combined IVS solutions as well as between the Center for Orbit Determination (CODE) solution and an IGS PPP time series; both intra-technique comparisons are with standard deviations of about 3?C6?mm. The best inter space geodetic technique agreement of ZTD during CONT08 is found between the combined IVS and the IGS solutions with a mean standard deviation of about 6?mm over all sites, whereas the agreement with numerical weather models is between 6 and 20?mm. The standard deviations are generally larger at low latitude sites because of higher humidity, and the latter is also the reason why the standard deviations are larger at northern hemisphere stations during CONT08 in comparison to CONT02 which was observed in October 2002. The assessment of the troposphere gradients from the different techniques is not as clear because of different time intervals, different estimation properties, or different observables. However, the best inter-technique agreement is found between the IVS combined gradients and the GPS solutions with standard deviations between 0.2 and 0.7?mm.     

Implementation and testing of the gridded Vienna Mapping Function 1 (VMF1)

The new gridded Vienna Mapping Function (VMF1) was implemented and compared to the well-established site-dependent VMF1, directly and by using precise point positioning (PPP) with International GNSS Service (IGS) Final orbits/clocks for a 1.5-year GPS data set of 11 globally distributed IGS stations. The gridded VMF1 data can be interpolated for any location and for any time after 1994, whereas the site-dependent VMF1 data are only available at selected IGS stations and only after 2004. Both gridded and site-dependent VMF1 PPP solutions agree within 1 and 2 mm for the horizontal and vertical position components, respectively, provided that respective VMF1 hydrostatic zenith path delays (ZPD) are used for hydrostatic ZPD mapping to slant delays. The total ZPD of the gridded and site-dependent VMF1 data agree with PPP ZPD solutions with RMS of 1.5 and 1.8 cm, respectively. Such precise total ZPDs could provide useful initial a priori ZPD estimates for kinematic PPP and regional static GPS solutions. The hydrostatic ZPDs of the gridded VMF1 compare with the site-dependent VMF1 ZPDs with RMS of 0.3 cm, subject to some biases and discontinuities of up to 4 cm, which are likely due to different strategies used in the generation of the site-dependent VMF1 data. The precision of gridded hydrostatic ZPD should be sufficient for accurate a priori hydrostatic ZPD mapping in all precise GPS and very long baseline interferometry (VLBI) solutions. Conversely, precise and globally distributed geodetic solutions of total ZPDs, which need to be linked to VLBI to control biases and stability, should also provide a consistent and stable reference frame for long-term and state-of-the-art numerical weather modeling.     

Estimation and evaluation of real-time precipitable water vapor from GLONASS and GPS

The revitalized Russian GLONASS system provides new potential for real-time retrieval of zenith tropospheric delays (ZTD) and precipitable water vapor (PWV) in order to support time-critical meteorological applications such as nowcasting or severe weather event monitoring. In this study, we develop a method of real-time ZTD/PWV retrieval based on GLONASS and/or GPS observations. The performance of ZTD and PWV derived from GLONASS data using real-time precise point positioning (PPP) technique is carefully investigated and evaluated. The potential of combining GLONASS and GPS data for ZTD/PWV retrieving is assessed as well. The GLONASS and GPS observations of about half a year for 80 globally distributed stations from the IGS (International GNSS Service) network are processed. The results show that the real-time GLONASS ZTD series agree quite well with the GPS ZTD series in general: the RMS of ZTD differences is about 8 mm (about 1.2 mm in PWV). Furthermore, for an inter-technique validation, the real-time ZTD estimated from GLONASS-only, GPS-only, and the GPS/GLONASS combined solutions are compared with those derived from very long baseline interferometry (VLBI) at colocated GNSS/VLBI stations. The comparison shows that GLONASS can contribute to real-time meteorological applications, with almost the same accuracy as GPS. More accurate and reliable water vapor values, about 1.5–2.3 mm in PWV, can be achieved when GLONASS observations are combined with the GPS ones in the real-time PPP data processing. The comparison with radiosonde data further confirms the performance of GLONASS-derived real-time PWV and the benefit of adding GLONASS to stand-alone GPS processing.     

Impact of the Halloween 2003 ionospheric storm on kinematic GPS positioning in Europe

Using dual-frequency data from 36 GPS stations from the EUREF Permanent Network (EPN), the influence of the October 30, 2003 Halloween geomagnetic storm on kinematic GPS positioning is investigated. The Halloween storm induced ionospheric disturbances above the northern part of Europe and Scandinavia. It is shown that kinematic position repeatabilities for this period are mainly affected for stations in northern Europe with outliers reaching 12 cm in the horizontal, and 26 cm in the vertical. These magnitudes are shown to be possibly due to the second-order ionospheric delays on GPS signals, not accounted for in the kinematic GPS positioning analysis performed. In parallel, we generate hourly TEC (Total Electron Content) maps on a 1° × 1° grid using the dense EPN network. These TEC maps do not use any interpolation but provide a high resolution in the time and space and therefore allow to better evidence small structures in the ionosphere than the classical 2-hourly 2.5° × 5° grid Global Ionospheric TEC Maps (GIM). Using the hourly 1° × 1° TEC maps, we reconstruct and refine exactly the zones of intense ionosphere activity during the storm, and we show the correlation between the ionospheric activity and assess the quality of GPS-based kinematic positioning performed in the European region.     

Combination of GPS and VLBI on the observation level during CONT11—common parameters,ties and inter-technique biases

Multi-technique space geodetic analysis software has been developed which allows to combine data on the observation level. In addition to local tie information, site-wise common parameters, i.e., troposphere and clocks, can be estimated with this software. Thus, it will be discussed how common parameters have to be estimated and where biases/offsets need to be taken into account. To test such a novel concept, Global Positioning System (GPS) and Very Long Baseline Interferometry (VLBI) data from the CONT11 campaign are being utilized. Since the VLBI baselines of this campaign extend over several thousands of kilometers, GPS data are processed in precise-point positioning mode and satellite orbits and clocks are kept fixed to the IGS final products. From the obtained results, it can be shown that the combination of space geodetic data on the observation level leads to a consistent improvement of station position repeatability as well as nuisance parameters like troposphere estimates. Furthermore, estimation of common parameters (troposphere or clocks) at co-located sites helps to improve the solution further and derive an utmost physically consistent model of the concerned parameters.     

Real-Time River Level Monitoring Using GPS Heighting

This paper presents the current progress of the River Level Monitoring using GPS Heighting (RiGHt) project. The aim of the project is to develop an integrated system to allow the continuous monitoring of river heights using a buoy equipped with Global Positioning System (GPS) and satellite communications and using Geographical Information System (GIS) techniques. ? 2000 John Wiley & Sons, Inc.     

Numerical simulation of troposphere-induced errors in GPS-derived geodetic time series over Japan

Troposphere-induced errors in GPS-derived geodetic time series, namely, height and zenith total delays (ZTDs), over Japan are quantitatively evaluated through the analyses of simulated GPS data using realistic cumulative tropospheric delays and observed GPS data. The numerical simulations show that the use of a priori zenith hydrostatic delays (ZHDs) derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) numerical weather model data and gridded Vienna mapping function 1 (gridded VMF1) results in smaller spurious annual height errors and height repeatabilities (0.45 and 2.55 mm on average, respectively) as compared to those derived from the global pressure and temperature (GPT) model and global mapping function (GMF) (1.08 and 3.22 mm on average, respectively). On the other hand, the use of a priori ZHDs derived from the GPT and GMF would be sufficient for applications involving ZTDs, given the current discrepancies between GPS-derived ZTDs and those derived from numerical weather models. The numerical simulations reveal that the use of mapping functions constructed with fine-scale numerical weather models will potentially improve height repeatabilities as compared to the gridded VMF1 (2.09 mm against 2.55 mm on average). However, they do not presently outperform the gridded VMF1 with the observed GPS data (6.52 mm against 6.50 mm on average). Finally, the commonly observed colored components in GPS-derived height time series are not primarily the result of troposphere-induced errors, since they become white in numerical simulations with the proper choice of a priori ZHDs and mapping functions.     

Forecast Vienna Mapping Functions 1 for real-time analysis of space geodetic observations

The Vienna Mapping Functions 1 (VMF1) as provided by the Institute of Geodesy and Geophysics (IGG) at the Vienna University of Technology are the most accurate mapping functions for the troposphere delays that are available globally and for the entire history of space geodetic observations. So far, the VMF1 coefficients have been released with a time delay of almost two days; however, many scientific applications require their availability in near real-time, e.g. the Ultra Rapid solutions of the International GNSS Service (IGS) or the analysis of the Intensive sessions of the International VLBI Service (IVS). Here we present coefficients of the VMF1 as well as the hydrostatic and wet zenith delays that have been determined from forecasting data of the European Centre for Medium-Range Weather Forecasts (ECMWF) and provided on global grids. The comparison with parameters derived from ECMWF analysis data shows that the agreement is at the 1 mm level in terms of station height, and that the differences are larger for the wet mapping functions than for the hydrostatic mapping functions and the hydrostatic zenith delays. These new products (VMF1-FC and hydrostatic zenith delays from forecast data) can be used in real-time analysis of geodetic data without significant loss of accuracy.     

基于相空间重构和高斯过程回归的对流层延迟预测

天顶对流层延迟(zenith tropospheric delay,ZTD)是影响GPS定位精度的关键因素,为了提高ZTD的预测精度,提出一种基于相空间重构的高斯过程回归预测模型。针对ZTD时间序列的混沌特性,利用国际GNSS服务(International GNSS Service,IGS)站提供的ZTD数据,采用Cao方法确定嵌入维数,对ZTD数据进行相空间重构,探究高斯过程(Gaussian process,GP)模型对12个位于南、北半球不同纬度等级IGS站的ZTD预测精度和准确性。为了验证GP模型的有效性,将预测结果分别与原始数据和反向传播(back propagation,BP)神经网络模型预测结果作对比分析,进一步探究不同时间对ZTD预测精度的影响,并分析了经度和海拔对ZTD预测精度的影响。结果表明,GP模型预测结果的均方根误差(root mean square error,RMSE)达到mm级,GP模型与理论值的相关性达到0.997,预测精度指标明显优于BP神经网络模型;GP模型在南半球的预测精度高于北半球,且在高纬地区的RMSE小于3.6 mm,更适用于高纬地区的对流层延迟预测;在研究时域内,GP模型在大部分站点对晚上的预测精度高于白天,经度对ZTD预测精度的影响不明显,海拔与ZTD预测精度呈正比。     

Testing of global pressure/temperature (GPT) model and global mapping function (GMF) in GPS analyses

Several sources of a priori meteorological data have been compared for their effects on geodetic results from GPS precise point positioning (PPP). The new global pressure and temperature model (GPT), available at the IERS Conventions web site, provides pressure values that have been used to compute a priori hydrostatic (dry) zenith path delay z _h estimates. Both the GPT-derived and a simple height-dependent a priori constant z _h performed well for low- and mid-latitude stations. However, due to the actual variations not accounted for by the seasonal GPT model pressure values or the a priori constant z _h, GPS height solution errors can sometimes exceed 10 mm, particularly in Polar Regions or with elevation cutoff angles less than 10 degrees. Such height errors are nearly perfectly correlated with local pressure variations so that for most stations they partly (and for solutions with 5-degree elevation angle cutoff almost fully) compensate for the atmospheric loading displacements. Consequently, unlike PPP solutions utilizing a numerical weather model (NWM) or locally measured pressure data for a priori z _h, the GPT-based PPP height repeatabilities are better for most stations before rather than after correcting for atmospheric loading. At 5 of the 11 studied stations, for which measured local meteorological data were available, the PPP height errors caused by a priori z _h interpolated from gridded Vienna Mapping Function-1 (VMF1) data (from a NWM) were less than 0.5 mm. Height errors due to the global mapping function (GMF) are even larger than those caused by the GPT a priori pressure errors. The GMF height errors are mainly due to the hydrostatic mapping and for the solutions with 10-degree elevation cutoff they are about 50% larger than the GPT a priori errors.