Tropospheric refractivity and zenith path delays from least-squares collocation of meteorological and GNSS data

Precise positioning requires an accurate a priori troposphere model to enhance the solution quality. Several empirical models are available, but they may not properly characterize the state of troposphere, especially in severe weather conditions. Another possible solution is to use regional troposphere models based on real-time or near-real time measurements. In this study, we present the total refractivity and zenith total delay (ZTD) models based on a numerical weather prediction (NWP) model, Global Navigation Satellite System (GNSS) data and ground-based meteorological observations. We reconstruct the total refractivity profiles over the western part of Switzerland and the total refractivity profiles as well as ZTDs over Poland using the least-squares collocation software COMEDIE (Collocation of Meteorological Data for Interpretation and Estimation of Tropospheric Pathdelays) developed at ETH Zürich. In these two case studies, profiles of the total refractivity and ZTDs are calculated from different data sets. For Switzerland, the data set with the best agreement with the reference radiosonde (RS) measurements is the combination of ground-based meteorological observations and GNSS ZTDs. Introducing the horizontal gradients does not improve the vertical interpolation, and results in slightly larger biases and standard deviations. For Poland, the data set based on meteorological parameters from the NWP Weather Research and Forecasting (WRF) model and from a combination of the NWP model and GNSS ZTDs shows the best agreement with the reference RS data. In terms of ZTD, the combined NWP-GNSS observations and GNSS-only data set exhibit the best accuracy with an average bias (from all stations) of 3.7 mm and average standard deviations of 17.0 mm w.r.t. the reference GNSS stations.     

Troposphere gradients from the ECMWF in VLBI analysis

Modeling path delays in the neutral atmosphere for the analysis of Very Long Baseline Interferometry (VLBI) observations has been improved significantly in recent years by the use of elevation-dependent mapping functions based on data from numerical weather models. In this paper, we present a fast way of extracting both, hydrostatic and wet, linear horizontal gradients for the troposphere from data of the European Centre for Medium-range Weather Forecasts (ECMWF) model, as it is realized at the Vienna University of Technology on a routine basis for all stations of the International GNSS (Global Navigation Satellite Systems) Service (IGS) and International VLBI Service for Geodesy and Astrometry (IVS) stations. This approach only uses information about the refractivity gradients at the site vertical, but no information from the line-of-sight. VLBI analysis of the CONT02 and CONT05 campaigns, as well as all IVS-R1 and IVS-R4 sessions in the first half of 2006, shows that fixing these a priori gradients improves the repeatability for 74% (40 out of 54) of the VLBI baseline lengths compared to fixing zero or constant a priori gradients, and improves the repeatability for the majority of baselines compared to estimating 24-h offsets for the gradients. Only if 6-h offsets are estimated, the baseline length repeatabilities significantly improve, no matter which a priori gradients are used.     

Comparative analysis of real-time precise point positioning zenith total delay estimates

The continuous evolution of global navigation satellite systems (GNSS) meteorology has led to an increased use of associated observations for operational modern low-latency numerical weather prediction (NWP) models, which assimilate GNSS-derived zenith total delay (ZTD) estimates. The development of NWP models with faster assimilation cycles, e.g., 1-h assimilation cycle in the rapid update cycle NWP model, has increased the interest of the meteorological community toward sub-hour ZTD estimates. The suitability of real-time ZTD estimates obtained from three different precise point positioning software packages has been assessed by comparing them with the state-of-the-art IGS final troposphere product as well as collocated radiosonde (RS) observations. The ZTD estimates obtained by BNC2.7 show a mean bias of 0.21 cm, and those obtained by the G-Nut/Tefnut software library show a mean bias of 1.09 cm to the IGS final troposphere product. In comparison with the RS-based ZTD, the BNC2.7 solutions show mean biases between 1 and 2 cm, whereas the G-Nut/Tefnut solutions show mean biases between 2 and 3 cm with the RS-based ZTD, and the ambiguity float and ambiguity fixed solutions obtained by PPP-Wizard have mean biases between 6 and 7 cm with the references. The large biases in the time series from PPP-Wizard are due to the fact that this software has been developed for kinematic applications and hence does not apply receiver antenna eccentricity and phase center offset (PCO) corrections on the observations. Application of the eccentricity and PCO corrections to the a priori coordinates has resulted in a 66 % reduction of bias in the PPP-Wizard solutions. The biases are found to be stable over the whole period of the comparison, which are criteria (rather than the magnitude of the bias) for the suitability of ZTD estimates for use in NWP nowcasting. A millimeter-level impact on the ZTD estimates has also been observed in relation to ambiguity resolution. As a result of a comparison with the established user requirements for NWP nowcasting, it was found that both the G-Nut/Tefnut solutions and one of the BNC2.7 solutions meet the threshold requirements, whereas one of the BNC2.7 solution and both the PPP-Wizard solutions currently exceed this threshold.     

Modeling neutral-atmospheric electromagnetic delays in a “big data” world

If left unmodeled, the delay suffered by electromagnetic waves while crossing the neutral atmosphere negatively affects Global Navigation Satellite System positioning. The modeling of the delay has been carried out by means of empirical models formulated based on climatological information or using information extracted from numerical weather prediction (NWP) models. This paper explores the potential use of meteorological information of several types that will become available with the increasing number of sensors (e.g. a cell phone, or the thermometer of a nearby smart home) in cyberspace. How can we make use of these potentially huge data-sets, which may help to provide the best possible representation of the neutral atmosphere at any given time, as readily and as accurately as possible? This situation falls in the realm of Big Data. A few potential scenarios, a sequential improvement of Marini mapping function coefficients, a self-feeding NWP, and near real-time empirical model updates, are discussed in this paper. The pros and cons of each approach are discussed in comparison with what is done today. Experiments indicate that they have potential for a positive contribution.     

Atmospheric modelling in GPS analysis and its effect on the estimated geodetic parameters

Permanently operating Global Positioning System (GPS) receivers are used today, for example, in precise positioning and determination of atmospheric water vapour content. The GPS signals are delayed by various gases when traversing the atmosphere. The delay due to water vapour, the wet delay, is difficult to model using ground surface data and is thus often estimated from the GPS data. In order to obtain the most accurate results from the GPS processing, a modelling of the horizontal distribution of the wet delay may be necessary. Through simulations, three such models are evaluated, one of which is developed in this paper. In the first model the water vapour is assumed to be horizontally stratified, thus the wet delay can be described by only one zenith parameter. The second model gives the wet delay with one zenith and two horizontal gradient parameters. The third model uses the correlation between the wet-delay values in different directions. It is found that for large gradients and strong turbulence the two latter models yield lower errors in the estimated vertical coordinate and wet-delay parameters. For large gradients this improvement is up to 7 mm in the zenith wet-delay parameter, from 9 mm down to 2 and 4 mm for the second and third models, respectively. Received: 7 May 1998 / Accepted: 1 March 1999     

基于北斗的精密单点定位估计对流层天顶延迟精度分析

通过全球导航卫星（GNSS）系统获取对流层天顶延迟对于气象和电波折射修正具有重要应用价值。利用自主研发的静态精密单点定位软件CRPPP,基于国际GNSS地球动力学服务局（IGS）发布的北斗系统（BDS）精密星历和精密钟差,给出了BDS估算天顶延迟结果。以IGS发布的全球定位系统（GPS）结果为参考对比,BDS估算天顶延迟结果平均偏差优于5mm,均方根误差（rms）优于2．3cm．同时,给出了西沙地区GPS与BDS估计结果,结果表明：利用北斗系统估计的对流层天顶延迟精度与GPS相当。     

Using external tropospheric corrections to improve GNSS positioning of hot-air balloon

High accurate global navigation satellite systems (GNSS) require to correct a signal delay caused by the troposphere. The delay can be estimated along with other unknowns or introduced from external models. We assess the impact of the recently developed augmentation tropospheric model on real-time kinematic precise point positioning (PPP). The model is based on numerical weather forecast and thus reflects the actual state of weather conditions. Using the G-Nut/Geb software, we processed GNSS and meteorological data collected during the experiment using a hot-air balloon flying up to an altitude of 2000 m. We studied the impacts of random walk noise setting of zenith total delay (ZTD) on estimated parameters and the mutual correlations, the use of external tropospheric corrections, the use of data from a single or dual GNSS constellation and the use of Kalman filter and backward smoothing processing methods. We observed a significant negative correlation of the estimated rover height and ZTD which depends on constraining ZTD estimates. Such correlation caused a degraded performance of both parameters when estimated simultaneously, in particular for a single GNSS constellation. The impact of ZTD constraining reached up to 50-cm differences in the rover height. Introducing external tropospheric corrections improved the PPP solution regarding: (1) shortened convergence, (2) better overall robustness, particularly, in case of degraded satellite geometry, (3) less adjusted parameters with lower correlations. The numerical weather model-driven PPP resulted in 9–12- and 5–6-cm uncertainties in the rover altitude using the Kalman filter and the backward smoothing, respectively. Compared to standard PPP, it indicates better performance by a factor of 1–2 depending on the availability of GNSS constellations, the troposphere constraining and the processing strategy.     

基于GGOS Atmosphere数据的ZHD模型精度分析

对流层天顶干延迟(ZHD)建模是对流层延迟建模的一个重要组成部分,由于ZHD变化较为规律,因此,通常用模型来表达。而对流层天顶湿延迟(ZWD)变化不规则且随机性大,所以在GNSS处理中将它作为一个未知的待估参数。不精确的ZHD模型,会影响到ZWD估算的准确性,因此,选择精确合理的ZHD模型具有重要的意义。传统无线电探空仪数据获取的ZHD由于不能覆盖全球所有位置,尤其是海洋地区,而且在特殊天气使用也受限。为了更能全面反映ZHD模型的精度,本文尝试使用GGOS Atmosphere数据比较分析3种经典ZHD模型、即Saastamoinen模型、Hopfield模型和Black模型。通过对全球范围内的657个站点且时间覆盖长达5年的GGOS Atmosphere数据进行比较分析,我们得到以下结论:Saastamoinen模型优于Hopfield模型和Black模型,Saastamoinen模型的ZHD的精度可以优于1.5 mm。因此,在GNSS用户使用ZHD模型时,Saastamoinen模型可以作为使用模型。具体可以应用到GNSS大地测量学、GNSS车辆导航定位以及GNSS气象学。     

Ray-traced slant factors for mitigating the tropospheric delay at the observation level

Three-dimensional ray tracing through a numerical weather model has been applied to a global precise point positioning (PPP) campaign for modeling both the elevation angle- and azimuth-dependence of the tropospheric delay. Rather than applying the ray-traced slant delays directly, the delay has been parameterized in terms of slant factors, which are applied in a similar manner to traditional mapping functions, but which can account for the azimuthal asymmetry of the delay. Five strategies are considered: (1) Vienna Mapping Functions 1 (VMF1) and estimation of a residual zenith delay parameter; (2) VMF1, estimation of a residual zenith delay and estimation of two tropospheric gradient parameters; (3) three-dimensional ray-traced slant factors and estimation of a residual zenith delay; (4) using only ray-traced slant factors and no estimation of any tropospheric parameters and; (5) using both ray-traced slant factors and estimating a residual zenith delay and two tropospheric gradient parameters. The use of the ray-traced slant factors (solution 3) showed a 3.8% improvement in the repeatability of the up component when compared to the assumption of a symmetric atmosphere (solution 1), while the estimation of two tropospheric gradient parameters gave the best results showing an 7.6% improvement over solution 1 in the up component. Solution 4 performed well in the horizontal domain, allowing for sub-centimeter repeatability but the up component was degraded due to deficiencies in the modeling of the zenith delay, particularly for stations located at equatorial latitudes. The magnitude of the differences in the mean coordinates between solution 2 and solution 3, and the strong correlation with the differences between the north component and the ray-traced gradients (coefficient of correlation of 0.83), as well as the impact of observation geometry on the gradient solution indicate that the use of the ray-traced slant factors could have an implication on the realization of reference frames. The estimated tropospheric products from the PPP solutions were compared to those derived from ray tracing. For the zenith delay, a root mean square (RMS) of 5.4 mm was found, while for the gradient terms, a correlation coefficient of 0.46 for the N–S and 0.42 for the E–W was found for the north–south and east–west components, suggesting that there are still important differences in the gradient parameters which could be due to either errors in the NWM or to non-tropospheric error sources leaking into the PPP-estimated gradients.     

Troposphere delays from space geodetic techniques, water vapor radiometers, and numerical weather models over a series of continuous VLBI campaigns

Continuous, very long baseline interferometry (VLBI) campaigns over 2 weeks have been carried out repeatedly, i.e., CONT02 in October 2002, CONT05 in September 2005, CONT08 in August 2008, and CONT11 in September 2011, to demonstrate the highest accuracy the current VLBI was capable at that time. In this study, we have compared zenith total delays (ZTD) and troposphere gradients as consistently estimated from the observations of VLBI, Global Navigation Satellite Systems (GNSS), and Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) at VLBI sites participating in the CONT campaigns. We analyzed the CONT campaigns using the state-of-the-art software following common processing strategies as closely as possible. In parallel, ZTD and gradients were derived from numerical weather models, i.e., from the global European Centre for Medium-Range Weather Forecasts (ECMWF) analysis fields, the High Resolution Limited Area Model (European sites), the Japan Meteorological Agency-Operational Meso-Analysis Field (MANAL, over Japan), and the Cloud Resolving Storm Simulator (Tsukuba, Japan). Finally, zenith wet delays were estimated from the observations of water vapor radiometers (WVR) at sites where the WVR observables are available during the CONT sessions. The best ZTD agreement, interpreted as the smallest standard deviation, was found between GNSS and VLBI techniques to be about 5–6 mm at most of the co-located sites and CONT campaigns. We did not detect any significant improvement in the ZTD agreement between various techniques over time, except for DORIS and MANAL. On the other hand, the agreement and thus the accuracy of the troposphere parameters mainly depend on the amount of humidity in the atmosphere.     

UNB3m_pack: a neutral atmosphere delay package for radiometric space techniques

Several hybrid neutral atmosphere delay models have been developed at the University of New Brunswick. In this paper we are presenting UNB3m_pack, a package with subroutines in FORTRAN and corresponding functions in MatLab which provides neutral atmospheric information estimated using the UNB3m model. The main goal of UNB3m is to provide reliable predicted neutral atmosphere delays for users of global navigation satellite systems (GNSS) and other transatmospheric radiometric techniques. Slant neutral atmosphere delays are the main output of the package, however, it can be used to estimate zenith delays, Niell mapping functions values, delay rates, mapping function rates, station pressure, temperature, relative humidity and the mean temperature of water vapor in the atmospheric column. The subroutines work using day of year, latitude, height and elevation angle as input values. The files of the package have a commented section at the beginning, explaining how the subroutines work and what the input and output parameters are. The subroutines are self-contained, i.e., they do not need any auxiliary files. The user has simply to add to his/her software one or more of the available files and call them in the appropriate way. The GPS Tool Box is a column dedicated to highlighting algorithms and source code utilized by GPS engineers and scientists. If you have an interesting program or software package you would like to share with our readers, please pass it along; e-mail it to us at gps-toolbox@ngs.noaa.gov. To comment on any of the source code discussed here, or to download source code, visit our website at . This column is edited by Stephen Hilla, National Geodetic Survey, NOAA, Silver Spring, Maryland, and Mike Craymer, Geodetic Survey Division, Natural Resources Canada, Ottawa, Ontario, Canada.     

Assessment of ECMWF-derived tropospheric delay models within the EUREF Permanent Network

The Global Positioning System (GPS) observations from the EUREF Permanent Network (EPN) are routinely analyzed by the EPN analysis centers using a tropospheric delay modeling based on standard pressure values, the Niell Mapping Functions (NMF), a cutoff angle of 3° and down-weighting of low elevation observations. We investigate the impact on EPN station heights and Zenith Total Delay (ZTD) estimates when changing to improved models recommended in the updated 2003 International Earth Rotation and Reference Systems Service (IERS) Conventions, which are the Vienna Mapping Functions 1 (VMF1) and zenith hydrostatic delays derived from numerical weather models, or the empirical Global Mapping Functions (GMF) and the empirical Global Pressure and Temperature (GPT) model. A 1-year Global Positioning System (GPS) data set of 50 regionally distributed EPN/IGS (International GNSS Service) stations is processed. The GPS analysis with cutoff elevation angles of 3, 5, and 10° revealed that changing to the new recommended models introduces biases in station heights in the northern part of Europe by 2–3 mm if the cutoff is lower than 5°. However, since large weather changes at synoptic time scales are not accounted for in the empirical models, repeatability of height and ZTD time series are improved with the use of a priori Zenith Hydrostatic Delays (ZHDs) derived from numerical weather models and VMF1. With a cutoff angle of 3°, the repeatability of station heights in the northern part of Europe is improved by 3–4 mm.     

Optimum stochastic modeling for GNSS tropospheric delay estimation in real-time

GPS Solutions - In GNSS data processing, the station height, receiver clock and tropospheric delay (ZTD) are highly correlated to each other. Although the zenith hydrostatic delay of the...     

基于中尺度气象模式（MM5）计算GNSS对流层水汽延时

基于中尺度气象模式MM5得到的三维气象场数据,建立了渤海湾地区的湿折射率场。采用切比雪夫多项式和微积分等数学方法计算了GNSS卫星信号传播方向上的水汽延时。通过与Bernese软件处理的GNSS结果比较分析来看,二者天顶总延时相差最大不超过2cm,在1cm附近波动。得到的湿延偏差在7mm左右,最大相差10mm.MM5模式积分计算的水汽延时结果可信,具有较理想的精度。     

A reference station-based GNSS computing mode to support unified precise point positioning and real-time kinematic services

Currently, the GNSS computing modes are of two classes: network-based data processing and user receiver-based processing. A GNSS reference receiver station essentially contributes raw measurement data in either the RINEX file format or as real-time data streams in the RTCM format. Very little computation is carried out by the reference station. The existing network-based processing modes, regardless of whether they are executed in real-time or post-processed modes, are centralised or sequential. This paper describes a distributed GNSS computing framework that incorporates three GNSS modes: reference station-based, user receiver-based and network-based data processing. Raw data streams from each GNSS reference receiver station are processed in a distributed manner, i.e., either at the station itself or at a hosting data server/processor, to generate station-based solutions, or reference receiver-specific parameters. These may include precise receiver clock, zenith tropospheric delay, differential code biases, ambiguity parameters, ionospheric delays, as well as line-of-sight information such as azimuth and elevation angles. Covariance information for estimated parameters may also be optionally provided. In such a mode the nearby precise point positioning (PPP) or real-time kinematic (RTK) users can directly use the corrections from all or some of the stations for real-time precise positioning via a data server. At the user receiver, PPP and RTK techniques are unified under the same observation models, and the distinction is how the user receiver software deals with corrections from the reference station solutions and the ambiguity estimation in the observation equations. Numerical tests demonstrate good convergence behaviour for differential code bias and ambiguity estimates derived individually with single reference stations. With station-based solutions from three reference stations within distances of 22–103 km the user receiver positioning results, with various schemes, show an accuracy improvement of the proposed station-augmented PPP and ambiguity-fixed PPP solutions with respect to the standard float PPP solutions without station augmentation and ambiguity resolutions. Overall, the proposed reference station-based GNSS computing mode can support PPP and RTK positioning services as a simpler alternative to the existing network-based RTK or regionally augmented PPP systems.     

Using a regional numerical weather prediction model for GNSS positioning over Brazil

The global navigation satellite system (GNSS) can provide centimeter positioning accuracy at low costs. However, in order to obtain the desired high accuracy, it is necessary to use high-quality atmospheric models. We focus on the troposphere, which is an important topic of research in Brazil where the tropospheric characteristics are unique, both spatially and temporally. There are dry regions, which lie mainly in the central part of the country. However, the most interesting area for the investigation of tropospheric models is the wet region which is located in the Amazon forest. This region substantially affects the variability of humidity over other regions of Brazil. It provides a large quantity of water vapor through the humidity convergence zone, especially for the southeast region. The interconnection and large fluxes of water vapor can generate serious deficiencies in tropospheric modeling. The CPTEC/INPE (Center for Weather Forecasting and Climate Studies/Brazilian Institute for Space Research) has been providing since July 2012 a numerical weather prediction (NWP) model for South America, known as Eta. It has yield excellent results in weather prediction but has not been used in GNSS positioning. This NWP model was evaluated in precise point positioning (PPP) and network-based positioning. Concerning PPP, the best positioning results were obtained for the station SAGA, located in Amazon region. Using the NWP model, the 3D RMS are less than 10 cm for all 24 h of data, whereas the values reach approximately 60 cm for the Hopfield model. For network-based positioning, the best results were obtained mainly when the tropospheric characteristics are critical, in which case an improvement of up to 7.2 % was obtained in 3D RMS using NWP models.     

融合大气数值模式的高精度对流层天顶延迟计算方法

针对现有对流层天顶延迟模型改正法因水汽参数难以精确获取所导致的时空分辨率与精度上的不足问题,提出了一种融合WRF(weather research and forecasting model)大气数值模式的对流层天顶延迟估计方法。通过分析WRF模式的数值模拟机理及其数据结构特征,采用直接积分与模型改正相结合的混合计算方式,实现了全球任意位置上小时级的对流层天顶延迟估计。验证结果表明,该方法计算的小时级ZTD再分析值精度为13.6mm,日均值精度更是可达9.3mm,比传统模型UNB3m的49.6mm以及目前标称精度最高模型GPT2w的34.6mm,精度分别提高了约5倍和3.5倍。在30h的预报时段内,预报值精度也可达22mm。无论是ZTD再分析值还是预报值比现有模型的估计值精度均有明显提高。     

Analysis of tropospheric delay prediction models: comparisons with ray-tracing and implications for GPS relative positioning

Ray-tracing is used to examine the accuracy of several well known models for tropospheric delay prediction under varying atmospheric conditions. The models considered include the Hopfield zenith delay model and related mapping functions, the Saastamoinen zenith delay model and mapping function, and three empirical mapping functions based upon the Marini continued fraction form. Modelled delays are benchmarked against ray-tracing solutions for representative atmospheric profiles at various latitudes and seasons. Numerical results are presented in light of the approximations inherent in model formulation. The effect of approximations to the temperature, pressure and humidity structure of the neutral atmosphere are considered; the impact of surface layer anomalies (i.e., inversions) on prediction accuracy is examined; and errors resulting from the neglect of ray bending are illustrated. The influence of surface meteorological parameter measurement error is examined. Finally, model adaptability to local conditions is considered. Recommendations concerning the suitability of the models for GPS relative positioning and their optimal application are made based upon the results presented.     

PPPH: a MATLAB-based software for multi-GNSS precise point positioning analysis

The integration of different GNSS constellations offers considerable opportunities to improve Precise Point Positioning (PPP) performance. Being aware of the limited number of the alternatives that utilize the potential advantages of the multi-constellation and multi-frequency GNSS, we developed a MATLAB-based GNSS analysis software, named PPPH. PPPH is capable of processing GPS, GLONASS, Galileo and BeiDou data, and forming their different combinations depending on user’s preference. Thanks to its user-friendly graphical interface, PPPH allows users to determine a variety of processing options and parameters. In addition to an output file including the estimated parameters for every single epoch, PPPH also presents several analyzing and plotting tools for evaluating the results, such as positioning error, tropospheric zenith total delay, receiver clock estimation, satellite number, dilution of precisions. On the other hand, we conducted experimental tests to both validate the performance of PPPH and assess the potential benefits of multi-GNSS on PPP. The results indicate that PPPH provides comparable PPP solution with the general standards and also contributes to the improvement of PPP performance with the integration of multi-GNSS. Consequently, we introduce a GNSS analysis software that is easy to use, has a robust performance and is open to progress with its modular structure.     

Assessment of local GNSS baselines at co-location sites

As one of the major contributors to the realisation of the International Terrestrial Reference System (ITRS), the Global Navigation Satellite Systems (GNSS) are prone to suffer from irregularities and discontinuities in time series. While often associated with hardware/software changes and the influence of the local environment, these discrepancies constitute a major threat for ITRS realisations. Co-located GNSS at fundamental sites, with two or more available instruments, provide the opportunity to mitigate their influence while improving the accuracy of estimated positions by examining data breaks, local biases, deformations, time-dependent variations and the comparison of GNSS baselines with existing local tie measurements. With the use of co-located GNSS data from a subset sites of the International GNSS Service network, this paper discusses a global multi-year analysis with the aim of delivering homogeneous time series of coordinates to analyse system-specific error sources in the local baselines. Results based on the comparison of different GNSS-based solutions with the local survey ties show discrepancies of up to 10 mm despite GNSS coordinate repeatabilities at the sub-mm level. The discrepancies are especially large for the solutions using the ionosphere-free linear combination and estimating tropospheric zenith delays, thus corresponding to the processing strategy used for global solutions. Snow on the antennas causes further problems and seasonal variations of the station coordinates. These demonstrate the need for a permanent high-quality monitoring of the effects present in the short GNSS baselines at fundamental sites.