Tropospheric Zenith Total Delay Research Articles

An Efficient Deep Learning-Based Troposphere ZTD Dataset Generation Method for Massive GNSS CORS Stations

Nowadays, a huge amount of GNSS continuously operating reference stations (CORS) have been established around the world, which have already been and will continue providing massive troposphere zenith total delay (ZTD) data. This paper proposes an efficient deep learning-based troposphere ZTD dataset generation method including ZTD series segmentation, addictive and innovational outlier detection, and missing data imputation. The overall standard deviation of first-order ZTD difference series between adjacent epochs of the selected CORS station in January 2018 is reduced from 0.84 to 0.26 mm with the 3-sigma rule and the wavelet decomposition strategy for outlier elimination. A dense neural network (DNN) is subsequently designed to impute missing ZTD data. Only 3.4 minutes are required for the DNN training using a NVIDIA GeForce RTX 3090Ti GPU. The complete ZTD series with missing ZTD data imputed by the well-trained DNN model has a good agreement with the ZTD series before the data imputation in terms of mean value (-0.0184 vs -0.0187 mm) and standard deviation (5.43 vs 5.26 mm). Complete ZTD series of 120 CORS stations are generated to further evaluate the computational efficiency of the proposed method. An average of 2.56/5.38/5.77/4.33 hours are necessary to generate the ZTD dataset for January/April/July/October in 2018, respectively. Our study confirms that the proposed method can efficiently generate CORS-based ZTD dataset, which could be extended to applications including troposphere temporal-spatial pattern exploration and ZTD augmentation on high-precision GNSS positioning.

Preliminary Results on Tropospheric ZTD Estimation by Smartphone

The Global Navigation Satellite System (GNSS) receiver is one of the many sensors embedded in smartphones. The early versions of the Android operating system could only access limited information from the GNSS, allowing the related Application Program Interface (API) to obtain only the location. With the development of the Android 7.0 (Nougat) operating system in May 2016, raw measurements from the internal GNSS sensor installed in the smartphone could be accessed. This work aims to show an initial analysis regarding the feasibility of Zenith Total Delay (ZTD) estimation by GNSS measurements extracted from smartphones, evaluating the accuracy of estimation to open a new window on troposphere local monitoring. Two different test sites have been considered, and two different types of software for data processing have been used. ZTDs have been estimated from both a dual-frequency and a multi-constellation receiver embedded in the smartphone, and from a GNSS Continuously Operating Reference Station (CORS). The results have shown interesting performances in terms of ZTD estimation from the smartphone in respect of the estimations obtained with a geodetic receiver.

Estimating Station Specific Zenith Tropospheric Delay in a Local GPS Network from Observed Surface Meteorology

The total zenith tropospheric delay (ZTD) is an important parameter of the atmosphere which directly or indirectly give reflection of the atmospheric condition in a local GPS network. The use of the global tropospheric models such as the Saastamoinen model, Hopfield model, Neil model etc in estimating the tropospheric effects at the local level leaves much to be desired. These models are derived using data from available radiosonde obtained from Europe and North America continents. The global atmospheric condition used as constants in these models provides a broad approximation of the tropospheric conditions, but ignores the actual atmospheric conditions on a given location i.e. do not take into account the latitudinal and seasonal variations in the atmosphere. It is necessary to assess the effects of the troposphere on geodetic measurements based on ground meteorological measurements including temperature, pressure, and relative humidity. Daily RINEX GPS data from eight (8) Malaysian Real Time Kinematic GPS Network (MyRTKnet) stations in Southern Malaysia from year 2006 to June 2008 thus; covering 2½ years were processed. A computer program for modelling 2½ years of local meteorology within the network was developed and called MetMOD, similarly a program, call SaastroMOD was developed to estimate the local zenith hydrostatic delay. The results showed that, the estimated local tropospheric delay considered the temporal and spatial variation of the network thus; giving true reflection of the tropospheric delay in a local GPS network as against the standard atmosphere which ignores the actual local condition with a standard deviation of 0.18 m having a maximum zenith tropospheric delay (ZTD) of about 2.6 m. The best zenith hydrostatic delay (ZHD) comes from station JHJY with a standard deviation of 0.353 cm, while the best zenith wet delay (ZWD) comes from station TGRH with a standard deviation of 5.943 cm. The models show that, while parameters evolved for ZHD are constant at different locations, however, those parameters evolved for ZWD show significant variations from one location to the other. Hence then use of the local meteorological parameter in modelling tropospheric delay improves GPS positional accuracy.

Зенитная тропосферная задержка по данным GPS наблюдений и измерений радиометром водяного пара в пункте Badg (Бадары, Республика Бурятия)

A comparison was carried out of the values of the total zenith tropospheric delay (ZTD) revealed from the observations of the GPS satellite navigation system and measurements by a microwave radiometer of water vapor (MRWV) at the BADG permanent measurement point located on the territory of the “Badary” Observatory of the Institute of Applied Astronomy of the Russian Academy of Sciences. GPS antenna, MRWV device and meteorological station are located in close proximity to each other. This significantly affected the accuracy of the processed data. The differences in the values of the total zenith tropospheric delay obtained from GPS observations and measurements with a microwave radiometer of water vapor are analyzed in terms of mean and standard deviations and the coefficient of cross-correlation. Comparison of the results for 2020 year showed very good agreement. In summer, the BIAS of the difference between the ZTD data from GPS and MRWV observations is about 0.63% of the average summer ZTD value, the cross-correlation coefficient between the data is K = 0.85. In winter, the BIAS of the difference was about 0.21% of the average winter value of ZTD, the cross-correlation coefficient between the data is about K = 0.93. A high degree of reliability of data on ZTD and tropospheric moisture content obtained by continuous GPS measurements is shown.

ASSESSMENT OF ATMOSPHERIC WATER VAPOR REMOTE SENSING USING GPS SIGNALS BY RADIOSONDE AND MODIS SATELLITE IMAGES

This paper is an evaluation of the atmospheric water vapor remote sensing by GPS signals. The integrated water vapor (IWV) is calculated based on the measurement of the tropospheric zenith total delay (ZTD) effects on the microwave signals emitted by GPS satellites. The methodology proposed in this work is based on the combination of the global navigation satellite system (GNSS) observations and navigation data from the international GNSS service (IGS) products with meteorological data, measured at the stations level, to calculate the ZTD delay and estimate the integrated water vapor value. This work was carried out using data records from12 IGS stations distributed in seven countries in the four seasons of the year. The obtained results are compared with the values generated by Radiosonde measurement and MODIS satellite images level 2 (Water Vapor data product). In more than 90% of cases, the difference between the GPS and Radiosonde solutions is less than 3 mm with a monthly RMS less than 1.6 and a correlation of about 95%. The comparison between the GPS and MODIS shows that in more than 65 % of the time, the difference between the two solutions is less than 4 mm with amonthly RMS less than 2.3, and the correlation is about 73%.

The Impact of Different Ocean Tide Loading Models on GNSS Estimated Zenith Tropospheric Delay Using Precise Point Positioning Technique

Global navigation satellite systems (GNSSs) have become an important tool to derive atmospheric products, such as the total zenith tropospheric delay (ZTD) and precipitable water vapor (PWV) for weather and climate studies. The ocean tide loading (OTL) effect is one of the primary errors that affects the accuracy of GNSS-derived ZTD/PWV, which means the study and choice of the OTL model is an important issue for high-accuracy ZTD estimation. In this study, GNSS data from 1 January 2019 to 31 January 2019 are processed using precise point positioning (PPP) at globally distributed stations. The performance of seven widely used global OTL models is assessed and their impact on the GNSS-derived ZTD is investigated by comparing them against the ZTD calculated from co-located radiosonde observations. The results indicate that the inclusion or exclusion of the OTL effect will lead to a difference in ZTD of up to 3–15 mm for island stations, and up to 1–2 mm for inland stations. The difference of the ZTD determined with different OTL models is quite small, with a root-mean-square (RMS) value below 1.5 mm at most stations. The comparison between the GNSS-derived ZTD and the radiosonde-derived ZTD indicates that the adoption of OTL models can improve the accuracy of GNSS-derived ZTD. The results also indicate that the adoption of a smaller cutoff elevation, e.g., 3° or 7°, can significantly reduce the difference between the ZTDs determined by GNSS and radiosonde, when compared against a 15° cutoff elevation. Compared to the radiosonde-derived ZTD, the RMS error of GNSS-derived ZTD is approximately 25–35 mm at a cutoff elevation of 15°, and 15–25 mm when the cutoff elevation is set to 3°.

Evaluation of precipitable water vapor variation for east mediterranean using GNSS

The study of climate change is an important field of research. Monitoring of atmospheric variability especially the tropospheric precipitable water vapor (PWV) is a powerful way to investigate climate change. Global navigation satellite systems (GNSS) provide a good tool for studying atmospheric parameters as GNSS signals along its path from the satellites to the ground based receivers suffer a significant delay due to the refractivity of earth’s atmosphere. GNSS signals are not only delayed but also refracted in the neutral atmosphere. The zenith wet delays (ZWD) caused by the troposphere can be estimated during the geodetic processing of GNSS signals. Since the ZWD is tightly correlated to the PWV, GNSS observations can be used to study the changes of PWV. In this study GNSS data from the Egyptian permanent GNSS network (EPGN), International GNSS Service (IGS), EUREF Permanent Network (EPN) and Scripps Orbit and Permanent Array Center (SOPAC), for the years 2013 and 2014, were used. These GNSS stations provided a good geometrical coverage over the respective region. All GNSS data were processed using Bernese V 5.2 software. The needed product from GNSS data processing is the tropospheric zenith total delay (ZTD) over each GNSS site. The ZTD is divided based on physical parameters into zenith hydrostatic delay (ZHD) and zenith wet delay (ZWD). The ZWD is the basic observable used to calculate PWV. The values of the PWV were calculated and its variation over the study area was investigated. The quality of calculated PWV values from GNSS data evaluated against traditional Radiosonde (RS) measurements. The results of GNSS PWV showed good agreement with RS PWV when the PWV values were low, but this agreement became worse at high PWV values as the differences between the two techniques increased. The correlation coefficient between RS PWV and GNSS PWV varied from 0.31 to 0.84. Standard deviation of the differences between RS PWV and GNSS PWV ranged from 2.369 to 5.973 mm. The PWV estimated from GNSS observations had annual cycle, and its cycle in 2013 was different from that in 2014. The PWV differences between the 2 years clarified that the water vapor content over the east Mediterranean in most of 2014 days was higher than that in 2013. Furthermore, PWV variations were noted on both temporal and spatial scales. The highest temporal variation value was 25.41 mm whereas the maximum value of the spatial variation was 19.67 mm. The present study illustrated the importance of using geodetic networks to provide atmospheric information.

Study of the moisture content of the troposphere over the ULAB (Ulaanbaatar) monitoring station using GPS measurement, radio sounding and surface meteorology data

The water vapor content is calculated in a conditional vertical column to the tropopause level from remote sensing data on the lower atmosphere . The calculations are based on GPS measurements, surface meteorological data and vertical meteorological profiles produced by radiosonde s. A total zenith tropospheric delay (ZTD) is estimated as a difference between an estimated straight line , along which the GPS signal propagates in vacuum , and a length of the path between the signal source and the receiver , which is refracted in the real medium. A direct correlation is noted between changes in the ‘ wet ’ component of the tropospheric delay of the GPS signal and variations in the moisture content of the troposphere. A ‘ wet ’ component value of the tropospheric delay can be converted with a very high confidence into a value of integral water vapor above the observation point. In order to determine the integral water vapor amount s over the ULAB (Ulaanbaatar) permanent GPS monitoring station, empirical equations were used for the linear regressions of the ratios of surface temperature and mean weighted temperature for the water vapor elasticity using the data of radiosonde s launche d in the city of Ulaanbaatar and Muren settlement. We studied the features of the dynamics of variations in the integral water vapor, surface values of atmospheric pressure, air temperature and precipitation volumes over the ULAB station, using the data of July 2016.

Real-time tropospheric delay retrieval with GPS, GLONASS, Galileo and BDS data

The precise point positioning (PPP) is a promising technology for the real-time retrieval of atmospheric parameters with a single receiver in anywhere, all-weather and any time. The real-time atmospheric parameters can be applied to the time-critical meteorology, such as the severe weather nowcasting. The PPP is a satellite-based technology. Multi-constellation integration can enhance satellite geometry and increase measurement redundancy so that the solutions of atmospheric parameters are expected to be improved. Currently, the Global Navigation Satellite System (GNSS) family includes recovered GLONASS and modernized GPS as well as the emerging Galileo and BDS. A week of GNSS observations from 160 stations are processed to retrieve the tropospheric zenith total delay (ZTD) in real time. The four-constellation mixed real-time precise products including satellite orbit and clock corrections are adopted, and their quality is evaluated. The performance of ZTD estimates is assessed in terms of accuracy and convergence time by comparing with final tropospheric ZTD products provided by two analysis centers. The ZTDs retrieved from different constellation combinations (i.e., GPS/GLONASS/Galileo/BDS, GPS/GLONASS, and GPS-only), different processing models for ionospheric delays (i.e., ionospheric-free (IF) combined PPP, and uncombined (UC) PPP), and different modes (i.e., real-time mode, and post-processing mode) are compared.

On the Statistical Significance of Climatic Trends Estimated From GPS Tropospheric Time Series

AbstractFor more than two decades, Global Positioning System (GPS) tropospheric delays have successfully been exploited to monitor the tropospheric water vapor in near real time and reprocessing mode. Although reprocessed data are considered reliable for climatic research, it is important to address the often present gaps, inhomogeneities, and to use a proper model to describe the stochastic part of the time series so that trustworthy trends are estimated. Having relatively long time series, daily reprocessed tropospheric Zenith Total Delay, precipitable water vapor (PWV), and gradients from the Tide Gauge benchmark monitoring network are used in this work to estimate climatic trends. We use a first‐order autoregressive model AR(1) to describe the residuals after the trend estimation so that a correct trend uncertainty is estimated. Using the same model, we obtain the number of years of PWV data required to estimate statistically significant trends. For comparison, we produce tropospheric parameters at each Tide Gauge station based on ERA‐Interim refractivity fields. We found that 83% of 64 GPS stations show a positive PWV trend below 1 mm/decade independent of the time interval, with approximately half of the trends indicated significant. There is a strong correlation (86%) between the Global Navigation Satellite Systems and ERA‐Interim PWV trends. The trends tend to increase when moving east and south on the European map. The results show a percentage change of PWV of 3–8% per a degree Celsius rise in temperature. The number of years required to detect significant PWV trends varies between 30 and 40 years.

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.

GGOS tropospheric delay forecast product performance evaluation and its application in real-time PPP

Tropospheric delay is one of the main error sources in Global Navigation Satellite System (GNSS) precise positioning, as the GNSS signal is influenced by refraction when travelling through the troposphere. Generally, tropospheric delay is estimated as a parameter in GNSS data processing. With the increasing demand for GNSS real-time applications, high-precision tropospheric delay augmentation information is essential to enhance convergence speed and precision of positioning. The Global Geodetic Observing System (GGOS) Atmosphere provides total zenith tropospheric delay (ZTD) forecast grid data, globally, one day in advance, where the time resolution is 6 h and spatial resolution is 2.5° × 2°. Here, the GGOS ZTD forecast product is assessed compared with ZTD information from global IGS sites, including an analysis of the spatial and temporal distribution of its error and the weather influence on its precision. Ultimately, the application effect of the GGOS Atmosphere ZTD forecast product in real-time precise point positioning (PPP) is examined. The results show that the positioning precision and the speed of convergence are obviously advanced, especially in the U direction, which informs the potential for real-time application of GGOS forecast products.

Global model of zenith tropospheric delay proposed based on EOF analysis

Tropospheric delay is one of the main error budgets in Global Navigation Satellite System (GNSS) measurements. Many empirical correction models have been developed to compensate this delay, and models which do not require meteorological parameters have received the most attention. This study established a global troposphere zenith total delay (ZTD) model, called Global Empirical Orthogonal Function Troposphere (GEOFT), based on the empirical orthogonal function (EOF, also known as geographically weighted PCAs) analysis method and the Global Geodetic Observing System (GGOS) Atmosphere data from 2012 to 2015. The results showed that ZTD variation could be well represented by the characteristics of the EOF base function Ek and associated coefficients Pk. Here, E1 mainly signifies the equatorial anomaly; E2 represents north–south asymmetry, and E3 and E4 reflects regional variation. Moreover, P1 mainly reflects annual and semiannual variation components; P2 and P3 mainly contains annual variation components, and P4 displays semiannual variation components. We validated the proposed GEOFT model using tropospheric delay data of GGOS ZTD grid data and the tropospheric product of the International GNSS Service (IGS) over the year 2016. The results showed that GEOFT model has high accuracy with bias and RMS of −0.3 and 3.9cm, respectively, with respect to the GGOS ZTD data, and of −0.8 and 4.1cm, respectively, with respect to the global IGS tropospheric product. The accuracy of GEOFT demonstrating that the use of the EOF analysis method to characterize ZTD variation is reasonable.

Generation of real‐time mode high‐resolution water vapor fields from GPS observations

AbstractPointwise GPS measurements of tropospheric zenith total delay can be interpolated to provide high‐resolution water vapor maps which may be used for correcting synthetic aperture radar images, for numeral weather prediction, and for correcting Network Real‐time Kinematic GPS observations. Several previous studies have addressed the importance of the elevation dependency of water vapor, but it is often a challenge to separate elevation‐dependent tropospheric delays from turbulent components. In this paper, we present an iterative tropospheric decomposition interpolation model that decouples the elevation and turbulent tropospheric delay components. For a 150 km × 150 km California study region, we estimate real‐time mode zenith total delays at 41 GPS stations over 1 year by using the precise point positioning technique and demonstrate that the decoupled interpolation model generates improved high‐resolution tropospheric delay maps compared with previous tropospheric turbulence‐ and elevation‐dependent models. Cross validation of the GPS zenith total delays yields an RMS error of 4.6 mm with the decoupled interpolation model, compared with 8.4 mm with the previous model. On converting the GPS zenith wet delays to precipitable water vapor and interpolating to 1 km grid cells across the region, validations with the Moderate Resolution Imaging Spectroradiometer near‐IR water vapor product show 1.7 mm RMS differences by using the decoupled model, compared with 2.0 mm for the previous interpolation model. Such results are obtained without differencing the tropospheric delays or water vapor estimates in time or space, while the errors are similar over flat and mountainous terrains, as well as for both inland and coastal areas.

The impact of solid Earth-tide model error on tropospheric zenith delay estimates and GPS coordinate time series

Any unmodelled or mismodelled subdaily signals left in the model may not only affect the instantaneous site positions and the associated estimates, but also propagate into spurious seasonal signals, contaminating the daily coordinate time series. To demonstrate how subdaily ‘error’ in the modelling of the solid Earth-tide affects the estimates of tropospheric zenith total delay (ZTD) and how it propagates into long-period signal in the daily GPS time series, we analyse GPS observations collected between 2009 and 2013 for 13 sites in the coastal regions of Antarctica using the GAMIT/GLOBK 10.6 software. We find that ZTD differenced time series, with amplitude at 2 mm level, have inverse correlation with the input K1 correction, and the corresponding admittances range from 6% to 14%; Propagated spurious annual signals are evident in the vertical component of coordinate differenced time series, with amplitudes at the mm level and admittances of around 2–11%.

Tropospheric Anomaly Detection in Multi-reference Stations Environment during Localized Atmosphere Conditions-(1) : Basic Concept of Anomaly Detection Algorithm

Extreme tropospheric anomalies such as typhoons or regional torrential rain can degrade positioning accuracy of the GPS signal. It becomes one of the main error terms affecting high-precision positioning solutions in network RTK. This paper proposed a detection algorithm to be used during atmospheric anomalies in order to detect the tropospheric irregularities that can degrade the quality of correction data due to network errors caused by inhomogeneous atmospheric conditions between multi-reference stations. It uses an atmospheric grid that consists of four meteorological stations and estimates the troposphere zenith total delay difference at a low performance point in an atmospheric grid. AWS (automatic weather station) meteorological data can be applied to the proposed tropospheric anomaly detection algorithm when there are different atmospheric conditions between the stations. The concept of probability density distribution of the delta troposphere slant delay was proposed for the threshold determination.

Multi-year GNSS monitoring of atmospheric IWV over Central and South America for climate studies

Abstract. Atmospheric water vapour has been acknowledged as an essential climate variable. Weather prediction and hazard assessment systems benefit from real-time observations, whereas long-term records contribute to climate studies. Nowadays, ground-based global navigation satellite system (GNSS) products have become widely employed, complementing satellite observations over the oceans. Although the past decade has seen a significant development of the GNSS infrastructure in Central and South America, its potential for atmospheric water vapour monitoring has not been fully exploited. With this in mind, we have performed a regional, 7-year-long and homogeneous analysis, comprising 136 GNSS tracking stations, obtaining high-rate and continuous observations of column-integrated water vapour and troposphere zenith total delay. As a preliminary application for this data set, we have estimated local water vapour trends, their significance, and their relation with specific climate regimes. We have found evidence of drying at temperate regions in South America, at a rate of about 2 % per decade, while a slow moistening of the troposphere over tropical regions is also weakly suggested by our results. Furthermore, we have assessed the regional performance of the empirical model GPT2w to blindly estimate troposphere delays. The model reproduces the observed mean delays fairly well, including their annual and semi-annual variations. Nevertheless, a long-term evaluation has shown systematical biases, up to 20 mm, probably inherited from the underlying atmospheric reanalysis. Additionally, the complete data set has been made openly available as supplementary material.

Evaluation of ocean tide loading effects on GPS-estimated precipitable water vapour in Turkey

Global Positioning System (GPS) has been widely used to estimate the total zenith tropospheric delay (ZTD) and precipitable water vapour (PWV) for weather prediction and atmospheric research as a continuous and all-weather technique. However, estimations of ZTD and PWV are subject to effects of geophysical models with large uncertainties, particularly imprecise ocean tide models of inland seas in Turkey. In this paper, GPS data from Jan. 1, 2010 to Dec. 31, 2011 are processed using GAMIT/GLOBK at four co-located GPS stations (ISTN, ERZR, SAMN, and IZMI) with Radiosonde from the Turkish Met-Office together with several nearby IGS stations. Four widely used ocean tide models are adopted to evaluate their effects on GPS-estimated PWV, such as IERS recommended FES2004, NAO99b, CSR4.0 and GOT00. Five different strategies are taken without ocean tide model and with four ocean tide models, respectively, which are used to evaluate ocean tide models effects on GPS-estimated PWV through comparing with co-located Radiosonde. Results showed that ocean tide models have greatly affected the estimation of the precipitable water vapour at stations near coasts. The ocean tide model FES2004 gave the best results when compared to Radiosonde with ±2.12 mm in PWV at stations near coastline. While other ocean tides models agree each other at millimeter level in PWV. However, at inland GPS stations, ocean tide models have less effect on GPS-estimated PWV.

EFFECTS OF OCEAN TIDE MODELS ON GNSS-ESTIMATED ZTD AND PWV IN TURKEY

Abstract. Global Navigation Satellite System (GNSS) observations can precisely estimate the total zenith tropospheric delay (ZTD) and precipitable water vapour (PWV) for weather prediction and atmospheric research as a continuous and all-weather technique. However, apart from GNSS technique itself, estimations of ZTD and PWV are subject to effects of geophysical models with large uncertainties, particularly imprecise ocean tide models in Turkey. In this paper, GNSS data from Jan. 1st to Dec. 31st of 2014 are processed at 4 co-located GNSS stations (GISM, DIYB, GANM, and ADAN) with radiosonde from Turkish Met-Office along with several nearby IGS stations. The GAMIT/GLOBK software has been used to process GNSS data of 30-second sample using the Vienna Mapping Function and 10° elevation cut-off angle. Also tidal and non-tidal atmospheric pressure loadings (ATML) at the observation level are also applied in GAMIT/GLOBK. Several widely used ocean tide models are used to evaluate their effects on GNSS-estimated ZTD and PWV estimation, such as IERS recommended FES2004, NAO99b from a barotropic hydrodynamic model, CSR4.0 obtained from TOPEX/Poseidon altimetry with the model FES94.1 as the reference model and GOT00 which is again long wavelength adjustments of FES94.1 using TOPEX/Poseidon data at 0.5 by 0.5 degree grid. The ZTD and PWV computed from radiosonde profile observations are regarded as reference values for the comparison and validation. In the processing phase, five different strategies are taken without ocean tide model and with four aforementioned ocean tide models, respectively, which are used to evaluate ocean tide models effects on GNSS-estimated ZTD and PWV estimation through comparing with co-located Radiosonde. Results showed that ocean tide models have greatly affected the estimation of the ZTD in centimeter level and thus the precipitable water vapour in millimeter level, respectively at stations near coasts. The ocean tide model FES2004 that is the product of assimilation of the altimetric data of ERS2, TOPEX/POSEIDON and the data of a global tide gauge network, gave the most accurate results when compared to radiosonde with ±1.99 mm in PWV at stations near coastline. While other ocean tides models agree each other at millimeter level in PWV. However, at inland GNSS stations, ocean tide models have less effects on GNSS-estimated ZTD and PWV, e.g., with ±1.0 mm in ZTD and ±0.1 mm in PWV.

Diagnostics of atmospheric water vapor content according to GPS measurements

A continuously operating GPS network, comprising seven permanent observation sites, is created to study the geodynamic processes in the Baikal region. Processing of the initial GPS data provides continuous atmospheric data in the form of total zenith tropospheric delay, which can be used for meteorological and climatological studies. The total delay is the sum of “dry”, or hydrostatic, and “wet” components. The wet component determines the total water vapor amount and amount of precipitable water over the measurement site. Thus, GPS measurements make it possible to obtain initial data for creating new numerical models of zenith tropospheric delay and total precipitable water vapor for meteorological applications.