Zenith Tropospheric Delay Values Research Articles

Analysis of the effect of the 2021 Semeru eruption on water vapor content and atmospheric particles using GNSS and remote sensing

Mount Semeru, an active volcano in East Java, Indonesia, erupted on December 4, 2021, following extreme rainfall that caused an avalanche of hot pyroclastic flows and lava. The tropospheric conditions and dominant particle components in the atmosphere can be monitored using Global Navigation Satellite System (GNSS) technology and remote sensing satellites. GNSS signal propagation delay in Precise Point Positioning (PPP) processing can be used to determine Zenith Tropospheric Delay (ZTD) and Precipitable Water Vapor (PWV) variables so that atmospheric conditions can be generated. In addition, by using remote sensing satellite data, it is possible to obtain rainfall data with high temporal resolution as well as the dominant particle and gas content values during eruptions. During the eruption period, the high value of PWV was dominated by the high intensity of precipitation during the rainy season. High rainfall before the eruption caused activity inside the mountain to increase, which occurred in avalanche type eruption. Apart from that, the atmosphere around Semeru was also dominated by SO2 content, which spreaded for tens of kilometers. SO2 content began to be detected significantly by remote sensing sensors on December 7, 2021. In this study, deformation and atmospheric monitoring were also carried out using low-cost GNSS at the Semeru Monitoring Station on September 9–15, 2022. The results of the ZTD and ZWD values show the dominance of the wet component, which is directly proportional to rainfall activity in this period.

An ERA5 tropospheric parameters-augmented approach for improving GNSS precise point positioning

Precise Point Positioning (PPP) technology has developed into a potent instrument for geodetic positioning, ionospheric modeling, tropospheric atmospheric parameter detection, and seismic monitoring. As atmospheric reanalysis data products' accuracy and spatiotemporal resolution have improved recently, it has become important to apply these products to obtain high-accuracy tropospheric delay parameters, like zenith tropospheric delay (ZTD) and tropospheric horizontal gradient. These tropospheric delay parameters can be applied to PPP to reduce the convergence time and to increase the accuracy in the vertical direction of the position. The European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) atmospheric reanalysis data is the latest product with a high spatiotemporal resolution released by the European Center for Medium-Range Weather Forecasts (ECMWF). Only a few researches have evaluated the application of ERA5 data to Global Navigation Satellite System (GNSS) PPP. Therefore, this study compared and validated the ZTD products derived from ERA5 data using ZTD values provided by 290 global International GNSS Service (IGS) stations for 2016–2017. The results indicated a stable performance for ZTD, with annual average bias and RMS values of 0.23 cm and 1.09 cm, respectively. Further, GNSS observations for one week in each of the four seasons (spring: DOY 92–98; summer: DOY 199–205; autumn: DOY 275–281; and winter: DOY 22–28) from 34 multi-GNSS experiments (MGEX) stations distributed globally in 2016 were considered to evaluate the performance of ERA5-derived tropospheric delay products in GNSS PPP. The performance of ERA5-enhanced PPP was compared with that of the two standard GNSS PPP schemes (without estimated tropospheric horizontal gradient and with estimated tropospheric horizontal gradient). The results demonstrated that ERA5-enhanced GNSS PPP showed no significant improvement in the convergence times in both the Eastern (E) and Northern (N) directions, while the average convergence time over four weeks in the vertical (U) direction improved by 53.3% and 52.7%, respectively (in the case of pngm station). The average convergence times for each week in the U direction of the northern and southern hemisphere stations indicated a decrease of 16.3%, 12.6%, 9.6%, and 9.1%, and 16.9%, 9.6%, 8.9%, and 14.5%, respectively. Regarding positioning accuracy, ERA5-enhanced PPP showed an improvement of 13.3% and 16.2% over the two standard PPP schemes in the U direction, respectively. No significant improvement in the positioning performance was observed in both the E and N directions. Thus, this study demonstrated the potential application of the ERA5 tropospheric parameters-augmented approach to Beidou navigation and positioning.

High-Precision ZTD Model of Altitude-Related Correction

Zenith tropospheric delay (ZTD) is one of the main error sources in space geodesy. The existing regional or global models, such as Global Pressure and Temperature 3 (GPT3), Global Tropospheric model, Global Hopfield, and Shanghai Astronomical observatory tropospheric delay model models, have good performance. However, the precision of these models is relatively low in regions with a large height difference, which becomes the focus of this article. A high-precision ZTD model considering the height effect on tropospheric delay is proposed, and China is selected as study area due to its large height difference, which is called the high-precision ZTD model for China (CHZ). The initial ZTD value is calculated on the basis of the GPT3 model, and the periodic terms of ZTD residual between the global navigation satellite system (GNSS) and GPT3 model, such as annual, semiannual, and seasonal periods, are determined by the Lomb–Scargle periodogram method in different subareas of China. The relationship between the ZTD periodic residual term and the height of the GNSS station is further analyzed at different seasons, and linear ZTD periodic residual models are obtained. A total of 164 GNSS stations derived from the Crustal Movement Observation Network of China and 87 radiosonde stations are selected to validate the proposed CHZ model, and hourly ZTD data derived from GNSS are used to establish the CHZ model. Statistical result shows that the averaged root mean square and Bias of the CHZ model are 21.12 and −2.51 mm, respectively, in the whole of China. In addition, the application of CHZ model in precision point positioning (PPP) show that the convergence time is improved by 34%, 15%, and 35%, respectively, in N, E, and U components when compared to GPT3-based PPP.

A new empirical troposphere model using ERA5's monthly averaged hourly dataset

Due to contents of the dry air and water vapor, troposphere affects radio signals of the space geodetic techniques (e.g., GNSS and VLBI) as range delays. These tropospheric delays should be eliminated to achieve precise point positioning. Over the years, researchers have been developed many of troposphere model. However, the existing models differ from each other in their resolution, data source used and especially in their accuracy. In this paper, a new troposphere model has been presented. The new model considers annual, semi annual and diurnal effects in both sine and cosine form unlike its ancestors. ERA5's monthly averaged hourly dataset has been used to produce the new model. In order to validate new model, the data of ERA5 and terrestrial meteorological stations have been used. Moreover, zenith tropospheric delay (ZTD) values obtained by the new model have been validated by IGS products. Accuracy of the ZTD values has been obtained 3.15 cm. According to the results, it can be concluded that including diurnal effects in both sine and cosine forms improves the accuracies of determined parameters.

ГЕОДЕЗІЯ, КАРТОГРАФІЯ І АЕРОФОТОЗНІМАННЯ

The aim of this work is to evaluate the accuracy of determining the wet component of zenith tropospheric delay (ZTD) from GNSS-measurements and the accuracy of determining the hydrostatic component according to the Saastamoinen model in comparison with the radio sounding data as well. Zenith tropospheric delay is determined mainly by two methods - traditional, using radio sounding or using atmospheric models, such as the Saastamoinen model, and the method of GNSS measurements. Determination of the hydrostatic component of the zenith tropospheric delay was performed by radio sounding data obtained at the aerological station Praha-Libus in 2011-2013 and in 2018. Data were processed for the middle decades of January and July of each year at 0h o’clock of the Universal Time. The wet component was calculated from GNSS observations. By a significant number of radio soundings at the Praha-Libus aerological station, hydrostatic and wet components of zenith tropospheric delay (ZTD) and the same number of ZTD values derived for the corresponding time intervals from GNSS measurements at the GOPE reference station were determined. The values of the wet component of ZTD were determined and compared with the corresponding data obtained from radio soundings. We found that the error of the hydrostatic component in winter does not exceed 10 mm in absolute value, and in summer it is approximately 1.5 times smaller. This is due to differences in the stratification of the troposphere and lower stratosphere in winter and summer. As for the wet component of ZTD, its errors do not exceed: in winter 15 mm, in summer – 35 mm. The resulting differences in summer have a negative sign, indicating a systematic shift, and in winter – both negative and positive. Today, there are many studies aimed at improving the accuracy of determining zenith tropospheric delay by both Ukrainian and foreign authors, but the problem of the accuracy of the hydrostatic component remains open. The study provides recommendations for further research to improve the accuracy of zenith tropospheric delay.

Regional Zenith Tropospheric Delay Modeling Based on Least Squares Support Vector Machine Using GNSS and ERA5 Data

The meteorological reanalysis data has been widely applied to derive zenith tropospheric delay (ZTD) with a high spatial and temporal resolution. With the rapid development of artificial intelligence, machine learning also begins as a high-efficiency tool to be employed in modeling and predicting ZTD. In this paper, we develop three new regional ZTD models based on the least squares support vector machine (LSSVM), using both the International GNSS Service (IGS)-ZTD products and European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) data over Europe throughout 2018. Among them, the ERA5 data is extended to ERA5S-ZTD and ERA5P-ZTD as the background data by the model method and integral method, respectively. Depending on different background data, three schemes are designed to construct ZTD models based on the LSSVM algorithm, including the without background data, with the ERA5S-ZTD, and with the ERA5P-ZTD. To investigate the advantage and feasibility of the proposed ZTD models, we evaluate the accuracy of two background data and three schemes by segmental comparison with the IGS-ZTD of 85 IGS stations in Europe. The results show that the overall average Root Mean Square Errors (RMSE) value of all sites is 30.1 mm for the ERA5S-ZTD, and 10.7 mm for the ERA5P-ZTD. The overall average RMSE is 25.8 mm, 22.9 mm, and 9 mm for the three schemes, respectively. Moreover, the overall improvement rate is 19.1% and 1.6% for the ZTD model with ERA5S-ZTD and ERA5P-ZTD, respectively. In order to explore the reason of the lower improvement for the ZTD model with ERA5P-ZTD, the loop verification is performed by estimating the ZTD values of each available IGS station. In actuality, the monthly improvement rate of estimated ZTD is positive for most stations, and the biggest improvement rate can even reach about 40%. The negative rate mainly comes from specific stations, these stations are located on the edge of the region, near the coast, as well as the lower similarity between the individual verified station and training stations.

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.

Evaluation of the ZWD/ZTD Values Derived from MERRA-2 Global Reanalysis Products Using GNSS Observations and Radiosonde Data.

Tropospheric delay is one of the main errors affecting high-precision positioning and navigation and is a key parameter of water vapor detection in the Global Navigation Satellite System (GNSS). The second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) is the latest generation of reanalysis data collected by the National Aeronautics and Space Administration (NASA), which can be used to calculate tropospheric delay products with high spatial and temporal resolution. However, there is no report analyzing the accuracy of the zenith tropospheric delay (ZTD) and zenith wet delay (ZWD) calculated from MERRA-2 data. This paper evaluates the performance of the ZTD and ZWD values derived from global MERRA-2 data using global radiosonde data and International GNSS Service (IGS) precise ZTD products. The results are as follows: (1) Taking the precision ZTD products of 316 IGS stations from around the world from 2015 to 2017 as the reference, the average root mean square (RMS) of the ZTD values calculated from the MERRA-2 data is better than 1.35 cm, and the accuracy difference between different years is small. The bias and RMS of the ZTD values show certain seasonal variations, with a higher accuracy in winter and a lower accuracy in summer, and the RMS decreases from the equator to the poles. However, those of the ZTD values do not show obvious variations according to elevation. (2) Relative to the radiosonde data, the RMS of the ZWD and ZTD values calculated from the MERRA-2 data are better than 1.37 cm and 1.45 cm, respectively. Furthermore, the bias and RMS of the ZWD and ZTD values also show some temporal and spatial characteristics, which are similar to the test results of the IGS stations. It is suggested that MERRA-2 data can be used for global tropospheric vertical profile model construction because of their high accuracy and good stability in the global calculation of the ZWD and ZTD.

Improved GPT2w (IGPT2w) model for site specific zenith tropospheric delay estimation in China

Despite being a systematic error source in global navigation satellite system (GNSS) positioning and navigation, tropospheric delay is a key parameter in GNSS meteorology. Therefore, deriving a zenith tropospheric delay (ZTD) value as accurately as possible from an empirical model without using auxiliary data is a prerequisite for the high-precision application of GNSS positioning and navigation. To reach the goal above, this paper proposes an improved model to estimate the ZTD based on the Global Pressure and Temperature 2 wet (GPT2w) model, which is called the improved GPT2w (IGPT2w) model. The GPT2w-derived ZTD is first calculated as the initial value of the IGPT2w model, and the time series of ZTD residual can thus be obtained between the GNSS- and GPT2w-derived ZTDs over GNSS stations. Analysis of the long time series variation of ZTD residuals using the multichannel singular spectrum analysis method reveals evident periodic signals. The Lomb–Scargle method is then used to determine the specific values of these periodic signals, and different periods are identified at various GNSS stations. Therefore, a ZTD residual model that considers annual, semi-annual, and seasonal periods is established. The IGPT2w model, in which the ZTD value is obtained by combining the estimated ZTD residual and the GPT2w-derived ZTD, can be acquired. A total of 188 GNSS stations in China throughout 2015 to 2017 are selected to validate the IGPT2w model. In the model, the GNSS-derived ZTD is obtained using the GAMIT/GLOBK software, and the accuracy is validated using radiosonde data with root mean square and bias of 1.9 and 0.1 cm, respectively, at 33 collocated stations in China. Statistical results reveal that the accuracy of the IGPT2w-derived ZTD is improved by 13.7% compared with that of the GPT2w-derived ZTD when the GNSS-derived ZTD is regarded as the reference. Such result indicates that the proposed IGPT2w model outperforms the GPT2w model in China.

Zenith Wet Delay (ZWD) Seasonal Correlation with Rainfall in Cikapundung River Discharge, North Bandung Region, Indonesia

In a GPS survey study, the biases produced by the ionosphere and troposphere layers are known as ionospheric biases and troposphere bias. The distance deviation due to the slowing travel time of GPS signals in troposphere is commonly referred to as Zenith Tropospheric Delay (ZTD). The magnitude of this ZTD can also be used to characterize and analyze the troposphere conditions around the GPS observation area. This can be done by separating the wet delay component from ZTD, so as to obtain Zenith Wet Delay (ZWD) and dry component so as to obtain Zenith Hydrostatic Delay (ZHD). The total moisture content in the troposphere (precipitable water vapor, PWV) of an area can be estimated based on the bias characteristics of zenith wet delay (ZWD). The ZWD pattern is very important in the study of atmospheric water cycles which are associated with rainfall patterns and flood events. The methods used in the research include preliminary data processing and estimation of ZTD value using RTKLIB 2.4.2. This article analyzes the correlation between ZWD, rainfall and Cikapundung river discharge in the North Bandung Region (KBU), based on the daily average data in the 2011-2015 observation period. Based on the reconstruction of harmonic components, it was found that the seasonal pattern of river discharge is correlating with the seasonal pattern of rainfall and moisture content in the troposphere. The pattern of the three variables is strongly influenced by the Asian and Australian Monsoon exchanges phenomena. Linear correlation between ZWD and river discharge exhibits clear results, which is based on the Pearson correlation value is 88.84% with a 95% confidence level using t-student statistic. Based on cross-spectrum analysis, the three variables are dominated by the seasonal cycle of one-year monsoon (annual) and the six-month cycle phenomenon (semi-annual).

Regional spatio-temporal zenith tropospheric delay modelling using independent component analysis

Accurate modelling of the zenith tropospheric delay (ZTD) is of significant value in many applications such as Global Navigation Satellite System (GNSS) positioning. Most ZTD models require meteorological parameters, which are difficult to obtain in many practical applications. Though some empirical models can predict the ZTD values without meteorological parameters, their performances are usually unsatisfactory. To overcome these issues, a spatio-temporal ZTD modelling method based on independent component analysis (ICA) without using meteorological parameters is proposed in this study. In this method, multi-dimensional ZTD data can be reconstructed by several temporal independent components and corresponding spatial response values. Regional ICA ZTD models for Hong Kong, UK and China mainland were established using the daily GNSS ZTD data. Results show that ICA regional ZTD models perform better than Saastamoinen, UNB3m and GPT2w models in general. The proposed ICA ZTD modelling method is proven to have advantages of simpler modelling process, fewer model parameters and higher applicability. This study suggests that ICA is very promising in modelling spatio-temporal variation of ZTD, especially for a region with dense GNSS network.

Analysing the Zenith Tropospheric Delay Estimates in On-line Precise Point Positioning (PPP) Services and PPP Software Packages.

As Global Navigation Satellite System (GNSS) signals travel through the troposphere, a tropospheric delay occurs due to a change in the refractive index of the medium. The Precise Point Positioning (PPP) technique can achieve centimeter/millimeter positioning accuracy with only one GNSS receiver. The Zenith Tropospheric Delay (ZTD) is estimated alongside with the position unknowns in PPP. Estimated ZTD can be very useful for meteorological applications, an example is the estimation of water vapor content in the atmosphere from the estimated ZTD. PPP is implemented with different algorithms and models in online services and software packages. In this study, a performance assessment with analysis of ZTD estimates from three PPP online services and three software packages is presented. The main contribution of this paper is to show the accuracy of ZTD estimation achievable in PPP. The analysis also provides the GNSS users and researchers the insight of the processing algorithm dependence and impact on PPP ZTD estimation. Observation data of eight whole days from a total of nine International GNSS Service (IGS) tracking stations spread in the northern hemisphere, the equatorial region and the southern hemisphere is used in this analysis. The PPP ZTD estimates are compared with the ZTD obtained from the IGS tropospheric product of the same days. The estimates of two of the three online PPP services show good agreement (<1 cm) with the IGS ZTD values at the northern and southern hemisphere stations. The results also show that the online PPP services perform better than the selected PPP software packages at all stations.

Erratum and addendum to the paper ‘A new ZTD model based on permanent ground-based GNSS-ZTD data’, Survey Review, 2016, 48(351), 385–391

We correct some errors and give some more research for our paper published in Survey Review, 2016, 48(351), 385–391. This note is a correction owing to the use of the questionable surface meteorological measurements of the International GNSS Service (IGS) and also gives more sufficient studies to validate our method due to our inadequate study. Numerical weather model values of surface meteorological data were used to check the IGS surface meteorological measurements and long-time zenith tropospheric delay values at 76 radiosonde stations in Russia and near Russia were added as test data. Revised, updated and additional results were shown and analysed, which provide more evidence to show that the new proposed ISAAS model has a better accuracy than the Saastamoinen in Russia.

An analysis of GPT2/GPT2w+Saastamoinen models for estimating zenith tropospheric delay over Asian area

The tropospheric delay is a systematic error source in the Global Navigation Satellite System (GNSS) positioning. However, without accuracy meteorological information, the quality of the Zenith Tropospheric Delay (ZTD) derived from empirical tropospheric models like Saastamoinen model will degrade, leading to inaccurate estimates of positions. To solve the above problem, on the basis of Global Pressure and Temperature 2/2w (GPT2/GPT2w) model, this paper conducted GPT2/GPT2w+Saastamoinen models for estimating ZTD over Asian area. As GPT2w model has two resolutions of 1 and 5 degrees, the effects of two models (GPT2_5w+S refers to GPT2w+Saastamoinen model with the resolution of 5 degree; GPT2_1w+S refers to GPT2w+Saastamoinen model with the resolution of 1 degree) were analyzed respectively. The model’s validation was carried out using the International GNSS Service (IGS) ZTD values derived from the observed data in the year 2012 at 27 IGS stations. The results show that the GPT2_1w+S model can provide tropospheric delay corrections with bias of 0.66cm and Root Mean Square (RMS) of 4.93cm, which is superior to GPT2+S model. The annual bias and RMS for the GPT2_5w+S model are slightly worse than that for the GPT2_1w+S model. For most stations, the bias and RMS show seasonal characteristics. The relation between the annual bias and RMS with latitude for the models is not obvious, and a latitude dependency between the models could not be detected.

Establishment of a global zenith troposphericdelay model using multi-source data

Radio space-based geodesy techniques suffer from atmosphere propagation delays, of which the ionospheric delay can be largely eliminated by iono-free carrier phase combination techniques, and then the tropospheric delay becomes the main error source. In general, we project the slant delay to zenith direction with mapping function in GNSS navigation and positioning, so modeling the zenith tropospheric delay (ZTD) is a common method to reduce the tropospheric influence on signal travelling. Currently, the commonly used tropospheric delay models are all based on single data source. In this paper we initially used multi-source ZTD data to construct a tropospheric delay model. The ZTD data used for modeling are gridded data from GGOS Atmosphere and IGS troposphere products respectively. The Global Geodetic Observing System (GGOS) Atmosphere is a project that aims to establish atmospheric models. It provides gridded data of global zenith delays with temporal resolution of 6 h (0:00, 6:00, 12:00, 18:00UTC) and spatial resolution of 2.5°×2° (Lon× Lat), which are derived from the reanalysis data provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). IGS troposphere products are derived from position solutions of IGS stations with a high temporal resolution of 5 min and a high accuracy. Firstly, we used IGS ZTD data to analyze the characteristics of short periodic variations (diurnal cycle and semidiurnal cycle). Then, on basis of this analysis and previous researches on ZTD periodic variations conducted by other researchers, we combined GGOS ZTD data and IGS ZTD data to establish ZTD model in accordance with the idea of direct ZTD modeling. We obtained the temporal parameters via cycle fitting for ZTD data and saved the parameters in the form of global Delaunay triangles. For the proposed ZTD model, the ZTD values can be estimated by the methods of height reduction and linear triangle interpolation. The cycle fitting residuals of GGOS ZTD data and IGS ZTD data show that the internal accuracy are 3.62 and 3.60 cm respectively, indicating that our function model with diurnal cycle and semidiurnal cycle can well describe the temporal variations of ZTD. We validated the multi-source data model with respect to ZTD grid data from 94 globally distributed IGS stations during 2013, which were not involved in modeling. The obtained results show that the global average bias and RMS are - 0.31 cm and 4.16 cm respectively. Compared to other tropospheric delay models, multi-source data model is significantly superior to GZTD model (bias: - 0.48 cm; RMS: 4.46 cm) which ignores the short cycles of ZTD and is better than the GGrid model without IGS ZTD involved in modeling. With an accuracy reduce of only 0.2 mm, the multi-source data model is comparable to the most accurate and complicated GPT2w model (bias: - 0.04 cm; RMS: 4.14 cm). At the same time, we validated the stability of multi-source model in space and time, the testing results show the good correction performance and reliability. In addition to the globally applicable convenience, the multi-source model also show a characteristic of regional augmentation, which can greatly improve the tropospheric correction performances in areas around IGS sites. With the gradual increase of regional Continuously Operating Reference Stations (CORS) and global IGS stations and the development of meteorological data sources, how to assimilate diverse ZTD data sources to establish a more comprehensive global multi-source tropospheric delay needs more detailed and further study.

A comparative study of zenith tropospheric delay and precipitable water vapor estimates using scientific GPS processing software and web based automated PPP service

The zenith tropospheric delay (ZTD) is a significant error source which affects the GPS signal propagation time. ZTD time series can directly or indirectly reflect the weather variations. In geodetic studies their computation is important since it improves position accuracy. Sophisticated software packages using network data of ground-based GPS receivers are used for this purpose. During the last years, various web based precise point positioning (PPP) services can provide position solutions. Additional products, such as ZTD estimates, can be derived both from PPP as well as from network solutions. Research institutes and laboratories like JPL provide similar services. This study’s objective is twofold. In a first instance we used the Bernese and GAMIT software packages and the PPP service via the JPL webpage to estimate ZTD values every hour for a period of one month. We selected a geographical area in Greece, where seasonal weather variations are frequent and GPS permanent station infrastructure is available. The estimated ZTD values derived from GPS processing for a single station were compared with the ZTD estimates derived directly from the Saastamoinen model using meteorological data from a co-located meteorological sensor as input to this model. The results show an rms agreement of about 45 mm. The second scope of this study is to compare precipitable water (PW) values between different processing schemes. For this purpose, we used the derived zenith wet delay estimates of each processing scheme and a global formula for the computation of the weighted mean temperature of the atmosphere for our area of study. The rms differences between the web PPP solution and the Bernese derived estimates were 0.35 mm. The rms of the differences between and the web PPP solution and the GAMIT derived estimates of PW were 1.67 mm. We conclude that this difference follows from the zenith hydrostatic delay component that needs to be properly modeled when high accuracy results are required.

Tropospheric delay correction with dense GPS network in L1-SAIF augmentation

The L1-SAIF (L1 Submeter-class Augmentation with Integrity Function) signal is one of the Quasi-Zenith Satellite System (QZSS) navigation signals, which provides an augmentation function for mobile users in Japan. The tropospheric delay correction in the L1-SAIF augmentation is discussed in detail. Because the topographical features in Japan are complicated, the correction information is generated from GPS observation data collected at 200 GPS stations which are densely distributed over Japan. A total of 210 Tropospheric Grid Points (TGPs) are arranged to fully cover Japan. The TGPs that provide the correction information are selected adaptively to achieve the expected correction accuracy. This selection of TGPs is provided by the TGP mask message. Mobile users acquire the zenith tropospheric delay (ZTD) value at neighboring TGPs from the correction messages, and can estimate the local ZTD value accurately by using a suitable ZTD model. Only up to seven L1-SAIF messages are sufficient to provide the full correction information. Accuracy evaluations have proven that it is possible to achieve a correction accuracy of 13.4 mm RMS. The strategy presented here has been implemented into the augmentation system using the L1-SAIF signal, and its application guidance is presented in the QZSS interface specification.

Study of Alternative GPS Network Meteorological Sensors in Taiwan: Case Studies of the Plum Rains and Typhoon Sinlaku

Plum rains and typhoons are important weather systems in the Taiwan region. They can cause huge economic losses, but they are also considered as important water resources as they strike Taiwan annually and fill the reservoirs around the island. There are many meteorological sensors available for investigating the characteristics of weather and climate systems. Recently, the use of GPS as an alternative meteorological sensor has become popular due to the catastrophic impact of global climate change. GPS provides meteorological parameters mainly from the atmosphere. Precise Point Positioning (PPP) is a proven algorithm that has attracted attention in GPS related studies. This study uses GPS measurements collected at more than fifty reference stations of the e-GPS network in Taiwan. The first data set was collected from June 1st 2008 to June 7th 2008, which corresponds to the middle of the plum rain season in Taiwan. The second data set was collected from September 11th to September 17th 2008 during the landfall of typhoon Sinlaku. The data processing strategy is to process the measurements collected at the reference stations of the e-GPS network using the PPP technique to estimate the zenith tropospheric delay (ZTD) values of the sites; thus, the correlations between the ZTD values and the variation of rainfall during the plum rains and typhoon are analyzed. In addition, several characteristics of the meteorological events are identified using spatial and temporal analyses of the ZTD values estimated with the GPS network PPP technique.

Prediction of zenith tropospheric delay by multi-layer perceptron

The aim of the present study was to use the artificial neural network approach and specifically the multi-layer perceptron algorithm in order to predict total zenith tropospheric delay (ZTD) for various time spans of 1, 3 and 6 hours. The test data was ZTD values derived from the analysis centers of the EUREF Permanent tracking Network. The prediction process was applied to six EUREF permanent GPS stations for using period data of 2006 and 2007. The results obtained show an agreement at the order of few centimetres (2–3 cm) with those derived from EPN. Comparisons were also made with ZTD values calculated by other methods like the radiosonde observations and Saastamoinen model using ground measurements in order to confirm the final results and the feasibility of the neural network methodology.

L1-SAIFメッセージによる対流圏遅延補正の試み

L1-SAIF signal is one of the navigation signals of Quasi-Zenith Satellite System, which provides an augmentation function for mobile users in Japan. This paper presents the detail of the tropospheric delay correction in L1-SAIF augmentation. The tropospheric delay correction information is generated at the ground station using the data collected at GEONET (GPS Earth Observation NETwork) stations. The correction message contains the information of the zenith tropospheric delay (ZTD) values at 105 Tropospheric Grid Points (TGP) in the experiment area. From this message a mobile user can acquire the ZTD value at some neighboring TGPs, and estimate the local ZTD value accurately by using a suitable ZTD model function. Only 3 L1-SAIF messages are necessary to provide all of the tropospheric correction information. Several investigations using the actual data observed at many GEONET stations overall Japan have proved that it is possible to achieve the correction accuracy of 13.2mm (rms).