scholarly journals A Regional Zenith Tropospheric Delay (ZTD) Model Based on GPT3 and ANN

2021 ◽  
Vol 13 (5) ◽  
pp. 838
Author(s):  
Fei Yang ◽  
Jiming Guo ◽  
Chaoyang Zhang ◽  
Yitao Li ◽  
Jun Li

The delays of radio signals transmitted by global navigation satellite system (GNSS) satellites and induced by neutral atmosphere, which are usually represented by zenith tropospheric delay (ZTD), are required as critical information both for GNSS positioning and navigation and GNSS meteorology. Establishing a stable and reliable ZTD model is one of the interests in GNSS research. In this study, we proposed a regional ZTD model that makes full use of the ZTD calculated from regional GNSS data and the corresponding ZTD estimated by global pressure and temperature 3 (GPT3) model, adopting the artificial neutral network (ANN) to construct the correlation between ZTD derived from GPT3 and GNSS observations. The experiments in Hong Kong using Satellite Positioning Reference Station Network (SatRet) were conducted and three statistical values, i.e., bias, root mean square error (RMSE), and compound relative error (CRE) were adopted for our comparisons. Numerical results showed that the proposed model outperformed the parameter ZTD model (Saastamoinen model) and the empirical ZTD model (GPT3 model), with an approximately 56%/52% and 52%/37% RMSE improvement in the internal and external accuracy verification, respectively. Moreover, the proposed method effectively improved the systematic deviation of GPT3 model and achieved better ZTD estimation in both rainy and rainless conditions.

2019 ◽  
Vol 37 (1) ◽  
pp. 89-100
Author(s):  
Yibin Yao ◽  
Linyang Xin ◽  
Qingzhi Zhao

Abstract. As an innovative use of Global Navigation Satellite System (GNSS), the GNSS water vapor tomography technique shows great potential in monitoring three-dimensional water vapor variation. Most of the previous studies employ the pixel-based method, i.e., dividing the troposphere space into finite voxels and considering water vapor in each voxel as constant. However, this method cannot reflect the variations in voxels and breaks the continuity of the troposphere. Moreover, in the pixel-based method, each voxel needs a parameter to represent the water vapor density, which means that huge numbers of parameters are needed to represent the water vapor field when the interested area is large and/or the expected resolution is high. In order to overcome the abovementioned problems, in this study, we propose an improved pixel-based water vapor tomography model, which uses layered optimal polynomial functions obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF) by adaptive training for water vapor retrieval. Tomography experiments were carried out using the GNSS data collected from the Hong Kong Satellite Positioning Reference Station Network (SatRef) from 25 March to 25 April 2014 under different scenarios. The tomographic results are compared to the ECMWF data and validated by the radiosonde. Results show that the new model outperforms the traditional one by reducing the root-mean-square error (RMSE), and this improvement is more pronounced, at 5.88 % in voxels without the penetration of GNSS rays. The improved model also has advantages in more convenient expression.


2018 ◽  
Vol 106 (1) ◽  
pp. 35-42 ◽  
Author(s):  
Marcelo Romero ◽  
Mike Mustafa Berber

Abstract Twenty four hour GNSS (Global Navigation Satellite System) data acquired monthly for 5 years from 8 CORS (Continuously Operating Reference Station) stations in Central Valley, California are processed and vertical velocities of the points are determined. To process GNSS data, online GNSS data processing service APPS (Automatic Precise Positioning Service) is used. GNSS data downloaded from NGS (National Geodetic Survey) CORS are analyzed and subsidence at these points is portrayed with graphics. It is revealed that elevation changes range from 5 mm uplift in the north to 163 mm subsidence in the southern part of the valley.


2020 ◽  
Author(s):  
◽  
Juan Manuel Aragón Paz

En el presente trabajo de tesis se desarrolla el diseño e implementación de un sistema de cálculo, en tiempo casi real, de parámetros troposféricos mediante técnicas de navegación global por satélite (GNSS, del inglés Global Navigation Satellite System) para Sudamérica. El desarrollo de la llamada Meteorología GNSS se remonta a principios de la década del 90 donde se encuentran los trabajos fundacionales de esta disciplina. Con el correr de los años, nuevas contribuciones han ido definiendo los reales alcances de esta técnica, poniendo en práctica metodologías cada vez más contrastadas con los métodos de medición tradicionales. En los últimos años los esfuerzos se han enfocado en el desarrollo de procedimientos de cálculo que permitan la utilización de los datos GNSS, cada vez más numerosos, en la asimilación para modelos meteorológicos (en especial los de corto plazo), permitiendo así anticipar eventos con alto impacto a la sociedad civil (tormentas con granizo, inundaciones repentinas, eventos convectivos de mesoescala, etc). Numerosos trabajos se han centrado en la implementación de la meteorología GNSS en Europa, Estados Unidos y Japón. Para la región Sudamericana existen pocos y recientes antecedentes de la aplicación de estas metodologías. Se desarrolló un sistema de cálculo, que permite hacer uso de infraestructura existente en la región, tanto meteorológica como geodésica, enfocado en la obtención de las variables de interés meteorológico como son el retardo troposférico cenital (ZTD, del inglés Zenith Total Delay) y el vapor de agua integrado (IWV, del inglés Integrated Water Vapor). Por otra parte, se han realizado estudios en la aplicación del ZTD y el IWV a índices que permitan dar información rápida acerca de posibles eventos meteorológicos severos. En este trabajo se desarrollan las estrategias diseñadas para la adquisición de los datos, su disponibilidad y alcance. Las problemáticas en la disponibilidad de los mismos, de acuerdo a su procedencia, son descriptas y sorteadas. Seguidamente se brinda una detallada descripción de la metodología de estimación de las observaciones, haciendo especial foco en los parámetros de retardo troposférico cenital (ZTD, del ingles Zenith Tropospheric Delay) y vapor de agua integrado (IWV, del inglés Integrated Water Vapor) mediante el procesamiento de las observaciones GNSS y meteorológicas. Una vez que se tienen los resultados, la presentación de los mismos y los posibles formato de intercambio con las instituciones potenciales usuarias del dato son discutidos. Finalizando esta sección se hace un análisis de la performance del sistema de procesamiento contra las técnicas de radio sondeo (convencionales) y alguno de los modelos de reanálisis mas utilizados. En una segunda etapa se explora las distintas capacidades del IWV GNSS para representar las variaciones temporales y espaciales de la distribución del vapor de agua atmosférico frente a distintas situaciones meteorológicas. También, se describe el desarrollo de posibles índices de alerta que hagan utilización de la información disponible a partir del IWV GNSS. Basándose en bibliografía actualizada se comparan las distintas posibilidades de aplicación a la región de estudio en función de la frecuencia temporal y espacial de las observaciones. Los resultados son presentados analizando un evento de interés meteorológico para la región central de Argentina. Finalmente, los puntos mas salientes del presente trabajo son presentados en las conclusiones. Las mismas abarcan desde el sistema de descarga de datos hasta la implementación de los índices de alerta. Se formulan las posibles derivaciones del trabajo y sus implicancias en la mejora continua de este sistema, que en tiempo casi real, provee información sobre los parámetros de ZTD e IWV. Una sección final describe cuáles son las recomendaciones que permitirían mejoras en la utilización de los datos provistos para conseguir un máximo aprovechamiento de los mismos.


2018 ◽  
Vol 11 (3) ◽  
pp. 1347-1361 ◽  
Author(s):  
Katarzyna Stepniak ◽  
Olivier Bock ◽  
Pawel Wielgosz

Abstract. Though Global Navigation Satellite System (GNSS) data processing has been significantly improved over the years, it is still commonly observed that zenith tropospheric delay (ZTD) estimates contain many outliers which are detrimental to meteorological and climatological applications. In this paper, we show that ZTD outliers in double-difference processing are mostly caused by sub-daily data gaps at reference stations, which cause disconnections of clusters of stations from the reference network and common mode biases due to the strong correlation between stations in short baselines. They can reach a few centimetres in ZTD and usually coincide with a jump in formal errors. The magnitude and sign of these biases are impossible to predict because they depend on different errors in the observations and on the geometry of the baselines. We elaborate and test a new baseline strategy which solves this problem and significantly reduces the number of outliers compared to the standard strategy commonly used for positioning (e.g. determination of national reference frame) in which the pre-defined network is composed of a skeleton of reference stations to which secondary stations are connected in a star-like structure. The new strategy is also shown to perform better than the widely used strategy maximizing the number of observations available in many GNSS programs. The reason is that observations are maximized before processing, whereas the final number of used observations can be dramatically lower because of data rejection (screening) during the processing. The study relies on the analysis of 1 year of GPS (Global Positioning System) data from a regional network of 136 GNSS stations processed using Bernese GNSS Software v.5.2. A post-processing screening procedure is also proposed to detect and remove a few outliers which may still remain due to short data gaps. It is based on a combination of range checks and outlier checks of ZTD and formal errors. The accuracy of the final screened GPS ZTD estimates is assessed by comparison to ERA-Interim reanalysis.


2017 ◽  
Author(s):  
Katarzyna Stepniak ◽  
Olivier Bock ◽  
Pawel Wielgosz

Abstract. Though Global Navigation Satellite System (GNSS) data processing has been significantly improved over years it is still commonly observed that Zenith Tropospheric Delay (ZTD) estimates contain many outliers which are detrimental to meteorological and climatological applications. In this paper, we show that ZTD outliers in double difference processing are most of the time caused by sub-daily data gaps at reference stations which cause disconnections of clusters of stations from the reference network and common–mode biases due to the strong correlation between stations in short baselines. They can reach a few centimetres in ZTD and coincide usually with a jump in formal errors. The magnitude and sign of these biases are impossible to predict because they depend on different errors in the observations and on the geometry of the baselines. We elaborate and test a new baseline strategy which solves this problem and significantly reduces the number of outliers compared to the standard strategy commonly used for positioning (e.g. determination of national reference frame) in which the pre-defined network is composed of a skeleton of reference stations to which secondary stations are connected in a star-like structure. The new strategy is also shown to perform better than the widely-used strategy maximising the number of observations which available in many GNSS software. The reason is that observations are maximised before processing whereas the final number of used observations can be dramatically lower because of data rejection (screening) during the processing. The study relies on the analysis of one year of GPS (Global Positioning System) data from a regional network of 136 GNSS stations processed using Bernese GNSS Software v.5.2. A post-processing screening procedure is also proposed to detect and remove a few outliers which may still remain due to short data gaps. It is based on a combination of range checks and outlier checks of ZTD and formal errors. The accuracy of the final screened GPS ZTD estimates is assessed by comparison to ERA-Interim reanalysis.


2020 ◽  
Vol 55 (4) ◽  
pp. 171-184
Author(s):  
Mohamed Abdelazeem ◽  
Ahmed El-Rabbany

AbstractThis study assesses the precision of zenith tropospheric delay (ZTD) obtained through triple-constellation global navigation satellite system (GNSS) precise point positioning (PPP). Various ZTD estimates are obtained as by-products from GPS-only, GPS/Galileo, GPS/BeiDou, and triple-constellation GPS/Galileo/BeiDou PPP solutions. Triple-constellation GNSS observations from a number of globally distributed reference stations are processed over a period of seven days in order to investigate the daily performance of the ZTD estimates. The estimated ZTDs are then validated by comparing them with the International GNSS Service (IGS) tropospheric products and the University of New Brunswick (UNB3m) model counterparts. It is shown that the ZTD estimates agree with the IGS counterparts with a maximum standard deviation (STD) of 2.4 cm. It is also shown that the precision of estimated ZTD from the GPS/Galileo and GPS/Galileo/BeiDou PPP solutions is improved by about 4.5 and 14%, respectively, with respect to the GPS-only PPP solution. Moreover, it is found that the estimated ZTD agrees with the UNB3m model with a maximum STD of 3.1 cm. Furthermore, the GPS/Galileo and GPS/Galileo/BeiDou PPP enhance the precision of the ZTD estimates by about 6.5 and 10%, respectively, in comparison with the GPS-only PPP solution.


2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Fei Yang ◽  
Xiaolin Meng ◽  
Jiming Guo ◽  
Debao Yuan ◽  
Ming Chen

AbstractThe tropospheric delay is a significant error source in Global Navigation Satellite System (GNSS) positioning and navigation. It is usually projected into zenith direction by using a mapping function. It is particularly important to establish a model that can provide stable and accurate Zenith Tropospheric Delay (ZTD). Because of the regional accuracy difference and poor stability of the traditional ZTD models, this paper proposed two methods to refine the Hopfield and Saastamoinen ZTD models. One is by adding annual and semi-annual periodic terms and the other is based on Back-Propagation Artificial Neutral Network (BP-ANN). Using 5-year data from 2011 to 2015 collected at 67 GNSS reference stations in China and its surrounding regions, the four refined models were constructed. The tropospheric products at these GNSS stations were derived from the site-wise Vienna Mapping Function 1 (VMP1). The spatial analysis, temporal analysis, and residual distribution analysis for all the six models were conducted using the data from 2016 to 2017. The results show that the refined models can effectively improve the accuracy compared with the traditional models. For the Hopfield model, the improvement for the Root Mean Square Error (RMSE) and bias reached 24.5/49.7 and 34.0/52.8 mm, respectively. These values became 8.8/26.7 and 14.7/28.8 mm when the Saastamoinen model was refined using the two methods. This exploration is conducive to GNSS navigation and positioning and GNSS meteorology by providing more accurate tropospheric prior information.


2017 ◽  
Vol 71 (1) ◽  
pp. 117-133
Author(s):  
Su-Kyung Kim ◽  
Tae-Suk Bae

The current Korean national geodetic reference frame, KGD2002, refers to the fixed epoch at 2002·0 under the assumption that there is no crustal movement of the Korean peninsula. A discontinuity in the coordinates of the reference stations may occur due to the relocation of the stations, antenna replacement, or earthquakes. The static reference frame has difficulty in covering continuous and/or discontinuous crustal movements at the same time. A new dynamic local geodetic reference frame has been calculated based on eight years (2007–2014) of Global Navigation Satellite System (GNSS) data. The final geodetic coordinates and velocities were calculated on the basis of the IGb08 reference frame. The discontinuity caused by the 2011 Tohoku earthquake can be addressed using the newly proposed model in this study, which ensures the consistency and continuity of the local geodetic datum.


2021 ◽  
Vol 13 (19) ◽  
pp. 3818
Author(s):  
Hao Wang ◽  
Nan Ding ◽  
Wenyuan Zhang

Global Navigation Satellite System (GNSS) water vapor tomography provides a four-dimensional (4-D) distribution of water vapor in the atmosphere for weather monitoring. It has developed into a widely used technique in numerical weather prediction (NWP). Vertical stratification is essential in discretizing the tomographic region. Traditional discretization methods divide the tomographic area into regular voxels with an equal height interval, which ignores the dynamic exponential distribution of water vapor. In recent years, non-uniform stratification methods have been widely validated by tomographic experiments. However, such experiments have not proposed a specific calculation method for stratification thickness. Therefore, in this paper, we introduced an adaptive non-uniform stratification method that follows the exponential distribution of water vapor in the tomographic region and presented the process of iterative calculation to acquire the optimal stratification interval. The proposed approach was applied based on the exponential decreasing trend in water vapor with increasing altitude. Moreover, it could adaptively calculate the interval of stratification height according to water vapor content. The tomographic experiments were performed using Global Positioning System (GPS) data from 19 ground-based stations in the Hong Kong Satellite Positioning Reference Station Network (SatRef) from 1 to 31 August 2019. The results indicated that, compared to the traditional stratification method, the root mean square error derived from the proposed approach was reduced by 0.26 g/m3. Additionally, severe weather can negatively affect the accuracy of the tomographic results. The results also showed that the accuracy of the tomographic results was reduced with increasing altitude. Moreover, the performance of the tomographic water vapor fields below 3000 m was improved by the proposed approach.


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