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

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6440
Author(s):  
Liangke Huang ◽  
Lijie Guo ◽  
Lilong Liu ◽  
Hua Chen ◽  
Jun Chen ◽  
...  
Keyword(s):  
Satellite System ◽  
Reanalysis Data ◽  
Radiosonde Data ◽  
Tropospheric Delay ◽  
International Gnss Service ◽  
Vapor Detection ◽  
Lower Accuracy ◽  
Temporal And Spatial Characteristics ◽  
Global Navigation Satellite ◽  
Better Than

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.

scholarly journals Analysis and Comparison of GPS Precipitable Water Estimates between Two Nearby Stations on Tahiti Island

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5578
Author(s):  
Fangzhao Zhang ◽  
Jean-Pierre Barriot ◽  
Guochang Xu ◽  
Marania Hopuare
Keyword(s):  
Mapping Function ◽  
Precipitable Water ◽  
Satellite System ◽  
Tropospheric Delay ◽  
Horizontal Distance ◽  
International Gnss Service ◽  
Weighted Mean Temperature ◽  
The Difference ◽  
Global Navigation Satellite ◽  
The Impact

Since Bevis first proposed Global Positioning System (GPS) meteorology in 1992, the precipitable water (PW) estimates retrieved from Global Navigation Satellite System (GNSS) networks with high accuracy have been widely used in many meteorological applications. The proper estimation of GNSS PW can be affected by the GNSS processing strategy as well as the local geographical properties of GNSS sites. To better understand the impact of these factors, we compare PW estimates from two nearby permanent GPS stations (THTI and FAA1) in the tropical Tahiti Island, a basalt shield volcano located in the South Pacific, with a mean slope of 8% and a diameter of 30 km. The altitude difference between the two stations is 86.14 m, and their horizontal distance difference is 2.56 km. In this paper, Bernese GNSS Software Version 5.2 with precise point positioning (PPP) and Vienna mapping function 1 (VMF1) was applied to estimate the zenith tropospheric delay (ZTD), which was compared with the International GNSS Service (IGS) Final products. The meteorological parameters sourced from the European Center for Medium-Range Weather Forecasts (ECMWF) and the local weighted mean temperature ( T m ) model were used to estimate the GPS PW for three years (May 2016 to April 2019). The results show that the differences of PW between two nearby GPS stations is nearly a constant with value 1.73 mm. In our case, this difference is mainly driven by insolation differences, the difference in altitude and the wind being only second factors.

First Preliminary Fast Static Ambiguity Resolution Results of Medium-Baseline with Triple-Frequency Beidou Wavebands

2014 ◽  
Vol 67 (6) ◽  
pp. 1109-1119 ◽  
Author(s):  
Shengyue Ji ◽  
Xiaolong Wang ◽  
Ying Xu ◽  
Zhenjie Wang ◽  
Wu Chen ◽  
...  
Keyword(s):  
Frequency Band ◽  
Ambiguity Resolution ◽  
Past Research ◽  
Satellite System ◽  
Tropospheric Delay ◽  
Dual Frequency ◽  
Long Distance ◽  
Triple Frequency ◽  
Global Navigation Satellite ◽  
Better Than

Fast high precision relative Global Navigation Satellite System (GNSS) positioning is very important to various applications and ambiguity resolution is a key requirement. It has been a continuing challenge to determine and fix GNSS carrier-phase ambiguity, especially for medium- and long-distance baselines. In past research, with dual-frequency band Global Positioning System (GPS), it is almost impossible for fast ambiguity resolution of medium- and long-distance baselines mainly due to the ionospheric and tropospheric effects. With the launch of the BeiDou system, triple-frequency band GNSS observations are available for the first time. This research aims to test the ambiguity resolution performance with BeiDou triple-frequency band observations. In this research, two mathematical models are compared: zenith tropospheric delay as an unknown parameter versus corrected tropospheric delay. The ambiguity resolution performance is investigated in detail with BeiDou observations. Different distance baselines are tested: 45 km, 70 km and 100 km and the performances are investigated with different elevation cut-off angles. Also the performance with BeiDou alone and combined BeiDou and GPS are compared. Experimental results clearly show that with practical observations of triple-frequency bands, ambiguity of medium- or long-distance baselines can be fixed. The results also show that: the performance of ambiguity resolution with an elevation cutoff angle of 20° is much better than that of 15°; The performance with tropospheric effect corrected is slightly better than that with tropospheric effect as an estimated parameter; Dual-frequency band GPS observations will benefit ambiguity resolution of integrated BeiDou and GPS.

scholarly journals Validating HY-2A CMR precipitable water vapor using ground-based and shipborne GNSS observations

2020 ◽  
Vol 13 (9) ◽  
pp. 4963-4972
Author(s):  
Zhilu Wu ◽  
Yanxiong Liu ◽  
Yang Liu ◽  
Jungang Wang ◽  
Xiufeng He ◽  
...  
Keyword(s):  
Water Vapor ◽  
Microwave Radiometer ◽  
Precipitable Water ◽  
Satellite System ◽  
Precipitable Water Vapor ◽  
Tropospheric Delay ◽  
High Temporal Resolution ◽  
International Gnss Service ◽  
Global Navigation Satellite ◽  
Gnss Observations

Abstract. The calibration microwave radiometer (CMR) on board the Haiyang-2A (HY-2A) satellite provides wet tropospheric delay correction for altimetry data, which can also contribute to the understanding of climate system and weather processes. The ground-based global navigation satellite system (GNSS) provides precise precipitable water vapor (PWV) with high temporal resolution and could be used for calibration and monitoring of the CMR data, and shipborne GNSS provides accurate PWV over open oceans, which can be directly compared with uncontaminated CMR data. In this study, the HY-2A CMR water vapor product is validated using ground-based GNSS observations of 100 International GNSS Service (IGS) stations along the global coastline and 56 d shipborne GNSS observations over the Indian Ocean. The processing strategy for GNSS data and CMR data is discussed in detail. Special efforts were made in the quality control and reconstruction of contaminated CMR data. The validation result shows that HY-2A CMR PWV agrees well with ground-based GNSS PWV with 2.67 mm as the root mean square (rms) within 100 km. Geographically, the rms is 1.12 mm in the polar region and 2.78 mm elsewhere. The PWV agreement between HY-2A and shipborne GNSS shows a significant correlation with the distance between the ship and the satellite footprint, with an rms of 1.57 mm for the distance threshold of 100 km. Ground-based GNSS and shipborne GNSS agree with HY-2A CMR well.

scholarly journals A Comprehensive Evaluation of Key Tropospheric Parameters from ERA5 and MERRA-2 Reanalysis Products Using Radiosonde Data and GNSS Measurements

2021 ◽  
Vol 13 (15) ◽  
pp. 3008
Author(s):  
Lijie Guo ◽  
Liangke Huang ◽  
Junyu Li ◽  
Lilong Liu ◽  
Ling Huang ◽  
...  
Keyword(s):  
Comprehensive Evaluation ◽  
Spatial Scales ◽  
Precipitable Water ◽  
Satellite System ◽  
Reanalysis Data ◽  
Radiosonde Data ◽  
Tropospheric Delay ◽  
Weighted Mean Temperature ◽  
Temporal And Spatial ◽  
Environmental Prediction

Tropospheric delay is a major error source in the Global Navigation Satellite System (GNSS), and the weighted mean temperature (Tm) is a key parameter in precipitable water vapor (PWV) retrieval. Although reanalysis products like the National Centers for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-Interim (ERA-Interim) data have been used to calculate and model the tropospheric delay, Tm, and PWV, the limitations of the temporal and spatial resolutions of the reanalysis data have affected their performance. The release of the fifth-generation accurate global atmospheric reanalysis (ERA5) and the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) provide the opportunity to overcome these limitations. The performances of the zenith tropospheric delay (ZTD), zenith wet delay (ZWD), Tm, and zenith hydrostatic delay (ZHD) of ERA5 and MERRA-2 data from 2016 to 2017 were evaluated in this work using GNSS ZTD and radiosonde data over the globe. Taking GNSS ZTD as a reference, the ZTD calculated from MERRA-2 and ERA5 pressure-level data were evaluated in temporal and spatial scales, with an annual mean bias and root mean square (RMS) of 2.3 and 10.9 mm for ERA5 and 4.5 and 13.1 mm for MERRA-2, respectively. Compared to radiosonde data, the ZHD, ZWD, and Tm derived from ERA5 and MERRA-2 data were also evaluated on temporal and spatial scales, with annual mean bias values of 1.1, 1.7 mm, and 0.14 K for ERA5 and 0.5, 4.8 mm, and –0.08 K for MERRA-2, respectively. Meanwhile, the annual mean RMS was 4.5, 10.5 mm, and 1.03 K for ERA5 and 4.4, 13.6 mm, and 1.17 K for MERRA-2, respectively. Tropospheric parameters derived from MERRA-2 and ERA5, with improved temporal and spatial resolutions, can provide a reference for GNSS positioning and PWV retrieval.

scholarly journals Assessment of GNSS PPP-Based Zenith Tropospheric Delay

2020 ◽  
Vol 55 (4) ◽  
pp. 171-184
Author(s):  
Mohamed Abdelazeem ◽  
Ahmed El-Rabbany
Keyword(s):  
Precise Point Positioning ◽  
Satellite System ◽  
Tropospheric Delay ◽  
International Gnss Service ◽  
Zenith Tropospheric Delay ◽  
Global Navigation Satellite ◽  
The University ◽  
Globally Distributed ◽  
By Products ◽  
Gnss Observations

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.

scholarly journals Improved Zenith Tropospheric Delay Modeling Using the Piecewise Model of Atmospheric Refractivity

2020 ◽  
Vol 12 (23) ◽  
pp. 3876
Author(s):  
Liu Yang ◽  
Jingxiang Gao ◽  
Dantong Zhu ◽  
Nanshan Zheng ◽  
Zengke Li
Keyword(s):  
Weather Forecasting ◽  
Vertical Direction ◽  
Satellite System ◽  
Exponential Model ◽  
Reanalysis Data ◽  
Radiosonde Data ◽  
Tropospheric Delay ◽  
Zenith Tropospheric Delay ◽  
Piecewise Model ◽  
Surrounding Areas

As one of the atmosphere propagation delays, the tropospheric delay is a significant error source that should be properly handled in high-precision global navigation satellite system (GNSS) applications. We propose an improved zenith tropospheric delay (ZTD) modeling method whereby the piecewise model of the atmospheric refractivity is introduced. Compared with using the exponential model to fit ZTD in vertical direction, the ZTD piecewise model has a better performance. Based on ERA5 2.5° × 2.5° reanalysis data produced by the European Centre for Medium-Range Weather Forecasting (ECMWF) from 2013 to 2017, we establish the regional gridded ZTD model (RGZTD) using a trigonometric function for China and the surrounding areas, which ranges from 70° E to 135° E in longitude and from 15° N to 55° N in latitude. To verify the performance of RGZTD model, the ERA5 ZTD data in 2017–2018, the radiosonde ZTD data from 86 radiosonde stations over China in 2017–2018, and the tropospheric delay products on 251 GNSS stations from Crustal Movement Observation Network of China (CMONOC) in 2016–2017 are used as external compliance check data. The results show that the overall accuracy of RGZTD model is better than that of exponential model, UNB3m model, and GPT3 model. Moreover, the accuracy can be improved by about 13.4%, 7.1%, and 6.2% when ERA5 reanalysis data, radiosonde data, and CMONOC data are used as reference values, respectively. High-accuracy ZTD data can be provided because the RGZTD model takes into account the vertical variation of ZTD through the new piecewise model.

scholarly journals NLOS Multipath Classification of GNSS Signal Correlation Output Using Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2503
Author(s):  
Taro Suzuki ◽  
Yoshiharu Amano
Keyword(s):  
Machine Learning ◽  
Satellite System ◽  
Training Data ◽  
Support Vector ◽  
Positioning Errors ◽  
Automated Method ◽  
Global Navigation Satellite ◽  
Better Than ◽  
Signal Correlation

This paper proposes a method for detecting non-line-of-sight (NLOS) multipath, which causes large positioning errors in a global navigation satellite system (GNSS). We use GNSS signal correlation output, which is the most primitive GNSS signal processing output, to detect NLOS multipath based on machine learning. The shape of the multi-correlator outputs is distorted due to the NLOS multipath. The features of the shape of the multi-correlator are used to discriminate the NLOS multipath. We implement two supervised learning methods, a support vector machine (SVM) and a neural network (NN), and compare their performance. In addition, we also propose an automated method of collecting training data for LOS and NLOS signals of machine learning. The evaluation of the proposed NLOS detection method in an urban environment confirmed that NN was better than SVM, and 97.7% of NLOS signals were correctly discriminated.

Performance Assessment of GNSS-R Polarimetric Observations for Sea Level Monitoring

2021 ◽  
Author(s):  
Mahmoud Rajabi ◽  
Mstafa Hoseini ◽  
Hossein Nahavandchi ◽  
Maximilian Semmling ◽  
Markus Ramatschi ◽  
...  
Keyword(s):  
Time Series ◽  
Circular Polarization ◽  
Sea Level ◽  
Tide Gauge ◽  
Satellite System ◽  
Sea Surface ◽  
Analysis Tool ◽  
Lower Accuracy ◽  
Coastal Sea ◽  
Global Navigation Satellite

<p>Determination and monitoring of the mean sea level especially in the coastal areas are essential, environmentally, and as a vertical datum. Ground-based Global Navigation Satellite System Reflectometry (GNSS-R) is an innovative way which is becoming a reliable alternative for coastal sea-level altimetry. Comparing to traditional tide gauges, GNSS-R can offer different parameters of sea surface, one of which is the sea level. The measurements derived from this technique can cover wider areas of the sea surface in contrast to point-wise observations of a tide gauge.  </p><p>We use long-term ground-based GNSS-R observations to estimate sea level. The dataset includes one-year data from January to December 2016. The data was collected by a coastal GNSS-R experiment at the Onsala space observatory in Sweden. The experiment utilizes three antennas with different polarization designs and orientations. The setup has one up-looking, and two sea-looking antennas at about 3 meters above the sea surface level. The up-looking antenna is Right-Handed Circular Polarization (RHCP). The sea-looking antennas with RHCP and Left-Handed Circular Polarization (LHCP) are used for capturing sea reflected Global Positioning System (GPS) signals. A dedicated reflectometry receiver (GORS type) provides In-phase and Quadrature (I/Q) correlation sums for each antenna based on the captured interferometric signal. The generated time series of I/Q samples from different satellites are analyzed using the Least Squares Harmonic Estimation (LSHE) method. This method is a multivariate analysis tool which can flexibly retrieve the frequencies of a time series regardless of possible gaps or unevenly spaced sampling. The interferometric frequency, which is related to the reflection geometry and sea level, is obtained by LSHE with a temporal resolution of 15 minutes. The sea level is calculated based on this frequency in six modes from the three antennas in GPS L1 and L2 signals.</p><p>Our investigation shows that the sea-looking antennas perform better compared to the up-looking antenna. The highest accuracy is achieved using the sea-looking LHCP antenna and GPS L1 signal. The annual Root Mean Square Error (RMSE) of 15-min GNSS-R water level time series compared to tide gauge observations is 3.7 (L1) and 5.2 (L2) cm for sea-looking LHCP, 5.8 (L1) and 9.1 (L2) cm for sea-looking RHCP, 6.2 (L1) and 8.5 (L2) cm for up-looking RHCP. It is worth noting that the GPS IIR block satellites show lower accuracy due to the lack of L2C code. Therefore, the L2 observations from this block are eliminated.</p>

scholarly journals Centro de Análise Sirgas - IBGE: novas estratégias de processamento e combinação, e a influência da mudança do referencial global nos resultados

2012 ◽  
Vol 18 (1) ◽  
pp. 63-85
Author(s):  
Sonia Maria Alves Costa ◽  
Alberto Luis Da Silva ◽  
Marco Aurélio De Almeida Lima ◽  
Newton José De Moura Júnior
Keyword(s):  
Global Navigation Satellite System ◽  
Satellite System ◽  
Navigation Satellite ◽  
International Gnss Service ◽  
Global Navigation ◽  
Global Navigation Satellite

Atualmente, o SIRGAS (Sistema de Referência Geocêntrico para as Américas) é realizado por uma rede GNSS (Global Navigation Satellite System) permanente denominada SIRGAS-CON, com cerca de 240 estações em funcionamento permanente, distribuídas na América do Sul, Central e Caribe. Os Centros de Análise SIRGAS foram estabelecidos com a finalidade de determinar sistematicamente as coordenadas das estações SIRGAS-CON, seguindo padrões estabelecidos internacionalmente, a fim de apoiar a manutenção do sistema e as atividades do Grupo de Trabalho SIRGAS-GT I (Sistema de Referência). Desde agosto de 2008 a Coordenação de Geodésia do Instituto Brasileiro de Geografia e Estatística-IBGE assumiu oficialmente as atividades de um Centro de Análise. Este é um trabalho cuja dedicação é crescente uma vez que o número de estações no continente Sul Americano vem aumentando rapidamente nos últimos anos. Desta atividade diária são geradas dentre outros resultados, as séries temporais das coordenadas de cada estação, possibilitando assim a determinação dos deslocamentos das estações em função da movimentação da crosta terrestre, os movimentos locais como subsidência e/ou soerguimento crustal, causados por fenômenos naturais, como por exemplo, terremotos, além de efeitos sazonais causados por fatores diversos. Paralelamente a atividade de processamento dos dados GNSS, o IBGE também realiza semanalmente a combinação das soluções semanais dos nove Centros de Processamento SIRGAS. Esta combinação tem por objetivo comparar os resultados com os obtidos pelo DGFI (Deutsches Geodätisches Forschungsinstitut), o qual disponibiliza a solução final semanal da rede SIRGAS-CON. Por se tratar de resultados precisos, a mudança em alguma informação no processamento pode acarretar alterações nas coordenadas determinadas e, conseqüentemente, descontinuidades nas séries temporais de cada estação. Recentemente, em 17 de abril de 2011 (semana GPS 1632), as órbitas (finais e rápidas), as correções dos relógios dos satélites e o modelo de calibração das antenas disponibilizado pelo International GNSS Service - IGS, passaram a estar referidos à nova realização do IGS, denominada IGS08. Conseqüentemente, a partir dessa data, os processamentos GPS que utilizam os produtos IGS terão seus resultados referidos a este novo sistema de referência, o que poderá acarretar descontinuidades nas coordenadas. O objetivo desse trabalho é apresentar a estratégia de processamento atualmente em operação, bem com uma nova estratégia visando à melhoria dos resultados. Outro objetivo é apresentar alguns resultados do processamento e combinação semanal realizados pelo IBGE, bem como esclarecer as alterações ocorridas com a adoção da nova versão da Rede de Referência Global para soluções GNSS, o IGS08 e uma análise preliminar da conseqüência desta mudança.

scholarly journals A comparison between the GNSS tomography technique and the WRF model in retrieving 3D wet refractivity field in Hong Kong

2018 ◽  
Author(s):  
Zhaohui Xiong ◽  
Bao Zhang ◽  
Yibin Yao
Keyword(s):  
Hong Kong ◽  
Water Vapor ◽  
Weather Prediction ◽  
Wrf Model ◽  
Vertical Direction ◽  
Lower Troposphere ◽  
Reanalysis Data ◽  
Radiosonde Data ◽  
Rainy Period ◽  
Lower Accuracy

Abstract. Water vapor plays an important role in various scales of weather processes. However, there are limited means to monitor its 3-dimensional (3D) dynamical changes. The Numerical Weather Prediction (NWP) model and the Global Navigation Satellite System (GNSS) tomography technique are two of the limited means. Here, we conduct an interesting comparison between the GNSS tomography technique and the Weather Research and Forecasting (WRF) model (a representative of the NWP models) in retrieving Wet Refractivity (WR) in Hong Kong area during a rainy period and a rainless period. The GNSS tomography technique is used to retrieve WR from the GNSS slant wet delay. The WRF Data Assimilation (WRFDA) model is used to assimilate GNSS Zenith Tropospheric Delay (ZTD) to improve the background data. The WRF model is used to generate reanalysis data using the WRFDA output as the initial values. The radiosonde data are used to validate the WR derived from the GNSS tomography and the reanalysis data. The Root Mean Square (RMS) of the tomographic WR, the reanalysis WR that assimilate GNSS ZTD, and the reanalysis WR that without assimilating GNSS ZTD are 6.50 mm/km, 4.31 mm/km and 4.15 mm/km in the rainy period. The RMS becomes 7.02 mm/km, 7.26 mm/km and 6.35 mm/km in the rainless period. The lower accuracy in the rainless period is mainy due to the sharp variation of WR in the vertical direction. The results also show that assimilating GNSS ZTD into the WRFDA model only slightly improves the accuracy of the reanalysis WR and that the reanalysis WR is better than the tomographic WR in most cases. However, in a special experimental period when the water vapor is highly concentrated in the lower troposphere, the tomographic WR outperforms the reanalysis WR in the lower troposphere. When we assimilate the tomographic WR in the lower troposphere into the WRFDA model, the reanalysis WR is improved.

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