Zenith Tropospheric Delay Research Articles

Simultaneous Retrieval of PWV and VTEC by Low‐Cost Multi‐GNSS Single‐Frequency Receivers

AbstractPrecipitable water vapor (PWV) and ionospheric vertical total electron content (VTEC) are two essential components of space‐atmosphere parameters. The zenith troposphere delay can be converted into PWV, which plays a crucial role in meteorological studies. In the meantime, the importance of the VTEC lies in providing ionospheric corrections for single‐frequency (SF) positioning, navigation, and timing users. Currently, the global navigation satellite system (GNSS) has become one of the most commonly used tools for retrieving PWV and VTEC and normally relies on dual‐frequency, geodetic‐grade receivers and antennas. However, this reliance also implies high hardware costs. In this paper, we propose a single‐frequency ionosphere and troposphere retrieval approach that enables the simultaneous retrieval of PWV and VTEC from multi‐GNSS data collected by low‐cost SF receivers. The use of SF receivers can greatly reduce the cost of hardware. Furthermore, the simultaneous provision of PWV and VTEC also has a positive effect on studying the coupling mechanisms of the ionosphere and troposphere. The accuracy of the estimated zenith troposphere delay can be better than 10 mm compared with the troposphere products published by the International GNSS Service, and the PWV is no more than 3 mm compared with radiosonde‐derived results. Referring to the final International GNSS Service global ionosphere map products and the Jason altimeter data, the VTEC retrieved from the single‐frequency ionosphere and troposphere retrieval method can perform at roughly equal levels compared to the customary dual‐frequency method.

Interpretation of the Tropospheric Gradients Estimated With GPS During Hurricane Harvey

During the last decade Global Positioning System (GPS) Continuous Operating Reference Stations networks have become a new important data source for meteorology. This has dramatically improved the ability to remotely sense the atmosphere under the influence of severe mesoscale and synoptic systems. The zenith tropospheric delay (ZTD) is one of the atmospheric variables continuously observed, and its horizontal variations, the horizontal tropospheric gradients, are routinely computed nowadays within the dual‐frequency GPS processing, but their interpretation and relationship with the weather is still an open question. The purpose of this paper is to contribute in this direction by studying the effect that Hurricane Harvey had on the spatial and temporal behavior of the ZTDs and gradients, when it reached Texas coast, during 18–31 August 2017. The results show that ZTD time series present a clear and rapid increase larger than 10 cm in a few hours when the hurricane reached the area. Gradients behaviors show that the hurricane also produced significant changes on them, since the magnitude and predominant directions before and after the hurricane arrived are completely different. Noticeably, the gradient vectors before the landing are consistently related to the horizontal winds and pressure fields. In this manuscript we demonstrate that the ZTD gradients can show a consistent signature under severe weather events, strongly suggesting their potential application for short‐term weather forecasting.

Analysis of GNSS sensed precipitable water vapour and tropospheric gradients during the derecho event in Poland of 11th August 2017

Nowadays, one of the techniques that meets the increasing requirements of meteorologist in terms of monitoring of severe weather events is global navigation satellite systems (GNSS), which can provide information about the tropospheric state independently of the weather conditions and even in real time. In this paper we present the usage of GNSS sensed tropospheric data to monitor sudden and intense weather events. Our analyses were performed on the example of a derecho event in Poland of 11th August 2017. We used GPS/GLONASS observations from 278 GNSS reference stations located in Poland and, using Bernese GNSS Software ver. 5.2, we estimated the zenith tropospheric delays (ZTD) and tropospheric gradients with 5 and 15-min intervals respectively. Next, using meteorological data from the synoptic stations, we estimated the precipitable water vapour (PWV) which gives information about the amount of water vapour in the atmosphere. By applying a dense network of GNSS receivers, we were able to create the PWV, rate of the PWV (ROP), and the tropospheric gradients maps, which in turn allowed us to monitor the derecho event. We also conducted case studies for the selected GNSS stations where a comparison between PWV, reflectivity, and microwave radiometer were performed. During the main phase of the event we obtained the maximum value of PWV equal to 52.1 mm at 20:30 UTC. We also acquired high agreement between the PWV/ROP maps and reflectivity derived from meteorological radars. This applies to both the direction and speed of the phenomena as well as the time and place of the occurrence of the main phase of the derecho. This was possible only owing to the use of data derived from the dense network of the GNSS receivers.

Implementation of quasi-real-time estimation of BDS clock

To obtain high reliability and accuracy of the zenith tropospheric delay more quickly, this study describes a parameter estimation method that uses an epoch-differenced and undifferenced function model to estimate the clock of the BeiDou navigation satellite system (BDS)/global positioning system (GPS) satellites using a quasi-real-time process. Forty-five MGEX tracking stations distributed globally were selected for study. The initial orbit information of the clock estimation used the ultra-rapid orbit products released by the German Research Center for Geosciences and post-products as reference values. The experimental results showed that the accuracy of the GPS satellite clock was better than 0.06 ns. The precision of clock for three kinds of BDS satellites was between 0.04 and 0.08 ns, slightly worse than the GPS. The estimated BDS clock appears to meet the demands for computing the quasi-real-time zenith tropospheric delay.

Triple-frequency carrier phase precise time and frequency transfer models for BDS-3

The third-generation BeiDou navigation satellite system (BDS-3) began providing global positioning, navigation and timing service on December 27, 2018. We present three triple-frequency carrier phase (CP) precise time and frequency transfer models using the BDS-3 B1I/B3I/B2a signals, named IF-PPP1, IF-PPP2 and UC-PPP models, respectively. The BDS B1I/B3I dual-frequency ionospheric-free (IF) model is also introduced, known as IF-PPP0 model. The corresponding mathematical and stochastic models are developed. Two stations located at time laboratories and connected to a high-precision atomic clock are utilized to assess the performances of the proposed CP precise time and frequency transfer models. In addition, the number of visible satellites, position dilution of precision, time dilution of precision, estimated positioning errors, zenith tropospheric delay and inter-frequency bias for two stations are also analyzed. The results show that BDS CP precise time and frequency transfer can achieve better performances with increasing number of BDS-3 observations. The proposed models all can be applied for precise time and frequency transfer with the BDS-3 triple-frequency signals, with stability and accuracy identical to the BDS IF-PPP0 solution. The stability of 10,000 s for the proposed BDS CP precise time and frequency models is better than 1.5 × 10−14.

Predicting precipitable water vapor by using ANN from GPS ZTD data at Antarctic Zhongshan Station

Precipitation plays an important role in human activities, and accurate prediction of precipitation is expected to make the arrangements accordingly, especially in Antarctic area with complicated weather conditions. Since directly forecasting precipitation usually requires a lot of meteorological data, which is difficult to be collected in Antarctic area, the precipitation is usually predicted indirectly by using precipitable water vapor (PWV). The PWV can be calculated by Hopfield model using GPS zenith tropospheric delay (ZTD) data if only the temperature and pressure data is available. In this paper, we adopt the artificial neural network (ANN) with genetic algorithm (GA) to predict the PWV of the Zhongshan Station in 6 and 12 h by four different input schemes, including ZTD, ZTD with real-time meteorological data, PWV, and intrinsic mode functions (IMFs) of PWV. The predicted results show that the worst prediction is got by using ZTD sequences with the correlation coefficient of about 0.50. The results of using ZTD with real-time meteorological data and PWV have approximate correlation coefficient of about 0.80. The best prediction is obtained by using IMFs of PWV sequences to predict 6 h PWV with the correlation coefficient of 0.95.

Retrieving geophysical signals from GPS in the La Plata River region

Over the last few years, efforts to model short-term deformations of the Earth’s crust have multiplied. Sudden water level rise can cause sporadic, but significant, motions in the solid Earth’s surface. In this work, we address the problem of retrieving reliable estimates of the vertical displacement of a Global Positioning System (GPS) station located very close to the eastern shore of the La Plata River, during a strong storm surge event. Capturing sub-daily GPS displacements demands an elaborate processing strategy because several highly correlated parameters must be estimated simultaneously. We present a successful strategy that reduces the number of unknowns that have to be estimated simultaneously, by using an empirical model that describes the elastic response of the Earth’s crust to the hydrological load variations. We incorporate this model into the observation equations so that, instead of estimating the station position, we estimate every epoch a single parameter of the empirical model, i.e., the empirical elastic parameter EEP, that is assumed to be a constant of the Earth’s crust in the region of the GPS station. We verify that the estimated parameter agrees well with the value calculated from the CRUST 1.0-A model of the Earth’s crust. The GPS receiver was tied to an external cesium clock, which allowed us to process the data according to two different strategies: (a) estimating the receiver clock error (Δt) as an epoch-wise free parameter, which is equivalent to ignoring the presence of the external clock, and (b) conditioning the variability of that estimate with a small a priori variance compatible with the external clock’s variability. We find that, without having an external atomic clock, the estimation of all the parameters, i.e., the zenith tropospheric delay, Δt, and the EEP, worsens when the GPS station is affected by sub-daily vertical displacements.

Variability and accuracy of Zenith Total Delay over the East African tropical region

The Global Navigation Satellite System (GNSS) can be used to derive accurately the Zenith Tropospheric Delay (ZTD) under all-weather conditions. The derived ZTDs play a vital role in climate studies, weather forecasting and are operationally assimilated into numerical weather prediction models. In this study, variations and statistical analysis of GNSS-derived ZTD over the East African tropical region are analysed. The data is collected from 13 geodetic permanent stations for the period of 4 years from 2013 to 2016. The 13 stations consist of 5 International GNSS Service (IGS) stations plus 8 stations as follows: 4 Africa Array stations and 4 Malawi Rifting stations from Uganda, Kenya, Tanzania and Rwanda. The ZTD time series were processed using goGPS software version 1.0 beta1, a MATLAB based GNSS processing software, originally developed for kinematic applications but recently re-engineered for quasi static applications. The annual variation of the ZTD time series was investigated using Lomb Scargle periodograms. The semi-annual frequency has the dominant power in subregion 1 (latitudes 4 °S and 4 °N) and the annual frequency has the dominant power in subregion 2 (latitudes 12 °S to 4 °S). The highest ZTD estimates occur during the rainy seasons, at all stations, and the lowest estimates occur during the dry seasons. The results also show that the ZTD estimates are largest at stations located at low elevation (regions close to the Indian Ocean). The derived ZTDs are compared to the values derived from the GIPSY-OASIS via Jet Propulsion Laboratory (JPL) online Automatic Precise Positioning Service (APPS) and the Unified Environmental Modelling System (UEMS) numerical weather prediction (NWP) model. The comparison of goGPS and APPS ZTD at the 13 stations shows an overall average bias, Root Mean Square (RMS) and standard deviation (stdev) of −0.9 mm, 3.2 mm and 3.0 mm respectively, with correlation coefficients ranging from 0.974 to 0.999. The comparison of goGPS ZTD against UEMS NWP ZTD at 8 selected stations shows average bias, RMS and stdev of −12.4 mm, 22.0 mm and 17.6 mm respectively, with correlation coefficients ranging from 0.802 to 0.974. The agreement between the GPS ZTD and the NWP ZTD indicates that goGPS ZTD can be assimilated into NWP models in the East African region.

Establishment of a Real-Time Local Tropospheric Fusion Model

The tropospheric delay is one major error source affecting the precise positioning provided by the global navigation satellite system (GNSS). This error occurs because the GNSS signals are refracted while travelling through the troposphere layer. Nowadays, various types of model can produce the tropospheric delay. Among them, the globally distributed GNSS permanent stations can resolve the tropospheric delay with the highest accuracy and the best continuity. Meteorological models, such as the Saastamoinen model, provide formulae to calculate temperature, pressure, water vapor pressure and subsequently the tropospheric delay. Some grid-based empirical tropospheric delay models directly provide tropospheric parameters at a global scale and in real time without any auxiliary information. However, the spatial resolution of the GNSS tropospheric delay is not sufficient, and the accuracy of the meteorological and empirical models is relatively poor. With the rapid development of satellite navigation systems around the globe, the demand for real-time high-precision GNSS positioning services has been growing dramatically, requiring real-time and high-accuracy troposphere models as a critical prerequisite. Therefore, this paper proposes a multi-source real-time local tropospheric delay model that uses polynomial fitting of ground-based GNSS observations, meteorological data, and empirical GPT2w models. The results show that the accuracy in the zenith tropospheric delay (ZTD) of the proposed tropospheric delay model has been verified with a RMS (root mean square) of 1.48 cm in active troposphere conditions, and 1.45 cm in stable troposphere conditions, which is significantly better than the conventional tropospheric GPT2w and Saastamoinen models.

Assessment of BeiDou-3 and Multi-GNSS Precise Point Positioning Performance.

With the launch of BDS-3 and Galileo new satellites, the BeiDou navigation satellite system (BDS) has developed from the regional to global system, and the Galileo constellation will consist of 26 satellites in space. Thus, BDS, GPS, GLONASS, and Galileo all have the capability of global positioning services. It is meaningful to evaluate the ability of global precise point positioning (PPP) of the GPS, BDS, GLONASS, and Galileo. This paper mainly contributes to the assessment of BDS-2, BDS-2/BDS-3, GPS, GLONASS, and Galileo PPP with the observations that were provided by the international Global Navigation Satellite System (GNSS) Monitoring and Assessment System (iGMAS). The Position Dilution of Precision (PDOP) value was utilized to research the global coverage of GPS, BDS-2, BDS-2/BDS-3, GLONASS, and Galileo. In particular, GPS-only, BDS-2-only, BDS-2/BDS-3, GLONASS-only, Galileo-only, and multi-GNSS combined PPP solutions were analyzed to verify the capacity of the PPP performances in terms of positioning accuracy, convergence time, and zenith troposphere delay (ZTD) accuracy. In view of PDOP, the current BDS and Galileo are capable of global coverage. The BDS-2/BDS-3 and Galileo PDOP values are fairly evenly distributed around the world similar to GPS and GLONASS. The root mean square (RMS) of positioning errors for static BDS-2/BDS-3 PPP and Galileo-only PPP are 10.7, 19.5, 20.4 mm, and 6.9, 18.6, 19.6 mm, respectively, in the geographic area of the selected station, which is the same level as GPS and GLONASS. It is worth mentioning that, by adding BDS-3 observations, the positioning accuracy of static BDS PPP is improved by 17.05%, 24.42%, and 35.65%, and the convergence time is reduced by 27.15%, 27.87%, and 35.76% in three coordinate components, respectively. Similar to the static positioning, GPS, BDS-2/BDS-3, GLONASS, and Galileo have the basically same kinematic positioning accuracy. Multi-GNSS PPP significantly improves the positioning performances in both static and kinematic positioning. In terms of ZTD accuracy, the difference between GPS, BDS-2/BDS-3, GLONASS, and Galileo is less than 1 mm, and the BDS-2/BDS-3 improves ZTD accuracy by 20.48% over the BDS-2. The assessment of GPS, BDS-2, BDS-2/BDS-3, GLONASS, Galileo, and multi-GNSS global PPP performance are shown to make comments for the development of multi-GNSS integration, global precise positioning, and the construction of iGMAS.

A Real-Time Precipitable Water Vapor Monitoring System Using the National GNSS Network of China: Method and Preliminary Results

The development of the International Global Navigation Satellite System (GNSS) Service (IGS) Real-Time Pilot Project shows promise for real-time GNSS-based precipitable water vapor (GNSS-PWV) retrieval. For better applications of real-time GNSS meteorology over China, a method is proposed to establish a real-time GNSS-PWV monitoring system using the national GNSS network of China. The prototype system generating the zenith tropospheric delay (ZTD) is based on the real-time precise point positioning technique, in which the real-time data streams and state-space-representative satellite orbit and clock corrections are processed. The parallel computing technology is embedded in the system for decoding and processing the real-time data streams, which enables the multistation processing mode and improves the computing efficiency. At the initial phase, a total of 215 global positioning system (GPS) stations from the crustal movement observation network of China are used to generate the real-time GPS-ZTDs. The pressure data for separating the zenith wet delay (ZWD) from the ZTD are obtained from the collocated meteorological sensors. An advanced weighted mean temperature model, namely, Gridded-Mixed Tm , is adopted in the system to determine the conversion factor “Π” (converting GPS-ZWD to GPS-PWV) in real-time mode with the measured temperatures input. The generated real-time GPS-PWV products have a time resolution of 5 min. To validate the system performance, comparisons between the real-time GPS-PWV and the PWVs derived from nearby radiosonde data (RS-PWV) and reanalysis data from the National Centers for Environmental Prediction (NCEP)-Department of Energy Reanalysis II (NCEP-II-PWV) are conducted over a period of 83 days. The comparisons show a mean bias of −0.1 mm with a root mean square (RMS) of 1.7 mm between the real-time GPS-PWV and RS-PWV. The agreement between the real-time GPS-PWV and NCEP-II-PWV is approximately 2.0 mm in terms of RMS and has a mean bias of −0.8 mm. These results confirm that the established system can be used for real-time PWV monitoring across China.

PENCITRAAN DISTRIBUSI VERTIKAL UAP AIR DI KAWASAN BANDUNG MENGGUNAKAN TEKNIK GPS TOMOGRAFI 1D

Global Positioning System (GPS) tidak hanya berguna untuk keperluan navigasi dan penentuan posisi. GPS juga dapat dimanfaatkan untuk keperluan meteorologi seperti pemantauan kondisi atmosfer Bumi. Sinyal GPS yang ditransmisikan dari satelit ke receiver mengalami perlambatan dan pembelokan akibat adanya partikel-partikel pada lapisan troposfer. Salah satu partikel yang memiliki peranan penting terhadap berlangsungnya siklus hidrologi di Bumi adalah uap air. Uap air tersebut bersifat sangat dinamis baik secara spasial maupun temporal. Perbedaan kandungan uap air pada setiap tempat dan ketinggian menyebabkan besarnya refraktivitas pada lapisan troposfer juga bervariasi. Pemantauan uap air dengan ketelitian tinggi masih menjadi tantangan di Indonesia. Informasi yang akurat mengenai uap air tentunya bermanfaat dalam melakukan prediksi cuaca lokal maupun mempelajari iklim global. Salah satu produk dari pengolahan data GPS adalah informasi mengenai estimasi besarnya bias troposfer pada arah zenith atau disebut sebagai Zenith Tropospheric Delay (ZTD). Besarnya hasil estimasi tersebut kemudian dapat dipisahkan menjadi komponen kering atau Zenith Hydrostatic Delay (ZHD) dan uap air atau Zenith Wet Delay (ZWD). Untuk mengetahui besarnya kandungan uap air pada setiap lintasan sinyal, maka ZWD harus dikonversi menjadi Slant Wet Delay (SWD) dengan mengalikan ZWD dan mapping function. Nilai SWD kemudian digunakan untuk melakukan rekonstruksi distribusi vertikal uap air pada troposfer dengan teknik tomografi. Pada penelitian ini digunakan data pengamatan GPS dari stasiun GPS kontinu (CGPS) ITB selama satu hari. Hasil yang didapatkan menyatakan bahwa Multiplicative Algebraic Reconstruction Technique (MART) berhasil diterapkan untuk menyelesaikan persamaan linear dalam menentukan refraktivitas komponen basah dengan GPS tomografi 1D. Penelitian lebih lanjut dengan memanfaatkan jaringan stasiun CGPS dan pengembangan metode numerik dapat memberikan hasil yang lebih optimal dan akurat.

Independent Assessment of On-Board Microwave Radiometer Measurements in Coastal Zones Using Tropospheric Delays From GNSS

Zenith tropospheric delays (ZTDs) computed at a network of 60 global navigation satellite system (GNSS) stations have been used to assess microwave radiometer (MWR) measurements from eight altimeter missions in coastal zones, where some of these observations become invalid. Results show that ZTDs are determined with an accuracy of a few millimeters; however, jumps are detected in some stations in standard products. The comparison between the MWR-derived wet tropospheric correction (WTC) and the GNSS-derived WTC at the nearby coastal stations illustrates the effect of land contamination in the MWR measurements and yields the distance from coast at which this contamination appears. This distance is different for the analyzed altimetric missions, due to their different footprint sizes and different MWR retrieval algorithms, varying from 10 to 30 km. The root mean square of the differences between GNSS and MWR-derived WTC, at the closest distance at which no land contamination occurs, is in the range of 1.6–1.9 cm for all missions. This coastal assessment also shows the ability of the GNSS-derived path delay plus algorithm to remove this land contamination and to improve the WTC retrieval. Aiming at inspecting the long-term stability of the MWR measurements, the comparisons with GNSS show nonsignificant differences and drifts less than 0.3 mm/year. Therefore, the GNSS-derived WTC is a useful independent source to inspect the land effects on MWR observations and to monitor the stability of these instruments, thus contributing to the retrieval of precise water surface heights from satellite altimetry.

An adaptive Kalman filter based on variance component estimation for a real-time ZTD solution

The Global Navigation Satellite System (GNSS) precise point positioning (PPP) technology is currently used to process GNSS water vapor observations in real time or near real time. Further developments are required to improve the accuracy and real-time performance of processing tropospheric delays from which the water vapor observations are extracted. In real-time BDS/GPS precise clock correction estimation with square-root information filtering and PPP solution with Kalman filtering, a fixed variance is often assigned for the process noise of the troposphere dynamics model. However, this fixed value may deviate from reality as the weather conditions change, especially for extreme weather. In this paper, a new adaptive Kalman filter is proposed for tropospheric delay processing, in which the variance of the process noise for the zenith tropospheric delay (ZTD) dynamics model is tuned in real time using the least-squares variance component estimation technique. MGEX/IGS data of 15 consecutive days were processed in a stepwise manner. Namely: Real-time BDS/GPS precise clock corrections were estimated firstly, followed by comparison among ZTD solutions of four schemes based on these real-time clocks of first step and GFZ multi-GNSS precise clock (GBM) final clocks: (1) real-time solution of ZTD (G(GPS), GC(GPS and BDS)) without VCE; (2) real-time solution of ZTD (G, GC) with VCE; (3) final solution of ZTD (G, GC, GR (GPS and GLONASS), GE (GPS and GALILEO), GRC (GPS, GLONASS and BDS), GREC (GPS, GLONASS, GALILEO and BDS) without VCE; and (4) final solution of ZTD (G, GC, GR, GE, GRC, GREC) with VCE. The performance of the ZTD and positioning solution was analyzed. Results showed that the accuracy of estimated real-time satellite clock correction was 0.27, 1.31, 0.29, and 0.21 ns for GPS, BDS/GEO, BDS/IGSO, and BDS/MEO, respectively. For the ZTD solutions, the results of schemes 1 and 2 were 12.8 mm (GC) and 10.1 mm (GC) in terms of mean root-mean-square (RMS) values and 2.1 mm (GC) and 1.6 mm (GC) in terms of minimum RMS values, respectively, thereby showing an improvement for scheme 2 of 1.8–81.4% over scheme 1 with average increasing rates of 20.7% (GC) and 20.2% (G). The results for schemes 3 and 4 were 7.6 mm (G) and 6.3 mm (GRC) in terms of mean RMS values and 2.1 mm (G) and 1.9 mm (GRCE) in terms of minimum RMS values, respectively, thereby showing an improvement in scheme 4 over scheme 3 by 1.3–85.6% with average increasing rates of 22.1% (GRCE), 21.9% (GRC), 18.4% (GR), 15.9% (GC), 15.2% (GE), and 12.1% (G). Similar results can be observed for the positioning solution, especially in the height component. These findings clearly show the advantage of the proposed method, which is consistent with the theoretical analysis. Notably, the advantage of the adaptive VCE becomes significant with the inclusion of additional satellite systems.

Comparisons between the WRF data assimilation and the GNSS tomography technique in retrieving 3-D wet refractivity fields in Hong Kong

Abstract. Water vapor plays an important role in various scales of weather processes. However, there are limited means to accurately describe its three-dimensional (3-D) dynamical changes. The data assimilation technique 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 Data Assimilation (WRFDA) model (a representative of the data assimilation models) in retrieving wet refractivity (WR) in the Hong Kong area during a wet period and a dry period. The GNSS tomography technique is used to retrieve WR from the GNSS slant wet delays. The WRFDA is used to assimilate the zenith tropospheric delay to improve the background data. The radiosonde data are used to validate the WR derived from the GNSS tomography, the WRFDA output, and the background data. The root mean square (rms) of the WR derived from the tomography results, the WRFDA output, and the background data are 6.50, 4.31, and 4.15 mm km−1 in the wet period. The rms becomes 7.02, 7.26, and 6.35 mm km−1 in the dry period. The lower accuracy in the dry period is mainly due to the sharp variation of WR in the vertical direction. The results also show that assimilating GNSS ZTD into the WRFDA only slightly improves the accuracy of the WR and that the WRFDA 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 WRFDA WR in the lower troposphere. When we assimilate the tomographic WR in the lower troposphere into the WRFDA, the retrieved WR is improved.

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).

Application of GNSS derived precipitable water vapour prediction in West Africa

Abstract Atmospheric water vapour, a major component in weather systems serves as the main source for precipitation, provides latent heat which helps maintain the earth’s energy balance and a major parameter in Numerical Weather Prediction (NWP) models. An observational technique based on the Global Navigation Satellite System (GNSS) has made it possible to easily retrieve Precipitable Water (PW) at station’s antenna position with very high spatial and temporal variabilities. GNSS techniques are superior to ground-based and balloons sensors in terms of accuracy, ease of use, wider coverage and easier assimilation into NWP models. This study sought to use prediction models using daily observational data from Four (4) International GNSS Service stations in West Africa. The best prediction model can be used in cases of station outages and to predict PW over data poor regions using computed Zenith Tropospheric Delays (ZTD). gLAB software was used to process the stations’ data in Precise Point Positioning mode and PW were retrieved using station’s temperature and pressure values. Computed PW were compared against Total Column Water Vapour from ERA-Interim Reanalysis data in 2016. Correlation coefficient (R2) values ranging from 0.947 — 0.995 were obtained for the four stations. With computed PW’s, three regression models were tested to find the best-fit with PW as the dependent variable and ZTD being the independent variable. The quadratic model gave the highest R2 and lowest RMSE values as against the linear and exponential models. Time series forecasts models such as moving average, autoregressive, exponential smoothing and autoregressive integrated moving average were also employed. The forecasts results were compared against ZTD with autoregressive model reporting the highest R2 and lowest RMSE amongst the forecast models developed.

Estimating Zenith Tropospheric Delay Based on GPT2w Model

To precisely and conveniently estimate zenith tropospheric delay (ZTD), troposphere refractivity is deduced through global pressure and temperature 2w (GPT2w) model and surface meteorology devices, ZTD is estimated based on integration of refractivity in the zenith direction. When surface meteorological measurements are absent, all parameters including surface meteorology and lapse rate are estimated by GPT2w. Validation is carried out using observed data in the year 2012 at 8 international GNSS service (IGS) stations. Results indicate that when surface meteorological parameters are available, the annual accuracy is improved by 27% than Saastamoinen model. Meanwhile, annual bias of the other scheme is decreased by 21% than the GPT2w+Saastamoinen model. For most stations, the bias shows seasonal characteristics, high elevation, high longitude and low latitude can bring less bias.

A Simulation Study on Triple Frequency Ambiguity Resolution for Reference Stations Using Different Strategy Regarding Elevation angles

This paper proposes an ambiguity resolution method using triple frequency for reference stations. Using the reference coordinate information, geometry based ambiguity resolution performance is analysed. Although orbit errors and tropospheric model errors still remain, wide lane ambiguity could be fixed in several epochs. However, the narrow lane wave length of about 10cm is too short to overcome error sources by simply combining the measurement. Therefore, we have divided the elevation angle into 5 degree intervals and investigated the measurement errors and the time to fix of each section. For high elevation satellites, it is possible to determine in several epochs by integer rounding. On the other hand, if the elevation is lower than 30 degrees, the tropospheric zenith delay must be estimated with ambiguities. The proposed algorithm estimates ambiguities and tropospheric zenith delay simultaneously utilizing ambiguity free observations of high elevation satellites. Ambiguities for high elevation satellites are resolved by integer rounding in several epochs. The algorithm has been verified by generating the simulated observation data for the ‘Cheon-an’ and ‘Boen’ reference stations in the Korea.

Estimation of Coordinates of the Eastern European Permanent GNSS Stations in the IGb08 Reference Frame for GPS Weeks 1709–1933

From October 7, 2012, to January 28, 2017 (GPS weeks 1709–1933) all products of the International GNSS Service (IGS)—precise ephemerides of GPS and GLONASS satellites, coordinates and velocities of permanent GNSS stations, etc.—were based on the IGb08 reference frame, the updated IGS realization of the release of the International Terrestrial Reference Frame (ITRF2008). Observations of GNSS satellites at permanent stations located in Ukraine and in Eastern Europe for this period were processed in the GNSS Data Analysis Centre of the Main Astronomical Observatory of the National Academy of Sciences of Ukraine. The processing was carried out with Bernese GNSS Software ver. 5.2 according to the requirements of the European Permanent GNSS Network (EPN) that were valid at that time. In total, observations on 232 GNSS stations, including 201 Ukrainian stations belonging to the following operators of GNSS networks were processed: MAO NAS of Ukraine, Research Institute of Geodesy and Cartography, NU Lviv Polytechnic (GeoTerrace), PJSC System Solutions (System.NET), TNT TPI company (TNT TPI GNSS Network), Navigation Geodetic Center Ltd. (NGC.net), UA-EUPOS/ZAKPOS, Europromservice Ltd. (EPS), Coordinate Navigation Maintenance System of Ukraine (CNMSU), and Kharkiv National University of Radio Electronics. The IGb08 reference frame was set by No-Net-Translation conditions on the coordinates of the IGS Reference Frame stations. As result, the stations’ coordinates in the IGb08 reference frame and the zenith tropospheric delays for all stations were estimated. The mean repeatabilities for components of stations’ coordinates for all weeks (the characteristics of the precision of the received daily and weekly solutions) are in the following ranges: for north and east components—from 0.5 mm to 1.6 mm (average values are 0.99 mm and 1.01 mm respectively), for hight component—from 2.2 mm to 5.4 mm (average value is 3.75 mm) with an outlier of 6.91 mm for GPS week 1759.