Global Navigation Satellite System Processing Research Articles

An efficient parallel approach for quad-constellation GNSS real-time precise orbit determination enabling 5-second intervals updating

Real-time Global Navigation Satellite System (GNSS) precise orbits are essential prerequisites for real-time GNSS-based applications. However, the high computational demands of filter-based real-time multi-GNSS POD methods present a significant challenge for practical utilization. This study introduces an efficient parallel approach for quad-constellation GNSS real-time POD using the square root information filter (SRIF). In the proposed approach, parallel QR factorization algorithms are implemented to expedite parameter estimation based on SRIF, while parallel processing model is designed for real-time POD to enhance its computational efficiency. Validation experiments show that the computation time for measurement and time update in SRIF can be reduced by 78.5% and 80.5%, respectively, compared to the traditional serial approach. Additionally, parallel computing improves the computational efficiency of GNSS processing algorithms in real-time POD by approximately 70%. The proposed approach enables the completion of quad-system real-time POD solutions with 90 stations within 5 s, representing an impressive 73.0% reduction.

Hard SyDR: A Benchmarking Environment for Global Navigation Satellite System Algorithms.

A Global Navigation Satellite System (GNSS) is widely used today for both positioning and timing purposes. Many distinct receiver chips are available as Application-Specific Integrated Circuit (ASIC)s off-the-shelf, each tailored to the requirements of various applications. These chips deliver good performance and low energy consumption but offer customers little-to-no transparency about their internal features. This prevents modification, research in GNSS processing chain enhancement (e.g., application of Approximate Computing (AxC) techniques), and design space exploration to find the optimal receiver for a use case. In this paper, we review the GNSS processing chain using SyDR, our open-source GNSS Software-Defined Radio (SDR) designed for algorithm benchmarking, and highlight the limitations of a software-only environment. In return, we propose an evolution to our system, called Hard SyDR to become closer to the hardware layer and access new Key Performance Indicator (KPI)s, such as power/energy consumption and resource utilization. We use High-Level Synthesis (HLS) and the PYNQ platform to ease our development process and provide an overview of their advantages/limitations in our project. Finally, we evaluate the foreseen developments, including how this work can serve as the foundation for an exploration of AxC techniques in future low-power GNSS receivers.

Multi-GNSS ultra-rapid orbit determination through epoch-parallel processing

High-precision Global Navigation Satellite Systems (GNSS) orbits are critical for real-time clock estimation and precise positioning service; however, the prediction error grows gradually with the increasing prediction session. In this study, we present a new efficient precise orbit determination (POD) strategy referred to as the epoch-parallel processing to reduce the orbit update latency, in which a 24-h processing job is split into several sub-sessions that are processed in parallel and then stacked to solve and recover parameters subsequently. With a delicate handling of parameters crossing different sub-sessions, such as ambiguities, the method is rigorously equivalent to the one-session batch solution, but is much more efficient, halving the time-consuming roughly. Together with paralleling other procedures such as orbit integration and using open multi-processing (openMP), the multi-GNSS POD of 120 satellites using 90 stations can be fulfilled within 30 min. The lower update latency enables users to access orbits closer to the estimation part, that is, 30–60-min prediction with a 30-min update latency, which significantly improves the orbit quality. Compared to the hourly updated orbit, the averaged 1D RMS values of predicted orbit in terms of overlap for GPS, GLONASS, Galileo, and BDS MEO are improved by 39%, 35%, 41%, and 37%, respectively, and that of BDS GEO and IGSO satellites is improved by 47%. We also demonstrate that the boundary discontinuities of half-hourly orbit are within 2 cm for the GPS, GLONASS, and Galileo satellites, and for BDS the values are 2.6, 15.5, and 9.8 cm for MEO, GEO, and IGSO satellites, respectively. This method can also be implemented for any batch-based GNSS processing to improve the efficiency.

EVALUATION OF A GNSS/IMU/LIDAR-INTEGRATION FOR AIRBORNE LASER SCANNING USING RTKLIB PPK AND PPP GNSS SOLUTIONS

Abstract. Airborne laser scanning allows for efficient acquisition of accurate 3D data for large areas. Because georeferencing of the LiDAR data requires knowledge of the platform trajectory, the laser scanner system commonly comprises a global navigation satellite system (GNSS) receiver/antenna and an inertial measurement unit (IMU). The standard processing pipeline consists of GNSS/IMU integration, georeferencing, and subsequent adjustment of the laser data. Here, we consider a holistic GNSS/IMU/LiDAR-integration approach based on least-squares adjustment. The GNSS is loosely coupled, and the GNSS positions are obtained using either postprocessing kinematic or precise point positioning GNSS processing strategies using the open-source software RTKLib. In this contribution, we compare the resulting point clouds to those of a standard processing workflow and evaluate the impact of the different processing strategies on point cloud quality in terms of internal consistency and absolute accuracy for a airborne laser bathymetry (ALB) dataset. Although the GNSS solutions themselves differ strongly, both the PPK- and the PPP-derived point clouds show better strip differences (below 2.5 cm) and similar absolute accuracy (<4 cm RMSE w.r.t. reference targets after correction of constant datum shift) compared to the reference solution.

Estimation of tropospheric parameters with GNSS smartphones in a differential approach

With the introduction of the operating system Android 7 Nougat in the year 2016, it became possible to access Global Navigation Satellite System (GNSS) code and carrier phase observations. These observations can be processed with the state-of-the-art GNSS processing software packages, which allows an in-depth evaluation of the smartphone’s GNSS performance. The availability of carrier phase observations enables sub-decimeter-level positioning. A few years ago, smartphones wearing dual-frequency GNSS chipsets hit the mass market. In this study, we investigate the capability of such a device for the estimation of tropospheric delays. Static measurements carried out over the period of two weeks are performed using a Google Pixel 4 XL smartphone. The measurements are processed using relative positioning methods with a baseline length of about 33 kilometers, where a continuously operating reference station (CORS) acts as a base. The estimated differential zenith tropospheric wet delay (dZWD), obtained for the smartphone are then combined with absolute values computed at the reference station, in order to obtain time series of Zenith Total Delay (ZTD). Using this method, we demonstrate that high-precision ZTDs can be successfully determined from smartphone GNSS observations. When comparing the estimated tropospheric delays with those determined at a nearby geodetic receiver to assess the accuracy of the acquired time series of ZTD, differences in the range of few millimeters to a centimeter are visible. We examine the impact of various error sources, such as antenna phase center variations and residual effects of the ionosphere. Given that the obtained accuracies are at the level of a centimeter and below, the suggested method shows the potential to resolve small-scale tropospheric structures in near real-time, and thus, could be an interesting data source for numerical weather prediction models or related GNSS crowdsourcing projects.

Incorporation of Real-Time Earthquake Magnitudes Estimated via Peak Ground Displacement Scaling in the ShakeAlert Earthquake Early Warning System

ABSTRACTThe United States earthquake early warning (EEW) system, ShakeAlert®, currently employs two algorithms based on seismic data alone to characterize the earthquake source, reporting the weighted average of their magnitude estimates. Nonsaturating magnitude estimates derived in real time from Global Navigation Satellite System (GNSS) data using peak ground displacement (PGD) scaling relationships offer complementary information with the potential to improve EEW reliability for large earthquakes. We have adapted a method that estimates magnitude from PGD (Crowell et al., 2016) for possible production use by ShakeAlert. To evaluate the potential contribution of the modified algorithm, we installed it on the ShakeAlert development system for real-time operation and for retrospective analyses using a suite of GNSS data that we compiled. Because of the colored noise structure of typical real-time GNSS positions, observed PGD values drift over time periods relevant to EEW. To mitigate this effect, we implemented logic within the modified algorithm to control when it issues initial and updated PGD-derived magnitude estimates (MPGD), and to quantify MPGD uncertainty for use in combining it with estimates from other ShakeAlert algorithms running in parallel. Our analysis suggests that, with these strategies, spuriously large MPGD will seldom be incorporated in ShakeAlert’s magnitude estimate. Retrospective analysis of data from moderate-to-great earthquakes demonstrates that the modified algorithm can contribute to better magnitude estimates for Mw>7.0 events. GNSS station distribution throughout the ShakeAlert region limits how soon the modified algorithm can begin estimating magnitude in some locations. Furthermore, both the station density and the GNSS noise levels limit the minimum magnitude for which the modified algorithm is likely to contribute to the weighted average. This might be addressed by alternative GNSS processing strategies that reduce noise.

Geodetic evidence of land subsidence in Cirebon, Indonesia

The subsidence phenomena occur in numerous cities in Indonesia (Jakarta, Bandung, and Semarang) and have been observed over the last few decades using geodetic techniques such as interferometric synthetic aperture radar (InSAR) and the Global Navigation Satellite System (GNSS). Three variables are considered the leading causes of substantial subsidence in those cities: urban development, excessive groundwater removal, and geological context. Considering these considerations, we assess surface displacement in the surrounding area of Cirebon, Indonesia, which has similar background circumstances. We used 43 Sentinel-1A images covering from 2014 to 2021 and processed them using the small baseline subset (SBAS) method obtaining 78 interferograms for time series analysis. A weighted correction from two weather models was used to correct tropospheric errors. The results from the InSAR time series were compared with the continuous GNSS time series (2010–2021) processed using GAMIT/GLOBK GNSS processing softwares. Cirebon experienced a slow land subsidence rate with an average magnitude of -2.6 mm/yr. Furthermore, we underline that more significant subsidence rates were found in several locations. Conic-shaped subsidence with a diameter of around 1 km was observed in a highly inhabited area, with a maximum rate of up to -17 mm/yr near the cone’s center. We also found more prominent land subsidence along the coastline with magnitudes up to -25 mm/yr. Surface lowering with a magnitude of up to -32 mm/yr also affects power plant regions close to Cirebon city. Meanwhile, the fastest subsidence rate was observed over the salt evaporation field area of about -50 mm/yr. We attribute the natural and anthropogenic factors to causing the subsidence in this area.

Assessment of SIRGAS-CON tropospheric products using ERA5 and IGS

Abstract Zenith Tropospheric Delays (ZTDs) are used to correct tropospheric effects that cause a delay in the signal measured by Global Navigation Satellite Systems (GNSS) receivers and obtain accurate measurements. ZTD can be estimated from GNSS processing, which means they may suffer from occasional or systematic errors. Therefore, it is necessary to assess the quality and stability of these data over time, since ZTDs are used in several applications that require centimeter precision. Within this context, this work aims to assess the available ZTD of the whole Geodetic Reference System for the Americas Continuously Operating Network (SIRGAS-CON), consisting of 467 stations, spanning the period from January 2014 to December 2020 using the most recent Numerical Weather Model ERA5 from the European Centre for Medium-Range Weather Forecasts and common stations to the International GNSS Service (IGS) for an intercomparison. Results show that 10% of the stations present some instability, such as periods of highly dispersed data or discontinuities, with more occurrence in stations located in Argentina, Uruguay and Colombia. The remaining 90% proved to have stable and reliable ZTD, both in comparison with ERA5 and IGS.

Accuracy Assessment for GNSS Precise Point Position Using Online Service and Offline Software

There are many applications of Global Navigation Satellite System (GNSS) (GPS, GLONASS, Galileo, and BeiDou) such as civilian (agriculture, mapping, road and traffic safety) and military services. Precise point positioning (PPP) solution is considered as a main geodetic surveying task in post processing of GNSS observations. In last years (PPP) solution package are developed as online services and offline software’s. This study aims to introduce a comparative study between solutions of post processing free online processing (CSRS-PPP) and free offline software (PPPH). Field observations were carried out on 9 IGS stations utilizing a static GNSS observation method and an observation RINEX 3 format for period of 24hr for 3 consecutive days in January and 3 consecutive days in March 2022. Post-processing of the obtained data was done using online and offline software. The coordinates from online and offline compared with coordinates from IGS station to assess their respective differences and accuracy. The minimum difference 0 cm for both solutions and the maximum difference 1.568 cm for online and 1.404 cm for offline. Online GNSS processing services can be used for engineering and geodetic applications since they are simple to use like PPPH, and are easy to execute.

(Near) Real-Time Snow Water Equivalent Observation Using GNSS Refractometry and RTKLIB.

Global navigation satellite system (GNSS) refractometry enables automated and continuous in situ snow water equivalent (SWE) observations. Such accurate and reliable in situ data are needed for calibration and validation of remote sensing data and could enhance snow hydrological monitoring and modeling. In contrast to previous studies which relied on post-processing with the highly sophisticated Bernese GNSS processing software, the feasibility of in situ SWE determination in post-processing and (near) real time using the open-source GNSS processing software RTKLIB and GNSS refractometry based on the biased coordinate Up component is investigated here. Available GNSS observations from a fixed, high-end GNSS refractometry snow monitoring setup in the Swiss Alps are reprocessed for the season 2016/17 to investigate the applicability of RTKLIB in post-processing. A fixed, low-cost setup provides continuous SWE estimates in near real time at a low cost for the complete 2021/22 season. Additionally, a mobile, (near) real-time and low-cost setup was designed and evaluated in March 2020. The fixed and mobile multi-frequency GNSS setups demonstrate the feasibility of (near) real-time SWE estimation using GNSS refractometry. Compared to state-of-the-art manual SWE observations, a mean relative bias below 5% is achieved for (near) real-time and post-processed SWE estimation using RTKLIB.

GNSS Storm Nowcasting Demonstrator for Bulgaria

Global Navigation Satellite System (GNSS) is an established atmospheric monitoring technique delivering water vapour data in near-real time with a latency of 90 min for operational Numerical Weather Prediction in Europe within the GNSS water vapour service (E-GVAP). The advancement of GNSS processing made the quality of real-time GNSS tropospheric products comparable to near-real-time solutions. In addition, they can be provided with a temporal resolution of 5 min and latency of 10 min, suitable for severe weather nowcasting. This paper exploits the added value of sub-hourly real-time GNSS tropospheric products for the nowcasting of convective storms in Bulgaria. A convective Storm Demonstrator (Storm Demo) is build using real-time GNSS tropospheric products and Instability Indices to derive site-specific threshold values in support of public weather and hail suppression services. The Storm Demo targets the development of service featuring GNSS products for two regions with hail suppression operations in Bulgaria, where thunderstorms and hail events occur between May and September, with a peak in July. The Storm Demo real-time Precise Point Positioning processing is conducted with the G-Nut software with a temporal resolution of 15 min for 12 ground-based GNSS stations in Bulgaria. Real-time data evaluation is done using reprocessed products and the achieved precision is below 9 mm, which is within the nowcasting requirements of the World Meteorologic Organisation. For the period May–September 2021, the seasonal classification function for thunderstorm nowcasting is computed and evaluated. The probability of thunderstorm detection is 83%, with a false alarm ration of 38%. The added value of the high temporal resolution of the GNSS tropospheric gradients is investigated for a storm case on 24–30 August 2021. Real-time tropospheric products and classification functions are integrated and updated in real-time on a publicly accessible geoportal.

Phase Centre Corrections of GNSS Antennas and Their Consistency with ATX Catalogues

Changes of the antenna models on permanent global navigation satellite system (GNSS) stations can lead to jumps and discontinuities in the coordinate time series. In this paper, the results of research on the adequacy of the antenna phase centre corrections (PCC) variations are presented by analysing its component—the antennas’ phase centre offset (PCO). For this purpose, height differences were determined using different and independent methods: EUREF Permanent Network (EPN) combined solutions, Precise Point Positioning (PPP), and the single baseline solution. The results of GNSS processing were referenced to direct geometric levelling outputs. The research was conducted only within the global positioning system (GPS) system due to the compatibility of one of the receivers, and the experiment was based on a comparison of the height differences between four GNSS antennas located on the roof of a building: two permanent station antennas and two auxiliary points. The antennas were located at similar heights; precise height differences were determined by geometric levelling, both at the beginning and the end of the session. Post-processing was conducted with the use of the GPS system, precise ephemeris, the adopted antenna correction model, and a zero-elevation mask. For one of the antennas, a change of the antenna characteristic model from IGS08 to IGS14 leads to an 8-mm difference in height. Older antennas used in the national (or transnational) permanent network need individual PCC.

Assessment of tropospheric modeling on PPP-AR performances under brazilian atmospheric condition

In the Global Navigation Satellite System (GNSS), ambiguity resolution (AR) can shorten observation time and increase the positioning quality. The correct tropospheric modeling is intrinsically related to the ability to perform AR. Here, we assessed the influence of different tropospheric correction alternatives on AR for static Precise Point Positioning (PPP) in Brazilian territory. Our goal was to provide directions to users when choosing a suitable tropospheric model for application in PPP-AR under Brazilian atmospheric conditions. Thus, this study was carried out using well-known models such as the Saastamoinen model and the Zenith Tropospheric Delay (ZTD) Estimation and Numerical Weather Prediction (NWP) model from CPTEC/INPE. Six GNSS stations from the Brazilian Network for Continuous Monitoring (RBMC) (BRAZ, UFPR, RNNA, POVE, SMAR, and SAGA) were selected. Different GNSS processing setups were considered for GNSS data registered at selected stations during summer and winter. The assessment was based on a statistical analysis of positioning accuracy during one-hour sessions. The results indicated that such as the ZTD Estimation, the NWP model provides an accuracy of a few centimeters. On the other hand, the Saastamoinen model provided decimeter level accuracy, thus it is not the recommended choice for PPP-AR in the experimental conditions.

GROOPS: A software toolkit for gravity field recovery and GNSS processing

The Gravity Recovery Object Oriented Programming System (GROOPS) is a software toolkit written in C++ that enables the user to perform core geodetic tasks. Key features of the software include gravity field recovery from satellite and terrestrial data, the determination of satellite orbits from global navigation satellite system (GNSS) measurements, and the computation of GNSS constellations and ground station networks. Next to raw data processing, GROOPS is capable to operate on time series and spatial data to directly analyze and visualize the computed data sets. Most tasks and algorithms are (optionally) parallelized through the Message Passing Interface, thus the software enables a smooth transition from single-CPU desktop computers to large distributed computing environments for resource intensive tasks. For an easy and intuitive setup of complex workflows, GROOPS contains a graphical user interface to create and edit configuration files. The source code of the software is freely available on GitHub (https://github.com/groops-devs/groops) together with documentation, a cookbook with guided examples, and step-by-step installation instructions.

A GNSS velocity field for geophysical applications in Fennoscandia

In Fennoscandia, tectonics, Glacial Isostatic Adjustment (GIA), and climatic changes cause ongoing crustal deformation of some millimetres per year, both vertically and horizontally. These displacements of the Earth can be measured to a high degree of precision using a Global Navigation Satellite System (GNSS). Since about three decades, this is the major goal of the Baseline Inferences for Fennoscandian Rebound, Sea-level, and Tectonics (BIFROST) project.We present a new velocity field for an extended BIFROST GNSS network in the ITRF2008 reference frame making use of the GNSS processing package GPS Analysis Software of MIT (GAMIT). Compared to earlier publications, we have almost doubled the number of stations in our analysis and increased the observation time span, thereby avoiding the early years of the network with many instrument changes. We also provide modelled vertical deformation rates from contributing processes, i.e. elastic deformation due to global atmospheric and non-tidal ocean loading, ice mass and hydrological changes as well as GIA. These values for the vertical component can be used for removal of these contributions so that the residual uplift signal can be further analysed, e.g., in the context of local or regional deformation processes or large-scale but low-magnitude geodynamics.The velocity field has an uplift maximum of 10.3 mm/yr in northern Sweden west of the Gulf of Bothnia and subsidence exceeding 1 mm/yr in northern Central Europe. The horizontal velocity field is dominated by plate motion of more than 20.0 mm/yr from south-west to north-east. The elastic uplift signal sums up to 0.7–0.8 mm/yr for most stations in Northern Europe. Hence, the maximum uplift related to the past glaciation is ca. 9.6 mm/yr. The residual uplift signal after removal of the elastic and GIA contribution may point to possible improvements of the GIA model, but may also indicate regional tectonic and erosional processes as well as local deformation effects. We show an example of such residual signal discussing potential areas of interest for further studies.

Integrated water vapour content retrievals from ship-borne GNSS receivers during EUREC<sup>4</sup>A

Abstract. In the framework of the EUREC4A (Elucidating the role of clouds–circulation coupling in climate) campaign that took place in January and February 2020, integrated water vapour (IWV) contents were retrieved over the open tropical Atlantic Ocean using Global Navigation Satellite System (GNSS) data acquired from three research vessels (R/Vs): R/V Atalante, R/V Maria S. Merian and R/V Meteor. This paper describes the GNSS processing method and compares the GNSS IWV retrievals with IWV estimates from the European Centre for Medium-range Weather Forecasts (ECMWF) fifth reanalysis (ERA5), from the Moderate Resolution Imaging Spectroradiometer (MODIS) infrared products and from terrestrial GNSS stations located along the tracks of the ships. The ship-borne GNSS IWV retrievals from R/V Atalante and R/V Meteor compare well with ERA5, with small biases (−1.62 kg m−2 for R/V Atalante and +0.65 kg m−2 for R/V Meteor) and a root mean square (rms) difference of about 2.3 kg m−2. The results for the R/V Maria S. Merian are found to be of poorer quality, with an rms difference of 6 kg m−2, which is very likely due to the location of the GNSS antenna on this R/V prone to multipath effects. The comparisons with ground-based GNSS data confirm these results. The comparisons of all three R/V IWV retrievals with MODIS infrared products show large rms differences of 5–7 kg m−2, reflecting the enhanced uncertainties in these satellite products in the tropics. These ship-borne IWV retrievals are intended to be used for the description and understanding of meteorological phenomena that occurred during the campaign, east of Barbados, Guyana and northern Brazil. Both the raw GNSS measurements and the IWV estimates are available through the AERIS data centre (https://en.aeris-data.fr/, last access: 20 September 2020). The digital object identifiers (DOIs) for R/V Atalante IWV and raw datasets are https://doi.org/10.25326/71 (Bosser et al., 2020a) and https://doi.org/10.25326/74 (Bosser et al., 2020d), respectively. The DOIs for the R/V Maria S. Merian IWV and raw datasets are https://doi.org/10.25326/72 (Bosser et al., 2020b) and https://doi.org/10.25326/75 (Bosser et al., 2020e), respectively. The DOIs for the R/V Meteor IWV and raw datasets are https://doi.org/10.25326/73 (Bosser et al., 2020c) and https://doi.org/10.25326/76 (Bosser et al., 2020f), respectively.

An efficient parallel computing strategy for the processing of large GNSS network datasets

The Global Navigation Satellite System (GNSS) has been an indispensable tool for geodetic surveying and geodynamics research and has rapidly developed over the past few years with abundant ground networks, modern constellations and multiple signal frequencies. However, due to increasing numbers of stations and satellites, the data processing burden has increased significantly. In this contribution, an improved parallel computing method is proposed for processing large GNSS network datasets. First, a parallelization strategy is introduced for the traditional GNSS processing model by analyzing the practicability of parallel integrated processing for GNSS network data. In addition, to maximize the advantages of modern microprocessors and local area network environments, we present the multi-core parallel computing of traditional GNSS data processing methods; then, the product is released as a service-oriented architecture that can be found and invoked through multiple nodes in the Internet. Obviously, this method combines the advantages of multi-core parallelism and network parallelism. Experiments show that the efficiency of the proposed method can be further increased with the accumulation of GNSS data and additional nodes. For example, in a network with 2000 stations, the efficiency of the parallel scheme with four quad-core nodes is at least 8 times faster than that of the traditional serial scheme. All the results demonstrate that the proposed strategy is an efficient and promising approach for processing large GNSS network datasets.

Monitoring Surface Displacement of a Deep-Seated Landslide by a Low-Cost and near Real-Time GNSS System

A prototype of a low-cost GNSS (Global Navigation Satellite System) monitoring system was installed on a deep-seated landslide in north-western Slovenia to test its performance under field conditions. The system consists of newly developed GNSS stations based on low-cost, dual-frequency receivers and open-source GNSS processing software. It automatically receives GNSS data and transmits them over the Internet. The system processes the data server-side and makes them available to the end user via a web portal. The detected surface displacements were evaluated through a comparison with the network of classic geodetic measurements. The results of a nine-month monitoring period using seven GNSS stations provided a detailed insight into the spatial and temporal pattern of deep-seated landslide surface movements. The displacement data were correlated with precipitation measurements at the site to reveal how different parts of the landslide react to rainfall. These data form the basis for the further development of an early-warning system which will help to manage the risk the landslide poses to the local population and infrastructure.

A GNSS-based near real time automatic Earth Crust and Atmosphere Monitoring Service for Turkey

Turkey is located in a highly active earthquake zone. Many geodynamic and seismic activities occur during a day, such as earthquakes, landslides, sinkholes and creep movements. In addition to seismicity, Turkey has unique physical features like being surrounded by seas on three sides, affected by different climate types. It is located on mid latitudes, which makes Turkey very suitable for atmospheric studies. For this reason, Turkey serves as a natural laboratory for geodesy, geophysical and atmospheric scientists. Therefore, Global Navigation Satellite System (GNSS) data are used in many areas. However, not all the scientists can reach or process the data for coordinate-based studies. Within the scope of the study, a GNSS-based Earth Crust and Atmosphere Monitoring Service is established at the Zonguldak Bulent Ecevit University. Using the results of the GNSS processing, time series of GNSS station positions are produced and used to infer strain solutions related to earthquakes. Estimates of the Precipitable Water Vapour (PWV) and the Total Electron Content (TEC) in the ionosphere are made available for tropospheric and ionospheric studies, respectively. Visualisation of the results are intended to be provided to the scientific community. Results show that the root mean square (RMS) differences of the PWV between GNSS and radiosondes are in the range of 1–3 mm. RMS differences of the TEC is in the range of 2–3 TEC units when comparing our GNSS estimates with the Global Ionospheric Maps (GIM) from the International GNSS Service (IGS). One of the main results obtained from the analysis centre is near real-time strain rates and their relations to actual earthquakes. Results show that near real-time strain rates can be assessed as a precursor parameter for earthquakes.

An ERA5-Based Hourly Global Pressure and Temperature (HGPT) Model

The Global Navigation Satellite System (GNSS) meteorology contribution to the comprehension of the Earth’s atmosphere’s global and regional variations is essential. In GNSS processing, the zenith wet delay is obtained using the difference between the zenith total delay and the zenith hydrostatic delay. The zenith wet delay can also be converted into precipitable water vapor by knowing the atmospheric weighted mean temperature profiles. Improving the accuracy of the zenith hydrostatic delay and the weighted mean temperature, normally obtained using modeled surface meteorological parameters at coarse scales, leads to a more accurate and precise zenith wet delay estimation, and consequently, to a better precipitable water vapor estimation. In this study, we developed an hourly global pressure and temperature (HGPT) model based on the full spatial and temporal resolution of the new ERA5 reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). The HGPT model provides information regarding the surface pressure, surface air temperature, zenith hydrostatic delay, and weighted mean temperature. It is based on the time-segmentation concept and uses the annual and semi-annual periodicities for surface pressure, and annual, semi-annual, and quarterly periodicities for surface air temperature. The amplitudes and initial phase variations are estimated as a periodic function. The weighted mean temperature is determined using a 20-year time series of monthly data to understand its seasonality and geographic variability. We also introduced a linear trend to account for a global climate change scenario. Data from the year 2018 acquired from 510 radiosonde stations downloaded from the National Oceanic and Atmospheric Administration (NOAA) Integrated Global Radiosonde Archive were used to assess the model coefficients. Results show that the GNSS meteorology, hydrological models, Interferometric Synthetic Aperture Radar (InSAR) meteorology, climate studies, and other topics can significantly benefit from an ERA5 full-resolution model.