Kinematic ZTD Estimation from Train-Borne Single-Frequency GNSS: Validation and Assimilation

Water vapour is one of the most important parameters utilized for the description of state and evolution of the Earth’s atmosphere. It is the most effective greenhouse gas and shows high variability, both in space and time. Thus, detailed knowledge of its distribution is of immense importance for weather forecasting, and therefore high resolution observations are crucial for accurate precipitation forecasts, especially for the short-term prediction of severe weather. Although not intentionally built for this purpose, Global Navigation Satellite Systems (GNSS) have proven to meet those requirements. The derivation of water vapour content from GNSS observations is based on the fact that electromagnetic signals are delayed when travelling through the atmosphere. The most prominent parameterization of this delay is the Zenith Total Delay (ZTD), which has been studied extensively as a major error term in GNSS positioning. On the other hand, the ZTD has also been proven to provide substantial benefits for atmospheric research and especially Numerical Weather Prediction (NWP) model performance. Based on these facts, the scientific area of GNSS Meteorology has emerged. The present study goes beyond the current status of GNSS Meteorology, showing how reasonable estimates of ZTD can be derived from highly-kinematic, single-frequency (SF) GNSS data. This data was gathered from trains of the Austrian Federal Railways (ÖBB) and processed using the Precise Point Positioning (PPP) technique. The special nature of the observations yields a number of additional challenges, ranging from appropriate pre-processing and parameter settings in PPP to more sophisticated validation and assimilation methodologies . The treatment of the ionosphere for SF-GNSS data represents one of the major challenges of this study. Two test cases (train travels) were processed using different strategies and validated using ZTD calculated from ERA5 reanalysis data. The validation results indicate a good overall agreement between the GNSS-ZTD solutions and ERA5-derived ZTD, although substantial variability between solutions was still observed for specific sections of the test tracks. The bias and standard deviation values ranged between 1 mm and 8 cm, heavily depending on the utilized processing strategy and investigated train route. Finally, initial experiments for the assimilation of GNSS-ZTD estimates into a NWP model were conducted, and the results showed observation acceptance rates of 30–100% largely depending on the test case and processing strategy.

A Regional Model for Predicting Tropospheric Delay and Weighted Mean Temperature in China Based on GRAPES_MESO Forecasting Products

Accurate tropospheric delay (TD) and weighted mean temperature (Tm) are important for Global Navigation Satellite System (GNSS) positioning and GNSS meteorology. For this purpose, plenty of empirical models have been built to provide estimates of TD and Tm. However, these models cannot resolve TD and Tm variations at synoptic timescales since they only model the average annual, semi-annual, and/or daily variations. As a result, the existed empirical models cannot perform well under extreme weather conditions. To address this limitation, we propose to estimate Zenith Hydrostatic Delay (ZHD), Zenith Wet Delay (ZWD), and Tm directly from the stratified numerical weather forecasting products of the mesoscale version of the Global/Regional Assimilation and PrEdiction System (GRAPES_MESO) of China. The GRAPES_MESO forecasting data has a temporal resolution of 3 h, which provides the opportunity to resolve the synoptic variation. However, it is found that the estimated ZWD and Tm exhibit apparent systematic deviation from in situ observation-based estimates, which is due to the inherent biases in the GRAPES_MESO data. To solve this problem, we propose to correct these biases using a linear model and a spherical cap harmonic model. The estimates after correction are termed as the “CTropGrid” products. When validated by the radiosonde data, the CTropGrid product has biases of 1.5 mm, −0.7 mm, and −0.1 K, and Root Mean Square (RMS) error of 8.9 mm, 20.2 mm, and 1.5 K for ZHD, ZWD, and Tm. Compared to the widely used GPT2w model, the CTropGrid products have improved the accuracies of ZHD, ZWD, and Tm by 11.9%, 55.6%, and 60.5% in terms of RMS. When validating the Zenith Tropospheric Delay (ZTD) products (the sum of ZHD and ZWD) using the IGS ZTD data, the CTropGrid ZTD has a bias of −0.7 mm and an RMS of 35.8 mm, which is 22.7% better than the GPT2w model in terms of RMS. Besides the accuracy improvements, the CTropGrid products well model the synoptic-scale variations of ZHD, ZWD, and Tm. Compared to the existing empirical models that only capture the tidal (seasonal and/or diurnal) variations, the CTropGrid products capture well the non-tidal variations of ZHD, ZWD, and Tm, which enhances the tropospheric delay corrections and GNSS water vapor monitoring at synoptic timescales. Therefore, the CTropGrid product is an important progress in GNSS positioning and GNSS meteorology.

Detection of Alpine Foehn in GNSS-ZWD time series: An innovative application of GNSS Meteorology

<p>The atmospheric delay experienced by a signal of the Global Navigation Satellite System (GNSS) is proportional to the water vapour content along the signal path. This fact is typically exploited in GNSS Meteorology by introducing GNSS derived atmospheric parameters like the Zenith Wet Delay (ZWD) in data assimilation schemes. In numerous studies, the positive impact on the (especially precipitation) forecast has been demonstrated. However, while mostly precipitation-related studies represent the current focus of research, other meteorological phenomena might also be investigated by means of GNSS.</p><p>The present study represents an initial investigation on the detection of another important meteorological phenomena using GNSS time series: Foehn winds. Foehn denotes a gusty, warm fall wind occurring in mountainous regions worldwide, leading to a relatively mild climate in affected areas. On the other hand, Foehn can also be characterized as severe weather leading to disasters, due to the high wind speeds frequently encountered.</p><p>The proposed detection method of Foehn in ZWD time series is based on the significant drying/wetting effects on the lee/luv side of an affected mountain range associated with Foehn. The comparison of ZWD from stations on both sides of the main Alpine ridge reveals characteristic features like distinctive ZWD minima/maxima and significant decrease in correlation between the stations.</p><p>In this study we investigate a number of well-documented Foehn events in the Swiss Alps (therefore called Alpine Foehn) using ZWD time series from the Automated GNSS Network Switzerland (AGNES) station network, operated by the Swiss Federal Office of Topography (swisstopo). Based on these case studies, an assessment of the usability of GNSS-ZWD for Foehn detection is presented and possible strengths and weaknesses will be analysed. Finally, an outlook on possible improvements and innovative extensions to the presented approach is given. These range from embedment of ZWD data in operational Foehn classification and the application of Machine-Learning techniques for detection, to the establishment of collocated GNSS/weather stations, which come with a number of scientific benefits - not only for Foehn investigations but GNSS Meteorology in general.</p>

Review on the Role of GNSS Meteorology in Monitoring Water Vapor for Atmospheric Physics

After 30 years since the beginning of the Global Positioning System (GPS), or, more generally, Global Navigation Satellite System (GNSS) meteorology, this technique has proven to be a reliable method for retrieving atmospheric water vapor; it is low-cost, weather independent, with high temporal resolution and is highly accurate and precise. GNSS ground-based networks are becoming denser, and the first stations installed have now quite long time-series that allow the study of the temporal features of water vapor and its relevant role inside the climate system. In this review, the different GNSS methodologies to retrieve atmospheric water vapor content re-examined, such as tomography, conversion of GNSS tropospheric delay to water vapor estimates, analyses of errors, and combinations of GNSS with other sources to enhance water vapor information. Moreover, the use of these data in different kinds of studies is discussed. For instance, the GNSS technique is commonly used as a reference tool for validating other water vapor products (e.g., radiosounding, radiometers onboard satellite platforms or ground-based instruments). Additionally, GNSS retrievals are largely used in order to determine the high spatio-temporal variability and long-term trends of atmospheric water vapor or in models with the goal of determining its notable influence on the climate system (e.g., assimilation in numerical prediction, as input to radiative transfer models, study of circulation patterns, etc.).

Ground-Based GNSS Meteorology and Reflectometry Studies on Horseshoe Island during the 4th National Antarctic Science Expedition of Turkey: Installation and configuration of sea/ice level and water vapor monitoring stations.

<p>The radiation balance of our planet affect climate system that showing signs of breaking down due to the rising temperatures, melting of ice and water flows to the oceans from glaciers. In the last decade, GNSS Meteorology and Reflectometry methods are increasingly used for global climate change studies that provides important parameters such as water vapor in the troposphere and ice/sea level measured based on reflected signals. The main purpose of the study is retrieving meteorological and physical parameters of the Earth's surface in the Antarctica to contribute monitoring climate change. For this purpose, dual antenna and single antenna GNSS stations were specially designed within the scope of TUBITAK research project 118Y322 to produce output by combining an ultrasonic sensor to detect real-time ice/sea level. These two GNSS stations including meteorological station were installed on Horseshoe Island during 4th National Antarctic Science Expedition of Turkey (TAE-4). It is believed that these stations will contribute to monitor global climate change by providing important information about troposphere and physical characteristics of Earth surface. In this study, the processes and objectives from the design works of the stations to their installation in Antarctica are explained.  </p>

Assessment of the Accuracy of the Saastamoinen Model and VMF1/VMF3 Mapping Functions with Respect to Ray-Tracing from Radiosonde Data in the Framework of GNSS Meteorology

In this paper, we assess, in the framework of Global Navigation Satellite System (GNSS) meteorology, the accuracy of GNSS propagation delays corresponding to the Saastamoinen zenith hydrostatic delay (ZHD) model and the Vienna Mapping function VMF1/VMF3 (hydrostatic and wet), with reference to radiosonde ray-tracing delays over a three-year period on 28 globally distributed sites. The results show that the Saastamoinen ZHD estimates have a mean root mean square (RMS) error of 1.7 mm with respect to the radiosonde. We also detected some seasonal signatures in these Saastamoinen ZHD estimates. This indicates that the Saastamoinen model, based on the hydrostatic assumption and the ground pressure, is insufficient to capture the full variability of the ZHD estimates over time with the accuracy needed for GNSS meteorology. Furthermore, we found that VMF3 slant hydrostatic delay (SHD) estimates outperform the corresponding VMF1 SHD estimates (equivalent SHD RMS error of 4.8 mm for VMF3 versus 7.1 mm for VMF1 at 5° elevation angle), with respect to the radiosonde SHD estimates. Unexpectedly, the situation is opposite for the VMF3 slant wet delay (SWD) estimates compared to VMF1 SWD estimates (equivalent SWD RMS error of 11.4 mm for VMF3 versus 7.0 mm for VMF1 at 5° elevation angle). Our general conclusion is that the joint approach using ZHD models and mapping functions must be revisited, at least in the framework of GNSS meteorology.

Considering different recent advancements in GNSS on real-time zenith troposphere estimates

Global navigation satellite system (GNSS) remote sensing of the troposphere, called GNSS meteorology, is already a well-established tool in post-processing applications. Real-time GNSS meteorology has been possible since 2013, when the International GNSS Service (IGS) established its real-time service. The reported accuracy of the real-time zenith total delay (ZTD) has not improved significantly over time and usually remains at the level of 5–18 mm, depending on the station and test period studied. Millimeter-level improvements are noticed due to GPS ambiguity resolution, gradient estimation, or multi-GNSS processing. However, neither are these achievements combined in a single processing strategy, nor is the impact of other processing parameters on ZTD accuracy analyzed. Therefore, we discuss these shortcomings in detail and present a comprehensive analysis of the sensitivity of real-time ZTD on processing parameters. First, we identify a so-called common strategy, which combines processing parameters that are identified to be the most popular among published papers on the topic. We question the popular elevation-dependent weighting function and introduce an alternative one. We investigate the impact of selected processing parameters, i.e., PPP functional model, GNSS selection and combination, inter-system weighting, elevation-dependent weighting function, and gradient estimation. We define an advanced strategy dedicated to real-time GNSS meteorology, which is superior to the common one. The a posteriori error of estimated ZTD is reduced by 41%. The accuracy of ZTD estimates with the proposed strategy is improved by 17% with respect to the IGS final products and varies over stations from 5.4 to 10.1 mm. Finally, we confirm the latitude dependency of ZTD accuracy, but also detect its seasonality.

GNSS-METEOROLOGY: OPPORTUNITIES AND PROSPECTS FOR DEVELOPMENT IN RUSSIA AND ABROAD

The article considers the possibilities and prospects for the development of GNSS meteorology based on domestic and foreign research. It is noted that the tropospheric delay of the GNSS signal is a valuable source of information about the state of the troposphere. The algorithm for estimating tropospheric delay and the services that perform this assessment (international GNSS service IGS and online service GAPS) are described. The content of the IGS output file with tropospheric delays at the IGS point is considered. The necessary conditions for the implementation of GNSS meteorology are listed, as well as structural diagrams of existing GNSS meteorology systems in the United States and Japan. It is shown that research in this area is being carried out in Russia. It is concluded that the network of permanent base stations in the Novosibirsk Region has the potential for the development of GNSS meteorology in the covered area.