Application of Global Positioning System slant path delay data for mesoscale modelverification and four-dimensional variational assimilation

Observation modeling is required in order to make use of slant path delay data, processed from ground-based Global Positioning System (GPS) measurements, for verification purposes and numerical weather prediction. A rigorous ray-tracing algorithm based on the Euler-Lagrange equation derived from Fermat's principle is developed to simulate the propagation of GPS radio signals in a mesoscale model. The ray-tracing algorithm is based on a finite difference scheme and allows the direct numerical simulation of GPS slant path delays.Slant Path Delay-Daten, die aus bodengestützten Global Positioning System (GPS)-Messungen abgeleitet werden, können zur Verifikation von mesoskaligen Modellen und zur numerischen Wettervorhersage verwendet werden. Dazu ist die Entwicklung eines Vorwärtsmodells notwendig. Ein rigoroser Ray Tracing Algorithmus basierend auf den Euler-Lagrange-Gleichungen abgeleitet aus Fermat's Prinzip wurde entwickelt, um die Ausbreitung von GPS Radiosignalen in einem mesoskaligen Modell zu simulieren. Der Ray Tracing-Algorithmus basiert auf einem Finite Differenzen-Verfahren und erlaubt die direkte numerische Simulation von GPS Slant Path Delay-Daten

Estimating integrated water vapor trends from VLBI, GPS,and numerical weather models: sensitivity totropospheric parameterization

©2018. American Geophysical UnionIn this study, we estimate integrated water vapor (IWV) trends from very long baseline interferometry (VLBI) and global navigation satellite systems (GNSS) data analysis, as well as from numerical weather models (NWMs). We study the impact of modeling and parameterization of the tropospheric delay from VLBI on IWV trends. We address the impact of the meteorological data source utilized to model the hydrostatic delay and the thermal deformation of antennas, as well as the mapping functions employed to project zenith delays to arbitrary directions. To do so, we derive a new mapping function, called Potsdam mapping functions based on NWM data and a new empirical model, GFZ‐PT. GFZ‐PT differs from previous realizations as it describes diurnal and subdiurnal in addition to long‐wavelength variations, it provides harmonic functions of ray tracing‐derived gradients, and it features robustly estimated rates. We find that alternating the mapping functions in VLBI data analysis yields no statistically significant differences in the IWV rates, whereas alternating the meteorological data source distorts the trends significantly. Moreover, we explore methods to extract IWV given a NWM. The rigorously estimated IWV rates from the different VLBI setups, GNSS, and ERA‐Interim are intercompared, and a good agreement is found. We find a quite good agreement comparing ERA‐Interim to VLBI and GNSS, separately, at the level of 75%.DFG, 255986470, GGOS-SIM-2: Simulation des "Global Geodetic Observing System

Retrieving Precipitable Water Vapor From Shipborne Multi‐GNSS Observations

©2019. American Geophysical UnionPrecipitable water vapor (PWV) is an important parameter for climate research and a crucial factor to achieve high accuracy in satellite geodesy and satellite altimetry. Currently Global Navigation Satellite System (GNSS) PWV retrieval using static Precise Point Positioning is limited to ground stations. We demonstrated the PWV retrieval using kinematic Precise Point Positioning method with shipborne GNSS observations during a 20‐day experiment in 2016 in Fram Strait, the region of the Arctic Ocean between Greenland and Svalbard. The shipborne GNSS PWV shows an agreement of ~1.1 mm with numerical weather model data and radiosonde observations, and a root‐mean‐square of ~1.7 mm compared to Satellite with ARgos and ALtiKa PWV. An improvement of 10% is demonstrated with the multi‐GNSS compared to the Global Positioning System solution. The PWV retrieval was conducted under different sea state from calm water up to gale. Such shipborne GNSS PWV has the promising potential to improve numerical weather forecasts and satellite altimetry

A methodology to compute GPS slant total delays in a numerical weather model

A numerical algorithm based on Fermat's Principle was developed to simulate the propagation of Global Positioning System (GPS) radio signals in the refractivity field of a numerical weather model. The unique in the proposed algorithm is that the ray-trajectory automatically involves the location of the ground-based receiver and the satellite, i.e. the posed two-point boundary value problem is solved by an implicit finite difference scheme. This feature of the algorithm allows the fast and accurate computation of the signal travel-time delay, referred to as Slant Total Delay (STD), between a satellite and a ground-based receiver. We provide a technical description of the algorithm and estimate the uncertainty of STDs due to simplifying assumptions in the algorithm and due to the uncertainty of the refractivity field. In a first application, we compare STDs retrieved from GPS phase-observations at the German Research Centre for Geosciences Potsdam (GFZ STDs) with STDs derived from the European Center for Medium-Range Weather Forecasts analyses (ECMWF STDs). The statistical comparison for one month (August 2007) for a large and continuously operating network of ground-based receivers in Germany indicates good agreement between GFZ STDs and ECMWF STDs; the standard deviation is 0.5% and the mean deviation is 0.1%

Estimating the impact of Global Navigation Satellite System horizontal delay gradients in variational data assimilation

We developed operators to assimilate Global Navigation Satellite System (GNSS) Zenith Total Delays (ZTDs) and horizontal delay gradients into a numerical weather model. In this study we experiment with refractivity fields derived from the Global Forecast System (GFS) available with a horizontal resolution of 0.5 degrees. We begin our investigations with simulated observations. In essence, we extract the tropospheric parameters from the GFS analysis, add noise to mimic observation errors and assimilate the simulated observations into the GFS 24h forecast valid at the same time. We consider three scenarios: (1) the assimilation of ZTDs (2) the assimilation of horizontal delay gradients and (3) the assimilation of both ZTDs and horizontal delay gradients. The impact is measured by utilizing the refractivity fields. We find that the assimilation of the horizontal delay gradients in addition to the ZTDs improves the refractivity field around 800 hPa. When we consider a single station there is a clear improvement when horizontal delay gradients are assimilated in addition to the ZTDs because the horizontal delay gradients contain information that is not contained in the ZTDs. On the other hand, when we consider a dense station network there is not a significant improvement when horizontal delay gradients are assimilated in addition to the ZTDs because the horizontal delay gradients do not contain information that is not already contained in the ZTDs. Finally, we replace simulated by real observations, that is, tropospheric parameters from a Precise Point Positioning solution provided with the G-Nut/Tefnut software, in order to show that the GFS 24h forecast is indeed improved when GNSS horizontal delay gradients are assimilated in addition to GNSS ZTDs; for the considered station (Potsdam, Germany) and period (June and July, 2017) we find an improvement in the retrieved refractivity of up to 4%.Web of Science111art. no. 4

Benchmark campaign and case study episode in central Europe for development and assessment of advanced GNSS tropospheric models and products

Initial objectives and design of the Benchmark campaign organized within the European COST Action ES1206 (2013–2017) are described in the paper. This campaign has aimed to support the development and validation of advanced Global Navigation Satellite System (GNSS) tropospheric products, in particular high-resolution and ultra-fast zenith total delays (ZTDs) and tropospheric gradients derived from a dense permanent network. A complex data set was collected for the 8-week period when several extreme heavy precipitation episodes occurred in central Europe which caused severe river floods in this area. An initial processing of data sets from GNSS products and numerical weather models (NWMs) provided independently estimated reference parameters – zenith tropospheric delays and tropospheric horizontal gradients. Their provision gave an overview about the product similarities and complementarities, and thus a potential for improvements of a synergy in their optimal exploitations in future. Reference GNSS and NWM results were intercompared and visually analysed using animated maps. ZTDs from two reference GNSS solutions compared to global ERA-Interim reanalysis resulted in accuracy at the 10 mm level in terms of the root mean square (rms) with a negligible overall bias, comparisons to Global Forecast System (GFS) forecasts showed accuracy at the 12 mm level with the overall bias of −5 mm and, finally, comparisons to mesoscale ALADIN-CZ forecast resulted in accuracy at the 8 mm level with a negligible total bias. The comparison of horizontal tropospheric gradients from GNSS and NWM data demonstrated a very good agreement among independent solutions with negligible biases and an accuracy of about 0.5 mm. Visual comparisons of maps of zenith wet delays and tropospheric horizontal gradients showed very promising results for future exploitations of advanced GNSS tropospheric products in meteorological applications, such as severe weather event monitoring and weather nowcasting. The GNSS products revealed a capability of providing more detailed structures in atmosphere than the state-of-the-art numerical weather models are able to capture. In an initial study on the contribution of hydrometeors (e.g. cloud water, ice or snow) to GNSS signal delays during severe weather, the effect reached up to 17 mm, and it was suggested that hydrometeors should be carefully accounted for within the functional model. The reference products will be further exploited in various specific studies using the Benchmark data set. It is thus going to play a key role in these highly interdisciplinary developments towards better mutual benefits from advanced GNSS and meteorological products.Web of Science973008298

Inter-technique validation of tropospheric slant total delays

An extensive validation of line-of-sight tropospheric slant total delays (STD) from Global Navigation Satellite Systems (GNSS), ray tracing in numerical weather prediction model (NWM) fields and microwave water vapour radiometer (WVR) is presented. Ten GNSS reference stations, including collocated sites, and almost 2 months of data from 2013, including severe weather events were used for comparison. Seven institutions delivered their STDs based on GNSS observations processed using 5 software programs and 11 strategies enabling to compare rather different solutions and to assess the impact of several aspects of the processing strategy. STDs from NWM ray tracing came from three institutions using three different NWMs and ray-tracing software. Inter-techniques evaluations demonstrated a good mutual agreement of various GNSS STD solutions compared to NWM and WVR STDs. The mean bias among GNSS solutions not considering post-fit residuals in STDs was -0.6 mm for STDs scaled in the zenith direction and the mean standard deviation was 3.7 mm. Standard deviations of comparisons between GNSS and NWM ray-tracing solutions were typically 10 mm +/- 2 mm (scaled in the zenith direction), depending on the NWM model and the GNSS station. Comparing GNSS versus WVR STDs reached standard deviations of 12 mm +/- 2 mm also scaled in the zenith direction. Impacts of raw GNSS post-fit residuals and cleaned residuals on optimal reconstructing of GNSS STDs were evaluated at intertechnique comparison and for GNSS at collocated sites. The use of raw post-fit residuals is not generally recommended as they might contain strong systematic effects, as demonstrated in the case of station LDB0. Simplified STDs reconstructed only from estimated GNSS tropospheric parameters, i.e. without applying post-fit residuals, performed the best in all the comparisons; however, it obviously missed part of tropospheric signals due to non-linear temporal and spatial variations in the troposphere. Although the post-fit residuals cleaned of visible systematic errors generally showed a slightly worse performance, they contained significant tropospheric signal on top of the simplified model. They are thus recommended for the reconstruction of STDs, particularly during high variability in the troposphere. Cleaned residuals also showed a stable performance during ordinary days while containing promising information about the troposphere at low-elevation angles.Web of Science1062208218

Improving the vertical modeling of tropospheric delay

Accurate tropospheric delays from Numerical Weather Models (NWM) are an important input to space geodetic techniques, especially for precise real-time Global Navigation Satellite Systems, which are indispensable to earthquake and tsunami early warning systems as well as weather forecasting. The NWM-based tropospheric delays are currently provided either site-specific with a limited spatial coverage, or on two-dimensional grids close to the Earth surface, which cannot be used for high altitudes. We introduce a new method of representing NWM-derived tropospheric zenith hydrostatic and wet delays. A large volume of NWM-derived data is parameterized with surface values and additional two or three coefficients for their vertical scaling to heights up to 14 km. A precision of 1–2 mm is achieved for reconstructing delays to the NWM-determined delays at any altitudes. The method can efficiently deliver NWM-derived tropospheric delays to a broader community of space geodetic techniques.DFG, 434617780, SFB 1464: Relativistische und quanten-basierte Geodäsie (TerraQ

Sensitivity of GNSS tropospheric gradients to processing options

An analysis of processing settings impacts on estimated tropospheric gradients is presented. The study is based on the benchmark data set collected within the COST GNSS4SWEC action with observations from 430 Global Navigation Satellite Systems (GNSS) reference stations in central Europe for May and June 2013. Tropospheric gradients were estimated in eight different variants of GNSS data processing using precise point positioning (PPP) with the G-Nut/Tefnut software. The impacts of the gradient mapping function, elevation cut-off angle, GNSS constellation, observation elevation-dependent weighting and real-time versus post-processing mode were assessed by comparing the variants by each to other and by evaluating them with respect to tropospheric gradients derived from two numerical weather models (NWMs). Tropospheric gradients estimated in post-processing GNSS solutions using final products were in good agreement with NWM outputs. The quality of high-resolution gradients estimated in (near-)real-time PPP analysis still remains a challenging task due to the quality of the real-time orbit and clock corrections. Comparisons of GNSS and NWM gradients suggest the 3 degrees elevation angle cut-off and GPS+GLONASS constellation for obtaining optimal gradient estimates provided precise models for antenna-phase centre offsets and variations, and tropospheric mapping functions are applied for low-elevation observations. Finally, systematic errors can affect the gradient components solely due to the use of different gradient mapping functions, and still depending on observation elevation-dependent weighting. A latitudinal tilting of the troposphere in a global scale causes a systematic difference of up to 0.3 mm in the north-gradient component, while large local gradients, usually pointing in a direction of increasing humidity, can cause differences of up to 1.0 mm (or even more in extreme cases) in any component depending on the actual direction of the gradient. Although the Bar-Sever gradient mapping function provided slightly better results in some aspects, it is not possible to give any strong recommendation on the gradient mapping function selection.Web of Science37344642

GNSS Remote Sensing:Overview and selected recent developments

Ponencia expuesta online en el 8th International Radio Occultation Working Group Meeting (2021) celebrado del 7 al 9 de abrilGround and satellite based GNSS Remote Sensing (GNSS-RS) developed during the recent two decades into a very powerful and versatile tool for Earth System Research. A highlight of these developments is the operational use of spaceborne GNSS Radio Occultation (RO) data from several satellite missions to improve day-by-day global weather predictions. GNSS Remote Sensing is briefly introduced with selected applications. One prominent example is the improvement of regional and global weather forecasts. GNSS signals, reflected from water, ice and land surfaces (GNSS-Reflectometry, GNSS-R) can usefully complement the observation capabilities of GNSS-RO mission and enable versatile additional geophysical applications such as observation of wind speed and precipitation over oceans, which are illustrated. Finally, selected aspects for a comprehensive GNSS based Earth Observation with small satellite constellations are presented