EGU General Assembly 2022  

In this presentation a kaleidoscopic overview of some geodetic inferential challenges and opportunities will be given. The topics addressed are (1) Interferometric inference; (2) Distributive computing; and (3) Predictive quality. They represent samples of fertile grounds for the typical researcher (PhD student and Postdoc alike) interested in geodetic data processing and modelling, and eager to take up a difficult challenge and/or looking for research opportunities that can make a difference.

Interferometric inference: Although considerable advances have been made in this field, particularly through the very successful global research in interferometric-GNSS, important challenges posed by our mixed-integer models remain. These challenges will be discussed, with a particular reference to distributional multimodality and integer-estimability of FDMA and LTE based carrier-phase systems.

Distributed computing: With data growth numerically straining conventional centralized approaches, complementary cooperative inferential capabilities are asked for. The opportunities of such principles are discussed and examples will be given of dividing estimation problems into easier-to-solve nodal problems which are then coordinated towards an improved, ideally optimal, solution by means of iterative schemes.

Predictive quality: As parameter estimation and statistical testing are typically combined in any geodetic inference, their interactions are to be taken into account when describing the quality of one’s model predictions. The challenges and intricacies that this brings are highlighted, whereby it is suggested that several of the existing validation and representation procedures need revisiting to ensure suitability of their quality descriptions.

How to cite: Teunissen, P.: Geodetic inference: a selection of some challenging topics, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13344, https://doi.org/10.5194/egusphere-egu22-13344, 2022.

Understanding how the Earth’s shape, gravity field and rotation change in response to shifting hydrological, atmospherical and oceanic mass loads at its surface has great potential for monitoring the evolving climate. Recent advances in the field, namely hydrogeodesy, have required hand-in-hand development and improvement of the observing techniques and of our understanding of the solid Earth-climate interactions. 

In particular, measurement of the spatial and temporal variations of the Earth's gravity field by the GRACE and GRACE-Follow On satellite missions offer an unprecedented measurement of the evolution of water mass redistribution, at timescales ranging from months to decades. However, the use of GRACE and GRACE-FO data for hydrological applications presents two major difficulties. First, the mission design and data processing lead to measurement noise and errors that limit GRACE missions to large-scale applications and complicates geophysical interpretation. Moreover, temporal observational gaps, including the 11 month-long gap between missions, prevent the interpretation of long-term mass variations. Secondly, disentangling sources of signals from the solid Earth and continental hydrology is challenging and requires to develop methods benefiting from multiple geodetic techniques. 

To reduce noise and enhance geophysical signals in the data, we develop a method based on a spectral analysis by Multiple Singular Spectrum Analysis (M-SSA) which, using the spatio-temporal correlations of the GRACE-GRACE-FO time series, can fill observational gaps and remove a significant portion of the distinctive noise pattern while maintaining the best possible spatial resolution. This processing reveals hydrological signals that are less well or not resolved by other processing strategies. We discuss regional hydrological mass balance, including lakes, aquifers and ice caps regions, derived from the GRACE-GRACE-FO M-SSA solution. Furthermore, we discuss methods to separate sources of gravity variations using additional in-situ hydrological data or geodetic measurements of the Earth’s deformation. 

How to cite: Chanard, K.: Geodesy: a sensor for hydrology, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12642, https://doi.org/10.5194/egusphere-egu22-12642, 2022.

Earthquakes are one of the most devastating natural disasters, and their impact on human society, in terms of casualties and economic damage, has been significant throughout history. Earthquake prediction can aid in preparing for this major event, and its purpose is to identify earthquake-prone areas and reduce their financial and human losses. Any parameter that changes before the earthquake in a way that one can predict the earthquake with a careful study of its variations is called a precursor. Recently, more attention has been paid to geophysical, geomagnetic, geoelectrical, and electromagnetic precursors. In the present study, the geomagnetic data of three stations, obtained through INTERMAGNET, with a distance of less than 500 km to the 5 Sep. Japan earthquake are investigated. Then the method of characteristic curves is used to remove the effect of diurnal variation of the geomagnetic field. After that, by examining the anomalies which are more distinct after implementation of the method, the cases are matched with the seismic activities of the region. By separating the noise from the desired signal, a pure anomaly can be observed. Among the various magnetic components, the horizontal components are more suitable than the others for the proposed process because of more variations in the geomagnetic field in the vertical direction due to the presence of the geomagnetic gradient. In the present study, one year of magnetic data, including three stations and for X, Y, and Z components, and seismic data for Japan are used to implement this method. The method is based on plotting different magnetic field components in specific time intervals in the same 24 hours frame. This will lead to a plot which shows the geomagnetic nature of each component of the geomagnetic field for each station After averaging the values for every point at the horizontal axis of the plot, which is a unit of time depending on the sampling (hourly mean, minute mean, etc.) a curve will be obtained which is called the characteristic curve. Then we reduce the characteristic curve values from geomagnetic data to reveal the anomalies, free of diurnal variation noise so that the possible anomalies related to earthquakes will be shown more distinctly. After drawing the components of the magnetic field and removing the daily changes from each of the components, we can observe the anomalies related to the earthquakes to justify the observed anomalies better and considering the standard deviation for each component, pre-seismic anomalies have a more significant distinction than the original data for being studied as a seismic precursor. After all, further investigation revealed the presence of a magnetic storm during the time period under investigation. This led to uncertainty in the feasibility of using the geomagnetic data in the present study as a precursor. However, several other pieces of evidence confirm the existence of precursory geomagnetic phenomena before earthquakes. Thus based on the current data and results, it is not possible to conclude the applicability of precursory geomagnetic studies and further data and studies are required.

How to cite: Taherinia, H. and Pourbeyranvand, S.: Investigation of earthquake precursors using magnetometric stations in Japan, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-400, https://doi.org/10.5194/egusphere-egu22-400, 2022.

Reliable and direct geothermal heat flow (GHF) measurements in Africa are sparse. It is a challenging task to create a map that reflects the GHF and covers the African continent in in its entirety.

We approached this task by training a random forest regression algorithm. After carefully tuning the algorithm's hyperparameters, the trained model relates the GHF to various geophysical and geological covariates that are considered to be statistically significant for the GHF. The covariates are mainly global datasets and models like Moho depth, Curie depth, gravity anomalies. To improve the predictions, we included some regional datasets. The quality and reliability of the datasets are assessed before the algorithm is trained.

The model's performance is validated against Australia, which has a large database of GHF measurements. The predicted GHF map of Africa shows acceptable performance indicators and is consistent with existing recognized GHF maps of Africa.

How to cite: Al-Aghbary, M., Sobh, M., and Gerhards, C.: A first attempt at a continental scale geothermal heat flow model for Africa, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1545, https://doi.org/10.5194/egusphere-egu22-1545, 2022.

In this study, the effects of seasonal variation on the vertical position accuracy of GPS calculated by time series analysis of continuous GPS stations were investigated. Weather changes, water vapor in the atmosphere affect the position accuracy of GPS and cause fluctuations in GPS height values. It is also known that the height component has more air passage changes. Since it is easier to interpret the effects of the height component due to its topographic features and seasonal changes are more effective than the rest of the country, four continuous GPS stations, covering the 2014-2019 date range, from the Turkish National Permanent GNSS Network (TUSAGA-Aktif) were used in the East of Turkey were chosen. The daily coordinates of the stations were obtained as a result of GAMIT/GLOBK software solution. By applying time series analysis to the daily coordinate values of the stations, statistically significant trend, periodic and stochastic components of the stations were determined. As a result of the analysis, the vertical annual velocities of the stations and the standard deviations of the velocities were determined.

For the stations determined according to the ellipsoid heights, the velocity and standard deviation values of the height component were calculated for each month, season and year. As the ellipsoid height increases, the velocity and its standard deviation values decrease. While the minimum velocity values are observed for the station with the lowest ellipsoidal height in winter, for the station with the highest ellipsoidal height in autumn, the minimum their standard deviation values are determined in winter for the station with the lowest ellipsoidal height, and in summer for the station with the highest ellipsoidal height. According to the results obtained, the coordinate displacements caused by seasonal variation may be important and their effects should be considered especially in high precision geodetic surveys.

In addition, the velocity values of the stations were calculated for different years, and a decrease was observed in the height component depending on the observation duration. As the observation duration for the height component increases, both the velocity values and their standard deviation values decrease. In order to avoid velocity estimation error completely, the data length should be more than 4.5 years.

Keywords: GPS height compenent, GPS time series, Seasonal effect, Velocity estimation

How to cite: Tekin Ünlütürk, N. and Doğan, U.: The Effects of Seasonal Variation on GPS Height Component, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1590, https://doi.org/10.5194/egusphere-egu22-1590, 2022.

Water mass changes at and below the surface of the Earth cause changes in the Earth’s gravity field which can be observed by at least three geodetic observation techniques: ground-based point measurements using terrestrial gravimeters, space-borne gravimetric satellite missions (GRACE and GRACE-FO) and geometrical deformations of the Earth’s crust observed by GNSS. Combining these techniques promises the opportunity to compute the most accurate (regional) water mass change time series with the highest possible spatial and temporal resolution, which is the goal of a joint project with the interdisciplinary DFG Collaborative Research Centre (SFB 1464) "TerraQ – Relativistic and Quantum-based Geodesy".

A method well suited for data combination of time-variable quantities is the Kalman filter algorithm, which sequentially updates water storage changes by combining a prediction step with observations from the next time step. As opposed to the standard way of describing gravity field variations by global spherical harmonics, we will introduce space-localizing radial basis functions as a more suitable parameterization of high-resolution regional water storage change. A closed-loop simulation environment has been set up to allow the testing of the setup and the tuning of the algorithm. In a first step only simulated GRACE data together with realistic correlated observation errors will be used in the Kalman filter to sequentially update the parameters of a regional gravity field model. However, the implementation was designed to flexibly include further observation techniques (GNSS, terrestrial gravimetry) at a later stage. This presentation will outline the Kalman filter framework, introduce the regional parameterization approach, and address challenges related to, e.g., ill-conditioned matrices and the proper choice of the radial basis function parameterization.

How to cite: Wöhnke, V., Eicker, A., Jensen, L., and Weigelt, M.: Regional modeling of water storage variations in a Kalman filter framework, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2447, https://doi.org/10.5194/egusphere-egu22-2447, 2022.

The approximation of the gravitational potential is still of interest in geodesy as it is utilized, e.g., for the mass transport of the Earth. The Inverse Problem Matching Pursuits (IPMPs) were proposed as alternative solvers for these kind of problems. They were successfully tested on diverse applications, including the downward continuation of the gravitational potential.

It is well-known that, for such linear inverse problems on the sphere, there exist a variety of global as well as local basis systems, e.g. spherical harmonics, Slepian functions as well as radial basis functions and wavelets. Each type has its specific pros and cons. Nonetheless, approximations are often represented in only one of them. On the contrary, the IPMPs enable an approximation as a mixture of diverse trial functions. They are chosen iteratively from an intentionally overcomplete dictionary such that the Tikhonov functional is reduced. However, an a-priori defined, finite dictionary has its own drawbacks, in particular with respect to efficiency.

Thus, we developed a learning add-on which uses an infinite dictionary instead while simultaneously reducing the computational cost. The add-on is implemented as constrained non-linear optimization problems with respect to the characteristic parameters of the different basis systems. In this talk, we give details on the matching pursuits and, in particular, the learning add-on and show recent numerical results with respect to the downward continuation of the gravitational potential.

How to cite: Schneider, N. and Michel, V.: Experimenting with automatized numerical methods, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2963, https://doi.org/10.5194/egusphere-egu22-2963, 2022.

The solid Earth’s deformation response to surface loading by ocean tides depends on the material properties of Earth’s interior. Comparisons of observed and predicted oceanic load tides can therefore shed new light on the structure of the crust and mantle. Recent advances in satellite geodesy, including altimetry and Global Navigation Satellite Systems (GNSS), have improved the accuracy and spatial resolution of ocean-tide models as well as the ability to measure precisely three-dimensional surface displacements caused by ocean tidal loading. Here, we investigate oceanic load tides in the western United States using measurements of surface displacement made by a dense array of GNSS stations in the Network of the Americas (NOTA). Dominant tidal harmonics from three frequency bands are considered (M₂, O₁, M_f). We compare the empirical load-tide estimates with predictions of surface displacements made by the LoadDef software package (Martens et al., 2019), with the goal of refining models for Earth’s (an)elastic and density structure through the crust and upper mantle of the western US.

How to cite: Martens, H., Simons, M., Rivera, L., van Driel, M., and Boehm, C.: Oceanic load tides in the western United States, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3240, https://doi.org/10.5194/egusphere-egu22-3240, 2022.

Understanding and modelling the properties of the stochastic variability -- often referred to as noise -- in geodetic time series is crucial to obtain realistic uncertainties for deterministic parameters, e.g., long-term velocities, and helpful in characterizing non-modelled processes. With the ever-increasing span of geodetic time series, it is expected that additional observations would help better understanding the low-frequency properties of the stochastic variability. In the meantime, recent studies evidenced that the choice of the functional model for the time series may bias the assessment of these low-frequency stochastic properties. In particular, the presence of frequent offsets, or step discontinuities, in position time series tends to systematically flatten the periodogram of position residuals at low frequencies and prevents the detection of possible random-walk-type variability.

In this study, we investigate the ability of frequently-used statistical tools, namely the Lomb-Scargle periodogram and Maximum Likelihood Estimation (MLE) method, to correctly retrieve low-frequency stochastic properties of geodetic time series in the presence of frequent offsets. By evaluating the biases of each method for several functional models, we demonstrate that neither of these tools is reliable for low-frequency investigation. By assessing alternative approaches, we show that using  Least-Squares Harmonic Estimation and Restricted Maximum Likelihood Estimation (RMLE) solves part of the problems reported by previous works. However, we evidence that, even when using those optimal methods, the presence of frequent offsets inevitably blurs the estimated low-frequency properties of geodetic time series by increasing low-frequency stochastic parameter uncertainties more than that of other stochastic parameters.

How to cite: Gobron, K., Rebischung, P., de Viron, O., Demoulin, A., and Van Camp, M.: Impact of Offsets on Assessing the Low-Frequency Stochastic Properties of Geodetic Time Series, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3605, https://doi.org/10.5194/egusphere-egu22-3605, 2022.

The modelling of the stochastic noise properties of GNSS daily coordinate time series allows to associate realistic uncertainties with the estimated geophysical parameters (e.g. tectonic rate, seasonal signal). Up to now, geodetic software based on Maximum Likelihood Estimation (MLE) jointly inverse a functional (i.e. geophysical parameters) and stochastic noise models. This method suffers from a computational time exponentially increasing  with the length of the GNSS time series, which becomes an issue when considering that the first permanent stations were installed in the late 80’s – early 90’s having recorded more than 25 years of geodetic data. Combining this issue with the tremendous number of permanent stations blanketing the world (i.e. more than 20,000 stations), the processing time in the analysis of large GNSS network is a key parameter. 

Here, we propose an alternative to the MLE called the Generalized Method of Wavelet Moments (GMWM). This method is based on the wavelet variance, i.e. a decomposition of the time series using the Haar wavelet. We show the first results and compare them with the MLE in terms of computational efficiency and absolute error on the estimated parameters. The versatility of this new method is its flexibility of choosing various stochastic noise models (e.g., Matérn, power law, flicker, white noise, random walk), and its robustness against outliers. Additional developments to account for deterministic components such as seasonal signal, offsets or post-seismic relaxation is easy. We explain the principle beyond the method and apply it to both simulated and real GNSS coordinate time series. Our first results are compared with the estimation using  the Hector software.

How to cite: kermarrec, G., cucci, D., montillet, J., and guerrier, S.: Application of the Generalized Method of Wavelet Moments to the analysis of daily position GNSS time series., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3766, https://doi.org/10.5194/egusphere-egu22-3766, 2022.

Considering that the precise orbit and clock products provided by international GNSS service (IGS) were of a magnitude different from those required by the global geodetic observing system (GGOS) in accuracy of 1 mm, the Lomb-Scargle periodogram was used to analyze the systematic deviation and the periodical deviation between the precise products of GNSS analysis centers (ACs) and the IGS final precision products. On this basis, a deviation correction model was established based on the least square method for the correction of precision parameters. The deviation correction results show that the standard deviation of the precise clock decreases by 15.4% on average, the standard deviation of the radial orbit decreases by 33.3% on average, and the standard deviation of the ensemble effects of radial orbit and clock decreases by 24.0% on average. The signal-in-space user ranging error (SISURE) also significantly decreases from the level of centimeters to millimeters. The positioning verification results of the 15 stations show that the consistency between the positioning results of the precision products using single AC and the positioning results of IGS final precision products is also improved after deviation correction, and the average improvement ratio of three ACs is 14.3%. It is proved that the deviation correction model can effectively improve the consistency between the precision products of ACs and the final products of IGS.

How to cite: Hou, Y., Chen, J., and Zhang, Y.: Characteristics analysis and correction of GPS precise products in analysis centers based on Lomb-Scargle periodogram, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6864, https://doi.org/10.5194/egusphere-egu22-6864, 2022.

The determination of GPS velocity accuracy and velocity uncertainty has been one of the topics of interest to researchers in recent years. Velocity and velocity uncertainty from continuous GPS data have been studied as deeply as possible, but velocity and velocity uncertainty from campaign measurements are still the subject of ongoing research. Recent studies have shown that the positioning accuracy of GPS PPP is latitude-dependent. At the same time, the velocity and velocity uncertainty produced by the PPP should also be treated in the same way. In this sense, it is necessary to make a global assessment. NASA JPL offers researchers a rich global database constituting GNSS time series analysis results across the globe. In this study, an experiment is conducted to determine the velocity quality of GPS campaign measurements from around 30 globally distributed stations of the IGS network. This time, our motivation is to determine the accuracy and uncertainty of GPS campaign rates from at least 4 years of data, which are performed annually on the same date. As in our previous study, we decimated coordinate components from the NASA JPL time series to generate GPS campaigns. In other words, we use 24-hour data for annual campaign measurements and repeat campaigns on three consecutive days each year. The deformation rates from NASA JPL were considered real and the accuracy of the deformation rates produced by our experiments was evaluated. Preliminary findings suggest that velocity deviations from the truth may be more severe, at 4 mm/year horizontally and 10 mm/year vertically. In the presentation, we discuss the ground truths that lead to this bias and the global distribution of velocity accuracy and velocity uncertainty.

How to cite: Sanli, D. U., Uysal, E., Oz Demir, D., and Duman, H.: Accuracy of velocities from annually repeated GPS campaigns, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8369, https://doi.org/10.5194/egusphere-egu22-8369, 2022.

We establish a theoretical framework, an algorithmic basis, and a computational workflow for the statistical analysis of multi-variate multi-dimensional random fields - sampled (possibly irregularly, with missing data) and finite (possibly bounded irregularly). Our research is practically motivated by geodetic and scientific problems of topography and gravity analysis in geophysics and planetary physics, but our solutions fulfill the more general need for sophisticated methods of inference that can be applied to massive remote-sensing data sets, and as such, our mathematical, statistical, and computational solutions transcend any particular application. The generic problem that we are addressing is: two (or more) spatial fields are observed, e.g., by passive or active sensing, and we desire a parsimonious statistical description of them, individually and in their relation to one another. We consider the fields to be realizations of a random process, parameterized as a Matern covariance structure, a very flexible description that includes, as special cases, many of the known models in popular use (e.g. exponential, autoregressive, von Karman, Gaussian, Whittle, ...) Our fundamental question is how to find estimates of the parameters of a Matern process, and the distribution of those estimates for uncertainty quantification. Our answer is, fundamentally: via maximum-likelihood estimation.  We now provide a computationally and statistically efficient method for estimating the parameters of a stochastic covariance model observed on a regular spatial grid in any number of dimensions. Our proposed method, which we call the Debiased Spatial Whittle likelihood, makes important corrections to the well-known Whittle likelihood to account for large sources of bias caused by boundary effects and aliasing. We generalise the approach to flexibly allow for significant volumes of missing data including those with lower-dimensional substructure, and for irregular sampling boundaries. We build a theoretical framework under relatively weak assumptions which ensures consistency and asymptotic normality in numerous practical settings including missing data and non-Gaussian processes. We also extend our consistency results to multivariate processes. We provide detailed implementation guidelines which ensure the estimation procedure can still be conducted in O(n log n) operations, where n is the number of points of the encapsulating rectangular grid, thus keeping the computational scalability of Fourier and Whittle-based methods for large data sets. We validate our procedure over a range of simulated and real world settings, and compare with state-of-the-art alternatives, demonstrating the enduring practical appeal of Fourier-based methods, provided they are corrected and augmented by the procedures that we developed.

How to cite: Simons, F. J., Guillaumin, A. P., Sykulski, A. M., and Olhede, S. C.: Efficient Parameter Estimation of Sampled Random Fields Using the Debiased Spatial Whittle Likelihood, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10879, https://doi.org/10.5194/egusphere-egu22-10879, 2022.

Global Navigation Satellite Systems (GNSS) can be operated 24 hours in all weather conditions; thus, it is widely preferred in many geodetic studies. With GNSS, position information can be obtained with high accuracy. However, in order to achieve precise position, GNSS error sources such as atmospheric effects should be eliminated. Since ionospheric delay depends on the frequency of the transmitted signal, it can be eliminated with dual-frequency receivers. But, the tropospheric delay does not depend on the signal frequency. Therefore, it can not be eliminated by signal combinations. The effect of tropospheric delay depends on various factors such as station’s altitude, signal direction, cut off angle, atmospheric pressure, temperature and relative humidity. Although tropospheric delays occur along the signal path, these delays are estimated in zenith direction. Tropospheric mapping functions (MFs) are used to project slant to zenith delay. In this study, the effects of most preferred MFs in the literature, which are Global Mapping Function (GMF), Niell Mapping Function (NMF) and Vienna Mapping Function 1 (VMF1), on position accuracy was investigated. For this aim, three networks with different baseline lengths, (1) less than 100 km, (2) between 100 km and 500 km and (3) more than 500 km, were designed including 10 stations. In addition, to examine the seasonal effect of the MFs, four month dataset (January – April – July – October) were selected. These dataset were processed with the Bernese software implementing relative point positioning method by fixing 3 stations. Moreover, the dataset were subdivided into different session durations (2-3-4-6-8-12 and 24 hours) and the effect of session duration on position accuracy was analysed. According to the initial results, it can be concluded that the position accuracy on short session duration depends on the baseline length and more accurate results were obtained in the shortest network. In addition, more accurate results were obtained by VMF1 for the up component; however, for the horizontal components, there were no significant differences between the MFs.

Keywords: GPS, Accuracy, Troposphere, Mapping Functions, Bernese

How to cite: Sezer, G. and Erdogan, B.: Effects of different tropospheric mapping functions on GPS positioning, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-245, https://doi.org/10.5194/egusphere-egu22-245, 2022.

For highly precise and accurate positioning and navigation solutions with GNSS, it is mandatory to take all error sources – including phase center corrections (PCC) – adequately into account. These corrections are provided by different calibration facilities and are published in the official IGS antenna exchange format (ANTEX) file for several geodetic antennas.

Currently, the IGS antenna working group (AWG) is discussing which metrics should be used as a basis for accepting new calibration facilities as an official IGS calibration facility. To this end, requirements have to be set for comparing different sets of PCC for the same type of antenna.

Mostly, characteristic values of difference patterns (dPCC) are analysed, e.g. maximum deviations, RMS of dPCC, or percentage of dPCC values that are smaller than 1 mm. For users and station providers, however, it is most interesting to investigate the impact of dPCC on geodetic parameters, e.g. topocentric coordinate deviations and troposphere estimates. Since the impact is not only depending on the antenna in use and the station’s location but also on the applied processing strategies, a standardized comparison strategy is needed.

In this contribution, we present the impact of different PCC values on geodetic parameters using a standardized simulation approach. We show results for several globally distributed stations using different processing strategies and their respective impact on the geodetic parameters. This includes the application of different elevation cut-off angles, observation weightings w.r.t satellite coverages and elevation angles as well as use of different frequencies and linear combinations. The obtained results are analysed in detail, repeated behaviours are grouped and compared to widely used characteristic values of dPCC. Thus, an overall conclusion of the similarity of different PCC models can not only be drawn on the pattern level, but also their impact on geodetic parameters can be assessed.

How to cite: Kröger, J., Kersten, T., Breva, Y., Brekenkamp, M., and Schön, S.: Impact of Different Phase Center Correction Values on Geodetic Parameters: A Standardized Simulation Approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1146, https://doi.org/10.5194/egusphere-egu22-1146, 2022.

Global Navigation Satellite Systems (GNSS) are used for different geodetic applications such as monitoring deformations and determining plate velocities. Precise positions of stations are needed for such studies. GNSS error sources should be modelled or eliminated to achieve precise coordinates. Some error sources (e.g., receiver and satellite clock errors) can be eliminated by differencing techniques in relative point positioning. However, in precise point positioning (PPP) these errors should be modelled since the technique uses un-differenced and ionosphere-free combinations. Tropospheric signal delay, one of the atmospheric error sources of GNSS, does not depend on the signal frequency; hence, it should be modelled. This delay is modelled in zenith direction, although it occurs along the signal path. This relation is provided with tropospheric mapping functions (MFs). In this study, the effects of MFs for different station heights and latitudes have been investigated. The datasets of 294 continuously operating reference stations were processed with Jet Propulsion Laboratory’s GipsyX v1.2 software. Moreover, the datasets were subdivided into non-overlapping periods between 2 and 24 h to examine the effects of MFs on different session durations.

Keywords: GPS, PPP, Troposphere, Mapping Functions, GipsyX v1.2

How to cite: Durmus, F. C., Dogan, A. H., and Erdogan, B.: Investigation of the effect of tropospheric mapping functions for different station heights and latitudes on PPP, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1304, https://doi.org/10.5194/egusphere-egu22-1304, 2022.

Global Navigation Satellite Systems (GNSSs) are widely used for Earth system monitoring, e.g., solid earth and atmosphere. However, the time series of station coordinates and zenith tropospheric delay derived using GNSS are inherently affected by several technique-specific errors that influence the interpretation of geophysical processes and phenomena. GPS plays a crucial role and is most often used in interdisciplinary studies. However, the multiplicity of navigation systems, including fully operational GLONASS and Galileo, allowed us to assess system-specific high-frequency signals and inconsistencies arising from using different constellations.

This work shows that using different GNSS constellations leads to the appearance of various artificial signals with amplitudes up to several millimeters in the series of station coordinates. The presence of the GNSS system-specific artifacts and inter-system disagreements are demonstrated using the 2-year long series of station coordinates and zenith total delay parameters for 15 stations using Precise Point Positioning algorithms. Finally, we assessed the benefit of using GPS, GLONASS, and Galileo jointly.

We identified the origin of the spurious signals in orbital errors. The most dominant orbital artifacts for Galileo appear with periods of 14.08 h, 17.09 h, 34.20 h, 2.49 d, ~3.4 d. The corresponding signals for GLONASS appear with periods of 5.63 h, 7.36 h, 10.64 h, 21.26 h, 3.99 d, and ~8 d. Moreover, when estimating discrete 24-hour solutions from high-rate GNSS data, high-frequency signatures are under-sampled, resulting in long-term aliased periodic signals. The GPS orbital signals arise at the periods corresponding to the harmonics of the K₁ tide, which leads to the inconsistency of the GPS-based products with ocean tidal loading models reaching on average 12 mm for the K₂ tidal term in the Up component. The magnitude of the orbital signals varies between different site locations and depends on the GNSS observation geometry and dominant direction of satellites' flybys. For example, because of the high inclination of the GLONASS orbital planes, the stations located in absolute low latitudes observe mostly North-South satellite flybys; thus, the estimated East component of the coordinates is exposed to the orbital artifacts.

Galileo is less vulnerable to the orbital signals than GPS or GLONASS. The difference is visible mainly for the East coordinate component. The Galileo-based daily estimates are up to 55% and 36% better than those delivered from GLONASS and GPS. Finally, using a combination of GPS and Galileo increases the precision of estimates by 10% compared with the best-case Galileo-only solution and remarkably reduces the system-specific errors in station coordinate time series.

How to cite: Zajdel, R., Kazmierski, K., and Sośnica, K.: Inconsistency in Precise Point Positioning products from GPS, GLONASS and Galileo, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2327, https://doi.org/10.5194/egusphere-egu22-2327, 2022.

Although the full operational capability of the Galileo system has not been officially announced as yet, the European GNSS, Galileo, has already remarkably contributed to geodesy, positioning, navigation, timing, and fundamental physics. Galileo metadata with the details on the satellite construction and surface properties allow for the development of the high-accuracy satellite macro-models and precise orbit determination. Two integrated onboard observation techniques – satellite laser ranging (SLR) and microwave GNSS – allow for the integration of space geodetic techniques and co-location in space. Calibrated satellite and receiver antenna offsets allow for scale realization and scale transfer for the reference frames.

GNSS orbits of superior quality constitute the basis for other geodetic products, such as Earth rotation parameters, station coordinates, geocenter motion, international terrestrial reference frames, tropospheric and ionospheric delays. Moreover, the high-quality orbits and clocks installed on a pair of Galileo satellites launched onto eccentric orbits allow for studying effects emerging from general relativity, both related to the time redshift, as well as to orbital Schwarzschild, Lense-Thirring, and de Sitter effects constituting the essential issues of fundamental physics. Finally, high-quality and frequently-updated broadcast orbits together with very stable clocks onboard Galileo assure the superior accuracy of the real-time positioning when compared to other GNSS.

We discuss the advantages and limitations of the Galileo system in terms of its applicability to geodesy, concentrating on daily and sub-daily Earth rotation parameters – polar motion and length-of-day variability, station coordinates, and geocenter motion. We address the system-specific errors discovered in GPS, GLONASS, and Galileo time series due to different satellite revolution periods, aliasing effects, tidal constituents, and orbit modeling issues. Some orbit modeling issues related, e.g., to thermal effects, remain unresolved, however, their impact may be mitigated by estimating empirical parameters and the combination of laser and microwave observations. The co-location in space onboard Galileo paves new opportunities for the realization of the reference frames tied in space, onboard GNSS satellites. We provide results on the recent developments of precise orbit determination and co-location in space based on integrated SLR and GNSS observations. Eventually, we discuss the latest applications of high-accurate orbits of Galileo satellites in near-circular and eccentric orbits toward the verification of the effects emerging from general relativity.

How to cite: Sośnica, K., Zajdel, R., Bury, G., Kazmierski, K., Hadaś, T., Mikoś, M., Lackowski, M., and Strugarek, D.: Contribution of the Galileo system to space geodesy and fundamental physics, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2477, https://doi.org/10.5194/egusphere-egu22-2477, 2022.

The global data coverage of the Global Navigation Satellite Systems (GNSS) provides a fundamental and unique dataset for a wide range of applications, such as crustal deformation, topographic measurements, or near surface processes studies. However, a strong limitation is represented by the high costs of the GNSS receivers and the supporting software, which make them available only by the scientific communities capable of affording them. The GNSS technology has been continuously and rapidly growing and, in recent years, new cost-efficient (low-cost) instruments have entered the mass market, gaining the attention of the scientific community for potentially being high-performing alternative solutions. In this study, we matched in parallel a dual-frequency cost-effective receiver (u-blox ZED F9P) and two high-cost receivers, all connected to the same geodetic-class antenna. We tested the system by processing the data together with the observations coming from a network of GNSS permanent stations operating in North-East Italy. We compare the time-series obtained using cost-effective geodetic equipment with those obtained using geodetic-class instruments. We show that mm-order precision can be achieved by cost-effective GNSS receivers, while the results in terms of time series are largely comparable to those obtained using high-price geodetic receivers.

How to cite: Tunini, L., Zuliani, D., and Magrin, A.: Cost-effective GNSS sensors applied for crustal deformation purposes: insights from an experiment in NE-Italy, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2512, https://doi.org/10.5194/egusphere-egu22-2512, 2022.

Global navigation satellite systems (GNSS) are integral to a wide array of scientific and commercial applications. Precise orbit determination of satellites in low Earth orbit relies on high-quality GNSS products. Examples of such satellites are those of the Copernicus Earth observation program of the European Union or the satellite gravimetry missions GRACE/GRACE-FO and GOCE. Numerous ground-based applications also require these products, for example: estimation of terrestrial water storage variations, earthquake monitoring, GNSS reflectometry, tropospheric and ionospheric research, surveying, or civil engineering. Furthermore, GNSS-derived station coordinates play an important role in the determination of the International Terrestrial Reference Frame. The analysis centres of the International GNSS Service (IGS) generate such products by processing observations from a global network of ground stations to one or more GNSS constellations.

So far, this kind of processing only incorporates elevation-dependent a priori modelling of observation variances and disregards temporal correlations. Meanwhile, numerous studies have shown the positive impact the incorporation of sophisticated stochastic modelling has on GNSS processing and resulting products. However, there have not been any large-scale investigations regarding the impact of stochastic modelling of observation noise on global GNSS processing.

In this contribution, we discuss a post-fit residuals approach for deriving temporal correlations in global multi-GNSS processing and their limitations. We used several years of observations and a selected IGS network of ground stations. Based on this data we analysed the post-fit residuals and the derived temporal correlations per station with respect to their seasonal effects, specific used receivers, antennas, and different transmitter signal types.

How to cite: Dumitraschkewitz, P., Mayer-Gürr, T., and Strasser, S.: Empirical stochastic modeling of observation noise in global GNSS network processing, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2566, https://doi.org/10.5194/egusphere-egu22-2566, 2022.

The polar ionosphere is characterized by massive structures, known as patches, resulting from intake of mid-latitude plasma or, to a lesser extent, from particle precipitation. The occurrence of patches is an object of multi-instrumental investigations performed with various space- and ground-based techniques, involving among others the measurements of Global Navigation Satellite Systems. With regard to the latter approach, the patch definition has to be reformulated to the electron density accumulated along a signal path. This step requires an additional validation of the relation between an elevation angle of GNSS measurements and an integrated enhancement of plasma.

The work compares polar patch signatures observed in GNSS time series during a maximum solar activity. The assessment of integrated patch enhancement was realized with relative STEC values that are computed for several GNSS stations located in the northern polar cap. Investigating the results at different elevation angles, one can observe a lack of typical geometrical dependency of relative STEC. We believe this effect is related to an approximately spherical shape of patches. Such a conclusion seems to be confirmed by a similar enhancement observed for measurements with different orientations. According to the obtained results, we find this is justified to use STEC as an indicator of patch enhancement for GNSS data.    

How to cite: Sieradzki, R.: A study on the relation between an elevation angle of GNSS measurements and an integrated plasma enhancement of polar patches., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3870, https://doi.org/10.5194/egusphere-egu22-3870, 2022.

How to cite: Steigenberger, P., Hauschild, A., and Montenbruck, O.: Orbit, clock and attitude analysis of QZS-1R, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4504, https://doi.org/10.5194/egusphere-egu22-4504, 2022.

Ambiguity fixing on the geometry free combination presents some desirable characteristics. In particular, it does not require precise ephemeris, modelling of station displacement motion or tropospheric modelling or estimation. For such reasons, it can be particularly interesting in the case where such data and models are not available or if simpler processing is wanted. Such fixing procedure has been studied in the past for dual-frequency and triple frequency cases. Unfortunately, especially in the two frequency case, this procedure is not practical due to the long observation period needed to reliable fix a correct integer set. In this contribution, we review the fixing performances of the “geometry free” model using an undifferenced uncombined approach. Furthermore, we present the case to four and five frequency cases using Galileo and Beidou observations showing that reliable fixing in a reduced time span is possible. All analyses presented are performed using real GNSS data from the IGS permanent network. Finally, some possible applications are presented with a focus on ionospheric studies.

How to cite: Tagliaferro, G.: Ambiguity fixing on geometry free like model using modernized GNSS signals, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4881, https://doi.org/10.5194/egusphere-egu22-4881, 2022.

The adverse effects of ionospheric delays limit the positioning accuracy of single-frequency GNSS users. To mitigate these effects, GNSS system providers make several ionospheric delays models available for their global users. For example, the GPS has offered the Klobuchar model from the beginning. More recently, Galileo users can use the NeQuick G model. In the meantime, several independent models available for real-time navigation have emerged. Recent examples are the NTCM (Neustrelitz Total Electron Content Model) correction model provided by the German Aerospace Center (DLR) and real-time global ionosphere maps (RT-GIMs) provided by the National Centre for Space Studies (CNES).

In this contribution, we evaluate the performance of several global ionospheric delay correction models in SPP mode. We used single-frequency pseudorange data from 12 GNSS stations distributed globally, covering different latitudes for the evaluation. The test data includes GNSS observations from DOY 93/2020 to DOY 80/2021, covering almost one full year of increasing solar activity. We validated the performance of the NTCM-G model driven by the Galileo Az parameters against the Klobuchar, NeQuick 2, NeQuick G, and CNES RT GIMs models. Finally, we compared the results to reference solutions obtained with CODE GIM and also using the ionosphere-free linear combination. We showed that NTCM-G corrections presented accuracy comparable with the NeQuick G model and better than the Klobuchar one.

How to cite: Milanowska, B., Wielgosz, P., Hoque, M., Tomaszewski, D., Jarmołowski, W., Krypiak-Gregorczyk, A., Krzykowska-Piotrowska, K., and Rapiński, J.: Evaluation of NTCM-G ionospheric delay correction model for single-frequency SPP users., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5477, https://doi.org/10.5194/egusphere-egu22-5477, 2022.

    Global Navigation Satellite System (GNSS) is a well-recognized observation technique in studies on the ionosphere due to its sensitivity to the total electron content (TEC). The era of modern smartphones, running on Android version 7.0 and higher, facilitates the acquisition of raw dual-frequency GNSS measurements, paving the way for the GNSS community data to be potentially exploited in geoscience applications. One can assume that the continuous progress in this domain may result in future in a performance of those smart devices reaching the level of GNSS receivers (and antennas) used for atmospheric monitoring. The prospective utilization of a very large number of GNSS-capable smartphones, as a dynamic crowdsourcing receiver network, could form thus an attractive source of complementary GNSS data, allowing to significantly increase the spatial resolution of observations available for the analysis and cover areas of the globe where GNSS receivers are not yet present. The enormous volume of prospective GNSS community data brings, however, major challenges related to data acquisition, its storage, and subsequent processing for deriving various parameters of interest, also in near-real time. The same applies to the analysis of such huge and heterogeneous data sets, requiring a dedicated approach in order to exploit the data in a thorough manner and fully benefit from such a concept.
Application of Machine Learning Technology for GNSS IoT data fusion (CAMALIOT) is an ongoing ESA NAVISP project with activities covering acquisition of GNSS observations from modern smartphones and development of the dedicated infrastructure regarding GNSS processing and machine learning at scale. An Android application, developed within that project, is utilized to retrieve code and phase observations from the modern generation of smartphones. The acquired user-specific data is available to the user in the form of RINEX3-compliant files and can be uploaded by the user to the central server for subsequent processing.
This contribution highlights the CAMALIOT project in relation to the ionosphere and provides information on the developed Android application, data ingestion and processing, complemented with methodology and initial results related to the TEC retrieval based on smartphone data collected in the vicinity of geodetic GNSS receivers, with the latter used for deriving reference time series. Concerning the smartphone data, the amount and quality of observations are much lower compared to the high-grade GNSS equipment and a dedicated pre-processing stage is needed in order to discard bad observations in a proper manner. An apparent correlation between the data quality, utilized frequency bands and satellite constellation involved is visible too. This area of GNSS still suffers from the limitations related mainly to the components comprising the smartphone, resulting in the lower quality of the acquired GNSS observations, compared to those obtained with the use of high-grade GNSS receivers and antennas. This translates to a greater susceptibility to multipath as well as a much more frequent occurrence of observation gaps and cycle slips, affecting the data availability and continuity of the carrier-phase measurements.

How to cite: Kłopotek, G., Soja, B., Awadaljeed, M., Crocetti, L., Rothacher, M., See, L., Weinacker, R., Sturn, T., McCallum, I., and Navarro, V.: Total Electron Content Monitoring Complemented with Crowdsourced GNSS Observations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5780, https://doi.org/10.5194/egusphere-egu22-5780, 2022.

Ionospheric irregularities impair GNSS signals and, in turn, affect the performance of GNSS positioning. Such effects are especially evident for the high latitudes, which are currently gaining the attention of research and industry branches. These activities should be supported with reliable positioning and navigation services. Such needs motivate us to assess, for the first time, the impact of ionospheric irregularities on GNSS positioning performance in Greenland. We fill the gap and evaluate the performance of positioning methods that were not investigated comprehensively until now but meet the demands of a wide range of users. In this regard, we address the needs of mass-market users that most frequently employ single-frequency receivers and expect a meter to submeter-level accuracy in an absolute mode; and the users who require the highest precision solution based on geodetic-grade dual-frequency receivers. We take advantage of the datasets collected at the GNET permanent network in Greenland during three ionospheric storms, namely the St. Patrick storm of March 17, 2015, June 22, 2015, and August 25–­26, 2018. We discover a significant impact of the ionospheric disturbances on the ambiguity resolution performance and the accuracy of the float solution in RTK positioning. Next, assessing the single-frequency ionospheric-free PPP, we demonstrate that the model is generally unaffected by the ionospheric disturbances. Hence, the model is predestined for the application by the users of single-frequency receivers in the areas of frequent ionospheric disturbances. Finally, based on the observation analyses, we revealed that phase signals on the L2 frequency band are more prone to the cycle slips induced by ionospheric irregularities than those transmitted on the first one.

How to cite: Paziewski, J., Jin, Y., Miloch, W. J., Sieradzki, R., Jarmolowski, W., Hernandez-Pajares, M., Wielgosz, P., Berdermann, J., Hoque, M., Høeg, P., Garcıa-Rigo, A., Lyu, H., Milanowska, B., Clausen, L. B. N., Monte-Moreno, E., and Orús-Pérez, R.: On the implications of ionospheric disturbances for GNSS precise positioning: a case study of Greenland, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7150, https://doi.org/10.5194/egusphere-egu22-7150, 2022.

At present, significant development of the positioning methods using the Global Navigation Satellite System (GNSS) can be seen. One of the most developed methods is the absolute Precise Point Positioning (PPP) method. This can be particularly seen using multi-GNSS measurements. The development of multi-GNSS increases the number of satellites observed and increases the accuracy of the products, but also creates new requirements for observation modeling. Obtaining the correct values, ​​of the estimated parameters, requires the appropriate determination of the deterministic model as well as the stochastic model. Currently, the deterministic model is well known. In contrast, the stochastic model is not fully known and still requires a number of studies. Stochastic modeling is based on determining the covariance matrix and which can be modeled using a weighting function that takes into account the elevation angle of the observed satellite. ​

In our analysis, we focus on studies on the weighting functions of GNSS observations for the PPP method. Analysis was performed on the Multi-GNSS Pilot Project (MGEX) stations which were characterized by global distribution and various equipment in 2021. Studies were conducted for the GPS‑only, Galileo-only, and GPS+Galileo constellations, with particular emphasis on the Galileo observations, which has achieved significant progress in recent years. Eight different observation weighting models have been selected for analysis: one of them assumes that all observations have the same precision, without dependence on the elevation angle; for the other used functions, the observation precision value depends on the elevation angle. Parameters such as accuracy, convergence time, zenith path delay (ZPD), and inter-system bias (ISB) are analyzed.

Based on the tests performed, we show that, depending on the solutions adopted (i.e. GPS-only, Galileo-only, GPS+Galileo), the best results were obtained for different weighting functions. We have shown that using different weighting functions have no impact on the horizontal component but a visible impact on the vertical component,  the tropospheric delay, and the convergence time. Also, we choose the best functions for GPS-only and Galileo-only and used them for the GPS+Galileo solution. For this new approach obtained a shorter convergence time and higher accuracy of the ZPD. More information and results will be presented at the conference.

How to cite: Kiliszek, D., Araszkiewicz, A., and Kroszczyński, K.: Analysis of different weighting functions of observations for GPS and Galileo PPP, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7489, https://doi.org/10.5194/egusphere-egu22-7489, 2022.

The aim of the study is to investigate the quality of the tropospheric estimates obtained with the use of the latest dual-frequency low-cost GNSS receivers. We aim to verify if the low-cost receivers may provide information on the parameters that describe the state of the troposphere with accuracy and reliability close to that of high-grade receivers. In this way, we address a scientific question on the potential usability of such receivers for climate applications. We investigate selected GNSS tropospheric estimates such as zenith tropospheric delays (ZTDs) and horizontal gradients. ZTD accuracy is validated in comparison to ERA5, which is the fifth generation reanalysis for the global climate and weather produced by European Centre for Medium-Range Weather Forecasts (ECMWF).

The experiment is based on GNSS data collected during two measurement campaigns. The 1^st campaign was carried out over three days in the winter 2020; the 2^nd one was held over three days in the summer 2021. Three collocated stations equipped with u-blox ZED F9P receivers and one station with a high-grade Trimble Alloy receiver were used. Receivers were connected to two different types of GNSS antennas: a surveying-grade Leica AR10 and a patch ANN-MB antenna. Collected GNSS data were processed using Bernese GNSS Software v.5.2 in Precise Point Positioning (PPP) mode based on dual-frequency ionosphere-free model.

The presented results confirm that the tropospheric solutions based on low-cost receivers data can achieve high accuracy. Low-cost equipment provides tropospheric parameters with precision and reliability only slightly lower than that of high-grade one. We also show that an application of a surveying-grade antenna to a low-cost receiver may noticeably enhance the accuracy of the tropospheric estimates derived with such receivers. Finally, validation against the ERA5 climate reanalysis confirms that both sets can provide high-quality, accurate tropospheric estimates, which can be further used in climate applications.

How to cite: Stępniak, K. and Paziewski, J.: Validation of low-cost receiver derived tropospheric products against ERA5 reanalysis, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7899, https://doi.org/10.5194/egusphere-egu22-7899, 2022.

The European Plate Observing System (EPOS) is a very large and complex European e-infrastructure that provides pre-operational access to a first set of datasets and services for Solid Earth research. The EPOS-GNSS Data Gateway provides, through an Application Program Interface (API) and a web portal, access to GNSS (Global Navigation Satellite Systems) RINEX data from a distributed infrastructure of data nodes. Currently, ten EPOS-GNSS nodes have been installed, and three of them are still in the pre-operational phase. To monitor the long-term data quality of EPOS-GNSS stations at the nodes level, ROB is developing a new service. The first step of this service is a web portal (www.gnssquality-epos.oma.be) that provides access to data quality metrics of the RINEX data available from the different EPOS-GNSS nodes.

The web portal presents plots of the long-term tracking performance of more than 1000 EPOS-GNSS stations. The plots focus on several data quality metrics such as the number of observed versus expected observations, the number of missing epochs, the number of observed satellites, the number of cycle slips, and multipath values on code observations. These metrics have been computed at the node level using GLASS and Anubis Software (https://gnutsoftware.com/software/anubis). The metrics provide helpful information for node managers or station users to assess the EPOS-GNSS station’s performance and detect potential degradation of the RINEX data quality. The outlook of this work is to investigate the possible usage of data quality metrics to detect data unsuitable for high-precision GNSS analysis for geophysical or meteorological applications. Here, we will present the newly developed web portal, the considered data quality metrics, and some preliminary results of this ongoing work.

How to cite: Bamahry, F., Legrand, J., Bruyninx, C., and Fabian, A.: First experience with GNSS data quality monitoring in the distributed EPOS e-infrastructure, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7927, https://doi.org/10.5194/egusphere-egu22-7927, 2022.

With the introduction of the operating system Android 7 Nougat in the year 2016, it became possible to access the GNSS code and carrier phase observations on Android smartphones. These observations can now be processed with state-of-the-art GNSS processing software, which allows an in-depth evaluation of the smartphone`s GNSS performance. The availability of the carrier phase observations is an important step towards sub-decimeter-level positioning. Since a few years, there are also smartphones on the market that are equipped with dual-frequency GNSS chipsets.

In this presentation, the capability of dual-frequency GNSS smartphones for the estimation of tropospheric delays is investigated. Static measurements over several weeks are performed using a Google Pixel 4 XL smartphone. The measurements are processed using relative positioning methods in a real-time mode, where a Continuously Operating Reference Station (CORS) acts as a base. The estimated differential tropospheric parameters – derived for short and medium baseline lengths – are then added to the absolute values computed at the reference station by Precise Point Positioning (PPP). Using this method, we demonstrate that the tropospheric zenith total delays can be successfully determined from smartphone observations. When comparing the estimated tropospheric delays with those determined at a nearby geodetic receiver, differences in the range of a few millimeters to centimeters are visible. In view of these accuracies, the suggested method shows the potential to resolve small-scale tropospheric structures and thus, can be an interesting data source for numerical weather prediction models or related GNSS crowdsourcing projects.

How to cite: Stauffer, R., Hohensinn, R., Herrera Pinzón, I. D., Möller, G., and Rothacher, M.: Tropospheric Parameter Estimation with Dual-Frequency GNSS Smartphones, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8242, https://doi.org/10.5194/egusphere-egu22-8242, 2022.

For a long time, the main factor affecting the accuracy of GPS PPP has been the observing session duration. Researchers have recently shown that the accuracy of PPP also varies with latitude. The reason for the latitudinal variation is the inability to determine the tropospheric zenith delay with a globally homogeneous precision and its impact on the position determination results. A formula has been developed to give the accuracy of the PPP position in a local geocentric system based on observation session duration and latitude. Currently, the interest of researchers is to determine the accuracy of Multi-GNSS solutions. In this context, the MGEX experiment of the IGS provides a rich data source to researchers. In this study, 15 globally distributed GNSS stations were selected from the MGEX network, GPS+GLONASS data was evaluated with CSRSPPP software, and the accuracy of the GNSS positioning was investigated. Continuous GNSS observations and 8-hour campaign measurements are evaluated comparatively. The results of the study showed that 60% of the RMS values obtained from the 24-hour data became smaller, indicating that it was equal between the horizontal and vertical coordinate components. The improvement in campaign solutions is better and around 80% overall. The share of this between horizontal position and vertical position is around 73% and 87%, respectively. The average improvement in the RMS of the coordinate components is around 0.5 mm for the campaign solutions, but the improvement can reach up to 2 mm at some stations. Our motivation was to determine whether this improvement was reflected in the accuracy modeling. Initial findings show that the results are in agreement with the latest accuracy modeling, and it turns out that the positioning accuracy of GNSS PPP also depends on the latitude of the GNSS site as well as the observation session, as in the GPS PPP.

How to cite: Cetin, D., Sanli, D. U., and Ogutcu, S.: Accuracy of GNSS positioning: GPS+GLONASS case, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8890, https://doi.org/10.5194/egusphere-egu22-8890, 2022.

In recent years, dual-frequency GNSS chipsets became available on the mass market. The ongoing developments in sensor and processing technologies steadily improve the positioning performance so that nowadays sub-decimeter accuracies can be achieved with such devices, even in real-time. Thus these sensors become a powerful, inexpensive choice for equipping or densifying existing GNSS monitoring networks. Station densification can be of significant added value for earthquake early warning systems, assimilation of GNSS water vapor estimates into numerical weather prediction models and the detection of severe weather events. Even if somewhat noisier, smartphone data can be used for GNSS-based remote sensing purposes as well.

This contribution is twofold, and focusses on both, the current capabilities and the perspectives of these GNSS low-cost technologies for such remote sensing applications. In the first part we highlight the accuracy of PPP-enabled seismic and tropospheric monitoring using low-cost loggers and stations developed in-house. We show that differential smartphone GNSS observations on short- and medium-length baselines can be used to sense the state of the regional troposphere. In the second part, we present first results on the performance of the u-blox D9S application board, which enables highest precision by PPP-RTK with ambiguity resolution, and the feasibility of high-precision positioning is assessed for long baselines involving smartphone data as well. Finally, we briefly discuss the potential of data-driven methods for mitigating multipath, which is still one of the main error sources when using equipment of low quality. Concerning the GNSS processing, we rely on further-developed versions of open-source and commercial GNSS software packages. Regarding sensor technology, u-blox chips -- which are currently deployed in our self-sufficient GNSS stations -- are used together with different low-cost and medium-grade GNSS antennas (both, patch and recent helical-type low-cost antennas).

We conclude that low-cost GNSS sensor technology is on the way to satisfy the same demands in accuracy as geodetic-grade equipment -- centimeter-level accuracy can be obtained, even in real-time. New possibilities for station densifications arise by employing low-cost, autonomous stations or by crowdsourcing of GNSS data with smartphones. These observations can aid in resolving small-scale structures in the atmosphere, or for a quick detection and localization of geohazards.

How to cite: Hohensinn, R., Stauffer, R., Herrera Pinzón, I. D., Möller, G., Aichinger-Rosenberger, M., Rossi, Y., Pan, Y., Kłopotek, G., Soja, B., and Rothacher, M.: Low-cost and smartphone GNSS sensors: current capabilities and perspectives for seismic and tropospheric monitoring applications, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9079, https://doi.org/10.5194/egusphere-egu22-9079, 2022.

It is difficult to imagine today's world without Global Navigation Satellite Systems (GNSS). The dynamic development of GNSS has contributed to the fact that current users are able to use four global systems that use more than 120 satellites. This progress was related not only to the space segment but also to the user segment. Modern technology and miniaturization have resulted in the users' disposal of different types of GNSS receivers, including geodetic receivers, gaining popularity low-cost receivers, or other devices using the GNSS signal, such as smartphones, sports trackers, or sports watches.

Modern sports watches are equipped with many sensors, among which GNSS chipsets play an important role. Those GNSS chipsets make it possible to determine the distance traveled and other related parameters that are important from the point of view of athletes. The most modern constructions can track several constellations at the same time. However, it is difficult to find reliable information to determine the actual quality of positioning by these low-cost GNSS receivers. Most of the works use comparative methods of watches and visual analysis of the route covered. Due to the above-mentioned gap in this area, the positioning quality of leading manufacturers of sports watches was assessed in this study.

Ten sports watches from Garmin, Polar, and Suunto were assessed in the study regarding the geodetic grade GNSS Trimble receiver. The watches were evaluated in three experiments: field positioning experiment, distance accuracy experiment conducted on the athletics track, and the accuracy of the altitude determination conducted on the 37 m high tower. The tests were performed for all the GNSS system options available in watches. The best positioning quality was obtained for the Polar M430 watch that uses only GPS for which almost all recorded epochs obtain positioning accuracy better than 5 m. When measuring distance, most watches had a result that was less than 1% from the theoretical value. Garmin Vivoactive 4s achieved the best results in height determination. For 11 different measured levels, located about 3 m apart, it obtained an average difference equal to 0.48 m. The results show also that the use of the additional GNSS system degrades the obtained results in some cases.

How to cite: Kazmierski, K., Mikos, M., and Wachulec, N.: Evaluation of positioning accuracy with the use of sports watches equipped with GNSS modules, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11197, https://doi.org/10.5194/egusphere-egu22-11197, 2022.

Large earthquakes strongly shake the upper atmosphere, leaving distinctive signatures in total electron content (TEC) measured using GNSS trans-ionospheric monitoring. The ionosphere is particularly sensitive to brutal uplift motions of the ground or sea surface, triggering upward propagating mechanical waves. In specific conditions that we will detail in this presentation, GNSS-TEC measurements contain critical information on the immediate consequences of an earthquake. If accurate and provided rapidly, independent knowledge of the sea surface deformation extent and distribution could feed tsunami early warning systems.

Radio waves emitted by GNSS satellites integrate the ionospheric electron density wavefield along their propagation path. At ground level, GNSS receivers can only sense the TEC, which contains the contribution of the ionospheric wavefronts. These wavefronts are destructively or constructively integrated, depending on the involved geometry of observation. In some conditions, even a close station will not sense the TEC perturbation, while a station located 200 km away will sense large TEC fluctuations. This complex behavior mainly depends on the line-of-sight 3D geometry crossing the electron density perturbation. To study how this geometry can affect the estimation of the generating motion, we first build TEC sensitivity maps and highlight more blind or sensitive zones at the Earth’s surface. We apply the procedure to past tsunamigenic earthquakes at mid and low latitudes. Those are the 2010 Mw 7.6 Mentawaii earthquake (Indonesia), the 2016 Mw 7.8 Kaikoura earthquake (New Zealand), and the 2010 Mw 8.8 Maule earthquake (Chile). The TEC sensitivity maps allow us to investigate how the reciprocal locations of the available GNSS stations and satellites can affect the localization of the origin of the ionospheric disturbances. In a second step, we build localization maps with a full waveform method (IonoSeis software) and, where possible, with a time delay fitting method. We compare the resulting maps with the Earth’s surface deformation distribution estimated by more conventional seismo-geodetic methods. We finally show how the extension and densification of GNSS networks with multi-GNSS low-cost receivers and enhanced ionosphere monitoring could help mitigate tsunamis better.

How to cite: Rolland, L., Munaibari, E., Zedek, F., Anthony, S., Mikesell, T. D., Pierdavide, C., and Bertrand, D.: Rapid characterization of tsunami sources with GNSS-TEC ionospheric monitoring, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11421, https://doi.org/10.5194/egusphere-egu22-11421, 2022.

The use of zero-difference processing schemes becomes more and more popular within the GNSS (Global Navigation Satellite Systems) community. This change from double- to zero-difference approaches increases the demand of PPP-AR (Ambiguity Resolution for Precise Point Positioning) enabling products. Those products can be created in two ways, either estimate the geometrical part (orbits) based on a double-difference global network solution with a separate zero-difference solution for the clocks and phase biases, or in a combined zero-difference solution. The latter one allows a more flexible approach; however, the challenge lies in the handling of the increased number of parameters and ambiguity resolution.

The estimation of combined orbit and clock zero-difference enabling products needs a thought-out design of the processing strategy, where the elimination and back-substitution steps are vital to deal with the large number of parameters. Nonetheless, the amount of ambiguity parameters dramatically grows with an increasing size of the network, posing some computational limitations, since they should not be eliminated for a successful ambiguity resolution. Such a restriction originates from fixing float orbits: their accuracy does not allow to estimate reliable ambiguity parameters. To cope with that, we propose a new algorithm capable to decouple them from the orbits, allowing to fix between-satellite ambiguities in a later station-wise parallelisation.

On the poster, we describe selected details on the ambiguity resolution strategy that we have developed. The obtained results are characterized and compared to other solutions using classical ambiguity resolution schemes.

How to cite: Calero Rodríguez, E. J., Villiger, A., Schaer, S., Dach, R., and Jäggi, A.: Combined orbit and clock zero-difference solution at CODE: ambiguity resolution strategy, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11628, https://doi.org/10.5194/egusphere-egu22-11628, 2022.

Climate change has led to an increase in the frequency and severity of weather events with intense precipitation and subsequently a greater susceptibility to flash flooding of cities worldwide. As a result, accurate fore- and now-casting of imminent extreme precipitation has become critical for the warning and mitigation of these hydro-meteorological hazards. Networks of ground-based Global Navigation Satellite System (GNSS) stations enable the measurement of integrated water vapour along slant pathways, providing three-dimensional (3D) water vapour distributions at low cost and in real-time. This makes these data a valuable complementary source of information for tracking storm events and predicting their paths. However, it is well established that multipath effects at GNSS stations do impact incoming signals, especially at low elevations. While the GNSS products for meteorology to date consist predominantly of estimates of zenith total delay and horizontal gradients, these products are not optimal for constraining the 3D distribution of water vapour above a station. The direct use of slant delays counteracts this lack of azimuthal information but is more susceptible to multipath errors at low elevations. This study investigates the impact of multipath-corrected slant wet delay (SWD) estimates on tracking extreme weather events using the convective storm event over Bulgaria, Greece and Turkey on July 27, 2017, which resulted in flash floods and significant property damage. First, we recovered the one-way SWD by adding GNSS post-fit phase residuals, representing the non-isotropic component of the SWD, i.e., the higher-order inhomogeneity. As the MP errors in the GNSS phase observables can significantly affect the SWD from individual satellites, we employed an averaging strategy for stacking the post-fit phase residuals obtained from our Precise Point Positioning (PPP) processing strategy to generate station-specific MP correction maps. The spatial stacking was carried out in congruent cells with an optimal resolution in elevation and azimuth at the local horizon but with decreasing azimuth resolution as the elevation angle increases. This permits an approximately equal number of observations allocated to each cell. Using these MP correction maps in a final step, the one-way SWD were improved to employ them for the analysis of the weather event. We found that the non-isotropic component of the one-way SWD contributes up to 11% of the SWD estimates. Moreover, we validated the SWD between ground-based water-vapour radiometry and GNSS-derived SWD for different elevation angles. Furthermore, the spatio-temporal fluctuations in the SWD as measured by GNSS closely mirrored the moisture field from the ERA5 re-analysis associated with this weather event. By employing an adequate windowing system for generating these MP correction maps in combination with high-precision real-time GNSS analysis, it is possible to provide improved SWD estimates for the tracking of severe weather events.

How to cite: Teferle, N., Hunegnaw, A., Duman, H., Baltaci, H., Ejigu, Y. G., and Dousa, J.: On the Impact of GNSS Multipath Correction Maps on Slant Wet Delays for Tracking Severe Weather Events, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12264, https://doi.org/10.5194/egusphere-egu22-12264, 2022.

Signal biases are hardware delays that occur during the transmission and reception of GNSS signals. On the satellite side, there is a delay between the generation of a signal and its transmission at the antenna. The same is the case on the receiver side, where a delay occurs between signal reception at the antenna and the actual measurement of a specific signal in the receiver. As the name suggests, code biases refer to the delays affecting code observations. Similarly, phase observations are affected by phase biases. In general, signal biases differ per constellation, satellite, frequency, signal attribute, as well as receiver hardware and settings.

The main issue with signal biases is that they are usually not known. Therefore, they have to be estimated during GNSS processing. However, the relative nature of GNSS observations prevents the estimation of absolute signal biases. This results in several rank deficiencies in the normal equation system when signal biases are estimated together with other geodetic parameters in a global multi-GNSS processing.

We present a general approach based on eigenvalue analysis to solve these rank deficiencies. Therefore, the co-estimation of pseudo-absolute transmitter and receiver signal biases in our multi-GNSS processing becomes possible. This approach also enables ambiguity resolution of GLONASS phase obervations.

How to cite: Strasser, S., Mayer-Gürr, T., Süsser-Rechberger, B., and Dumitraschkewitz, P.: Estimable phase and code biases in the frame of global multi-GNSS processing, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12557, https://doi.org/10.5194/egusphere-egu22-12557, 2022.

During the last decade, GNSS interferometric reflectometry (GNSS-IR) has shown great potential for sea level monitoring. In combination with geodetic positioning, GNSS-IR provides a possibility to directly link the sea level measurements to the global terrestrial reference frame. However, many error sources can still be better modeled, and the accuracy of GNSS-IR sea level measurements can be improved. Specifically, we revise the tropospheric error model in ground-based GNSS-IR for sea level applications. Unlike GNSS positioning applications, in GNSS-IR the bending effect is as important as the delay effect. Also, usually very low elevation angle observations are used in GNSS-IR, which makes the atmospheric impact even more important. For the bending effect, we propose a new calculation which takes into account the water vapour content and utilizes the widely used mapping function approach to account for the elevation dependence. For the GNSS-IR atmospheric delay, we revise the geometry of the GNSS signal path for the case of coastal GNSS-IR where the antenna is within < 100 m from the sea surface. The atmospheric delay for the reflected signal is separately evaluated at the surface specular reflection point. The delay from the satellite to the reflection point and the direct signal can both be derived from the zenith delay and mapping function, at their respective local coordinates. The delay from the reflection point to the antenna is obtained assuming an average layer refractivity. We validated our model with ray-tracing radiosonde data. At 2° elevation angle, the new method can correct > 98 % of the atmospheric bending effect, compared to about 88 % with the previously adopted approach. With fewer approximations than the previous approach (directly using the mapping function), the new delay error model is also more accurate but with less absolute improvement of about 3 % compared to the previously existing model.

How to cite: Feng, P., Haas, R., Elgered, G., and Strandberg, J.: Calibrating tropospheric errors on ground-based GNSS reflectometry: calculation of bending and delay effects, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12698, https://doi.org/10.5194/egusphere-egu22-12698, 2022.

The use of theoretical modeling algorithms to compute the satellite altitude causes some errors which are eventually absorbed by the satellite clocks. This adversely reduces the fixed positioning performance in global navigation satellite system (GNSS) precise point positioning (PPP). Currently, different International GNSS service (IGS) analysis centers (ACs) provide satellite altitude quaternions which are an auxiliary dataset necessary in PPP fixed solutions. Hence, this study aims at a comprehensive evaluation of the effect of accounting for the BeiDou satellite attitude quaternions in PPP. The quaternions provided by different ACs are applied to BeiDou PPP using different weighting schemes suitable for handling satellites in three distinct orbits. The obtained numerical results indicate that considering the quaternions in BeiDou PPP reduces the observation residuals, improves the ambiguity fixing, and enhances positioning performance.

How to cite: Suya, R. G., Chen, Y.-T., Kwong, C.-F., and Zhang, P.: Considering Satellite Attitude Quaternions in BeiDou Precise Point Positioning Performance, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12926, https://doi.org/10.5194/egusphere-egu22-12926, 2022.

Deformation measurements and deformation analysis are important fields of study in geodesy. Investigating the results obtained from the deformation analysis is very important for human safety. By monitoring the movements of the earth's crust or engineering structures, many measures can be taken to protect human life against potential disasters. For this reason, geodetic measurement techniques have been used since the beginning of the 20th century. Important studies have been carried out, especially with the development of GNSS measurement techniques for monitoring displacement movements and deformations. Both academic and commercial software are available for deformation analysis for the determination of earth crust movements. However, the increasing interest in studying crustal movements has revealed new demands. Today, developing technology has allowed the development of new platforms for deformation analysis.

In this study, an open source web-based deformation analysis platform named Web-NDefA (Web-'N'etwork 'Def'ormation 'A'nalysis), which was developed for 3D static deformation analysis using geodetic methods, is introduced. In addition, the analysis of a data group obtained from Continuously Operating Reference Stations in the Marmara Region with this platform is also explained. After the processing of the base vectors obtained from univariant GNSS networks with the LGO (Leica Geo Office) software, Web-NDefA is used to load the ASCII file of the base solutions to the platform, to adjust the measurements according to the free adjustment method, to obtain the confidence criteria and to analyse the networks compared according to the static deformation model and S-Transformation method. It is a static deformation analysis platform that performs 3-Dimensional statistical analysis that provides visualization, computation of coordinate differences, and drawing velocity vectors. This platform is written with client-side programming languages. HTML (HyperText Markup Language), CSS (Cascading Style Sheets), JavaScript applications were made.

As a result, in this study, information about the design of the have developed open source web platform is given and GNSS data obtained from certain days in 2016, 2019 and 2020 in the Marmara Region are analysed. In this way, a new vision is put forward to the applications used in GNSS-based static deformation analysis and experts who are interested in monitoring and analysing deformations can access such platforms more easily.

How to cite: Bak, M. and Celik, R. N.: A Web Based Open Source Deformation Analysis Platform for identifying Crustal Movements, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13326, https://doi.org/10.5194/egusphere-egu22-13326, 2022.

The 2022 Tonga event highlight the necessity to have more and more knowledge about the activity
of volcanoes. To this point, it is well known that volcanoes explosion can trigger ionospheric
perturbation detectable through the Global Navigation Satellite System (GNSS) signal [1].
The VARION (Variometric Approach for Real-Time Ionosphere Observation) algorithm has been
successfully applied to detection of ionospheric perturbations in several real-time scenarios [2, 3].
VARION, thus, estimates sTEC (slant total electron content) variations starting from the single time
differences of geometry-free combinations of GNSS carrier-phase measurements.
The aim of this work is to analyse some Etna explosions occurred in 2021 with the VARION algorithm
in order to better study the coupling between volcanoes and ionosphere. This study can pave the
way to a real-time ionospheric monitoring of Etna volcano.
[1] Manta, Fabio, et al. "Correlation between GNSS‐TEC and eruption magnitude supports the use
of ionospheric sensing to complement volcanic hazard assessment." Journal of Geophysical
Research: Solid Earth 126.2 (2021): e2020JB020726.
[2] Ravanelli, Michela, et al. "GNSS total variometric approach: first demonstration of a tool for
real-time tsunami genesis estimation." Scientific Reports 11.1 (2021): 1-12.
[3] Savastano, Giorgio, et al. "Advantages of geostationary satellites for ionospheric anomaly
studies: Ionospheric plasma depletion following a rocket launch." Remote Sensing 11.14 (2019):
1734.

How to cite: Ravanelli, M., Ferrara, F., Fuso, F., Cannata, A., Crespi, M., and Occhipinti, G.: The VARION approach to volcanoes: case study on 2021 Etna eruptions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13439, https://doi.org/10.5194/egusphere-egu22-13439, 2022.

Tsunami detection and forecasting require observations from open-ocean sensors. It is well known that tsunamis can generate internal gravity waves that propagate through the ionosphere from the earthquake center along with the tsunami wave. These disturbances can be detected by Global Navigation Satellite Systems (GNSS) receivers. The VARION (Variometric Approach for Real-Time Ionosphere Observation) algorithm has been successfully applied to detecting traveling ionospheric perturbations (TIDs) in several real-time scenarios, and it has also been successfully demonstrated that this algorithm is suitable for moving systems such as ship-based GNSS receivers. We present analyses of GNSS data collected from ships and examine the potential of a ship-based GNSS network for the ionospheric detection of tsunamis. 

In this project, we focused on the detection of tsunami signals from the TIDs using deep learning methods. Benefiting from the large amount of data from widely distributed GNSS permanent stations, we developed a prototype convolutional neural network for tsunami detection, achieving highly accurate prediction scores on the validation and test data. We used the observations coming from our 10-ship pilot network real-time GNSS system from the Pacific ocean to detect the TIDs related to the 2015 Illapel, Chile earthquake and tsunami. Using our algorithm in a post-processing mode we found that our ships successfully detected the ionospheric tsunami signal even though there was no detectable sea-surface height perturbation for the ship. Comparing the performance using our deep learning method with other anomaly detection approaches in a real-time scenario, we found that our approach works very efficiently with the pre-trained model. The results of our study, although preliminary, are very encouraging and we conclude that ships can be cost-effective real-time tsunami early-warning sensors. Given that there are thousands of existing ships in the Pacific Ocean, this is a promising opportunity to improve hazard mitigation.

How to cite: Xie, Y., Foster, J., Ravanelli, M., and Crespi, M.: Ship-based GNSS ionospheric observations for the detection of tsunamis with deep learning, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-405, https://doi.org/10.5194/egusphere-egu22-405, 2022.

Nowadays, many applications such as Global Navigation Satellite Systems (GNSS) or spacecraft tracking require a rapid determination, or even predictions, of the Earth Orientation Parameters (EOP). However, due to the measurement techniques utilized to estimate EOP, the latency can be considerably longer than required, which especially hinders real-time applications, resulting in a need for accurate EOP prediction methods.

With the resurgence of machine learning in the last decade, time series prediction is increasingly studied in this context. We propose a learning algorithm for the prediction of polar motion components (xp, yp). The algorithm is based on the concept of Ordinary Differential Equation (ODE) fitting. Within this investigation, a general formula for ODE fitting based on multivariate time series is proposed, with special focus on second order ODEs. The mathematical relations are derived and presented in both linear and non-linear forms, particularly with LSTM and Elman neural networks. In addition, a sensitivity analysis framework is proposed for the linear case, which is used for the determination of the importance of features. 

We compared the prediction performance of our method with those from three different studies. First, the conditions of the first Earth Orientation Prediction Comparison Campaign (EOPPCC) are followed. In this case, the ultra-short term predictions (up to 10 days) can be improved on average by 62.5% and 45.6% for xp and yp, respectively,  compared to the best performing EOPPCC method. Second, the prediction performance in long-term prediction (up to one year) is compared against Multichannel Singular Spectrum Analysis (MSSA). In this case, the prediction performance is improved on average for xp and yp by 40.9% and 66.4%, respectively. Finally, comparisons against Copula-based methods for long-term prediction are conducted (average improvement 32.3% for xp and 57.8% for yp).

The advantages of this method include (1) exploitation of physical information via Effective Angular Momentum (EAM) functions and by using the concept of ODE fitting, which often corresponds to the laws governing physical phenomena; (2) presence of sensitivity analysis frameworks; and (3) high predictive performance.

How to cite: Kiani Shahvandi, M., Schartner, M., and Soja, B.: Differential Learning: A method for polar motion time series prediction, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1101, https://doi.org/10.5194/egusphere-egu22-1101, 2022.

Multipath is the main unmodeled error source hindering high-precision GNSS (Global Navigation Satellite System) data processing. Classical multipath mitigation methods, such as sidereal filtering (SF) and multipath hemispherical map (MHM), have certain disadvantages: they are either too complicated for implementation or not effective enough for multipath mitigation. In this study, we demonstrate that machine learning (ML) based models, such as random forest, can overcome these drawbacks by spatial interpolation over sky map and thus mitigate multipath effectively. 30 days of 1 Hz geodetic grade GPS data as well as 6 days of low-cost data are used to train and test the ML models. Based on a series of test cases, the best number of days for model training and the validity period for the models are discussed in this contribution. For quantification, the multipath reduction rate and kinematic positioning precision are computed using different ML models and compared to those derived from SF and MHM. The statistical results show that the XGBoost ML model can achieve higher multipath reduction rates compared to SF and MHM, especially for pseudorange measurements, which is important for low-cost devices. It reduces the multipath by 48% and 55% for pseudorange and carrier phase measurements, respectively, and outperforms SF (40% and 52%) and MHM (37% and 49%). The positioning precision when using different multipath models is similar, with differences of less than 1 mm. We conclude that the ML based multipath mitigation method is effective and easy-to-use, which can be applied under real-time scenarios.

How to cite: Pan, Y., Möller, G., Hohensinn, R., and Soja, B.: Machine learning based multipath mitigation for high-precision GNSS data processing, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1503, https://doi.org/10.5194/egusphere-egu22-1503, 2022.

Precise orbit determination is vital for the increasingly vast number of space objects around the Earth. Moreover, accurate orbit prediction of GNSS satellites is essential for many real-time geodetic applications, including real-time navigation. The typical way to obtain accurate orbit predictions is using physics-based orbit propagators. However, the prediction errors accumulate with time because of insufficient modeling of the changing perturbing forces. Motivated by the rapid expansion of computing power and the considerable data volume of satellite orbits available in recent years, we can apply machine learning (ML) and deep learning (DL) algorithms to assess if they can be used to further reduce orbit errors.

In this study, we focus on the orbit prediction of GNSS constellations. We investigate the potential of using different ML and DL algorithms for improving the accuracy of the ultra-rapid products from IGS. As ground truth we consider the IGS final products, and the differences between the ultra-rapid and final products are computed and serve as targets for the ML/DL methods. In this context, we combine the advantages of physics-based and data-driven ML/DL methods. Since the major errors of GNSS orbits are expected to be caused by the deficiency of solar radiation pressure models, we consider different related parameters as additional features to implicitly model the solar impact, such as the C_0,0 terms of global ionosphere maps. In order to accurately model the effect of solar radiation pressure on the radial, along-track and cross-track components of the satellite orbit system, the geometric relation between the Sun, the satellite and the Earth are also considered. Furthermore, the performances of different ML/DL algorithms are compared and discussed. Due to the temporal characteristics of the problem, certain sequential modeling algorithms, such as Long Short-Term Memory and Gated Recurrent Unit, show superiority. Our approach shows promising results with average improvements of over 40% in 3D RMS within the 24-hours prediction interval of the ultra-rapid products.

How to cite: Gou, J., Rösch, C., Shehaj, E., Chen, K., Kiani Shahvandi, M., Soja, B., and Rothacher, M.: Improving the Accuracy of GNSS Orbit Predictions using Machine Learning Approaches, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1834, https://doi.org/10.5194/egusphere-egu22-1834, 2022.

Tropospheric delays have been a major error source for space geodetic techniques and the performance of their modeling is significantly limited due to the high spatiotemporal variability of the moisture in the lower atmosphere. In this study, tropospheric zenith wet delay (ZWD) modeling was realized based on the machine learning (random forest approach, RF) and using 10 years (2010-2019) of radiosonde measurements at 586 globally distributed stations. Subsequently, the ZWD modeling accuracy was validated based on the sounding profiles across the globe for the year 2020. We find that ZWD modeling accuracy is significantly improved by taking account meteorological parameters in the functional formulation, especially for surface water vapor pressure. When surface meteorological data are available, the RF-based ZWD models with meteorological parameterization can achieve an overall accuracy of 2.9 cm and the bias close to zero across the globe, which clearly outperforms current empirical models, such as the GPT3, or other models based on surface meteorological measurements. From the analyses of spatial characteristics of the ZWD accuracy, it can be concluded that the RF-based ZWD models especially mitigate the systematic biases in the regions with monsoon climate and tropical rainforest climate types. 

How to cite: Li, Q., Böhm, J., Yuan, L., and Weber, R.: Development of a global model for zenith wet delays based on the random forest approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2702, https://doi.org/10.5194/egusphere-egu22-2702, 2022.

Abstract:

In Machine Learning (ML), one of the crucial tasks is understanding data characteristics to be able to extract exactly relevant information, while noise contained in data can cause misleading estimations and decrease the generalizability of ML-based prediction models. So far, only few previous studies have applied noise filtering techniques when building forecast models. Hence, their efficiency on ML-based forecasts has not yet been comprehensively demonstrated. Therefore, we aim to determine optimal noise filters to enhance the forecast performance of Total Electron Contents (TEC), crustal motion, and Earth’s polar motion. We investigate six noise filtering algorithms (Moving Mean, Moving Median, Lowess, Loess, and Savitzky Golay) on forecast models to select the best-suited filters. Five ML algorithms are applied to train forecast models, that are Support Vector Machine (SVM), Regression Trees, Linear Regression (LR), Ensembles of Trees, and Gaussian Process Regression (GPR). The findings show that the Savitzky Golay algorithm is the most effective on the ML-based forecast models, followed by Loess and Gaussian filters, while Moving Mean is the least sensitive. Noise filters are more sensitive for forecast models based on SVM and LR than Ensembles of Trees and GPR. Applying the Savitzky Golay filter for SVM and LR optimal models can enhance the prediction accuracy up to 14.0 %, 16.1 % and 89.5 % corresponding to forecasting TEC, crustal motion, and Earth's polar motion, respectively; while that for Ensembles and GPR are only from approximate 3.0 to 27.0 %. Overall, using noise filters is one of the practical solutions to improve prediction performance. They can also be used to smoothen time series with variable characteristics and to generalize high-rate data.

Keywords:

Machine Learning, Noise filters, Savitzky Golay filter, TEC forecast, Crustal motion, Earth’s polar motion.

How to cite: Le, N., Männel, B., Natras, R., Sakic, P., Deng, Z., and Schuh ‬‬‬‬‬‬‬‬‬‬‬‬‬, H.: Apply noise filters for better forecast performance in Machine Learning, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4039, https://doi.org/10.5194/egusphere-egu22-4039, 2022.

Radio signals transmitted by Global Navigation Satellite System (GNSS) satellites propagate through the atmosphere before being received on Earth. Thereby, the signal is delayed and tropospheric parameters can be estimated. The good global coverage of GNSS receivers, combined with the high temporal resolution and the high accuracy, make GNSS a suitable tool for studies on the atmosphere.

Atmospheric delays are differentiated into a zenith hydrostatic (ZHD) and a non-hydrostatic, or zenith wet delay (ZWD). The hydrostatic part has a larger contribution (causing a delay of roughly 2.4 meters in the zenith direction) but can be modeled with sufficient accuracy using analytical methods. The ZWD has a smaller contribution (causing a delay between 0 to 40 centimeters) and depends mainly on the water vapour content in the atmosphere. However, due to the variable nature of water vapour, the ZWD is difficult to model and is therefore typically estimated. Its quantification is essential since it drives weather systems and climate change to a great extent. For many applications, such as weather forecasting or positioning using low-cost GNSS receivers such as smartphones, global real-time monitoring or even predictions of ZWD would be required and be beneficial.

In the last decade, machine learning (ML) algorithms have gained a lot of interest and are successfully utilized in many different fields. Thereby, ML algorithms have proven to be able to efficiently process and combine large amounts of data and solve problems of various kinds.

This motivated us to investigate the feasibility of ML algorithms for the prediction of tropospheric parameters, in particular ZWD, with the help of meteorological data such as the water vapour content. The work aims to develop a global model capable of predicting ZWD in space and time. Therefore, different ML algorithms are used to train a model based on meteorological features. The performance of the utilized algorithms is evaluated based on commonly used performance metrics, such as Root Mean Squared Error (RMSE) and R².

Preliminary investigations are carried out utilizing 3000 GNSS stations distributed over Europe. The performance of various ML methods, such as Linear Regression methods, Random Forest, (Extreme) Gradient Boosting, and Multilayer Perceptron is compared. Furthermore, different feature combinations, as well as training sample sizes are investigated. It is revealed that linear methods are not able to properly reflect the observations. Instead, our Random Forest approach provides, so far, the highest model accuracy with an RMSE of 1.7 centimeters and an R² value of 0.88.

How to cite: Crocetti, L., Soja, B., Kłopotek, G., Awadaljeed, M., Rothacher, M., See, L., Weinacker, R., Sturn, T., McCallum, I., and Navarro, V.: Machine learning and meteorological data for spatio-temporal prediction of tropospheric parameters, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4531, https://doi.org/10.5194/egusphere-egu22-4531, 2022.

The CyGNSS (Cyclone Global Navigation Satellite System) satellite system measures GNSS signals reflected off the Earth’s surface. A global ocean wind speed dataset is derived, which fills a gap in Earth observation data and can improve cyclone forecasting. We proposed CyGNSSnet(1), a deep learning model for predicting wind speed from CyGNSS observables, and found an improved performance of 29% compared to the current operational model. However, the prediction of extreme winds remained challenging: For wind speeds exceeding 12 m/s, the operational model outperformed CyGNSSnet.

Here, we explore methods to improve the performance of CyGNSSnet at high wind speeds. We introduce a hierarchical model that combines specialized CyGNSSnet instances trained in different wind speed regimes with a classifier to select an instance. In addition, we explore strategies to improve the wind speed predictions by emphasizing extreme values in training, and we discuss the potentials and shortcomings of the approaches.

• (1) Asgarimehr, M., Arnold, C., Weigel, T., Ruf, C. & Wickert, J. GNSS reflectometry global ocean wind speed using deep learning: Development and assessment of CyGNSSnet. Remote Sensing of Environment 269, 112801 (2022).

How to cite: Arnold, C., Zhao, D., Xiao, T., Mou, L., and Asgarimehr, M.: Deep learning for extreme wind speed prediction with CyGNSSnet, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5003, https://doi.org/10.5194/egusphere-egu22-5003, 2022.

Space weather can cause strong sudden disturbances in the Earth’s ionosphere that can degrade the performance and reliability of Global Navigation Satellite System (GNSS) operations. To minimize such degradations, ionospheric effects need to be precisely and timely corrected by providing information of the spatially and temporally variable Total Electron Content (TEC). To obtain such corrections and early warning information of space weather events, we need to model the nonlinear space weather processes focusing on their impact on the ionosphere. Machine Learning (ML) models can learn nonlinear relationships from data to solve complex phenomena such as space weather. To interpret ML model results, it is crucial to know their quality and reliability. Quantifying the uncertainty of the ML results is an important step toward developing a “trustworthy” model, providing reliable results, and improving the model explainability.

This study presents a novel ML model to forecast the vertical TEC (VTEC) utilizing state-of-the-art supervised learning techniques and robustly assessing the uncertainty of the achieved results. The data are systematically analyzed, selected and pre-processed for optimal model learning, especially during space weather events. Results from our previous study (Natras and Schmidt, 2021) were improved in terms of data, ensemble modelling, and uncertainty quantification. The input data are expanded with additional parameters of the solar wind and the interplanetary magnetic field from OmniWeb and spectral irradiance measurements from the solar instrument LYRA onboard the spacecraft PROBA2 (Dominique et al., 2013). Also, new input features have been derived, such as daily differences, time derivatives, moving averages, etc. We applied ensemble modeling to combine diverse ML models based on different learning algorithms with different training data sets. The ensemble model enhances the performance of base learners and quantifies the uncertainty of results. This approach shows potential for forecasting VTEC in different ionospheric regions during quiet and storm periods, while providing the uncertainties of the forecasting results.

Keywords: Machine Learning, Space Weather, Ionosphere, Vertical Total Electron Content (VTEC), Forecasting, Uncertainty Quantification

References:

Dominique, M., Hochedez, JF., Schmutz, W. et al. (2013): The LYRA Instrument Onboard PROBA2: Description and In-Flight Performance. Sol Phys 286, 21-42 https://doi.org/10.1007/s11207-013-0252-5

Natras, R., Schmidt, M. (2021): Ionospheric VTEC Forecasting using Machine Learning, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8907, https://doi.org/10.5194/egusphere-egu21-8907

How to cite: Natras, R., Soja, B., Schmidt, M., Dominique, M., and Türkmen, A.: Machine Learning Approach for Forecasting Space Weather Effects in the Ionosphere with Uncertainty Quantification, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5408, https://doi.org/10.5194/egusphere-egu22-5408, 2022.

As a specific family of machine learning algorithms, deep learning (DL), successfully applied to several application areas is a relatively new and novel methodology receiving much attention. The DL has been widely applied to a series of problems including email filtering, image and speech recognition, and language processing, but is only beginning to impact on geoscience problems. On the other hand, the standard least-squares (SLS) theory of linear models has been widely used in many earth science areas. This theory connects the explanatory variables to the predicted ones, called observations, through a linear(ized) model in which the unknowns of this relation are estimated using the least squares method. The design matrix, containing the explanatory variables of a set of objects, is usually linearly related to the predicted variables. There are however applications that the predicted variables are unknown (nonlinear) functions of explanatory variables, and hence such a design matrix is not known a-priori. We present a methodology that formulates the deep learning problem in the least squares framework of the linear models. As a supervised method, a network is trained to construct an appropriate design matrix, an essential element of the linear model. The entries of this design matrix, as nonlinear functions of the explanatory variables, are trained in an iterative manner using the descent optimization methods. Such a design matrix allows to employ the existing knowledge on the least squares theory to the DL applications. A few examples are presented to demonstrate the theory.

How to cite: Amiri-Simkooei, A.: Least-squares-based formulation of deep learning: Theory and applications to geoscience data analytics, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7272, https://doi.org/10.5194/egusphere-egu22-7272, 2022.

Precise modeling of the ionospheric Total Electron Content (TEC) is critical for reliable and accurate GNSS applications. TEC is the integral of the location-dependent electron density along the signal path and is a crucial parameter that is often used to describe ionospheric variability, as it is strongly affected by solar activity. TEC is highly depended on local time (temporal variability), latitude, longitude (spatial variability), solar and geomagnetic conditions. The propagation of the signals from GNSS (Global Navigation Satellite System) satellites throughout the ionosphere is strongly influenced by temporal changes and ionospheric regular or irregular variations. Here, we propose a deep learning architecture for the prediction of the vertical total electron content (VTEC) of the ionosphere based on GNSS data. 

The data used in many deep learning tasks until recently where mostly represented in the Euclidean space. However, geodesy studies data that have an underlying structure that is non-Euclidean space. Geospatial data are large and complex, as in the case of GNSS networks data, and their non- Euclidean nature has imposed significant challenges on the existing machine learning algorithms. The task of VTEC prediction is challenging mainly due to the complex spatiotemporal dependencies and an inherent difficulty in temporal forecasting. Spatial-temporal graph neural networks (STGNNs) aim to learn hidden patterns from spatial-temporal graphs. The key idea of STGNNs is to consider spatial and temporal dependency at the same time. Spatial Dependency: Assuming a network of permanent stations of International GNSS Service (IGS), each station represents a node of the graph, and their Euclidean distance is used to formulate the set of edges of the graph. Thus, we achieve exchange between nodes and their neighbors. Temporal dependency: The graph operates in a dynamic environment. Thus, we leverage the recurrent neural networks (RNNs) to model the temporal dependency. As a result, time series of VTEC data can be predicted to future epochs. Solar and geomagnetic indices are formulated as node attributes and are also present temporal variability.

Topics to be discussed in the study include the design of the graph neural network structure, the training methods exploiting steepest descent algorithms, data analysis, as well as preliminary testing results of the VTEC predictions as compared, with state-of-the-art graph architectures.

How to cite: Kaselimi, M., Gikas, V., Doulamis, N., Doulamis, A., and Delikaraoglou, D.: Spatio-temporal Graph Neural Networks for Ionospheric TEC Prediction Using Global Navigation Satellite System Observables, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7331, https://doi.org/10.5194/egusphere-egu22-7331, 2022.

Global Navigation Satellite System (GNSS) long-term residual height time series exhibit signals related to environmental influences. These can partly b explained through environmental surface loads, which are described with physical models. In this work, a model is computed to connect the GNSS residuals with raw meteorological parameters. A Temporal Convolutional Network (TCN) is trained on 206 GNSS stations in central Europe, and applied to 68 test stations in the same area. The resulting Root Mean Square (RMS) error reduction is on average 0.8% lower for the TCN modeled time series, compared to using physical models for the reduction. In a further experiment, the TCN is trained on the GNSS time series after reducing those by the surface loading models. The aim is a further increase of RMS reduction, which is achieved with 2.7% on average, resulting in an overall mean reduction of 28.6%. The results suggest that with meteorological features as input data, TCN modeled reductions are able to compete with reductions derived from physical models. Trained on the residuals reduced by environmental loading models, the TCN is able to slightly increase the overall reduction of variations in the GNSS station position time series.

How to cite: Ruttner, P., Hohensinn, R., D'Aronco, S., Wegner, J. D., and Soja, B.: Modeling of Residual GNSS Station Motions through Meteorological Data in a Machine Learning Approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9105, https://doi.org/10.5194/egusphere-egu22-9105, 2022.

Detecting small Slow Slip Events (SSEs) is still an open challenge. The difficulty in revealing low magnitude events is related to their detection in the geodetic data, which must be improved either by employing more powerful equipment or by developing novel methods for the systematic discovery of small events, which can be crucial for the precise characterization of the slip spectrum. The improvement of the ability to detect small SSEs and the associated seismic response can play a decisive role in the understanding of the mechanics of active faults, remarkably subduction in which tremors cannot serve as a proxy for the slow slip or Episodic Tremor and Slip (ETS) is not regularly observed, making it necessary to provide new observations and methods to perceive potential bursts of slow slip.

Here we explore three Deep Learning–based strategies applied to GNSS data to characterize earthquakes and SSEs. Unlike seismic data, geodetic observations are crucial for dealing with SSEs, since they contain the required spatiotemporal information. Yet, since the low number of available labelled events (earthquakes or SSEs) producing significant displacement at GNSS station does not allow to adequately train Deep Learning models, we adopt synthetic geodetic data (Okada, 1985), obtained by generating events with uniformly distributed parameters. Thus, the model will not be biased towards the most numerous parameters, with a possibly stronger predictive power. The approach inspired by (van den Ende, Ampuero, 2020) was used for the characterization (i.e., estimation of epicentral location and magnitude), which associates geodetic time series with the location information of the GNSS stations. Yet, rearranging the geodetic displacement from GNSS time series into images can let Convolutional Neural Networks (CNN) to better account for the data spatial consistency, leading to more precise results. Furthermore, Transformers have also been tested with image time series of ground deformation. To assess the reliability of the tested methods, a magnitude threshold on the synthetic test set has been estimated, which depends on the depth and the hypocenter location of the event, showing a trade-off between the Signal-to-Noise (SNR) ratio and the relative position of the test events with respect to the GNSS network, revealing physical consistence. The results are also spatially consistent, as the location and magnitude errors tend to increase as the actual epicenters move offshore, with the location error showing a strong inverse proportionality on the magnitude. The employment of time series of deformation with Transformer networks lead to the best results and may allow us to better handle the noise complexity and to account for a spatio–temporal analysis of the ground deformation linked to SSE triggering. Nevertheless, the image–based model outperforms the other two on real data, showing evidence that the synthetic data does still not overlap with the real one, opening towards several perspectives. A more complex synthetic noise can be produced by allowing for synthetic data gaps and outliers (e.g., common modes), or machine learning–based denoising strategies can be envisioned to pre–process the data to improve the SNR ratio.

How to cite: Costantino, G., Giffard-Roisin, S., Dalla Mura, M., Marsan, D., Radiguet, M., and Socquet, A.: Towards the characterization of Slow Slip deformation by means of deep learning, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12032, https://doi.org/10.5194/egusphere-egu22-12032, 2022.

The aim of this study is to study the effects of datum definition on the estimation of vertical velocities at the continuous GNSS stations and campaign GNSS sites. The observations have been analyzed to measure the accuracy of vertical deformations derived from GPS stations depending on the definition datum of the geodetic network.

This investigation was carried out six campaign GNSS sites and twenty-one continuous GNSS stations operated by the National Permanent Network in Turkey (TUSAGA-Active) in the coastal regions of Turkey during the period 2001-2018. The GNSS observations were processed in the ITRF2014 reference frame using Bernese v5.2 software with different approaches based on four International GNSS Service (IGS) reference stations, which are thought to be less affected by tectonic movements.

The results show that the sensitivity of GNSS vertical velocities depends on the geometrical distribution of the reference stations and on the chosen set of reference stations that define the datum of the geodetic network. Moreover, the accuracy from the number of reference stations is one to three is less good than four or more reference stations, and the vertical velocities of our solution derived from four reference stations agree with those of the IGS solution.

How to cite: Erkoç, M. H. and Doğan, U.: Effects of Datum Definition on Estimation of GNSS Vertical Velocities, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-304, https://doi.org/10.5194/egusphere-egu22-304, 2022.

Gravity forward modelling is one of the fundamental topics in geodesy and geophysics. A spherical shell is a commonly used reference model among the mass bodies for the spatial domain of gravity forward modelling. The reason is that it has simple analytical expressions for gravitational effects (e.g. gravitational potential (GP), gravity vector (GV), gravity gradient tensor (GGT), and gravitational or gravity curvatures (GC)). The finer grid size will need more computation time when adopting the numerical strategy of a spherical shell discretized using tesseroids. This contribution presents the simpler analytical expressions for the GV and GGT of a homogeneous zonal band. The new analytical formula of the GC of a homogeneous zonal band is derived. The computation time and relative errors of the GP, GV, GGT, and GC between a spherical zonal band and a spherical shell discretized using tesseroids are quantitatively investigated with different grid sizes. Numerical results reveal that the computation time of a spherical zonal band discretized using tesseroids is about 180/n (i.e. n is the grid size) times less than that of a spherical shell discretized using tesseroids in double and quadruple precision. The relative errors' mean values of the GP, GV, GGT, and GC for a spherical zonal band discretized using tesseroids are smaller than those for a spherical shell discretized using tesseroids. In short, the benefit of a spherical zonal band in comparison with a spherical shell discretized using tesseroids regarding both the computation time and errors is confirmed numerically. The numerical approach of a spherical zonal band discretized using tesseroids can be applied instead of the classical numerical strategy in numerical evaluation of a tesseroid or other spherical mass bodies in gravity field modelling. This study is supported by the project funded by China Postdoctoral Science Foundation (Grant No. 2021M691402).

How to cite: Deng, X.-L.: A comparison of gravitational effects between a spherical zonal band and a spherical shell discretized using tesseroids, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-875, https://doi.org/10.5194/egusphere-egu22-875, 2022.

For the representation of the Earth’s global gravity field, Spherical Harmonics (SH) are widely used in geodetic community. On the other hand, for the representation of a local or regional gravity field, Spherical Cap Harmonics (SCH) and Rectangular Harmonics (RH) are alternative techniques with important advantages over SH. Although SCH are extensively presented in literature, RH are found in very few applications, especially of the gravity field. This work derives different functional forms of the disturbing potential, outside of the Earth’s masses, using RH. Also, the necessary transformation from geocentric into local rectangular coordinates is presented. The Rectangular Harmonic Coefficients (RHC) of the different mathematical models of the disturbing potential can be estimated through a least squares’ adjustment process. In order to select the best mathematical model, numerical experiments, based on data generated from a geopotential model, are conducted and the results are validated. Then, for the best model of the disturbing potential, its functionals (gravity anomaly and disturbance, height anomaly, geoid undulation and deflection of vertical) are given in terms of RHC. We conclude that RH representations are both suitable and convenient for the modelling of the local or regional gravity field.

How to cite: Panou, G. and Korakitis, R.: Modelling the local gravity field by rectangular harmonics with numerical validations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1880, https://doi.org/10.5194/egusphere-egu22-1880, 2022.

We present a numerical approach for solving the oblique derivative boundary value problem (BVP) based on the finite element method (FEM) with mapped infinite elements. To that goal, we formulate the BVP consisting of the Laplace equation in 3D semi-infinite domain outside the Earth which is bounded by the approximation of the Earth's surface where the oblique derivative boundary condition is given. At infinity, regularity of the disturbing potential is prescribed. As the numerical method, we have implemented the FEM with mapped infinite elements, where the computational domain is divided into
two centrical parts, one meshed with finite elements and one with infinite ones. In numerical experiments, we firstly test a convergence of the proposed numerical scheme and then we deal with global gravity field modelling using EGM2008 data. To perform such numerical experiments, we create a special discretization of the Earth's surface to fulfil the conditions that arise from correct geometrical properties of finite elements. Then a reconstruction of EGM2008 aims to indicate efficiency of the presented numerical approach.

How to cite: Macák, M., Minarechová, Z., Čunderlík, R., Mikula, K., and Tomek, L.: Global gravity field modelling by the finite element method involving mapped infinite elements., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2429, https://doi.org/10.5194/egusphere-egu22-2429, 2022.

We present nonlinear diffusion filtering of the GOCE-based satellite-only mean dynamic topography (MDT) based on the geodesic mean curvature flow (GMCF). GMCF represents a curvature-driven diffusion filtering, where the processed data are considered as a set of specific contour lines. A properly designed evolution of these contour lines corresponds to smoothing of the processed data. A main advantage is an adaptive smoothing of the contour lines while respecting significant values of gradients. This property can be beneficial for filtering the MDT models since it allows preserving important gradients along main ocean surface currents. We present numerical solution of the GMCF-based diffusion partial differential equations using the finite volume method (FVM) on regular grids. The derived numerical scheme is applied for filtering the satellite-only MDT models obtained as a combination of the DTU21_MSS model and the recent GOCE-based satellite-only global geopotential models. Then the filtered MDT models are used to derive velocities of the surface geostrophic currents over oceans.

How to cite: Čunderlík, R., Kollár, M., and Mikula, K.: Surface geostrophic currents derived from the nonlinear diffusion filtering of the GOCE-based satellite-only MDT using the geodesic mean curvature flow, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2553, https://doi.org/10.5194/egusphere-egu22-2553, 2022.

The secular change in the flattening of Earth and its effect on global tectonics is a subject still to be investigated.

Tidal friction causes a constant despinning of the rotation of Earth. It happens at a rate of Δω = – (5.4 ± 0.5) ∙ 10^-22s^-2, resulting in a change of the length of day with ∆LOD = (2.3 ± 0.1) ms/century (Stacey, 1992). The slowly decreasing rotational speed creates a change in the flattening of the Earth, that produces a latitude dependent stress field. The meridional stress component is always positive (i.e. tensional), while the azimuthal stress is negative (i.e. compressional) from the equator, up to the critical latitudes (~ ±48.2°), and positive poleward. This means two major tectonic provinces: in the equatorial region a strike-slip province and towards the poles, a normal fault province (Denis & Varga, 1990).

From the 1960s reliable seismological catalogues are available. ISC GEM Catalogue contains re-computed moment magnitude (Mw) values, what is essential for calculating the released seismic energy, since at higher magnitudes, it doesn’t go into saturation. One can obtain the energy released by an event with the formula logE = 5.2 + 1.44Mw (Båth, 1966). Based on this catalogue, a 52-year period with moment magnitudes higher than 5.8, all in all 8799 events were used.

Our study shows that the effect of the despun Earth is reflected in the latitudinal distribution of earthquake energy, which is symmetric with respect to the equator and there are clear maxima at mid-latitudes. The distribution of seismic energy released by either normal fault or strike-slip earthquakes also follow a pattern previously described. Especially on the northern hemisphere normal fault events occur dominantly towards the poles while strike-slip earthquakes tend to happen at lower latitudes. We can conclude that tidal friction actually creates the proposed stress field on Earth, and is visible if we observe how global seismicity behaves with respect to latitude.

Båth, M. (1966). Earthquake energy and magnitude. Physics and Chemistry of the Earth, 7, 115-165.

Denis, C., Varga, P. (1990). Tectonic consequences of the Earth’s variable rotation, In: Brosche P, Sündermann J (eds.) Earth rotation from eons to days. Springer, pp. 146-162.

Stacey, F. D. (1992). Physics of the Earth, Brookfield Press, Australia, ISBN 0-646-09091-7.

How to cite: Fodor, C. and Varga, P.: Relationship between temporal variation of Earth's flattening and spatial distribution of global earthquake energy, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2608, https://doi.org/10.5194/egusphere-egu22-2608, 2022.

Since 2014, total station-based QDaedalus astrogeodetic measurement systems have been used to observe astronomical latitudes and longitudes to determine the astrogeodetic deflection of the vertical (DoV). In this study, the Leica Nova MS60 MultiStation-based QDaedalus system’s precision was determined at the HEIG-VD test station, located on the university campus in Yverdon-les-Bains, Switzerland. The data were collected over 13 nights (in an observation period of 44 days from February-April 2021), and comprise 115 series of observations performed over 26 sessions. The term “series” here describes the DoV data obtained during a specified period; QDaedalus observations were executed at ~15 minutes per series, and up to seven series of observations were conducted per session. The standard deviations (SDs) were calculated as 0.11″ and 0.09″ for the N-S and E-W components of the DoV, respectively. The SDs of the results from the HEIG-VD test station show that the N-S DoV components are not as precise as the E-W DoV components. There is a systematic trend in the observed N-S DoV data; the spread of the data in the N-S direction (0.92″) is larger than in the E-W direction (0.71″). The large trend in the N-S direction may be explained by the 0.008″/day trend (0.38″ over the 44-day observation period) in the N-S DoV components; however, this will require further investigation.

This study is the most extensive thus far for determining the precision of the QDaedalus astrogeodetic measurement system. We can conclude that the precisions of the two components lie on the same order of magnitude of 0.1″. These results and the applied method show that the MS60-based QDaedalus system is at least as reliable as the previously-reported total station-based QDaedalus systems. As a result, the MS60-based QDaedalus system can be used effectively in astrogeodetic applications that require high precision. Also, this study demonstrates that astrogeodetic test observations can be conducted at the HEIG-VD test station to determine the precision of newly installed QDaedalus systems.

How to cite: Albayrak, M., Willi, D., and Guillaume, S.: A Performance Analysis of the Leica MS60 MultiStation-Based QDaedalus Astrogeodetic Measurement System at the HEIG-VD Test Station, Switzerland, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2610, https://doi.org/10.5194/egusphere-egu22-2610, 2022.

The quality of a geodetic network is classically determined with the precision criteria computed from the cofactor matrix of the unknown parameters. One of the precision criteria having more information compared to the Helmert position error and the mean error of the unknown parameters is the Helmert mean error ellipsoid. In two-dimensional networks – and the celestial reference frame realized by extragalactic radio sources can be considered as such - the Helmert mean error ellipse consists of three parameters which are the semi-major and semi-minor axis of the error ellipse and the direction of the semi-major axes. In a well-designed geodetic network, the error ellipses should have homogenous structures. In other words, the semi-axes of the error ellipses for all radio sources should be similar. In this study, daily IVS sessions of the CONT17 were evaluated with The Potsdam Open Source Radio Interferometry Tool (PORT) and the parameters of the Helmert mean error ellipses were computed for the radio sources in each session. Also, the results are compared with the number of observations and the angular position of the radio sources. As a result of this study, it can be seen how the precision criteria are affected depending on the angular position of the radio sources.

How to cite: Küreç Nehbit, P., Glaser, S., Lunz, S., Heinkelmann, R., Schuh, H., and Konak, H.: Applying Precision Criteria to the Radio Sources in the Daily IVS Sessions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5626, https://doi.org/10.5194/egusphere-egu22-5626, 2022.

A study by Afrasteh et al. (2021) has shown that combining model-based hydrodynamic leveling data with data of the Unified European Leveling Network (UELN) has great potential to improve the quality of the European Vertical Reference Frame (EVRF). In the current study, we made our first attempt to actually include the model-based hydrodynamic leveling data as new observations and compute a new realization for the European Vertical Reference System (EVRS). Please note, at this stage our results are provisional and should not be considered as an official realization for EVRS. For the spirit leveling data, we have used the potential differences from UELN, including the third leveling epoch in Great Britain. To generate the model-based hydrodynamic leveling data, 3D DCSM-FM hydrodynamic model that covers the North-east Atlantic Ocean including the North Sea is used to simulate the mean water level for January 1997 to January 2019. The tide gauges records covering the same period have been collected for the North Sea countries to compute the observed water level time series. The difference between observation- and the model-derived mean water level is used to generate the noise model for the hydrodynamic leveling data. We observe an improvement in the precision of the estimated heights in all coastal countries surrounding the 3D DCSM-FM domain. Moreover, our results show that adding model-based hydrodynamic leveling connections significantly reduces the south-north tilt in Great Britain, comparing the EVRF heights with the EGG2015 geoid model. Such a tilt in the British vertical datum, which is caused by a systematic error in the British leveling observations, has been reported in several studies. Our results show that using the model-based hydrodynamic leveling data could solve this problem in the British spirit leveling-based network and provide a stronger tie between Great Britain and other North Sea countries.

Y. Afrasteh, D. C. Slobbe, M. Verlaan, M. Sacher, R. Klees, H. Guarneri, L. Keyzer, J. Pietrzak, M. Snellen, and F. Zijl. The potential impact of hydrodynamic leveling on the quality of the European vertical reference frame. Journal of Geodesy, 95(8), 2021. doi: 10.1007/s00190-021-01543-3.

How to cite: Afrasteh, Y., Slobbe, C., Verlaan, M., Sacher, M., Klees, R., Guarneri, H., Keyzer, L., Pietrzak, J., Snellen, M., and Zijl, F.: New realization for European vertical reference system; a first attempt to include the hydrodynamic leveling data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6136, https://doi.org/10.5194/egusphere-egu22-6136, 2022.

The Laplace operator has a relatively simple structure in terms of spherical or ellipsoidal coordinates which are frequently used in geodesy. However, in treating the geodetic boundary value problem the physical surface of the Earth substantially differs from a sphere or an oblate ellipsoid of revolution, even if optimally approximated. Therefore, an alternative between the boundary complexity and the complexity of the coefficients of the Laplace partial differential equation governing the solution is discussed. The situation is more convenient in a system of general curvilinear coordinates such that the physical surface of the Earth (smoothed to a certain degree) is imbedded in the family of coordinate surfaces. The idea is close to concepts followed also in other branches of engineering and mathematical physics. A transformation of coordinates is applied. Subsequently, tensor calculus is used to express the Laplace operator in the system of new coordinates. The structure of the Laplacian is more complicated now, but in a sense it represents the topography of the physical surface of the Earth. Finally, the Green’s function method together with the method of successive approximations is used for the solution of the geodetic boundary value problem expressed in terms of the new coordinates. The structure of iteration steps is analyzed and where useful and possible, modified by means of integration by parts. The iteration steps and their convergence are discussed and interpreted, numerically and in terms of functional analyses.

How to cite: Holota, P. and Nesvadba, O.: Structure of the Laplace operator, geometry of the Earth’s surface and successive approximations in the solution of the geodetic boundary value problem, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9362, https://doi.org/10.5194/egusphere-egu22-9362, 2022.

We present results for geodetic SAR which is a technique in the field of geodesy and remote sensing that enables the localization of specifically designed radar targets. It might help to connect the GNSS network to tide gauge stations and then to link the sea level records of tide gauge stations to the geometric network. In further perspective it will also enable the determination of vertical movements of the Earth's crust at these stations, allowing the estimation of the absolute value of sea level changes in various regions of the world, which are important in the study of climate change. In order to investigate the feasibility of using active SAR transponders ESA Project Baltic+ Theme No. 5. ‘Geodetic SAR for Baltic Height System Unification and Baltic Sea Level Research (SAR-HSU)’ was completed in 2019 – 2021 by international consortium. During the project SAR novel active transponders were located around the Baltic Sea. Among the locations, two transponders were placed in Wladyslawowo and Leba, Poland under the care of the Space Research Centre of the Polish Academy of Sciences (SRC PAS).

The installation of permanent radar targets allows for long-term position monitoring. The technique is a particularly interesting for displacement and height changes observations. The research illustrates the results acquired from the electronic corner reflectors operating in Poland. For purpose of this research SAR images captured by the Sentinel-1 are used as ESA offers unrestricted access to all the data acquired at study region. Level 1 SLC products together with geodetic data are the main input for the study. With a repeat cycle of 6 days, the number of Sentinel-1 SAR observations per test site amounts to about 180 measurements for one year.

We present the outcomes of ECR positioning from July 2021 to January 2022 when further tests of active transponders were conducted beyond the end of the project. The research is carried out with the software developed in SRC PAS and designed for purposes of geodetic SAR. Software consists of several modules e.g. for data preparation (including SAR data, EOP, precise orbits, ionosphere and troposphere models) or for processing data related to geodynamic effects and corrections to radar measurements. Here we present results for Absolute Location Error in the azimuth and range. We show our experience in processing data for active transponders and our comments on their maintenance and exploitation.

How to cite: Kur, T., Zdunek, R., Nastula, J., Gisinger, C., and Śliwińska, J.: Geodetic SAR – the use of electronic corner reflectors in Wladyslawowo and Leba, Poland, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9425, https://doi.org/10.5194/egusphere-egu22-9425, 2022.

Geodetic boundary-value problems (BVPs) and their solutions represent an important tool for describing and modelling potential fields such as the Earth’s gravitational field. Solutions to spherical geodetic BVPs lead to spherical harmonic series or surface convolution integrals with Green’s kernel functions. New BVPs have recently been formulated reflecting development of sensors. BVPs have been also developed for observables measured by kinematic sensors on moving platforms, i.e., airplanes and satellites. Solutions to BVPs for higher-order derivatives of the gravitational potential as boundary conditions are represented by multiple integral transforms. For example, solutions to gravimetric, gradiometric and gravitational curvature BVPs are represented by two, three and four integral transforms, respectively. Theoretically, each of the nine transforms provides an identical value of the gravitational potential, but practically, when discrete noisy observations are exploited, they provide different estimates. Combination of solutions to the above mentioned geodetic BVPs in terms of surface integrals with Green’s kernel functions by a spectral method is investigated in this contribution. It is assumed that the first-, second- and third-order directional derivatives of the Earth’s gravitational potential can be measured at the satellite altitude. They are downward continued to the Earth’s surface and converted into height anomalies. Thus, the spectral combination method serves in our numerical procedure also as the downward continuation technique. The spectral combination method requires deriving corresponding spectral weights for all nine estimators. A generalized formula for evaluation of spectral weights for the estimators is formulated. Properties of spectral combinations are investigated in both spatial and spectral domains.

How to cite: Pitoňák, M., Šprlák, M., and Novák, P.: Combination of integral transforms by spectral weighting – an overview , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9610, https://doi.org/10.5194/egusphere-egu22-9610, 2022.

Theoretically, solving the geodetic boundary-value problems, we don't need any height systems to include them into integral equations. E.g. so called telluroid and the normal gravity on it are determined not by the normal height itself, but by the curvilinear coordinates of the points with the normal geopotential difference equal to the real geopotential difference. The length of the normal forceline, determining normal height value, is secondary. Similarly, gravity anomalies include normal gravity, determined also by the same geopotential difference in normal field.

Practically, using of the measured geopotential differences in geodesy is uncomfortable, since the corresponding levelling staff would have the variable step of the measuring scale, depending on the position of the point on the earth's surface and in space. Comparison and standardization of that staff is impossible. Then all the height systems we introduce to convert the geopotential values into the linear measure are non-optimal.

To determine the geoid at the same time with the orthometric height, the three only practically ways are possible (first fig.).

First way is the vertical spirit levelling, when the gravimeter is lowered into a vertical well and readings are taken from it at equal distances (a). The point with the geopotential number equal to zero will show us the point “on” the geoid, the rope length is the orthometric height. The second way is similar to the first with the spirit levelling along the paths on the walls of the quarry (b). The third way is a mechanical construction of a tunnel, the floor of which starts from the sea level and is built at a constant zero elevation (c).

Even if we know the upper crust mass distribution (with accuracy we need we must consider it completely unknown), the difficult volume integrals must be calculated for any benchmark.

The normal height is determined when M. S. Molodensky (1945) formulate his integro-differential equation (p. 55 of the English translation): “we compute the [curvilinear] coordinate q corresponding to the known potential of the real Earth..., neglecting the disturbing potential and the deflection of the vertical – an obvious first approximation”. In other words we may reformulate this, that the normal height is the ortometric height in the normal field. Moreover, the role of the geoid in normal field plays the level ellipsoid, not the quasigeoid (second fig.)!

In general, we don't need in “quasigeoid” in any physical or geometrical meaning, e.g. for the height measuring, as a “brother” of the geoid or in the BVP solving. So, strictly speaking, the quasigeoid is not a “vertical reference surface”, and the normal heights they are counted/measured not from ellipsoid nor from quasigeoid. The height mark is calculated and assigned as a “passport value” to each point of the earth’s surface.

How to cite: Popadyev, V. and Rakhmonov, S.: Some remarks about orthometric and normal height systems, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10246, https://doi.org/10.5194/egusphere-egu22-10246, 2022.

Spherical harmonic transforms aiming at degrees as high as a few tens of thousands are vital in geodesy to improve our knowledge of the Earth's gravity field.  A prominent example is spectral gravity forward modelling of topographic masses, which is able to approximate fine gravity field structures up to the sub-km-level and beyond (degree ~20,000 and higher).  Driven by these applications, we have developed CHarm, a C library to perform spherical harmonic transforms.  CHarm is centered around (but not limited to) high-degree expansions, say, well beyond degree 2700.  Its goal is to be numerically stable on the one hand, while achieving reasonable computational efficiency with minimized memory requirements on the other hand.  Supported are surface spherical harmonic analysis and solid (3D) synthesis, both with point and area-mean data values.  Standard quadratures due to Gauss--Legendre and Driscoll--Healy are implemented for exact harmonic analysis of point data values.  The library can be compiled in double precision or, in case higher numerical accuracy is sought, in quadruple precision.  For efficient FFT transforms along the latitude parallels, the state-of-the-art FFTW library is employed to boost the performance.  Unique to CHarm is a routine integrating solid spherical harmonic expansions on band-limited undulated surfaces.  It can deliver, for instance, area-mean potential values on planetary surfaces.  Available are also routines to compute Fourier coefficients of Legendre functions and integrals of a product of two spherical harmonics or of two Legendre functions over a restricted domain.  To utilize the power of multicore processors, CHarm can be compiled with enabled parallelization on shared-memory architectures (OpenMP).  A significant effort is put into the documentation of the library (HTML, PDF) to allow its easy use.

In this contribution, we discuss the motivation behind the development of CHarm, explain its main functionalities and demonstrate some usage case studies.  Within a high-degree closed-loop synthetic environment, we assess the numerical accuracy, the computational speed and the memory management of the library.  A discussion on the future work closes the contribution.  CHarm is available at https://edisk.cvt.stuba.sk/~xbuchab/charm/doc/index.html.

How to cite: Bucha, B.: CHarm: C library to work with spherical harmonics up to almost arbitrarily high degrees, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11206, https://doi.org/10.5194/egusphere-egu22-11206, 2022.

Global Navigation Satellite Systems (GNSS) play a critical role for providing real-time positioning and navigation services, and the precise satellite orbit and clock products are essential for the high-precision GNSS applications. The International GNSS Service (IGS) and its Analysis Centers (ACs) have been working on the study on precise GNSS data processing and provision of the precise products. The German Research Center for Geosciences (GFZ), as one of the ACs, also provides the multi-GNSS rapid products: the GBM product. We introduce the GBM data processing strategy, analyze the precision of GBM multi-GNSS orbits from 2015 to 2021, and present the impact of applying the undifferenced ambiguity resolution on satellite orbits. The GPS orbits of GBM products agree with the IGS final orbits at the level of 11-13 mm in the three directions, and the GPS orbit 6-hour prediction precision is around 6 cm. The 6-hour prediction precision of GLONASS is around 12 cm, slightly worse than that of GALILEO, which hold an average value of 10 cm in the same period but shows a significant improvement to around 5 cm after end of 2016. The prediction precision of BDS MEO satellites are around 10 cm, and that of the BDS GEO satellites and QZSS satellites are at the level of 1 to 3 meter. The Satellite Laser Ranging (SLR) residuals show that the orbit precision of GALILEO, GLONASS, and BD3-MEO is 23 mm, 41 mm, and 47 mm, respectively. Moreover, comparing the double-differenced ambiguity resolution, adopting the undifferenced ambiguity resolution improves the 6-hour orbit prediction precision by 9-15%，15-18%，11-13%，6-17%和14-25% for the GPS, GLONASS, GALILEO, BDS-2 and BDS-3 MEO satellites, respectively.

How to cite: Deng, Z., Wang, J., and Ge, M.: The GBM Rapid Product and the Improvement from Undifferenced Ambiguity Resolution, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-794, https://doi.org/10.5194/egusphere-egu22-794, 2022.

Since 2010s, many companies such as SpaceX, OneWeb, Amazon and Samsung showed their interests to launch hundreds and even thousands of low Earth orbit (LEO) satellites for global internet service. Due to their unique characteristics compared to medium Earth orbit (MEO) and geostationary Earth orbit (GEO) satellites, these LEO mega-constellations soon draw much attention from the scientific community. Studies from constellation design, to applications such as positioning, ionosphere modelling and gravity recovery are investigated by many researchers.

Orbit determination is a key to many applications. Traditionally, onboard Global Navigation Satellite System (GNSS) receivers are used to determine LEO satellite orbits. However, with thousands of satellites in space in the future, an independent system without relying on GNSS is worth to be studied. Since these LEO satellites are intended for internet service, connections between the satellites and to the ground are available by nature. But how would the distribution of a station network affect the orbit accuracy? How many stations would be sufficient to determine a precise orbit? Besides observations from ground stations, inter-satellite link (ISL) is also proposed and implemented by many current GNSSs. It already showed its potential to improve the orbits. Could this technique also be applied to the orbit determination of LEO satellites?

This simulation study investigates the influence of ground station distribution to orbit determination, as well as the benefit from ISL observations. By using a constellation with 60 LEO satellites, we show that for regional station networks, a high latitude network leads to worse orbit accuracy than a middle or low latitude network. With the help of ISL observations, orbit errors reach the same level as a global station network. We further investigate the influence of different number of stations contained in the network. The results prove that although increasing the station number could improve orbits, the improvement is minimal when the global network contains more than 16 stations. While for a regional network, even with 60 stations, the orbit errors are 1.5 times larger than for a small global network with 6 stations. This proves that the ground station distribution is more important than the number of observations. Furthermore, if the ISL technique is adopted, even a regional station network with 16 stations could be sufficient to determine an accurate orbit.

How to cite: He, X., Hugentobler, U., Schlicht, A., Nie, Y., and Duan, B.: Influence of ground station network distribution on orbit accuracy of low Earth orbit (LEO) satellites, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1607, https://doi.org/10.5194/egusphere-egu22-1607, 2022.

The precise orbit determination (POD) of Low Earth Orbiters (LEO), e.g. the Copernicus Sentinel Earth observation satellites, relies on the precise knowledge of the Earth gravity field and its variations with time. The most precise observation of time-variable gravity on a global scale is currently provided by the GRACE-FO satellites. But the monthly gravity field solutions are released with a latency of approx. 2 months, therefore they cannot be used for operational POD.

We present a deterministic signal model (DSM) that is fitted to the time-series of COST-G combined monthly gravity fields and describe the differences with respect to the available long-term gravity models including seasonal and secular time-variations. To validate the DSM, dynamic POD of the Sentinel-2B, -3B and -6A satellites is performed based on long-term or monthly gravity field models, and on the COST-G DSM. We evaluate the model quality on the basis of carrier phase residuals, orbit overlap analysis and independent satellite laser ranging observations, and study the limitation on orbit altitude posed by the reduced spherical harmonic resolution of the monthly models and the DSM.

The COST-G DSM is updated quarterly with the most recent GRACE-FO combined monthly gravity fields. It is foreseen to apply a sliding window approach with flexible window length to allow for an optimal adjustment in case of singular events like major earthquakes.

How to cite: Meyer, U., Peter, H., Lasser, M., and Jäggi, A.: The new COST-G deterministic signal model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1614, https://doi.org/10.5194/egusphere-egu22-1614, 2022.

The use of CubeSats is expanding in space and earth science applications due to the low costs of building and the possibility of launching them in a large low-earth orbits (LEO) constellation. Such constellation can serve as an augmentation system for positioning, navigation and timing. However, real-time precise orbit determination (POD) is still one of the challenges for this application. Real-time reduced-dynamic POD requires more processing capability than what is available in current CubeSats, and the kinematic POD highly depends on the number and the quality of the signals from Global Navigation Satellite Systems (GNSS). In this study, an approach is proposed to increase the orbital accuracy by implementing the precise inter-satellite ranges in the Kinematic POD. The precise orbits of a set of CubeSats from the Spire Global constellation that are determined using the reduced-dynamic POD is to be used to generate the precise inter-satellite ranges. These ranges vary from hundreds to thousands of kilometres and are constrained in the relative kinematic POD between the tested CubeSats. The results, which depend on the length of the inter-satellite ranges, show the improvement of the orbital accuracy in all directions. An initial architecture for implementing such a method in a smart CubeSats constellation is proposed and the limitations and remedies are discussed.

How to cite: Allahvirdi-Zadeh, A. and El-Mowafy, A.: The impact of precise inter-satellite ranges on relative precise orbit determination in a smart CubeSats constellation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2215, https://doi.org/10.5194/egusphere-egu22-2215, 2022.

Day-boundary orbit comparison is one of the criteria used to assess the performance of GNSS orbits. The overall statistics of orbit discontinuities such as RMS are usually computed to assess dynamical modeling and the processing configurations. Additional information about the systematic orbit errors is also accessible through their spectral content.

A particular feature is the flicker or 1/f noise describing the low-frequency band, indicating time-correlated orbital errors. This type of noise is observed not only in the orbits but also in other GNSS-derived geodetic time series such as in station positions, Earth rotation parameters,... The sources explaining this feature, either from the GNSS orbit modeling or from unaccounted orbital perturbations, are not well understood. By computing simulated orbits, we look at possible causes in the orbit determination processing.

How to cite: Ait-Lakbir, H., Santamaria, A., Perosanz, F., and Ray, J.: Investigation of the flicker nature of the day-boundary differences of GNSS orbits, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2383, https://doi.org/10.5194/egusphere-egu22-2383, 2022.

An accurate model of all the forces acting on a satellite is an essential precondition of achieving high orbit accuracy. Solar radiation pressure (SRP), the largest non-gravitational perturbation for GNSS satellites is typically modeled by an empirical model (i.e., Empirical CODE Orbit Model, ECOM/ECOM2). If satellite metadata information is available, an analytical box-wing model can be formed to reinforce the ECOM models. However, the current GNSS satellite orbits show notable degradation during eclipse seasons in particular for long-arc solutions and orbit predictions. The reason is proven to be mostly due to the ignoring of the thermal imbalanced forces (i.e., radiator emission and thermal radiation of solar panels). The ECOM parameters can compensate these thermal radiation forces fairly well outside eclipse seasons, while this is not true when satellites are inside eclipse seasons, because the Earth’s shadowing of a satellite in orbit causes periodic changes of the thermal environment. On one hand, these thermal imbalanced forces contribute also inside the shadow while inside the shadow all the ECOM parameters are deactivated. On the other hand, satellite attitude could be far from the nominal inside the shadow, making that these thermal imbalanced forces cannot be well absorbed by the ECOM parameters. To capture these thermal forces, we set up physical thermal force models for each Block type of GNSS satellites. In the absence of published thermal properties, we estimate necessary thermal modeling parameters using tracking data over long time period. With the use of the physical thermal force models, satellite orbits inside eclipse seasons are greatly improved. For instance, orbit misclosures are improved by a factor of two for BDS-3 and Galileo satellites when using the 5-parameter ECOM model.

How to cite: Duan, B. and Hugentobler, U.: Impact of thermal imbalanced radiation forces on GNSS satellite orbits, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2832, https://doi.org/10.5194/egusphere-egu22-2832, 2022.

Observing Earth-orbiting satellites additionally to natural extra-galactic radio sources with Very Long Baseline Interferometry (VLBI) radio telescopes offers a variety of new possibilities and allows expanding the research activities of this highly accurate technique. The combination of observations to satellites and quasars permit the determination of the satellite orbit from VLBI observations in the terrestrial as well as in the International Celestial Reference Frame. The latter is enabled by the unique capability of VLBI to determine Universal Time UT1.

In this contribution for the first time, the precision of short satellite orbital arcs determined with simulated VLBI observations to Galileo satellites for different observation geometries using various VLBI networks and arc lengths is investigated. For this purpose, schedules including both, observations to quasars and satellites, are created using the scheduling software VieSched++. The simulations of the scheduled observations and the estimation of the satellite arcs are carried out using the Vienna VLBI and Satellite Software (VieVS). The quality of the estimated orbits is investigated and assessed based on the mean formal errors and the repeatabilities of the individual components of the satellite positions based on Monte Carlo simulations. 

How to cite: Wolf, H., Böhm, J., Nothnagel, A., Hugentobler, U., and Schartner, M.: Precision of Galileo satellite orbits obtained from simulated VLBI observations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4834, https://doi.org/10.5194/egusphere-egu22-4834, 2022.

The Copernicus POD (Precise Orbit Determination) Service is a consortium responsible for providing orbit products and auxiliary data files from the Copernicus Sentinel-1, -2, -3, and -6 missions to the corresponding Payload Data Ground Segment (PDGS) processing chains at ESA and EUMETSAT. Products and data are also made available to external users through the ESA Copernicus Open Access Hub.

Sentinel-6 Michael Freilich launched in November 2020 is the newest satellite in the Copernicus POD Service operations. A near real-time orbit product computed based on GNSS data is delivered to EUMETSAT, acting as backup the DORIS DIODE aboard. For the first time, a combined GPS and Galileo receiver is used for POD. In addition, the satellite is equipped with a DORIS receiver and a Laser Retro Reflector for Satellite Laser Ranging (SLR). Additional GPS observations usable for POD are delivered from the POD antenna of the GNSS-RO (radio occultation) instrument. All these observations allow for various cross-comparisons between orbits from the different observation techniques and instruments. The quarterly and yearly Regular Service Reviews include validation of post-processed Sentinel-6 orbit solutions from various members of the Copernicus POD Quality Working Group (QWG).  

This contribution focuses on post-processed POD based on the combined GPS & Galileo receiver and validation with SLR done at the Copernicus POD Service. Precise orbits may be derived as single-system or combined solutions. Integer ambiguity resolution is a key technique to obtain highest accuracy orbits.

Precise orbit determination results from GPS-only, Galileo-only and combined GPS & Galileo observations with resolved integer ambiguities are presented. Cross-comparison between the different solutions, SLR validation, and comparison to other orbit solutions provided by members of the Copernicus POD QWG are shown and analysed.

How to cite: Fernandez Sanchez, J., Peter, H., Fernandez, M., Femenias, P., and Andres, Y.: Sentinel-6 Orbit Determination at the Copernicus POD Service, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4985, https://doi.org/10.5194/egusphere-egu22-4985, 2022.

G4S_2.0 is a project funded by the Italian Space Agency aiming to perform a set of Fundamental Physics measurements using the two Galileo FOC satellites GSAT0201 (Doresa) and GSAT0202 (Milena). Indeed, the orbits of these satellites are characterized by a relatively high eccentricity, about 0.16, which represents a good prerequisite for a series of tests and measurements concerning the predictions of different theories of gravitation, as compared with the General Relativity (GR) ones. The main objectives include a new measurement of the gravitational redshift effect of the on-board atomic clocks --- thanks to its modulation with the orbital period due to the high eccentricity of the orbits --- and the measurement of the main precessions of relativistic origin, primarily the Schwarzschild one.

To achieve these significant results, and possibly improve the current constraints of several theories of gravitation with respect to GR, it is of fundamental importance to take a step forward --- compared to the state of the art --- in the reliability of the dynamic model used for the orbits of the satellites and, as a direct consequence of this, in their precise orbit determination (POD). In this context, non-gravitational perturbations (NGPs) are the most subtle and difficult to model because of the complex shape of the Galileo satellites and their attitude law. In this regard, the main challenge is represented by a more refined and reliable model for the direct solar radiation pressure (SRP), the largest NGP on Galileo satellites, as well as on every satellite of every GNSS constellation.

Our final goal is to build a finite element model (FEM) of the Galileo FOC spacecraft, as refined as possible, and apply a dedicated raytracing technique to it to compute the perturbing accelerations due to radiation pressure. In view of this, we have already developed a 3D-CAD model of the spacecraft. As an intermediate step, we have built a Box-Wing (BW) model based on the relatively poor information presently available on the geometrical and physical properties of the spacecraft. This BW model has been used to compute the perturbing accelerations due to the direct SRP and to the Earth's albedo and infrared radiation.

The results obtained for the accelerations, to be included in the POD process, will be presented in various cases. Then, by computing the residuals in the orbital elements, it will be possible to verify the goodness of the POD results and observe the expected progressive improvement starting from the BW model towards the FEM one. The present analyses were made using the nominal attitude law of the Galileo FOC spacecraft; the application of this law will be discussed in the case of satellites in elliptical orbit. We finally highlight that the results of G4S_2.0 in terms of POD improvements are particularly useful for all applications of the Galileo FOC satellites in the fields of space Geodesy and Geophysics.

How to cite: Lucchesi, D., Cinelli, M., Di Marco, A., Fiorenza, E., Lefevre, C., Loffredo, P., Lucente, M., Magnafico, C., Peron, R., Santoli, F., Sapio, F., and Visco, M.: The Galileo for Science (G4S_2.0) project: Precise Orbit Determination for Fundamental Physics and Space Geodesy, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5884, https://doi.org/10.5194/egusphere-egu22-5884, 2022.

The constellation of China’s BeiDou navigation satellite system (BDS) has been fully constructed since July 2020 and provides open services for worldwide users. Due to the natural sensitivity of satellite technique to geocenter motion, BDS has the capability to determine the time series of geocenter coordinates (GCCs). The purpose of this study is to assess the impact of solar radiation pressure (SRP) modeling on the BDS-derived geocenter motion. To that end, 3-year sets of daily GCCs have been determined with data of BDS. The data was recorded over the period 2019-2021 by a global network of 93 iGMAS stations. Different SRP models including the empirical CODE orbit model (ECOM/ECOM2) and the a prior box-wing model have been applied for BDS geocenter estimation, respectively. We find that under the purely empirical SRP model, the peak-to-peak amplitude of geocenter z-coordinates (GCC-Zs) can reach to 10 cm. In additional, IGSOs would bring obvious jumps to GCC-Zs during earth eclipse periods. The introduction of an a priori box-wing model can largely mitigate the spurious signals in the spectra of GCC-Zs, presenting (13.0, 4.5, 2.1, 2.4) mm for the amplitude of the 1, 3, 5, 7 cpy signals, compared to (26.2, 5.9, 1.2, 2.0) mm in the ECOM case. However, the jumps brought by IGSOs still remains, which could be caused by distortion of optical properties. Therefore, we simultaneously estimate the optical properties together with other parameters in the processing. This model, known as a prior adjustable bow-wing model (ABW), appears to improve the orbit modeling in the eclipsing season and eliminate the negative influence of IGSOs on GCC-Zs, which is reflected in the decrease of spurious signal at periods other than annual one and the amplitude of the 1, 3, 5, 7 cpy signals for GCC-Zs are (16.2, 3.8, 1.4, 0.3) mm. The ABW solution is thus closer to the geocenter motions determined with other space-geodetic techniques.

How to cite: Huang, S., Yuan, Y., Zhang, K., and Li, X.: Geocenter motions derived from BDS: The impact of solar radiation force model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6796, https://doi.org/10.5194/egusphere-egu22-6796, 2022.

Neutral gas atmosphere bends and delays propagation of microwave signals in satellite-based navigation. Weather prediction models can be used to estimate these effects by providing 3-dimensional refraction fields for signal delay computation. In this study, a global numerical weather prediction model (Open Integrated Forecasting System (OpenIFS) licensed for Academic use by the European Centre for Medium-Range Weather Forecast) is used to generate the refraction fields. The slant delays are produced using a Least Travel Time (LTT) ray-tracer. Finally, the GNSS satellite orbits are solved using the GROOPS (Gravity Recovery Object Oriented Programming System) software toolkit of the Technical University of Graz which applies the raw observation method. Specifically, our implementation supplies the slant delays directly to the orbit solver without an intermediate mapping step, i.e., mapping of zenith delay to a prescribed functional form of azimuth and elevation angles. Essentially, this removes the assumption that signal delays follow some functional form, and allows hence to take full advantage of local refraction field asymmetries in GNSS signal processing that are partially lost in the mapping procedure. Our results indicate that this has clear benefits, both in terms of accuracy of the tropospheric correction and stream-lining the information flow in GNSS processing. Our view is that this new framework exposes the synergies in space geodesy and meteorology better than the earlier approaches.

How to cite: Navarro Trastoy, A., Strasser, S., Tuppi, L., Vasiuta, M., Motlaghzadeh, S., Poutanen, M., Mayer-Gürr, T., and Järvinen, H.: Tropospheric corrections in GNSS orbit determination without the mapping step, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6929, https://doi.org/10.5194/egusphere-egu22-6929, 2022.

The Copernicus Sentinel Earth observation satellites provide crucial earth observation measurements, e.g., sea surface-height. It is of highest importance that the underlying precise orbit determination (POD) of these low Earth orbiters (LEOs) is of high accuracy. The POD is based on observations from Global Navigational Satellite Systems (GNSS). All Sentinel satellites collect measurements from the Global Positioning System (GPS), whereas Sentinel-6A additionally collects measurements from the Galileo system. To achieve highly accurate POD, it is of crucial importance to have exact knowledge of the phase center position of the LEO receiver antenna for both the GPS and Galileo measurements. The phase center position is composed of the antenna reference point (ARP) and frequency-dependent phase center offsets (PCOs) and phase center variations (PCVs). It is known that the pre-launch characterization of the LEO receiver antennas is difficult and corresponding estimates are therefore less precise than those of the ARP. This makes it necessary to apply in-flight determined corrections to the initial pre-launch values of the PCO.

Previous studies have shown that there are deficits in the PCOs of the Sentinel-1 GPS antennas. For example, different estimates of empirical orbit parameters of similar satellites point to such deficits. The aim of this study is to determine corrections to the currently used PCOs of the Sentinel-1,2,3 and 6A satellites and to investigate their variability and reliability. Initial results show that non-negligible corrections result for the PCOs of the satellites studied.

The estimation of the corrections of the PCOs is performed as part of the POD process, which is performed with the Bernese GNSS software. The application of single receiver ambiguity resolution is necessary because it improves the stability of the estimated PCOs. It is of high importance that the modeling of non-gravitational forces acting on the satellite is as accurate as possible because modeling deficits may degrade the estimation of PCOs. The influence of such modeling deficits on the PCO estimation is investigated in this study. The estimation of PCO corrections can thus serve to not only get a better accuracy of observation modelling, but also to identify potential non-gravitational force modeling deficits.

Since the Sentinel-1,2,3 satellites are identical in construction in pairs (A and B), a direct comparison of the estimated corrections of the PCOs is possible. This can serve as a measure for the plausibility of the PCO correction estimation. Because the Sentinel-3 and Sentinel-6A satellites are altimetry satellites, the radial direction is of particular importance. Therefore, it is important to investigate the possible changes in radial levelling by applying corrections to the PCO. This can be done by analyzing Satellite Laser Ranging (SLR) measurements. The Sentinel-3 and Sentinel-6A satellites are equipped with SLR retroreflectors, which allows for SLR validations, which serves as a reliability test of the PCO correction estimations.

How to cite: Kobel, C., Arnold, D., and Jäggi, A.: Estimation of phase center offset corrections for Sentinel satellites, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7136, https://doi.org/10.5194/egusphere-egu22-7136, 2022.

Low Earth orbiting (LEO) satellites require routine maneuvers to maintain the predefined trajectories. However, spaceborne scientific instruments might suffer from data discontinuities or even anomalies due to instantaneous orbit changes caused by the performed maneuvers. With the advances of spaceborne Global Navigation Satellite System (GNSS) technique, the high-low satellite-to-satellite tracking observations enable us to generate high precision satellite orbits for the nominal orbit operation periods, and more importantly, also for the maneuver periods. This research will outline the recent developments of Precise Orbit Determination (POD) for  maneuvering LEO satellites at the Astronomical Institute of the University of Bern (AIUB). The Sentinel-3 mission, an European Space Agency (ESA) Earth observation satellite formation devoted to oceanography and land-vegetation monitoring, is used as test example.

A prerequisite input for this research is the maneuver information collected by the telemetry measures which clarify the maneuver time span and accelerations. Due to unavoidable in-flight software delays and hardware performance accuracy, the maneuver information may not be perfect and needs to be improved  in the POD process. Essentially two solutions are made in this research: a. estimating the full accelerations or corrections to the known maneuver accelerations, b. estimating instantaneous velocity pulses at the requested epochs. Both algorithms are tested using the Bernese GNSS Software and POD performances for the maneuver days during 2018-2020 will be assessed. Results reveal that the post-fit carrier phase residuals can be significantly reduced, ensuring better internal consistency between the reduced-dynamic and kinematic orbit solutions. Besides, a few institution members from the Copernicus POD Quality Working Group (QWG) have been routinely generating orbit products for the maneuver days, allowing for the direct cross-validations with our new AIUB products. This research implies promising benefits to the Sentinel-3 POD and scientific research community.

How to cite: Mao, X., Arnold, D., and Jäggi, A.: Precise orbit determination for the maneuvering Sentinel-3 satellites, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7335, https://doi.org/10.5194/egusphere-egu22-7335, 2022.

The Y-bias as present on most global navigation satellite system (GNSS) spacecraft plays an important role in precise orbit determination and prediction. Accurate knowledge about the Y-bias and its temporal variability is particularly relevant for the Galileo system in order to fulfil its once-in-a-lifetime station-keeping maneuver requirements. Despite the widely recognized importance, however, no consensus has been reached on the physical mechanism that is responsible for the Y-bias. In this presentation, we shed light on the origins of the Galileo Y-bias using temperature and attitude data series from spacecraft telemetry to analytically determine Y-bias time histories for different Galileo satellites. We start by calculating the thermal radiation pressure forces generated by the two surface radiators at the main body's +Y and -Y sides of satellite GSAT0204 over a period of five years, from the activation of the spacecraft's search and rescue payload in early 2016 to the deactivation of its navigation payload in December 2017 and beyond. The net force from both radiators yields the Y-bias as it evolves over time, with some striking discontinuities due to abrupt changes in the amount of dissipated heat after the payload units have been turned on or off. Comparison against empirical Y-bias estimates from satellite laser ranging long arc analyses proves the correctness of our Y-bias model. In addition, we report on yearly variations in the Y-bias acceleration of GSAT0101 between -0.10 nm/s² and +0.05 nm/s², leading to a secular increase in the satellite orbit's semi-major axis since January 2016. Yaw error measurements from the spacecraft's fine sun sensor (FSS) spanning 2016-2019 provide compelling evidence that these Y-bias variations originate from an attitude-related mispointing of the satellite's solar panels by a few tenths of a degree. Least square fitting of the FSS measurements led to the development of a refined yaw model for GSAT0101. As a result of this new model, estimates of the Y-bias parameter are significantly reduced in magnitude and less dependent upon the position of the sun relative to the orbit plane. Overall, our analyses provide the first hard evidence that the Galileo Y-bias is primarily of thermal origin and, contrary to popular belief, that solar panel orientation errors only play a secondary role. The implications for precise orbit determination will be discussed. In addition, our results confirm the long-standing hypothesis that Y-bias and solar panel orientation error are linearly related.

How to cite: Dilssner, F., Gonzalez, F., Schönemann, E., Springer, T., and Enderle, W.: GNSS Satellite Force Modeling: Unveiling the Origins of the Galileo Y-bias, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7653, https://doi.org/10.5194/egusphere-egu22-7653, 2022.

The number of low Earth orbit (LEO) satellites equipped with Global Navigation Satellite System (GNSS) receivers is rapidly increasing. GNSS observations in space are no longer limited to a small number of Earth observation satellites, but the rapid development of large nanosatellite constellations enables a dense network of GNSS observations around the Earth. An example of this is the Astrocast CubeSat constellation, to which we contribute with our low-cost multi-GNSS payload board. The first 10 satellites of the Astrocast constellation have successfully been launched on 24 January 2021 (5 satellites) and 30 June 2021 (5 satellites). Further Astrocast CubeSats equipped with dual-frequency GNSS receivers will be launched in the coming years, completing a constellation of 100 satellites by 2024.

The formation of a homogeneous and highly dynamic GNSS network in space holds great potential for geodetic Earth observation, as it has some advantages over a ground-based GNSS network and GNSS observations on board single or formation-flying satellites: A space-based GNSS network can be autonomously processed in a double-difference mode without the need for ground observations, thus, GNSS signals are not affected by tropospheric refraction, and it provides a better observation geometry improving the sensitivity to certain geodetic parameters. In this study, we investigate the feasibility of forming such a space-based GNSS network for estimating geodetic parameters, namely the orbit parameters of the LEO and GNSS satellites, the antenna phase center corrections of the GNSS satellites, and the low-degree coefficients of the Earth’s gravity field including the geocenter coordinates.

We consider 3 different constellation scenarios: (1) A LEO constellation of 36 satellites uniformly distributed over 6 orbital planes with an inclination of 55° and (2) the expected configuration of the complete Astrocast constellation, with sun-synchronous polar orbits and equatorial orbits. In both cases (1) and (2), the GNSS observations are simulated with the Bernese GNSS software based on the given orbit specifications. (3) In a third scenario, we use real GNSS observations from various existing Earth observation missions, including GRACE, OSTM/Jason-2 and Swarm, which are combined to a pseudo-constellation.

For each scenario, the number of possible GNSS single- and double-differences and the corresponding baseline lengths will be computed. Based on these observations, we will examine, how well carrier-phase ambiguities can be resolved and how this depends on the constellation configuration. With a network processing of GNSS double-difference observations, we will estimate concrete parameters related to the LEO orbits, the GNSS antenna phase center corrections and the Earth’s gravity field. To estimate the expected accuracy for these parameters, we examine their sensitivity to small errors in the observation data resulting from, e.g., the force model, once-per-revolution parameters, stochastic pulses or small accelerations like ocean tide or Earth albedo effects. Based on this research, we will draw conclusions about the potential of large satellite constellations to complement or replace the existing geodetic Earth observation missions in the future.

How to cite: Müller, L., Chen, K., and Rothacher, M.: Formation of a GNSS network in space based on LEO satellite constellations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7681, https://doi.org/10.5194/egusphere-egu22-7681, 2022.

At the last EGU and AGU conferences, we have proposed and demonstrated the feasibility of a laser GNSS receiver in the LEO orbit in order to provide carrier-phase measurements on a CW laser between a LEO satellite and GNSS satellites equipped with SLR arrays. This is a novel approach in space geodesy for precise orbit determination (POD) of LEO satellites and the gravity field mapping from space. Considering that the wet delay in signal propagation is typically 67x smaller for optical than for microwaves, we have extended this laser GNSS receiver to laser occultation for atmosphere sounding where use of a modulation on a CW laser could be applied to combine this method with the GNSS radio-occultation (GNSS-RO). In that case, one could compare in LEO orbit microwave GNSS measurements and CW laser measurements between a LEO and GNSS satellites from the top of the atmosphere down to the clouds and the lower troposphere.

Here we propose to further extend the laser GNSS approach in space geodesy, and to demonstrate the combination of a CW laser and GNSS measurements with a ground parabolic antenna of about 60 cm diameter. The CW laser and the receiving photodiode is to be placed in the optical center and collocated with the phase center of the parabolic GNSS antenna. If the same parabolic mirror is used as an antenna to track laser and microwave GNSS measurements to a single GNSS satellite in the zenith direction, all geometry effects can be removed (geometry-free), ending up with the Galileo satellite clock and GNSS receiver clock parameter being the only parameters of such a geometry-free ground-to-space optical/microwave metrology link for Galileo. Considering that optical frequency of a CW laser, stabilized by an internal cavity, can be provided with the frequency stability of <7×10^-16, it can be transformed into a microwave band (with frequency comb) and with the same level of stability used as a reference frequency of the GNSS receiver. Therefore, one can use optical frequency of a CW laser via microwave Galileo signal to compare frequency of Galileo satellite clocks or optical clocks in the timing labs. Atmosphere effects for optical band (CW laser) can be applied a priori, whereas for microwave GNSS, troposphere zenith delays (TZDs) need to be estimated with the noise level of about a few millimeters in the zenith direction. Therefore, by selecting one Galileo satellite, close to zenith from two optical clocks on the ground, all Galileo satellite-related errors will be removed including Galileo satellite clock parameter, and time and frequency of optical clocks could be compared at the 10^-17 - 10^-18 frequency uncertainty level. This opens up the possibility of using Galileo by the timing labs for the generation of the official time (TAI, UTC) and for metrology in space, along with the laser GNSS applications in LEO orbit for POD and atmosphere sounding that very nicely complement the microwave GNSS.

How to cite: Svehla, D.: Laser GNSS Receiver for LEO POD, Laser Occultation and Time & Frequency Transfer of Optical Clocks in the Timing Labs, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12288, https://doi.org/10.5194/egusphere-egu22-12288, 2022.

GNSS velocities estimated by different analysts can significantly differ due to the choices made concerning the GNSS data processing (corrections applied and noise level of the series), the completeness of the series, the removed position discontinuities and the alignment to a terrestrial reference frame. The position discontinuities that populate the GNSS time series have probably the biggest impact on the error or dispersion of the velocity estimates at the same sites. Even when using exactly the same position series, different analysts may provide different velocity estimates and uncertainties mainly due to the choice of removing different position discontinuities.

The IAG Joint Working Group 3.2 (2019 – 2023) aims at providing a global combined GNSS velocity field that takes into account the repeatability, the alignment and the relative weighting of the velocity estimates by different groups. We expect that this IAG’s unified GNSS velocity field will be useful for the scientific community inside, but especially outside, the geodetic community in areas such as tectonics, sea-level change and GIA modeling among others.

In this contribution, we present the current status of the global combined velocity field, aligned to the recently released ITRF2020, and based on the velocity fields provided by several other groups.

How to cite: Santamaría, A., Rietbroek, R., Frederikse, T., Rebischung, P., and Legrand, J.: Towards an IAG combined global GNSS velocity field, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1183, https://doi.org/10.5194/egusphere-egu22-1183, 2022.

The current international and regional reference frame research is mainly realized by single GPS (Global Position System) technology. With the full deployment of BDS (Beidou Navigation System), it is urgent to study and establish the corresponding terrestrial reference frame. Since 2019, the global and regional BDS service performance has been evaluated and tested, and the long-term BDS observations of MGEX (Multi GNSS Experiment) sites distributed worldwide provide the possibility for the preliminary construction of the BDS terrestrial reference frame. We aim to preliminarily realize and evaluate the CTRF2020 (COMPASS/BDS Terrestrial Reference Frame at the epoch of 2020.0) that can be expressed with the coordinates and velocities of a series of reference sites at the epoch of 2020.0. Firstly, the actual BDS global service performance evaluation reflects BDS satellite's high visibility and change trend in recent three years, which provides primary input data for the frame. Then, the BDS observations of about 100 global sites in the recent three years are calculated by PPP (Precise Point Positioning) and NET solution, to obtain the global high-precision BDS coordinate time series. Then, the BDS time series of the two solutions are fitted and compared with the IGS14 velocity field. The results show that the series accuracy of PPP-BDS and NET-BDS solutions is equivalent, and there is an mm-level systematic deviation with IGS14 solutions. The horizontal series fitting accuracy of PPP-BDS and NET-BDS solutions is better than that of the vertical direction, the accuracy of NET-BDS solution is slightly better than PPP-BDS, and the difference of fitting accuracy is 0.12, 0.13, and 0.50 mm in the NEU direction. The velocity field accuracy of PPP-BDS and NET-BDS solution is the same, and the overall three-dimensional velocity difference is less than 0.2 mm/a. The velocity fields of PPP-BDS and NET-BDS solution have little difference from IGS14, and the overall difference is less than 0.5 mm/a. Finally, we give the limitations and improvement points of CTRF2020. The preliminary realization and evaluation of CTRF2020 may be expected to provide a reference for the future realization of a comprehensive terrestrial reference framework dominated by BDS technology and supplemented by multi-source space geodetic technology.

How to cite: ren, Y., wang, H., and wang, J.: The preliminary realization and evaluation of BDS3 global terrestrial reference framework (CTRF2020), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1394, https://doi.org/10.5194/egusphere-egu22-1394, 2022.

In historical versions of the International Terrestrial Reference Frame (ITRF), the time evolution of station positions was described by piece-wise linear models. These kinematic models have been extended with exponential and logarithmic functions in ITRF2014 to account for post-seismic displacements, then with annual and semi-annual sine waves in ITRF2020 to account for the seasonal deformation of the Earth. However, part of the Earth’s surface deformation, such as inter-annual hydrological loading deformation, or high-frequency atmospheric loading deformation, is still not captured by such deterministic functions.

A reference frame in the form of a time series could allow such aperiodic displacements to be taken into account. This would require the aperiodic motions sensed by the different space geodetic techniques to be tied in a common frame by means of co-motion constraints. However, common aperiodic displacements between co-located space geodetic stations have not been evidenced at a global scale so far, and the relevance of such constraints is thus debatable. In this study, in order to investigate the possible existence of common aperiodic displacements at ITRF co-location sites, we use the solutions provided by the technique services for ITRF2014. Those solutions are first carefully aligned to a common reference frame in order to minimize differential network effects and obtain comparable position time series across techniques. The obtained position time series are then cleaned from linear, post-seismic and periodic signals (including seasonal deformation and technique systematic errors). The remaining aperiodic displacements are finally inter-compared at co-location sites.

Modest correlations are thus evidenced between the GNSS residual position time series and the other space geodetic techniques, mostly in the vertical component. The magnitude of the common aperiodic displacements evidenced in this study is finally discussed.

How to cite: de La Serve, M., Rebischung, P., Altamimi, Z., Collilieux, X., and Métivier, L.: Study of common aperiodic displacements at ITRF co-location sites, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2985, https://doi.org/10.5194/egusphere-egu22-2985, 2022.

JPL's newly developed software for determining terrestrial reference frames, known as SREF (Square-root REference Frame filter), has been used to produce JTRF2020, a combined terrestrial reference frame determined from the input SINEX files submitted by the IVS, IGS, ILRS, and IDS for ITRF2020. SREF, being based upon a square-root information filter and smoother, determines the reference frame sequentially from the input station position time series. Incorporating process noise in SREF, determined from geophysical fluid loading models, allows the observed station positions to be smoothed between discontinuities caused by earthquakes and equipment changes. Reference frames determined by SREF, like JTRF2020, are represented by this set of smoothed station position time series. SREF also fits a model (consisting of a piecewise linear trend, annual and semi-annual periodic terms, and a sum of exponential terms to represent postseismic motion) to the station's observations and uses the model to fill gaps in the station's observing history, to forecast the position of the station after it stopped observing, and to hindcast its position before it started observing. The result of using SREF to determine JTRF2020 will be presented.

How to cite: Gross, R., Abbondanza, C., Chin, T. M., Heflin, M., and Parker, J.: A Sequentially Estimated Terrestrial Reference Frame: JTRF2020, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3221, https://doi.org/10.5194/egusphere-egu22-3221, 2022.

We examine DORIS (Doppler Orbitography and Radiopositioning Integrated by Satellite) position time series processed by the IDS (International DORIS Service) within “ids21wd02” reprocessing, serving as an official input into the newest International Terrestrial Reference Frame, namely ITRF2020. The ids21wd02 set includes the North, East and Up coordinate time series of the 201 stations located at the 87 DORIS sites since 1993.0. These coordinate time series were delivered by the IDS as a byproduct of the IDS contribution to the 2020 realization of ITRF (International Terrestrial Reference Frame). From a number of 201 stations distributed globally, we choose a number of 115 sites, whose time series are longer than 5 years.  Position time series are carefully pre-processed by means of removing outliers and offsets. To reliably describe the DORIS position time series, we use a time series model of long-term non-linear signal, linear trend, seasonal oscillations and a stochastic part. Both deterministic and stochastic components are determined using maximum likelihood estimation. Our analysis is performed in three different ways. Firstly, we search for a preferred noise model and demonstrate, that there is an ongoing improvement of noise parameters over years. This is related to the persisting improvement in background models, antenna types, etc. Then, both deterministic and stochastic parameters are compared to the ITRF2014 IDS solution, to find the usefulness of a newly applied models or strategies, especially to prove an impact of the new C STAREC antenna type. Finally, we compare DORIS position time series to the GPS (Global Positioning System) position time series for a number of 267 co-located stations (official input of International GNSS Service into ITRF2020); both deterministic and stochastic components are compared, with a special attention paid to the differences of velocities and their errors, as they are employed for kinematic reference frames realization or in geodynamical interpretations.

How to cite: Bogusz, J., Klos, A., and Moreaux, G.: Assessment of IDS contribution to ITRF2020, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3417, https://doi.org/10.5194/egusphere-egu22-3417, 2022.

In the context of the 2020 realization of the International Terrestrial Reference Frame, the three IERS Production Centers (DGFI, IGN and JPL) delivered three independent solutions from the contributions of the four space geodetic techniques (DORIS, GNSS, SLR and VLBI). Even if these three ITRF2020 realizations are based on the same input, they differ on several points such as the space geodetic techniques weighting, the coordinate time series discontinuities and on the modelling of the station displacements.

In this study, we use the coordinate time series of the two hundred DORIS stations from 1993.0 to 2021.0 as benchmark to investigate the characteristics of the three ITRF2020 realizations. This set of DORIS station positions correspond to the 1456 weekly solutions delivered by the International DORIS Service (IDS) as the DORIS contribution to the ITRF2020.

After presentation of the overall performance of these three TRF realizations in terms of geocenter, scale and mean velocities, we assess the quality of the weekly restitution of the DORIS station positions by the DTRF2020, ITRF2020 and JTRF2020 solutions. Then, we make benefit of the almost complete year (2021) since the ending of the ITRF2020 time period to evaluate these three 2020 ITRF solutions in terms of prediction of the DORIS station positions.

How to cite: Moreaux, G.: DORIS Assessment of the 2020 ITRF Realizations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3897, https://doi.org/10.5194/egusphere-egu22-3897, 2022.

More than 30 years of space geodetic data have been reprocessed
by the International Association of Geodesy technique services
and submitted to compute the new realization of the
International Terrestrial Reference System (ITRS). The new
realization, ITRF2020, is intended to replace ITRF2014. It is
provided in the form of an augmented reference frame so that in
addition to station positions and velocities, parametric
functions for both post-seismic deformation (PSD) and seasonal
signals (expressed in the Center of Mass frame derived from
Satellite Laser Ranging data) will also be delivered to the
users. The presentation summarizes the main results of ITRF2020
analysis and evaluates its internal consistency via some key
performance indicators. In particular, the paper discusses the
level of the scale agreement between the four techniques, its
linear and nonlinear time evolution, and the strategy adopted
for the ITRF2020 scale definition. In addition, we evaluate the
performance of the parametric functions for both seasonal
signals and PSD and the level of consistency between the four
techniques at colocation sites.

How to cite: Altamimi, Z., Rebischung, P., Collilieux, X., Metivier, L., and Chanard, K.: ITRF2020: main results and key performance indicators, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3958, https://doi.org/10.5194/egusphere-egu22-3958, 2022.

The deviations of phase center offsets (PCOs) of GPS satellites were and still are significant bias sources for GPS-based terrestrial reference frames (TRF). Because of the strong correlation between the scale of the TRF and the satellite PCOs in the z-direction (z-PCOs), a no-net-scale (NNT) condition relative to, for instance, the International Terrestrial Reference Frame (ITRF) is commonly applied. Based on the released Galileo metadata, the GPS z-PCOs have been calibrated without introducing a scale determined by other techniques in the third re-processing of the International GNSS Service (IGS). Another approach purely based on GNSS is by integrating low Earth orbiters (LEOs) into the estimation of the GPS z-PCOs and the realization of the scale. Within this study, we estimated the GPS z-PCOs based on zero-difference ionosphere-free observations from six low LEOs and ground networks with different numbers of stations in 2019 and 2020. Besides the study based on six LEOs in two years, a twelve-year-based estimation of GPS z-PCOs and scale realization is done by using the two satellites of the GRACE mission.

We jointly estimate orbits (GPS and LEOs), station coordinates, z-PCOs of GPS satellites, and some other parameters in an integrated processing. The NNT condition on the ground network is not applied in the processing. By adding six LEOs, the correlation coefficients between the GPS z-PCOs and the scale is reduced significantly (from about 0.85 to 0.30). It means that the GPS z-PCOs and the scale have been decorrelated efficiently, and consequently the precision of the estimation is improved. For GPS satellites operated in 2019 and 2020, excluding GPS III, their estimated z-PCOs have an average difference of -231 mm compared to the values in igs14_2134.atx and the corresponding scale to the IGS14 reference frame is +1.89 part per billion. These results agree well with the solutions based on the metadata of Galileo. The improvement due to different numbers of LEOs and the impact of LEO z-PCO errors on the estimation is studied, where more LEOs decorrelate the GPS z-PCOs and the scale more efficiently. The accuracy of the LEO z-PCOs is critical to the solution. A one-millimeter accuracy of the z-PCOs of the LEOs is required to achieve a one-millimeter scale on the surface of the Earth. Thanks to the long-term available data of LEO missions in the last decade and even longer, the LEO-based method has an advantage on the real-data-based estimation of PCOs of former GPS satellites over the Galileo-based method. The z-PCOs of satellites of GPS blocks IIA, IIR, IIRM, and IIF are estimated by integrating the two GRACE satellites from 2004 to 2015. A twelve-year scale relative to the ITRF is realized simultaneously. The performance of the LEO-based method is shown by the long-time series.  

How to cite: Huang, W., Männel, B., Brack, A., and Schuh, H.: LEO-based solution of GPS PCOs and impact on terrestrial scale, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4436, https://doi.org/10.5194/egusphere-egu22-4436, 2022.

The ITRF2020 is the upcoming realization of the International Terrestrial Reference Frame. As the successor of the ITRF2014, it is based on an inter-technique combination of all four space-geodetic techniques, i.e., VLBI, GNSS, SLR and DORIS, and it is based on contributions from different institutions around the world. In this context, the Combination Centre of the International VLBI Service for Geodesy and Astrometry (IVS) – operated by the Federal Agency for Cartography and Geodesy (BKG, Germany) and the Deutsches Geodätisches Forschungsinstitut (DGFI-TUM, Germany) – generates the VLBI intra-technique combination for ITRF2020 utilizing the individual contributions of multiple IVS Analysis Centres (AC).

For the contribution to the ITRF2020 solution, sessions containing 24h VLBI observations from 1979 until the end of 2020 are reprocessed by 11 ACs and submitted to the IVS Combination Centre. All individual sessions include datum-free normal equations containing station coordinates and source positions as well as full sets of Earth Orientation Parameters (EOP) in the required SINEX format. For ensuring consistently combined solutions, time series of EOP and station coordinates, as well as a VLBI-only Terrestrial Reference Frame (VTRF), have been investigated.

This contribution focuses on detailed investigations concerning the session-dependency of the scale and the impact of the individual AC contributions to the combination. Thereby significant differences of the scale estimates from the different session types are investigated. Also, the evaluation of the ACs’ contributions to the combined solution will be presented.

How to cite: Hellmers, H., Modiri, S., Bachmann, S., Thaller, D., Bloßfeld, M., Seitz, M., and Gipson, J.: Evaluation of the IVS contribution to the ITRF2020, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5116, https://doi.org/10.5194/egusphere-egu22-5116, 2022.

The member ACs of the ILRS Analysis Standing Committee—ASC, evaluated the preliminary release of ITRF2020—ITRF2020P.  For the most part, this evaluation is based on the reanalysis of part or all of the SLR data from geodetic spherical targets in the model; in particular, we focused on the two LAGEOS and two Etalons from 1993 to the end of 2020, extended by one year of data NOT included in the model: all of 2021. The evaluation report was submitted to ITRS for consideration in the finalization of the ITRF2020 model. Some ACs used additional data that do not contribute to ITRF development for testing. The reanalysis used the same improved modeling that was used for the development of the ILRS contribution to ITRF2020.

We will focus on the implementation of the new approach in handling systematic errors at the stations and how users will need to adapt their data analysis procedures to benefit the most from the new model. The 2021 ILRS contribution to ITRF2020 minimized the scale difference between SLR and VLBI below 2 mm (ITRF2014 ~9 mm). The reanalysis incorporates an improved “target signature” model (CoG) for better separation of true systematic errors from errors in describing the target’s signature. This model will be periodically updated from now on, so that it represents accurately the state of operations at all sites in the ILRS network of tracking stations. SLR data users should make sure from now on to use each ITRF model with the appropriate (consistent) Data Handling file and “target signature” model.

The presentation will provide an overview of the analysis procedures and models, and it will demonstrate the level of improvement with respect to the previous ILRS product series, focusing especially on the Core ILRS sites.

How to cite: Pavlis, E. C., Luceri, V., Basoni, A., Sarrocco, D., Kuzmicz-Cieslak, M., Evans, K., and Bianco, G.: The ILRS Analysis Centers’ Report on the Evaluation of ITRF2020P, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5212, https://doi.org/10.5194/egusphere-egu22-5212, 2022.

The release of the next International Terrestrial Reference Frame (ITRF) 2020 is based on the four geodetic techniques, namely Satellite Laser Ranging (SLR), Very Long Baseline Interferometry (VLBI), Global Navigation Satellite Systems (GNSS), and Doppler Orbitography and Radio-positioning Integrated by Satellite instrument (DORIS). The upcoming release will presumably define the scale based on the first two techniques.

The GNSS scale is mainly driven by the z-component of the satellite antenna phase center offsets. With the disclosure of the Galileo metadata by the European GNSS Agency (GSA) the satellite antenna pattern became available to the public and enabled the GNSS scale determination.

We aim to analyze the consistency between the preliminary ITRF 2020 solution and the GNSS based scale. In addition, we will extend our study with all available TRF solutions and compare their consistency with the GNSS derived scale and discuss the resulting comparisons. 

How to cite: Villiger, A., Dach, R., Prange, L., Arnold, D., Kalarus, M., Schaer, S., Stebler, P., and Jäggi, A.: Compatibility between the preliminary ITRF2020 solution and GNSS antenna phase center offsets, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5530, https://doi.org/10.5194/egusphere-egu22-5530, 2022.

Temporally and spatially correlated noise has long been reported in Global Navigation Satellite System (GNSS) station position time series. Accounting for the temporal correlations of the noise is crucial to obtain realistic uncertainties for deterministic parameters, e.g., station velocities, while accounting for its spatial correlations is beneficial to various applications such as offset detection, velocity estimation and detection of local geophysical signals. The origins of the spatio-temporally correlated noise in GNSS series are however still unclear, and a realistic spatio-temporal noise model also remains to be elaborated. In this study, we therefore analysed GNSS residual time series from the International GNSS Service (IGS) third reprocessing (repro3), corrected from loading deformation models, with the purpose of characterizing and modeling their spatio-temporal correlations in detail.

We first estimated spectral correlation coefficients as a function of both the distance between GNSS stations and the temporal frequency. Different spatial correlation regimes could thus be evidenced for different frequency bands. Spatial correlations are in particular higher, and range longer distances, at the frequencies of the periodic (e.g., draconitic, fortnightly) errors in GNSS time series. Broadband spatial correlations are consequently reduced when these periodic errors are filtered out from the series.

To investigate possible spatial non-stationarities of the noise, we then estimated its spatial covariance, as a function of the distance between stations, over different regions. While the estimated spatial covariance is similar to the global average in Europe, Eastern US and Australia, it is consistently higher in Eastern South America, New Zealand and Western US. This may point to a partially geophysical origin of the spatially correlated noise in the latter regions, possibly attributable to unmodeled hydrological loading and tectonic deformation, respectively.

We finally converted the globally averaged spatial covariance of the residual repro3 series into a spatial power spectrum, i.e., power as a function of the spherical harmonic degree. It thus turns out that the average spatial covariance is well described by a spatial power-law model attenuated at the lowest degrees.

How to cite: Niu, Y., Rebischung, P., Altamimi, Z., Wei, N., and Li, M.: Analysis of spatio-temporal correlations of IGS repro3 station position time series, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5578, https://doi.org/10.5194/egusphere-egu22-5578, 2022.

The international celestial and terrestrial reference frames (ICRF and ITRF) are two important realizations of the global geodetic reference frame (GGRF). As the basis for high-accuracy astrometry and space exploration, ICRF is currently determined by the Very Long Baseline Interferometry (VLBI) technique solely and independently from the ITRF, whereas a consistent determination of TRF and CRF by a combination of different techniques is highly desirable. We conduct the Global Navigation Satellite Systems (GNSS) and VLBI integrated processing on the observation level and investigate the impact of applying global ties (that is, Earth Orientation Parameters, EOP), local ties, and tropospheric ties on the precision of both TRF and CRF. The GNSS and VLBI observations in VLBI continuous campaigns from CONT05 to CONT17 are processed simultaneously in the common least-squares estimator using the Positioning And Navigation Data Analyst (PANDA) software. We present that the precision of the VLBI station coordinates is significantly improved in the integrated solution, such as the horizontal components by global ties and the vertical components by local and tropospheric ties. Focusing on the precision of active galactic nuclei (AGN) coordinates, we demonstrate that the global ties can slightly reduce the AGN coordinate formal errors by up to 4%, and the local ties mainly improve the declination precision by about 10%. As for the tropospheric ties, the formal error of AGN coordinate can be reduced by 10% on average, and the repeatability can also be improved, especially the declination (10%). Moreover, the southern AGN are more improved than the northern ones, due to the observation geometry of the VLBI ground station distribution.

How to cite: Wang, J., Ge, M., Glaser, S., Balidakis, K., Heinkelmann, R., and Schuh, H.: On the contribution of global, local, and tropospheric ties to TRF and CRF in GNSS and VLBI integrated solution, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6387, https://doi.org/10.5194/egusphere-egu22-6387, 2022.

As one of the ITRS Combination Centres of the IERS, DGFI-TUM is in charge of computing an ITRS 2020 realisation. Since the ITRS 2014 realisation, many innovations have occurred. These include the six years longer observation period, but also new observation stations and satellites, and the use of refined background models in the analysis of the space-geodetic techniques. In addition, the combination strategy of the DTRF has also been improved. Namely, non-tidal loading (NTL) corrections over the full observation period and for all three components (atmospheric, hydrological and oceanic) are taken into account, as well as modelled post-seismic deformations (PSD). Both corrections are carried out - according to the combination strategy of DGFI-TUM - on the level of the normal equation (NEQ) by reducing each input NEQ.

Due to all the improvements mentioned above, ranging from observation to analysis and combination, it can be assumed that all ITRS 2020 realisations are not only more up-to-date but also more accurate than their predecessors. In the presentation, we demonstrate the DTRF2020 solution as well as first comparisons and analyses. We will also present the DTRF2020 release which will include SINEX files and an EOP file, plus the time series of SLR translations, NTL and PSD corrections, and station position residuals.

How to cite: Seitz, M., Angermann, D., Glomsda, M., Bloßfeld, M., Rudenko, S., and Zeitlhöfler, J.: The ITRS 2020 realization of DGFI-TUM: DTRF2020, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6932, https://doi.org/10.5194/egusphere-egu22-6932, 2022.

In this contribution we highlight the challenges of the combination of space geodetic techniques through local ties, during the rigorous estimation of geodetic parameters, for the realisation of a global Terrestrial Reference Frame (TRF). Local ties at geodetic fundamental sites play an important role in the determination of a TRF, providing the necessary links to connect the different geodetic techniques. Moreover, the growing demands on the accuracy and stability of the ITRF, have turned the analysis of the quality of these ties into a crucial element to achieve a highly consistent frame, providing additionally the opportunity to identify technique-specific systematic biases  when comparing the space geodetic results with local measurements.

To study the impact of the local ties at fundamental sites, we use the Very Long Baseline Interferometry (VLBI) observations collected during the CONT17 campaign, together with simultaneous Global Navigation Satellite System (GNSS) observations of a subset of the International GNSS Service (IGS) global network. To this end, our approach performs the rigorous estimation of all parameter types common to the two techniques, namely station coordinates, troposphere zenith delays and gradients, and the full set of five Earth Orientation Parameters (EOPs) and their rates, and we include their full variance-covariance information during the combination process. In the central step of this processing scheme, we realise the GNSS-VLBI combination via the "official" ITRF coordinate ties, using and evaluating different weighting schemes, to obtain a unique set of consistent parameters. Moreover, we study the impact of tropospheric ties between the collocated VLBI and GNSS stations, which are essential for the height estimates. Thus, based on the analysis of the station coordinate repeatabilities and the characteristics and behaviour of the EOPs, we discuss the impact of the accuracy and weighting of the local coordinate and troposphere ties on the estimation of the different geodetic parameters.

How to cite: Herrera Pinzón, I. and Rothacher, M.: Local Tie Analysis at Fundamental Sites in the CONT17 Campaign, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9240, https://doi.org/10.5194/egusphere-egu22-9240, 2022.

The Hermert-like constrain condition is commonly used in various space geodetic reference frame alignment and reference frame definition, this often demands discussions on the proper constrain strength, selection of fiducial network, and more. Thus, the published and constrained reference frame products/solutions are often demanded the transformation to alternative constrain condition due to the area of interest change, reduction of the coverage, or other reasons.

We present an efficient methodology to transform reference reframe product to a posterior selection of the constrained condition from the product which either minimum or redundant datum constraints have been imposed. This analytical methodology significantly reduces the computation effort for datum alignment, especially for the large GNSS network. By avoiding the expensive normal equation system reconstruction and the subsequent inversion thereof, we achieved computational complexity reduction with an inversion of an auxiliary matrix of up to 14X14 dimension, while the computation is validated analytically as well as numerically to the truncation error level. This Fast Constraints Transformation (FCT) method can be conveniently applied to the widely used space geodetic solution files following the Solution Independent Exchange (SINEX) format, especially with our provided software package written in Matlab. We validate and evaluated FCT with two globally distributed GNSS-derived solutions and one South America terrestrial reference frame. The results confirm the numerical equivalence of the classical method and FCT. We also present the discussion on the computation efficiency with the above networks as well as numerical simulations. For the large network of up to 5000 stations, The FCT accelerates the transformation by more than 100 times compared to the classical strategy.

FCT method could serve as a beneficial procedure to many TRF-related applications, including but not limited to:

• Deploy Over Constain condition to an existing solution
• Transforming an Over Constrained solution to a Minimal Constrained solution
• Re-computation of a specified Minimal Constrained solution from an Over Constained or loosely-constrained solution.
• For global networks with a large number of stations the FCT significantly reduces the computation effort.
• For the cases of regional and local TRFs, the methodology shows significant advantages since the final product can be considered an Over Constrain solution.
• FCT could be applied for local and regional networks removing the imposed constraints and deriving the initial GNSS network.

How to cite: Wang, L., Ampatzidis, D., Mouratidis, A., and Balidakis, K.: Solution-Level Fast Constraints Transformations with Case Studies for GNSS Networks, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10229, https://doi.org/10.5194/egusphere-egu22-10229, 2022.

SLR data of LAGEOS-1/2 and Etalon-1/2 satellites were used for generating weekly solution sets containing station coordinates, Earth Rotation Parameters, as well as accommodating systematic range errors, for the period from 1993 to 2020. The solutions follow the approach developed within the ILRS Analysis Standing Committee, with smoothed systematic range errors applied to station range normal points where required. The satellite centre-of-mass corrections developed by Rodriguez et al (2019), and his continuing updates, were applied to the NP ranges. The solutions were used for an evaluation of the ITRF2020P reference frame and to conduct comparisons to ITRF2014. Following our previous investigations into the impact on the scale of the ITRF of systematic range errors, we investigate in particular the difference in scale of the reference frame from our current solutions when mapped using weekly Helmert transformations onto ITRF2014 and onto ITRF2020P.

How to cite: Susnik, A., Appleby, G., and Rodriguez, J.: Evaluation of the ITRF2020P reference frame by means of Satellite Laser Observations (SLR) data analysis, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10320, https://doi.org/10.5194/egusphere-egu22-10320, 2022.

Geodesy Observatory Pecný (GOP) analysis center is one of the International DORIS Service (IDS) analysis centers. GOP fully contributed to the IDS combination of the ITRF2020, reaching various improvements in comparison to the ITRF2014 reprocessing. GOP also participates in the IDS operational solutions. A major progress has been reached in the data preprocessing strategy, South Atlantic Anomaly mitigation and satellite orbit & attitude modeling.  improvements in the internal strategy together with an updating of external models to the recent standards resulted in the significant improvement in the station positioning including of the stability of the transformation parameter time series. Also the pole coordinates estimation accuracy has been increased. This improvement is illustrated comparing the statistics of GOP contributions to the IDS combination for the ITRF2014 and ITRF2020. Important improvement in the GOP processing capability is the adaption of the software tools to the RINEX data processing, getting closer to raw DORIS measurement. In addition, we present initial results of the data processing and a modeling verification for the post-ITRF2020 data from the DORIS satellites Sentinel-6A, HY-2C and HY-2D.

How to cite: Stepanek, P. and Filler, V.: The GOP DORIS analysis center: data processing and innovation strategy, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10401, https://doi.org/10.5194/egusphere-egu22-10401, 2022.

Preliminary results of the ITRF2020 show that the Very Long Baseline Interferometry 
(VLBI) solution appears to have a scale problem, with larger scatter of the scale factor and a 
potential scale drift after around 2014. There are several possible reasons that have been 
brought into discussion, ranging from specific VLBI stations having technical problems to 
the use of various geophysical models in the VLBI data analysis, such as atmospheric 
pressure loading and post-seismic deformation models, and other models to account for, e.g., 
thermal and gravitational deformation of radio telescopes. This work focuses on the impact of 
such reasons on the VLBI scale. We first investigate the VLBI contribution of the Onsala 
Observatory which made used of the software package ASCOT and that enters in the IVS 
combined solution, and we then expand to the IVS combined solution and other individual 
contributions. 

How to cite: Le Bail, K., Nilsson, T., Haas, R., and Nyström Lindé, F.: Investigating the VLBI scale behavior, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13464, https://doi.org/10.5194/egusphere-egu22-13464, 2022.

Precise point positioning (PPP) is an available solution for one-frequency receivers if the ionosphere delay is informed during the data processing. Such information may be retrieved from the ionospheric maps, which can have a global or regional coverage. IGS has traditionally being providing them globally, throughout different analyses centers. On the other hand, regional products have been increasingly catching the interest of the scientific community.  Regional Ionosphere Maps (RIM) will use local active GNSS networks with multi-frequency receivers to model and represent the ionospheric delays. Because of the larger amount of information from a specific region, which may lack in the global products, the representation can be better and show improvements for areas where the ionosphere is more active. For the South American area, studies have been conducted using active networks. GIB (Brazilian Ionospheric Grid) was developed in 2010 and computes regional maps using GPS data from the Brazilian Continuous Monitoring Stations (RBMC). More recently (2018) the Meteorología espacial, Atmosfera terrestre, Geodesia, Geodinámica, diseño Instrumental y Astrometría (MAGGIA) made available its regional product covering the same area using GNSS data from Brazil, Uruguay and Argentina. Presently we are verging to the beginning of the next solar cycle and understanding the availability of global and regional products for ionosphere correction, and its level of accuracy will be a crucial information to be hold. In this contribution, an evaluation of four products was performed using kinematic PPP for the day 80 of 2021, of course with a reduced amount of data. The global products (CODE and GFZ) used the IGS network on its construction. A reference station from RBMC, with known coordinates was used as the ground truth to determine the accuracy of each product using a simulated PPP kinematics. with residuals and needed system transformation the accuracy and precision for each product was acquired. Overall results show that the MAGGIA product presents the best accuracy, followed by the GFZ, IGS and GIB. For this analysis it was possible to conclude that two elements play an important role when creating ionosphere maps: not only the regional characterization but also using multi constellation GNSS data will play a key role in the products quality. MAGGIA and GIB, both regional products, obtained the best and the worse results, respectively and the major difference being the use of only one GNSS constellation (GIB) and multiple GNSS constellations (MAGGIA) for its calculation.

How to cite: Siqueira, L., Francisco Galera Monico, J., and Rodrigues de Aguiar, C.: Assessment of global and regional ionospheric maps over Brazil using simulated kinematic precise point positioning., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-306, https://doi.org/10.5194/egusphere-egu22-306, 2022.

Within the frame of the “Modernization of the Hellenic Gravity Network” project, the homogenization of the Hellenic Vertical Datum is investigated. Two study areas in northern and southern Greece were selected, where the zero-level geopotential value W_o is estimated for each area. Additionally, a combined value is also estimated using a weighted least squares adjustment of Helmert orthometric heights and surface gravity values, that were recently measured, as well as recent global geopotential models. The biases in the vertical datum between northern and southern Greece are investigated through the comparison with a global conventional value. The validation of the results can lead to valuable conclusions on the possibility of a contemporary definition of the Hellenic Vertical Datum.

How to cite: Andritsanos, V. D., Grigoriadis, V. N., Natsiopoulos, D., and Vergos, G. S.: Zero-height geopotential level estimation for the homogenization and modernization of the Vertical Datum of Greece, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-762, https://doi.org/10.5194/egusphere-egu22-762, 2022.

The GGOS Bureau of Networks and Observations works with the IAG Services (IVS, ILRS, IGS, IDS, IGFS, IERS, and PSMSL) to advocate for the expansion and modernization of space geodetic networks for the maintenance and improvement of the reference frame and other applications, as well as for the integration of the techniques.  Of particular interest is the integration of gravimetric and tide gauge networks in view of the forthcoming establishment of a new absolute gravity reference frame and of the International Height Reference System/Frame. New sites are being established following the GGOS concept of “core” and co-location sites, and new technologies are being implemented to enhance performance in data yield as well as accuracy. 

The IAG Committees and Joint Working Groups play an essential role in the Bureau activity. The Standing Committee on Performance Simulations and Architectural Trade-offs (PLATO) uses simulation and analysis techniques to project future network capability and to examine trade-off options. The Committee on Data and Information is working on a strategy for a GGOS metadata system for data products and a more comprehensive long-term plan for an all-inclusive system. The Committee on Satellite Missions is working to enhance communication with the space missions, to advocate for missions that support GGOS goals and to enhance ground systems support. The IERS Working Group on Site Survey and Co-location (also participating in the Bureau) is working to enhance standardization in procedures, outreach and to encourage new survey groups to participate and improve procedures to determine systems’ reference points, a crucial aid in the detection of technique-specific systematic errors.

We will give a brief update on the status and projection of the network infrastructure for the next several years, and the progress and plans of the Committees/Working Groups in their critical role in enhancing data product quality and accessibility to the users, scientists and the general community.   

How to cite: Pearlman, M., Behrend, D., Craddock, A., Pavlis, E., Saunier, J., Barzaghi, R., Bradshaw, E., Carabajal, C., Thaller, D., Maennel, B., Hippenstiel, R., Pail, R., Shum, C., Brown, N., Blevins, S., and Sanchez, L.: An Update on the GGOS Bureau of Networks and Observations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2070, https://doi.org/10.5194/egusphere-egu22-2070, 2022.

Measuring, studying, and understanding global change effects demand unified geodetic reference frames with (i) an order of accuracy higher than the magnitude of the effects to be observed, (ii) consistency and reliability worldwide, and (iii) long-term stability. The development of the International Terrestrial Reference System (ITRS) and its realisation, the International Terrestrial Reference Frame (ITRF), enable the precise description of the Earth’s geometry by means of geocentric Cartesian coordinates with an accuracy at the cm-level and with global consistency. An equivalent high-precise global physical reference system that provides the basis for the consistent determination of gravity field-related coordinates worldwide, in particular geopotential differences or physical heights is missing. Without a conventional global height system, most countries are using local height systems, which have been implemented individually, applying in general non-standardised procedures. It is proven that their combination in a global frame presents discrepancies at the metre level. Therefore, a core objective of the international geodetic community is to establish an international standard for the precise determination of physical heights. This standard is known as the International Height Reference System (IHRS). Its realisation has been a main topic of research during the last years. Recent achievements concentrate on (1) compiling detailed standards, conventions, and guidelines for the IHRS realisation, (2) evaluating computational approaches for the consistent determination of potential differences, and (3) designing an operational infrastructure that ensures the maintenance and long-term stability of the IHRS and its realization. This contribution summarises advances and current challenges in the establishment, realization and sustainability of the IHRS.

How to cite: Sanchez, L., Huang, J., Barzaghi, R., and Vergos, G. S.: Towards an international standard for the precise determination of physical heights, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2523, https://doi.org/10.5194/egusphere-egu22-2523, 2022.

Geodetic observations on Earth accurate to better than a part per billion require a common reference for the same precision as described in the goals of the Global Geodetic Observing System. The International Gravity Reference System (IGRS) is proposed as a new reference for terrestrial gravity observations (Wziontek et al. 2021).

The International Gravity Reference Frame (IGRF) as the realization of IGRS is represented by absolute gravity measurements traceable to the SI. Due to the lack of a natural reference, absolute gravimeters need to be compared and the gravity reference is realized based on a set of measurements by a group of absolute gravimeters and the functional model for their processing.

We present the international comparison of absolute gravimeters WET-CAG2021 hosted at the Geodetic Observatory Wettzell in autumn 2021. This comparison is classified as an additional comparison following the strategy paper of the Consultative Committee for Mass and related quantities (CCM) and IAG. Seven FG5/X absolute gravimeters and two AQG quantum gravimeters have observed up to four individual piers over a period of twelve weeks. The individual observation epochs are connected by recordings of the continuously operating superconducting gravimeter GWR OSG 030 in the same laboratory.

We show the procedure of data analysis following Pálinkáš et al. (2021) and discuss the results also with respect to the latest regional metrological EURAMET comparison 2018 at the same location.

Marti, U., Richard, P., Germak, A., Vitushkin, L., Pálinkáš, V., Wilmes, H.: CCM-IAG Strategy for Metrology in Absolute Gravimetry, 11 March 2014

Pálinkáš, V., Wziontek, H., Vaľko, M. et al.: Evaluation of comparisons of absolute gravimeters using correlated quantities: reprocessing and analyses of recent comparisons. J Geod 95, 21 (2021). https://doi.org/10.1007/s00190-020-01435-y

Wziontek, H., Bonvalot, S., Falk, R. et al.: Status of the International Gravity Reference System and Frame. J Geod 95, 7 (2021). https://doi.org/10.1007/s00190-020-01438-9

How to cite: Rülke, A., Falk, R., Engfeldt, A., Glässel, J., Hellerschmied, A., Iacovone, D., Kostelecký, J., Pálinkáš, V., Reich, M., Timmen, L., Ullrich, C., Valluzzi, A., Wziontek, H., and Zehetmaier, B.: WET-CAG2021: An international comparison of absolute gravimeters for the realization of the International Gravity Reference System, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2964, https://doi.org/10.5194/egusphere-egu22-2964, 2022.

The Bureau of Products and Standards (BPS) is a key component of the Global Geodetic Observing System (GGOS) of the International Association of Geodesy (IAG). It supports GGOS in its goal to provide consistent geodetic products needed to monitor, map, and understand changes in the Earth’s shape, rotation, and gravity field. In addition to the operational structure, the Committees “Earth System Modeling” and “Essential Geodetic Variables” as well as the Working Group “Towards a consistent set of parameters for the definition of a new Geodetic Reference System (GRS)” are associated to the BPS. This contribution presents the structure and role of the BPS. It highlights some of the recent activities, which are focused on the classification of geodetic products and on the generation of user-friendly product descriptions to support the establishment of a comprehensive Internet portal for Geodesy under the responsibility of GGOS. The GGOS website www.ggos.org serves as an “entrance door” and information platform to geodetic data and products, and should become an essential tool to make these data and products easier findable and accessible. With this, GGOS is contributing to address different user needs (e.g., geodesists, geophysicists, other geoscientists and further customers) and to make other disciplines and society aware of Geodesy and the importance of its products.

How to cite: Angermann, D., Gruber, T., Gerstl, M., Heinkelmann, R., Hugentobler, U., Sanchez, L., Steigenberger, P., Heki, K., Schuh, H., and Sehnal, M.: GGOS Bureau of Products and Standards: Description and Promotion of Geodetic Products, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4537, https://doi.org/10.5194/egusphere-egu22-4537, 2022.

RAEGE (Atlantic Network of Geodynamic and Space Stations) is a project resulting from the cooperation between the National Geographic Institute of Spain (IGN) and the Government of Azores. It is a unique project at a geodetic and geodynamic level, in which it is committed to the combination of geodetic techniques in four stations - two in Spain (Yebes and Gran Canaria) and two in Azores (Flores and Santa Maria). Santa Maria and Yebes stations are already fully implemented. The instrumentation foreseen for all four stations and that are currently implemented are radiotelescopes that use the VLBI technique, GNSS receivers, superconductive gravimetries, seismographs, and maser clocks. Furthermore, an SLR system will be shortly installed at Yebes station.

These stations are integrated into the VGOS network and in the Global Geodetic Reference System (GGOS), as multi-technique observatories. These multi-technical observatories are key in the definition of reference systems, as they allow the integration of the individual networks of each technique into a single system. Additionally, they provide an idea of the quality and precision of the systems themselves, thanks to the validation of the results between techniques. Apart from the multi-technique, the uniqueness of the RAEGE project resides in the fact that the four stations will be located on three different tectonic plates, hence their data will be of great importance to understand this triple tectonic junction.

RAEGE not only focuses on providing the necessary infrastructure for observations but also, among its objectives, to promote multi-technical geodetic analysis and obtain studies and results supported by the data collected. The purpose of this contribution is, therefore, to present the current state of the RAEGE project, including the sites and instrumentation, as well as the current analysis activities and prospects, particularly concerning the combination of the techniques present at the stations. 

How to cite: Moreira, M., Azcue, E., Puente, V., García, A., Avelar, D., Martínez, E., Ferreira, J., González-García, J., López-Pérez, J., and Cuambe, V.: RAEGE Project: Status, Analysis Endeavours, and Future Prospects, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8593, https://doi.org/10.5194/egusphere-egu22-8593, 2022.

The Global Geodetic Observing System (GGOS) is a collaborative contribution of the global Geodesy community to the observation and monitoring of the Earth System. Geodesy is the science of determining the shape of the Earth, its gravity field, and its rotation as functions of time. Essential to reaching this goal are stable and consistent geodetic reference frames, which provide the fundamental layer for the determination of time-dependent coordinates of points or objects, and for describing the motion of the Earth in space. With modern instrumentation and analytical techniques, Geodesy is capable of detecting time variations ranging from large and secular scales to very small and transient deformations – all with increasing spatial and temporal resolution, high accuracy, and decreasing latency. The geodetic observational and analysis infrastructures as well as the high-quality geodetic products provide the foundation upon which advances in Earth and planetary system sciences and applications are built. In this way, GGOS endeavors to facilitate and enable production and sharing of the Earth observations needed to monitor, map, and understand changes in the Earth’s shape, rotation, and mass distribution. GGOS also advocates the global geodetic frame of reference as the fundamental backbone for measuring and consistently interpreting global change processes as well as the essential geospatial infrastructure to ensure a homogeneous and sustainable development worldwide.

GGOS closely works with its parent organization, the International Association of Geodesy (IAG), to keep these fundamental geodetic contributions sustainable. The IAG Services provide the infrastructure and products on which all contributions of GGOS are based, and the IAG Commissions and IAG Inter-Commission Committees provide expertise and support to address key scientific issues within GGOS. Additionally, GGOS supports the IAG by strengthening external and interdisciplinary relations and contributions to the broader geospatial information community, including relevant United Nations groups, in particular, the UN Committee of Experts on Global Geospatial Information Management (GGIM), its Subcommittee on Geodesy, and the new UN Global Geodetic Centre of Excellence (scheduled to commence operations in early 2022). The main contribution of GGOS in this regard is to support actions and initiatives to communicate the value of Geodesy to society as well as to help to understand and solve complex issues facing the global geodesy community. Towards this objective, GGOS is developing a comprehensive Geodesy portal (https://ggos.org/) including detailed descriptions of geodetic observations (https://ggos.org/obs/) and products (https://ggos.org/products/), and various outreach tools such as short videos to explain the roles and importance of Geodesy to non-geodesists.

How to cite: Miyahara, B., Sánchez, L., Sehnal, M., and Craddock, A.: The Global Geodetic Observing System (GGOS) - infrastructure for Science and Society -, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9106, https://doi.org/10.5194/egusphere-egu22-9106, 2022.

Geodetic measurements allow the determination of a wide variety of parameters describing the Earth system, including its shape, gravity field, and orientation in space. The importance of such parameters to science and society is manifested through geodetic contributions to the examination of geodynamic phenomena, climate change monitoring and navigation both on the Earth's surface and in space. In a recent effort led by the Global Geodetic Observing System (GGOS), a set of Essential Geodetic Variables (EGVs) has been defined, which are key quantities characterizing geodetic properties of the Earth. Certain requirements have been assigned to EGVs, including accuracy, spatio-temporal resolution, and latency.

For many real-time applications, the latency of geodetic products has become increasingly critical. Forecasts of certain EGVs at various time horizons are needed to accommodate the user's needs for many applications. In addition, spatial prediction of geodetic quantities on standardized grids on global and regional scales are of great benefit to certain scientific disciplines. The Space Geodesy group at ETH Zurich has thus established a new Geodetic Prediction Center (GPC), which aims to produce spatio-temporal predictions of various EGVs by employing state-of-the-art methods and providing them freely to the scientific community and other interested parties.

In the field of time series forecasting and spatial prediction, machine learning (ML) has become increasingly powerful in recent years due to its high accuracy, efficiency in coping with large amounts of heterogeneous data sets, and capability of capturing complex relationships between various data sources. For instance, ML allows to include auxiliary data in geodetic predictions, also in the cases when no mathematical or physical relation is known. The application of ML has demonstrated promising results in terms of geodetic time series prediction and is thus the tool of choice for many of the parameters provided by the GPC. ML methods applied in this framework include tree-based methods such as random forest as well as variants of convolutional and recurrent neural networks. Such a ML-based approach allows to assimilate geodetic measurements, environmental models, and auxiliary data sets with the aim to provide predictions of utmost accuracy.

Currently, ETH Zurich is invested in the prediction of Earth orientation parameters, Earth angular momentum functions, station coordinates, tropospheric zenith wet delays, ionospheric total electron content, and satellite orbits. In this contribution, an overview of these efforts in the framework of the Geodetic Prediction Center will be provided, highlighting the most recent scientific results.

How to cite: Soja, B., Kiani Shahvandi, M., Schartner, M., Gou, J., Kłopotek, G., Crocetti, L., and Awadaljeed, M.: The New Geodetic Prediction Center at ETH Zurich, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9285, https://doi.org/10.5194/egusphere-egu22-9285, 2022.

Satellite Laser Ranging (SLR) is the only one space geodetic technique in which troposphere correction is calculated based on in situ measurements (pressure, temperature, and humidity) and used in the least square adjustment process as a fixed value measured at the epoch of observation.  In the past few years, we observe that the use of malfunctioning barometers for some of the SLR stations significantly affects the SLR-based global geodetic parameter estimates, such as station coordinates, geocenter coordinates, and terrestrial reference frame scale. Thus, we examine different handling of the SLR range tropospheric delay to LAGEOS by analysing the a priori zenith total delay from the standard Mendes and Pavlis (2004) model with a corresponding mapping function, the estimated tropospheric correction, and the range bias parameter. Moreover, we conduct a simulation study of artificial pressure bias, investigating the capability of tested approaches to properly reconstruct the tropospheric error. The new approach based on the estimation of the troposphere delay correction for SLR solutions, which is also widely used in microwave techniques, explicitly demonstrates more suitable handling of errors affecting the SLR station than solutions based on estimation of range biases.

The progress in precise orbit determination of low Earth orbiter (LEO) satellites using GPS demands improvements of the SLR procedures considering their orbit validation, determination of station coordinates, and global geodetic parameters from SLR to LEOs solutions. Within this study, we also consider including the proper handling of range errors in SLR to LEOs. We test solutions incorporating the estimation of tropospheric biases with and without horizontal gradients, range biases, and station coordinate corrections in an example of the SLR observations to LEO Swarm satellites. We discuss the values of estimated corrections and their impact on the solution quality, and dependency of residuals to different measurement conditions, such as elevation angle, azimuth angle, station-satellite distance, or satellite view from a station. Estimating tropospheric biases once-per-day and horizontal gradients, absorbs elevation- and azimuth-dependent errors, provides a reduction of solution statistics, and dependency of SLR residuals for almost all used SLR stations.

How to cite: Strugarek, D., Drożdżewski, M., Sośnica, K., Zajdel, R., and Bury, G.: Estimation of tropospheric biases in SLR to Swarm, and LAGEOS satellites, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9834, https://doi.org/10.5194/egusphere-egu22-9834, 2022.

Over the last two decades, the precision of individual measurements of Space Geodesy improved to a millimeter level. However, the overall achieved accuracy remains at a centimeter level due to systematic errors. The fundamental stations operating more than one space geodetic measurement technique present a keystone in systematic error investigation and mitigation. Due to regular surveys, the distances and mutual movements of the reference points are established with millimeter accuracy. The problem arises in the combination at the observation level, where the residuals of the measurements do not match with the established geometrical ties sufficiently well. Internal instrumental signal delays within each technique are causing this detrimental effect.

We have identified time coherence between the individual techniques and fundamental stations as the proper tool to overcome this problem. Within IAG Project QuGe we examine referencing the instrumentations to the optical clocks. In this scenario, the clock parameter in geodesy does not need to be adjusted any more, and all systematic effects would promote. To transfer clock stability within an entire station campus, we use a mode-locked fs-pulse laser, which is distributed using actively delay compensated fiber links, provides the necessary means to identify and remove these systematic errors. This talk illustrates some results and introduces the novel time distribution system of the Geodetic Observatory Wettzell, which realizes an ideal test bench for these clock ties.

How to cite: Kodet, J., Schreiber, U., Klügel, T., and Eckl, J.: Towards Clock Ties for a Global Geodetic Observing System, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10553, https://doi.org/10.5194/egusphere-egu22-10553, 2022.

Improving and homogenizing time and space references on Earth and, more directly, realizing the terrestrial reference system with an accuracy of 1 mm and a long-term stability of 0.1 mm/yr are relevant for many scientific and societal endeavours. The knowledge of the terrestrial reference frame (TRF) is fundamental for Earth system monitoring and related applications. For instance, quantifying sea level change strongly depends on an accurate determination of the geocenter motion but also of the position of continental or island reference stations, such as those located at tide gauges, as well as the ground stations of the tracking networks. Also, numerous applications in geophysics require absolute millimetre precision from the reference frame, as for example monitoring tectonic motion or crustal deformation for predicting natural hazards. The TRF accuracy to be achieved (mentioned above) represents the consensus of various authorities, including the International Association of Geodesy, which has enunciated geodesy requirements for Earth science (see GGOS-2020). Moreover, as stated in the A/RES/69/266 United Nations Resolution: “A global geodetic reference frame for sustainable development”, the UN recognizes the importance of “the investments of Member States in developing satellite missions for positioning and remote sensing of the Earth, supporting a range of scientific endeavours that improve our understanding of the Earth system and underpin decision-making, and… that the full societal benefits of these investments are realized only if they are referenced to a common global geodetic reference frame at the national, regional and global levels”. These strong statements by international bodies underline that a dedicated mission is highly needed and timely. Today we are still far away from this ambitious goal. It can be achieved by combining and co-locating, on one satellite platform, the full set of fundamental space-time geodetic systems, namely GNSS and DORIS radio satellite tracking systems, the satellite laser ranging (SLR) technique, and the very long baseline interferometry (VLBI) technique, that currently operates by recording the signals from quasars. This platform can then be considered as a dynamic space geodetic observatory carrying all these geodetic instruments referenced to one another on a unique well-calibrated platform through carefully measured space ties and a very precise atomic clock. It is necessary to set up a co-location of the techniques in space to resolve the inconsistencies and biases between them. Such a mission will be proposed as the first one of a series of missions in the GNSS/NAV Science Programme. The purpose of this abstract/talk is to revive the support of the scientific community for this mission.

How to cite: Karatekin, Ö., Dehant, V., Ventura-Traveset, J., Rothacher, M., Delva, P., Hugentobler, U., Altamimi, Z., Boehm, J., Couhert, A., Flechtner, F., Glaser, S., Haas, R., Jaeggi, A., Maennel, B., Perosanz, F., Schuh, H., and Sert, H.: GENESIS-1 mission for improved reference frames and Earth science applications., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10616, https://doi.org/10.5194/egusphere-egu22-10616, 2022.

The “GGOS Working Group on Digital Object Identifiers (DOIs) for Geodetic Data Sets” is entering its third year of regular meetings and discussions to develop best practices, recommendations and advocate for improved global coordination for using DOI to geodetic data and products. The group was established by the International Association of Geodesy’s (IAG) Global Geodetic Observing System (GGOS) and includes international representatives of IAG Services and geodetic data centres and associated members.

Data publications with digital object identifiers (DOI) are best practice for FAIR sharing data. They are fully citable in scholarly literature and many journals require the data underlying a publication to be available. Initial metrics for data citation allows data providers to demonstrate the value of the data collected by institutes and individual scientists. This possibility to get credit for providing data products and running data services has been identified in the group as key requirement for the motivation to implement DOIs to geodetic data.

Our group activities include the collection of data products and discussions on already existing and planned DOI activities for IAG services and geodetic data centres, including for recent projects, like FAIR GNSS. Whenever possible, we recommend that DOIs shall be included in standard data formats (e.g. Rinex) and cited when using the data. This presentation will give an update of the group activities.

How to cite: Elger, K. and the GGOS DOI Working Group: News from the GGOS DOI Working Group, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10982, https://doi.org/10.5194/egusphere-egu22-10982, 2022.

Very Long Baseline Interferometry (VLBI) technique was developed in the 1960s by astronomers, for high angular resolution observations of celestial radio sources. In the late 1970s, it was adopted for high-precision geodetic applications, in a reverse manner. In this application, VLBI is used to monitor the kinematics of individual points on the Earth, and also of the Earth as a body in the space using the precisely known astronomical positions of radio sources. Despite differences between astronomical and geodetic applications, the instrumentation and analysis techniques employed in VLBI are broadly similar, allowing for antennas designed for VLBI to be usable for either application. In this presentation, we describe a proposal for upgradation of three existing communication antennas with 18-m, 30-m and 32-m diameter, located at Arvi, Pune, India, for astronomical and geodetic VLBI purposes. The main objective is to retrofit the antenna with new gearboxes and modern servo control systems to make them compatible for use in VLBI observations, as well as with suitable L, S, and C band receivers and digital recorders, in a short period of time. Each motor will be driven by a drive with close loop precision pointing system, making it suitable to point to and track celestial sources. The antennas will be fitted with suitable antenna feeds and receiver systems, after the analysis of the dish parameters and its mounting possibilities. A development of cooled S-band feed will also be initiated simultaneously. Further, the three antennas will be fitted with new front-end electronics, baseband converter and digital recorders. The observed bandpass with different feeds (S and C band) will be down converted to L-band. This signal will be transported over optical fibre to the Giant Meterwave Radio Telescope (GMRT) facility, which is located nearby, for data recording and correlation activities. The retrofitted instrument will provide a test bed for instrumentation, tuning analysis pipelines and software, while providing the capability to carry out both astronomical and geodetic VLBI experiments with other international facilities.

How to cite: Laha, A., Tiwari, A., Srivastava, S., Singh, S., Joshi, B. C., Balasubramanian, N., Kumar, A., Gupta, Y., and Dikshit, O.: Retrofitting communication antennas for astronomical and geodetic VLBI applications, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13321, https://doi.org/10.5194/egusphere-egu22-13321, 2022.

Surface loading on GNSS stations in Africa

Usifoh Saturday E^1,2,3, Nhung Le Thi^1,2, Benjamin Männel¹, Pierre Sakic¹, Dodo Joseph³, Harald Schuh^1,2
1GFZ German Research Centre for Geosciences, Potsdam, Germany, ²Institut für Geodäsie und Geoinformationstechnik Technische Universität, Berlin, Germany, ³Centre for Geodesy and Geodynamics, Toro, Bauchi State, Nigeria.

 Corresponding author: parker@gfz-potsdam.de

Abstract

The global navigation satellite systems (GNSS) have revolutionalized the ability to monitor the Earth’s system related to different types of natural processes. This includes tectonic and volcanic deformation, earthquake-related displacements, redistribution of oceanic and atmospheric mass, and changes in the continental water storage. As loading affects the GNSS cordinates, we investigated the effect and assessed the impact of applying dedicated corrections provided by the Earth System Modeling group of German Research Center for Geosciences (GFZ). However, loading caused by mass redistribution results in displacement, predominantly with seasonal periods. Significant temporal changes in mass redistribution (e.g caused by climate change) will result to further trends in the station coordinate time series.

In this contribution, we will compare the PPP coordinate time series with the loading-corrected PPP time series by looking at the amplitude and the correlation between the GNSS time series and the model corrections. Also we will compare the PPP coordinate time series with the loading time series by assessing the RMS reduction and change of amplitude.The result shows that loading-induced displacement varies considerably among GNSS stations and applying corrections to the derived time series has favourable impacts on the reduction in the non-linear motion in GNSS height time series of the African stations.

How to cite: Usifoh, S. E., Le, T. N., Männel, B., Sakic, P., Joseph, D., and Schuh, H.: Surface loading on GNSS stations in Africa, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-64, https://doi.org/10.5194/egusphere-egu22-64, 2022.

Hydrological loading is one of the main contributors into seasonal displacements of the Earth’s crust, as derived from the Global Positioning System (GPS) permanent stations. Recent studies proved that hydrological signatures may be also observed in GPS displacements outside seasonal band. Such estimates may be, however, biased, since (1) total character of GPS displacements is generated by a set of geophysical phenomena combined with GPS-specific signals and errors and (2) the exact sensitivity of GPS for individual components has not yet been properly recognized. In this study, we propose a completely new approach to establish a set of benchmarks of GPS stations, for which sensitivity to geophysical phenomena is identified. We focus on hydrological changes within the Amazon basin, but the same approach could be employed to analyze other phenomena. Analysis is performed for vertical displacements from 63 GPS stations provided by the Nevada Geodetic Laboratory (NGL), collected between 1995 and 2021. Results are compared to data from GRACE (Gravity Recovery and Climate Experiment) and GRACE Follow-On missions (2002-2021), provided by GFZ (GeoForschungsZentrum) as RL06 solution in a form of spherical harmonic coefficients truncated to d/o 96, filtered with DDK3 decorrelation anisotropic filter. We also utilize GLWS (Global Land Water Storage) datatset provided by University of Bonn, as a result of assimilation of GRACE Total Water Storage (TWS) anomalies into WaterGAP Global Hydrological Model (WGHM). We make also use of two hydrological models: pure WGHM and GLDAS (Global Land Data Assimilation System), for which TWS values are provided. Both GRACE and TWS data are converted to vertical displacements of Earth’s crust using load Love numbers, while GPS displacements are reduced for non-tidal atmospheric and oceanic changes. We find the largest values of trends and annual signals for GPS stations proximate to Amazon river. GRACE, GLWS and hydrological models disagree at the level of 8 mm, at maximum. This is mainly caused by the GLDAS model which lacks in the contribution of surface water. Supplementing GLDAS with surface water layer employed from WGHM reduces this difference to 1 mm. Benchmarks of GPS stations are established by using a wavelet decomposition with Meyer’s mother wavelet. We divide both the GPS, GRACE and GLWS displacement time series into 4 decomposition levels, defined by exact periods they contain. Then, we compute correlation coefficients between individual levels of details. We show that the number of 32%, 64%, 97%, 89% and 68% out of 63 GPS stations is significantly correlated to GRACE for periods, respectively, from 2 to 5 months, from 4 to 9 months, from 7 months to 1.4 years, from 1.1 to 3.0 years and from 3.0 years onwards. These numbers change into: 48%, 73%, 100%, 81% and 50% out of 63 GPS stations, when GRACE is replaced with GLWS. 12 or 21 out of 63 GPS stations correlate positively with GRACE or GLWS within entire frequency band, which means that a character of these GPS displacement time series is generated mostly by hydrological changes.

How to cite: Leszczuk, G., Klos, A., Kusche, J., Lenczuk, A., Gerdener, H., and Bogusz, J.: Benchmarking Amazonian GPS stations: an improved way to model hydrological changes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-246, https://doi.org/10.5194/egusphere-egu22-246, 2022.

Observed time-series of water transport in rivers can be perceived mathematically as a superposition of non-linear long-term trends, periodic variations, episodic events, colored instrument noise, and other components. Various statistical methods are readily available to extract and quantify both stationary and non-stationary components in order to subsequently attribute parts of the signal to underlying causal mechanisms. However, the available algorithms differ vastly in terms of computational complexity and implicit assumptions, and may thus have their own individual advantages and disadvantages. By employing a suite of time-series analysis methods for 1D (Wavelets, Singular Spectrum Analysis, Empirical Mode Decomposition) and additional statistical assessments like Pruned Exact Linear Time (PELT) tests for change point detection, we will analyze data from two virtual stations at Elbe River (Germany) and Urmia Lake (Iran) that are representative for the central European region with a rather humid climate, and the more arid conditions of Central Asia with much smaller hydrological signal variations, respectively. It is in particular the latter region with a much less developed in situ hydrometeorological observing system, where we expect that carefully processed geodetic data might contribute most to the monitoring of large-scale terrestrial water dynamics. This contribution will highlight the benefits of more advanced signal analysis methods for extracting relevant hydrometeorological information over more conventionally applied algorithms.

How to cite: Iran Pour, S., Eicker, A., Balidakis, K., Karimi, H., Amiri-Simkooei, A., and Dobslaw, H.: Efficiency of different signal processing methods to isolate signature characteristics in altimetric water level measurements, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1449, https://doi.org/10.5194/egusphere-egu22-1449, 2022.

Global and interactively coupled climate models are important tools for projecting future climate conditions. Even though the quality and reliability of such models has increased during the most recent years, large model uncertainties still exist for various climate elements, so that it is crucial to continuously evaluate them against independent observations. Changes in the distribution and availability of terrestrial water storage (TWS), which can be measured by the satellite gravimetry missions GRACE and GRACE-FO, represent an important part of the climate system in general, and the terrestrial water cycle in particular. However, the use of satellite gravity data for the evaluation of interactively coupled climate models has only very recently become feasible. Challenges mainly arise from large model differences with respect to land water storage-related variables, from conceptual discrepancies between modeled and observed TWS, and from the still rather short time series of satellite data.

This presentation will highlight the latest results achieved from our ongoing research on climate model evaluation based on the analysis of an ensemble of models taking part in the Coupled Model Intercomparison Project Phase 6 (CMIP6). We will focus on long-term wetting and drying conditions in TWS, by deriving several hot spot regions of common trends in GRACE/-FO observations and regions of large model consensus. However, as the observational record currently only covers about 20 years, observed trends may still be obscured by natural climate variability. Therefore, to further attribute the wetting or drying in the identified hot spot regions to either interannual/decadal variability or anthropogenic climate change, we investigate the influence of dedicated climate modes (such as ENSO, PDO, AMO etc.) on TWS variability and trends. Furthermore, we perform a numerical model investigation with 250 years of CMIP6 TWS data to quantify the degree to which trends computed over differently long time intervals can be expected to represent long-term trends, and to discriminate regions of rather robust trends from regions of large fluctuations in the trend caused by decadal climate variability.

How to cite: Jensen, L., Eicker, A., and Dobslaw, H.: Attributing land water storage trends from satellite gravimetry to long-term wetting and drying conditions with global climate models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2335, https://doi.org/10.5194/egusphere-egu22-2335, 2022.

Understanding variations in the ocean heat content is tightly linked to understanding interactions of the global energy cycle with the regional water cycle. Mass, volume, temperature and density changes of  the ocean water column can be estimated with complimentary observations of sea surface height from radar altimetry, ocean bottom pressure from Gravity Recovery and Climate Experiment (GRACE), temperature and salinity from Argo floats. These three techniques have their specific deficiencies and advantages, which can be exploited in a joint inversion framework in order to improve temporal and spatial coverage of oceanic temperature and salinity estimates as well as regionally varying sea level contributions. Solving an inverse problem for temperature and salinity, forward operators are formulated linking the satellite observations to temperature and salinity at depth. This is done by (1) parametrization of temperature and salinity profiles over the full depth of the ocean with B-splines to reduce dimensionality while keeping complexity of the data intact and (2) linearization of the integrated density from parameterized T/S curves. We apply forward operators in the East Indian Ocean to resolve for sea surface height, ocean bottom pressure, temperature and salinity, and assess the regional importance of these factors. We explore the stability of a joint inversion using these forward operators in combination with along-track radar altimetry, GRACE and temperature and salinity by exploring a closed-loop inversion.

How to cite: Yakhontova, A., Rietbroek, R., Kusche, J., Stolzenberger, S., and Uebbing, B.: Contributions of ocean bottom pressure and density changes to regional sea level change in the East Indian Ocean from GRACE, altimetry and Argo data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2586, https://doi.org/10.5194/egusphere-egu22-2586, 2022.

The German-American satellite missions GRACE (Gravity Recovery and Climate Experiment) and its successor GRACE-Follow-On (GRACE-FO) observed the unique data set of total water storage (TWS) variations over the continents since 2002. With this nearly 20 years of data, we can investigate trends in water storage beyond the strong declining trends of the ice sheets and glaciers. Unlike all other continents, Africa exhibits an overall positive trend in TWS. This contribution will take a detailed look into Africa's water storage changes and trends. Further, we attempt to explain these trends by comparison to other hydrological observations such as precipitation.

The long-term TWS increase in Africa is most pronounced in the East-African rift centred around Lake Victoria and the Niger River Basin. Other regions such as Madagaskar exhibit a (statistically significant) negative TWS trend. Furthermore, the trends are not monotonous over time. For example, the increasing trend in East Africa only started around the year 2006 and accelerated after 2012. On the other hand, South Africa wetted until 2012 and dried again since then.

This study divides the African continent into climatically similar regions and investigates the regional mean TWS signals. They are more complex than a linear trend and sinusoidal annual and semiannual seasonality; thus, we employ the STL method (Seasonal Trend decomposition based on Loess). In this way, turning points are identified in the so-called trend component to mark significant trend changes.

The observed TWS changes in Africa are caused mainly by changing precipitation patterns, as observed, for example, with the GPCP (Global Precipitation Climatology Project) data set. In some regions, such as South Africa, the correlation between precipitation and TWS change is evident, whereas other areas show a more complex relationship between these two variables.

How to cite: Boergens, E. and Güntner, A.: Trends in Africa’s Terrestrial Water Storage, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3415, https://doi.org/10.5194/egusphere-egu22-3415, 2022.

At the level of a watershed, the conservation of mass imposes that the net moisture transport through the atmospheric boundaries is balanced by the river discharge and an accumulation/depletion in terrestrial sources such as the soil, surface waters and groundwater.

There are considerable uncertainties connected with modelled water balance components, especially since most models only simulate part of the system: either the atmosphere, the surface or the subsurface. Uncertainties in boundary conditions propagate as biases in the simulated results. For example, not accounting for anthropogenic groundwater extraction potentially introduces biases in arid regions, where groundwater is a non-negligible source of moisture for the atmosphere. The use of observations is therefore an important aid to evaluate model performances and to detect possible biases in water balance components.

In this contribution, we compare total water storage changes derived from the Gravity Recovery Climate Experiment (GRACE) and its follow-on mission, with modelled components of the water balance. We use ERA5 reanalysis data to compute (net) atmospheric transports, and river discharge from GloFAS (Global Flood Awareness System). Furthermore, we use precipitation estimates (e.g. from GPCC) together with evapotranspiration from the Surface Energy Balance System (SEBS). We finally perform an accounting of the water balance components for the world’s largest watersheds and show to what extent we can find agreements, inconsistencies and biases in the data and models.

How to cite: Rietbroek, R., Penning de Vries, M., Zeng, Y., and Su, B.: Closing the water balance of large watersheds using satellite gravimetry, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3734, https://doi.org/10.5194/egusphere-egu22-3734, 2022.

Though machine learning (ML) methods have been around for decades, they have only more recently been adopted in the geosciences. The availability of existing long data records combined with the capability of ML algorithms to learn highly non-linear relationships between data sources means there is even more potential for the replacement or augmentation of existing scientific analyses with ML methods. Here, I give an example of how I used a convolutional neural network (CNN) for the task of pixelwise classification of the North American Land Data Assimilation System (NLDAS) Total Water Storage data into their corresponding drought levels based on the Palmer Drought Severity Index (PDSI). Promising results indicate there is much to be explored in the application of ML to drought identification and monitoring.

How to cite: Vassallo, C., Bettadpur, S., and Wilson, C.: Drought Identification in NLDAS Data using Machine Learning Methods, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4918, https://doi.org/10.5194/egusphere-egu22-4918, 2022.

We propose a spatial characterization of the hydrological contributions of several climate drivers that impact continental water mass storage of Australia determined by remote sensing techniques over the period 2002 - 2021. For this purpose, the Slepian functions help for recognizing the signatures of such important changes in the varying gravity field solutions provided by GRACE and GRACE-FO satellite missions such as mascon solutions of 400-km resolution. Time series of 25 Slepian coefficients that correspond to ~99.9% of the eigenvalue spectrum are used to be analyzed and compared to the profiles of climate indexes i.e. El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and South Annular Mode (SAM). The best correlations enable to extract specific Slepian coefficients, and then reconstruct the regional hydrological structures that concern each climate driver, in particular for the southeastern basins strongly influenced by the important flooding during La Niña episode of 2010.

How to cite: Ramillien, G., Seoane, L., and Darrozes, J.: Water mass impacts of the main climate drivers over Australia by satellite gravimetry, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5765, https://doi.org/10.5194/egusphere-egu22-5765, 2022.

In recent years, the detection and correction of the non-natural irregularities in the long climatic records, so-called homogenization, has been studied. This work is motivated by the problem of identification of origins of the breakpoints in the segmentation of difference series (difference between a candidate series and a reference series). Several segmentation methods have been developed for the difference series, but many of them assume that the reference series is homogenous. However, the homogeneity of the reference series, in reality, is uncertain and unproven. In our study, we applied the segmentation method GNSSseg (Quarello et al., 2020) on the difference between the Integrated water vapour estimates of the CODE REPRO2015 GNSS data set and the ERA5 reanalysis. About 36.5% of change points can be validated from the GPS metadata, and the origins of the remaining 64.5% are questionable (Nguyen et al., 2021). The ambiguity can be leveraged when there is at least one nearby GPS station with respect to which the candidate series can be compared. The proposed method uses weighted t-tests combining the candidate GPS and ERA series and their homologues (denoted GPS' and ERA') from each nearby station. If sufficient consistency emerges from the six tests for all the nearby stations, a decision can be made whether the breakpoint detected in the candidate GPS-ERA series is due to GPS or, alternatively, to ERA. For each quadruplet (GPS, ERA, GPS', ERA'), six t-tests are performed, and the outcomes are combined. In a set of 81 globally distributed GNSS time series spanning more than 25 years, 56 series have at least one nearby station, where 171 breakpoints are detected in segmentation, in which 136 breakpoints are attributed to the GPS. Among those, 94 breakpoints have consistent results between all the nearby stations. GPS-related breakpoints are used for the correction of the mean shift in the difference series. The impact of the breakpoint correction on the GNSS IWV trend estimates is then evaluated. 

Quarello A, Bock O, & Lebarbier E. (2020). A new segmentation method for the homogenisation of GNSS-derived IWV time-series. arXiv: Methodology.

Nguyen KN, Quarello A, Bock O, Lebarbier E. Sensitivity of Change-Point Detection and Trend Estimates to GNSS IWV Time Series Properties. Atmosphere. 2021; 12(9):1102. https://doi.org/10.3390/atmos12091102

How to cite: Nguyen, K. N., Bock, O., and Lebarbier, E.: A new method for the attribution of breakpoints in segmentation of IWV difference time series, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6390, https://doi.org/10.5194/egusphere-egu22-6390, 2022.

Drought has struck the southwest U.S. for the fourth time this millennium, reducing freshwater available to agriculture and urban centers.  We are bringing new insight by quantifying change in water in the ground using GPS elastic displacements, GRACE gravity, artificial reservoir levels, and snow models. Precipitation in Water Year 2021 was half of normal; the rise in total water in autumn and winter is 1/3 of the seasonal average (estimated using chiefly GPS); water was parched from the ground in the spring and summer, bringing water in the ground to its historic low (estimated using primarily GRACE).  In the Central Valley, soil moisture plus groundwater each year increases by 11 km3 and is maximum in April.  Only half of groundwater lost during periods of drought is replenished in subsequent years of heavy precipitation.  The Central Valley has lost groundwater at 2 km3/year from 2006 to 2021, with 2/3 of the loss coming from the southern Valley.

How to cite: Argus, D., Martens, H., Borsa, A., Wiese, D., Knappe, E., Larochelle, S., Anderson, M., Peidou, A., Khatiwada, A., Lau, N., White, A., Hoylman, Z., Swarr, M., Cao, Q., Pan, M., Chanard, K., Avouac, J.-P., Payton, G., and Landerer, F.: Intensifying hydrologic drought in California, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6800, https://doi.org/10.5194/egusphere-egu22-6800, 2022.

Earth's visible environmental changes, both natural and man-made, are influencing climate change on a global scale. For this reason, it is necessary to continuously monitor these changes and study the impact of human activities on them. One of the parameters indicating climate change is the systematic increase in temperature for the last 80 years. It causes more evaporation of water from natural and artificial water bodies. Consequently, the water content in the atmosphere is also increasing. Precipitable water is therefore one of the most important parameters when studying climate change. 

The aim of this study was to analyze long-term precipitation water data from a dense GNSS network over Poland. Twelve-year observations from over a hundred ASG-EUPOS stations were used to estimate changes in precipitation water values. These data were verified by comparison with available radio sounding data. Analysis of GPS-based PW values showed a clear increasing trend in PW values by 0.078 mm/year. The spatial-temporal distribution of mean PW values and their fluctuations over the years have been investigated. The obtained results confirm the fact that Poland lies on the border of continental and oceanic climate influence, and are in agreement with climate research concerning this region. 

How to cite: Araszkiewicz, A., Mierzwiak, M., Kiliszek, D., Nowak Da Costa, J., and Szołucha, M.: GPS-based multi-annual variation of the precipitable water over Poland territory, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7081, https://doi.org/10.5194/egusphere-egu22-7081, 2022.

To assess realistic climate change mitigation strategies, it is important to research and understand the global carbon cycle. Carbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases. Their atmospheric concentrations are affected by anthropogenic emissions as well as exchange fluxes with oceans and the terrestrial biosphere. For the prediction of future atmospheric CO2 and CH4 concentrations, it is critical to understand how the natural exchange fluxes respond to a changing climate. One of the factors that impact these fluxes is the changing hydrological cycle.        
In our project, we combine information about the hydrological cycle from geodetic satellites (e.g. GRACE & GRACE-FO) with carbon cycle observations from other satellites (e.g. TROPOMI & OCO-2). Specifically, we plan to investigate the impact of a changing water level in soils on CH4 emissions from wetlands and on the photosynthetic CO2 uptake of plants. Details of our approach and first results will be presented.

How to cite: Klemme, A., Warneke, T., Bovensmann, H., Weigelt, M., Müller, J., Notholt, J., and Lämmerzahl, C.: Using satellite geodesy for carbon cycle research, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7583, https://doi.org/10.5194/egusphere-egu22-7583, 2022.

Since 2002, estimates of the spatio-temporal variations of Earth’s gravity field derived from the Gravity Recovery and Climate Experiment (GRACE and now GRACE-FO) mission measurements have provided new insights into large scale water redistributions at inter-annual, seasonal and sub-seasonal timescales. It has been shown for example that for many large drainage basins the empirical relationship between aggregated Terrestrial Water Storage (TWS) and discharge at the outlet reveals an underlying dynamic that is approximately linear and time-invariant.

In this contribution, we further analyse this relationship in the case of the Amazon basin and sub-basins by investigating different physically interpretable, lumped-parameter models for the TWS-discharge dynamics. To this end, we first put forward a linear and continuous-time model using a state-space representation. We then enhance the model by introducing a non-linear term accounting for the observed saturation of the discharge. Finally, we reformulate the model by replacing the discharge by the river stage at the outlet and add a prescribed model of the rating curve to obtain the discharge. The suggested models are successively calibrated against TWS anomaly derived from GRACE data and discharge or river stage records using the prediction-error-method. It is noteworthy that one of the estimated parameters can be interpreted as the total amount of drainable water stored across the basin, a quantity that cannot be observed by GRACE alone. This quantity is estimated to be on average 1,750 km³ during the period 2004-2009. These models are eventually combined with the equation of water mass balance, in order to obtain a consistent representation of the basin-scale rainfall-runoff dynamics suited to data assimilation.

How to cite: Douch, K., Saemian, P., and Sneeuw, N.: Identification of conceptual rainfall-runoff models of large drainage basins based on GRACE and in-situ data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7903, https://doi.org/10.5194/egusphere-egu22-7903, 2022.

Continuous monitoring of the Global Terrestrial Water Storage changes (TWS) is challenging because of the large surface of continents and the variety of storage compartments (WCRP, 2018). The only observing system which provides global TWS mass change estimates so far is space gravimetry. Unfortunately, most storage compartments (lakes, groundwater, glaciers…) are too small to be resolved given the current spatial resolution of gravimetry missions. This intrinsic property makes gravimetry-based TWS changes estimates difficult to attribute and to interpret at individual basin scale.

In this context, combining gravimetry-based TWS estimates with other sources of information with higher spatial resolution is a promising strategy. In this study, we combine gravimetry data with independent observations from satellite altimetry and high resolution visible imagery to derive refined estimates of the TWS changes in hydrological basins containing lakes and glaciers (See Data used). The combination consists in including independent observations of glacier (Hugonnet et al., 2021) and lake (Cretaux et al., 2016) mass changes in the conversion process from gravity L2 data to water mass changes data. The combination is done for all regions of the world on a monthly basis.

This approach allows to split properly glacier and TWS changes at interannual to decadal time scales, and derive glacier-free estimates of TWS in the endorheic basins and the exorheic basins. We find that for the period from 2002 to 2020, the total TWS trend of 0.23±0.25 mm SLE/yr is mainly due to a mass loss in endorheic basins TWS of 0.20±0.12 mm SLE/yr. Over the same period, exorheic basins present a non-significative trend of 0.03±0.14 mm SLE/yr. On the contrary, the interannual variability in the TWS change of 4 mm SLE is mainly due to the exorheic basins TWS change.

How to cite: Blazquez, A., Berthier, E., Meyssignac, B., Longuevergne, L., and Crétaux, J.-F.: Combining space gravimetry observations with data from satellite altimetry and high resolution visible imagery to resolve mass changes of endorheic basins and exorheic basins., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8525, https://doi.org/10.5194/egusphere-egu22-8525, 2022.

Satellite gravity missions are unique observation systems to directly observe mass transport processes in the Earth system. Since 2000, CHAMP, GRACE, GOCE, and GRACE-FO have almost continuously been observing Earth’s mass changes and have improved our understanding of large-scale processes such as the global water cycle, melting of continental ice sheets and mountain glaciers, changes in ocean mass that are closely related to the mass-related component of sea-level rise, which are subtle indicators of climate change, on global to regional scale. The existing observation record of more than two decades is already closing in on the minimum time series of 30 years needed to decouple natural and anthropogenic forcing mechanisms according to the Global Climate Observing System (GCOS).

Next Generation Gravity Missions (NGGMs) are expected to be implemented in the near future to continue the observation record. The Mass-change And Geoscience International Constellation (acronym: MAGIC) is a joint investigation of ESA with NASA’s MCDO study resulting in a jointly accorded Mission Requirements Document (MRD) responding to global user community needs. These NGGM concepts have set high anticipation for enhanced monitoring capabilities of mass transports in the Earth’s system with significantly improved spatial and temporal resolution. They will allow an evaluation of long-term trends within the Terrestrial Water Storage (TWS), which was adopted as a new Essential Climate Variable in 2020.

This study is based on modeled mass transport time series of components of the TWS, obtained from future climate projections until the year 2100 following the shared socio-economic pathway scenario 5-8.5 (SSP5-8.5). It evaluates the recoverability of long-term climate trends, annual amplitude, and phase of the TWS employing closed-loop numerical simulations of different current and NGGM concepts up to a spatial resolution of 250 km (Spherical Harmonic Degree 80). The assumed satellite constellations are GRACE-type in-line single-pair missions and Bender double-pair missions with realistic noise assumptions for the key payload and ocean-tide background model errors. In the interpretation and discussion of the results, special emphasis will be given on the dependence of the length of the measurement time series and the quantification of the robustness of the derived trends, systematic changes, as well as possibilities to improve the trend parameterization.

How to cite: Schlaak, M., Pail, R., Jensen, L., and Eicker, A.: Closed Loop Simulations on Recoverability of Climate-Related Mass Transport Signals in Current and Next-Generation Satellite Gravity Missions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8529, https://doi.org/10.5194/egusphere-egu22-8529, 2022.

The Federal Office of Metrology and Surveying (BEV) in Austria is responsible for the geodetic reference system like gravity and height reference frame. Some of these gravity reference stations are monitored regularly by different geodetic terrestrial techniques. The gravity data on some stations show variations and/or changes in gravity. In this presentation, the alpine geodetic reference stations Obergurgl and Franz-Josefs- Höhe in the Austrian eastern Alps will be presented. Both stations are investigated with different geodetic terrestrial techniques in a cooperation of the University of Luxemburg with BEV.

Global warming and associated climate change during the last century and recent decades are among the main reasons for glacier retreat in the Alps. Absolute gravity measurements have been regularly performed in the Austrian Eastern Alps since 1987 in the Ötztal Valley at Obergurgl. In addition, absolute gravity has been regularly observed at Obergurgl from 1987 to 2009 with the absolute gravimeter JILAg6. From 2010, the absolute gravity measurements were continued with the highest accurate absolute gravimeters FG5 from BEV and FG5x from University of Luxemburg. The newest gravity data show again a small increase of gravity. Additionally, a permanent GNSS station was established in 2019 to record information about the assumed vertical uplift at this station.

A second alpine research station was established near the Pasterze Glacier at Großglockner Mountain in 2019. The Pasterze Glacier is one of the largest glaciers in the eastern Alps and is in the vicinity of the highest mountain of Austria, the Großglockner. The station is monitored by repeated absolute gravity measurements and is equipped with a permanent GNSS station. In addition, precise leveling measurements were also tied to this station. In this contribution, initial results of the geodetic research like the gravity results, precise leveling and GNSS measurements will be presented. In the future, gravity data will be quantitively compared to ice mass balance information derived from glacier inventories. A Geodetic Global Navigation Satellite System reflectometry (GNSS-R) antenna will also be installed to study glacier-ice change. A third station at an altitude of 3300 m is planned and will be checked for operating absolute gravity measurements there. The geodynamical processes like vertical uplift and postglacial deformation will be investigated together with glacier retreat on these stations.

How to cite: Ullrich, C., Francis, O., Tabibi, S., and Titz, H.: Geodetic climate research in the Austrian Alps, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9943, https://doi.org/10.5194/egusphere-egu22-9943, 2022.

Global Navigation Satellite System (GNSS) networks in South Africa indicate a spatially coherent uplift. The cause of this uplift is not clear, but one hypothesis is a crustal deformation due to mantle flow and dynamic topography (Hammond et al., 2021, JGR Solid Earth). We provide an alternative evidence based on elastic loading modelling and independent observations, suggesting that land water loss due to multiple drought periods is a dominant driver of land uplift in South Africa.

The use of continuously measuring GNSS stations has proven to be a successful method for quantifying terrestrial water mass changes, by inverting the observed vertical displacements of the Earth’s crust. Depending on the density of the GNSS network, this method has the potential to derive not only temporal but also spatial higher-resolution total water storage change (TWSC) than the Gravity and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions. Since vertical displacements in GNSS data are not only affected by water mass changes, extensive time series analyses are required to reduce or eliminate non-hydrology-related deformations, such as non-tidal oceanic and atmospheric loading. In this way, GNSS also offers an alternative method to monitor the frequently occurring droughts in South Africa, like the severe “Day Zero” drought in Cape Town from 2015-2017.

In this study, daily GNSS time series of vertical displacements (2000-present) are analysed. A long-term trend as well as annual and semi-annual signals are separated from the noisy observations using Singular Spectral Analysis (SSA). The final time series of all stations are inverted into water mass loading over a uniform grid, with the deformation properties of the Earth’s crust being defined by the Preliminary Reference Earth Model (PREM). An experimental approach shows that a 2° x 2° grid resolution of the GNSS-derived TWSC provides appropriate solutions over most of South Africa. The GNSS solution agrees with a GRACE-assimilated solution and a hydrological model at monthly scale over different provinces, with correlations up to 93% and 94%, respectively. The long-term trend averaged over the entire country is correlated with 80% and 54%, respectively. Negative long-term TWSC trends are evident in all data sets and provide compelling evidence that long-term land uplift in South Africa has a hydrological origin.

How to cite: Mielke, C., Karegar, M., Gerdener, H., and Kusche, J.: GNSS observations of the land uplift in South Africa: Implication for water loss estimation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10152, https://doi.org/10.5194/egusphere-egu22-10152, 2022.

The relationship between water storage and vegetation growth differs with changes in different water
compartments such as total water storage, soil moisture and groundwater. This relationship can be
established between variations in water storage and Normalized Difference Vegetation Index (NDVI)
values. The compartments of water storage anomalies were computed with Gravity Recovery and Climate
Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) data sets. NDVI data from
Global Inventory Monitoring and Modeling System (GIMMS) was used to compare with water storage
anomalies. These water storage anomalies and NDVI values were aggregated over each sub-basin of the
Ganga catchment. A correlation analysis was made between water storage components and NDVI values,
which helped to determine how vegetation growth depends on changes in different water compartments.
Initial computations of auto-correlation and cross-correlation between water storage components and
NDVI show different lags for different sub-basins. 

How to cite: Pernati, S., Bharath Narayana Reddy, K., and Devaraju, B.: How changes in compartments of water storage affect the vegetation?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10986, https://doi.org/10.5194/egusphere-egu22-10986, 2022.

Understanding how the Earth’s shape, gravity field and rotation change in response to shifting hydrological, atmospherical and oceanic mass loads at its surface has great potential for monitoring the evolving climate. Recent advances in the field, namely hydrogeodesy, have required hand-in-hand development and improvement of the observing techniques and of our understanding of the solid Earth-climate interactions. 

In particular, measurement of the spatial and temporal variations of the Earth's gravity field by the GRACE and GRACE-Follow On satellite missions offer an unprecedented measurement of the evolution of water mass redistribution, at timescales ranging from months to decades. However, the use of GRACE and GRACE-FO data for hydrological applications presents two major difficulties. First, the mission design and data processing lead to measurement noise and errors that limit GRACE missions to large-scale applications and complicates geophysical interpretation. Moreover, temporal observational gaps, including the 11 month-long gap between missions, prevent the interpretation of long-term mass variations. Secondly, disentangling sources of signals from the solid Earth and continental hydrology is challenging and requires to develop methods benefiting from multiple geodetic techniques. 

To reduce noise and enhance geophysical signals in the data, we develop a method based on a spectral analysis by Multiple Singular Spectrum Analysis (M-SSA) which, using the spatio-temporal correlations of the GRACE-GRACE-FO time series, can fill observational gaps and remove a significant portion of the distinctive noise pattern while maintaining the best possible spatial resolution. This processing reveals hydrological signals that are less well or not resolved by other processing strategies. We discuss regional hydrological mass balance, including lakes, aquifers and ice caps regions, derived from the GRACE-GRACE-FO M-SSA solution. Furthermore, we discuss methods to separate sources of gravity variations using additional in-situ hydrological data or geodetic measurements of the Earth’s deformation.