Thermosphere density is one of the largest sources of uncertainty in the orbit estimation and prediction for satellites in low Earth orbit. With the rapidly growing number of satellites in this region, accurate knowledge of thermosphere density is becoming increasingly important for e.g. collision risk assessment and avoidance, mission design and lifetime predictions. Accurate in situ density observations are valuable to improve our knowledge of the thermosphere. Such observations can be obtained from a limited number of space-borne accelerometers and can also be derived from precise GNSS tracking data of satellites in low Earth orbit, which are more commonly available.
TU Delft maintains a database of precise thermosphere density and crosswind observations derived from the CHAMP, GRACE, GOCE, Swarm, and GRACE-FO satellites. We continually strive to improve the accuracy of these observations by enhancing our density retrieval strategy. This presentation provides an overview of the most notable improvements. They consist of accurate accelerometer data calibration via precise orbit determination, using high-fidelity satellite geometry models for simulating the aerodynamic and radiation pressure forces, and accounting for the satellite thermal emissions. Recently, an improved retrieval of aerodynamic accelerations from GNSS data was implemented, which leads to a substantially larger signal-to-noise ratio of the GNSS-derived density data, triggering a full reprocessing of the Swarm density observations derived from those data. In a next step, we propose a new gas-surface interaction model that accounts for surface roughness. Since the surface roughness is unknown for the satellites in our database, the model’s roughness parameter must be determined from in-flight data collected during attitude maneuvers and orbital conjunctions. Finally, we have developed a method to comprehensively quantify the uncertainty of density observations, enabling us to augment the observations with uncertainty estimates in the future.
How to cite: van den IJssel, J., Siemes, C., Anton, S., Hladczuk, N., and Visser, P.: Thermosphere density from accelerometer and GNSS data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1601, https://doi.org/10.5194/egusphere-egu25-1601, 2025.
NeQuick is a global empirical model describing the median climatological behavior of the electron density in the ionosphere–plasmasphere system. NeQuick allows a fast calculation of total electron content (TEC) values up to GNSS heights by numerical integration of the modeled electron density profile, making the model valuable for use in many geodetic and space weather applications. To ensure the highest reliability in TEC predictions, an accurate description of the topside ionosphere region and of the overlying plasmasphere is fundamental since they contain the largest fraction of TEC.
NeQuick describes the topside ionosphere and its plasmaspheric extension with a single semi-Epstein layer anchored to the F2-layer peak with a height-dependent effective scale height H, which is empirically formulated based on three topside parameters: H0, g, and r. H0 is the scale height value at the F2-layer peak; g represents the scale height vertical gradient near the F2-layer peak; while r is the parameter controlling the H behavior very distant from the F2-layer peak, namely, in the plasmasphere. While the H0 and g parameters can be reliably estimated based on COSMIC/FORMOSAT-3 (COSMIC-1) radio occultation (RO) profiles, the r parameter requires a different approach due to the limited altitudinal extension of COSMIC-1 RO profiles. To constrain the r parameter, we complemented COSMIC-1 RO profiles with TEC values from precise orbit determination (POD) antennas from the same satellites. POD TEC values are representative of the electron content of the upper part of the topside ionosphere (above the COSMIC-1 satellites) and of the plasmasphere.
The r parameter optimization is based on a twofold procedure. First, given a specific RO profile, H0, g, and r parameters are obtained from the topside section of the RO profile; thereafter, H0 and g are kept fixed while r, starting from the first-guess value obtained from the RO profile, is varied until it matches the topside TEC value obtained by adding the TEC measured by the POD antenna to the TEC of the RO topside section. In this way, the optimized r parameter improves the description of H in the plasmasphere and then the NeQuick modelling of the electron density in this region.
The proposed procedure has been applied to RO profiles and POD TEC values from the whole dataset of COSMIC-1 observations recorded between the years 2006 and 2020. Spatial and time variations of the optimized r values have been studied and compared with previous values obtained by only RO profiles. The reliability of the optimized r values has been tested by calculating H values in the plasmasphere through the NeQuick formulation and comparing them with the corresponding values obtained by Van Allen probes observations. These advancements are presented and discussed in view of the development and implementation of a revised NeQuick topside ionosphere model.
How to cite: Pignalberi, A., Nava, B., Prol, F., Haralambous, H., Themens, D., Smirnov, A., Pezzopane, M., and Coïsson, P.: Enhancing the NeQuick model performance in the topside ionosphere and plasmasphere through radio occultation and POD TEC observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9588, https://doi.org/10.5194/egusphere-egu25-9588, 2025.
The data volume of ionospheric observations has been dramatically enlarged these years by ground-based and spaceborne measuring techniques including global GNSS network, scientific and commercial plans of radio occultation, and satellite altimetry. Given the diverse observing geometries, vertical data coverages and intermission biases among different measurements, it is imperative to evaluate their absolute accuracies and estimate systematic biases to determine reasonable weights and error variances when integrating different sources of data. This research focus on the data assessment of several satellite missions launched in China such as MSS-1 and Yunyao constellation, and conducts comprehensive comparison among radio occultation, global ionospheric maps and satellite altimetry. The large amount of daily ionospheric radio occultation data from about 20 satellites and ground GNSS observations are devoted to the data assimilation system driven by Kalman filter. The observational accuracy provides essential information for determining error covariance and weight matrices in the total electron content assimilation model.
How to cite: Wu, M.: Comprehensive evaluation of spaceborne and ground-based ionospheric observations and their application in data assimilation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15062, https://doi.org/10.5194/egusphere-egu25-15062, 2025.
A geomagnetic storm involves a complex interplay between the solar-magnetosphere-ionosphere coupling system and may significantly impact satellite navigation and positioning systems through ionospheric responses. The severity of these storms varies across different events, as the ionospheric electron density fluctuates with different spatial and temporal scales. This study focuses on the geomagnetic storm that occurred on May 10–11, 2024, recognized as one of the most intense storms during the past two decades. Due to its long-lasting effects on both the interplanetary and terrestrial environments, it has gathered considerable attention from both the scientific community and the public sector.
We present a comprehensive analysis of the ionospheric response to the May 2024 storm and its impacts on precise point positioning (PPP) for geodetic GNSS receivers on a global scale. Unlike previous studies, this investigation focuses on the effects on positioning accuracy at the centimeter level, which is an aspect often overlooked in previous research. The results suggest that this storm caused long-lasting and widespread ionospheric disturbances across the North and South American, Asia, Australian, and European sectors. Consequently, high-precision GNSS positioning with a common processing strategy for PPP ambiguity resolution experienced a significant outage. These PPP outages coincided with the growth and decay of the SYM-H index and persisted for over a day at numerous stations located in North America and Australia. This highlights the vulnerability of high-precision positioning applications to the risks imposed by ionospheric disturbances during periods of intense geomagnetic activity.
How to cite: Yang, Z. and Morton, J.: Global Perspectives on the May 2024 Geomagnetic Storm Impact on High-Precision Positioning Based on Geodetic GNSS Observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3977, https://doi.org/10.5194/egusphere-egu25-3977, 2025.
Reconstructing the ionosphere with high precision is critical for understanding space weather and its impacts on satellite communications, navigation, and radar systems. Traditionally, ionospheric studies rely on ionosondes and radar measurements as well as ground based Total Electron Content derived from GNSS (Global Navigation Satellite System) as local measurements, but also GNSS Radio Occultation (RO) and insitu electron density from Low Earth Orbiting Satellites (LEO) as global measurements. While GNSS RO has been instrumental in advancing ionospheric modeling, it is limited by its dependence on GNSS satellite orbits and geometry, leading to gaps in spatial and temporal coverage.
This study explores the integration of slant TEC from LEO-PNT (Position Navigation and Timing) satellites, focusing on the potential of ground-to-LEO signal paths to complement GNSS RO observations. LEO satellite constellations, characterized by their dense, global coverage and low orbital altitudes, offer a promising opportunity for enhancing ionospheric reconstruction in both the altitudes between ground and LEO and altitudes between LEO and GNSS. Ground-to-LEO links provide a unique observational perspective, capturing slant total electron content (TEC) across diverse geometries that are inaccessible to GNSS RO. By incorporating these measurements into tomographic reconstruction frameworks, we demonstrate improved spatial resolution and accuracy in modeling ionospheric structures using synthetic data from well-established models such as IRI-2020.
We perform a series of ionospheric electron density reconstructions. The input data includes synthetic slant TEC from ground to GNSS, LEO to GNSS, LEO-RO, and LEO-PNT. We compare the full solution with LEO-RO and LEO-PNT to solutions, where either one or both of these inputs are omitted. Preliminary results highlight the added value of ground-to-LEO measurements in reproducing the IRI-2020 values and extending coverage in regions with sparse GNSS RO sampling. This approach is further validated using synthetic datasets and real-world orbits from existing LEO satellite constellations, such as Swarm, GRACE-FO, Sentinel, COSMIC-2, Jason-3, Sentinel, Spire, ...
Our findings underscore the transformative potential of leveraging LEO satellites in ionospheric science, paving the way for next-generation ionospheric monitoring systems. This contribution aims to stimulate discussion on future directions in multi-platform ionospheric research, emphasizing the synergies between GNSS RO and emerging ground-LEO link observations.
How to cite: Schreiter, L., Brack, A., Männel, B., Jäggi, A., Arnold, D., and Schuh, H.: Analysis of complementary LEO-PNT and Radio Occultation observations for Ionospheric reconstruction., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4742, https://doi.org/10.5194/egusphere-egu25-4742, 2025.
The Earth’s ionosphere is of considerable importance for medium- and long-range high-frequency communication, positioning, and over-the-horizon radar systems. Positioning and communication applications require new capabilities to understand, model, and predict the ionosphere's characteristics, including electron density profiles and total electron content (TEC), on a global scale. Geodetic observations are crucial for understanding the structure of the ionosphere. Nanosatellite technology has recently grown in importance for a wide range of applications, including communication, technological demonstration, heliophysics, astrophysics, earth research, and planetary science. The goal of this study is to assess the potential for reconstructing the 3D ionospheric characteristic by means of simultaneous measurements from nanosatellite constellations that are equipped with low-cost GNSS receivers.
In this paper, we present a novel ionospheric imaging technique based on a tomography-based modelling approach, using four Astrocast nanosatellites placed in a "string-of-pearls" pattern in December 2022. The investigation found up to 1800 radio occultation events during the 14-hour observation period. To estimate electron density fields, the ionospheric excess phase was extracted from the GPS L1 code and phase measurements and integrated into a tomographic system together with ray-traced signal paths. The findings of this study highlight the potential of this cutting-edge observation technique for three-dimensional sensing of the ionosphere, providing significant opportunities for future atmospheric investigations.
Keywords: STEC, nanosatellites, tomography technique, GNSS radio occultation measurements
How to cite: Kosary, M., Müller, L., Hanna, N., Rothacher, M., Rondot, S., and Moeller, G.: Imaging ionosphere using single-frequency GNSS data onboard nanosatellite missions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4348, https://doi.org/10.5194/egusphere-egu25-4348, 2025.
Over the years, TU Graz has processed thermospheric densities for several satellite missions. Thanks to recent adaptations of our GROOPS software package, we have been able to estimate such a time series for TerraSAR-X, a LEO satellite in sun-synchronous orbit, up to the present day. In order to make these data available to researchers who are interested in space weather related studies, we are switching to a new publishing scheme to provide the data with less latency.
Estimating these thermospheric densities from accelerometer measurements or GNSS observations is a tedious process that depends on several parameter choices. For example, the Sentman model is often used to calculate drag coefficients for satellites. In addition to the geometry of the satellite, the drag coefficient of this model depends on the surrounding gas (temperature, composition) as well as the surface properties of the satellite (energy accommodation coefficient). While it is easy to compute solutions for different parameter choices, it is usually not trivial to decide which result is best.
In this pre-study, we investigate the possibility of fine-tuning the choice of aerodynamic parameters by evaluating the quality of the resulting gravity field. This may be a feasible approach for GRACE-FO due to the specific design of the mission: two identical satellites following each other in essentially the same orbit while measuring their precise distance. The failure of the second satellite's accelerometer requires a "transplant" of the measurements from the first satellite to the second. This procedure includes the estimation of the thermospheric density, and thus the gravity field is sensitive to the chosen parameters.
How to cite: Strasser, A., Öhlinger, F., Krauss, S., Süßer-Rechberger, B., and Mayer-Gürr, T.: An Update to TU Graz Thermospheric Density Estimates and Fine-Tuning Attempts, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17141, https://doi.org/10.5194/egusphere-egu25-17141, 2025.
Knowing the locations of the north and south Equatorial Ionization Anomaly (EIA) crests and their corresponding widths is essential for characterizing the spatiotemporal and solar activity variations of the low latitude ionosphere. The crest region is characterized by strong electron density gradients that significantly affect GNSS applications. However, there is still a lack of complete characterization and modeling of the spatiotemporal and solar activity variations of the EIA crest positions and widths. Therefore, the purpose of this study is to characterize and model the spatiotemporal and solar activity variations of EIA crest widths and positions. These characteristics are described and modeled using 13 years (2009-2017 and 2020-2023) NmF2 data, which are obtained from radio occultation electron density profiles of GRACE, COSMIC-1, and COSMIC-2 satellites over the globe. Crest positions and widths exhibit diurnal, semi-diurnal, and annual variations. There is a slight linear correlation between the solar activity and the crest positions and widths. Furthermore, longitudinal variations in the geomagnetic field declination and the interplay between wave number 3 diurnal tides and planetary waves may be related to longitudinal variations in the crest positions and widths. The results of the analysis are used to create semi-empirical EIA crest position and width models. These models provide a good description of the crest widths and positions verified by vTEC altimeter measurements. These models can serve as subroutines for the improvement of current ionospheric TEC and F2-layer maximum electron density models, applicable for improving terrestrial communications and GNSS positioning and navigation.
How to cite: Nigussie, M., Jakowski, N., and Hoque, M.: Equatorial Ionization Anomaly Crest Parameters Modeling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4104, https://doi.org/10.5194/egusphere-egu25-4104, 2025.
The Passive REflecTometry and dosimeTrY (PRETTY) satellite has been launched into a low Earth orbit, of about 570 km altitude, on 9th October 2023. Its main payload is dedicated to reflectometry using signals of Global Navigation Satellite Systems (GNSS). The on-board reflectometry receiver provides delay maps of the Earth-reflected signal. The main objective of the mission is to exploit the delay maps for ocean and sea ice altimetry.
Observations are recorded in grazing angle geometry. It means that incident and reflected ray reach a maximum elevation angle at the reflection point of 15°, higher elevation observations are out of scope. These grazing angle observations have advantages compared to higher ones: reduced roughness effect on the reflected signal, higher coherent reflection power and wider coverage of reflection points over the ocean. However, grazing geometry brings also challenges: a reduced altimetric sensitivity (to surface height changes), as well as, higher magnitude and complexity of atmospheric delays.
The presented study modifies the initial altimetric idea and uses reflectometry data with known surface height to investigate the structure of ionospheric layers. The study concentrates on four PRETTY delay maps recorded over Arctic sea ice. Correcting the delay for other effects, especially surface height and troposphere delay, reveals characteristic ionospheric delay profiles. These profiles, of the reflected signal delay relative to the direct signal, reach a minimum in the grazing angle range before they vanish in the limit of tangent Earth reflection. Both, retrieved profiles, from PRETTY observations, and simulated profiles, assuming ionospheric electron density of the Neustrelitz Electron Density Model (NEDM), confirm the characteristic minimum of the profiles.
For a deeper analysis of the profiles we run simulations with configurable electron density distribution according to Chapman layers and the PRETTY satellite geometry. Dominating F-layers are assumed with peak heights from 250 to 350 km. The corresponding profiles show minima from about 2° to about 4° of elevation. The inversion of peak height and other parameters of ionospheric layers from delay profiles will be developed further in the on-going study. An extended validation of results, with different ionosphere models, shows an overall agreement in the existence of local minima. However, uncertainties among the models persist with minima positions deviating by 1 or 2 degrees. It indicates space for improvement of existing models.
How to cite: Semmling, M., Moreno, M., Zus, F., Dielacher, A., Hoque, M., Wickert, J., and Nahavandchi, H.: Grazing angle GNSS reflectometry with the PRETTY satellite: an opportunity to resolve the structure of ionospheric layers, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15445, https://doi.org/10.5194/egusphere-egu25-15445, 2025.
The GNSS NavAer project has been under development since 2017, focusing on creating a comprehensive infrastructure dedicated to monitoring and analyzing space weather phenomena. This project represents a significant investment in scientific research and technology, aimed at enhancing our understanding of various atmospheric and environmental processes. The infrastructure established through the GNSS NavAer project is versatile and can be deployed across several scientific disciplines, including Geodesy, Aeronomy, and Space Weather, among others.
One of the primary motivations behind the GNSS NavAer project is the increasing reliance on Global Navigation Satellite Systems (GNSS) for navigation, communication, and positioning applications. As these systems become more integral to modern society, understanding the factors that can disrupt their performance is of great insterest. Space weather events, particularly those affecting the ionosphere, have been identified as significant sources of interference that can degrade the accuracy and reliability of GNSS signals.
Ionospheric scintillation, a phenomenon characterized by rapid amplitude and phase fluctuations of GNSS signals, poses a particular challenge. This can result from natural irregularities in the ionosphere, often intensified by solar activity. When these irregularities are present, GNSS signals can experience disruptions that may lead to positioning errors, loss of signal lock, and degraded navigation accuracy. Such disruptions can have serious implications for air navigation, autonomous systems, and any application that relies on precise positioning data.
In this presentation, we will focus on the specific use of the GNSS NavAer infrastructure for monitoring space weather, with an emphasis on IS. The infrastructure includes a network of strategically placed GNSS receivers that continuously collect real-time data on ionospheric conditions, which are stored in a databank and can be explored via a dedicated toll specially developed for that (ISMR Query Tool). By integrating advanced data processing techniques and algorithms, researchers can analyze these data to identify and characterize scintillation events as they occur.
The significance of this monitoring cannot be overstated. By providing timely information on ionospheric conditions, stakeholders can better prepare for and mitigate the impacts of space weather on GNSS applications. For instance, real-time observations can help aviation authorities make informed decisions regarding flight operations, ensuring that aircraft can navigate safely even in conditions that would typically be challenging due to ionospheric disturbances.
Furthermore, the GNSS NavAer project facilitates collaborative efforts among scientists and researchers in various fields. By sharing data and findings, the project promotes a more comprehensive understanding of space weather and its impacts. International cooperation is vital, as space weather events often affect multiple regions simultaneously, making a collaborative approach essential for effective monitoring and response strategies.
In conclusion, the GNSS NavAer project is a groundbreaking initiative aimed at enhancing our ability to monitor and understand the complexities of space weather. Through its dedicated infrastructure, it addresses the challenges posed by IS and aims to provide solutions that improve the reliability of GNSS applications. The deterioration in positioning and navigation will be presented, together to some trial to reduce such problem.
How to cite: Monico, J. F. G., Tsuchiya, I., and Vani, B.: The INCT GNSS NavAer infrastructure for Space Weather Monitoring., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-76, https://doi.org/10.5194/egusphere-egu25-76, 2025.
Space weather events significantly disrupt Earth's ionosphere, affecting atmospheric properties and degrading radio signal quality. This study investigates ionospheric Total Electron Content (TEC) variations to characterize space weather phenomena, focusing on the F2 layer. Using GNSS dual-frequency observations and ground- and satellite-based solar indices, the research examines events such as the geomagnetic storms of March 24, 2023, and April 24, 2023, and the solar flare of March 3, 2023.
TEC time-series analysis reveals latitudinal and semi-annual variations in ionization, with maximum TEC during equinoxes due to enhanced thermospheric circulation and dominance of atomic oxygen. In contrast, solstice months exhibit reduced ionization efficiency due to asymmetric heating and dynamics. Correlation analysis during the March storm identifies a significant impact of geomagnetic disturbances, with a negative correlation (-0.44) between the Dst index and TEC. The April storm shows a stronger positive correlation (0.41) between the Kp index and TEC, highlighting the heightened ionospheric response to global geomagnetic activity.
Wavelet analysis uncovers latitudinal periodicities linked to solar rotation cycles. Equatorial regions exhibit TEC modulation with a 22.7-day periodicity due to intense solar EUV radiation, while mid-latitudes show a 24.7-day periodicity influenced by geomagnetic storms and solar radiation. High-latitude regions are dominated by geomagnetic activity, with TEC fluctuations modulated at a 27.9-day periodicity by high-speed solar wind interactions and auroral activity. These findings underscore the complex interplay between solar activity, geomagnetic disturbances, and ionospheric dynamics, providing insights critical for improving space weather prediction models.
How to cite: Reuveni, Y. and Linjouom, R. H.: Assessing Space Weather Phenomena using GPS ionospheric TEC analysis, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5920, https://doi.org/10.5194/egusphere-egu25-5920, 2025.
The neutral mass density of the upper thermosphere can be determined by orbit and accelerometer data from Low Earth Orbit (LEO) satellites. Especially the accelerometers of geodetic satellites, measuring the non-gravitational accelerations acting on these satellites, are a very useful observation for precise density estimation also on very short time scales. Currently, due to the lac of direct measurements, the most accurate atmospheric density estimates are computed from such data.
We present here our latest density solution based on a new approach for the drag coefficient (Cd) modelling. We employ the DRIA (Diffuse Reflection with Incomplete Accommodation) drag model but changed the utilization of the model with our detailed Finite Element Models (FEM) processing and the shadowing computation within the approach. We compare resulting density and Cd values with our previous published data (zarm.uni-bremen.de/zarm_daten/), as well as with data from TU Delft and show the effect of the different Cd modelling approaches on the estimated density. Exemplarily we use here the data from GRACE and GRACE-FO.
How to cite: Wöske, F., Fumenti, F., Huckfeldt, M., and Rievers, B.: Updated thermospheric neutral density retrieval from geodetic satellite's accelerometer data with improved drag model based on DRIA and detailed finite element satellite models , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20326, https://doi.org/10.5194/egusphere-egu25-20326, 2025.
Thermospheric density measurements are crucial for satellite operations and for understanding the dynamic behaviour of the upper atmosphere, where thousands of LEO satellites orbit. In this study, we use thermospheric densities derived from high-precision accelerometer data from GRACE-FO, provided by Delft University, sampled at 0.1 Hz (every 10 seconds). We focus on high-frequency density variations (f > 1 mHz) observed between 2018 and 2024, a period covering the solar minimum of cycle 24 and the ascending phase of cycle 25. As solar maximum approaches, the densities increase by two orders of magnitude.
After removing diurnal, semi-diurnal, and seasonal periodicities, higher-frequency disturbances become apparent, even during low geomagnetic activity (Kp = 3), with stronger signatures near the North Pole. We observe a consistent downward trend when GRACE-C is within the Earth’s shadow, while more intense disturbances occur near the solar terminator. During the ascending phase of cycle 25, strong equatorial signals also emerge. A correlation analysis with the Hp30 geomagnetic index highlights the importance of using high-cadence geomagnetic indices to capture short-term disturbances. Additionally, spectral analysis during major geomagnetic storms over the six-year period shows how thermospheric densities respond to increased geomagnetic activity at higher latitudes in both hemispheres.
How to cite: Tzamali, M., Glover, A., and Luntama, J.-P.: High-Frequency Variations in Thermospheric Densities from GRACE C Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20153, https://doi.org/10.5194/egusphere-egu25-20153, 2025.
This study presents a comprehensive nowcasting and forecasting approach for ionospheric peak parameters, including foF2, NmF2, and TEC, using a Physics Informed Neural Network (PINN). This approach integrates multiple datasets, utilizing extensive ground-based ionosonde station measurements and COSMIC satellite observations to model and predict these parameters in relation to ionospheric conditions and space weather dynamics.
Our work also explores the response of ionospheric peak parameters to extreme solar eruptions and geomagnetic storms, providing critical insights into the behaviour of the ionosphere under these challenging conditions. The PINN incorporates fundamental physical laws as constraints, including the Chapman function, continuity equation, ion production rates as a function of F10.7, recombination reactions, geomagnetic and electric fields, and Abel inversion effects. Our model utilizes a comprehensive set of input features, including COSMIC satellite foF2, NmF2, TEC measurements, temporal and spatial parameters, and various solar and geomagnetic indices. Data normalization and a deep neural network architecture with multiple dense layers and batch normalization were employed to capture complex, non-linear relationships in the ionospheric data. These constraints enable highly accurate predictions achieving a high average correlation of 0.92 between COSMIC satellite and ionosonde measurements.
A detailed random forest parameter importance analysis identified key contributors to ionospheric variability, revealing that atmospheric dynamics (meridional and zonal winds) and solar activity (notably F10.7) play dominant roles. Spatial and temporal factors were also considered critical compared to other space weather parameters.
These findings highlight the potential of physics-informed machine learning as a robust tool for advancing our understanding of ionospheric behaviour and improving predictive capabilities for space weather applications. Furthermore, this study underscores the value of integrating ground- and space-based observations with physical principles to achieve accurate and reliable forecasts of ionospheric peak parameters.
How to cite: Seba, E. and Poedts, S.: Physics-Informed Machine Learning for Predicting Ionospheric Peak Parameters Using Ground- and Space-Based Observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18292, https://doi.org/10.5194/egusphere-egu25-18292, 2025.
The project CASPER is an interdisciplinary collaboration between the Institute of Geodesy and the Institute of Physics and is funded by the Austrian Research Promotion Agency. It deals with the influence of solar eruptions such as coronal mass ejections and solar flares on the Earth's neutral atmosphere and ionosphere. In this study we focus on the most severe geomagnetic storms that occurred in solar cycle 25. This includes the effects of the extreme "Gannon storms" on 10/11 May, as well as solar eruptions that occurred in August and October in 2024. We present a detailed analysis of various interplanetary and terrestrial measurements to allegorise the individual solar storms. For the thermospheric variations, the analysis is based on observations from the GRACE-FO and SWARM satellite missions using accelerometer and kinematic orbit data. On this basis, we are able to present changes in the Earth's neutral in terms of satellite orbit decays. Regarding the ionosphere, the part of the Earth’s atmosphere where solar radiation ionizes the atoms and molecules, we present the latest implementations in our software GROOPS. The slant total electron content (STEC) parameter is determined using a least-squares adjustment approach. To enhance the accuracy, high-order ionospheric correction terms are integrated into the estimation process. This information allows the derivation of additional ionospheric parameters, such as vertical total electron content (VTEC), for various altitude layers to be comparable with neutral density estimates. Finally, in terms of the predictability of the impact of solar eruptions on the satellite altitude, we also present the current status of the SODA forecast service which is part of the ESA's Space Safety Programme Ionospheric Weather Expert Service Centre (I.161).
How to cite: Tieber-Hubmann, C., Strasser, A., Temmer, M., Krauss, S., Koller, F., Milosic, D., Süsser-Rechberger, B., and Mayer-Gürr, T.: Analysis of thermospheric and ionospheric variations during recent solar storms in 2024 in the framework of the project CASPER, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16238, https://doi.org/10.5194/egusphere-egu25-16238, 2025.
Ionospheric scintillation significantly impacts the performance and reliability of space-based navigation and communication systems. Scintillation effects cause fluctuations in the amplitude and phase of (Global Navigation Satellite Systems) GNSS received signals. Significant variations in signal power causes loss in signal-to-noise ratio which, in combination with phase variations, can severely impact GNSS receiver performance by impairing signal acquisition or causing a loss of lock during tracking. Several studies, such as Delay et al. (2015), Jiao et al. (2016), and Moraes et al. (2017), have shown that modern GNSS signals are more vulnerable to ionospheric scintillation. This increased vulnerability arises from their lower operating frequencies, which make them more sensitive to small-scale plasma irregularities and rapid phase distortions caused by ionospheric irregularities. However, there is a notable lack of research on the performance of modernized GNSS observables, particularly regarding how different codes and channels perform across GNSS signal frequencies under ionospheric scintillation. To address this gap, this work evaluates the behavior of data and pilot codes/channels across different frequencies under challenging ionospheric conditions, focusing on signal availability, continuity using different signal and channel combinations. In terms of signal availability, the results reveal that L1 signals (C1C, C1X, L1X and L1C) exhibit the highest availability and resilience to ionospheric scintillation, followed by L5 and L2 signals (L5X, C5X, L2X, C2X), which exhibit moderate availability and reliability. The lowest signal availability is observed in the L2 signals (L2W, C2W), reflecting reduced performance. The performance of modernized GPS signals during ionospheric scintillation varies by signal frequency. The L5 signal is the most affected, showing the highest percentage of ionospheric scintillation index (S4) values, indicating significant susceptibility to scintillation. The L1 signal is the least affected, with the lowest S4 percentages, suggesting greater resilience. The analysis demonstrates that the L1X signal exhibits the highest continuity, with the lowest percentage of data gaps, indicating superior robustness. In contrast, the L2X signal shows the highest susceptibility to interruptions, with the greatest percentage of data gaps, followed by the L5X signal, which displays slightly fewer gaps than L2X. The observed correlation between ionospheric scintillation intensity and signal loss highlights the frequency-dependent nature of signal disruptions, with L1X proving to be the most resilient and L2X the most vulnerable. These findings highlight the frequency-dependent nature of GNSS signal performance and the importance of selecting appropriate signal and channel combinations for reliable ionospheric estimations.
How to cite: Christovam de Souza, A. L., Prol, F., Moraes, A., and Monico, J. F. G.: Performance of data and pilot code/channel of modernized GPS signals , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19114, https://doi.org/10.5194/egusphere-egu25-19114, 2025.
The main objective of the present study is to perform analysis of the space weather impact in the cases of each day periodic occurrence in various seasons in selected monthly nights at the GPS positioning results of Latvian CORS (Continuously Operating Reference Stations) in time span 2007 to 2017. The analysis performed of the GPS (Global Positioning System) 90-second kinematic post-processing solutions, obtained using Bernese GNSS Software v5.2. To complete this study, the time series of daily outliers are analyzed for all the Latvian CORS that occurs simultaneously in two or more CORS stations. Over 36 million position determination solutions were examined. Daily regular ionospheric scintillation phenomena with duration around 4-7 minutes were observed in solar activity years daily, starting from March till December. The research articles were searched where similar scintillation events have been analyzed. The articles on Pc1 scintillation waves were found where similar phenomena has been described. The results of statistical analysis of the occurrence events will be presented, focusing especially on the periodic ionospheric scintillations observed in the region of Latvia, with a latitude around 57º N.
How to cite: Normand, M., Balodis, J., and Mitrofanovs, I.: Analysis of GPS positioning disturbing periodic radiation bursts in 24th solar cycle, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19658, https://doi.org/10.5194/egusphere-egu25-19658, 2025.
How to cite: Dreyer, J., Chevalier, J.-M., and Bergeot, N.: Global VTEC Maps of the Geomagnetic Storm in May 2024 and Their Application to Study the Evolution of the Ionospheric and Plasmaspheric VTEC Distribution, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12567, https://doi.org/10.5194/egusphere-egu25-12567, 2025.
Coronal mass ejections (CMEs) from the Sun can cause geomagnetic storms which cause the thermosphere to expand. This leads to enhanced air drag for satellites in low Earth orbit (LEO). This work focuses on the evaluation of orbital decay with a focus on selected geomagnetic storm events. Using the Bernese GNSS Software (BSW), reduced-dynamic orbits of different LEO satellites are computed from GNSS data of on-board receivers, where non-gravitational accelerations are modelled by means of estimated empirical piecewise-constant accelerations (PCAs). The orbital decay is then calculated by using the PCAs, or, in case of the GRACE Follow-On satellite, calibrated accelerometer data, to solve Gauss’s perturbation equation for the satellite’s semi-major axis. This method is compared to an approach where a fit model is applied to the osculating semi-major axis derived from the reduced-dynamic orbits computed by BSW. The fit model consists of a piece-wise linear model of the time-varying mean orbital decay and the time-varying amplitudes of the most dominant periodic oscillations. The results of both methods are compared and found to be similar for large orbital decays induced by CMEs. But the fit model struggles with low orbital decay. The Gaussian perturbation equation approach is far more precise than the fit model and can react, e.g., instantaneously to satellite maneuvers which change the semi-major axis. For satellites without an on-board accelerometer, PCAs can be estimated and used for the numerical integration.
How to cite: Walter, L., Mercea, V.-M., Arnold, D., and Jäggi, A.: Orbital decay of low Earth orbiting satellites during geomagnetic storms, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11256, https://doi.org/10.5194/egusphere-egu25-11256, 2025.
Understanding ionospheric disturbances is essential not only for enhancing the accuracy of space geodetic applications but also for advancing our knowledge of space weather and space climate dynamics. Recently, this analysis has become increasingly valuable in early warning systems and assessing the effects of natural disasters such as geomagnetic storms, earthquakes, and tsunamis. To facilitate the monitoring of ionospheric instabilities worldwide, the GFZ Helmholtz Centre for Geosciences is developing a global network of high-rate GNSS stations operating at a frequency of 50 Hz. This report introduces the current status of the monitoring system and presents initial findings from stations located near the magnetic equator. The 3D model of ionospheric perturbations on a global scale (based on ROTI) and locally (based on the S4 index) at monitoring stations clearly illustrates the temporal and spatial characteristics of severe ionospheric conditions. We emphasize the impact of ionospheric irregularities on GNSS signal quality and employ statistical algorithms to evaluate the effects of scintillations on GPS, GLONASS, and Galileo satellite navigation systems across different frequencies.
How to cite: Nguyen, C., Ramatschi, M., Wickert, J., Arras, C., Männel, B., Bradke, M., Trung, D., Le, T., Nguyen, M., and Bui, L. K.: Global Monitoring System for Ionospheric Disturbances: Initial Findings on the Impact of Scintillations on GNSS Signal Quality Across Frequencies, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7003, https://doi.org/10.5194/egusphere-egu25-7003, 2025.
The severe geomagnetic activities pose significant affect in modification of the electron concentrations of the ionospheric layer, especially along the equatorial and polar regions, causing challenging environments considering positioning perspectives. The recent availability of the Real-Time Global Ionosphere Maps (RT-GIMs) by some specialized IGS associated analysis centers such as Centre National d’Etudes Spatiales (CNES), Chinese Academy of Sciences (CAS), Universitat Politècnica de Catalunya (UPC), and Wuhan University (WHU), provides exciting opportunity to comprehend the ionospheric modification under these geomagnetic influences in real-time, while the RTGIMs can be integrated to the real-time precise point positioning (RT-PPP) to reduce the convergence time. Therefore, we perform the accuracy evaluation of these RT-GIM under the presence of a severe G-4 class geomagnetic storm during the year 2024. The performance of these RT-GIM products is evaluated by comparing the RT-GIM vertical Total Electron Content (VTEC) values with Final GIMs provided by Center for Orbit Determination in Europe (CODE) over land and Jason-3 altimetry satellite over oceans. The CNES RT-GIMs undergoes severe accuracy degradation across all continents recording a significant -20 to -40 TECU bias offset compared to the final CODE GIMs (CODGs) during the main phase of the geomagnetic storm. Similarly, the performance of the WHU RTGIMs sightly deteriorates upto -10 TECU along the equatorial, south pacific, and south pole regions. However, CAS and UPC RT-GIMs show a relatively consistent performances during the initial and main phase of the severe geomagnetic storm. However, during the final phase of the geomagnetic storm, both WHU and CAS RTGIMs exhibit overperformances of more than 10 TECU over the Antarctica compared to the final CODGs. Additionally, on the comparison with the Jason-3, the CNES and WHU RTGIMs shows worst performances once again with the average deviations of 10-15 TECU over the oceans during the high intensity period of the geomagnetic storm. Meanwhile, UPC RT-GIM remain the most consistent and stable performer (both, globally and over oceans) that provides accurate global ionospheric information, almost similar to the final GIMs, which is promising for their applications in real-time precise GNSS positioning.
How to cite: Adil, M. A., Hadas, T., and Hernandez-Pajares, M.: Influence of the Severe Geomagnetic Activity over the Performance of the Real-Time Global Ionosphere Maps, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8298, https://doi.org/10.5194/egusphere-egu25-8298, 2025.
