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.