Low-earth orbits (LEO) satellites have been harnessing the concept of GNSS radio occultation (RO) for several atmospheric applications. With the advent of CubeSat technology, many space companies are now extending the GNSS-RO for ionospheric and space weather studies. This study demonstrates the capabilities of Spire’s constellation of CubeSats in detecting ionospheric scintillations. High rate 50 Hz GNSS measurements received by the STRATOS receivers onboard Spires’s CubeSats are used to detect scintillations over low latitude African sector. Spire’s GNSS-RO atmPhs files are accessed from University Corporation for Atmospheric Research (UCAR) data repository along with COSMIC-2 conPhs files.

The amplitude scintillation index (S4) is computed for each COSMIC-2 and Spire RO profiles. While COSMIC-2 conPhs files are restricted to tangent point altitudes up to ~130 km, the scintillation detection algorithm onboard Spire receivers enable to downlink the associated 50 Hz phase and pseudorange data of the extended RO profiles (up to zenith). Spire’s extended RO profiles enable to detect F-layer amplitude scintillations often occurring in post-sunset hours. The occurrences of scintillations are corroborated by equatorial plasma bubble (EPB) structures observed from NASA’s Global‐scale Observations of the Limb and Disk (GOLD) satellite.

This study indicates the potential of Spire GNSS-RO data in augmenting and complementing ionospheric scintillation studies available from COSMIC-2 and other similar RO missions. This capability can provide an important contribution to scintillation monitoring and can further be extended to space weather nowcasts and forecasts

How to cite: Mohanty, S. and Hoque, M. M.: Ionospheric scintillations studies using Spire and COSMIC-2 radio occultation and GOLD satellite data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3149, https://doi.org/10.5194/egusphere-egu23-3149, 2023.

    The ionosphere serves as a critical medium for radio signal propagation in outer space. A good morphology of the global TEC distribution is very useful for both ionospheric studies and their relative applications. In this work, a deep learning framework was constructed for better spatial estimation in ionospheric TEC. Both the DCGAN and WGAN-GP were considered, and their performances were evaluated with spatial completion for a regional TEC. The performances were evaluated using the correlation coefficient, RMSE, and MAE. Moreover, the IAAC rapid products were used to make comparisons. The results show that both the DCGAN and WGAN-GP outperformed the IAAC CORG rapid products. The spatial TEC estimation clearly goes well with the solar activity trend. The RMSE differences had a maximum of 0.5035 TECu between the results of 2009 and 2014 for the DCGAN and a maximum of 0.9096 TECu between the results of 2009 and 2014 for the WGAN-GP. Similarly, the MAE differences had a maximum of 0.2606 TECu between the results of 2009 and 2014 for DCGAN and a maximum of 0.3683 TECu between the results of 2009 and 2014 for WGAN-GP. The performances of the CORG, DCGAN, and WGAN-GP were also verified for two selected strong geomagnetic storms in 2014 and 2017. The maximum RMSEs were 1.8354 TECu and 2.2437 TECu for the DCGAN and WGAN-GP in the geomagnetic storm on February 18, 2014, respectively, and the maximum RMSEs were 1.3282 TECu and 1.4814 TECu in the geomagnetic storm on September 7, 2017. The GAN-based framework can extract the detailed features of spatial TEC daily morphologies and the responses during geomagnetic storms. It shows that the GAN-based framework can extract the detailed features of the spatial TEC responses to geomagnetic storms. Further investigation can be conducted to improve the generator and discriminator architecture of the GAN-based framework for better and higher spatial descriptions of TEC morphology.

How to cite: Liu, Y. and Yang, K.: Global Ionospheric Total Electron Content Completion with a GAN-based Deep Learning Framework, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4087, https://doi.org/10.5194/egusphere-egu23-4087, 2023.

Global Navigation Satellite System (GNSS) is one of the valuable techniques used in researching ionospheric total electron content (TEC). GNSS observations above ground-based stations can be used to obtain high-precision ionospheric TEC with the so-called inverse technique. Subsequently, regional and/or global ionospheric TEC models could be established with some modeling techniques. Ionospheric TEC modeling with GNSS has become a great significance for improving the accuracy of GNSS navigation and positioning, as well as analyzing the ionospheric spatial structure, which is a great motivation to the development of ionospheric TEC modeling. There is no doubt that it is easier to get a satisfactory ionospheric TEC modeling result if the used stations are evenly distributed. However, stations are usually unevenly distributed because of some practical factors. For instance, there are few stations in ocean and Antarctic region. Due to lack of GNSS observations in ocean and Antarctic regions, ionosphere pierce points (IPPs) in these regions are also unevenly distributed or even blank. Consequently, the accuracy of ionospheric modeling is less satisfactory and some negative TEC values without physical meaning even occurred. In order to improve the accuracy of global ionospheric modeling, this work tries to solve this problem by using virtual TEC observations from empirical ionospheric models as constraints in global ionospheric TEC modeling. The spherical harmonic function was employed as the modeling technique, three empirical ionospheric models, Klobuchar, International Reference Ionosphere (IRI) and NeQuick, are used to calculate virtual TEC observations in four regions with no IPP, and GNSS observations above 279 global stations are used to calculate the ionospheric TEC values. Through experimental analysis, this work compares the accuracy improvement in global ionospheric modeling by using additional empirical constraints, and studies performance of the three used empirical ionospheric models in different IPP-blank regions. The results show that additional virtual TEC observations could effectively improve the accuracy of global ionospheric TEC modeling, especially for regions with very few IPPs. The contribution of TEC constraints from empirical models to global ionospheric modeling in different epochs is different. Taking the results in UT11 as an example, three empirical ionospheric models can improve the accuracy of global ionospheric modeling from 11.43 TECU to 3.28, 3.42 and 4.15 TECU, respectively. Generally, improvement performances of the three used empirical ionospheric models in mid-high latitude region and Antarctic are comparably, while Klobuchar model is relatively advantaged in mid-latitude region and IRI model outperforms the others in equator region.

How to cite: Wang, M.: Usage of virtual TEC observations from empirical models for global ionospheric TEC modeling with spherical harmonic function, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4170, https://doi.org/10.5194/egusphere-egu23-4170, 2023.

An ever-increasing fleet of low earth orbiting (LEO) satellites equipped with dual-frequency GNSS receivers can provide slant TEC observations of the topside ionosphere. If occultation measurements are included, the observed range is extended well below LEO altitude also covering the peak of the F2 layer. To reconstruct the topside electron density a large number of observations with good coverage across magnetic latitude and local time with a large variety of elevation angles are required.

Apart from scientific missions like Swarm, GRACE-FO, Sentinel-1/2/3, Jason-3, and COSMIC-2 large fleets of LEO satellites operated by new-space companies like Spire Global help to increase the observation density. The Spire Lemur satellites are 3U cubesats, which carry dual-frequency GPS receivers and thus allow to compute slant TEC measurements.

We will discuss the data quality of TEC measurements derived by both, the scientific and new-space cubesat satellite missions and include Spire GPS data into a three-dimensional ionospheric reconstruction together with GPS data from Swarm, GRACE-FO, Sentinel, Jason-3, and COSMIC-2. B-Splines are used to represent the electron density in magnetic latitude, magnetic local time and altitude. Code biases are co-estimated. Since the scientific satellite missions, apart from the low inclination COSMIC-2 satellites, are in polar obits, special emphasis will be put on the improvements in observation geometry provided by the Spire Lemur satellites.

How to cite: Schreiter, L., Brack, A., Männel, B., Arnold, D., and Jäggi, A.: Electron density reconstruction using fleets of LEO satellites, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5054, https://doi.org/10.5194/egusphere-egu23-5054, 2023.

An accurate estimation of the Thermospheric Neutral Density (TND) is important for predicting the orbit of satellites and objects, for example, those with the altitude of less than 1000 km. Models are often used to simulate TNDs but their accuracy is limited due to uncertainties. Satellite missions such as CHAMP, GRACE, GOCE, Swarm, and GRACE-FO or the Satellite Laser Ranging (SLR) missions can be used to estimate along-track TNDs. However, spatial and temporal coverage of these space borne TNDs is restricted to the mission design. To make the best use of the modelling tools and measurements, we applied these along-track TND measurements within the sequential Calibration and Data Assimilation (C/DA) framework proposed by (Forootan et al., 2022, doi:10.1038/s41598-022-05952-y). The C/DA is used to re-calibrate the NRLMSISE00 model, which is called “C/DA-NRLMSISE00”, whose outputs fit well to the introduced space-borne TNDs. The C/DA-NRLMSISE00 is applicable for forecasting TNDs and individual neutral mass compositions at any predefined vertical level (between ~100 and ~600 km) with user-defined spatial-temporal sampling. Seven periods (between 2003 - 2020) with considerable geomagnetic activity are selected for our investigations because most of the available models lack accuracy to provide reasonable TND simulations. Independent comparisons are performed with the space-borne TNDs that were not used within the C/DA framework, as well as with the outputs of other thermospheric models such as Jacchia-Bowman 2008 (JB2008) and the High Accuracy Satellite Drag Model (HASDM) database. The numerical results indicate that indeed the new model is suitable for producing multi-level global thermospheric neutral density fields.

How to cite: Forootan, E., Farzaneh, S., Kosary, M., Borries, C., Kodikara, T., Doornbos, E., and Schumacher, M.: Assessing a calibration and data assimilation technique for predicting multi-level global thermospheric neutral density fields, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5804, https://doi.org/10.5194/egusphere-egu23-5804, 2023.

Vertical total electron content (VTEC) values are commonly distributed in regular grids by means of the so-called global ionospheric maps (GIMs). Besides the global products, several analysis centers also compute regional ionospheric maps (RIMs) which often incorporate a larger number of GNSS stations, i.e. a denser network, allowing the description of finer structures of the ionosphere. The different global and regional ionospheric products can also present some differences, for instance related to spatial and temporal resolutions. In this work we present a comparison of the performance of seven ionospheric maps: four global, two regional and one hybrid product, which combines regional and global data. The assessment/validation is performed based in ionosonde data and global navigation satellite systems (GNSS) positioning. Data from ionosondes and GNSS stations over the Brazilian region is used during a week with active geomagnetic storm. In general, the performance of RIM products leads to better results considering the ionosonde data approach. The assessment with GNSS positioning leads to larger errors close to the equatorial anomaly; the best performance is obtained with the proposed hybrid product.

How to cite: Jerez, G., Hernández-Pajares, M., Goss, A., Prol, F., Alves, D., Monico, J., and Schmidt, M.: Performance of global and regional ionospheric maps over a low latitude region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8243, https://doi.org/10.5194/egusphere-egu23-8243, 2023.

The total electron content (TEC) measured along different satellite-receiver links is strongly sensitive to severe spatial gradients and rapid changes in the ionosphere. Therefore, key information on space weather conditions and, in particular, on the perturbation degree of the ionosphere is crucial to assure stable and reliable services using Global Navigation Satellite Systems (GNSS) signals. By using dual-frequency GNSS measurements, the German Aerospace Center has developed the Gradient Ionospheric indeX (GIX) and the Sudden Ionospheric Disturbance indeX (SIDX) as proxies capable of estimating spatial and temporal perturbations degree of the ionosphere instantaneously, without the necessity to include historical data in the analysis.

In this talk, we present our advances for characterizing spatial and temporal ionospheric perturbations by utilizing GIX and SIDX in the framework of the Coordinated Ionospheric Study of Scales and Indices (CISSI) initiative, within the scientific activities of the Committee on Space Research (COSPAR). Namely, we report on the outcomes achieved with these approaches when applying them to GNSS datasets acquired over Europe and South America during a stormy and a quiet period of geomagnetic activity in 2015 (Day of Year 75-78 and 142-145, respectively). Moreover, we examine the scientific potential of these ionospheric perturbation indices at different GNSS configurations, latitudinal zones and distance ranges, and discuss their applicability in space weather services.

How to cite: Cahuasquí, J. A., Nykiel, G., Hoque, M., and Jakowski, N.: Ionospheric indices GIX and SIDX for the regional characterization of ionospheric perturbations degree, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10746, https://doi.org/10.5194/egusphere-egu23-10746, 2023.

Atmospheric drag acceleration is the largest non gravitational acceleration acting on low Earth orbiting satellites. Precise models of the drag acceleration are needed for precise orbit determination of satellites that are not equipped with accelerometers. This applies to many Earth observation satellites such as altimeter satellites. The drag acceleration mainly depends on the density of the atmosphere. Both empirical and physical models of the upper atmosphere often fail to provide sufficient estimates of the density. Therefore, we use an ensemble Kalman filter to improve the density estimation of a physical model (TIE-GCM). In previous experiments, we showed that by assimilating accelerometer derived densities from the CHAMP satellite, using a two-step approach, we were able to significantly improve drag predictions for the GRACE satellites. We first calibrated an empirical model using the accelerometer derived densities, evaluated the calibrated model on a regular global grid and then assimilated the gridded densities. The two-step approach enables us to update the state of the atmosphere globally without relying on a correct representation of long-range correlations in the ensemble. Here, we aim to assimilate electron densities in a similar way. The electron densities are computed from a 4D model based on GNSS and satellite altimetry data as well as radio occultation measurements.

How to cite: Corbin, A., Vielberg, K., Schmidt, M., and Kusche, J.: Assimilation of gridded neutral and electron densities into TIE-GCM, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11784, https://doi.org/10.5194/egusphere-egu23-11784, 2023.

The forecast of the occurrence of scintillation for end-use predictions over the Indian region is a challenging task. In the context of this challenge, the understanding of the day-to-day spatial and temporal variability of the post-sunset equatorial F-region ionospheric irregularities represents a very important problem. Notably, the spatial (zonal) variations in the scintillation occurrence depends upon the day-to-day perturbations in the equatorial vertical ExB drift and the zonal movement of scintillation patches follow the zonal ExB drift patterns. A conceptual framework that combines information from scintillation indices (as derived from the GNSS receivers) with modelled background information (as derived from physics based ionospheric models) is proposed. The idea is to understand the dependence of local morphology on the physical mechanisms responsible for the formation of the equatorial F-region ionospheric irregularities in the range of 9^o N to 18^o N geographical latitudes and 74^o E to 82^o E geographic longitudes respectively. The Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) is chosen as a background model to provide several parameters of significance in this context. A day-wise correlation analysis for the year 2014 (high solar activity year) is performed between all the TIEGCM model outputs and observed S₄ index variations within the above mentioned pre-defined geographical boundary. The output parameters (e.g., equatorial zonal ExB drift, vertical ExB drift, critical height) show positive correlation with the observed post sunset variations in the S₄ index. Moreover, the zonal ExB drift is also ingested with observations from the Communication/Navigation Outage Forecast System (C/NOFS) satellite. A method to infer the zonal and vertical ExB drifts from the combination of TIEGCM outputs, C/NOFS in-situ data, and GNSS S₄ observations is introduced on the basis of a two-dimensional image evaluation approach. This framework establishes a basis for the prediction of spatial ionospheric irregularities over the region of interest.

How to cite: Babu Sree Harsha, P., Forte, B., and Dashora, N.: Conceptual framework enabling the spatio-temporal analysis of post-sunset equatorial ionospheric irregularities for space weather forecast, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12816, https://doi.org/10.5194/egusphere-egu23-12816, 2023.