G5.1

G5 EDI

The term space weather indicates physical processes and phenomena in space caused by the radiation of energy mainly from the Sun. Solar and geomagnetic storms can cause disturbances in positioning, navigation and communication; coronal mass ejections (CME) can affect serious disturbances and in extreme cases damages or even destruction of modern infrastructure. The ionosphere and the thermosphere are parts of a physically coupled systems ranging from the Earth surface to the Sun including the magnetosphere and the lower atmosphere. Therefore, conducting detailed investigations on governing processes in the solar-terrestrial environment have key importance to understand the spatial and temporal variations of ionospheric and thermospheric key parameters such as the total electron content (TEC) and the plasma density of the ionosphere, as well as the thermospheric neutral density, which are influencing the orbits of Low-Earth orbiting (LEO) satellites. To address all these interrelations and impacts, the Global Geodetic Observing System (GGOS) Focus Area on Geodetic Space Weather Research was implemented into the structure of the International Association of Geodesy (IAG).

This session will address recent progress, current understanding, and future challenges of thermospheric and ionospheric research including the coupling processes. Special emphasise is laid on the modelling and forecasting of space weather time series, e.g. EUV-, X-ray radiation and CMEs, and their impact on VTEC and electron density. We encourage further contributions to the dynamo electric field, the variations of neutral and ion compositions on the bottom and top side of the ionosphere, atmospheric gravity waves and TIDs. Furthermore, we appreciate contributions on the wind dynamo, electrodynamics and disturbances, including plasma drift, equatorial spread F, plasma bubbles, and resultant scintillation.

Another main topic is global and regional high-resolution and high-precision modelling of VTEC and the electron density based on empirical, analytical or physical data assimilation approaches, which are designed for post-processing or (near) real-time purposes.

Convener: Ehsan ForootanECSECS | Co-conveners: Andreas GossECSECS, Kristin VielbergECSECS, Mona KosaryECSECS, Michael Schmidt
Presentations
| Mon, 23 May, 08:30–11:05 (CEST)
 
Room -2.91

Presentations: Mon, 23 May | Room -2.91

Chairperson: Randa Natras
Ionosphere
08:30–08:37
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EGU22-4273
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Presentation form not yet defined
Oleg Zolotov and Maria Knyazeva

Many ionospheric studies require the global state of the Earth’s ionosphere D-Region. It is valuable for HF-band radio-waves propagation problems and as the lower boundary and/or initial conditions for the numerical modeling. A robust D-Region model is also required as the reference state that may be used for data interpretation, assimilation, to fill missed values, or as a convenient representation of observations. The existing trend of Python scientific infrastructure application for the ionosphere and space weather modeling triggers the need for a D-Region model for the Python ecosystem.


FIRI-2018 is a mature model of the Earth’s non-auroral non-disturbed ionospheric D-Region. It is the successor of FT-2001, a model included into IRI-2016, which is the de-facto standard model of the Earth’s ionosphere. To an end-user, the FIRI-2018 model was provided by Friedrich et al. (2018, https://doi.org/10.1029/2018JA025437 ) as a set of pre-calculated reference electron density profiles for the Northern Hemisphere. pyFIRI (https://doi.org/10.1016/j.softx.2021.100885) is the Python3 package built on top of those reference profiles. Our presentation aims to describe the principal features of the pyFIRI package and to highlight our preliminary results on FIRI-2018 extrapolation to the Southern Hemisphere.


Acknowledgement. Authors are grateful to Dr. Martin Friedrich for the fruitful discussion and detailed consulting on the FIRI-2018 model. We acknowledge Dr. Martin Friedrich, Dr. Klaus Torkar, and Christoph Pock for making FIRI-2018 data freely available, and for kind permission to adopt these data for the pyFIRI package. Without this, the pyFIRI package would not be possible to develop. 

How to cite: Zolotov, O. and Knyazeva, M.: On pyFIRI implementation: non-disturbed non-auroral ionospheric D-Region model for the Python ecosystem, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4273, https://doi.org/10.5194/egusphere-egu22-4273, 2022.

08:37–08:44
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EGU22-5129
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ECS
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Virtual presentation
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Lucas Schreiter, Guram Kervalishvili, Jan Rauberg, Claudia Stolle, Jose van den Ijssel, Daniel Arnold, Chao Xiong, and Andyara Oliveira Callegare

Topside Ionosphere Radio Observations from multiple Low Earth Orbiting (LEO)-missions (TIRO) is a project in ESA’s Swarm Data, Innovation, and Science Cluster (DISC) framework. TIRO provides high accuracy Total Electron Content (TEC) from dual-frequency GPS receivers onboard CHAMP (2000-2010), GRACE (2002-2017), and GRACE Follow-On (since 2018) missions. Special emphasis is put to ensure maximum consistency between the previously and operationally derived data sets from GOCE and Swarm to investigate conjunctions and thus ensure the consistency of the entire timeline from as early as CHAMP up to GRACE-FO. The primary science instrument onboard GRACE and GRACE-FO is a K-Band inter-satellite ranging system, which in this study is used to derive an estimate of the in-situ electron density. The derived electron density will be validated using both, the International Reference Ionosphere (IRI) model and radar observations taken at Millstone Hill, Arecibo, EISCAT, Resolute Bay, and Jicamarca. 

 

In combination, these products form long-term series and almost cover two full solar cycles by the continuous TEC data set and electron density either taken by CHAMP, GRACE, Swarm, or GRACE-FO. We will present climatological studies as well as case studies of selected events, such as equatorial plasma depletions, simultaneously observed by GPS and K-Band.  

How to cite: Schreiter, L., Kervalishvili, G., Rauberg, J., Stolle, C., van den Ijssel, J., Arnold, D., Xiong, C., and Callegare, A. O.: Topside Ionosphere Radio Observations from multiple LEO-missions , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5129, https://doi.org/10.5194/egusphere-egu22-5129, 2022.

08:44–08:51
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EGU22-8475
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Virtual presentation
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Karolina Kume, Yuri Shprits, Artem Smirnov, Irina Zhelavskaya, Ruggero Vasile, and Stefano Bianco

This study introduces a new two-step neural-network based approach for modelling vertical total electron content (VTEC) on a global level. The inputs to the neural network are chosen and evaluated through different feature selection techniques, namely time-lagged Pearson cross-correlation, mutual information, random forests and permutation feature importance. The feature sets consist of geomagnetic and solar wind indices, their time histories and geomagnetic and geographic coordinates. The parameters of the neural networks are tuned with cross validation and the final model is tested in extended time intervals covering a wide range of solar activity conditions. The proposed approach increases computational efficiency and provides with a high generalization skill.

How to cite: Kume, K., Shprits, Y., Smirnov, A., Zhelavskaya, I., Vasile, R., and Bianco, S.: Modelling global vertical total electron content with machine learning, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8475, https://doi.org/10.5194/egusphere-egu22-8475, 2022.

08:51–08:58
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EGU22-8785
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Virtual presentation
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Wojciech Jarmolowski, Enric Monte-Moreno, Paweł Wielgosz, Jacek Paziewski, Manuel Hernandez-Pajares, Wojciech Miloch, Yaqi Jin, Jens Berdermann, Mainul Hoque, Per Høeg, Alberto Garcıa Rigo, Beata Milanowska, Lasse Clausen, Heng Yang, Haixia Lyu, and Raul Orús-Pérez

The objective of the work is to compare geomagnetic storm impact on the ionosphere parameters measured from ground-based GNSS permanent stations and Swarm satellites. The analyses compare the changes of vertical total electron content (VTEC) measured along the entire ionosphere cross-section to the variations of electron density (ED) on the orbit, at ~500 km altitude. The objective is how sensitive are the measures of electric field variations available on the Earth, with respect to those obtained from the satellite orbit. The study applies Swarm in-situ ED measured by Langmuir Probes (LP), topside TEC from onboard Swarm GNSS receivers and vertical TEC determined from ground-based GNSS stations available in the area of the Northern polar cap. Ground and satellite data were processed in different ways. Ground-based VTEC is available at number of stations providing heterogeneous but useful horizontal coverage. Therefore ROTI values were calculated from VTEC as gradient values capable to indicate the disturbances. These ROTI values were interpolated spatially to obtain maps. Swarm passes over the polar cap starting from 45° lasts for several minutes each, and repeat in this region approximately every 1.5 h. Such along-track collected small data samples are useless in horizontal correlation analysis. Therefore Swarm data disturbances, in this case, are extracted with the use of Fourier transform-based filtering and are also analyzed in the spectrograms based on short-term Fourier transform (STFT). The case study has used three geomagnetic storms, namely: the St. Patrick storm of March 17, 2015, the storm on June 22, 2015, and the storm on August 25-26, 2018. The results reveal differences in storm impact on VTEC measured by GNSS on the Earth, with respect to the storm influence on topside TEC and in-situ ED disturbances measured onboard the Swarm. The overall summary statistics provide some preliminary conclusions on different times of the reaction to the storm. Additionally, some interesting differences between FT filtering and a very popular moving average are shown, with respect to Swarm data. The research was done in the frame of the FORSWAR project (Forecasting Space Weather in the Arctic Region) funded by ESA.

How to cite: Jarmolowski, W., Monte-Moreno, E., Wielgosz, P., Paziewski, J., Hernandez-Pajares, M., Miloch, W., Jin, Y., Berdermann, J., Hoque, M., Høeg, P., Garcıa Rigo, A., Milanowska, B., Clausen, L., Yang, H., Lyu, H., and Orús-Pérez, R.: Swarm in-situ electron density disturbances over Greenland compared to VTEC disturbances from ground-based GNSS, during three geomagnetic storms, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8785, https://doi.org/10.5194/egusphere-egu22-8785, 2022.

08:58–09:05
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EGU22-8931
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On-site presentation
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Anna Krypiak-Gregorczyk, Beata Milanowska, Michael Schmidt, Andreas Goss, Eren Erdogan, Wojciech Jarmołowski, and Paweł Wielgosz

In the last decades, advances in satellite technologies, data analysis techniques, and models, and a growing number of analysis centers allow modeling the ionospheric electron content with unprecedented accuracy. International GNSS Service (IGS) Ionosphere Associated Analysis Centers (IAAC) continuously provide global ionospheric maps (GIMs) based on processing GNSS data from the ground IGS network. It is a great advantage that these GIMs are often based on very different modeling techniques and thus, are also characterized by different accuracy levels. Due to the dynamic nature of the ionosphere, there is a permanent need to improve the modeling techniques of ionospheric key parameters such as the vertical total electron content (vTEC).

In this presentation, we evaluate a new ionosphere model from DGFI-TUM denoted OTHG, which is a candidate for a new IGS IAAC product. The OTHG model is based on tensor products of trigonometric B-spline functions in longitude and polynomial B-spline functions in latitude for a global representation (Goss et al. 2019). Here, we complement our earlier investigations of the seven analysis center models (Wielgosz et al. 2021) with new results for the OTHG GIMs. For these investigations, we use our own validation methodology presented in Krypiak-Gregorczyk et al. (2017), which is based on GIM-derived slant TEC (sTEC) comparison with carrier phase geometry-free combination of GNSS signals. In the presented study, we use one year of GNSS data collected by 25 globally distributed stations. The overall yearly RMS value is calculated for each product based on all 365 days of continuous observations from all stations. The results show that the overall RMS of the tested GIMs ranges from 0.93 TECU to 1.29 TECU. The OTHG GIMs performed as one of the best. In addition, GIM vTEC comparisons to Jason-2 and Jason - 3 altimetry data are studied. In these analyses, the OTHG GIMs also showed a good performance. Therefore, it can be concluded that  DGFI-TUM is a valuable ionospheric product for the research community.

 

Goss A., Schmidt M., Erdogan E., Görres B., Seitz F. (2019) High-resolution vertical total electron content maps based on multi-scale B-spline representations. Annales Geophysicae, 37(4), 10.5194/angeo-37-699-2019

Krypiak-Gregorczyk A., Wielgosz P., Borkowski A. (2017) Ionosphere Model for European Region Based on Multi-GNSS Data and TPS Interpolation, Remote Sensing, 9(12), 1221,  DOI:10.3390/rs9121221

Wielgosz P., Milanowska B., Krypiak-Gregorczyk A., Jarmołowski W. (2021) Validation of GNSS‑derived global ionosphere maps for different solar activity levels: case studies for years 2014 and 2018. GPS Solutions 25, 103. https://doi.org/10.1007/s10291-021-01142-x

How to cite: Krypiak-Gregorczyk, A., Milanowska, B., Schmidt, M., Goss, A., Erdogan, E., Jarmołowski, W., and Wielgosz, P.: Validation of DGFI-TUM’s new ionosphere model: case studies for year 2018, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8931, https://doi.org/10.5194/egusphere-egu22-8931, 2022.

09:05–09:12
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EGU22-11458
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ECS
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Virtual presentation
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Ningbo Wang, Yan Zhang, Zishen Li, Yang Li, and Andrzej Krankowski

Benefiting from the global multi-frequency and multi-constellation GNSS measurements provided by the International GNSS Real-Time Service (IGS-RTS), real-time global ionospheric maps (RT-GIMs) have been generated by the Chinese Academy of Science (CAS), Centre National d’Etudes Spatiales (CNES) and Universitat Politècnica de Catalunya (UPC) since 2017, and late by Wuhan University (WHU) since late 2020. To provide a more stable real-time ionospheric correction stream for precise GNSS application and ionospheric space weather monitoring, an experimental combined RT-GIM has been generated at CAS since late-2021 using real-time streams from CNES, UPC, WHU, and CAS itself. CAS combined RT-GIM streams are transmitted in both RTCM-SSR (IONO01IGS0) and IGS-SSR (IONO01IGS1) standards, which are freely accessible from IGS (products.igs-ip.net:2101) and CAS (cas-ip.gipp.org.cn:2101) casters. Following the motivation for the RT-GIM combination, the method used to generate the CAS combined RT-GIM is described in detail. The performance of CAS combined RT-GIM is validated in both RT-GPS dSTEC and single-frequency precise point positioning (SF-PPP) domains by comparison with the existing combined RT-GIM provided by UPC. CAS combined RT-GIM is presently validated and analyzed for a short period (2-3 months), and the analysis covering different time spans (e.g., different seasons) is being done together with the RT-GIM combination.

How to cite: Wang, N., Zhang, Y., Li, Z., Li, Y., and Krankowski, A.: Combination of IGS Real-Time Global Ionospheric Maps at CAS: Method and Analysis, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11458, https://doi.org/10.5194/egusphere-egu22-11458, 2022.

09:12–09:19
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EGU22-10430
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On-site presentation
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Juan Andrés Cahuasquí, Mainul Hoque, and Norbert Jakowski

GNSS single-frequency applications are affected by the interaction of the radio signals with the free electrons of the ionosphere, introducing range errors of up to 100 m in the L-band. Besides the GPS Klobuchar and the Galileo NeQuick ionospheric models, also the Neustrelitz Total Electron Content Model (NTCM) has been proposed as a practicable solution to mitigate such propagation errors.

In this investigation we present a global statistical validation of the NTCM version driven by Galileo ionization coefficients (NTCM-GlAzpar) by comparing its performance with the performance achieved by the NeQuickG and Klobuchar models in the position domain. For this aim, we used the ESA analysis tool “gLAB” in the Standard Point Positioning (SPP) mode and GNSS data over two different time periods. The first period covers one month of perturbed solar activity (December 2014) and the second period corresponds to a month of quiet conditions (December 2019). We achieved a worldwide coverage with data from up to 73 receivers of the International GNSS Service (IGS).

Our statistical analysis allows us to conclude that the NTCM-GlAzpar model clearly outperforms the results achieved with the Klobuchar model and is slightly better, or at least comparable, to the performance shown by NeQuickG. Indeed, the root mean squared (RMS) values of the hourly mean 3D position errors obtained for the global dataset are 4.36, 4.61 and 6.71 meters for perturbed conditions and 2.32, 2.35 and 2.75 meters for the quiet period, respectively for the NTCM-GlAzpar, NeQuickG and Klobuchar models. Nevertheless, through a geographic- and diurnal-specific analysis, we identify also that the performance of NTCM-GlAzpar slightly decreases for conditions of reduced solar activity – at night time, higher latitudes and low perturbations.

We further discuss the applicability of the NTCM-GlAzpar ionospheric model in GNSS single-frequency applications motivated by its simple software adaptations and low computational cost.

How to cite: Cahuasquí, J. A., Hoque, M., and Jakowski, N.: Positioning performance of the Neustrelitz Total Electron Content Model (NTCM) driven by Galileo ionization coefficients, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10430, https://doi.org/10.5194/egusphere-egu22-10430, 2022.

09:19–09:26
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EGU22-9517
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Virtual presentation
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Isabel Fernandez-Gomez, Timothy Kodikara, Claudia Borries, Ehsan Forootan, Michael Schmidt, and Mihail Codrescu

During geomagnetic storms, communication and navigation instruments can be dramatically affected by the rapid changes that occur in the upper atmosphere. The assimilation of data in physics-based models such as the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) model through and ensemble Kalman filter, can improve the representation of the thermosphere-ionosphere (TI) system. Due to the coupled nature of the TI system, the ionosphere is affected by, among others, changes in the neutral atmosphere. In this study, we investigate the capability of the CTIPe model to provide better estimates of the ionosphere by improving its specification of the thermosphere via data assimilation. Here, we assimilate thermospheric mass density (TMD) observations from the Swarm mission normalized to 400 km altitude during the 2015 St. Patrick’s Day storm. The changes that occur in the ionosphere due to assimilation of TMD data are measured by means of the difference between the model results with and without assimilation. To measure the improvement gained with data assimilation, we compare with independent measurements of electron density along the orbit of GRACE (Gravity Recovery and Climate Experiment) satellite, that shows a reduction in the root mean square error (RMSE) by a 22% with respect to the non-assimilation run. The impact on the global scale is measured by comparing the CTIPe model results with the corresponding output of the 3D B-Spline electron density model. The results illustrate that the electron density equatorial region is the most affected region by assimilation of TMD, with an average RMSE reduction of 25% at the assimilation altitude of 400 km.

How to cite: Fernandez-Gomez, I., Kodikara, T., Borries, C., Forootan, E., Schmidt, M., and Codrescu, M.: Improving the ionospheric state estimate during geomagnetic storm time through assimilation of neutral density data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9517, https://doi.org/10.5194/egusphere-egu22-9517, 2022.

09:26–09:33
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EGU22-4764
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ECS
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Virtual presentation
Evaluation of amplitude and phase scintillation impact on GPS and Galileo frequencies 
(withdrawn)
Ana Lucia Christovam de Souza, Gabriel Oliveira Jerez, and Paulo de Oliveira Camargo
09:33–09:40
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EGU22-8459
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ECS
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Virtual presentation
Gabriel Jerez, Manuel Hernández-Pajares, Andreas Goss, Crislaine Silva, Daniele Alves, and João Monico

The vertical total electron content (VTEC) is one of the main quantities to describe the state of the ionosphere. To dispose this information is important to mass market Global Navigation Satellite System (GNSS) users to correct the ionospheric delay for positioning. The VTEC values and the corresponding standard deviations are routinely provided in the so-called Global Ionosphere Maps (GIM), with time intervals of 2, 1 and 0.25 hours on regular grids with 2.5º resolution in latitude and 5º resolution in longitude. To determine the ionospheric corrections from the GIMs for positioning applications, a quadratic interpolation is typically applied to the VTEC grid values which generally does not take into account the VTEC uncertainties. In this context, the impact of the use of the VTEC standard deviation is assessed in the positioning domain, considering the GIMs of two different analysis centers. The impact of the VTEC uncertainties is analyzed by means of single-frequency precise point positioning (PPP), applied to four Brazilian GNSS stations in different regions, considering four scenarios: geomagnetic storm, low solar flux and high solar flux (equinox and solstice). The use of the VTEC uncertainties values provided a significant improvement coinciding with high solar flux, especially for stations in regions under the most intense ionospheric effect, with mean rates of improvements up to 47%.

How to cite: Jerez, G., Hernández-Pajares, M., Goss, A., Silva, C., Alves, D., and Monico, J.: Impact of GIM uncertainties on the single-frequency PPP over the Brazilian region, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8459, https://doi.org/10.5194/egusphere-egu22-8459, 2022.

09:40–09:47
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EGU22-2189
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ECS
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Virtual presentation
Barbara Suesser- Rechberger, Sandro Krauss, Manuela Temmer, Sofia Kroisz, Lukas Drescher, Saniya Behzadpour, and Torsten Mayer-Gürr

Low earth orbiting (LEO) satellites can be affected by space weather events like coronal mass ejections (CMEs) in such a way that the drag force acting on the spacecraft is enhanced due to increasing atmospheric neutral density. As a consequence, this leads to an additional storm induced orbit decay. LEO satellites equipped with accelerometers offer the possibility to deduce information on the current state of the atmospheric neutral mass density based on the measurements of non-gravitational forces acting on the spacecraft. However, satellites with suitable onboard accelerometers are extremely rare. An alternative method to derive atmospheric densities along a satellite trajectory can be realized through the usage of global navigation satellite system (GNSS) based kinematic orbit information. This approach offers the advantage that that theoretically almost every LEO satellite mission which is tracked by GNSS can be used for the evaluation. In addition, through the increasing number of analysable satellites the explorable altitude range can be expanded to 300 km - 800 km. Thus, a tomography of the upper Earth’s atmosphere is feasible and the impact of a solar event on a satellite can be estimated as a function of its orbital altitude. In this study, we present density estimates based on kinematic orbits during quiet and active solar periods. The results are compared to state-of-the-art thermosphere models like the NRLMSIS 2.0, JB2008 and HASDM. In the case of extreme solar events the investigations are extended by estimating the storm induced orbit decay for different altitudes and satellites.

How to cite: Suesser- Rechberger, B., Krauss, S., Temmer, M., Kroisz, S., Drescher, L., Behzadpour, S., and Mayer-Gürr, T.: Kinematic orbits and their usage in determining space weather storms induced orbit decays, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2189, https://doi.org/10.5194/egusphere-egu22-2189, 2022.

09:47–10:00
Thermosphere
Coffee break
Chairperson: Randa Natras
10:20–10:27
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EGU22-6303
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Virtual presentation
Michael Schmidt, Lea Zeitler, Armin Corbin, Kristin Vielberg, Sergei Rudenko, Anno Löcher, Mathis Bloßfeld, and Jürgen Kusche

A major problem in the precise orbit determination of Low-Earth-Orbiting (LEO) satellites at altitudes below 1000 km is the modeling of the aerodynamic drag which mainly depends on the thermospheric density and causes the largest non-gravitational acceleration. Typically, empirical thermosphere models such as NRLMSISE-00, JB2008 or DTM2013 are used to calculate density values at satellite positions. However, since the current thermosphere models cannot provide the required accuracy, unaccounted variations in the thermospheric density may lead to significantly incorrect satellite positions.

At EGU 2021, we presented a study comparing thermospheric density corrections for the NRLMSISE-00 model in terms of scale factors calculated from satellite laser ranging (SLR) measurements to various  spherical LEO satellites (Starlette, Stella, Larets, etc.) with the corresponding values from accelerometer measurements on-board CHAMP and GRACE. In the meantime we significantly extended our study and published the results (Zeitler et al. 2021).

Our results demonstrate that both measurement techniques can be used to derive comparable (with correlations of up to 80% and more depending on altitude) scale factors of the thermospheric density with a temporal resolution of 12 hours, which vary around the value 1. This indicates to which extent the NRLMSISE-00 model differs from the observed thermospheric density. On average, during high solar activity, the model underestimates the thermospheric density and should be scaled up using the estimated scale factors. We find our estimated scale factors close to the results from Emmert et al. (2021); except for the most recent period where a different trend is observed. We also find a linear decrease of the estimated thermospheric density scale factors above 680 km of about −5% per decade due to climate change. This fits well to the results from Solomon et al. (2015). Furthermore, we validate the approach of deriving scale factors from SLR measurements by using two independent software packages.

Emmert, J. T., Dhadly, M. S., & Segerman, A. M. (2021). A Globally Averaged Thermospheric Density Data Set Derived From Two-Line Orbital Element Sets and Special Perturbations State Vectors. Journal of Geophysical Research: Space Physics, 126 (8), e2021JA029455. doi: 10.1029/2021JA029455

Solomon, S. C., Qian, L., & Roble, R. G. (2015). New 3-D simulations of climate change in the thermosphere. Journal of Geophysical Research: Space Physics, 120 (3), 2183–2193. doi: 10.1002/2014JA020886

Zeitler L., Corbin A., Vielberg K., Rudenko S., Löcher A., Bloßfeld M., Schmidt M., & Kusche J. (2021). Scale factors of the thermospheric density ‐ a comparison of SLR and accelerometer solutions. Journal of Geophysical Research: Space Physics, 126, e2021JA029708. doi: 10.1029/2021JA029708

How to cite: Schmidt, M., Zeitler, L., Corbin, A., Vielberg, K., Rudenko, S., Löcher, A., Bloßfeld, M., and Kusche, J.: A comparison of scale factors for the thermospheric density from Satellite Laser Ranging and Accelerometer Measurements to LEO satellites, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6303, https://doi.org/10.5194/egusphere-egu22-6303, 2022.

10:27–10:34
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EGU22-7702
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ECS
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On-site presentation
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Florian Wöske and Benny Rievers

The neutral mass density of the upper atmosphere (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 the satellites, are a very useful observation for precise density determination also on very short time scales.

Nevertheless, the accelerometers of geodetic satellites are affected by bias and drift. Therefore a calibration of the data is indispensable. A time dependent bias and scale factor are to be determined. Usually calibration parameters are estimated by dynamic Precise Orbit Determination (POD) or Gravity Gield Recovery (GFR), together with all other parameters of interest. In both cases, the estimated accelerometer calibration parameters are not the major interest. With the used parametrizations and weighting of the observations, good gravitational field and orbit solutions, do not necessarily give good or physical accelerometer calibration solutions. This is unsatisfying, especially for the anticipated use in density determination and the direct comparison to modeled non-gravitational accelerations.

In this contribution we use dynamic POD and investigate different parametrization strategies tailored for an accurate and physical accelerometer calibration for thermospheric density determination. For example we investigate the effect of constraining the accelerometer calibration parameters in that way, that a continuous calibration over all arcs is achieved, where normally each arc is treated locally separated from all other arcs, leading to jumps in the calibration. The scale factor, which is highly correlated to the estimated bias, is concurrently estimated but over a longer batch of arcs. We compare different bias parametrizations, arc lengths, as well as different observation data and weighting strategies.

Finally we show some preliminary density estimation results with our approach and the influence of the accelerometer calibration.

How to cite: Wöske, F. and Rievers, B.: Accelerometer calibration for thermospheric neutral density estimation with GRACE data by dynamic Precise Orbit Determination (POD) with tailored parametrization, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7702, https://doi.org/10.5194/egusphere-egu22-7702, 2022.

10:34–10:41
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EGU22-9644
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Presentation form not yet defined
Ehsan Forootan, Mona Kosary, Saeed Farzaneh, and Maike Schumacher

Atmospheric drag has a direct relationship with the thermospheric neutral density (TND) and represents a considerable impact on the precise orbit determination (POD) and prediction of low Earth orbit (LEO) satellites, for example those with the altitude of less than 1000 km, as well as space debris. The distribution of TND combined with the solar and geomagnetic activity has a direct impact on the electron distribution in the ionosphere. The latter is important for medium- and long-range high frequency communication, positioning, and over-the-horizon radar systems. New capabilities to understand, model and predict thermosphere variables are typically provided by models; however, the quality of them is limited due to their imperfect structure and uncertainty of their inputs. In this study, we present various data assimilation frameworks to take advantage of freely available accelerometer derived TNDs from GRACE, GRACE-FO and Swarm missions. This is realized by (1) formulating ensemble Kalman filter (EnKF)-based calibration and data assimilation (C/DA) procedures to update the model's states (and simultaneously calibrates its key parameters if needed); and (2) an empirical decomposition-based data assimilation is applied to merge satellite derived along-track estimates with global model derived TND simulations. The results of these two frameworks are then evaluated against independent measurements. The technical challenges and benefits are discussed in detail.

How to cite: Forootan, E., Kosary, M., Farzaneh, S., and Schumacher, M.: Assimilation frameworks for merging accelerometer derived thermospheric neutral mass density estimates with empirical and physical models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9644, https://doi.org/10.5194/egusphere-egu22-9644, 2022.

10:41–10:48
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EGU22-2911
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ECS
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Virtual presentation
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Armin Corbin, Kristin Vielberg, and Jürgen Kusche

The TIE-GCM (Thermosphere Ionosphere Electrodynamics General Circulation Model) is a numerical model of the upper atmosphere, providing extensive information about the neutral and charged particles therein. It enables simulations of the neutral density that is required to compute the drag acceleration acting on satellites. We have developed an assimilative version of the TIE-GCM using PDAF (Parallel Data Assimilation Framework), to improve the neutral density modeling and the derived drag acceleration. Here, we present an experiment in which we assimilate neutral densities from a calibrated empirical model into the TIE-GCM: In a first step, we have scaled the NRLMSIS2.0 with densities derived from the CHAMP accelerometer, then evaluated it on a regular grid and finally assimilated the neutral densities into the TIE-GCM. We assess the performance of the assimilation framework using densities derived from the CHAMP and GRACE acceleromerters. The investigated time period includes quiet and stormy conditions.

How to cite: Corbin, A., Vielberg, K., and Kusche, J.: An Assimilative Version of TIE-GCM using PDAF, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2911, https://doi.org/10.5194/egusphere-egu22-2911, 2022.

10:48–10:55
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EGU22-282
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ECS
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Virtual presentation
Mona Kosary, Ehsan Forootan, Saeed Farzaneh, and Maike Schumacher

An accurate simulation global thermospheric neutral density (TND) on various altitudes is important for geodetic and space weather applications. In addition, this is essential for designing the low-Earth-orbit (LEO) missions, predict their missions’ lifetime and performing a reliable attitude control. Although empirical and physics-based models typically simulate TND variations, the quality of these models is limited due to various structural simplifications and the uncertainty of inputs. Here, we present an ensemble Kalman filter (EnKF)-based calibration and data assimilation (C/DA) technique that updates the model's states and simultaneously calibrates its key parameters. The proposed approach provides the opportunity to improve the now-cast and forecast skills of the NRLMISISE-00 and NRMSIS-2.0 models through re-calibrating the model’s key parameters including those controlling the influence of solar radiation and geomagnetic activity as well as those related to the calculation of exospheric temperature.

In this research, TND estimates from on-board accelerometer measurements of GRACE, GRACE-FO and Swarm are ingested as observations into the NRLMSISE-00 and NRLMSIS-2.0 models based on the C/DA. The newly calibrated model, called here ‘C/DA-NRLMSISE’, is then used to simulate global maps of TND as well as individual neutral mass densities covering the altitudes of 300-600 km. Various investigations are performed to test the temporal and vertical consistency of the TND outputs from C/DA-NRLMSISE.

How to cite: Kosary, M., Forootan, E., Farzaneh, S., and Schumacher, M.: A Calibration and Data Assimilation Approach to Use GRACE, GRACE-FO and Swarm Accelerometer Measurements for Forecasting Global and Multi-level Thermospheric Neutral Density Fields, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-282, https://doi.org/10.5194/egusphere-egu22-282, 2022.

10:55–11:05