Japan Geoscience Union Meeting 2023

Presentation information

[E] Online Poster

P (Space and Planetary Sciences ) » P-EM Solar-Terrestrial Sciences, Space Electromagnetism & Space Environment

[P-EM15] Study of coupling processes in solar-terrestrial system

Fri. May 26, 2023 3:30 PM - 5:00 PM Online Poster Zoom Room (4) (Online Poster)

convener:Mamoru Yamamoto(Research Institute for Sustainable Humanosphere, Kyoto University), Yasunobu Ogawa(National Institute of Polar Research), Satonori Nozawa(Institute for Space-Earth Environmental Research, Nagoya University), Akimasa Yoshikawa(Department of Earth and Planetary Sciences, Kyushu University)

On-site poster schedule(2023/5/26 17:15-18:45)

3:30 PM - 5:00 PM

[PEM15-P02] Improvement and case analysis of three dimensional ionospheric tomography based on GNSS-TEC observation with ionosonde data assimilation

*Taisei Nozaki1, Susumu Saito2, Nicholas Ssessanga3, Mamoru Yamamoto1 (1.Research Institute for Sustainable Humanosphere, Kyoto University, Japan, 2.Electronic Navigation Research Institute, National Institute of Maritime, Port, and Aviation Technology, Japan, 3.4-D Space, Department of Physics, University of Oslo, Blindern, 0316 Oslo, Norway)

Keywords:Tomography, Data assimilation, 3D-VAR

Structures of the electron density in the ionosphere cause reflection, absorption, and delay of radio waves, which can lead to interference in radio communications. Therefore, the observation of the ionospheric electron density is of great importance. One method of ionospheric analysis is tomography, which estimates the three-dimensional structure of the ionosphere from the GNSS-TEC observation data.
The original algorithm employed to cover the Japanese archipelago and the nearby surrounding region was the constrained least-squared fitting method implemented by Seemala et al. (2014) and Suzuki (2016). The method used the spatial gradient of the electron density as the constraint, and in addition, introduced boundary conditions at the top and the bottom to stabilize the results. The original algorithm was stable and useful. But it had problems with negative electron density as the solution. It also tended to estimate the peak electron density higher than the true height during autumn and winter.
To solve these problems, Ssessanga et al. (2021) proposed an improved algorithm based on a 3D-VAR method by adding ionosonde data. Recently we analyzed the improved version, and a discussion with the authors (private communication) revealed some inconsistencies in the background error covariance matrix (B), which specifies the correlation of voxels in vertical and horizontal directions. This study presents results after improving B; a comparison of the tomography solution of the modified algorithm and the original algorithm using MU radar’s observation confirmed that the modified algorithm improved the accuracy of peak height estimation. Also, a case study was conducted on the traveling ionospheric disturbance (TID) event from the Tonga eruption in January 2022. This is a unique ionospheric event, and the results were validated by modifying the algorithm.