11:00 〜 13:00
[PEM09-P11] Relationship between solar cycle variation of solar radio and EUV spectra
キーワード：太陽活動周期、電波放射、EUV放射
Extreme ultraviolet (EUV) emission from the Sun is absorbed by the Earth's thermosphere, affecting the formation of the ionosphere and the heating and density increase of the thermosphere. Since EUV emission does not reach the ground and observational data are limited during the satellite observation, microwave observations at 2.8 GHz, which called F10.7 have traditionally been used as proxies for EUV emission to estimate the impact of solar emission on the Earth's environment. However, recent satellite observations of EUV emission have shown that there is a discrepancy in the flux variation between F10.7 and the EUV emission affecting the Earth's ionosphere.
In this study, we investigate the solar cycle variation of the relationship between microwave and EUV emission spectra using data from the Nobeyama Radio Polarimeter (NoRP) and Thermosphere • Ionosphere • Mesosphere • Energetics and Dynamics (TIMED)/Solar Extreme ultraviolet Experiment (SEE). The NoRP measures the flux of microwave emissions from the full Sun at multiple frequencies (1, 2, 3.75, and 9.4 GHz), and TIMED/SEE measures the EUV emission spectrum in the range of 0.5 -190 nm with a resolution of 1 nm. We use daily data and the relationships between these microwaves and EUV emissions were investigated. For all frequencies of microwave emissions, the correlation with EUV emissions at shorter wavelengths was good, and the correlation became worse at longer wavelengths (>130 nm). The correlation became worse especially in the wavelength band of EUV emission that contains a lot of line emissions from the chromosphere.
Because of the complexity of the relationship between EUV and microwave emissions, we have developed an algorithm to derive EUV spectra from microwave emission observations using a machine learning method. Since the wavelength resolution of the TIMED/SEE is as fine as 1 nm, we investigated the relationship between the frequency of microwave emission and the EUV emission band for every 10 nm. As a result, it was found that the frequency of the microwave that affects the EUV emission is different for each band.
In this paper, we will report on the relationship between microwave and EUV emission and the relationship between these emissions and the aspect of the Earth's upper atmosphere, and discuss an algorithm for inferring EUV emission spectra using the NoRP's multi-frequency data.
In this study, we investigate the solar cycle variation of the relationship between microwave and EUV emission spectra using data from the Nobeyama Radio Polarimeter (NoRP) and Thermosphere • Ionosphere • Mesosphere • Energetics and Dynamics (TIMED)/Solar Extreme ultraviolet Experiment (SEE). The NoRP measures the flux of microwave emissions from the full Sun at multiple frequencies (1, 2, 3.75, and 9.4 GHz), and TIMED/SEE measures the EUV emission spectrum in the range of 0.5 -190 nm with a resolution of 1 nm. We use daily data and the relationships between these microwaves and EUV emissions were investigated. For all frequencies of microwave emissions, the correlation with EUV emissions at shorter wavelengths was good, and the correlation became worse at longer wavelengths (>130 nm). The correlation became worse especially in the wavelength band of EUV emission that contains a lot of line emissions from the chromosphere.
Because of the complexity of the relationship between EUV and microwave emissions, we have developed an algorithm to derive EUV spectra from microwave emission observations using a machine learning method. Since the wavelength resolution of the TIMED/SEE is as fine as 1 nm, we investigated the relationship between the frequency of microwave emission and the EUV emission band for every 10 nm. As a result, it was found that the frequency of the microwave that affects the EUV emission is different for each band.
In this paper, we will report on the relationship between microwave and EUV emission and the relationship between these emissions and the aspect of the Earth's upper atmosphere, and discuss an algorithm for inferring EUV emission spectra using the NoRP's multi-frequency data.