Evaluating Proton Intensities for the SMILE Mission

Abstract This study introduces five linear regression models developed to accurately predict proton intensities in the critical energy range of 92.2–159.7 keV. To achieve this task we utilized 14 years of data sourced from the Cluster's RAPID experiment and NASA's OMNI database. This data was then aligned with the Solar wind‐Magnetosphere‐Ionosphere Link Explorer (SMILE) mission's trajectory, to increase model accuracy in the relevant regions. Our approach diverges from existing methodologies by offering a user‐friendly model that doesn't require specialized software, making it accessible for broader applications in satellite mission planning and risk assessment. The research segregates the data set into four distinct regions, each analyzed for proton intensity dynamics. In the outer regions (YGSE) there is a pronounced dependence on radial distance and solar wind speed. In contrast, the inner regions (YGSE) demonstrate a significant dependence of proton intensities on the absolute value of the z‐coordinate and the magnetic field line topology. Our models achieved a Spearman correlation ranging from 0.57 to 0.72 on the test set, indicating good predictive capabilities. The findings emphasize the role of regional characteristics in space weather prediction and underscore the potential for tailored approaches in future research.

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Publication Details

Journal
Space Weather
Published
2024-12-01
DOI
https://doi.org/10.1029/2024sw003934
Citations
2
Primary Topic
Ionosphere and magnetosphere dynamics
Type
article
Field-Weighted Citation Impact
0.66

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article

Evaluating Proton Intensities for the SMILE Mission

C. P. Escoubet, E. A. Kronberg, Simon Patrick Mischel
2 citations
Space Weather
Ionosphere and magnetosphere dynamics
0.66
article

Evaluating Proton Intensities for the SMILE Mission

C. P. Escoubet, E. A. Kronberg, Simon Patrick Mischel
article en
2 citations

Abstract

Abstract This study introduces five linear regression models developed to accurately predict proton intensities in the critical energy range of 92.2–159.7 keV. To achieve this task we utilized 14 years of data sourced from the Cluster's RAPID experiment and NASA's OMNI database. This data was then aligned with the Solar wind‐Magnetosphere‐Ionosphere Link Explorer (SMILE) mission's trajectory, to increase model accuracy in the relevant regions. Our approach diverges from existing methodologies by offering a user‐friendly model that doesn't require specialized software, making it accessible for broader applications in satellite mission planning and risk assessment. The research segregates the data set into four distinct regions, each analyzed for proton intensity dynamics. In the outer regions (YGSE) there is a pronounced dependence on radial distance and solar wind speed. In contrast, the inner regions (YGSE) demonstrate a significant dependence of proton intensities on the absolute value of the z‐coordinate and the magnetic field line topology. Our models achieved a Spearman correlation ranging from 0.57 to 0.72 on the test set, indicating good predictive capabilities. The findings emphasize the role of regional characteristics in space weather prediction and underscore the potential for tailored approaches in future research.

Space WeatherVol. 22(12)
European Space Research and Technology Centre (NL), Ludwig-Maximilians-Universität München (DE)
Deutsche Forschungsgemeinschaft
Affordable and clean energy
Openalex Percentile: Top 27%
Ionosphere and magnetosphere dynamics
0.66
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