PreMevE Update: Forecasting Ultra‐Relativistic Electrons Inside Earth's Outer Radiation Belt
Abstract Energetic electrons inside Earth's Van Allen belts pose a major radiation threat to space‐borne electronics that often play vital roles in modern society. Ultra‐relativistic electrons with energies greater than or equal to two megaelectron‐volt (MeV) are of particular interest, and thu...
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| Format: | Article |
| Language: | English |
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Wiley
2021-09-01
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| Series: | Space Weather |
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| Online Access: | https://doi.org/10.1029/2021SW002773 |
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| author | Saurabh Sinha Yue Chen Youzuo Lin Rafael Pires de Lima |
| author_facet | Saurabh Sinha Yue Chen Youzuo Lin Rafael Pires de Lima |
| author_sort | Saurabh Sinha |
| collection | DOAJ |
| description | Abstract Energetic electrons inside Earth's Van Allen belts pose a major radiation threat to space‐borne electronics that often play vital roles in modern society. Ultra‐relativistic electrons with energies greater than or equal to two megaelectron‐volt (MeV) are of particular interest, and thus forecasting these ≥2 MeV electrons has a significant meaning to all space sectors. Here, we update the latest development of the predictive model for MeV electrons in the outer radiation belt. The new version, called PREdictive MEV Electron (PreMevE)‐2E, forecasts ultra‐relativistic electron flux distributions across the outer belt, with no need for in situ measurements of the trapped MeV electron population except at the geosynchronous orbit (GEO). Model inputs include precipitating electrons observed in low‐Earth‐orbits by NOAA satellites, upstream solar wind speeds and densities from solar wind monitors, as well as ultra‐relativistic electrons measured by one Los Alamos GEO satellite. We evaluated 32 supervised machine learning models that fall into four different classes of linear and neural network architectures, and successfully tested ensemble forecasting by using groups of top‐performing models. All models are individually trained, validated, and tested by in situ electron data from NASA's Van Allen Probes mission. It is shown that the final ensemble model outperforms individual models at most L‐shells, and this PreMevE‐2E model can provide 25‐h (∼1‐day) and 50‐h (∼2‐day) forecasts with high mean performance efficiency and correlation values. Our results also suggest that this new model is dominated by nonlinear components at L‐shells <∼4 for ultra‐relativistic electrons, different from the dominance of linear components for 1 MeV electrons as previously discovered. |
| format | Article |
| id | doaj-art-c2a1a9c6c4854801be4867ca7dde80a4 |
| institution | Kabale University |
| issn | 1542-7390 |
| language | English |
| publishDate | 2021-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-c2a1a9c6c4854801be4867ca7dde80a42025-01-14T16:26:53ZengWileySpace Weather1542-73902021-09-01199n/an/a10.1029/2021SW002773PreMevE Update: Forecasting Ultra‐Relativistic Electrons Inside Earth's Outer Radiation BeltSaurabh Sinha0Yue Chen1Youzuo Lin2Rafael Pires de Lima3Los Alamos National Laboratory Los Alamos NM USALos Alamos National Laboratory Los Alamos NM USALos Alamos National Laboratory Los Alamos NM USAGeological Survey of Brazil São Paulo BrazilAbstract Energetic electrons inside Earth's Van Allen belts pose a major radiation threat to space‐borne electronics that often play vital roles in modern society. Ultra‐relativistic electrons with energies greater than or equal to two megaelectron‐volt (MeV) are of particular interest, and thus forecasting these ≥2 MeV electrons has a significant meaning to all space sectors. Here, we update the latest development of the predictive model for MeV electrons in the outer radiation belt. The new version, called PREdictive MEV Electron (PreMevE)‐2E, forecasts ultra‐relativistic electron flux distributions across the outer belt, with no need for in situ measurements of the trapped MeV electron population except at the geosynchronous orbit (GEO). Model inputs include precipitating electrons observed in low‐Earth‐orbits by NOAA satellites, upstream solar wind speeds and densities from solar wind monitors, as well as ultra‐relativistic electrons measured by one Los Alamos GEO satellite. We evaluated 32 supervised machine learning models that fall into four different classes of linear and neural network architectures, and successfully tested ensemble forecasting by using groups of top‐performing models. All models are individually trained, validated, and tested by in situ electron data from NASA's Van Allen Probes mission. It is shown that the final ensemble model outperforms individual models at most L‐shells, and this PreMevE‐2E model can provide 25‐h (∼1‐day) and 50‐h (∼2‐day) forecasts with high mean performance efficiency and correlation values. Our results also suggest that this new model is dominated by nonlinear components at L‐shells <∼4 for ultra‐relativistic electrons, different from the dominance of linear components for 1 MeV electrons as previously discovered.https://doi.org/10.1029/2021SW002773supervised machine learningVan Allen electron radiation beltpredicting ultra‐relativistic electrons |
| spellingShingle | Saurabh Sinha Yue Chen Youzuo Lin Rafael Pires de Lima PreMevE Update: Forecasting Ultra‐Relativistic Electrons Inside Earth's Outer Radiation Belt Space Weather supervised machine learning Van Allen electron radiation belt predicting ultra‐relativistic electrons |
| title | PreMevE Update: Forecasting Ultra‐Relativistic Electrons Inside Earth's Outer Radiation Belt |
| title_full | PreMevE Update: Forecasting Ultra‐Relativistic Electrons Inside Earth's Outer Radiation Belt |
| title_fullStr | PreMevE Update: Forecasting Ultra‐Relativistic Electrons Inside Earth's Outer Radiation Belt |
| title_full_unstemmed | PreMevE Update: Forecasting Ultra‐Relativistic Electrons Inside Earth's Outer Radiation Belt |
| title_short | PreMevE Update: Forecasting Ultra‐Relativistic Electrons Inside Earth's Outer Radiation Belt |
| title_sort | premeve update forecasting ultra relativistic electrons inside earth s outer radiation belt |
| topic | supervised machine learning Van Allen electron radiation belt predicting ultra‐relativistic electrons |
| url | https://doi.org/10.1029/2021SW002773 |
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