Reconstruction of the Radiation Belts for Solar Cycles 17–24 (1933–2017)
Abstract We present a reconstruction of the dynamics of the radiation belts from solar cycles 17 to 24 which allows us to study how radiation belt activity has varied between the different solar cycles. The radiation belt simulations are produced using the Versatile Electron Radiation Belt (VERB)‐3D...
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| Format: | Article |
| Language: | English |
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Wiley
2021-03-01
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| Series: | Space Weather |
| Online Access: | https://doi.org/10.1029/2020SW002524 |
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| author | A. A. Saikin Y. Y. Shprits A. Y. Drozdov D. A. Landis I. S. Zhelavskaya S. Cervantes |
| author_facet | A. A. Saikin Y. Y. Shprits A. Y. Drozdov D. A. Landis I. S. Zhelavskaya S. Cervantes |
| author_sort | A. A. Saikin |
| collection | DOAJ |
| description | Abstract We present a reconstruction of the dynamics of the radiation belts from solar cycles 17 to 24 which allows us to study how radiation belt activity has varied between the different solar cycles. The radiation belt simulations are produced using the Versatile Electron Radiation Belt (VERB)‐3D code. The VERB‐3D code simulations incorporate radial, energy, and pitch angle diffusion to reproduce the radiation belts. Our simulations use the historical measurements of Kp (available since solar cycle 17, i.e., 1933) to model the evolution radiation belt dynamics between L* = 1–6.6. A nonlinear auto regressive network with exogenous inputs (NARX) neural network was trained off GOES 15 measurements (January 2011–March 2014) and used to supply the upper boundary condition (L* = 6.6) over the course of solar cycles 17–24 (i.e., 1933–2017). Comparison of the model with long term observations of the Van Allen Probes and CRRES demonstrates that our model, driven by the NARX boundary, can reconstruct the general evolution of the radiation belt fluxes. Solar cycle 24 (January 2008–2017) has been the least active of the considered solar cycles which resulted in unusually low electron fluxes. Our results show that solar cycle 24 should not be used as a representative solar cycle for developing long term environment models. The developed reconstruction of fluxes can be used to develop or improve empirical models of the radiation belts. |
| format | Article |
| id | doaj-art-9b62b8b290904a4a829ba5190996009f |
| institution | Kabale University |
| issn | 1542-7390 |
| language | English |
| publishDate | 2021-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-9b62b8b290904a4a829ba5190996009f2025-01-14T16:30:38ZengWileySpace Weather1542-73902021-03-01193n/an/a10.1029/2020SW002524Reconstruction of the Radiation Belts for Solar Cycles 17–24 (1933–2017)A. A. Saikin0Y. Y. Shprits1A. Y. Drozdov2D. A. Landis3I. S. Zhelavskaya4S. Cervantes5Department of Earth, Planetary, and Space Sciences University of California Los Angeles CA USADepartment of Earth, Planetary, and Space Sciences University of California Los Angeles CA USADepartment of Earth, Planetary, and Space Sciences University of California Los Angeles CA USADepartment of Earth, Planetary, and Space Sciences University of California Los Angeles CA USAHelmholtz Centre Potsdam GFZ German Research Centre for Geosciences University of Potsdam Potsdam GermanyHelmholtz Centre Potsdam GFZ German Research Centre for Geosciences University of Potsdam Potsdam GermanyAbstract We present a reconstruction of the dynamics of the radiation belts from solar cycles 17 to 24 which allows us to study how radiation belt activity has varied between the different solar cycles. The radiation belt simulations are produced using the Versatile Electron Radiation Belt (VERB)‐3D code. The VERB‐3D code simulations incorporate radial, energy, and pitch angle diffusion to reproduce the radiation belts. Our simulations use the historical measurements of Kp (available since solar cycle 17, i.e., 1933) to model the evolution radiation belt dynamics between L* = 1–6.6. A nonlinear auto regressive network with exogenous inputs (NARX) neural network was trained off GOES 15 measurements (January 2011–March 2014) and used to supply the upper boundary condition (L* = 6.6) over the course of solar cycles 17–24 (i.e., 1933–2017). Comparison of the model with long term observations of the Van Allen Probes and CRRES demonstrates that our model, driven by the NARX boundary, can reconstruct the general evolution of the radiation belt fluxes. Solar cycle 24 (January 2008–2017) has been the least active of the considered solar cycles which resulted in unusually low electron fluxes. Our results show that solar cycle 24 should not be used as a representative solar cycle for developing long term environment models. The developed reconstruction of fluxes can be used to develop or improve empirical models of the radiation belts.https://doi.org/10.1029/2020SW002524 |
| spellingShingle | A. A. Saikin Y. Y. Shprits A. Y. Drozdov D. A. Landis I. S. Zhelavskaya S. Cervantes Reconstruction of the Radiation Belts for Solar Cycles 17–24 (1933–2017) Space Weather |
| title | Reconstruction of the Radiation Belts for Solar Cycles 17–24 (1933–2017) |
| title_full | Reconstruction of the Radiation Belts for Solar Cycles 17–24 (1933–2017) |
| title_fullStr | Reconstruction of the Radiation Belts for Solar Cycles 17–24 (1933–2017) |
| title_full_unstemmed | Reconstruction of the Radiation Belts for Solar Cycles 17–24 (1933–2017) |
| title_short | Reconstruction of the Radiation Belts for Solar Cycles 17–24 (1933–2017) |
| title_sort | reconstruction of the radiation belts for solar cycles 17 24 1933 2017 |
| url | https://doi.org/10.1029/2020SW002524 |
| work_keys_str_mv | AT aasaikin reconstructionoftheradiationbeltsforsolarcycles172419332017 AT yyshprits reconstructionoftheradiationbeltsforsolarcycles172419332017 AT aydrozdov reconstructionoftheradiationbeltsforsolarcycles172419332017 AT dalandis reconstructionoftheradiationbeltsforsolarcycles172419332017 AT iszhelavskaya reconstructionoftheradiationbeltsforsolarcycles172419332017 AT scervantes reconstructionoftheradiationbeltsforsolarcycles172419332017 |