A Bayesian Inference‐Based Empirical Model for Scintillation Indices for High‐Latitude
Abstract Solar wind parameters, the solar radio flux index (F10.7), the Sun's declination and the SuperMAG Electrojet index are used to construct a Bayesian inference‐based empirical model for scintillation indices (S4 and σΦ) at high latitudes. For the present study, measurements from three Gl...
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| Format: | Article |
| Language: | English |
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Wiley
2021-06-01
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| Series: | Space Weather |
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| Online Access: | https://doi.org/10.1029/2020SW002710 |
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| author | K. Meziane A. Kashcheyev P. T. Jayachandran A. M. Hamza |
| author_facet | K. Meziane A. Kashcheyev P. T. Jayachandran A. M. Hamza |
| author_sort | K. Meziane |
| collection | DOAJ |
| description | Abstract Solar wind parameters, the solar radio flux index (F10.7), the Sun's declination and the SuperMAG Electrojet index are used to construct a Bayesian inference‐based empirical model for scintillation indices (S4 and σΦ) at high latitudes. For the present study, measurements from three Global Positioning System (GPS) L1 receivers located in the auroral zone, the cusp and in the polar cap are selected, respectively. The solar wind characteristics include the solar wind speed (VSW) and ram pressure (ρSW) as well as the Geocentric Solar Magnetospheric (GSM) By and the Bz components of the interplanetary magnetic field (IMF). Following a brief assessment on the independence of the variables (predictors), prior probabilities of occurrence in the case of a multinomial classification are constructed. Posterior‐probabilities are then deduced for any arbitrary set of predictors. We show that the model captures most variations seen in the measured indices whether they are associated or not with transient interplanetary events. Although the model tends to underestimate the actual phase index measurements, 95% of the validated events are predicted with an error less than 0.034 rad in σΦ. For the amplitude scintillation index, 5% of validated events have an error larger than 0.019. |
| format | Article |
| id | doaj-art-60174da984ad43898b70305ba262d565 |
| institution | Kabale University |
| issn | 1542-7390 |
| language | English |
| publishDate | 2021-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-60174da984ad43898b70305ba262d5652025-01-14T16:30:36ZengWileySpace Weather1542-73902021-06-01196n/an/a10.1029/2020SW002710A Bayesian Inference‐Based Empirical Model for Scintillation Indices for High‐LatitudeK. Meziane0A. Kashcheyev1P. T. Jayachandran2A. M. Hamza3Physics Department University of New Brunswick Fredericton NB CanadaPhysics Department University of New Brunswick Fredericton NB CanadaPhysics Department University of New Brunswick Fredericton NB CanadaPhysics Department University of New Brunswick Fredericton NB CanadaAbstract Solar wind parameters, the solar radio flux index (F10.7), the Sun's declination and the SuperMAG Electrojet index are used to construct a Bayesian inference‐based empirical model for scintillation indices (S4 and σΦ) at high latitudes. For the present study, measurements from three Global Positioning System (GPS) L1 receivers located in the auroral zone, the cusp and in the polar cap are selected, respectively. The solar wind characteristics include the solar wind speed (VSW) and ram pressure (ρSW) as well as the Geocentric Solar Magnetospheric (GSM) By and the Bz components of the interplanetary magnetic field (IMF). Following a brief assessment on the independence of the variables (predictors), prior probabilities of occurrence in the case of a multinomial classification are constructed. Posterior‐probabilities are then deduced for any arbitrary set of predictors. We show that the model captures most variations seen in the measured indices whether they are associated or not with transient interplanetary events. Although the model tends to underestimate the actual phase index measurements, 95% of the validated events are predicted with an error less than 0.034 rad in σΦ. For the amplitude scintillation index, 5% of validated events have an error larger than 0.019.https://doi.org/10.1029/2020SW002710ionospheric scintillationBayesian inferencesolar wind disturbances |
| spellingShingle | K. Meziane A. Kashcheyev P. T. Jayachandran A. M. Hamza A Bayesian Inference‐Based Empirical Model for Scintillation Indices for High‐Latitude Space Weather ionospheric scintillation Bayesian inference solar wind disturbances |
| title | A Bayesian Inference‐Based Empirical Model for Scintillation Indices for High‐Latitude |
| title_full | A Bayesian Inference‐Based Empirical Model for Scintillation Indices for High‐Latitude |
| title_fullStr | A Bayesian Inference‐Based Empirical Model for Scintillation Indices for High‐Latitude |
| title_full_unstemmed | A Bayesian Inference‐Based Empirical Model for Scintillation Indices for High‐Latitude |
| title_short | A Bayesian Inference‐Based Empirical Model for Scintillation Indices for High‐Latitude |
| title_sort | bayesian inference based empirical model for scintillation indices for high latitude |
| topic | ionospheric scintillation Bayesian inference solar wind disturbances |
| url | https://doi.org/10.1029/2020SW002710 |
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