Comparison of Low‐Latitude Ionospheric Scintillation Forecasting Techniques Using a Physics‐Based Model
Abstract The temporal change in height of a specific electron density can be used as a proxy for vertical plasma drift (PVPD) at the magnetic equator. The use of PVPDs as a predictor of low‐latitude ionospheric scintillation during the subsequent evening has previously been shown to have forecasting...
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Wiley
2021-07-01
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| Series: | Space Weather |
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| Online Access: | https://doi.org/10.1029/2020SW002462 |
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| author | L. D. Nugent S. Elvidge M. J. Angling |
| author_facet | L. D. Nugent S. Elvidge M. J. Angling |
| author_sort | L. D. Nugent |
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| description | Abstract The temporal change in height of a specific electron density can be used as a proxy for vertical plasma drift (PVPD) at the magnetic equator. The use of PVPDs as a predictor of low‐latitude ionospheric scintillation during the subsequent evening has previously been shown to have forecasting skill when using ionosonde data. The implementation of this approach using a physics‐based model is proposed to provide greater forecast antecedence without the need for local ionosondes. For the first time, the physics‐based model PVPD method is compared to another forecasting approach that uses a physics‐based model to calculate Rayleigh‐Taylor growth rates (RTGRs). In equinoctial test cases considered, when appropriate scintillation observation thresholds are selected, PVPD forecasting is shown to have skill similar to or better than the RTGR method using the same physics‐based model. PVPD forecasting requires only electron densities and corresponding altitudes. Therefore, this approach could be applied using an ionospheric data assimilation model whereas the majority of these models do not provide output for all variables required for RTGR forecasting. The forecasting skill in these test cases, the simplicity of physics‐based PVPD forecasting, and the suitability of this method for use of ionospheric data assimilation model output make this method attractive as a forecasting tool in an operational setting if skill can be further demonstrated for a wide range of conditions. However, both PVPD and RTGR forecasting skill are shown to be limited during solstitial months with high scintillation activity. This may be improved by using a data assimilation model. |
| format | Article |
| id | doaj-art-2d53ed51e7a94213bdf776b04bf6f112 |
| institution | Kabale University |
| issn | 1542-7390 |
| language | English |
| publishDate | 2021-07-01 |
| publisher | Wiley |
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| series | Space Weather |
| spelling | doaj-art-2d53ed51e7a94213bdf776b04bf6f1122025-01-14T16:35:19ZengWileySpace Weather1542-73902021-07-01197n/an/a10.1029/2020SW002462Comparison of Low‐Latitude Ionospheric Scintillation Forecasting Techniques Using a Physics‐Based ModelL. D. Nugent0S. Elvidge1M. J. Angling2Space Environment and Radio Engineering Group (SERENE), University of Birmingham Birmingham UKSpace Environment and Radio Engineering Group (SERENE), University of Birmingham Birmingham UKSpire Global UK Glasgow UKAbstract The temporal change in height of a specific electron density can be used as a proxy for vertical plasma drift (PVPD) at the magnetic equator. The use of PVPDs as a predictor of low‐latitude ionospheric scintillation during the subsequent evening has previously been shown to have forecasting skill when using ionosonde data. The implementation of this approach using a physics‐based model is proposed to provide greater forecast antecedence without the need for local ionosondes. For the first time, the physics‐based model PVPD method is compared to another forecasting approach that uses a physics‐based model to calculate Rayleigh‐Taylor growth rates (RTGRs). In equinoctial test cases considered, when appropriate scintillation observation thresholds are selected, PVPD forecasting is shown to have skill similar to or better than the RTGR method using the same physics‐based model. PVPD forecasting requires only electron densities and corresponding altitudes. Therefore, this approach could be applied using an ionospheric data assimilation model whereas the majority of these models do not provide output for all variables required for RTGR forecasting. The forecasting skill in these test cases, the simplicity of physics‐based PVPD forecasting, and the suitability of this method for use of ionospheric data assimilation model output make this method attractive as a forecasting tool in an operational setting if skill can be further demonstrated for a wide range of conditions. However, both PVPD and RTGR forecasting skill are shown to be limited during solstitial months with high scintillation activity. This may be improved by using a data assimilation model.https://doi.org/10.1029/2020SW002462scintillationequatorial plasma bubblesplasma driftionosphere |
| spellingShingle | L. D. Nugent S. Elvidge M. J. Angling Comparison of Low‐Latitude Ionospheric Scintillation Forecasting Techniques Using a Physics‐Based Model Space Weather scintillation equatorial plasma bubbles plasma drift ionosphere |
| title | Comparison of Low‐Latitude Ionospheric Scintillation Forecasting Techniques Using a Physics‐Based Model |
| title_full | Comparison of Low‐Latitude Ionospheric Scintillation Forecasting Techniques Using a Physics‐Based Model |
| title_fullStr | Comparison of Low‐Latitude Ionospheric Scintillation Forecasting Techniques Using a Physics‐Based Model |
| title_full_unstemmed | Comparison of Low‐Latitude Ionospheric Scintillation Forecasting Techniques Using a Physics‐Based Model |
| title_short | Comparison of Low‐Latitude Ionospheric Scintillation Forecasting Techniques Using a Physics‐Based Model |
| title_sort | comparison of low latitude ionospheric scintillation forecasting techniques using a physics based model |
| topic | scintillation equatorial plasma bubbles plasma drift ionosphere |
| url | https://doi.org/10.1029/2020SW002462 |
| work_keys_str_mv | AT ldnugent comparisonoflowlatitudeionosphericscintillationforecastingtechniquesusingaphysicsbasedmodel AT selvidge comparisonoflowlatitudeionosphericscintillationforecastingtechniquesusingaphysicsbasedmodel AT mjangling comparisonoflowlatitudeionosphericscintillationforecastingtechniquesusingaphysicsbasedmodel |