Modeling the Time‐Variability of the Ionospheric Electric Potential (TiVIE)
Abstract We present a statistical model of the ionospheric electric potential derived from line‐of‐sight plasma velocity measurements from the Super Dual Auroral Radar Network. Electric potential patterns are produced using an established technique that models the ionospheric electric potential as a...
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| Format: | Article |
| Language: | English |
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Wiley
2025-07-01
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| Series: | Space Weather |
| Online Access: | https://doi.org/10.1029/2024SW004139 |
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| author | M.‐T. Walach A. Grocott |
| author_facet | M.‐T. Walach A. Grocott |
| author_sort | M.‐T. Walach |
| collection | DOAJ |
| description | Abstract We present a statistical model of the ionospheric electric potential derived from line‐of‐sight plasma velocity measurements from the Super Dual Auroral Radar Network. Electric potential patterns are produced using an established technique that models the ionospheric electric potential as a spherical harmonic expansion. Improvements over existing models are achieved by the use of novel parameterizations that capture three major sources of time‐variability of the coupled solar wind‐magnetosphere‐ionosphere system. The first source of variability relates directly to the time‐dependence of the system on the upstream solar wind conditions, specifically the strength and orientation of the interplanetary magnetic field. The magnetosphere‐ionosphere system is not static under continuous driving by the solar wind but evolves with time, even if the solar wind conditions themselves remain steady. We account for this by defining a solar wind steadiness timescale with which we parameterize the electric potential. The second source of variability relates to the storage and release of energy in the magnetosphere that is associated with magnetospheric substorms. The electric potential evolves throughout the substorm cycle, and its morphology is strongly influenced by the location of substorm onset. We therefore parameterize by substorm onset location and the time relative to substorm onset. Lastly we account for the variability introduced by geomagnetic storms. The ionospheric electric potential evolves differently through each phase of a storm, so we parameterize by storm phase. We discuss the details of the model, and assess its performance by comparison to other models and to observations. |
| format | Article |
| id | doaj-art-e897cdee5e9442ed87d71e15a77ee7ef |
| institution | DOAJ |
| issn | 1542-7390 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-e897cdee5e9442ed87d71e15a77ee7ef2025-08-20T02:45:27ZengWileySpace Weather1542-73902025-07-01237n/an/a10.1029/2024SW004139Modeling the Time‐Variability of the Ionospheric Electric Potential (TiVIE)M.‐T. Walach0A. Grocott1Physics Department Lancaster University Lancaster UKPhysics Department Lancaster University Lancaster UKAbstract We present a statistical model of the ionospheric electric potential derived from line‐of‐sight plasma velocity measurements from the Super Dual Auroral Radar Network. Electric potential patterns are produced using an established technique that models the ionospheric electric potential as a spherical harmonic expansion. Improvements over existing models are achieved by the use of novel parameterizations that capture three major sources of time‐variability of the coupled solar wind‐magnetosphere‐ionosphere system. The first source of variability relates directly to the time‐dependence of the system on the upstream solar wind conditions, specifically the strength and orientation of the interplanetary magnetic field. The magnetosphere‐ionosphere system is not static under continuous driving by the solar wind but evolves with time, even if the solar wind conditions themselves remain steady. We account for this by defining a solar wind steadiness timescale with which we parameterize the electric potential. The second source of variability relates to the storage and release of energy in the magnetosphere that is associated with magnetospheric substorms. The electric potential evolves throughout the substorm cycle, and its morphology is strongly influenced by the location of substorm onset. We therefore parameterize by substorm onset location and the time relative to substorm onset. Lastly we account for the variability introduced by geomagnetic storms. The ionospheric electric potential evolves differently through each phase of a storm, so we parameterize by storm phase. We discuss the details of the model, and assess its performance by comparison to other models and to observations.https://doi.org/10.1029/2024SW004139 |
| spellingShingle | M.‐T. Walach A. Grocott Modeling the Time‐Variability of the Ionospheric Electric Potential (TiVIE) Space Weather |
| title | Modeling the Time‐Variability of the Ionospheric Electric Potential (TiVIE) |
| title_full | Modeling the Time‐Variability of the Ionospheric Electric Potential (TiVIE) |
| title_fullStr | Modeling the Time‐Variability of the Ionospheric Electric Potential (TiVIE) |
| title_full_unstemmed | Modeling the Time‐Variability of the Ionospheric Electric Potential (TiVIE) |
| title_short | Modeling the Time‐Variability of the Ionospheric Electric Potential (TiVIE) |
| title_sort | modeling the time variability of the ionospheric electric potential tivie |
| url | https://doi.org/10.1029/2024SW004139 |
| work_keys_str_mv | AT mtwalach modelingthetimevariabilityoftheionosphericelectricpotentialtivie AT agrocott modelingthetimevariabilityoftheionosphericelectricpotentialtivie |