The Impact of Solar Activity on Forecasting the Upper Atmosphere via Assimilation of Electron Density Data
Abstract This study presents a comprehensive comparison of the impact of solar activity on forecasting the upper atmosphere through assimilation of radio occultation (RO)‐derived electron density (Ne) into a physics‐based model (TIE‐GCM) using an ensemble Kalman filter (KF). Globally abundant RO‐der...
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| Format: | Article |
| Language: | English |
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Wiley
2021-05-01
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| Series: | Space Weather |
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| Online Access: | https://doi.org/10.1029/2020SW002660 |
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| author | Timothy Kodikara Kefei Zhang Nicholas Michael Pedatella Claudia Borries |
| author_facet | Timothy Kodikara Kefei Zhang Nicholas Michael Pedatella Claudia Borries |
| author_sort | Timothy Kodikara |
| collection | DOAJ |
| description | Abstract This study presents a comprehensive comparison of the impact of solar activity on forecasting the upper atmosphere through assimilation of radio occultation (RO)‐derived electron density (Ne) into a physics‐based model (TIE‐GCM) using an ensemble Kalman filter (KF). Globally abundant RO‐derived Ne offers one of the most promising means to test the effect of assimilation on the model forecasted state on a global scale. This study emphasizes the importance of understanding how the assimilation results vary with solar activity, which is one of the main drivers of thermosphere‐ionosphere dynamics. This study validates the forecast states with independent RO‐derived GRACE (Gravity Recovery and Climate Experiment mission) Ne data. The principal result of the study is that the agreement between forecast Ne and data is better during solar minimum than solar maximum. The results also show that the agreement between data and forecast is mostly better than that of the standalone TIE‐GCM driven with observed geophysical indices. The results emphasize that TIE‐GCM significantly underestimate Ne in altitudes below 250 km and the assimilation of Ne is not as effective in these lower altitudes as it is in higher altitudes. The results demonstrate that assimilation of Ne significantly impacts the neutral mass density estimates via the KF state vector—the impact is larger during solar maximum than solar minimum relative to a control case that does not assimilate Ne. The results are useful to explain the inherent model bias, to understand the limitations of the data, and to demonstrate the capability of the assimilation technique. |
| format | Article |
| id | doaj-art-bcea8802c75f4602be70e0737fc76c28 |
| institution | Kabale University |
| issn | 1542-7390 |
| language | English |
| publishDate | 2021-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-bcea8802c75f4602be70e0737fc76c282025-01-14T16:31:31ZengWileySpace Weather1542-73902021-05-01195n/an/a10.1029/2020SW002660The Impact of Solar Activity on Forecasting the Upper Atmosphere via Assimilation of Electron Density DataTimothy Kodikara0Kefei Zhang1Nicholas Michael Pedatella2Claudia Borries3Institute of Solar‐Terrestrial Physics German Aerospace Center Neustrelitz GermanySPACE Research Centre RMIT University Melbourne VIC AustraliaHigh Altitude Observatory National Center for Atmospheric Research Boulder CO USAInstitute of Solar‐Terrestrial Physics German Aerospace Center Neustrelitz GermanyAbstract This study presents a comprehensive comparison of the impact of solar activity on forecasting the upper atmosphere through assimilation of radio occultation (RO)‐derived electron density (Ne) into a physics‐based model (TIE‐GCM) using an ensemble Kalman filter (KF). Globally abundant RO‐derived Ne offers one of the most promising means to test the effect of assimilation on the model forecasted state on a global scale. This study emphasizes the importance of understanding how the assimilation results vary with solar activity, which is one of the main drivers of thermosphere‐ionosphere dynamics. This study validates the forecast states with independent RO‐derived GRACE (Gravity Recovery and Climate Experiment mission) Ne data. The principal result of the study is that the agreement between forecast Ne and data is better during solar minimum than solar maximum. The results also show that the agreement between data and forecast is mostly better than that of the standalone TIE‐GCM driven with observed geophysical indices. The results emphasize that TIE‐GCM significantly underestimate Ne in altitudes below 250 km and the assimilation of Ne is not as effective in these lower altitudes as it is in higher altitudes. The results demonstrate that assimilation of Ne significantly impacts the neutral mass density estimates via the KF state vector—the impact is larger during solar maximum than solar minimum relative to a control case that does not assimilate Ne. The results are useful to explain the inherent model bias, to understand the limitations of the data, and to demonstrate the capability of the assimilation technique.https://doi.org/10.1029/2020SW002660COSMICdata assimilationensemble Kalman filterionosphere forecastsneutral mass density forecastsTIE‐GCM |
| spellingShingle | Timothy Kodikara Kefei Zhang Nicholas Michael Pedatella Claudia Borries The Impact of Solar Activity on Forecasting the Upper Atmosphere via Assimilation of Electron Density Data Space Weather COSMIC data assimilation ensemble Kalman filter ionosphere forecasts neutral mass density forecasts TIE‐GCM |
| title | The Impact of Solar Activity on Forecasting the Upper Atmosphere via Assimilation of Electron Density Data |
| title_full | The Impact of Solar Activity on Forecasting the Upper Atmosphere via Assimilation of Electron Density Data |
| title_fullStr | The Impact of Solar Activity on Forecasting the Upper Atmosphere via Assimilation of Electron Density Data |
| title_full_unstemmed | The Impact of Solar Activity on Forecasting the Upper Atmosphere via Assimilation of Electron Density Data |
| title_short | The Impact of Solar Activity on Forecasting the Upper Atmosphere via Assimilation of Electron Density Data |
| title_sort | impact of solar activity on forecasting the upper atmosphere via assimilation of electron density data |
| topic | COSMIC data assimilation ensemble Kalman filter ionosphere forecasts neutral mass density forecasts TIE‐GCM |
| url | https://doi.org/10.1029/2020SW002660 |
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