Prediction of Dst During Solar Minimum Using In Situ Measurements at L5
Abstract Geomagnetic storms resulting from high‐speed streams can have significant negative impacts on modern infrastructure due to complex interactions between the solar wind and geomagnetic field. One measure of the extent of this effect is the Kyoto Dst index. We present a method to predict Dst f...
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| Format: | Article |
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Wiley
2020-05-01
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| Series: | Space Weather |
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| Online Access: | https://doi.org/10.1029/2019SW002424 |
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| author | R. L. Bailey C. Möstl M. A. Reiss A. J. Weiss U. V. Amerstorfer T. Amerstorfer J. Hinterreiter W. Magnes R. Leonhardt |
| author_facet | R. L. Bailey C. Möstl M. A. Reiss A. J. Weiss U. V. Amerstorfer T. Amerstorfer J. Hinterreiter W. Magnes R. Leonhardt |
| author_sort | R. L. Bailey |
| collection | DOAJ |
| description | Abstract Geomagnetic storms resulting from high‐speed streams can have significant negative impacts on modern infrastructure due to complex interactions between the solar wind and geomagnetic field. One measure of the extent of this effect is the Kyoto Dst index. We present a method to predict Dst from data measured at the Lagrange 5 (L5) point, which allows for forecasts of solar wind development 4.5 days in advance of the stream reaching the Earth. Using the STEREO‐B satellite as a proxy, we map data measured near L5 to the near‐Earth environment and make a prediction of the Dst from this point using the Temerin‐Li Dst model enhanced from the original using a machine learning approach. We evaluate the method accuracy with both traditional point‐to‐point error measures and an event‐based validation approach. The results show that predictions using L5 data outperform a 27‐day solar wind persistence model in all validation measures but do not achieve a level similar to an L1 monitor. Offsets in timing and the rapidly changing development of Bz in comparison to Bx and By reduce the accuracy. Predictions of Dst from L5 have a root‐mean‐square error of 9 nT, which is double the error of 4 nT using measurements conducted near the Earth. The most useful application of L5 measurements is shown to be in predicting the minimum Dst for the next 4 days. This method is being implemented in a real‐time forecast setting using STEREO‐A as an L5 proxy and has implications for the usefulness of future L5 missions. |
| format | Article |
| id | doaj-art-490c7ad2938b44c780428de2104d577d |
| institution | Kabale University |
| issn | 1542-7390 |
| language | English |
| publishDate | 2020-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-490c7ad2938b44c780428de2104d577d2025-01-14T16:27:36ZengWileySpace Weather1542-73902020-05-01185n/an/a10.1029/2019SW002424Prediction of Dst During Solar Minimum Using In Situ Measurements at L5R. L. Bailey0C. Möstl1M. A. Reiss2A. J. Weiss3U. V. Amerstorfer4T. Amerstorfer5J. Hinterreiter6W. Magnes7R. Leonhardt8Space Research Institute Austrian Academy of Sciences Graz AustriaSpace Research Institute Austrian Academy of Sciences Graz AustriaSpace Research Institute Austrian Academy of Sciences Graz AustriaSpace Research Institute Austrian Academy of Sciences Graz AustriaSpace Research Institute Austrian Academy of Sciences Graz AustriaSpace Research Institute Austrian Academy of Sciences Graz AustriaSpace Research Institute Austrian Academy of Sciences Graz AustriaSpace Research Institute Austrian Academy of Sciences Graz AustriaConrad Observatory Zentralanstalt für Meteorologie und Geodynamik Vienna AustriaAbstract Geomagnetic storms resulting from high‐speed streams can have significant negative impacts on modern infrastructure due to complex interactions between the solar wind and geomagnetic field. One measure of the extent of this effect is the Kyoto Dst index. We present a method to predict Dst from data measured at the Lagrange 5 (L5) point, which allows for forecasts of solar wind development 4.5 days in advance of the stream reaching the Earth. Using the STEREO‐B satellite as a proxy, we map data measured near L5 to the near‐Earth environment and make a prediction of the Dst from this point using the Temerin‐Li Dst model enhanced from the original using a machine learning approach. We evaluate the method accuracy with both traditional point‐to‐point error measures and an event‐based validation approach. The results show that predictions using L5 data outperform a 27‐day solar wind persistence model in all validation measures but do not achieve a level similar to an L1 monitor. Offsets in timing and the rapidly changing development of Bz in comparison to Bx and By reduce the accuracy. Predictions of Dst from L5 have a root‐mean‐square error of 9 nT, which is double the error of 4 nT using measurements conducted near the Earth. The most useful application of L5 measurements is shown to be in predicting the minimum Dst for the next 4 days. This method is being implemented in a real‐time forecast setting using STEREO‐A as an L5 proxy and has implications for the usefulness of future L5 missions.https://doi.org/10.1029/2019SW002424solar wind measurementsspace weather forecastingLagrange 5 pointDst index |
| spellingShingle | R. L. Bailey C. Möstl M. A. Reiss A. J. Weiss U. V. Amerstorfer T. Amerstorfer J. Hinterreiter W. Magnes R. Leonhardt Prediction of Dst During Solar Minimum Using In Situ Measurements at L5 Space Weather solar wind measurements space weather forecasting Lagrange 5 point Dst index |
| title | Prediction of Dst During Solar Minimum Using In Situ Measurements at L5 |
| title_full | Prediction of Dst During Solar Minimum Using In Situ Measurements at L5 |
| title_fullStr | Prediction of Dst During Solar Minimum Using In Situ Measurements at L5 |
| title_full_unstemmed | Prediction of Dst During Solar Minimum Using In Situ Measurements at L5 |
| title_short | Prediction of Dst During Solar Minimum Using In Situ Measurements at L5 |
| title_sort | prediction of dst during solar minimum using in situ measurements at l5 |
| topic | solar wind measurements space weather forecasting Lagrange 5 point Dst index |
| url | https://doi.org/10.1029/2019SW002424 |
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