Upstream Solar Wind Prediction up to Mars by an Operational Solar Wind Prediction System
Abstract Combining the upstream solar wind observations measured by Mars Atmosphere and Volatile Evolution (MAVEN), Advanced Composition Explorer(ACE) and Deep Space Climate Observatory (DSCOVR) from October 2014 to April 2021, we investigate the statistical properties of the background solar wind a...
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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Space Weather |
| Online Access: | https://doi.org/10.1029/2022SW003281 |
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| author | Jingjing Wang Yurong Shi Bingxian Luo Siqing Liu Linggao Kong Jijie Ma Wenya Li Binbin Tang Aibing Zhang Lei Li Liqin Shi Qiuzhen Zhong Yanhong Chen |
| author_facet | Jingjing Wang Yurong Shi Bingxian Luo Siqing Liu Linggao Kong Jijie Ma Wenya Li Binbin Tang Aibing Zhang Lei Li Liqin Shi Qiuzhen Zhong Yanhong Chen |
| author_sort | Jingjing Wang |
| collection | DOAJ |
| description | Abstract Combining the upstream solar wind observations measured by Mars Atmosphere and Volatile Evolution (MAVEN), Advanced Composition Explorer(ACE) and Deep Space Climate Observatory (DSCOVR) from October 2014 to April 2021, we investigate the statistical properties of the background solar wind at Mars and Earth. By applying an operational solar wind prediction system (Wang et al., 2018, https://doi.org/10.1051/swsc/2018025) in Space Weather Prediction Center (SEPC), we simulate the solar wind conditions and carry out a comparative analysis with observations to study our model performance. We find that our model is able to simulate the solar wind conditions upstream of Earth and Mars, corresponding to the different heliocentric distances and different levels of solar activity. Furthermore, we apply an event‐based evaluation by analyzing the high speed enhancements (HSEs), and find that the hit rate of HSEs is 70.38% and 66.37% for Earth and Mars, respectively. By predicting the HSEs at Earth (Mars), our model reaches a Mean Absolute Error (MAE) of 83.93 km/s (65.91 km/s) and 22.98 hr (21.65 hr) for maximum speed and arrival time prediction error, respectively. We also conduct a three‐month case study, from November 2020 to January 2021, analyzing solar wind conditions upstream of Earth, Mars, and measured by Tianwen‐1 (China's first Mars mission), for which our model is capable to predict the upstream solar wind conditions up to Mars. |
| format | Article |
| id | doaj-art-317568f50e4e4e54a41a93ec1f5f3daf |
| institution | Kabale University |
| issn | 1542-7390 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-317568f50e4e4e54a41a93ec1f5f3daf2025-01-14T16:35:23ZengWileySpace Weather1542-73902023-01-01211n/an/a10.1029/2022SW003281Upstream Solar Wind Prediction up to Mars by an Operational Solar Wind Prediction SystemJingjing Wang0Yurong Shi1Bingxian Luo2Siqing Liu3Linggao Kong4Jijie Ma5Wenya Li6Binbin Tang7Aibing Zhang8Lei Li9Liqin Shi10Qiuzhen Zhong11Yanhong Chen12State Key Laboratory of Space Weather National Space Science Center Chinese Academy of Sciences Beijing ChinaState Key Laboratory of Space Weather National Space Science Center Chinese Academy of Sciences Beijing ChinaState Key Laboratory of Space Weather National Space Science Center Chinese Academy of Sciences Beijing ChinaState Key Laboratory of Space Weather National Space Science Center Chinese Academy of Sciences Beijing ChinaKey Laboratory of Science and Technology on Environmental Space Situation Awareness Chinese Academy of Sciences Beijing ChinaKey Laboratory of Science and Technology on Environmental Space Situation Awareness Chinese Academy of Sciences Beijing ChinaState Key Laboratory of Space Weather National Space Science Center Chinese Academy of Sciences Beijing ChinaState Key Laboratory of Space Weather National Space Science Center Chinese Academy of Sciences Beijing ChinaKey Laboratory of Science and Technology on Environmental Space Situation Awareness Chinese Academy of Sciences Beijing ChinaState Key Laboratory of Space Weather National Space Science Center Chinese Academy of Sciences Beijing ChinaState Key Laboratory of Space Weather National Space Science Center Chinese Academy of Sciences Beijing ChinaState Key Laboratory of Space Weather National Space Science Center Chinese Academy of Sciences Beijing ChinaState Key Laboratory of Space Weather National Space Science Center Chinese Academy of Sciences Beijing ChinaAbstract Combining the upstream solar wind observations measured by Mars Atmosphere and Volatile Evolution (MAVEN), Advanced Composition Explorer(ACE) and Deep Space Climate Observatory (DSCOVR) from October 2014 to April 2021, we investigate the statistical properties of the background solar wind at Mars and Earth. By applying an operational solar wind prediction system (Wang et al., 2018, https://doi.org/10.1051/swsc/2018025) in Space Weather Prediction Center (SEPC), we simulate the solar wind conditions and carry out a comparative analysis with observations to study our model performance. We find that our model is able to simulate the solar wind conditions upstream of Earth and Mars, corresponding to the different heliocentric distances and different levels of solar activity. Furthermore, we apply an event‐based evaluation by analyzing the high speed enhancements (HSEs), and find that the hit rate of HSEs is 70.38% and 66.37% for Earth and Mars, respectively. By predicting the HSEs at Earth (Mars), our model reaches a Mean Absolute Error (MAE) of 83.93 km/s (65.91 km/s) and 22.98 hr (21.65 hr) for maximum speed and arrival time prediction error, respectively. We also conduct a three‐month case study, from November 2020 to January 2021, analyzing solar wind conditions upstream of Earth, Mars, and measured by Tianwen‐1 (China's first Mars mission), for which our model is capable to predict the upstream solar wind conditions up to Mars.https://doi.org/10.1029/2022SW003281 |
| spellingShingle | Jingjing Wang Yurong Shi Bingxian Luo Siqing Liu Linggao Kong Jijie Ma Wenya Li Binbin Tang Aibing Zhang Lei Li Liqin Shi Qiuzhen Zhong Yanhong Chen Upstream Solar Wind Prediction up to Mars by an Operational Solar Wind Prediction System Space Weather |
| title | Upstream Solar Wind Prediction up to Mars by an Operational Solar Wind Prediction System |
| title_full | Upstream Solar Wind Prediction up to Mars by an Operational Solar Wind Prediction System |
| title_fullStr | Upstream Solar Wind Prediction up to Mars by an Operational Solar Wind Prediction System |
| title_full_unstemmed | Upstream Solar Wind Prediction up to Mars by an Operational Solar Wind Prediction System |
| title_short | Upstream Solar Wind Prediction up to Mars by an Operational Solar Wind Prediction System |
| title_sort | upstream solar wind prediction up to mars by an operational solar wind prediction system |
| url | https://doi.org/10.1029/2022SW003281 |
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