A New Method for Deriving the Nightside Thermospheric Density Based on GUVI Dayside Limb Observations
Abstract We propose a new method to derive the nightside thermospheric density by extending Global Ultraviolet Imager (GUVI) dayside limb observations using empirical orthogonal function (EOF) analysis. First, we acquire the GUVI dayside total mass density during 2002–2005 to construct a preliminary...
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| Format: | Article |
| Language: | English |
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Wiley
2020-02-01
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| Series: | Space Weather |
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| Online Access: | https://doi.org/10.1029/2019SW002304 |
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| _version_ | 1841536404119617536 |
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| author | Tingting Yu Zhipeng Ren You Yu Weixing Wan |
| author_facet | Tingting Yu Zhipeng Ren You Yu Weixing Wan |
| author_sort | Tingting Yu |
| collection | DOAJ |
| description | Abstract We propose a new method to derive the nightside thermospheric density by extending Global Ultraviolet Imager (GUVI) dayside limb observations using empirical orthogonal function (EOF) analysis. First, we acquire the GUVI dayside total mass density during 2002–2005 to construct a preliminary empirical model (EM). Simultaneously, we decompose the background thermospheric density from U.S. Naval Research Laboratory Mass Spectrometer and Incoherent Scatter Radar Extended model into different EOFs. The decomposed EOFs are then used to fit the continuous density from EM, to develop a new nightside extended model (NEM). The preliminary EM and developed NEM are further evaluated with Challenging Minisatellite Payload (CHAMP) satellite observations. Higher correlation coefficients and smaller relative standard errors between CHAMP observations and the NEM results are obtained than those between CHAMP observations and the EM results, and the NEM results are in good agreement with the CHAMP observations in time series during both daytime and nighttime, which all prove the NEM method is effective to the reproduction and extension of GUVI original dayside observations. Furthermore, the NEM reveals two typical seasonal variation features, the semiannual variation and equinoctial asymmetry of thermospheric density. The model provides an effective tool to derive the nightside thermospheric density and explore the thermospheric intrinsic structure, and needs the further development to achieve more widespread application of the thermosphere. |
| format | Article |
| id | doaj-art-59dec9580fb44d989d7fd238f1ad5f73 |
| institution | Kabale University |
| issn | 1542-7390 |
| language | English |
| publishDate | 2020-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-59dec9580fb44d989d7fd238f1ad5f732025-01-14T16:30:20ZengWileySpace Weather1542-73902020-02-01182n/an/a10.1029/2019SW002304A New Method for Deriving the Nightside Thermospheric Density Based on GUVI Dayside Limb ObservationsTingting Yu0Zhipeng Ren1You Yu2Weixing Wan3Key Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics Chinese Academy of Sciences Beijing ChinaKey Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics Chinese Academy of Sciences Beijing ChinaKey Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics Chinese Academy of Sciences Beijing ChinaKey Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics Chinese Academy of Sciences Beijing ChinaAbstract We propose a new method to derive the nightside thermospheric density by extending Global Ultraviolet Imager (GUVI) dayside limb observations using empirical orthogonal function (EOF) analysis. First, we acquire the GUVI dayside total mass density during 2002–2005 to construct a preliminary empirical model (EM). Simultaneously, we decompose the background thermospheric density from U.S. Naval Research Laboratory Mass Spectrometer and Incoherent Scatter Radar Extended model into different EOFs. The decomposed EOFs are then used to fit the continuous density from EM, to develop a new nightside extended model (NEM). The preliminary EM and developed NEM are further evaluated with Challenging Minisatellite Payload (CHAMP) satellite observations. Higher correlation coefficients and smaller relative standard errors between CHAMP observations and the NEM results are obtained than those between CHAMP observations and the EM results, and the NEM results are in good agreement with the CHAMP observations in time series during both daytime and nighttime, which all prove the NEM method is effective to the reproduction and extension of GUVI original dayside observations. Furthermore, the NEM reveals two typical seasonal variation features, the semiannual variation and equinoctial asymmetry of thermospheric density. The model provides an effective tool to derive the nightside thermospheric density and explore the thermospheric intrinsic structure, and needs the further development to achieve more widespread application of the thermosphere.https://doi.org/10.1029/2019SW002304nightside extended modelGUVI limb observationsEOF analysisempirical model |
| spellingShingle | Tingting Yu Zhipeng Ren You Yu Weixing Wan A New Method for Deriving the Nightside Thermospheric Density Based on GUVI Dayside Limb Observations Space Weather nightside extended model GUVI limb observations EOF analysis empirical model |
| title | A New Method for Deriving the Nightside Thermospheric Density Based on GUVI Dayside Limb Observations |
| title_full | A New Method for Deriving the Nightside Thermospheric Density Based on GUVI Dayside Limb Observations |
| title_fullStr | A New Method for Deriving the Nightside Thermospheric Density Based on GUVI Dayside Limb Observations |
| title_full_unstemmed | A New Method for Deriving the Nightside Thermospheric Density Based on GUVI Dayside Limb Observations |
| title_short | A New Method for Deriving the Nightside Thermospheric Density Based on GUVI Dayside Limb Observations |
| title_sort | new method for deriving the nightside thermospheric density based on guvi dayside limb observations |
| topic | nightside extended model GUVI limb observations EOF analysis empirical model |
| url | https://doi.org/10.1029/2019SW002304 |
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