NSSC OpenIR
Observing System Impact on Ionospheric Specification Over China Using EnKF Assimilation
Alternative TitleWOS:000589621000011
He, Jianhui1,2,3; Yue, Xinan1,2,3; Hu, Lianhuan1,2; Wang, Junyi1,2; Li, Mingyuan1,2,3; Ning, Baiqi1,2; Wan, Weixing1,2,3; Xu, Jiyao3,4
Source PublicationSPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS
2020
Volume18Issue:10Pages:e2020SW002527
DOI10.1029/2020SW002527
Language英语
KeywordENSEMBLE KALMAN FILTER SIMULATION EXPERIMENT FORECAST SKILL MODEL VALIDATION
AbstractAccurate ionospheric specification for the current and future is one of the key tasks in operational space weather. In this work, we have assessed the effect of a dense ground network consisting of different radio instruments either developed or under developing on ionosphere nowcasting and forecasting over China and adjacent region (0-60 degrees N and 70-140 degrees E) through observing system simulation experiments. The data assimilation system is an Ensemble Kalman filter (EnKF) ionosphere and thermosphere data assimilation algorithm. The National Center for Atmospheric Research Thermosphere Ionosphere Electrodynamics General Circulation Model is used as a background model. Effects of different observation types, including the slant total electron content from Beidou System geostationary satellite and Global Position System and electron density observations from ionosondes and incoherent scattering radar on the ionospheric nowcasting and forecasting, are examined by the accurate specification of ionosphere key parameters (total electron content and 3-D electron density). We found that simultaneously assimilating different observation types can greatly improve the quality of ionosphere specification. Furthermore, updating the thermospheric state variables in the coupled thermosphere-ionosphere forecast model in the assimilation step plays an important role in improving the ionosphere forecasting. The ionosphere forecasting capability can last longer (>24 hr) in each observing system simulation experiment due to the adjusted thermosphere states. This study can provide a reference for observing system design over the China region and future ionosphere forecasting operation. Plain Language Summary In this work, the different observation data types are ingested into the first principle physical model TIEGCM by Ensemble Kalman filter algorithm to evaluate the effect of every kind of data on the nowcasting and forecasting of ionosphere parameters in China and adjacent region (0-60 degrees N and 70-140 degrees E). Three different kinds of observations are used to evaluate the nowcasting and 24 hr predictions of ionosphere parameters in the observation system simulation experiments, which includes the slant total electron content data from Beidou geostationary satellite systems and other global navigation satellite systems (e.g., Global Position System) and electron density profile from ionosondes and incoherent scattering radar. We found that the better ionosphere ionospheric nowcasting and forecasting results can be achieved by simultaneously assimilating above three different types of observations. Meanwhile, the improvement of thermosphere states can be found in each observing system simulation experiment by the comparison of the value of [O/N-2]. The ionosphere forecasting capability can be enhanced to be 24 hr due to the adjusted thermosphere states.
Indexed BySCI
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Document Type期刊论文
Identifierhttp://ir.nssc.ac.cn/handle/122/7591
Collection中国科学院国家空间科学中心
Affiliation1.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Earth & Planetary Phys, Beijing, Peoples R China
2.Chinese Acad Sci, Innovat Acad Earth Sci, Beijing, Peoples R China
3.Chinese Acad Sci, Beijing Natl Observ Space Environm, Inst Geol & Geophys, Beijing, Peoples R China
4.Univ Chinese Acad Sci, Coll Earth & Planetary Sci, Beijing, Peoples R China
5.Chinese Acad Sci, Natl Space Sci Ctr, State Key Lab Space Weather, Beijing, Peoples R China
Recommended Citation
GB/T 7714
He, Jianhui,Yue, Xinan,Hu, Lianhuan,et al. Observing System Impact on Ionospheric Specification Over China Using EnKF Assimilation[J]. SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS,2020,18(10):e2020SW002527.
APA He, Jianhui.,Yue, Xinan.,Hu, Lianhuan.,Wang, Junyi.,Li, Mingyuan.,...&Xu, Jiyao.(2020).Observing System Impact on Ionospheric Specification Over China Using EnKF Assimilation.SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS,18(10),e2020SW002527.
MLA He, Jianhui,et al."Observing System Impact on Ionospheric Specification Over China Using EnKF Assimilation".SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS 18.10(2020):e2020SW002527.
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