FENG Jiandi, ZHAO Zhenzhen, HAN Baomin, ZHONG Huixin, ZHU Yuncong. A Single-Station Empirical TEC Model Suitable for MSNA Area: Taking ohi3 Station as an Example[J]. Geomatics and Information Science of Wuhan University, 2021, 46(2): 270-279,288. DOI: 10.13203/j.whugis20190211
Citation: FENG Jiandi, ZHAO Zhenzhen, HAN Baomin, ZHONG Huixin, ZHU Yuncong. A Single-Station Empirical TEC Model Suitable for MSNA Area: Taking ohi3 Station as an Example[J]. Geomatics and Information Science of Wuhan University, 2021, 46(2): 270-279,288. DOI: 10.13203/j.whugis20190211

A Single-Station Empirical TEC Model Suitable for MSNA Area: Taking ohi3 Station as an Example

Funds: 

The National Natural Science Foundation of China 41804032

the Open Fund of State Key Laboratory of Geodesy and Earth's Dynamics SKLGED2019-3-4-E

the Open Fund of Shanghai Key Laboratory of Space Navigation and Positioning Techniques 201920

More Information
  • Author Bio:

    FENG Jiandi, PhD, lecturer, specializes in GNSS data processing and ionospheric model. E-mail: jdfeng@whu.edu.cn

  • Corresponding author:

    HAN Baomin, PhD, professor. E-mail: hanbm@sdut.edu.cn

  • Received Date: September 29, 2019
  • Published Date: February 04, 2021
  • The diurnal variability of total electron content (TEC) in midlatitude summer nighttime anomaly (MSNA) region varies seasonally. Whether the characteristics of MSNA can be effectively described is one of the key indicators to test the accuracy of ionospheric empirical TEC model. A new ionospheric empirical TEC model named SSM-T2 (single station model type2) is proposed for MSNA anomalies. The effectiveness of the model is verified by an example of ohi3 located in the Antarctic Peninsula in the MSNA region. The SSM-T2 model consists of three parts: The diurnal variation component of TEC, the seasonal variation component and the solar activity component. The coefficients in the model are obtained by least square fitting. At the ohi3 station in the Antarctic Peninsula, test results of the model fitting show that the SSM-T2-ohi3 model fits well with the modeling data GPS-TEC, and describes the MSNA phenomenon well. By comparing and analyzing the models, it is found that SSM-T2-ohi3 is in good agreement with CODE GIMs (Center for Orbit Determination in Europe, Global Ionosphere Maps) and SSM-month models at extrapolated time points. It can effectively describe the characteristics of MSNA and has better prediction ability than IRI2016 model.
  • [1]
    Klobuchar J A. Ionospheric Time-Delay Algorithm for Single-Frequency GPS Users[J]. IEEE Transactions on Aerospace & Electronic Systems, 1987, 23(3): 325-331
    [2]
    Hochegger G, Nava B, Radicella S, et al. A Family of Ionospheric Models for Different Uses[J]. Physics and Chemistry of the Earth, 2000, 25(4): 307-310 https://www.sciencedirect.com/science/article/abs/pii/S1464191700000222
    [3]
    Radicella S M, Leitinger R. The Evolution of the DGR Approach to Model Electron Density Profiles[J]. Advances in Space Research, 2001, 27(1): 35-40 doi: 10.1016/S0273-1177(00)00138-1
    [4]
    Nava B, Coïsson P, Radicella S M. A New Version of the NeQuick Ionosphere Electron Density Model[J]. Journal of Atmospheric and Solar-Terrestrial Physics, 2008, 70(15): 1 856-1 862 doi: 10.1016/j.jastp.2008.01.015
    [5]
    刘长健. GNSS电离层建模方法与质量控制研究[D].郑州: 信息工程大学, 2011

    Liu Changjian. Study on Modeling Method and Model Quality Control of Ionosphere Based on GNSS[D]. Zhengzhou: Information Engineering University, 2011
    [6]
    耿长江.利用地基GNSS数据实时监测电离层延迟理论与方法研究[D].武汉: 武汉大学, 2011

    Geng Changjiang. Theory and Method of Ionospheric Real-Time Monitoring and Delay Correction Based on the Ground-Based GNSS[D]. Wuhan: Wuhan University, 2011
    [7]
    姜卫平, 邹璇, 唐卫明.基于CORS网络的单频GPS实时精密单点定位新方法[J].地球物理学报, 2012, 55(5):1 549-1 556 https://www.cnki.com.cn/Article/CJFDTOTAL-DQWX201205013.htm

    Jiang Weiping, Zou Xuan, Tang Weiming. A New Kind of Real-Time PPP Method for GPS Single-Frequency Receiver Using CORS Network[J]. Chinese Journal of Geophysics, 2012, 55(5):1 549-1 556 https://www.cnki.com.cn/Article/CJFDTOTAL-DQWX201205013.htm
    [8]
    张瑞.多模GNSS实时电离层精化建模及其应用研究[D].武汉: 武汉大学, 2013

    Zhang Rui. Theory and Method of Multimode GNSS Real-Time Refinement Ionospheric Modeling and Its Application[D]. Wuhan: Wuhan University, 2013
    [9]
    Yuen P C, Roelofs T H. Seasonal Variations in Ionospheric Total Electron Content[J]. Journal of Atmospheric & Terrestrial Physics, 1967, 29(3): 321-326
    [10]
    余涛, 万卫星, 刘立波, 等.利用IGS数据分析全球TEC的周年和半年变化特性[J].地球物理学报, 2006, 49(4): 943-949 doi: 10.3321/j.issn:0001-5733.2006.04.003

    Yu Tao, Wan Weixing, Liu Libo, et al. Using IGS Data to Analysis the Global TEC Annual and Semiannual Variation[J]. Chinese Journal of Geophysics, 2006, 49(4): 943-949 doi: 10.3321/j.issn:0001-5733.2006.04.003
    [11]
    Zhao B, Wan W, Liu L, et al. Features of Annual and Semiannual Variations Derived from the Global Ionospheric Maps of Total Electron Content[J]. Annales Geophysicae, 2008, 25(12): 2 513-2 527 http://cpfd.cnki.com.cn/Article/CPFDTOTAL-DZDQ200801001063.htm
    [12]
    Bagiya M, Joshi H, Iyer K, et al. TEC Variations During Low Solar Activity Period (2005–2007) Near the Equatorial Ionospheric Anomaly Crest Region in India[J]. Annales Geophysicae, 2009, 27(3): 1 047-1 057 doi: 10.5194/angeo-27-1047-2009
    [13]
    冯建迪, 王正涛, 赵珍珍.卫星导航服务的全球电离层时变特性分析[J].测绘科学, 2015, 40(2): 13-17 https://www.cnki.com.cn/Article/CJFDTOTAL-CHKD201502002.htm

    Feng Jiandi, Wang Zhengtao, Zhao Zhenzhen. Analysis of Temporal Variation of Global Ionosphere Based on IGS[J]. Science of Surveying and Mapping, 2015, 40(2): 13-17 https://www.cnki.com.cn/Article/CJFDTOTAL-CHKD201502002.htm
    [14]
    冯建迪, 王正涛, 时爽爽, 等.总电子含量赤道异常变化特性分析[J].测绘科学, 2016, 41(6): 44-47 https://www.cnki.com.cn/Article/CJFDTOTAL-CHKD201606010.htm

    Feng Jiandi, Wang Zhengtao, Shi Shuangshuang, et al. Using IGS to Analyze the Variation of Anomaly Equatorial Ionization[J]. Science of Surveying and Mapping, 2016, 41(6): 44-47 https://www.cnki.com.cn/Article/CJFDTOTAL-CHKD201606010.htm
    [15]
    Liu J, Hernandez-Pajares M, Liang X, et al. Temporal and Spatial Variations of Global Ionospheric Total Electron Content Under Various Solar Conditions[J]. Journal of Geodesy, 2017, 91: 485-502 doi: 10.1007/s00190-016-0977-7
    [16]
    李涌涛, 李建文, 魏绒绒, 等.全球电离层TEC格网时空变化特性分析[J].武汉大学学报·信息科学版, 2020, 45(5): 776-783 doi: 10.13203/j.whugis20180431

    Li Yongtao, Li Jianwen, Wei Rongrong, et al. Analysis of Temporal and Spatial Variation Characteristics of Global Ionospheric TEC Grid[J]. Geomatics and Information Science of Wuhan University, 2020, 45(5): 776-783 doi: 10.13203/j.whugis20180431
    [17]
    Crocetto N, Pingue F, Ponte S, et al. Ionospheric Error Analysis in GPS Measurements[J]. Annals of Geophysics, 2009, 51(4):585-595
    [18]
    Jakowski N, Hoque M M, Mayer C. A New Global TEC Model for Estimating Transionospheric Radio Wave Propagation Errors[J]. Journal of Geodesy, 2011, 85: 965-974 doi: 10.1007/s00190-011-0455-1
    [19]
    Feng J, Wang Z, Jiang W, et al. A New Regional Total Electron Content Empirical Model in Northeast China[J]. Advances in Space Research, 2016, 58(7): 1 155-1 167 doi: 10.1016/j.asr.2016.06.001
    [20]
    Schunk R W, Sojka J J, Bowline M D. Theoretical Study of the Electron Temperature in the High-Latitude Ionosphere for Solar Maximum and Winter Conditions[J]. Journal of Geophysical Research: Space Physics, 1986, 91(A11): 12 041-12 054 doi: 10.1029/JA091iA11p12041
    [21]
    Fuller-Rowell T J, Rees D, Quegan S, et al. Interaction Between Neutral Thermosphere Composition and the Polar Ionosphere Using a Coupled Ionosphere-Thermosphere Model[J]. Journal of Geophysical Research: Space Physics, 1987, 92(A7): 7 744-7 748 doi: 10.1029/JA092iA07p07744
    [22]
    Hoque M M, Jakowski N. A New Global Model for the Ionospheric F2 Peak Height for Radio Wave Propagation[J]. Annales Geophysicae, 2012, 30(262): 797-809 https://www.researchgate.net/publication/233399592_A_new_global_model_for_the_ionospheric_F2_peak_height_for_radio_wave_propagation
    [23]
    Mukhtarov P, Pancheva D, Andonov B, et al. Global TEC Maps Based on GNSS Data: 1. Empirical Background TEC Model[J]. Journal of Geophysical Research: Space Physics, 2013, 118(7): 4 594-4 608 doi: 10.1002/jgra.50413
    [24]
    Feng J, Jiang W, Wang Z, et al. Regional TEC Model Under Quiet Geomagnetic Conditions and Low-to-Moderate Solar Activity Based on CODE GIMs[J]. Journal of Atmospheric & Solar Terrestrial Physics, 2017, 161: 88-97 https://www.sciencedirect.com/science/article/abs/pii/S1364682617303334
    [25]
    Feng J, Wang Z, Jiang W, et al. A Single-Station Empirical Model for TEC over the Antarctic Peninsula Using GPS-TEC Data[J]. Radio Science, 2017, 52(1-2): 196-214 doi: 10.1002/2016RS006171
    [26]
    李慧茹.基于Kalman滤波的近实时电离层TEC监测与反演[D].西安: 长安大学, 2013

    Li Huiru. Near Real-Time Monitoring and Inverting TEC of Ionosphere Based on Kalman Filter[D]. Xi'an: Chang'an University, 2013
    [27]
    Mao T, Xing W W, Liu L B. An EOF-Based Empirical Model of TEC over Wuhan[J]. Chinese Journal of Geophysics, 2005, 48(4): 751-758
    [28]
    Huang Z, Yuan H. Ionospheric Single-Station TEC Short-Term Forecast Using RBF Neural Network[J]. Radio Science, 2014, 49(4): 283-292 doi: 10.1002/2013RS005247
    [29]
    Huang Z, Li Q B, Yuan H. Forecasting of Ionospheric Vertical TEC 1-h Ahead Using a Genetic Algorithm and Neural Network[J]. Advances in Space Research, 2015, 55(7): 1 775-1 783 doi: 10.1016/j.asr.2015.01.026
    [30]
    Hajra R, Chakraborty S K, Tsurutani B T, et al. An Empirical Model of Ionospheric Total Electron Content (TEC) Near the Crest of the Equatorial Ionization Anomaly (EIA)[J]. Journal of Space Weather & Space Climate, 2016, 6(A29): 1-9 https://www.researchgate.net/publication/305343883_An_empirical_model_of_ionospheric_total_electron_content_TEC_near_the_crest_of_the_equatorial_ionization_anomaly_EIA
    [31]
    Bellchambers W H, Piggott W R. Ionospheric Measurements Made at Halley Bay[J]. Nature, 1958, 182(4 649):1 596-1 597 doi: 10.1038/1821596a0
    [32]
    Lin C H, Liu J Y, Cheng C Z, et al. Three-Dimensional Ionospheric Electron Density Structure of the Weddell Sea Anomaly[J]. Journal of Geophysical Research: Space Physics, 2009, 114(A2): A02312 https://www.researchgate.net/publication/228339821_Three-dimensional_ionospheric_electron_density_structure_of_the_Weddell_Sea_Anomaly
    [33]
    Lin C H, Liu C H, Liu J Y, et al. Midlatitude Summer Nighttime Anomaly of the Ionospheric Electron Density Observed by FORMOSAT-3/COSMIC[J]. Journal of Geophysical Research: Space Physics, 2010, 115(A3): A03308 https://www.researchgate.net/publication/229045279_Midlatitude_summer_nighttime_anomaly_of_the_ionospheric_electron_density_observed_by_FORMOSAT-3COSMIC
    [34]
    Thampi S V, Lin C, Liu H, et al. First Tomographic Observations of the Midlatitude Summer Nighttime Anomaly over Japan[J]. Journal of Geophysical Research: Space Physics, 2009, 114(A10): A10318 https://www.researchgate.net/publication/251432212_First_tomographic_observations_of_the_Midlatitude_Summer_Nighttime_Anomaly_over_Japan
    [35]
    Horvath I, Lovell B C. An Investigation of the Northern Hemisphere Midlatitude Nighttime Plasma Density Enhancements and Their Relations to the Midlatitude Nighttime Trough During Summer[J]. Journal of Geophysical Research: Space Physics, 2009, 114(A8): A08308 https://www.researchgate.net/publication/43514221_An_investigation_of_the_northern_hemisphere_midlatitude_nighttime_plasma_density_enhancements_and_their_relations_to_the_midlatitude_nighttime_trough_during_summer
    [36]
    Liu H, Thampi S V, Yamamoto M. Phase Reversal of the Diurnal Cycle in the Midlatitude Ionosphere[J]. Journal of Geophysical Research: Space Physics, 2010, 115(A1): A01305 https://www.researchgate.net/publication/248805833_Phase_reversal_of_the_diurnal_cycle_in_the_midlatitude_ionosphere
    [37]
    Bilitza D, Altadill D, Truhlik V, et al. International Reference Ionosphere 2016: From Ionospheric Climate to Real-Time Weather Predictions[J]. Space Weather, 2017, 15(2): 418-429 doi: 10.1002/2016SW001593
    [38]
    Arikan F, Erol C B, Arikan O. Regularized Estimation of Vertical Total Electron Content from Global Positioning System Data[J]. Journal of Geophysical Research: Space Physics, 2003, 108(A12): 1 469 doi: 10.1029/2002JA009605
    [39]
    Arikan F, Arikan O, Erol C B. Regularized Estimation of TEC from GPS Data for Certain Midlatitude Stations and Comparison with the IRI Model[J]. Adv Space Res, 2007, 39(5): 867-874 doi: 10.1016/j.asr.2007.01.082
    [40]
    Arikan F, Erol C B, Arikan O. Regularized Estimation of Vertical Total Electron Content from GPS Data for a Desired Time Period[J]. Radio Science, 2004, 39(6): 867-879 doi: 10.1029/2004RS003061
    [41]
    Nayir H, Arikan F, Arikan O, et al. Total Electron Content Estimation with Reg-Est[J]. Journal of Geophysical Research: Space Physics, 2007, 112(A11): A11313
    [42]
    Arikan F, Nayir H, Sezen U, et al. Estimation of Single Station Interfrequency Receiver Bias Using GPS-TEC[J]. Radio Science, 2008, 43(4): 762-770
    [43]
    Sezen U, Arikan F, Arikan O, et al. Online, Automatic, Near-Real Time Estimation of GPS-TEC: IONOLAB-TEC[J]. Space Weather, 2013, 11(5): 297-305 doi: 10.1002/swe.20054
    [44]
    郭建鹏.太阳辐射对热层和电离层变化性的影响[D].北京: 中国科学院地质与地球物理研究所, 2008

    Guo Jianpeng. Soalr Irradiance Effects on the Variabilities of the Thermosphere and the Ionosphere[D]. Beijing: Institute of Geology and Geophysics, Chinese Academy of Sciences, 2008
    [45]
    Hedin A E. Correlations Between Thermospheric Density and Temperature, Solar EUV Flux, and 10.7-cm Flux Variations[J]. Journal of Geophysical Research: Space Physics, 1984, 89(A11): 9 828-9 834 doi: 10.1029/JA089iA11p09828
  • Related Articles

    [1]HU Deyong, QIAO Kun, WANG Xingling, ZHAO Limin, JI Guohua. Comparison of Three Single-window Algorithms for Retrieving Land-Surface Temperature with Landsat 8 TIRS Data[J]. Geomatics and Information Science of Wuhan University, 2017, 42(7): 869-876. DOI: 10.13203/j.whugis20150164
    [2]FENG Qi, CHENG Xuejun, SHEN Xin, XIAO Xiao, WANG Lihui, ZHANG Wen. Inland Riverine Turbidity Estimation for Hanjiang River with Landsat 8 OLI Imager[J]. Geomatics and Information Science of Wuhan University, 2017, 42(5): 643-647. DOI: 10.13203/j.whugis20141002
    [3]WANG Yuzhuo, LIU Xiuguo, ZHANG Wei. Raster River Networks Extraction Based on Parallel Multiple Flow Direction Algorithms[J]. Geomatics and Information Science of Wuhan University, 2015, 40(12): 1646-1652,1682. DOI: 10.13203/j.whugis20140645
    [4]LI Yuguang, LI Qingquan. A Fast Algorithm for Huge Volume Floating Car Data Map-Matching:A Vector to Raster Map Conversion Approach[J]. Geomatics and Information Science of Wuhan University, 2014, 39(6): 724-728. DOI: 10.13203/j.whugis20140071
    [5]DONG Jian, PENG Rencan, CHEN Yi, LI Ning. An Algorithm for Centre Line Generation Based on Model of Approaching Intersection of Buffering Borderline from Reciprocal Direction[J]. Geomatics and Information Science of Wuhan University, 2011, 36(9): 1120-1123.
    [6]ZHANG Junfeng, FEI Lifan, HUANG Lina, LIU Yining. Real-Time Dynamic Rendering Algorithm of Terrain Using 3D_DP Method and Quad_TIN Model[J]. Geomatics and Information Science of Wuhan University, 2011, 36(3): 346-350.
    [7]LAN Qiuping, FEI Lifan, LIU Yining. An Approach on Calculating Firn Volume Change from Multi-temporal DEMs[J]. Geomatics and Information Science of Wuhan University, 2010, 35(10): 1222-1225.
    [8]HUANG Lina, FEI Lifan. Experimental Investigation on the Three Dimension Generalization of Contour Lines using 3D D-P Algorithm[J]. Geomatics and Information Science of Wuhan University, 2010, 35(1): 55-58.
    [9]YAN Huiwu, ZHU Guorui, XU Zhiyong, GAO Shan. Volume Rendering and 3D Modeling of Hydrogeologic Layer Based on Kriging Algorithm[J]. Geomatics and Information Science of Wuhan University, 2004, 29(7): 611-614.
    [10]CHENG Penggen, GONG Jianya, SHI Wenzhong, LIU Shaohua. Geological Object Modeling Based on Quasi Tri-prism Volume and Its Application[J]. Geomatics and Information Science of Wuhan University, 2004, 29(7): 602-307.
  • Cited by

    Periodical cited type(17)

    1. 冉烽均,龚川. 基于OpenStreetMap数据的土地利用制图. 北京测绘. 2024(02): 238-244 .
    2. 樊潇. 以建立草原公园为抓手,推动牧区草原转型升级. 中国草食动物科学. 2022(01): 61-64 .
    3. 李霞,潘冬荣,孙斌,姜佳昌,俞慧云,王红霞,杜笑村,吴丹丹. 甘肃省草地退化概况分析——基于甘肃省第一、二次草原普查数据. 草业科学. 2022(03): 485-494 .
    4. 刘志刚,关文昊,何国兴,蒲小鹏,纪童,杨军银,李强,柳小妮. 黄河源5种高寒植物光谱特征分析及识别. 草原与草坪. 2022(04): 23-30 .
    5. 申紫雁,刘昌义,胡夏嵩,周林虎,许桐,李希来,李国荣. 黄河源区高寒草地不同深度土壤理化性质与抗剪强度关系研究. 干旱区研究. 2021(02): 392-401 .
    6. 王俊奇,王广军,梁四海,杜海波,彭红明. 1996—2015年黄河源区植被覆盖度提取和时空变化分析. 冰川冻土. 2021(02): 662-674 .
    7. 朱宁,王浩,宁晓刚,刘娅菲. 草地退化遥感监测研究进展. 测绘科学. 2021(05): 66-76 .
    8. 沈贝贝,侯路路,丁蕾,范蓓蕾,毛平平,徐大伟,闫瑞瑞,辛晓平,陈金强. 数字牧场研究进展浅析. 中国农业信息. 2021(05): 1-11 .
    9. 刘炜,孙海霞,杨晓波. 基于高光谱图像的协同分层波谱识别——以兰州、榆林地区为例. 红外与毫米波学报. 2020(01): 99-110 .
    10. 韩万强,靳瑰丽,岳永寰,王惠宁,宫珂,吴雪儿,吾鲁帕·阿得尔卡里. 伊犁绢蒿荒漠草地3种主要植物光谱及植被指数改进. 新疆农业科学. 2020(05): 950-957 .
    11. 刘炜,孙海霞,杨晓波,董建民. 对数变换、导数变换的高寒草地反射光谱特征分析与识别——以那曲地区HJ-1A/HSI图像为例. 光谱学与光谱分析. 2020(07): 2200-2207 .
    12. 董元,董梦,单莹. 基于高光谱遥感的树种识别. 华北理工大学学报(自然科学版). 2020(04): 11-16 .
    13. 付晶莹,彭婷,江东,林刚,边鹏,韩昊. 草地资源立体观测研究进展与理论框架. 资源科学. 2020(10): 1932-1943 .
    14. 苏玥. 基于遥感的草地退化研究综述. 内蒙古科技与经济. 2019(06): 53-54+56 .
    15. 查向浩,王玉洁,李有文,王超,莫治新. 草地土壤碳密度研究进展. 北方园艺. 2019(09): 159-163 .
    16. 王云艳,罗冷坤,周志刚. 改进型DeepLab的极化SAR果园分类. 中国图象图形学报. 2019(11): 2035-2044 .
    17. 张良培,刘蓉,杜博. 使用量子优化算法进行高光谱遥感影像处理综述. 武汉大学学报(信息科学版). 2018(12): 1811-1818 .

    Other cited types(9)

Catalog

    Article views (1174) PDF downloads (74) Cited by(26)
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return