期刊文献+

基于CHAMP、GRACE和COSMIC掩星数据的全球电离层h_mF_2建模研究 被引量:5

Global model of ionospheric h_mF_2 based on CHAMPE,GRACE and COSMIC radio occultation
下载PDF
导出
摘要 基于CHAMP、GRACE和COSMIC的电离层h_mF_2掩星数据,采用最小二乘法建立了一个包含地磁和太阳活动、经度、地方时、年积日和纬度信息的非线性多项式h_mF_2模型(Nonlinear Polynomial Peak Height Model—NPPHM).利用GRACE掩星数据对NPPHM与IRI2012进行了独立检验,结果显示这两个模型在2008年与GRACE数据的相关系数分别为0.798和0.532,均方根误差分别为25.97km和44.56km;在2012年,相关系数分别为0.732和0.488,均方根误差分别为31.39km和42.83km.选取全球不同地区14个测高仪站点数据,并引入相似离度对这两个模型的精度进行了评估,结果表明,NPPHM的相似离度远小于IRI2012,更加接近测高仪观测值.使用Athens站2003—2013年数据对模型进行了检验,结果显示IRI2012与Athens站测高仪数据的平均偏差达到8.11%,NPPHM则只有3.53%,并且在太阳活动低年及每年10月NPPHM的精度要明显高于IRI2012.此外,NPPHM也能够较好模拟出h_mF_2的日变化、季节变化及赤道异常等特性. For global ionospheric h_mF_2 modeling,a nonlinear polynomial model approach based on global h_mF_2 observational data form ionospheric radio occultation(IRO)measurements onboard CHAMP,GRACE,and COSMIC satellites is presented in this paper.The Nonlinear Polynomial Peak Height Model(NPPHM)is constructed by a nonlinear fit with h_mF_2 measurements in least squares sense and describes the dependencies of h_mF_2 on geomagnetic activity,solar activity,geographical longitude,local time,day of year and geographical latitude.Using independent data from CHAMP satellite,quantitative analysis is made.The correlation coefficients for proposed model NPPHM and CHAMP data are 0.798 in 2008and 0.732 in 2012,respectively.Thecorresponding coefficients for IRI2012 are 0.532 and 0.488.NPPHM shows root mean squared errors(RMS)of 25.97 km and 31.39 km in 2008 and 2012,respectively.The corresponding values for IRI2012 are 44.56 km and 42.83 km.Analog deviations are calculated to compare the NPPHM with IRI2012,using data from 14 different world wide ionosonde stations.The deviation of NPPHM is much less than that of IRI2012.Using observational data from the Athens station from 2003 to 2013,the mean deviation of IRI2012 is 8.11%,more than 3.53% of NPPHM.In low solar activity years and every October during the 11 years,the accuracy of NPPHM is much higher than that of IRI2012.What's more,NPPHM can well present the daily variation,seasonal variation and equatorial ionization anomaly phenomenon of h_mF_2.
出处 《地球物理学报》 SCIE EI CAS CSCD 北大核心 2016年第10期3555-3565,共11页 Chinese Journal of Geophysics
基金 国家自然科学基金项目(40505005)资助
关键词 电离层hmF2建模 非线性多项式 掩星数据 Ionospheric hmF2 modeling Nonlinear polynomial Radio occultation data
  • 相关文献

参考文献1

二级参考文献17

  • 1李龙,唐万年.台北地区冬季降水相似预报试验[J].解放军理工大学学报(自然科学版),2005,6(3):303-306. 被引量:3
  • 2毛田,万卫星,刘立波.用经验正交函数构造武汉地区电子浓度总含量的经验模式[J].地球物理学报,2005,48(4):751-758. 被引量:22
  • 3刘瑞源,刘顺林,徐中华,吴健,王先义,张北辰,胡红桥.自相关分析法在中国电离层短期预报中的应用[J].科学通报,2005,50(24):2781-2785. 被引量:29
  • 4Bilitza D. International reference ionosphere 2000 [J]. Ra- dio Sci., 2001, 36(2):261-275.
  • 5Bilitza D, Reinisch B W. International reference iono-sphere 2007: Improvements and new parameters [J]. Adv. Space Res., 2008(42):599-609.
  • 6Hochegger G, BRadicella N S, Leitinger R. A family of ionospheric models for different users. Phys. Chem. Earth, 2000, 25(4):307-310.
  • 7Ezquer R G, Jakowski N, Jadur A. Predicted and mea- sured total electron content over Havana[J]. J. Atmos. Solar Terr. Phys., 1997, 59:591.
  • 8Xenos Th D, Kouris S S, Casimiro A. Time-dependent pre- diction degradation assessment of neural-networks-based TEC forecasting models[J]. Nonl. Proc. Geophys., 2003, 10:585-587.
  • 9Habarulema J B, Mckinnell L A, Opperman B D L. A re- current neural network approach to quantitatively study- ing solar wind effects on TEC derived from GPS; prelim- inary results [J]. Ann. Geophys., 2009, 27:2111-2125.
  • 10Habaruiema J B, Mckinnell L A, Cilliers P J, et al. Ap- plication of Neural Networks to South African GPS TEC modeling [J]. Adv. Space Res., 2009, 43(11):1711-1720.

共引文献3

同被引文献67

引证文献5

二级引证文献7

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部