Assimilation of GPS Soundings in Ionospheric Models

  • Boris KhattatovEmail author


The ionosphere, usually defined to extend upward from about 80 km, is the region of the Earth’s atmosphere where concentration of ionized particles becomes sufficiently high to become easily observable. Below 80 km absorption of solar radiation by the atmosphere above decreases the probability of a neutral atmospheric molecule being ionized and results in negligible concentration of ionized particles. At altitudes higher than about 400 km, the density of neutral particles that are subject to ionization decreases substantially and absolute concentration of charged particles gets smaller with altitude.


Global Position System Total Electron Content Data Assimilation Neutral Particle Global Position System Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The author is very thankful to Dr. T. Fuller-Rowell and Dr. O. de la Beaujardiere for their interest in the work described here, encouragement, and guidance. A number of skilled computer scientists and software engineers helped to develop the numerical model and data assimilation scheme described here in a short time. GPS Solutions Inc was an integral part of developing the positioning augmentation service and provided the positioning engine. This work has primarily been funded by the US Air Force Research Laboratory in Hanscom, MA.


  1. Bailey, G.J. and N. Balan, 1996. A low-latitude ionosphere-plasmosphere model. In STEP: Handbook of Ionospheric Models, Schunk, R.W. (ed.), STEP Report.Google Scholar
  2. Banks, P.M. and G. Kockarts, 1973. Aeronomy, Parts A and B, Academic Press, Inc. New York, 430 pp (Part A), 355 pp (Part B).Google Scholar
  3. Blewitt, G., 1990. An Automatic editing algorithm for GPS data. Geophys. Res. Lett., 17, 199–205.CrossRefGoogle Scholar
  4. Fejer, B.G. and L. Scherliess, 1995. Time dependent response of equatorial ionospheric electric fields to magnetospheric disturbances. Geophys. Res. Lett., 22, 851–854.CrossRefGoogle Scholar
  5. Fuller-Rowell T.J., D. Rees, S. Quegan, R.J. Moffett, M.V. Codrescu and G.H. Millward, 1996. A coupled thermosphere ionosphere model (CTIM). In Handbook of Ionospheric Models, Schunk, R.W. (ed.), STEP Report.Google Scholar
  6. Hajj, G.A., B.D. Wilson, C. Wang, X. Pi and G. Rosen, 2004. Data assimilation of ground GPS total electron content into a physics-based ionospheric model by use of the Kalman filter. Radio Sci., 39, doi:10.1029/2002RS002859.Google Scholar
  7. Hedin, A.E., 1991. Extension of the MSIS thermosphere model into the middle and lower atmosphere. J. Geophys. Res., 96, 1159–1172.CrossRefGoogle Scholar
  8. Hedin, A.E., E.L. Fleming, A.H. Manson, F.J. Scmidlin, S.K. Avery, R.R. Clark, S.J. Franke, G.J. Fraser, T. Tsunda, F. Vial and R.A. Vincent, 1996. Empirical wind model for the upper, middle, and lower atmosphere. J. Atmos. Terr. Phys., 58, 1421–1447.CrossRefGoogle Scholar
  9. Huba, J., G. Joyce and J. Fedder, 2000. SAMI2 is another model of the ionosphere (SAMI2): A new low-latitude ionosphere model, J. Geophys. Res., 105, 23035–23053.CrossRefGoogle Scholar
  10. Khattatov, B.V., J.-F. Lamarque, L.V. Lyjak, R. Ménard, P. Levelt, X.X. Tie, G.P. Brasseur, G.P. and J.C. Gille, 2000. Assimilation of satellite observations of long-lived chemical species in global chemistry transport models. J. Geophys. Res., 105, 29135–29144.CrossRefGoogle Scholar
  11. Khattatov, B.V., M. Murphy, M. Gnedin, J. Sheffel, J. Adams, B. Cruickshank, V. Yudin, T. Fuller-Rowell and J. Retterer, 2005. Ionospheric nowcasting via assimilation of GPS measurements of ionospheric electron content in a global physics-based time-dependent model. Q. J. R. Meteorol. Soc., 131, 3543–3559.CrossRefGoogle Scholar
  12. Mannucci, A.J., B.D. Wilson, D.N. Yuan, C.H. Ho, U.J. Lindqwister and T.F. Runge, 1998. A global mapping technique for GPS-derived ionospheric total electron content measurements. Radio Sci., 33, 565–582.CrossRefGoogle Scholar
  13. Ménard, R., S.E. Cohn, L.P. Chang and P.M. Lyster, 2000. Stratospheric assimilation of chemical tracer observations using a Kalman filter, part I: Formulation. Mon. Weather Rev., 128, 2654–2671.CrossRefGoogle Scholar
  14. Millward, G.H., R.J. Moffett, S. Quegan and T.J. Fuller-Powell, 1996. A coupled thermosphere-ionosphere-plasmosphere model (CTIP). In STEP: Handbook of Ionospheric Models, Schunk, R.W. (ed.), STEP Report.Google Scholar
  15. Parkinson, B.W. and J.J. Spilker Jr., 1996. Global Positioning System: Theory and Applications (Vols. 1 and 2). American Institute of Aeronautics, 370 L’Enfant Promenade, SW, Washington, DC.CrossRefGoogle Scholar
  16. Pi, X., C. Wang, G.A. Hajj, I.G. Rosen, B.D.Wilson and G. Bailey, 2003. Estimation of E_B drift using a global assimilative ionospheric model: An observation system simulation experiment. J. Geophys. Res., 108, 1075–1087.CrossRefGoogle Scholar
  17. Rocken, C., Y.-H. Kuo, W. Schreiner, D. Hunt, S. Sokolovskiy and C. McCormick, 2000. COSMIC System Description. Terr. Atmos. Ocean. Sci., 11, 21–52.Google Scholar
  18. Scherliess, L., R.W. Schunk, J.J. Sojka and D.C. Thompson, 2004. Development of a physics-based reduced state Kalman filter for the ionosphere. Radio Sci., 39, RS1S04, doi:10.1029/2002RS002797.Google Scholar
  19. Schunk, R.W., 1988. A mathematical model of the middle and high latitude ionosphere. Pure Appl. Geophys., 127, 255–303.Google Scholar
  20. Schunk, R. and A. Nagy, 2000. Ionospheres, Cambridge University Press, Cambridge, 570 pp.CrossRefGoogle Scholar
  21. Schunk, R.W., L. Scherliess, J.J. Sojka, D.C. Thompson, D.N. Anderson, M. Codrescu, C. Minter, T.J. Fuller-Rowell, R.A. Heelis, M. Hairston and B.M. Howe, 2004. Global Assimilation of Ionospheric Measurements (GAIM). Radio Sci., 39, doi:10.1029/2002RS002794.Google Scholar
  22. Secan, J.R., R.M. Bussey, E.J. Fremouw and S. Basu, 1995. An improved model of equatorial scintillation. Radio Sci., 30, 607–617.Google Scholar
  23. Sultan, P.J., 1996. Linear theory and modeling of the Rayleigh-Taylor instability leading to the occurrence of equatorial spread. J. Geophys. Res., 101, 26875–26891.CrossRefGoogle Scholar
  24. Weimer, D.R., 2001. An improved model of ionospheric electric potentials including substorm perturbations and application to the GEM November 24, 1996 event. J. Geophys. Res., 106, 407–416.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Fusion Numerics IncBoulderUSA

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