Skip to main content
Log in

Effects of estimating the ionospheric and thermospheric parameters on electron density forecasts

  • Research Paper
  • Published:
Science China Earth Sciences Aims and scope Submit manuscript

Abstract

Based on the thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIEGCM), a thermospheric-ionospheric data assimilation and forecast system is developed. Using this system, we estimated the oxygen ions, neutral temperature, wind, and composition by assimilating the simulated data from Formosa Satellite 3/Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) occultation electron density profiles to evaluate their effects on the ionospheric forecast. An ensemble Kalman filter data assimilation scheme and combined state and parameter estimation methods are used to estimate the unobserved parameters in the model. The statistical results show that the neutral and ion compositions are more effective than the neutral temperature and wind for improving the forecast of the ionospheric electron density, whose root mean square errors in the assimilation period decreased by approximately 40%, 30%, and 10% due to the estimations of the neutral composition, oxygen ions, and neutral temperature, respectively. Due to the different physical and chemical processes that these parameters primarily affect, their e-folding times differ greatly from longer than 12 h for neutral composition to approximately 6 h for oxygen ions and 3 h for neutral temperature. The effect of estimating the neutral composition on improving the ionospheric forecast is greater than that of estimating the oxygen ions, which can be also be seen in an actual data assimilation experiment. This indicates that the neutral composition is the most important thermospheric parameter in ionospheric data assimilations and forecasts.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Aa E, Huang W, Yu S, Liu S, Shi L, Gong J, Chen Y, Shen H. (2015). A regional ionospheric TEC mapping technique over China and adjacent areas on the basis of data assimilation. J Geophys Res-Space Phys, 120: 5049–5061

    Article  Google Scholar 

  • Aa E, Liu S, Huang W, Shi L, Gong J, Chen Y, Shen H, Li J. (2016). Regional 3–D ionospheric electron density specification on the basis of data assimilation of ground-based GNSS and radio occultation data. Space Weather, 14: 433–448

    Article  Google Scholar 

  • Angling M J, Cannon P S. (2004). Assimilation of radio occultation measurements into background ionospheric models. Radio Sci, 39: RS1S08

    Article  Google Scholar 

  • Bust G S, Crowley G, Garner T W, Gaussiran Ii T L, Meggs R W, Mitchell C N, Spencer P S J, Yin P, Zapfe B. (2007). Four-dimensional GPS imaging of space weather storms. Space Weather, 5: 02003

    Article  Google Scholar 

  • Bust G S, Garner T W, Gaussiran T L. (2004). Ionospheric data assimilation three-dimensional (IDA3D): A global, multisensor, electron density specification algorithm. J Geophys Res, 109: A11312

    Article  Google Scholar 

  • Chartier A T, Jackson D R, Mitchell C N. (2013). A comparison of the effects of initializing different thermosphere-ionosphere model fields on storm time plasma density forecasts. J Geophys Res-Space Phys, 118: 7329–7337

    Article  Google Scholar 

  • Evensen G. (1994). Sequential data assimilation with a nonlinear quasigeostrophic model using Monte Carlo methods to forecast error statistics. J Geophys Res, 99: 10143–10162

    Article  Google Scholar 

  • Evensen G. (2003). The Ensemble Kalman filter: Theoretical formulation and practical implementation. Ocean Dyn, 53: 343–367

    Article  Google Scholar 

  • Gaspari G, Cohn S E. (1999). Construction of correlation functions in two and three dimensions. Q J R Meteorol Soc, 125: 723–757

    Article  Google Scholar 

  • Houtekamer P L, Mitchell H L. (1998). Data assimilation using an ensemble Kalman filter technique. Mon Weather Rev, 126: 796–811

    Article  Google Scholar 

  • Houtekamer P L, Mitchell H L. (2001). A sequential ensemble Kalman filter for atmospheric data assimilation. Mon Weather Rev, 129: 123–137

    Article  Google Scholar 

  • Howe B M, Runciman K, Secan J A. (1998). Tomography of the ionosphere: Four-dimensional simulations. Radio Sci, 33: 109–128

    Article  Google Scholar 

  • Hsu C T, Matsuo T, Wang W, Liu J Y. (2014). Effects of inferring unobserved thermospheric and ionospheric state variables by using an Ensemble Kalman filter on global ionospheric specification and forecasting. J Geophys Res-Space Phys, 119: 9256–9267

    Article  Google Scholar 

  • Lee I T, Matsuo T, Richmond A D, Liu J Y, Wang W, Lin C H, Anderson J L, Chen M Q. (2012). Assimilation of FORMOSAT-3/COSMIC electron density profiles into a coupled thermosphere/ionosphere model using ensemble Kalman filtering. J Geophys Res, 117: A10318

    Article  Google Scholar 

  • Mandrake L, Wilson B, Wang C, Hajj G, Mannucci A, Pi X. (2005). A performance evaluation of the operational jet propulsion laboratory/ university of southern California global assimilation ionospheric model (JPL/USC GAIM). J Geophys Res, 110: A12306

    Article  Google Scholar 

  • Matsuo T, Araujo-Pradere E A. (2011). Role of thermosphere-ionosphere coupling in a global ionospheric specification. Radio Sci, 46: RS0D23

    Article  Google Scholar 

  • Matsuo T, Lee I T, Anderson J L. (2013). Thermospheric mass density specification using an ensemble Kalman filter. J Geophys Res-Space Phys, 118: 1339–1350

    Article  Google Scholar 

  • Pi X, Wang C, Hajj G A, Rosen G, Wilson B D, Bailey G J. (2003). Estimation of E×B drift using a global assimilative ionospheric model: An observation system simulation experiment. J Geophys Res, 108: 1075

    Article  Google Scholar 

  • Richmond A D, Ridley E C, Roble R G. (1992). A thermosphere/ionosphere general circulation model with coupled electrodynamics. Geophys Res Lett, 19: 601–604

    Article  Google Scholar 

  • Rishbeth H, Müller-Wodarg I C F. (1999). Vertical circulation and thermospheric composition: A modelling study. Ann Geophys, 17: 794–805

    Article  Google Scholar 

  • Scherliess L, Schunk R W, Sojka J J, Thompson D C. (2004). Development of a physics-based reduced state Kalman filter for the ionosphere. Radio Sci, 39: RS1S04

    Article  Google Scholar 

  • Scherliess L, Schunk R W, Sojka J J, Thompson D C, Zhu L. (2006). Utah State University global assimilation of ionospheric measurements Gauss-Markov Kalman filter model of the ionosphere: Model description and validation. J Geophys Res, 111: A11315

    Article  Google Scholar 

  • Schunk R W, Scherliess L, Sojka J J, Thompson D C, Anderson D N, Codrescu M, Minter C, Fuller-Rowell T J, Heelis R A, Hairston M, Howe B M. (2004). Global assimilation of ionospheric measurements (GAIM). Radio Sci, 39: RS1S02

    Article  Google Scholar 

  • Van Leeuwen P J, Evensen G. (1996). Data assimilation and inverse methods in terms of a probabilistic formulation. Mon Weather Rev, 124: 2898–2913

    Article  Google Scholar 

  • Wang C, Hajj G, Pi X, Rosen I G, Wilson B. (2004). Development of the global assimilative ionospheric model. Radio Sci, 39: RS1S06

    Google Scholar 

  • Yue X A. (2008). Modeling and data assimilation of mid- and low-latitude ionosphere (in Chinese). Doctoral Dissertation. Beijng: Institude of Geology and Geophysics, Chinese Academy of Sciences

    Google Scholar 

  • Yue X, Schreiner W S, Lin Y C, Rocken C, Kuo Y H, Zhao B. (2011). Data assimilation retrieval of electron density profiles from radio occultation measurements. J Geophys Res, 116: A03317

    Article  Google Scholar 

  • Yue X, Schreiner W S, Lei J, Sokolovskiy S V, Rocken C, Hunt D C, Kuo Y H. (2010). Error analysis of Abel retrieved electron density profiles from radio occultation measurements. Ann Geophys, 28: 217–222

    Article  Google Scholar 

  • Yue X, Wan W, Lin L, Zheng F, Lei J, Zhao B, Xu G, Zahng S R, Zhu J. (2007). Data assimilation of incoherent scatter radar observation into a one-dimensional midlatitude ionospheric model by applying ensemble Kalman filter. Radio Sci, 42: RS6006

    Article  Google Scholar 

  • Zhang S R, Oliver W L, Fukao S, Kawamura S. (2001). Extraction of solar and thermospheric information from the ionospheric electron density profile. J Geophys Res, 106: 12821–12836

    Article  Google Scholar 

  • Zhang S R, Oliver W L, Holt J M, Fukao S. (2002). Solar EUV flux, exospheric temperature and thermospheric wind inferred from incoherent scatter measurements of the electron density profile at Millstone Hill and Shigaraki. Geophys Res Lett, 29: 72–1–72–4

    Google Scholar 

  • Zhang Y N, Wu X C and Hu X. (2017). TIEGCM Ensemble Kalman Filter Assimilation Model Design and Preliminary Results (in Chinese). Chin J Space Sci, 37: 168–176

    Google Scholar 

Download references

Acknowledgements

The TIEGCM were obtained from High Altitude Observatory, NCAR (URL: https://doi.org/www.hao.ucar.edu/modeling/tgcm/tie.php). The FORMOSAT-3/COSMIC data were obtained from COSMIC Data Analysis and Archival Center (CDAAC) (URL: https://doi.org/cdaac-www.cosmic.ucar.edu/cdaac/tar/rest.html). This work was supported by National Important Basic Research Project of China (Grant No. 2016YFB0501503) and National Natural Science Foundation of China (Grant No. 41204137).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yanan Zhang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Y., Wu, X. & Hu, X. Effects of estimating the ionospheric and thermospheric parameters on electron density forecasts. Sci. China Earth Sci. 61, 1875–1887 (2018). https://doi.org/10.1007/s11430-017-9251-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11430-017-9251-4

Keywords

Navigation