Journal of Geodesy

, Volume 91, Issue 5, pp 485–502 | Cite as

Temporal and spatial variations of global ionospheric total electron content under various solar conditions

  • Jingbin Liu
  • Manuel Hernandez-Pajares
  • Xinlian Liang
  • Jiachun An
  • Zemin Wang
  • Ruizhi Chen
  • Wei Sun
  • Juha Hyyppä
Original Article

Abstract

By utilizing the numerical technique of principal component analysis (PCA), this work analyses temporal and spatial variations of the ionosphere under various solar conditions during the period 1999–2013. Applying the PCA technique to the time series of the global ionospheric total electron content (TEC) maps provides an efficient method for analyzing the main ionospheric variability on a global scale that is able to decompose periodic variations (e.g., annual and semiannual oscillations) while retaining the asymmetry in the temporal and spatial domains (e.g., seasonal and equator anomalies). The TEC series of different local times are processed separately at two time scales: (1) the whole 15 years of the period of study and (2) the individual years. In contrast with previous studies, the analysis of the dataset of the 15 years shows that dawn (e.g., LT4–6) and late morning (LT10–12) are the more remarkable characteristic times for ionospheric variability. This study also reveals a cyclic trend of the variability with respect to local times. The first two modes, which contain 80–90% of the total variance, represent spatial distributions and temporal variations with respect to the different stages of the solar cycle and local times. Annual and semiannual variations are demodulated from the first two modes, and the results show that these variations evidently have distinct trends for daytime and nighttime. An exception is that, under active solar conditions, extremely strong solar irradiance during the daytime has a residual effect on the variability of the nighttime.

Keywords

Global ionosphere GNSS Principal component analysis Total electron content Atmosphere monitoring with geodetic techniques Ionospheric variability Ionospheric dynamics Numerical methods 

Notes

Acknowledgements

The CODE GIM dataset used in this study was downloaded from CODE’s data archive server (ftp://ftp.unibe.ch/aiub/CODE), and the solar and geomagnetic indices were downloaded from the National Geophysical Data Center (ftp://ftp.ngdc.noaa.gov/STP/). The Mg II index was downloaded from the data archive of the Institute of Environmental Physics at the University of Bremen in Germany (http://www.iup.uni-bremen.de/gome/gomemgii.html). This work was supported in part by the Finnish Centre of Excellence in Laser Scanning Research (Grant Number 272195) of the Academy of Finland, by the National Key Research Development Program of China with project No. 2016YFB0502204, and by the National Natural Science Foundation of China (Grant Nos. 41231064 and 41174029).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Jingbin Liu
    • 1
    • 2
  • Manuel Hernandez-Pajares
    • 3
  • Xinlian Liang
    • 2
  • Jiachun An
    • 4
  • Zemin Wang
    • 4
  • Ruizhi Chen
    • 1
  • Wei Sun
    • 5
  • Juha Hyyppä
    • 2
  1. 1.State Key Laboratory of Information Engineering in Surveying, Mapping and Remote SensingWuhan UniversityWuhanChina
  2. 2.Department of Remote Sensing and Photogrammetry, Center of Excellence in Laser Scanning ResearchFinnish Geospatial Research InstituteMasalaFinland
  3. 3.Department of Applied Mathematics IVTechnical University of Catalonia, UPC-IonSATBarcelonaSpain
  4. 4.Chinese Antarctic Center of Surveying and MappingWuhan UniversityWuhanChina
  5. 5.Wuhan Geomatics InstituteWuhanChina

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