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Causal Link of Longitudinal Plasma Density Structure to Vertical Plasma Drift and Atmospheric Tides – A Review

  • Hyosub Kil
  • Larry J. Paxton
Chapter
Part of the IAGA Special Sopron Book Series book series (IAGA, volume 2)

Abstract

This chapter reviews recent advances in our understanding of the characteristics and driving mechanisms of the longitudinal plasma density structure in the low-latitude F region. Various ionospheric observations have shown the development of a longitudinal wave-like pattern in plasma density. Typically, the wave number-4 (wave-4) pattern is pronounced during July–September, and the wave-3 pattern is pronounced during December–January. Variation of the longitudinal plasma density pattern with local time and season is causally linked to vertical plasma drift in the F region (or E-region dynamo electric fields). The wave-4 pattern is of special interest to the ionosphere-thermosphere community because this phenomenon is closely associated with the diurnal eastward propagating zonal wave number 3 tide (DE3). This idea is supported by observations of annual variation of the DE3 amplitude and diurnal variation of the DE3 phase that are consistent with the annual and diurnal variations of the wave-4 patterns in plasma density and dynamo electric fields. The connection of the ionospheric wave-3 pattern presumably to the diurnal eastward propagating zonal wave number 2 tide (DE2) further demonstrates the significant role of atmospheric tides in the formation of large-scale ionospheric structures. Formation of the large-scale longitudinal structures of the ionosphere is attributed to the modulation of the E-region dynamo electric fields by atmospheric tides, but recent studies indicate that the ionosphere and thermosphere can be directly modulated by the penetration of atmospheric tides into the F-region height.

Keywords

Plasma Density Total Electron Content Neutral Wind Atmospheric Tide Defense Meteorological Satellite Program 
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.

Notes

Acknowledgements

H. Kil and L. J. Paxton acknowledge support from NASA Grant NNX08AQ12G and NASA TIMED Program GUVI Grant NAG5-11412.

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Applied Physics LaboratoryThe Johns Hopkins UniversityLaurelUSA

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